[Federal Register Volume 69, Number 211 (Tuesday, November 2, 2004)]
[Rules and Regulations]
[Pages 63581-63887]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 04-24101]



[[Page 63579]]

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Part III





Department of Housing and Urban Development





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24 CFR Part 81



HUD's Housing Goals for the Federal National Mortgage Association 
(Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie 
Mac) for the Years 2005-2008 and Amendments to HUD's R

[[Page 63580]]

egulation of Fannie Mae and Freddie Mac; Final Rule

  Federal Register / Vol. 69, No. 211 / Tuesday, November 2, 2004 / 
Rules and Regulations  
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DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT

24 CFR Part 81

[Docket No. FR-4790-F-03]
RIN 2501-AC92


HUD's Housing Goals for the Federal National Mortgage Association 
(Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie 
Mac) for the Years 2005-2008 and Amendments to HUD's Regulation of 
Fannie Mae and Freddie Mac

AGENCY: Office of the Assistant Secretary for Housing--Federal Housing 
Commissioner, HUD.

ACTION: Final rule.

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SUMMARY: Through this final rule, the Department of Housing and Urban 
Development establishes new housing goal levels for the Federal 
National Mortgage Association (Fannie Mae) and the Federal Home Loan 
Mortgage Corporation (Freddie Mac) (collectively, the government 
sponsored enterprises, or GSEs) for calendar years 2005 through 2008. 
The new housing goal levels are established in accordance with the 
Federal Housing Enterprises Financial Safety and Soundness Act of 1992 
(FHEFSSA) and govern the purchase by Fannie Mae and Freddie Mac of 
mortgages financing low- and moderate-income housing, special 
affordable housing, and housing in central cities, rural areas and 
other underserved areas. This rule also establishes new subgoals for 
the GSEs' acquisitions of home purchase loans that qualify for each of 
the housing goals. The final rule also establishes a new regulatory 
section relating to GSE data integrity, amends and adds certain 
definitions, provides a method for imputing the distribution of GSE-
purchased mortgages that lack income data, prohibits goals credit for 
purchases of loans in transactions with an option to dissolve the 
purchase in less than one year, and makes a technical change to the 
counting rules to clarify HUD's rules on double counting of loans.

EFFECTIVE DATE: January 1, 2005.

FOR FURTHER INFORMATION CONTACT: Sandra Fostek, Director, Office of 
Government Sponsored Enterprises, Office of Housing, Room 3150, 
telephone 202-708-2224. For questions on data or methodology, contact 
John L. Gardner, Director, Financial Institutions Regulation Division, 
Office of Policy Development and Research, Room 8212, telephone (202) 
708-1464. For legal questions, contact Paul S. Ceja, Deputy Assistant 
General Counsel for Government Sponsored Enterprises/RESPA, Office of 
the General Counsel, Room 9262, telephone 202-708-3137. The address for 
all of these persons is Department of Housing and Urban Development, 
451 Seventh Street, SW., Washington, DC, 20410. Persons with hearing 
and speech impairments may access the phone numbers via TTY by calling 
the Federal Information Relay Service at (800) 877-8399.

SUPPLEMENTARY INFORMATION:

I. General

A. Authority

    HUD's authority to regulate the GSEs is established under:
    (1) The Federal National Mortgage Association Charter Act (``Fannie 
Mae Charter Act''), which is Title III of the National Housing Act, 
section 301 et seq. (12 U.S.C. 1716 et seq.);
    (2) The Federal Home Loan Mortgage Corporation Act (``Freddie Mac 
Act''), which is Title III of the Emergency Home Finance Act of 1970, 
section 301 et seq. (12 U.S.C. 1451 et seq.);
    (3) FHEFSSA, enacted as Title XIII of the Housing and Community 
Development Act of 1992 (Pub. L. 102-550, approved October 28, 1992) 
(12 U.S.C. 4501-4641); and
    (4) Section 7(d) of the Department of Housing and Urban Development 
Act (42 U.S.C. 3535(d)).

B. Background: Fannie Mae and Freddie Mac

    Fannie Mae and Freddie Mac were chartered by the Congress as GSEs. 
Pursuant to section 301 of the Fannie Mae Charter Act (12 U.S.C. 1716) 
and section 301(b) of the Freddie Mac Act (12 U.S.C. 1451), the GSEs 
were chartered expressly to:
    (1) Provide stability in the secondary market for residential 
mortgages;
    (2) Respond appropriately to the private capital market;
    (3) Provide ongoing assistance to the secondary market for 
residential mortgages (including activities relating to mortgages on 
housing for low- and moderate-income families involving a reasonable 
economic return that may be less than the return earned on other 
activities) by increasing the liquidity of mortgage investments and 
improving the distribution of investment capital available for 
residential mortgage financing; and
    (4) Promote access to mortgage credit throughout the nation 
(including central cities, rural areas, and other underserved areas) by 
increasing the liquidity of mortgage investments and improving the 
distribution of investment capital available for residential mortgage 
financing.
    Fannie Mae and Freddie Mac engage in two principal businesses: (1) 
Purchasing and otherwise investing in residential mortgages, and (2) 
guaranteeing securities backed by residential mortgages. As a result of 
their status as GSEs, Fannie Mae and Freddie Mac receive significant 
explicit benefits that are not enjoyed by fully private shareholder-
owned corporations in the mortgage market. These benefits include:
     Conditional access to a $2.25 billion line of credit from 
the U.S. Treasury (see section 306(c)(2) of the Freddie Mac Act and 
section 304(c) of the Fannie Mae Charter Act);
     Exemption from the securities registration requirements of 
the U.S. Securities and Exchange Commission and the State securities 
regulatory agencies (see section 306(g) of the Freddie Mac Act and 
section 304(d) of the Fannie Mae Charter Act); \1\ and
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    \1\ Fannie Mae and Freddie Mac have both announced their 
intention voluntarily to register their common stock with the 
Securities and Exchange Commission (SEC) under section 12(g) of the 
Securities Exchange Act of 1934. Fannie Mae's registration became 
effective March 31, 2003. Freddie Mac has stated that it will 
complete the process of voluntarily registering its common stock 
once it resumes timely reporting of its financial results.
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     Exemption from all State and local taxes except property 
taxes (see section 303(e) of the Freddie Mac Act and section 309(c)(2) 
of the Fannie Mae Charter Act).
    While the securities that the GSEs guarantee, and the debt 
instruments they issue, are explicitly not backed by the full faith and 
credit of the United States, and nothing in this rule should be 
construed otherwise, such securities and instruments trade at yields 
only a few basis points over those of U.S. Treasury securities with 
comparable terms. These securities also offer yields lower than those 
for securities issued by fully private firms that are more highly 
capitalized but otherwise comparable. In addition, the market does not 
require that individual GSE securities be rated by a national rating 
agency. Consequently, the GSEs are able to fund their operations at 
lower cost than other private firms with similar financial 
characteristics. In a recent report, the Congressional Budget Office 
(CBO) estimated that this funding advantage for the year 2003 resulted 
in a $19.6 billion annual combined subsidy for both GSEs. Of this 
amount, CBO estimated that the GSEs retained about $6.2 billion, or 
approximately one-third of the subsidy, for their officers and

[[Page 63581]]

shareholders, while the remainder accrued to borrowers.\2\
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    \2\ ``Updated Estimates of the Subsidies to the Housing GSEs,'' 
attachment to a letter from Douglas Holtz-Eakin, Director, 
Congressional Budget Office, to the Honorable Richard C. Shelby, 
Chairman, Committee on Banking, Houseing, and Urban Affairs, United 
States Senate, April 8, 2004. A related recent study is Wayne 
Passmore, ``The GSE Implicit subsidy and Value of Government 
Ambiguity,'' Board of Governors of the Federal Reserve System. 
Finance and Economics Discussion Series, FEDS Working Paper 2003-64, 
December 2003.
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    In return for the public benefits they receive, Congress has 
mandated in the GSEs' Charter Acts that the GSEs carry out public 
purposes not required of other private sector entities in the housing 
finance industry. These statutory mandates obligate the GSEs to work to 
ensure that everyone in the nation has a reasonable opportunity to 
enjoy access to the mortgage financing benefits resulting from the 
activities of these enterprises.
    With respect to these public purposes, Congress does not simply 
expect the GSEs to strive toward achievement of these purposes but 
rather to ``lead the mortgage finance industry'' and to ``ensure that 
citizens throughout the country enjoy access to the public benefits 
provided by these federally related entities.'' (See S. Rep. No. 102-
282, at 34 (1992).)

C. Statutory and Regulatory Background

    The statutory and regulatory background applicable to the 
chartering of Fannie Mae and Freddie Mac and HUD's regulatory authority 
over these two GSEs were set out in detail in the preamble to HUD's 
proposed rule published on May 3, 2004 (69 FR 24228). Therefore, this 
background information is not repeated here in the preamble to this 
final rule. Interested members of the public should refer to Section 
I.A. of the preamble to the proposed rule at pages 69 FR 24228 through 
69 FR 24230 for this information.

D. The Proposed Rule

    On May 3, 2004, HUD published a proposed rule setting forth new 
housing goal levels for Fannie Mae and Freddie Mac. (See 69 FR 24228.) 
HUD's rule proposed to increase the level of the housing goals 
(``Housing Goals'') for the purchase by Fannie Mae and Freddie Mac of 
mortgages financing low- and moderate-income housing, special 
affordable housing, and housing in central cities, rural areas, and 
other underserved areas. The rule also proposed to establish new 
subgoals for the GSEs' acquisitions of home purchase loans that qualify 
for each of the housing goals.
    In addition to soliciting public comments on the proposed goal 
levels and new subgoals, the rule solicited public comments on several 
other issues related to the housing goals, including: (1) Provisions 
relating to GSE data integrity, such as verification, certification, 
treatment of errors, omissions or discrepancies, and other enforcement 
authority; (2) amended definitions of ``underserved area,'' 
``metropolitan area'' and ``minority,'' and a new definition of the 
term ``home purchase mortgage''; (3) a method for imputing the 
distribution of GSE-purchased mortgages that lack income data; and (4) 
other changes related to the GSEs' bulk purchases of seasoned loans. 
More detailed information about HUD's proposals can be found in the 
preamble to HUD's May 3, 2004, proposed rule.

E. This Final Rule--Overview

    Under this 2004 rulemaking, the Department is setting new, higher 
levels for the Housing Goals, accompanied by subgoals under each of the 
Housing Goals for purchases of home purchase mortgages (i.e., excluding 
refinance mortgages) on owner-occupied properties in metropolitan 
areas. (The subgoals are referred to in this rule as the ``Home 
Purchase Subgoals.'')
    The Department's purpose in setting higher Housing Goals and in 
establishing new Home Purchase Subgoals in this final rule is to 
encourage the GSEs to facilitate greater financing and homeownership 
opportunities for families and neighborhoods targeted by the Housing 
Goals. The final rule establishes levels of the Housing Goals that will 
bring the GSEs to a position of market leadership in a range of 
foreseeable economic circumstances related to the future course of 
interest rates and consequent fluctuations in origination rates on home 
purchase and refinance mortgages--both multifamily and single-family.
    For each goal, HUD has projected goal-qualifying percentages of 
mortgage originations in terms of ranges that cover a variety of 
economic scenarios. The objective of HUD's Housing Goals is to bring 
the GSEs' performance to the upper end of HUD's market range estimate 
for each goal, consistent with the requirement in FHEFSSA that HUD 
should consider the GSEs' ability to lead the market for each goal.
    To enable the GSEs to achieve this leadership, the Department has 
established staged increases in Housing Goal levels for 2005, which 
will increase further, year-by-year through 2008, to achieve the 
ultimate objective for the GSEs to lead the market under a range of 
foreseeable economic circumstances by 2008.
    The staged increases established by this rule, are consistent with 
the statutory requirement that HUD consider the past performance of the 
GSEs in setting the Housing Goals. Staged annual increases in the Goals 
will provide the GSEs with the opportunity to adjust their business 
models, so as to meet the required 2008 levels without compromising 
other business objectives and requirements.
    The Department believes that the Home Purchase Subgoals established 
by this final rule are necessary and warranted. Increasing 
homeownership is a national priority. The past average performance of 
the GSEs in the home purchase market has been below market levels. As 
further discussed below, the GSEs must apply greater efforts to 
increasing homeownership for low- and moderate-income families, 
families living in underserved areas, and very-low income families and 
low-income families living in low-income areas. The addition of Home 
Purchase Subgoals to the regulatory structure will serve to better 
focus the GSEs' efforts in a clear and transparent manner. The Home 
Purchase Subgoals will better allow the government and public alike to 
monitor the GSEs' efforts in meeting the nation's homeownership needs. 
The increases in the levels of the Housing Goals, and the addition of 
the new Home Purchase Subgoals, are predicated upon the Department's 
recognition that the GSEs not only have the ability to achieve these 
Housing Goals and Subgoals but, also, that they are fully consistent 
with the statutory factors established under FHEFSSA. In addition, this 
rule is supported by the Department's comprehensive analyses of the 
size of the mortgage market, the opportunities available to the GSEs, 
America's unmet housing needs, and identified credit gaps.
    In addition to the establishment of higher Housing Goals for the 
years 2005 through 2008, and the establishment of Home Purchase 
Subgoals, specific changes included in the final rule from the 
provisions included in the May 3, 2004, proposed rule are as follows:
    (1) The final rule expands the existing provisions to permit the 
GSEs to impute incomes or rents when data are missing for some 
purchases, addressing the market's expanding use of low documentation 
mortgages;
    (2) The final rule provides that goals credit is available for 
purchases of loans in transactions involving seller dissolution 
options, such as repurchase

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agreements, only when the option provides for a minimum one-year 
lockout period;
    (3) The final rule clarifies the proposed provisions regarding 
HUD's procedures for correcting errors, omissions and discrepancies in 
current year-end data and in remedying material overstatements of 
housing goals performance for prior years;
    (4) The final rule changes the scope of the proposed certification 
statement that the GSEs must provide to make it closer to the 
certification used by the Office of Federal Housing Enterprise 
Oversight (OFHEO), the GSEs' financial safety and soundness regulator; 
and
    (5) The final rule makes a technical correction to the special 
counting rules prohibiting double counting of GSE purchases of seasoned 
mortgages toward the housing goals.
    In developing these regulations, the Department was guided by, and 
re-affirms, the following principles established in the Housing Goals 
1995 final rule (published on December 1, 1995 at 60 FR 1846):
    (1) The GSEs should fulfill FHEFSSA's intent that they lead the 
industry in ensuring that access to mortgage credit is made available 
for very low-, low- and moderate-income families and residents of 
underserved areas. HUD recognizes that, to lead the mortgage industry 
over time, the GSEs will have to stretch to reach certain Housing Goals 
and to close gaps between the secondary mortgage market and the primary 
mortgage market for various categories of loans. This recognition is 
consistent with the Congressional directive that ``the enterprises will 
need to stretch their efforts to achieve'' the goals. (See S. Rep. No. 
102-282, at 35 (1992).)
    (2) The Department's role as a regulator is to set broad 
performance standards for the GSEs through the Housing Goals, but not 
to dictate the specific products or delivery mechanisms the GSEs will 
use to achieve a Housing Goal. Regulating two exceedingly large 
financial enterprises in a dynamic market requires that HUD provide the 
GSEs with sufficient latitude to use their innovative capacities to 
determine how best to develop products to carry out their respective 
missions. HUD's regulations are intended to allow the GSEs the 
flexibility to respond quickly to market opportunities. At the same 
time, the Department must ensure that the GSEs' strategies address 
national credit needs, especially as they relate to housing for low- 
and moderate-income families and housing located in underserved 
geographical areas. The addition of Home Purchase Subgoals to the 
regulatory structure provides an additional means of encouraging the 
GSEs' affordable housing activities to address identified, persistent 
credit needs while leaving to the GSEs the specific approaches used to 
meet these needs.
    (3) Discrimination in lending continues to limit access to credit 
for purchasing homes by racial and ethnic minorities. Troublesome gaps 
in homeownership remain for minorities even after record growth in 
affordable lending and homeownership during the nineties. Studies 
indicate that, over the next few years, minorities will account for a 
growing share of the families seeking to buy their first home. HUD's 
analyses indicate, however, that Fannie Mae and Freddie Mac account for 
a disproportionately small share of the minority first-time homebuyer 
market. The GSEs have a responsibility to promote access to capital for 
minorities and others who are seeking their first homes, and to 
demonstrate the benefits of such lending to industry and borrowers 
alike. The GSEs also have an integral role in eliminating predatory 
mortgage lending practices.
    (4) In addition to the GSEs' purchases of single-family home 
mortgages, the GSEs also must continue to assist in the creation of an 
active secondary market for mortgages on multifamily rental housing. 
Affordable rental housing is essential for those families who cannot 
afford to become, or who choose not to become, homeowners. For this 
reason, the GSEs must assist in making capital available to assure the 
continued development of single-family and multifamily rental housing.

II. Discussion of Public Comments

A. Overview of Public Comments

    At the close of the public comment period on July 16, 2004, which 
was extended an additional two weeks beyond the original public comment 
deadline of July 2, 2004, HUD had received 302 comments, which are in 
HUD's docket file for this rule. In addition to the public comments 
received on the rule, during the public comment period, HUD met with 
representatives of several organizations, including Fannie Mae and 
Freddie Mac, to accommodate oral presentation of concerns about the 
rule. HUD's docket file for this rule contains information on the dates 
of these meetings, the attendees, and the subject discussed.
    Of the public comments received on the proposed rule, the most 
detailed comments were those submitted by the two directly affected 
GSEs, Fannie Mae and Freddie Mac. Neither GSE was supportive of the 
higher goal levels proposed for 2005-2008, nor did either support the 
creation of HUD's proposed Home Purchase Subgoals. The GSEs stated, 
among other comments that they made on the rule, that the effect of 
many goals and subgoals would be micromanagement of the GSEs. With 
their comments, the GSEs provided several appendices that provided 
alternative analyses of data and questioned the Department's 
methodology in determining market share for the three affordable 
housing goals, a key component for establishing the appropriate level 
of the housing goals and the subgoals.
    The GSEs did not object to HUD's special affordable multifamily 
subgoal levels for 2005-2008, but other commenters (mostly public 
advocacy groups) recommended that HUD increase the levels of these 
subgoals.
    In addition to the GSEs, the commenters included national and 
regional housing industry organizations, nonprofit organizations, 
alliances, councils, and advocacy organizations involved in housing or 
housing issues, lenders, academic researchers, Members of Congress, 
state and local government officials, and two individuals.
    In large measure, except for several nonprofit organizations and 
public advocacy groups that favored higher goals, the majority of 
commenters were not supportive of HUD's proposed goals, especially in 
the outer years when the goal levels would reach their highest levels. 
A particular concern cited by a number of commenters was the potential 
for adverse impact on middle-income borrowers, particularly higher 
interest rates and fees. Another concern raised by the commenters was 
the possibility of unintended consequences for the industry. Many 
commenters, including the GSEs, urged HUD to exclude all single-family 
refinances from the calculation of the goals.
    The Department received fewer comments that addressed other 
proposals in the rule, such as those regarding data integrity, large-
scale transactions involving seasoned loans, the treatment of missing 
income data, and modifying the definition of rural underserved areas. 
For those commenters who submitted comments on these proposals, the 
reactions were generally mixed.
    With respect to HUD's proposals for new data integrity provisions, 
the majority of those who commented on the new data integrity proposals 
were generally supportive of the concept and acknowledged the need for 
some sort of data verification process. However, two

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industry-related commenters expressed concern about the potential for 
HUD's proposals to result in increased reporting burdens for lenders. 
The GSEs' comments also reflected several concerns about the data 
integrity provisions, mainly with respect to definitions, procedures, 
and enforcement.
    The GSEs favored generous proxy provisions for the treatment of 
missing income data and submitted several suggestions. The majority of 
commenters on this issue, consisting chiefly of nonprofit and advocacy 
organizations, opposed using proxies, and several favored an outright 
ban on purchasing ``no income'' subprime mortgages.
    With regard to large-scale transactions involving seasoned loans, 
the GSEs commented that they should receive housing goals credit and 
that no change in HUD's current definition of ``mortgage purchase'' was 
warranted. However, a group of industry-related organizations opposed 
providing goals credit for seasoned loans, as did several advocacy 
organizations. Commenters offered no alternative definitions for 
``mortgage purchase'' in HUD's regulations.
    All but one commenter who addressed the issue of HUD's rural 
underserved area definition favored changing this definition to one 
that is census tract-based, rather than county-based. Those commenters 
favoring conversion to a tract-based definition believed that county-
level data do not show disparities in service that the GSEs should 
address. The dissenting commenter felt that lenders serving rural areas 
would face operational difficulties and expenses in shifting to a 
tract-based orientation.
    In addition to comments on its proposals related to housing goals, 
HUD received other comments on subjects pertaining to HUD's regulatory 
authority over the GSEs but which were not related to the rule's 
proposals on housing goals (for example, comments on new program 
authority, monitoring and reporting procedures, and public access to 
GSE mortgage data). Because these comments raised issues outside the 
scope of the May 3, 2004, proposed rule, they are not addressed in this 
final rule.
    A discussion of the general and specific comments on the rule, as 
well as HUD's responses to these comments, follows in subsequent 
sections in this preamble, as well as in the Appendices to this Final 
Rule. While comments are summarized, not all the comments are addressed 
explicitly in this preamble. HUD is appreciative of the full range of 
public comments received and acknowledges the value of all of the 
comments submitted in response to the proposed rule.

B. Subpart A--General

    In the May 3, 2004, rule, HUD proposed to add a definition of 
``home purchase mortgage'' in connection with its proposal to specify 
Home Purchase Subgoals under each of the three Housing Goals, to revise 
the definitions of ``metropolitan area'' and ``minority'' to conform 
HUD's regulations to changes in data collection practices made by the 
Office of Management and Budget (OMB), and to modify the current 
definition of ``underserved area'' with respect to the delineation of 
underserved portions of non-metropolitan areas.
1. Home Purchase Mortgage
    HUD proposed to insert a definition of ``home purchase mortgage'' 
for purposes of specifying the Home Purchase Mortgage Subgoals. Since 
no comments bearing directly on this definition were received and the 
Department has retained the subgoal concept in this final rule, the 
definition is adopted.
2. Metropolitan Area
    HUD proposed to alter the definition of ``metropolitan area'' to 
reflect a change in the definition of ``metropolitan area'' recently 
promulgated by OMB, in which the concept of ``Primary Metropolitan 
Statistical Area'' was removed. No comments were received on this 
proposed change; accordingly, it is adopted.
3. Minority
    HUD proposed to alter the definition of ``minority'' to reflect 
changes in standards for the classification of federal data on race and 
ethnicity previously promulgated by OMB and implemented in the 2000 
census and in data collection under the Home Mortgage Disclosure Act in 
2004. No comments were received on this proposed change; accordingly, 
it is adopted.
4. Underserved Area
    HUD proposed to alter the definition of ``underserved area'' to 
provide for the specification of underserved areas outside of 
metropolitan areas at the census tract level rather than at the county 
level.
    For properties in non-metropolitan (rural) areas, mortgage 
purchases have counted toward the Underserved Areas Housing Goal where 
such purchases finance properties that are located in underserved 
counties. This final rule incorporates a determination that mortgage 
purchases will count toward the Underserved Areas Housing Goal where 
such purchases finance properties that are located in underserved 
census tracts. These are defined as census tracts where either: (1) the 
median income in the tract does not exceed 95 percent of the greater of 
the median income for the non-metropolitan portions of the state or the 
median income of the non-metropolitan portions of the nation as a 
whole; or (2) minorities comprise at least 30 percent of the residents 
and the median income in the tract does not exceed 120 percent of the 
greater of the median incomes for the non-metropolitan portions of the 
state or of the nation as a whole.
    HUD originally adopted its current county-based definition for 
targeting GSE purchases to underserved non-metropolitan areas primarily 
based on information that rural lenders did not perceive their market 
areas in terms of census tracts, but rather, in terms of counties. A 
further concern was an apparent lack of reliability of geocoding 
software applied to non-metropolitan areas.
    Thirteen commenters endorsed HUD's proposed change in definition, 
observing that the change would produce more precise targeting and 
improved service toward underserved segments of the market within 
counties. One banking trade association advocated continuation of a 
county-based definition, stating that because the business perspective 
of community banks in rural areas is geared toward entire counties, 
there would be costs associated with monitoring the tract location of 
loans, and therefore, marketing toward borrowers at the tract level 
would be difficult.
    Recent research summarized in Appendix B to this rule indicates 
that a tract-based system will improve the extent to which the 
underserved area definition distinguishes areas by key socioeconomic 
and demographic characteristics such as median family income, poverty, 
unemployment, school dropout rates, and minority populations. Under a 
tract-based definition underserved areas stand out more as areas of 
lower income and low economic activity and as having somewhat larger 
minority population proportions. A tract-based definition will also 
improve the targeting of the goal to areas with relatively greater 
housing needs. Based on these findings, which are detailed in Appendix 
B to this rule, HUD is adopting a re-specification of underserved areas 
within non-metropolitan (rural) areas to

[[Page 63584]]

be based on census tracts rather than counties.

C. Subpart B--Housing Goals

1. Overview
    A substantial majority of the comments received criticized HUD's 
proposed levels of the housing goals on the basis that they would be 
difficult for the GSEs to achieve, particularly in periods of high 
refinance activity when higher-income borrowers comprise a relatively 
high proportion of mortgage borrowers. Several types of adverse 
consequences of such high goals were forecast, including diminution of 
availability of mortgage credit to some sectors of the mortgage market, 
unfavorable effects on neighborhood housing quality, and other adverse 
effects discussed below. This section of the final rule reviews the 
statutory factors the Department must consider in setting the level of 
the housing goals and the Department's determinations with regard to 
the levels of each of the housing goals as well as the proposed Home 
Purchase Subgoals.
2. Statutorily Required Factors in Setting the Levels of the Housing 
Goals and Subgoals
    The Housing Goals and Home Purchase Subgoals being implemented by 
this final rule were established following consideration of the six 
factors required by statute to be considered in establishing goal 
levels and establishing subgoals. A summary of HUD's findings relative 
to each of the six statutory factors follows. More detailed discussion 
of these points is included in Appendices A, B, and C to this rule.
a. Demographic, Economic, and Housing Conditions
(i) Demographic Trends
    Changing population demographics will result in a need for the 
primary and secondary mortgage markets to meet nontraditional credit 
needs, respond to diverse housing preferences and overcome information 
and other barriers that many immigrants and minorities currently face.
    The U.S. Census Bureau has projected that the U.S. population will 
grow by an average of 2.5 million persons per year between 2000 and 
2025, resulting in about 1.2 million new households per year. The aging 
of the baby-boom generation and the entry of the baby-bust generation 
into prime home-buying age will have a dampening effect on housing 
demand. Growing housing demand from minorities, immigrants and non-
traditional homebuyers will help offset declines in the demand for 
housing caused by the aging of the population.
    The continued influx of immigrants will increase the demand for 
rental housing, while those who immigrated during the 1980s and 1990s 
will be in the market for homeownership. Immigrants and minorities--who 
accounted for nearly 40 percent of the growth in the nation's 
homeownership rate over the past five years--will be responsible for 
almost two-thirds of the growth in the number of new households over 
the next 10 years.
    Non-traditional households have become more important, as overall 
household formation rates have slowed. With later marriages, divorce, 
and non-traditional living arrangements, the fastest growing household 
groups are single-parent and single-person households. By 2025, non-
family households will make up one-third of all households. The role of 
traditional 25-to-34 year-old married, first-time homebuyers in the 
housing market will be smaller in the current decade due to the aging 
of the population. Between 2000 and 2025, the Census Bureau projects 
that the largest growth in households will occur among householders who 
are age 65 and older.
    As these demographic factors play out, the overall effect on 
housing demand will likely be continued growth and an increasingly 
diverse household population from which to draw new renters and 
homeowners. A greater diversity in the housing market will, in turn, 
require greater adaptation by the primary and secondary mortgage 
markets.
(ii) Economic and Housing Conditions
    While most other sectors of the economy were weak or declining 
during 2001 and 2002, the housing sector showed remarkable strength. 
The housing market continued at a record pace during 2003.
    In 2002, the U.S. economy moved into recovery, with real Gross 
Domestic Product (GDP) growing 2.2 percent, although measures of 
unemployment continued to rise before declining again in 2003. In 
October 2002, the average 30-year home mortgage interest rate slipped 
below 6 percent for the first time since the mid-1960s. Favorable 
financing conditions and solid increases in house prices were the key 
supports to record housing markets during both 2002 and 2003. By the 
end of 2003, the industry had set new records in single-family home 
permits, new home sales, existing home sales, low interest rates, and 
rates of homeownership. Other indicators--total permits, starts, 
completions, and affordability--reached levels that were among the 
highest in the past two decades.
    The Administration's forecast for real GDP growth is 3.7 percent 
for 2005 and 3.1-3.4 percent in 2006-2009, while CBO projects that real 
GDP will grow at an average rate of 4.1 percent in 2005 and annual 
rates of 2.9-3.2 percent in 2006 through 2009.\3\ The Administration 
projects the 10-year Treasury rate to average 5.1 percent in 2005 and 
5.4-5.8 percent between 2006 and 2009 compared to its average of 4.6 
percent in 2002 and 4.0 percent in 2003.
---------------------------------------------------------------------------

    \3\ Fiscal Year 2005 Budget of the U.S. Government: Mid-Session 
review (July 30, 2004). Office of Management and Budget, also posted 
at http://www.whitehouse.gov/omb. The Budget and Economic Outlook: 
An Update, Washington, Congressional Budget Office, September 2004, 
also posted on http://www.cbo.gov.
---------------------------------------------------------------------------

    Standard & Poor's expects housing starts to average 1.8 million 
units in 2004-2005. Fannie Mae projects existing home sales for 2004 at 
6.1 million units, and for 2005 at 5.8 million, compared to their 
record level in 2003 of 6 million units.
(iii) Mortgage Market Conditions
    Low interest rates and record levels of refinancing caused mortgage 
originations to soar from $2.0 trillion in 2001 to $2.6 trillion in 
2002 and around $3.8 trillion in 2003. The Mortgage Bankers Association 
projects that mortgage originations will drop to $2.7 trillion in 2004 
and $1.8 trillion in 2005, as refinancing returns to more normal 
levels.\4\
---------------------------------------------------------------------------

    \4\ Mortgage Bankers Association of America, MBA Mortgage 
Finance Forecast, September 17, 2004.
---------------------------------------------------------------------------

    The volume of home purchase mortgages was $910 billion to $1.1 
trillion between 1999 and 2001 before jumping to $1.2 trillion in 2002 
and $1.3 trillion in 2003. As with housing starts, the home purchase 
origination market is expected to exhibit sustained growth.
b. National Housing Needs
(i) Affordability Problems
    Data from the 2000 Census and the American Housing Survey 
demonstrate that there are substantial housing needs among low- and 
moderate-income families. Many of these households are burdened by high 
homeownership costs or rent payments and, consequently, are facing 
serious housing affordability problems. There is evidence of persistent 
housing problems for Americans with the lowest incomes. Since 1977 the 
percentage of U.S. households with worst case needs has hovered around 
five percent, with the worst year being 1983 (6.03 percent) and the 
best being 1999 (4.72 percent). The

[[Page 63585]]

proportion in 2001 was 4.77 percent, which is not significantly 
different from the 1999 figure. HUD's analysis of American Housing 
Survey data reveals that, in 2001, 5.1 million unassisted very-low-
income renter households had ``worst case'' housing needs, defined as 
housing costs greater than 50 percent of household income or severely 
inadequate housing. Among these households, 90 percent had a severe 
rent burden, 6 percent lived in severely inadequate housing, and 4 
percent suffered from both problems. Among the 34 million renters in 
all income categories, 6.3 million (19 percent) had a severe rent 
burden and over one million renters (3 percent) lived in housing that 
was severely inadequate.
(ii) Disparities in Housing and Mortgage Markets
    Despite the strong growth in affordable lending over the past ten 
years, there are families who are not being adequately served by the 
nation's housing and mortgage markets. Serious racial and income 
disparities remain. The homeownership rate for minorities is 25 
percentage points below that for whites. A major HUD-funded study of 
discrimination in the sales and rental markets found that 
discrimination still persists in both rental and sales markets of large 
metropolitan areas nationwide, although its incidence has generally 
declined since 1989. The most prevalent form of discrimination observed 
in the study against Hispanic and African-American home seekers was 
Hispanics and African Americans being told that housing units were 
unavailable when non-Hispanic whites found them to be available. Levels 
of consistent adverse treatment experienced by the nation's largest 
minority groups when they inquire about a unit advertised for sale in 
metropolitan areas nationwide in 2000-2001 were: African Americans 16.8 
percent, Hispanics 18.3 percent, and Asians and Pacific Islanders 20.4 
percent.
    The study also found other worrisome trends of discrimination in 
metropolitan housing markets that persisted in 2000. Examples include 
geographical steering experienced by African-American homebuyers, and 
real estate agents who provided less assistance in obtaining financing 
for Hispanic homebuyers than for non-Hispanic whites.\5\ Racial 
disparities in mortgage lending are also well documented. HUD-sponsored 
studies of the pre-qualification process conclude that African 
Americans and Hispanics risk unequal treatment when they visit 
mainstream mortgage lenders. Studies reveal higher mortgage denial 
rates for African Americans and Hispanics, even after controlling for 
applicant income and a host of underwriting characteristics, such as 
the credit record of the applicant.\6\ However, substantial progress 
has been made since 1989.
---------------------------------------------------------------------------

    \5\ Margery Austin Turner, All Other Things Being Equal: A 
Paired Testing Study of Mortgage Lending Institutions, The Urban 
Institute Press, April 2002. Appendix A includes further discussion 
of this study.
    \6\ These studies are discussed in section B.1 of Appendix B.
---------------------------------------------------------------------------

    The existence of substantial neighborhood disparities in 
homeownership and mortgage credit is also well documented for 
metropolitan areas. HUD's analysis of Home Mortgage Disclosure Act 
(HMDA) data shows that mortgage credit flows in metropolitan areas are 
substantially lower in high-minority and low-income neighborhoods and 
that mortgage denial rates are much higher for residents of these 
neighborhoods. Studies have also documented that mainstream lenders 
often do not operate in inner-city minority neighborhoods, leaving 
their residents with only high-cost lenders as options. Too often, 
residents of these same neighborhoods have been subjected to the 
abusive practices of predatory lenders.
    These troublesome disparities mostly affect those families 
(minorities and immigrants) who are projected to account for almost 
two-thirds of the growth in the number of new households over the next 
10 years.
(iii) Single-Family Market: Trends in Affordable Lending and 
Homeownership
    Many younger, minority and lower-income families did not become 
homeowners during the 1980s due to slow growth of some earnings, high 
real interest rates, lower inflation, and continued increases in 
housing prices. Over the past 10 years, economic expansion, accompanied 
by low interest rates and increased outreach on the part of the 
mortgage industry, has improved affordability conditions for these 
families.
    As this preamble and the appendices note, there has been a 
``revolution in affordable lending'' that has extended homeownership 
opportunities to historically underserved households. The mortgage 
industry, including the GSEs, has offered more customized mortgage 
products, more flexible underwriting, and expanded outreach to low-
income and minority borrowers.
    HMDA data suggest that the industry and GSE initiatives are 
increasing the flow of credit to underserved borrowers. Between 1993 
and 2002, conventional loans to low-income and minority families 
increased at much faster rates than loans to upper-income and non-
minority families. Conventional home purchase originations to African 
Americans more than doubled between 1993 and 2002, and those to 
Hispanic borrowers more than tripled during this period. Home loans to 
low-income borrowers and to low-income and high-minority census tracts 
also more than doubled during this period.
    Thus, the 1990s and the early part of the current decade have seen 
the development of a strong affordable lending market. Homeownership 
statistics show similar trends. After declining during the 1980s, the 
homeownership rate has increased every year since 1994, reaching a 
record mark of 69.2 percent in the second quarter of 2004.
    The number of households owning their own home increased by 13.3 
million between 1994 and 2003. Gains in homeownership rates during the 
period of 1994 to 2003 have been widespread, with the homeownership 
rate for African-American households increasing from 42.5 percent to 
48.8 percent, for Hispanic households from 41.2 percent to 46.7 
percent, for non-Hispanic white households from 70.0 percent to 75.4 
percent, and for central city residents from 48.5 percent to 52.3 
percent.
    Despite the record gains in homeownership since 1994, a gap of 
approximately 25 percent in the homeownership rate prevails for 
African-American and Hispanic households as compared to white non-
Hispanic households. Studies show that these lower homeownership rates 
are only partly accounted for by differences in income, age, and other 
socioeconomic factors.
    In addition to low income, barriers to homeownership that 
disproportionately affect minorities and immigrants include: lack of 
capital for downpayment and closing costs; poor credit history; lack of 
access to mainstream lenders; little understanding of the home buying 
process; a limited supply of modestly priced homes in locations where 
these populations reside; and continued discrimination in housing 
markets and mortgage lending. These barriers are discussed in Appendix 
A to this rule.
(iv) Single-Family Market: Potential Homeowners
    As already noted, the potential homeowner population over the next 
decade will be highly diverse, as growing housing demand from

[[Page 63586]]

immigrants (both those who are already in this country and those who 
are projected to arrive), minorities, and non-traditional homebuyers 
will help to offset declines in the demand for housing caused by the 
aging of the population.
    Studies cited in Appendix A to this rule reveal that increased 
immigration during the 1990s directly accounted for 35 percent of the 
nation's rise in population during that decade, as a result of which 
the foreign-born population of the United States was 31.1 million in 
2000. These trends do not depend on the future inflow of new 
immigrants, as immigrants do not, on average, enter the home purchase 
market until they have been in this country for eleven years. Fannie 
Mae staff have noted that there are enough immigrants already in this 
country to keep housing demand strong for several years.
    Thus, the need for the GSEs and other industry participants to meet 
nontraditional credit needs, respond to diverse housing preferences, 
and to overcome the information barriers that many immigrants face will 
take on added importance. A new or recent immigrant may have no credit 
history or, at least, may not have a credit history that can be 
documented by traditional methods. In order to address these needs, the 
GSEs and the mortgage industry have been developing innovative products 
and seeking to extend their outreach efforts to attract these 
homebuyers, as discussed in Appendix A to this rule.
    In addition, the current low homeownership rates in inner cities 
(as compared with the suburbs) also suggest that urban areas may be a 
potential growth market for lenders. As explained in Appendix A to this 
rule, lenders are beginning to recognize that urban borrowers and 
properties have different needs than suburban borrowers and properties.
    Surveys indicate that these demographic trends will be reinforced 
by the fact that most Americans desire, and plan, to become homeowners. 
According to Fannie Mae's 2002 National Housing Survey, Americans rate 
homeownership as the best investment they can make, far ahead of 401(k) 
plans, other retirement accounts, and stocks. Forty-two percent of 
African-American families reported that they were ``very or fairly 
likely'' to buy a home in the next three years, up from 38 percent in 
1998 and 25 percent in 1997. Among Hispanics and Hispanic immigrants, 
the numbers reached 37 percent and 34 percent, respectively. The survey 
also reported that more than half of Hispanic renters cite 
homeownership as being ``one of their top priorities.''
    Despite these trends, potential minority and immigrant homebuyers 
see more obstacles to buying a home than does the general public. 
Typically, the primary barriers to homeownership are credit issues and 
a lack of funds for a downpayment and closing costs. However, other 
barriers also exist, such as a lack of affordable housing, little 
understanding of the home buying process, and language barriers. Thus, 
the new group of potential homeowners will have unique needs.
    The GSEs can play an important role in tapping this potential 
homeowner population. Along with others in the industry, they can 
address these needs on several fronts, such as expanding education and 
outreach efforts, introducing new products, and adjusting current 
underwriting standards to better reflect the special circumstances of 
these new households. These efforts are necessary for achieving the 
Administration's goal of expanding minority homeownership by 5.5 
million families by the end of the decade.
    The single-family mortgage market has been very dynamic over the 
past few years, experiencing volatile swings in originations (with the 
1998 and 2001-2003 refinancing waves), witnessing the rapid growth in 
new types of lending (such as subprime lending), incorporating new 
technologies (such as automated underwriting systems), and facing 
serious challenges (such as predatory lending). Fannie Mae and Freddie 
Mac have played a major role in the ongoing changes in the single-
family market and in helping the industry address the problems and 
challenges that have arisen.
    The appendices to this final rule discuss the various roles that 
Fannie Mae and Freddie Mac have played in the single-family market. A 
wide range of topics is examined, including the GSEs' automated 
underwriting technology used throughout the industry, their many 
affordable lending partnerships and underwriting initiatives aimed at 
extending credit to underserved borrowers, their development of new 
targeted low-downpayment products, their entry into new markets such as 
the subprime market, and their attempts to reduce predatory lending. As 
that discussion emphasizes, the GSEs have the ability to bring 
increased efficiencies to a market and to attract mainstream lenders 
into markets. (Readers are referred to Appendices A, B, and C to this 
rule for further discussion of the GSEs' role in different segments of 
the single-family mortgage market.)
(v) Multifamily Mortgage Market
    The market for financing of multifamily apartments has reached 
record volume. The favorable long-term prospects for apartments, 
combined with record low interest rates, have kept investor demand for 
apartments strong and have supported property prices despite recently 
high vacancy rates.
    Fannie Mae and Freddie Mac have been among those boosting their 
volumes of multifamily financing and both have introduced new programs 
to serve the multifamily market. Fannie Mae and, especially 
(considering its earlier withdrawal from the market), Freddie Mac have 
rapidly expanded their presence in the multifamily mortgage market 
under the Housing Goals.
    Freddie Mac has successfully rebuilt its multifamily acquisition 
program, as reflected by the increase in its purchases of multifamily 
mortgages: from $27 million in 1992 to $3.9 billion in 1998 and then 
rising to $9.5 billion in 2001, $10.7 billion in 2002, and $21.5 
billion in 2003. Multifamily units accounted for 9.0 percent of all 
dwelling units (both owner and rental) financed by Freddie Mac between 
1999 and 2003. Concerns regarding multifamily capabilities no longer 
constrain Freddie Mac's performance with regard to the Housing Goals.
    Although Fannie Mae never withdrew from the multifamily market, it 
has stepped up its activities in this area substantially, with 
multifamily purchases rising from $3.0 billion in 1992 to $10.0 billion 
in 1999, and $19.1 billion in 2001, then declining slightly to $16.6 
billion in 2002, and then rising markedly to $30.9 billion in 2003. 
Multifamily units accounted for 8.8 percent of all dwelling units (both 
owner and rental) financed by Fannie Mae between 1999 and 2003.
    The increased role of Fannie Mae and Freddie Mac in the multifamily 
market has major implications for the Low- and Moderate-Income Housing 
and Special Affordable Housing Goals, since high percentages of 
multifamily units have affordable-level rents and can count toward one 
or both of these Housing Goals. However, the potential of the GSEs to 
lead the multifamily mortgage industry has not been fully developed. 
The GSEs' purchases between 1999 and 2002 accounted for less than 40 
percent of the multifamily units that received financing during this 
period. Certainly there are ample opportunities and room for expansion 
of the GSEs' share of the multifamily mortgage market.

[[Page 63587]]

    The GSEs' size and market position between loan originators and 
mortgage investors make them the logical institutions to identify and 
promote needed innovations and to establish standards that will improve 
market efficiency. As their role in the multifamily market continues to 
grow, the GSEs will have the knowledge and market presence to push 
simultaneously for standardization and for programmatic flexibility to 
meet special needs and circumstances, with the ultimate goal of 
increasing the availability and reducing the cost of financing for 
affordable and other multifamily rental properties.
    The long-term outlook for the multifamily rental market is 
sustained, moderate growth, based on favorable demographics. The 
minority population, especially Hispanics, provides a growing source of 
demand for affordable rental housing. ``Lifestyle renters'' (older, 
middle-income households) are also a fast-growing segment of the rental 
population.
    At the same time, the provision of affordable housing units will 
continue to challenge suppliers of multifamily rental housing as well 
as policy makers at all levels of government. Low incomes, combined 
with high housing expenses, define the difficult situation of millions 
of renter households. Housing cost reductions are constrained by high 
land prices and construction costs in many markets. Regulatory barriers 
at the state and local level have an enormous impact on the development 
of affordable rental housing. Government action--through land use 
regulation, building codes, and occupancy standards--is a major 
contributor to high housing costs.
    Since the early 1990s, the multifamily mortgage market has become 
more closely interconnected with global capital markets, although not 
to the same degree as the single-family mortgage market. Loans on 
multifamily properties are still viewed as riskier by some than are 
mortgages on single-family properties, despite delinquency rates that 
in recent quarters have been lower than those on single-family 
mortgages.
    There is a need for an ongoing GSE presence in the multifamily 
secondary market, both to increase liquidity and to advance affordable 
housing efforts. The potential for an increased GSE presence is 
enhanced by the fact that an increasing proportion of multifamily 
mortgages are now originated in accordance with secondary market 
standards. Small multifamily properties, and multifamily properties 
with significant rehabilitation needs, have historically experienced 
difficulty gaining access to mortgage financing, and the flow of 
capital into multifamily housing for seniors has been historically 
characterized by volatility. The GSEs can play a role in promoting 
liquidity for multifamily mortgages and increasing the availability of 
long-term, fixed-rate financing for these properties.
c. GSEs' Past Performance and Effort Toward Achieving the Housing Goals
    Since the enactment of FHEFSSA and HUD's establishment in 1993 of 
the Housing Goals, both Fannie Mae and Freddie Mac have improved their 
affordable housing loan performance. However, the GSEs' mortgage 
purchases have generally lagged, and not led, the overall primary 
market in providing financing for affordable housing to low- and 
moderate-income families and underserved borrowers and their 
neighborhoods, indicating that there is more that the GSEs can do to 
improve their performance.
(i) Performance on the Housing Goals
    The year 2001 was the first year under the higher levels of the 
Housing Goals established in the Housing Goals 2000 final rule. Fannie 
Mae met all three Housing Goals in 2001, 2002, and 2003. Freddie Mac 
met all three Housing Goals in 2001 and 2003. However, in 2002 HUD 
discovered that Freddie Mac had counted 22,371 housing units towards 
the Low- and Moderate Income Goal even though it had previously counted 
these same housing units towards the same goal in 2001. Freddie Mac 
also counted 22,424 housing units towards the Underserved Area Goal 
even though these units had also been credited towards the same goal in 
2001. HUD's regulations prohibit double counting. To correct for these 
double-counting errors, the Department has adjusted its official 
performance results for Freddie Mac in 2002 by deducting the double-
counted housing units, including all bonus point credit that had been 
awarded for most of these units, from the official performance results 
it had previously reported publicly. As a result of these adjustments, 
Freddie Mac continued to meet the Low- and Moderate-Income Goal in 
2002. However, Freddie Mac fell short of the 31 percent target for the 
Underserved Areas goal by 90 units or 0.002 percent. Freddie Mac's 2002 
goal performance results are described more fully in Tables 4, 6 and 8 
in this preamble, including the accompanying footnotes.
(ii) The GSEs' Efforts in the Home Purchase Mortgage Market
    The Appendices to this final rule include a comprehensive analysis 
of each GSE's performance in funding home purchase mortgages for 
borrowers and neighborhoods targeted by the three Housing Goals--
special affordable and low- and moderate-income borrowers and 
underserved areas. The GSEs' role in the first-time homebuyer market is 
also analyzed. Because homeownership opportunities are integrally tied 
to the ready availability of affordable home purchase loans, the main 
findings from that analysis are provided below.
     Both Fannie Mae and Freddie Mac have increased their 
purchases of affordable home purchase mortgages since the Housing Goals 
were put into effect, as indicated by the increasing share of their 
business going to the three goals-qualifying categories. Between 1992 
and 2003, the special affordable share of Fannie Mae's business almost 
tripled, rising from 6.3 percent to 17.1 percent, while the underserved 
areas share increased more modestly, from 18.3 percent to 26.8 percent. 
The figures for Freddie Mac are similar. The special affordable share 
of Freddie Mac's business rose from 6.5 percent to 15.6 percent, while 
the underserved areas share also increased but more modestly, from 18.6 
percent to 24.0 percent.
     While both GSEs improved their performance, they have 
historically lagged the primary market in providing affordable home 
purchase mortgage loans to low-income borrowers and underserved 
neighborhoods. Freddie Mac's average performance, in particular, fell 
far short of market performance during the 1990s. Fannie Mae's average 
performance was better than Freddie Mac's during the 1993-2003 period 
as well as during the 1996-2003 period, which covers the period under 
HUD's currently-defined Housing Goals. Between 1993 and 2003, 12.2 
percent of Freddie Mac's mortgage purchases were for special affordable 
borrowers, compared with 13.3 percent of Fannie Mae's purchases, 15.4 
percent of loans originated by depositories, and 15.5 percent of loans 
originated in the conventional conforming market (without estimated B&C 
subprime loans).\7\
---------------------------------------------------------------------------

    \7\ Unless otherwise noted, the conventional conforming market 
data reported in this section exclude an estimate of B&C loans; the 
less-risky A-minus portion of the subprime market is included in the 
market definition. See section d below and Appendix D for a 
discussion of primary market definitions and the uncertainty 
surrounding estimates of the number of B&C loans in HMDA data. As 
noted there, B&C loans are much more likely to be refinance loans 
rather than home purchase loans.

---------------------------------------------------------------------------

[[Page 63588]]

     Between 2001 and 2003, both Fannie Mae and Freddie Mac 
fell significantly below the market in funding affordable home purchase 
mortgage loans. During this period, special affordable loans accounted 
for 15.1 percent of Fannie Mae's purchases, 14.7 percent of Freddie 
Mac's purchases, and 16.2 percent of loans originated in the market; 
thus, the ``Fannie-Mae-to-market'' ratio was 0.93 and the ``Freddie-
Mac-to-market'' ratio was also 0.91. During the same period, 
underserved area loans accounted for 24.7 percent of Fannie Mae's 
purchases, 23.1 percent of Freddie Mac's purchases, and 26.2 percent of 
loans originated in the market; the ``Fannie-Mae-to-market'' ratio was 
0.94 and the ``Freddie-Mac-to-market'' ratio was only 0.88.
     While Freddie Mac has improved its affordable lending 
performance in the past two years, it has continued to lag the 
conventional conforming market in funding affordable home purchase 
loans for special affordable and low- and moderate-income borrowers and 
underserved neighborhoods targeted by the Housing Goals. In 2003, 
Freddie Mac's performance on the underserved areas goal was 
particularly low relative to both the performances of Fannie Mae and 
the market; in that year, underserved area loans accounted for only 
24.0 percent of Freddie Mac's purchases compared with 26.8 percent of 
Fannie Mae's purchases and 27.6 percent of market originations.
     As noted above, Fannie Mae's average performance during 
past periods (e.g., 1993-2003, 1996-2003, 1999-2003) has been below 
market levels. However, it is encouraging that Fannie Mae markedly 
improved its affordable lending performance relative to the market 
during 2001, 2002, and 2003, the first three years under the higher 
housing goal targets that HUD established in the GSE Final Rule dated 
October 2000. Over this three-year period, Fannie Mae led the primary 
market in funding special affordable and low- and moderate-income home 
purchase mortgage loans but lagged the market in funding underserved 
areas home purchase loans. In 2003, Fannie Mae's increased performance 
placed it significantly above the special affordable market (a 17.1 
percent share for Fannie Mae compared with a 15.9 percent share for the 
market) and the low-mod market (a 47.0 percent share for Fannie Mae 
compared with a 44.6 percent share for the market). However, Fannie Mae 
continued to lag the underserved areas market in 2003 (a 26.8 percent 
share for Fannie Mae compared with a 27.6 percent share for the 
market). These data are based on the ``purchase year'' approach, that 
is, Fannie Mae's performance is based on comparing its purchases of all 
home purchase loans (both seasoned loans and newly-originated 
mortgages) during a particular year with loans originated in the market 
in that year. When Fannie Mae's performance is measured on an 
``origination year'' basis (that is, allocating Fannie Mae's purchases 
in a particular year to the year that the purchased loan was 
originated), Fannie Mae also led the 2003 market in funding special 
affordable and low- and moderate-income loans, and lagged the market in 
funding underserved area loans.
     Appendix A compares the GSEs' funding of first-time 
homebuyers with that of primary lenders in the conventional conforming 
market. Both Fannie Mae and Freddie Mac lag the market in funding 
first-time homebuyers, and by a rather wide margin. Between 1999 and 
2002, first-time homebuyers accounted for 27 percent of each GSE's 
purchases of home purchase mortgages, compared with 38 percent for home 
purchase mortgages originated in the conventional conforming market. 
For minority first-time homebuyers, the GSE ratio was 6.2 percent, 
compared to a market originations ratio of 10.6 percent. For African-
American and Hispanic first-time homebuyers, the GSE ratio was 3.8 
percent, compared to a market originations ratio of 6.9 percent. For 
first-time homebuyers, particularly first-time minority homebuyers, 
both GSEs substantially lag the private conventional conforming market.
     The GSEs account for a small share of the market for 
important groups such as minority first-time homebuyers. Considering 
all mortgage originations (both government and conventional) between 
1999 and 2001, it is estimated that the GSEs purchased only 14 percent 
of all loans originated for African-American and Hispanic first-time 
homebuyers, or one-third of their share (42 percent) of all home 
purchase loans originated during that period. Considering conventional 
conforming originations during the same time period, it is estimated 
that the GSEs purchased only 31 percent of loans for African-American 
and Hispanic first-time homebuyers, or about one-half of their share 
(57 percent) of all home purchase loans in that market. A large 
percentage of the lower-income loans purchased by the GSEs had 
relatively low loan-to-value ratios and consequently high downpayments, 
which may explain the GSEs' limited role in the first-time homebuyer 
market.
    Appendix A to this rule provides evidence that there is a 
significant population of potential homebuyers who are likely to 
respond well to increased homeownership opportunities produced by 
increased GSE purchases in this area. Immigrants and minorities, in 
particular, are expected to be a major source of future homebuyers.
d. Size of the Mortgage Market That Qualifies for the Housing Goals
    The Department has estimated the size of the conventional, 
conforming market for loans that would qualify under each Housing Goal 
category based on 2000 Census data and geography. These estimates, 
which are changed slightly from estimates reported in the proposed 
rule, are as follows:

 51-56 percent for the Low- and Moderate-Income Housing Goal
 23-27 percent for the Special Affordable Housing Goal
 35-39 percent for the Underserved Areas Housing Goal

    These market estimates exclude the B&C (i.e., subprime loans that 
are not A-minus grade) portion of the subprime market. The estimates, 
expressed as ranges, allow for economic and market affordability 
conditions that are more adverse than recent conditions. The market 
estimates are based on several mortgage market databases such as HMDA 
and American Housing Survey data. The Department's estimates of the 
size of the conventional mortgage market for each Housing Goal are 
discussed in detail in Appendix D to this rule.
    The GSEs have room for growth in serving the affordable housing 
mortgage market. The Department estimates that the two GSEs' mortgage 
purchases accounted for 55 percent of the total (single-family and 
multifamily) conventional, conforming mortgage market between 1999 and 
2002. In contrast, GSE purchases comprised 48 percent of the low- and 
moderate-income market, 48 percent of the underserved areas market, and 
a still smaller 41 percent of the special affordable market. Thus, the 
remaining 52-59 percent of the Goals-qualifying markets have not yet 
been touched by the GSEs.
    The GSEs' presence in mortgage markets for rental properties, where 
much of the nation's affordable housing is concentrated, is below that 
in the single-family-owner market. The GSEs' share of the total rental 
market

[[Page 63589]]

(including both single-family and multifamily) was also less than 40 
percent between 1999 and 2002. Obviously, there is room for the GSEs to 
increase their presence in the single-family rental and multifamily 
rental markets.
    Table 1 summarizes the Department's findings regarding GSE 
performance relative to market projections for 2005-2008 and the 
Housing Goal levels for 2005-2008.
BILLING CODE 4210-27-P

[[Page 63590]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.000


[[Page 63591]]


    The analysis for 2005 and later reflected in Table 1 is based on 
2000 Census data on area median incomes and minority concentrations, 
using the metropolitan area boundaries specified by OMB in June 2003. 
This affects the market percentages for all three Housing Goals, as 
well as the figures on area median incomes and minority percentage 
figures that will be used to measure GSE performance on the Housing 
Goals beginning in 2005. The greatest effect of the updated data is on 
the Underserved Areas Housing Goal. Expressing this goal in terms of 
2000 Census data adds approximately 5 percentage points to the Housing 
Goal and market levels, compared with analysis using 1990 Census data 
with Metropolitan Statistical Areas (MSAs) as defined prior to 2000.
    The GSEs' baseline performance figures in Table 1 exclude the 
effects of the bonus points for small multifamily and single-family 
two-to-four unit owner-occupied properties and the Temporary Adjustment 
Factor (TAF) for Freddie Mac that were applied in official scoring 
toward the Housing Goals in 2001-2003. The Department did not extend 
these adjustments beyond 2003.
    Table 1 reveals several features of HUD's Housing Goals. First, it 
is evident from this table that the 2005 level (22 percent) for the 
Special Affordable Housing Goal is below the low end (23 percent) of 
HUD's projected market range for 2005-2008. The 2005 level (52 percent) 
of the Low- and Moderate-Income Housing Goal is slightly above the low-
end (51 percent) of HUD's market estimate range.
    Second, the 2005 Underserved Areas Housing Goal level (37 percent) 
is consistent with the market range (35-39 percent) now projected by 
HUD for the Housing Goals using 2000 Census data.
    Third, the GSEs' performance on all of the Housing Goals was 
significantly below the market averages for 1999-2002. Appendix D to 
this rule provides market estimates for the years 1999-2002 under 
different assumptions about the multifamily mix (i.e., newly-mortgaged 
multifamily units as a share of all financed dwelling units). The 
estimates differ between the two home purchase years (1999 and 2000) 
and the heavy refinance years (2001 and 2002). For the low-mod goal, 
the estimates average approximately 56 percent for the two home 
purchase years and 52 percent for the two heavy refinance years, with 
an overall 1999-2002 low-mod average of 54 percent (five percentage 
points above Fannie Mae's performance and seven percentage points above 
Freddie Mac's performance). The market estimates for the underserved 
areas goal average slightly over 37 percent (38 percent during the two 
home purchase years and 36 percent during the two heavy refinance 
years), or approximately 2-4 percentage points above the GSEs' 
performance (see Table 1). The higher Housing Goals are intended to 
move the GSEs closer to or within the market range for 2005, and to the 
upper end of the market range projection by 2008.
    An analysis of the GSEs' mortgage purchases by property type shows 
that they have had much less presence in the ``goals-rich'' rental 
segments of the market, as compared with the ``less-goals-rich'' owner 
segment of the market. As shown in Figure 1, GSE mortgage purchases 
represented 37 percent of single-family and multifamily rental units 
financed between 1999 and 2002. This figure is much lower than their 61 
percent market share for single-family owner-occupied properties. 
(Figure 2 provides unit-level detail comparing the GSEs' purchases with 
originations in the conventional conforming market.)
    Typically, about 90 percent of rental units in single-family rental 
and multifamily properties qualify for the Low- and Moderate-Income 
Housing Goal, compared with about 44 percent of owner units. 
Corresponding figures for the Special Affordable Housing Goal are 
almost 60 percent of rental units and 16.4 percent of owner units. 
Thus, one reason that the GSEs' performance under the Low- and 
Moderate-Income Housing and Special Affordable Housing Goals has fallen 
short of HUD's market estimates is that the GSEs have had a relatively 
small presence in the two rental market segments, notwithstanding that 
these market segments are important sources of affordable housing and 
important components in HUD's market estimates.
BILLING CODE 4210-27-P

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    In the overall conventional conforming mortgage market, rental 
units in single-family properties and in multifamily properties 
represented approximately 25 percent of the overall mortgage market 
between 1999 and 2002, 42 percent of the units that collateralize 
mortgages qualifying for the Low- and Moderate-Income Housing Goal, and 
56 percent of the units that collateralize mortgages qualifying for the 
Special Affordable Housing Goal. Yet between 1999 and 2002, units in 
such properties accounted for only 17 percent of the GSEs' overall 
purchases, 32 percent of the GSEs' purchases meeting the Low- and 
Moderate-Income Housing Goal, and 44 percent of the GSEs' purchases 
meeting the Special Affordable Housing Goal.\8\ Continuing weakness in 
GSE purchases of mortgages on single-family rental and multifamily 
properties has been a significant factor underlying the shortfall 
between GSE performance and that of the primary mortgage market.
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    \8\ These percentage shares are computed from Table A.30 in 
Appendix A. Note that B&C loans are excluded from these data. See 
also Table A.31b in Appendix A.
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e. Ability of the GSEs To Lead the Industry
    An important factor in determining the overall Housing Goal level 
is the ability of the GSEs to lead the industry in making mortgage 
credit available for Housing Goals--qualifying populations and areas.
    The legislative history of FHEFSSA reflects Congress's strong 
concern that the GSEs need to do more to benefit low- and moderate-
income families and residents of underserved areas that lack access to 
credit. (See, e.g., S. Rep. No. 102-282, at 34.) The Senate Report on 
FHEFSSA emphasized that the GSEs should ``lead the mortgage finance 
industry in making mortgage credit available for low- and moderate-
income families.'' (Id.)
    Thus, FHEFSSA specifically requires that HUD consider the ability 
of the GSEs to lead the industry in establishing the level of the 
Housing Goals. FHEFSSA also clarified the GSEs' responsibility to 
complement the requirements of the CRA (see section 1335(a)(3)(B) of 
FHEFSSA, 12 U.S.C. 4565(a)(3)(B)), and fair lending laws (see section 
1325 of FHEFSSA, 12 U.S.C. 4545) in order to expand access to capital 
to those historically underserved by the housing finance market.
    While leadership may be exhibited through the GSEs' introduction of 
innovative products, technology, and processes, and through their 
establishment of partnerships and alliances with local communities and 
community groups, leadership must always involve increasing the 
availability of financing for homeownership and affordable rental 
housing. Thus, the GSEs' obligation to ``lead the industry'' entails 
leadership in facilitating access to affordable credit in the primary 
market for borrowers at different income levels, and with different 
housing needs, as well as in underserved urban and rural areas.
    Because the GSEs' market presence varies significantly by property 
type, the Department examined whether the GSEs have led the industry in 
three different market sectors served by the GSEs: single-family-owner, 
single-family rental (those with at least one rental unit and no more 
than four units in total), and multifamily rental.
    The GSEs' purchases between 1999 and 2002 financed almost 61 
percent of the approximately 36 million owner-occupied units financed 
in the conventional conforming market during that period. The GSEs' 
state-of-the-art technology, staff resources, share of the total 
conventional conforming market, and financial strength strongly suggest 
that they have the ability to lead the industry in making home purchase 
credit available for low-income families and underserved neighborhoods. 
From the analysis in Appendices A-D to this rule, it is clear that the 
GSEs are able to improve their performance and lead the primary market 
in financing Housing Goals--qualifying home purchase mortgages. In 
fact, Fannie Mae's improved performance in 2003 is evidence of this 
potential, as it led the market in funding home purchase loans for 
special affordable and low- and moderate-income families.
    As discussed in Appendix A to this rule, there are a wide variety 
of quantitative and qualitative indicators that demonstrate that the 
GSEs have ample, indeed robust, financial strength to improve their 
affordable lending performance. For example, the combined net income of 
the GSEs has risen steadily over the last 15 years, from $888 million 
in 1988 to $12.7 billion in 2003. This financial strength provides the 
GSEs with the resources to lead the industry in making mortgage 
financing available for families and neighborhoods targeted by the 
Housing Goals.\9\
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    \9\ As discussed in Appendix D, the GSEs questioned HUD's 
historical estimates of the multifamily market as too high. Section 
C of Appendix D discusses these comments and responds. As indicated 
in Table A.30, multifamily loans accounted for 14.8 percent of all 
financed units in the market, excluding B&C loans. As reported in 
Section G of Appendix A and Sections F-H of Appendix D, HUD also 
conducted sensitivity analyses that reduced its 1999-2002 
multifamily shares for the market by approximately two percentage 
points. As a result, 1999-2002 multifamily units decreased from 
7,018,044 units to 5,991,036 units (reducing the multifamily share 
from 14.8 percent to 12.6 percent). With these reduced multifamily 
market numbers, the GSEs' share of the multifamily market increased 
from 35 percent to 41 percent. The GSEs also accounted for higher 
shares of the goals-qualifying multifamily market: 42 percent for 
low-mod units, 34 percent for underserved area units, and 37 percent 
for special affordable units. In this case, the GSEs' shares of the 
overall goals-qualifying markets (including single-family-owner, 
single-family-rental, and multifamily mortgages) increased as 
follows: low-mod--from 48 percent (see right column of Table A.30 in 
Appendix A) to 50 percent (see right column of Table A.31b in 
Appendix A); underserved areas--from 48 percent to 50 percent; and 
special affordable--from 41 percent to 43 percent.
---------------------------------------------------------------------------

    As noted above, the GSEs have been much less active in providing 
financing for the rental housing market. Between 1999 and 2002, the 
GSEs financed 4.5 million rental dwelling units, which represented 37 
percent of the 12 million single-family and multifamily rental dwelling 
units that were financed in the conventional market during this period. 
Thus, the GSEs' share of the rental mortgage market was just three-
fifths of their share of the market for mortgages on single-family 
owner-occupied properties.
    Clearly there is room for the GSEs to increase their presence in 
the single-family rental and multifamily rental markets. As explained 
above, these markets are an important source of low- and moderate-
income housing since these units qualify for the Housing Goals in a 
greater proportion than do single-family owner-occupied properties. 
Thus, Fannie Mae and Freddie Mac can improve their performance on each 
of the three Housing Goals if they increase their purchases of 
mortgages on rental properties.
    As discussed below in Section II.C.4 of this preamble with respect 
to the Home Purchase Subgoals, both GSEs should be able to lead the 
market for single-family owner-occupied properties in all three housing 
goal categories--special affordable, low- and moderate-income, and 
underserved areas. The GSEs are already dominant players in this 
market, which, unlike the rental markets, is their main business 
activity. However, as already discussed, research studies conducted by 
HUD and academic researchers conclude that except for Fannie Mae's 
recent performance on the special affordable and low- and moderate-
income categories, the GSEs have not led the primary market in 
financing owner-

[[Page 63594]]

occupied housing for low-income families, for first-time homebuyers, or 
for properties located in underserved areas.
    As discussed above, the Housing Goals established by this rule are 
quantitative measures of how well the GSEs are serving low- and 
moderate-income homebuyers. HUD received comments on this factor from 
Freddie Mac and one other commenter. The commenter stated that, in 
addition to measuring leadership through the purchase of goal-
qualifying mortgages, Fannie Mae and Freddie Mac's leadership should be 
measured in more qualitative ways such as their ``development of 
products and technologies that the private sector may not be willing or 
able to do as well.'' This commenter asserted that through the 
qualitative leadership of the GSEs, homeownership opportunities are 
expanded and costs lowered for all potential purchasers, including 
those in more affordable markets.
    With respect to the issue of leadership, Freddie Mac contended in 
its comments on the proposed rule that HUD misinterpreted the ``leading 
the industry'' statutory factor and asserted that ``[t]here is no 
intimation in the Act or its legislative history that Congress intended 
industry leadership to be determined based on the enterprises purchases 
of goal-qualifying mortgages.'' Moreover, Freddie Mac commented that 
the GSEs are statutorily mandated to ``facilitate the financing of 
affordable housing for low- and moderate-income families in a manner 
consistent with their overall public purposes.'' Freddie Mac stated 
that the overall public purpose of the GSEs is to facilitate the 
operation of, and provide ongoing assistance to, the secondary market 
for residential mortgages. To the extent that the proposed goals 
inhibit or endanger Freddie Mac's ability to accomplish its general 
purpose of bringing liquidity and stability to the residential mortgage 
market, Freddie Mac contended that its ability to ``lead the market'' 
is in jeopardy. While the Department recognizes the degree of 
qualitative leadership provided by the GSEs, the Department also 
believes that their expertise and substantial financial resources allow 
them to lead quantitatively as well.
f. Need To Maintain the Sound Financial Condition of the GSEs
    Based on HUD's economic analysis prepared for this final rule 
(Economic Analysis) and review by OFHEO, the Department has concluded 
that the Housing Goals in this final rule will not adversely affect the 
sound financial condition of the GSEs. Further discussion of this issue 
is found in the Economic Analysis.
3. Determinations Regarding the Levels of the Housing Goals
    There are several reasons why the Department, having considered all 
the statutory factors as well as the comments on the May 3, 2004, 
proposed rule, is increasing the levels of the Housing Goals. The 
following sections describe these reasons and discuss and respond to 
comments received by HUD regarding the levels of the housing goals.
a. HUD's Market Analysis
    Summary of Comments and HUD's Determination. As part of the process 
of establishing goals, HUD estimates the size of the conventional 
conforming mortgage market. In this process, HUD separately analyzes 
the markets for several different categories of mortgage loans: single-
family owner-occupied housing units, rental units in two-to-four unit 
properties where the owner occupies one unit, rental units in one-to-
four-unit investor-owned properties, and rental units in multifamily 
(five or more units) properties. This categorization is necessary 
because the data sources differ for the various categories, and it is 
also desirable because goals-qualifying shares of units vary markedly 
by category. HUD described its methodology for analyzing each category 
in Appendix D to the proposed rule, and the GSEs commented on that 
analysis. Other commenters expressed concern about the magnitude of the 
goals, but did not discuss the analysis on which the goals calculations 
were based.
(i) Multifamily Share of the Mortgage Market
    An important component of HUD's calculation process is estimating 
the number of multifamily units financed each year as a percentage 
share of the total number of dwelling units financed (often referred to 
as the ``multifamily mix''); this is important because of the high 
proportions of multifamily units, which qualify for credit under all 
three goals. Section C of Appendix D to this Final Rule provides a 
detailed discussion of estimates of the size of the multifamily 
mortgage market, including estimates by HUD, the GSEs, and other 
researchers. As explained in Appendix D, comprehensive data on the 
annual volume of multifamily mortgage originations are much less 
available than similar data on single-family mortgage originations. 
This introduces a degree of uncertainty into the market sizing analysis 
and highlights the need for sensitivity analyses to show the effects of 
different multifamily mixes on the size of the goals-qualifying 
markets. As explained below, HUD's market analysis focused on 
multifamily mixes between 13.5 percent and 16.0 percent, with a 
baseline of 15 percent. This range and baseline is consistent with 
HUD's historical estimates of the multifamily mix reported in Table 
D.5b of Appendix D. For example, between 1995 and 2002, HUD estimated 
that the multifamily mix was in the 14-16 percent range.
    In its comments, Fannie Mae estimated a multifamily mix of 12.3 
percent, stating that HUD's range is too high for current conditions in 
the multifamily market. Fannie Mae cited the current high vacancy rates 
for multifamily properties and the fact that the population aged 20 to 
34 will not begin to increase until after 2007; this age group tends to 
be predominantly renters. Fannie Mae also projected a low multifamily 
refinance volume, because of a recent peak in multifamily originations; 
these recent originations will not be able to refinance easily under 
their current contracts until 2008 or later.
    At Freddie Mac's request, ICF Consulting also calculated the 
multifamily mix. In its best estimate, ICF projected an average of 14.2 
percent over the 2005-2008 period, ranging between 13.7 percent and 
14.7 percent in individual years, while recognizing that the actual 
outcomes may be higher or lower. ICF projected multifamily refinancings 
based on the number of units financed eight, nine, and ten years ago, 
because 10-year balloon mortgages are the most common multifamily 
mortgages, and prepayment possibilities are limited by yield 
maintenance agreements in their current mortgage contracts.
    In Appendix D to this rule, HUD reviews the evidence provided by 
the GSEs in their comments. HUD notes that the 2001 Residential Finance 
Survey (RFS) has recently been published by the Census Bureau, and that 
the RFS provides higher estimates of the multifamily mix for 1999-2001 
(the most recent years available) than either Fannie Mae or ICF. The 
RFS data and other data analyzed in Appendix D to this rule suggest 
that 15.0 percent is a reasonable baseline, particularly in a home 
purchase mortgage market environment, with a relatively small volume of 
refinanced mortgage originations. HUD also notes that the ICF average 
of 14.2 percent is fairly close to HUD's estimate of 15.0 percent. HUD 
therefore continues to use 15.0 percent as the best estimate of the

[[Page 63595]]

projected share of multifamily mortgages over the 2005-2008 period. HUD 
reports the goals-qualifying shares of mortgage originations on the 
basis of this estimate in Appendix D to this rule. HUD also publishes 
sensitivity analyses using other estimates of the multifamily mix, 
including 12.3 percent (Fannie Mae estimate), 13.5 percent (low end of 
HUD's range), 14.2 percent (ICF's best estimate), and 16.0 percent 
(high end of HUD's range). Using this range of multifamily mix 
estimates, the estimate of the goals-qualifying share of mortgage 
originations varies by about 1.5 to 2.5 percentage points for the low-
mod goal, by about 1.0 percentage point for the underserved areas goal, 
and by about 1.2 to 1.7 percentage points for the special affordable 
housing goal. The estimate varies depending on other market factors.
    As also discussed in Appendix D to this final rule, the multifamily 
mix is even lower during heavy refinance environments, as single-family 
owner refinance loans dominate both the market and the GSEs' purchases. 
This makes it more difficult for the GSEs to meet specific Housing Goal 
targets. As discussed in section b below of this preamble, HUD is 
soliciting public comments on how to structure and implement a 
regulatory provision to take account of the effects of high volumes of 
refinance loans in some years on the GSEs' ability to achieve the 
Housing Goals.
(ii) Single-Family Rental Share of the Mortgage Market
    HUD also estimated the distribution of mortgage originations for 
single-family properties, defined as structures with one-to-four units. 
In Appendix D to this rule, HUD disaggregates single-family mortgage 
originations into three categories: those on owner-occupied single-
family homes, those on structures with two to four units having one 
unit owner-occupied, and those on structures with one to four rental 
units owned by investors. HUD bases this categorization on the fact 
that the rental units in the latter two categories qualify at much 
higher rates for the housing goals.
    HUD uses two data sources in Appendix D to estimate the size of the 
investor category, the Residential Finance Survey (RFS) and the Home 
Mortgage Disclosure Act database (HMDA). HMDA provides data only on the 
investor category. The investor share of HMDA single-family loans 
averaged 7.8 percent over 1993-2003, and 8.3 percent over the recent 
period of 1999-2003. The share of investor loans has also been rising 
for home purchase loans; it was 9.6 percent over 1993-2003 and 11.2 
percent over 1999-2003. The RFS for 2001 reported a larger share of 
investor loans than HMDA, 13.4 percent compared to 7.8 percent. The RFS 
also reported larger investor shares for 1999 and 2000.
    In the proposed rule, HUD estimated the investor share of the 
single-family market at 10 percent, based on HMDA data and the 2001 
RFS, which was then the most recent available. HUD also considered 
alternatives of 8 percent and 12 percent. Both GSEs and ICF commented 
that HUD should use HMDA data rather than RFS data, and should use a 
lower investor share in setting the goals. While they agreed with HUD 
that the RFS provides the most accurate estimate of the true investor 
share of the market, they stated that lender reporting of investor 
loans to the GSEs is conceptually closer to HMDA data, which are based 
on lender reports. They commented that the actual opportunities 
available to the GSEs in the single-family investor loan market are 
best measured by data that lenders report, based on actual loan 
applications.
    Fannie Mae stated that HUD's two highest alternatives exceed the 
highest investor share ever reported in HMDA. Fannie Mae cited research 
indicating a reporting bias in HMDA, due to ``hidden investors.'' At 
the time of loan origination, a property may be owner-occupied or 
intended for owner-occupancy, but may become rental shortly after 
origination. Fannie Mae stated that the same bias exists in its own 
reporting. The hidden investors cannot be identified at the time of 
origination.
    Freddie Mac stated that investors have an incentive to claim 
falsely that they are owner-occupants because investor properties are 
subject to higher underwriting standards and loans tend to carry higher 
interest rates. Freddie Mac concluded that HUD should measure the 
opportunities that are actually available in the market to the GSEs, 
which are best measured by lender-reported HMDA data.
    In this rule, HUD has adopted HMDA data as the basis for its 
calculation of the investor share of single-family mortgage 
originations. The GSEs make a valid argument that lender-reported data 
at the time of origination measures the investor loans that are 
available for them to purchase; HMDA provides that data. As discussed 
in Appendix D to this rule, HUD projects the investor share to be 8.5 
to 9.0 percent (based on HMDA) during the 2005-2008 home purchase 
environments, rather than 10 percent. HUD also reports sensitivity 
analyses for higher and lower investor shares of 8.0 and 9.5 percent. 
Using this range of single-family investor share estimates, the 
estimate of the goals-qualifying share of mortgage originations varies 
by about 1.5 percentage points for the low-mod goal, and by 0.5 percent 
or less for the other two goals. The estimate varies depending on other 
market factors.
    In the proposed rule, HUD estimated that the share of the single-
family market consisting of two-to-four units properties with one unit 
owner-occupied was 2.0 percent of all single-family mortgages. This 
category is reported only in the RFS. The 2001 RFS reports that this 
category comprised 1.5 percent of all single-family mortgages. Because 
the RFS calculates a higher share of investor mortgages in the single-
family market (13.4 percent) than HUD employs in this rule (8.5 to 9.0 
percent), it is necessary to adjust the 2001 RFS figure upward.
    The RFS reports that 85.1 percent of all single-family mortgages 
were for owner-occupied homes. The estimated share of two-to-four units 
properties with one unit owner-occupied in the single-family market is 
calculated at 1.73 percent (i.e., 1.5 percent/[1.5 percent + 85.1 
percent]). This figure lies between Fannie Mae's share of about 2.0 
percent over 1999-2003 and Freddie Mac's share of about 1.5 percent. In 
this final rule, HUD uses a share of 1.6 percent. Sensitivity analyses 
for 2.0 percent are reported in Appendix D to this rule.
    Similarly, the single-family owner-occupied share is adjusted 
upward to take account of the lower share of investor loans, from 85.1 
percent to 89.9 percent.
    The estimated market share range for each of the three goals 
categories is as follows: 51-56 percent for the Low- and Moderate-
Income Goal, 35-39 percent for the Underserved Areas Goal, and 23-27 
percent for the Special Affordable Goal. These estimates are one 
percentage point below the market ranges reported in the Proposed Rule, 
for the reasons discussed above and detailed in Sections F-H of 
Appendix D. The top ends of the market ranges were reduced as follows: 
from 57 percent to 56 percent for the low- and moderate-income market; 
from 40 percent to 39 percent for the underserved areas market; and 
from 28 percent 27 percent for the special affordable market. 
Accordingly, the 2008 goals were also reduced by one percentage point 
from those included in the Proposed Rule. In the Final Rule, the Low- 
and Moderate-Income Goal increases from 52 percent in 2005 to 56 
percent in 2008, as

[[Page 63596]]

compared with an increase of 52 percent to 57 percent in the Proposed 
Rule. In the Final Rule, the Underserved Areas Goal increases from 37 
percent in 2005 to 39 percent in 2008, as compared with an increase of 
38 percent to 40 percent in the Proposed Rule. In the Final Rule, the 
Special Affordable Goal increases from 22 percent in 2005 to 27 percent 
in 2008, as compared with an increase of 22 percent to 28 percent in 
the Proposed Rule.
b. Attainability of the Goals in a High Refinance Environment
    Summary of Comments. A common theme of many of the public comments 
was concern about the volatility of the mortgage market and how such 
volatility makes setting Housing Goals a delicate and risky 
proposition.
    These commenters indicated that the goals proposed by HUD would be 
unattainable, particularly in a high refinance environment when a large 
portion of the mortgage market is comprised of refinance loans rather 
than home purchase mortgages.
    Fannie Mae and others suggested that including single-family 
refinance mortgages in goals calculations creates tension between 
liquidity goals and affordable housing goals by taking the emphasis 
away from increasing purchase money mortgages (and therefore 
homeownership) and placing the focus instead on meeting high goals.
    Freddie Mac, several trade associations, a financial organization 
and consumer advocacy groups also expressed concern that inclusion of 
single-family refinances jeopardizes the GSEs' abilities to increase 
homeownership through acquisitions of purchase money mortgages because 
the focus would be on attaining goals rather than providing affordable 
home purchases for the target population.
    One trade association, however, asserted that removing refinance 
mortgages from the goals calculations would only serve to encourage the 
GSEs to buy refinance loans instead of home purchase loans. By buying 
refinance loans, the GSEs could effectively ignore housing goals and 
both ``jeopardize the safety and soundness of the GSEs due to the 
higher default rate of refinance loans and increase the minority 
housing gap due to the lower rate of minority borrowers for refinance 
loans.''
    Other commenters suggested that the final rule should include 
mechanisms for making adjustments to the goals if there are changes in 
market conditions including a surge or drop in refinance volume. These 
commenters asserted that the GSEs' ability to successfully meet the 
goals should not be contingent upon interest rate stability. One 
suggestion that was offered for dealing with market mix fluctuations 
(i.e., between home purchase and refinance loans) was to remove from 
both the numerator and denominator ``any mortgage activity in excess of 
the percentage of home refinance loans used by HUD for estimating the 
size of this market (i.e., above 35%).''
    Another commenter stated that ``HUD should simply set goals that 
require the GSEs to lead the market, whatever the market turns out to 
be.'' This commenter explained that ``if 50% of home purchase loans are 
to low-moderate income borrowers in 2005, then HUD should expect that a 
slightly higher percentage than this, say 51%, of Fannie's and 
Freddie's home purchase loans should fit in the purchase category of 
loans to low-moderate income borrowers.''
    HUD's Determination. This final rule retains the approach of the 
May 3, 2004, proposed rule, in which the level of each Housing Goal 
will increase year-by-year so that by 2008 each goal will match the top 
of the market range established in section 2.d, above.
    The last three years have shown unprecedented volumes of refinance 
activity. For both GSEs, refinance loans accounted for 64 percent of 
all loans on single-family owner-occupied properties in 2001.\10\ The 
refinance shares increased to 70 percent for Fannie Mae and 73 percent 
for Freddie Mac in 2002, and rose even further last year, to 79 percent 
for Fannie Mae and 82 percent for Freddie Mac. These unexpected record 
refinance rates made it more challenging for the GSEs to attain the 
housing goals in the past few years, as discussed elsewhere in this 
Preamble. The goals in HUD's proposed rule for the latter part of the 
2005-2008 period would be even more challenging if (contrary to current 
expectations) very high refinance rates are experienced in those years.
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    \10\ By way of comparison, the refinance rate was 29 percent for 
both Fannie Mae and Freddie Mac in 2000.
---------------------------------------------------------------------------

    HUD received a number of public comments seeking a regulatory 
solution to the issue of the ability of the GSEs to meet the housing 
goals during a period when refinances of home mortgages constitute an 
unusually large share of the mortgage market. HUD is not addressing the 
refinance issue as a regulatory change in this final rule. Elsewhere in 
today's Federal Register, HUD is publishing an Advance Notice of 
Proposed Rulemaking that advises the public of HUD's intention to 
consider by separate rulemaking a provision that recognizes and takes 
into consideration the impact of high volumes of refinance transactions 
on the GSEs' ability to achieve the housing goals in certain years, and 
solicits proposals on how such a provision should be structured and 
implemented. HUD believes that it would benefit from further 
consideration and additional public input on this issue. HUD also notes 
that FHEFSSA provides a mechanism by which HUD can take into 
consideration market and economic conditions that may make the 
achievement of housing goals infeasible in a given year. (See 12 U.S.C. 
4566(b).)
c. Bonus Points
    The Housing Goals 2000 final rule provided for the award of bonus 
points (double credit) toward the Housing Goals for both GSEs' mortgage 
purchases that financed single-family, owner-occupied two-to-four unit 
properties and 5-50 unit multifamily properties. The rule also 
established a temporary adjustment factor (TAF) that awarded Freddie 
Mac 1.2 units credit for each multifamily unit in properties over 50 
units for calendar years 2001 through 2003. (Congress increased the 
level of the TAF to 1.35 per unit under section 1002 of Public Law 106-
554.)
    The Housing Goals 2000 final rule made clear that both of these 
measures were temporary, intended to encourage the GSEs to increase 
their efforts to meet financing needs that had not been well served. 
During the three years for which the temporary bonus points and TAF 
were established, HUD expected the GSEs to develop new, sustainable 
business relationships and purchasing strategies for the targeted 
needs. Data indicate that, because both GSEs did increase their 
financing of units targeted by the bonus points and the TAF, the 
original objectives were met. The Department determined at the end of 
the three years (2001-2003) not to extend the bonus points or the TAF.
    Summary of Comments. A number of non-GSE commenters, including 
organizations representing affordable housing and consumer groups, 
trade associations, organizations representing racial and ethnic 
minorities, other organizations, and both Fannie Mae and Freddie Mac, 
recommended that the Department reinstate the award of bonus points for 
the GSEs which were established for 2001-2003 but which the Department 
did not continue after the end of 2003. Various non-GSE commenters, in 
addition to recommending reinstatement, also suggested that HUD develop 
new bonus point incentives for other unmet housing needs, such as 
manufactured

[[Page 63597]]

housing, rural housing, or tax credit properties or for particular 
groups, e.g., Native Americans, other minority populations, or persons 
with disabilities.
    Fannie Mae recommended that HUD provide bonuses for targeted 
business such as extremely low-income households, i.e., those with 
incomes less than 30% of area median income (AMI); first-time 
homebuyers; manufactured housing; rural areas; and small multifamily 
properties. Freddie Mac suggested that instead of purchase money 
subgoals, the Department could provide bonus point incentives for these 
mortgages. Freddie Mac stated that the bonus points for two-to-four 
unit and 5-50 unit properties provided an extremely effective 
incentive. Freddie Mac indicated that other markets that could be 
assisted by bonus points are rural and manufactured housing. Freddie 
Mac noted that the Department's concern that bonus points obfuscate the 
GSEs' actual goals-qualifying performance is easily remedied by having 
the GSEs report two numbers, one with and one without the bonuses.
    HUD's Determination. The Department has fully considered the 
comments suggesting the re-introduction of bonus points, as well as 
other types of targeted incentives for the GSEs' mortgage purchases, 
and has determined not to reinstate the bonus points for the years 
covered by this rule. The position of the Department discussed in the 
preamble of the proposed rule (see 69 FR 24228, 24232) remains 
unchanged; that is, the continued use of the bonus points ``would only 
result in misleading information about the extent to which the GSEs 
are, in fact, meeting the Housing Goals.'' In addition, the Department 
reiterates that the ``decision to increase the levels of the Housing 
Goals substantially in a staged manner * * * and, at the same time, not 
renew the bonus points or TAF, will ensure that the GSEs continue to 
address the areas formerly targeted by these measures'' (see 69 FR 
24228, 24232).
d. Appropriate Levels of the Goals
    In the May 3, 2004, proposed rule, HUD set the Goals to increase to 
levels at or near the high end of the estimated market range for each 
goal category by 2008. A large number of commenters expressed concern 
that these goal levels were set too high, and could have deleterious 
consequences for the mortgage market as a whole, or for specific 
sectors of the market.
    Fannie Mae commented that a high allocation of affordable mortgage 
credit will take away from the broad middle class, especially in high-
housing cost regions. For example, Fannie Mae asserted that if the 
special affordable housing goal had been set at 28 percent in 2003, 
then it would have needed to greatly curtail support to the overall 
market to meet that goal. Fannie Mae concluded that such manipulation 
does not promote stability and limits liquidity, and that it can shut 
out working middle class borrowers, contribute to higher interest rates 
and lower conforming loan limits.
    Many commenters, including Freddie Mac, also claimed that setting 
the goals at a high percentage may lead to denominator management. They 
state that denominator management would occur if a GSE purposely 
abstained from buying mortgages in the markets that are not goals-
eligible, rather than increasing its purchases in markets that are 
goals-eligible. Freddie Mac contended that this may be necessary if 
goals are set above the market percentage of available goal-qualifying 
loans. One financial institution observed that denominator management 
``will be exacerbated by the fact that the GSEs do not operate in the 
primary market and do not have any direct control over the origination 
strategies of their customers.''
    In addition to the allocation problems discussed above, the GSEs 
stated that the liquidity requirements in their charters imply that 
they must stand ready to buy any and all conventional, conforming 
residential mortgages. They contend that denominator management is in 
direct conflict with these provisions, and goals set higher than market 
originations could force the GSEs to refuse to purchase mortgages that 
are not eligible. This, in turn, could reduce liquidity in the market. 
Knowing that the GSEs would no longer stand willing and able to 
purchase all conventional, conforming mortgages, other market 
participants might be less willing to hold these mortgages in their 
portfolios, and general liquidity would decline. The GSEs further 
asserted that changing market forces could cause swings in prices and 
trading volumes, and these temporary disturbances could create unstable 
markets, increase risk, and reduce the willingness of investors to 
invest in the sector. Thus, the GSEs maintained that denominator 
management decreases market stability.
    The GSEs pointed to specific historical examples that describe 
their positive influence on stability. They maintained that during the 
1990-1991 recession, the GSEs advised that they stood ready to purchase 
mortgages while many industry participants curtailed their purchase 
programs. Using historical trends in prices, the GSEs asserted that 
their presence in the mortgage market explains why mortgage-backed 
securities have a more stable price trend than commodity markets. They 
warned that because of denominator management resulting from 
unrealistic goals, they could not buy mortgage-backed securities and 
encourage stability in a financial crisis.
    The GSEs further contended that if they reduce their willingness to 
buy non-goals eligible mortgages, it will be harder for borrowers whose 
incomes marginally exceed goals eligibility requirements to obtain 
financing since the two income-based Housing Goals compare the incomes 
of the borrower or resident to area median income. For example, the 
combined incomes in a working family may just disqualify that family's 
loan for eligibility under the low- and moderate-income goal even 
though each individual's income would not be considered to be affluent. 
The GSEs and other commenters provided examples of working families in 
the middle class, such as ``teacher/fireman'' households, that could 
encounter difficulties in financing a home.
    Moreover, the commenters asserted that non-goal qualifying 
households may have higher costs associated with available financing 
since these mortgages would be less likely to be purchased by a GSE. 
Freddie Mac asserted that HUD did not take this into account in its 
cost/benefit analysis.
    Furthermore, commenters claimed that denominator management may 
contribute to higher interest rates and, as a result, harm the precise 
borrowers that HUD is trying to help. These commenters stated that if 
denominator management reduces liquidity then the supply of mortgage 
funds will decline and interest rates will rise. The GSEs contended 
that if they are less willing to buy mortgages under all conditions, 
then investors will be less willing to provide funds to the market. As 
a result, the GSEs claimed that as investors seek out safer 
instruments, home mortgage interest rates will rise, and this rise in 
home mortgage rates will harm even those borrowers that are still 
goals-eligible.
    Several commenters expressed concern about the effect of the goals 
on high cost markets. One commenter explained that while the goals are 
set with a national standard, a market level analysis ``reveals a 
pronounced shortage of affordable mortgages in high cost housing 
markets.'' Commenters stated that the GSEs' current loan purchasing 
patterns demonstrate that market affordability already has an impact on 
goals-related purchases. The

[[Page 63598]]

commenters expressed concern that high cost markets could see even 
tighter credit if the proposed goals are enacted.
    The GSEs note that under HUD's May 3, 2004, proposed rule, the goal 
levels rise to levels at the top of HUD's market range in 2008 and 
stabilize there. They state that the projected market range concept is 
one in which HUD projects market levels of loans generated within each 
goal category will fluctuate within the range, depending on relative 
volumes of single-family refinance loans relative to other loans, 
interest rates and other macroeconomic and housing market conditions. 
The GSEs express the concern that, in any particular year, they could 
be confronted with goal levels that are several percentage points 
higher than the market percentages of goal-qualifying loans, or goal 
levels that are at the market percentages. The GSEs state that if HUD's 
proposed Housing Goals are retained, they foresee years when the goal 
levels will be attainable only by means of ``denominator management'' 
in which they limit their purchases of loans that do not qualify for 
the goals.
    HUD's Determination. Many of the comments expressed concern about 
the goal levels established for the last year or two of the period 
covered by this rule. In these years, the goals are set at the market 
levels estimated by HUD. Also, since they are the later years, market 
projections are necessarily more imprecise. In particular, the 
possibility of a decline in mortgage interest rates in those years 
raises the possibility of another boom in refinancing, and thus greater 
difficulty for the GSEs to meet the housing goals without denominator 
management. The comments relating to middle-income borrowers are 
predicated on the difficulty of foreseeing refinance volatility. Recent 
years have seen large unexpected home refinance rates. Since higher 
income homeowners disproportionately engage in refinancing, inclusion 
of refinance loans in the denominator increases the difficulty of GSE 
goals performance. A middle-income borrower just above the low/mod 
bracket would be less attractive to the GSEs in high refinance years. 
As noted in section II.C.3.b., HUD is considering in a separate 
rulemaking a provision that recognizes and takes into consideration the 
impact of high volumes of refinance transactions on the GSEs' ability 
to achieve the housing goals in certain years. HUD also notes that 
FHEFSSA provides a mechanism by which HUD can take into consideration 
market and economic conditions that may make the achievement of housing 
goals infeasible in a given year. (See 12 U.S.C. 4566(b).)
    With regard to the effects of the goals on high-cost markets, HUD 
notes that the overall presence of the GSEs in these markets depends on 
the conforming loan limit, which has been established by Congress for 
all states, including states deemed to be ``high-cost areas.'' With 
regard to HUD's housing goals more specifically, the low- and moderate-
income and special affordable goals are based on borrower income 
relative to area median income, thus a mortgage for a lower-income 
family in a high-income metropolitan area will count towards the goals 
in the same manner as a mortgage for a lower-income family in a low-
income area. Underserved areas are defined in terms of median family 
income in a census tract relative for median income in the area; thus a 
mortgage for a family living in a lower-income tract in a high-income 
metropolitan area will count towards the goals in the same manner as a 
mortgage for a family living in a lower-income tract in a low-income 
area. Thus HUD concludes that its housing goals will have no adverse 
impact on borrowers or neighborhoods in areas with high housing costs.
e. Consequences of the Goals for FHA
    Fannie Mae, Freddie Mac, several trade associations, two advocacy 
groups and two financial institutions expressed concern over the impact 
HUD's proposed goals would have on the future solvency of the FHA 
program. One trade association asserted that ``excessive goals will 
push GSEs to expand into the least-risky part of the FHA market and put 
into question FHA's long-term viability.''
    The aforementioned commenters reiterated this point by stating that 
unrealistically high goals would compel the GSEs to increase 
competition with FHA for higher credit quality borrowers and would 
therefore further undermine the FHA program in the long-run. One 
advocacy group asserted that not only will these goals encourage the 
GSEs to compete with FHA more in the single family sector but in the 
multifamily sector as well.
    Freddie Mac and Fannie Mae agreed that they would be compelled to 
more aggressively compete with FHA in procuring top-quality borrowers. 
Freddie Mac stated that the GSEs would take as many as ``\1/3\ of all 
FHA borrowers.'' Freddie Mac and two trade associations further 
contended that such a loss to the FHA program would be seen in the 
increasing expenses to the remaining FHA borrowers. As the FHA program 
loses better quality loans to the GSEs, the result would be ``higher 
fees to FHA borrowers or government subsidies to pay claims, 
effectively making FHA the lender of last resort,'' said one trade 
association.
    One financial institution stated that the so-called competition for 
goals-qualifying loans would not be between traditional conventional 
lenders vying for loans with a separate group of traditional FHA 
lenders, but rather an acceleration of product competition within a 
single group of existing lenders who originate for both markets. This 
commenter stated that 12 of the top 15 (by volume) FHA/VA lenders are 
also among the top 15 conventional lenders and indicated that the 
increased product competition would not result in a net increase in 
goals-qualifying loans, but in a shift from FHA to the GSEs of FHA's 
relatively lower risks.
    HUD's Determination. The Department agrees with many of these 
commenters that improvements in technology, such as the widespread use 
of commercial credit scores, mortgage scores, and automated 
underwriting systems, have fundamentally changed the way lenders 
process loan applications in recent years. Where once rules-based 
underwriting distinctions between prime conventional and FHA loans were 
fairly clear, in recent years, with the new technology, these 
distinctions have become blurred. For example, loan applications with 
payment-to-income ratios above conventional market guidelines were once 
clearly candidates for FHA financing because FHA would accept 
applicants with higher payment-to-income ratios. However, today, the 
same application would be processed using an automated underwriting 
system (AUS) that scores the application based on the totality of the 
application's risk factors. What once may have been an unacceptable 
payment-to-income ratio for a prime conventional loan may now be 
acceptable if the application contains offsetting low risks in other 
key areas such as borrower cash reserves, loan-to-value ratio, or 
commercial credit scores.
    In addition to these technological changes, FHA made several 
changes to its underwriting guidelines in FY 1995 in order to promote 
increased homeownership opportunities among low-income and minority 
homebuyers. By doing so, FHA modestly increased the risk 
characteristics of its post-1995 books of business, but it succeeded in 
raising FHA's proportion of first-time homebuyers from 60.9 percent in 
fiscal year 1994 to 73.0 percent in fiscal year 2003. During the same 
period (fiscal years 1994 to 2003), FHA's proportion of minority 
borrowers increased from 24.8 percent to 33.0 percent, and has since 
remained at this level, or higher.

[[Page 63599]]

    The new technology may allow the conventional market to identify 
lower risk loan applications that historically have come to FHA. 
However, the ability to identify risks does not, in and of itself, 
equate to shifts in market share from FHA to conventional lenders. 
Better pricing for borrowers by the conventional market is required to 
lure lower risk borrowers from FHA. If conventional lenders use the new 
technology to not only evaluate risks but also to price according to 
risk, then there may be some shift from FHA to the conventional market. 
Such a shift can produce tangible benefits for borrowers in the form of 
lower cost mortgage financing.
    The Department does not believe it is FHA's mission to compete with 
the private sector. Rather, FHA's mission is to complement the 
conventional market, using FHA's cost of capital advantage where it can 
have the most benefit in creating homeownership opportunities for those 
households who might not otherwise be served by the prime conventional 
market.
    HUD gauges the soundness of FHA's insurance funds in several ways. 
The statutorily mandated annual independent actuarial review of FHA's 
principal single-family insurance fund, the Mutual Mortgage Insurance 
Fund (MMIF), provides the Department, and the public, with an outside 
expert's estimate of the capital ratio of the overall fund, and the 
economic value of new business coming into the fund. The capital ratio 
indicates whether the existing books of business (current portfolio) 
are financially sound, while the economic value estimates of new 
business show whether if the marginal impact of new loans insured is 
adding or detracting from the financial health of the fund.\11\ 
Specifically, the Fiscal Year 2003 actuarial review estimated the 
economic value of the MMIF at the end of Fiscal Year 2003 to be $22.7 
billion and the fund's capital ratio to be 5.21 percent--the eighth 
full year this ratio has exceeded the Congressionally mandated minimum 
of 2.0 percent. The economic value of new loans endorsed for insurance 
during 2003 was estimated by FHA's independent actuary to be $2.8 
billion, indicating new business coming into FHA is further 
contributing to FHA's reserves.
---------------------------------------------------------------------------

    \11\ ``Economic value'' is the net present value of the fund's 
reserves plus expected future cash flows, and the ``capital ratio'' 
is economic value divided by insurance-in-force.
---------------------------------------------------------------------------

    In comparison, the Fiscal Year 2002 actuarial review estimated the 
economic value and capital ratio of the MMIF at $22.6 billion and 4.52 
percent, respectively. The increases in both measures for Fiscal Year 
2003 were driven by the large positive economic value the actuary 
placed on a record dollar volume of new loans FHA insured in FY 2003 
along with the rapid prepayment of older loans, keeping the end-of-year 
insurance-in-force (denominator of the capital ratio) down.
    With regard to the GSEs taking multifamily business away from FHA, 
the Department notes that there are many differences between the types 
of multifamily mortgages FHA insures and those the GSEs purchase. For 
newly constructed multifamily properties, FHA insures the loan from the 
start of construction while GSE multifamily loan products generally do 
not. The GSEs do have forward commitment programs that can be used for 
new construction, but the purchase of the permanent loan by the GSEs 
generally requires the property to achieve minimum sustained occupancy 
levels, whereas FHA does not have this requirement. However, it is 
possible that the new goals will provide incentives for the GSEs to 
expand and refine their forward commitment products to be more 
attractive in the market for new multifamily housing. This could be a 
benefit to the market.
    The greatest potential impact of the higher housing goals on FHA's 
multifamily business may come from a reduction in two of FHA's programs 
that address the purchase or refinance of existing properties. The 
first is the Section 223(f) program, which insures mortgages for the 
purchase or refinance of existing (over three year old) properties that 
are not currently financed with an FHA mortgage. This program accounted 
for about $0.8 billion in endorsements for FHA during Fiscal Year 2003, 
and is expected to produce about $0.5 billion in endorsements during 
Fiscal Year 2004. FHA's 223(f) business is estimated to be profitable 
to FHA--it is estimated to have a credit subsidy (net present value of 
all cash flows from the insurance contract at the time of endorsement) 
of negative 3.0%.\12\ The second is the Section 223(a)(7) program, 
which insures mortgages for FHA-to-FHA refinances--that is, the 
refinance of an existing FHA-insured mortgage. Section 223(a)(7) is 
used, for example, to refinance loans previously insured under FHA's 
most used programs--i.e., Section 221(d)(4) new construction/
substantial rehabilitation, and Section 223(f). FHA endorsed over $2.1 
billion in Section 223(a)(7) loans during Fiscal Year 2003, and is 
expected to endorse about $1.4 billion during Fiscal Year 2004. As with 
the Section 223(f) program, FHA's Section 223(a)(7) program is also 
profitable to FHA--operating with an estimated negative credit subsidy 
of 2.2%.
---------------------------------------------------------------------------

    \12\ A negative credit subsidy of 3.0 percent means that the net 
present value of FHA's revenues (premiums, fees, recoveries from 
claims paid, etc.) will exceed the net present value of FHA's 
program costs (claims and related expenses) by 3.0 percent of the 
total insured mortgage amount.
---------------------------------------------------------------------------

    If FHA does lose some multifamily market share from its purchase or 
refinance programs for existing housing as a result of the goals, it 
would not likely have any significant impact on FHA overall.
f. Consequences of the Goals for the Multifamily Market
    Summary of Comments. Several organizations commented on potential 
adverse consequences if the housing goals are set too high. Fannie Mae 
and Freddie Mac, among others, cited the recent high vacancy rates for 
multifamily rental housing as an example that increased lending by the 
GSEs at this time would encourage overbuilding.
    Others stated that the multifamily market is already flush with 
capital and that inappropriate goals could promote overly aggressive 
bidding for loans and reckless lending.
    One trade association stated that the increased presence of the two 
GSEs would promote a duopsony (a market with only two buyers) that 
would hinder competition in the multifamily mortgage market.
    Other commenters suggested that increased loan purchases by the 
GSEs would skim the highest credit-quality loan from other mortgage 
lenders, and reduce the credit quality of multifamily loans remaining 
in the portfolios of pension funds or insured through FHA.
    Another commenter stated that increased goals pressure on the GSEs 
would cause them to concentrate on large properties, where a single 
loan would contribute more toward goal attainment.
    HUD's Determination. One of HUD's objectives in promulgating this 
final rule is to promote the availability of mortgage credit to 
affordable properties at the lowest possible cost. It is not the intent 
of this rule to promote the maximum flow of credit to this market, 
regardless of housing and mortgage market conditions.
    Increased competition for business, as intended by the rule, should 
bring benefits to borrowers, and therefore renters, through lower 
interest rates and more attractive non-price terms. Such increased 
competition does not imply impaired credit quality or lax

[[Page 63600]]

underwriting. As the GSEs compete more aggressively for multifamily 
business and gain market share, the market will not necessarily grow 
one-for-one with every additional loan purchased by the GSEs. It is 
likely that the market impacts will be more on the pricing of 
multifamily credit and less on the volume of credit supplied. Lower 
pricing of credit in and of itself does not promote overbuilding; its 
one unambiguous effect is to reduce the cost of supplying housing to 
consumers.
    Demand for multifamily mortgages will be responsive to cyclical 
macroeconomic factors. Beyond these influences, demand for multifamily 
housing will be supported by favorable demographics. In its comments on 
the proposed rule, Fannie Mae highlighted the prospective growth in the 
number of people ages 20 through 34 in arguing that the demographics do 
not become clearly favorable to rental demand until late in this 
decade. But fewer than half of all renter households are headed by 
someone of this age, and more comprehensive estimates and projections 
suggest a steadier path of moderate growth in the demographic component 
of demand for multifamily housing.
    Interest rates clearly will be important for the future path of 
mortgage lending, as noted by Fannie Mae, Freddie Mac, and other 
commenters. The historically low interest rates of recent years have 
spurred lending in both the multifamily and single-family markets. If 
interest rates should rise in the future, the volume of mortgage 
lending presumably would be lower than if rates were to remain at 
current levels. But the effect of higher rates on the GSEs' ability to 
achieve the housing goals is less clear. Because the goals are 
established in terms of shares of the GSEs' business, rather than 
levels, a key question is how higher interest rates would affect the 
relative demand for single-family and multifamily mortgage credit. 
Because of differences in prepayment provisions and other 
characteristics between single-family and multifamily mortgage lending, 
multifamily credit demand might drop off proportionally less than would 
single-family credit demand in response to higher rates.\13\ This in 
turn would make it easier to attain the goal levels if interest rates 
were to increase from current levels.
---------------------------------------------------------------------------

    \13\ This is suggested by recent experience of below-average 
multifamily mix in years where the volume of single-family 
refinancings has been high. Further support is provided by evidence 
of a relationship between interest rates and the multifamily share 
of the net change in residential mortgage debt between 1975 and 
2002.
---------------------------------------------------------------------------

    Regarding the market structure implications of increased GSE 
multifamily activity, HUD estimates that the GSEs purchased slightly 
less than one-third of the dollar volume of conventional multifamily 
loan originations during 2001-2003 (see Table D.2). There is room for 
increasing this market share without producing the duopsony alluded to 
in the previously cited comments. Furthermore, if the GSEs do increase 
their market penetration, it is because they are offering multifamily 
borrowers more attractive products or pricing than are their 
competitors, including the pension funds and FHA programs alluded to by 
some commenting organizations. The borrower and, ultimately, the rent-
paying affordable housing resident benefit from these more attractive 
products and pricing.
    In summary, the Department's determination is that the Housing Goal 
levels established by this rule are prudent and will improve the 
availability and pricing of credit for affordable multifamily 
properties. For the reasons stated above, it is the Department's view 
that the rule will not have the adverse consequences mentioned in some 
comments on the proposed rule.
g. Consequences of the Goals for the Single-Family Rental Market
    Summary of Comments. Several community organizations raised 
concerns about encouraging the single-family rental market. They 
asserted that the goals should target families who want to live in the 
financed houses, as opposed to the investors who purchase these homes. 
In these commenters' view, investors take affordable housing stock off 
the market, which raises the price for low and moderate-income first-
time homebuyers. They claimed that homeownership should be stressed 
because home equity is a large component of the disparity that exists 
in household net wealth between ethnic groups.
    Some commenters cited studies that suggest homeownership has 
beneficial neighborhood effects relative to investor-owned properties. 
According to one cited study, absentee landlords are much more likely 
to let housing stock decline but homeowners are much more likely to 
invest in the upkeep of their homes. In the view of one of these 
organizations, the incentives that the GSEs receive for rental housing 
should be to promote multifamily developments, not single-family homes.
    HUD's Determination. HUD considered many factors related to the 
single-family rental market. Single-family rentals are another source 
of affordable housing. Also, the capital provided by investors can help 
maintain demand for single-family homes in underserved neighborhoods. 
While some commenters complained that this raises the cost to first-
time homebuyers, investors also help to maintain the liquidity and 
value of owner-occupied homes. Further, there are some investors who 
make it their business to renovate the housing stock and resell the 
properties. On balance, HUD found no compelling evidence that single-
family rentals should be excluded from goals eligibility.
h. Consequences of the Goals for the Subprime Market
    Summary of Comments. Both GSEs indicated that they would need to 
increase their purchase of subprime loans to meet the higher goals. 
Freddie Mac stated that the increased affordable housing goals created 
tension in its business practices between meeting the goals and 
conducting responsible lending practices.
    In the past, Fannie Mae and Freddie Mac have voluntarily decided 
not to purchase subprime loans with features such as single-premium 
life insurance and prepayment penalty terms that exceed three years, or 
to purchase loans subject to the Home Ownership and Equity Protection 
Act (HOEPA). Freddie Mac indicated that the increased goals would limit 
its ability to influence subprime lending practices. More specifically, 
Freddie Mac claimed that, to meet the higher housing goals, it might 
not have the option in the future of turning away subprime loans that 
have less desirable loan terms than the subprime business it currently 
purchases.
    Several commenters suggested that if the GSEs are pushed to serve 
more of the subprime market, they will skim a significant portion of 
the lower-risk borrowers from that market. The resulting smaller 
subprime market would include the neediest borrowers. The commenters 
stated that these higher risk borrowers would pay more because lower 
risk borrowers would not be present to subsidize them, and the market's 
high fixed costs would be distributed across fewer borrowers.
    One industry group also suggested that a significantly smaller 
subprime market for private lenders would drive some lenders out of 
business and translate into less competition.
    While some industry commenters welcomed the entrance of the GSEs 
into the subprime market because their presence would bring stability 
and standardize business practices, the

[[Page 63601]]

commenters also expressed concern that unrealistically high goals could 
force the GSEs to jump into the market in a manner that negatively 
distorts underwriting and pricing. These commenters contended that the 
GSEs could bring capital and standards up, but that they must gradually 
and carefully enter the subprime market to have a positive effect. They 
strongly urged HUD to lower the goals to encourage the GSEs to expand 
their subprime activities at a measured pace.
    Some commenters suggested that bonus points, or other incentives 
for the GSEs' purchases of certain nonprime loans, could foster more 
deliberate and prudent purchases by the GSEs of subprime loans. One 
lender also suggested that incentives could be granted to the GSEs for 
other underserved market segments, such as manufactured homes, minority 
first time buyers, and nonprime first-time buyers.
    HUD's Determination. To date, the GSEs' involvement in the subprime 
market has benefited two types of borrowers: ``A'' risk and ``near A'' 
risk. The first group consists of borrowers with risk profiles similar 
to ``A'' borrowers, but receive mortgages from a subprime lender. The 
GSEs'' outreach and education efforts increase the likelihood that 
``A'' borrowers will use cheaper prime lenders for refinance mortgages, 
and reduce their reliance on subprime firms. The second group, 
borrowers who are near A credit risks, has growing access to mortgage 
products offered by the GSEs as these borrowers are increasingly served 
by GSE seller/servicers.
    The GSEs have been prudent in their pursuit of subprime lending, 
focusing on the top part of the market, the ``A-minus'' and ``Alt A'' 
segments. A-minus mortgages are typically those where borrowers have 
less than perfect credit. Alt A mortgages are originated to borrowers 
who cannot document all of the underwriting information in the 
application but generally have FICO scores similar to those in the 
prime market. The GSEs' subprime products are integrated into their 
automated underwriting systems and are approved based on mortgage 
scoring models. These models have proven over the years to be an 
effective tool in limiting risk layering. The GSEs charge lenders 
higher fees for guaranteeing these loans. As a result these higher risk 
loans are priced above those offered to prime borrowers but below what 
subprime lenders would otherwise charge for these loans.
    The GSEs' presence in the subprime mortgage market benefits many 
low-income and minority borrowers whose risk profiles differ markedly 
from borrowers who qualify for prime mortgage products. Millions of 
Americans with less than perfect credit or who cannot meet some of the 
tougher underwriting requirements of the prime market for reasons such 
as inadequate income documentation, limited downpayment or cash 
reserves, or the desire to take more cash out in a refinancing than 
conventional loans allow, rely on subprime lenders for access to 
mortgage financing. If the GSEs reach deeper into the subprime market, 
more borrowers will benefit from the advantages that greater stability 
and standardization create.
i. Consequences of the Goals for Mortgage Defaults; Neighborhood 
Impacts
    Summary of Comments. HUD received several comments concerning the 
impact of mortgage default rates on neighborhoods. Comments from 
mortgage insurance companies highlighted that the higher goals will 
likely lead to more expanded affordable housing products as well as 
higher foreclosures. Affordable products present challenges to 
borrowers and lenders. For borrowers, qualifying for an affordable 
mortgage does not insure they have a clear understanding of the risks 
of homeownership. Where aggressive affordable products are aimed at 
qualifying borrowers for home loans rather than qualifying families for 
homeownership, lenders need to be cautious of products that test the 
limits of borrowers' credit capabilities. Affordable products that have 
been introduced into the market under favorable economic conditions can 
experience increasing defaults and foreclosures during periods of 
higher interest rates, higher unemployment and/or lower house price 
appreciation rates. One commenter indicated that 15 percent or more of 
borrowers in some affordable housing products could experience default 
in an economic downturn.
    As defaults on affordable products rise, inner city neighborhoods 
can be especially hard hit. A large number of foreclosures in an area 
may lead to abandoned properties. While foreclosures devastate 
borrowers who lose their homes and damage borrowers' credit history, 
foreclosures also weaken the neighborhoods where the properties are 
located.
    The potential for affordable lending products to result in higher 
foreclosure during a less prosperous economic environment was echoed in 
Freddie Mac's comments. Its comment discussed how too many defaults in 
one neighborhood can lead to serious blight and disinvestment in the 
community. One commenter recommended that HUD establish safeguards 
against aggressive affordable products. The commenter suggested that 
HUD deny Housing Goal credit for GSE mortgage purchases that experience 
early-term serious defaults (e.g., delinquent 90 days or longer within 
12 months of the date of origination).
    The GSEs and community groups cautioned that the struggle to meet 
high goals for low-income groups could cause the GSEs to relax 
underwriting standards and/or extend loans to people who are 
unprepared. For example, the commenters pointed out that FHA default 
rates are higher than the conventional conforming market. High goals 
would encourage the GSEs to enter markets served by FHA. This incentive 
to extend credit to unprepared low-income people would rise if 
unexpected refinances decreased the proportion of goals-eligible units 
produced in the market.
    HUD's Determination. HUD carefully reviewed the comments regarding 
mortgage default rates. The Department believes that the GSEs' presence 
in underserved markets will be beneficial for neighborhoods. The GSEs 
have improved their underwriting methods to better identify risks in 
these markets, and also have instituted homebuyer education programs. 
An increased role for the GSEs' seller-services in inner-city 
neighborhoods will improve competition, reduce high-cost lending, and 
reduce predatory lending. As described in Appendix A, families living 
in inner-city, high-minority neighborhoods often have to rely on 
subprime lenders as their main source of mortgage credit. Studies 
indicate that many of these borrowers obtaining high-cost loans could 
qualify for lower-cost, prime mortgage credit. An active GSE effort in 
these neighborhoods will encourage traditional, mainstream lenders to 
increase their lending activities in these historically underserved 
areas. This will offer additional funding options for those lower-
income and minority borrowers who today may have to take out a high-
cost loan in order to purchase or renovate a home or to refinance an 
existing mortgage. Reductions in predatory lending reduce the costs of 
mortgages and the chances of default. As a result, the Department 
believes that GSE participation is a net benefit to lower income 
neighborhoods.

[[Page 63602]]

j. Consequences of the Goals for Residents of Puerto Rico
    Summary of Comments. Several associations stated that HUD's 
proposed affordable housing goals could be disadvantageous to residents 
of Puerto Rico, alleging that less than 10 percent of loans that are 
originated in the Puerto Rican market would qualify for the goals. 
These commenters were concerned that the GSEs might be unable to buy 
loans from Puerto Rico, and urged HUD to take special measures to 
ensure that owner and rental housing production are not deleteriously 
affected by the demographic and economic differences that exist between 
the mainland markets and the Puerto Rico market.
    HUD's Determination. Loans purchased by the GSEs for properties in 
Puerto Rico are counted in the same manner as loans purchased on 
properties in any other location. Since underserved areas are defined 
as low-income and/or high-minority census tracts in metropolitan areas 
or counties in non-metropolitan areas, the overwhelming majority of 
loans purchased by the GSEs on properties in Puerto Rico count toward 
that goal. In fact, in 2003, Fannie Mae reported that 95 percent of the 
units it financed in Puerto Rico qualified for the underserved areas 
goal; the corresponding figure for Freddie Mac was 98 percent.
    Relatively few of the loans in Puerto Rico that are purchased by 
the GSEs qualify for the two income-based goals. Despite this, HUD does 
not believe that the final housing goals will adversely affect Puerto 
Rico. In 2003, Puerto Rico accounted for only 0.2 percent of all units 
financed by Fannie Mae and only 0.1 percent of all units financed by 
Freddie Mac. Thus overall performance on these broad national goals is 
not materially affected by the characteristics of loans purchased by 
the GSEs in Puerto Rico.
    Apparently many lower-income families in Puerto Rico rely on 
consumer finance companies for financing their homes. Since such 
financing is typically more expensive to borrowers than traditional 
mortgages, this suggests that the GSEs could play an important role, 
working with mortgage originators, to better develop the mortgage 
market in Puerto Rico.
4. Determinations Regarding the Specification and Levels of the Home 
Purchase Subgoals
a. Overview
    Given that the past average performance of the GSEs in the home 
purchase market has been below market levels, and the Administration's 
emphasis on increasing homeownership opportunities, including those for 
low- and moderate-income and minority borrowers, HUD proposed to set 
Home Purchase Subgoals for GSE mortgage purchase activities to increase 
financing opportunities for low- and moderate-income, underserved, and 
special affordable borrowers who are purchasing single-family homes.
    Specifically, the Department proposed Home Purchase Subgoals for 
home purchase loans that qualify for the Housing Goals. The purpose of 
the Home Purchase Subgoals is to ensure that the GSEs focus on 
financing home purchases for the homeowners targeted by the Housing 
Goals. The Department believes that the establishment of Home Purchase 
Subgoals will place the GSEs in an important leadership position in the 
Housing Goals categories, while also facilitating homeownership. The 
GSEs have years of experience in providing secondary market financing 
for single-family properties and are fully capable of exerting such 
leadership.
    The focus of these Subgoals on home purchase loans meeting the 
Housing Goals will also help address the racial and income disparities 
in homeownership that exist today. As noted earlier, although minority 
homeownership has grown, the homeownership rate for African-American 
and Hispanic families is still approximately 25 percentage points below 
that for non-Hispanic white families. The focus of the Subgoals on home 
purchase will also increase the GSEs' support of first-time homebuyers, 
a market segment where they have lagged primary lenders.
    Summary of Comments. Fannie Mae claimed that the proposed Subgoals 
are not necessary and are, in fact, duplicative of the broader goals 
structure. Fannie Mae asserted that it is already a leader in financing 
home purchases, even in a period of aggressive refinancings. In 
addition, Fannie Mae stated that subgoals add complexity to the 
mortgage market and contribute to a loss of liquidity, and suggested 
that the proposed Subgoals do not reflect recent market experience 
because affordability may decline and HUD may mistreat missing data 
when formulating subgoals. Fannie Mae also stated that HUD improperly 
exercised its authority in proposing the Subgoals.
    Specifically, Fannie Mae contended that a complex subgoal structure 
harms liquidity and that when Fannie Mae needs to stretch in one market 
to meet a goal, it may have to reduce its willingness to purchase 
mortgages in another market. Fannie Mae stated that conflicts between 
the goals arise because the goals are set as a percentage of business, 
and fulfilling the numerator of one goal adds to the denominator of the 
other goals. Fannie Mae asserted that the GSEs could be forced to 
abstain from buying non-goal eligible mortgages that would count in the 
denominator, but that would not benefit its calculation of goals 
performance in the numerator. In Fannie Mae's view, its own abstention 
from buying implies an illiquid market.
    Other commenters affirmed Fannie Mae's comments and expressed 
concern that, given the market leadership of the GSEs, the manner in 
which home purchases are counted toward the Subgoals could distort the 
lending market.
    In addition, both Fannie Mae and Freddie Mac asserted that FHEFSSA 
requires that HUD consider each of the six statutory factors set forth 
in sections 1332(b) and 1334(b) of the statute in setting the levels of 
any Subgoals within those Housing Goals. Freddie Mac objected to the 
home purchase Subgoals because it claimed these Subgoals would 
constitute micromanagement of the GSEs' business decisions. Freddie Mac 
also noted that, in the past, HUD has declined to implement subgoals 
for that very reason.
    Several commenters expressed the view that HUD had overestimated 
available purchase money mortgages and noted that if Subgoals on these 
types of mortgages are set too high, adverse market distortions will 
occur.
    Other commenters contended that, regardless of the level of the 
Subgoals, a subgoal that targets home purchase mortgages unfairly 
allocates credit toward home buying rather than mortgage refinances. 
These commenters asserted that this credit allocation is unfair in that 
it penalizes borrowers who want to lower mortgage costs or improve 
their homes. They also contended that credit allocation that promotes 
purchase mortgages could push refinance borrowers into high-cost loans 
rather than conforming, GSE-eligible mortgages. To combat such effects, 
one organization suggested separate subgoals for both purchase money 
mortgages and refinances, with the overall low- and moderate-income 
goal as the weighted average of the different subgoals.
    Commenters also objected to mortgage purchase subgoals targeting 
only those loans originated in metropolitan areas because this 
geographic limitation allocates credit at the expense of residents of 
rural communities. The commenters stated that Congress

[[Page 63603]]

charged the GSEs in their charters to ``promote access to mortgage 
credit throughout the Nation (including central cities, rural areas, 
and underserved areas).'' One commenter stated that the lack of 
detailed HMDA data in rural areas makes market size estimates 
difficult, but suggested that other data from private vendors could 
provide acceptable measures (without offering any specific sources).
    HUD's Determination. Home purchase is a high national priority. The 
comments received and research reviewed document many studies revealing 
the desire of Americans to own their own home. HUD finds that the 
proposed home purchase subgoal furthers the statutory objectives of 
FHEFSSA. HUD set the level of the home purchase subgoal prudently. 
Details of HUD's methodology are found in Appendices A and D of this 
final rule and in chapter 3 of the Economic Analysis that accompanies 
the rule. Rather than distorting the market, the home purchase subgoal 
facilitates the desire of many Americans to use the market to acquire 
their own home.
    Several commenters asked HUD to extend the counting for the home 
purchase subgoal to rural areas even though data for rural areas is 
sparse. HUD disagrees. Although HMDA data for rural areas has improved, 
it is still too incomplete to support extending the counting system. 
Alternative sources from private lenders are similarly flawed. While 
HMDA's reporting of non-metropolitan areas has improved over the years, 
it continues to be unreliable. In 2001, 3,757 (3,280 of which were 
small banks) of the 4,394 non-metropolitan-area banks did not report 
under HMDA. In that same year, 324 (246 of which were small thrifts) of 
the 458 non-metropolitan-area thrift institutions did not report under 
HMDA.
    Except for Fannie Mae's recent performance in the Special 
Affordable and Low- and Moderate-Income categories, the GSEs have 
lagged the market in purchasing single-family, owner-occupied loans 
that qualify for the Housing Goals. In 2003, Fannie Mae continued to 
lag the market in financing properties located in underserved areas 
while Freddie Mac lagged the market in all three goals-qualifying 
categories. The Department's analysis reveals that there is ample room 
for both Fannie Mae and Freddie Mac to improve their performance in 
purchasing home loans that qualify for the Housing Goals, particularly 
in important market segments such as the minority, first-time homebuyer 
market.
    Both GSEs' funding of mortgages for first-time homebuyers lags the 
market's provision of funding for these families, and the lag is 
particularly large for first-time minority homebuyers. Table 2 compares 
the GSEs' funding of mortgages for first-time homebuyers with market 
loan originations for first-time homebuyers. This table shows that 
first-time homebuyers represented 37.6 percent of market loan 
originations, compared with 26.5 percent of the GSEs' purchases; thus, 
the GSEs fell substantially short of the market originations ratio for 
first-time homebuyers, over the period 1999-2001.
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    For minority first-time homebuyers, the GSE ratio was 6.2 percent, 
compared to a market originations ratio of 10.6 percent. For African-
American and Hispanic first-time homebuyers, the GSE ratio was 3.8 
percent, compared to a market originations ratio of 6.9 percent. For 
first-time homebuyers, particularly first-time minority homebuyers, 
both GSEs substantially lag the private conventional conforming market.
    As detailed in Appendix A to this rule, evidence suggests that 
there is a significant population of potential homebuyers who are 
likely to respond well to increased homeownership opportunities 
produced by increased GSE purchases in this area. Immigrants and 
minorities, in particular, are expected to be a major source of future 
homebuyers. Furthermore, studies indicate the existence of a large 
untapped pool of potential homeowners among the rental population. 
Indeed, the GSEs' recent experience with new outreach and affordable 
housing initiatives confirms the existence of this potential.
    The Department therefore is establishing through this rule Subgoals 
for home purchase loans that qualify for the three Housing Goals to 
encourage the GSEs to take a leadership position in creating 
homeownership financing opportunities within the categories that 
Congress expressly targeted with the Housing Goals.
b. HUD's Determinations Regarding the Home Purchase Subgoals
    Under FHEFSSA, HUD is authorized to establish nonenforceable 
Subgoals within the Low- and Moderate-Income Housing Goal and the 
Underserved Areas Housing Goal. HUD also is authorized under FHEFSSA to 
establish enforceable Subgoals within the Special Affordable Housing 
Goal. The Administration has proposed, as part of GSE regulatory 
reform, that Congress authorize HUD to establish a separate Home 
Purchase Goal that would include enforceable components. Pending the 
enactment of any such legislation, HUD is establishing the Home 
Purchase Subgoals described in this final rule under its current 
statutory authority.
    HUD stated in the preamble to the proposed rule that in setting a 
subgoal, ``[c]urrent law does not require that HUD consider the 
statutory factors set forth in FHEFSSA prior to establishing or setting 
the level of Subgoals.'' (69 FR 24244.) HUD's interpretation of this 
portion of FHEFSSA is unchanged. Each of the subsections identifying 
the factors for consideration indicates that the factors are to be 
considered in setting each respective goal; no mention is made of the 
subgoals. However, despite the absence of any statutory requirement to 
consider the listed factors in setting the levels of the subgoals, HUD 
has nevertheless carefully considered each of these factors in setting 
the subgoal levels in this final rule.
    The following sections provide an overview of HUD's reasons for 
establishing the Subgoals, which are detailed in the Appendices to this 
rule.
(i) The GSEs Have the Ability To Lead the Market
    The GSEs have the ability to lead the primary market for mortgages 
on single-family owner-occupied properties, which are the GSEs' 
principal line of business. Both GSEs have long experience in the home 
purchase mortgage market, and therefore there is no issue of the degree 
to which they have penetrated this market. In addition, because the 
Subgoals focus on homeownership opportunities and, thus, do not include 
refinance loans, there is no issue regarding potentially large year-to-
year changes in refinance mortgage volumes, which affect the magnitude 
of the denominator in calculating performance percentages under the 
Housing Goals, as experienced in the heavy refinance years of 1998 and 
2001-2003.
    Both GSEs have not only been operating in the single-family owner 
mortgage market for years, they have been the dominant players in that 
market, funding 57 percent of mortgages on single-family owner-occupied 
residences financed between 1999 and 2002. As discussed in Section G of 
Appendix A to this rule, their underwriting guidelines are industry 
standards and their AUS are widely used in the mortgage industry.
(ii) The GSEs' Performance Relative to the Market
    Even though the GSEs have had the ability to lead the home purchase 
market, their past average performance (1993-2003, 1996-2003, and 1999-
2003) has been below market levels. During 2002 and 2003, Fannie Mae 
improved its performance enough to lead the special affordable and low-
mod markets for home purchase loans, but Fannie Mae continued to lag 
the primary market in funding homes in underserved areas. The subgoals 
will ensure that Fannie Mae maintains and further improves its above-
market performance in the special affordable and low-mod markets, and 
also becomes a market leader in funding underserved areas. Freddie Mac, 
although it has also improved its recent performance, continues to lag 
behind the primary market on all housing goal categories. The subgoals 
will ensure that Freddie Mac erases its gaps with the market and takes 
a leadership position as well. The type of improvement needed for 
Freddie Mac to meet these new subgoals was demonstrated by Fannie Mae 
during 2001-2003. For example, Fannie Mae increased its low-mod 
purchases from 40.8 percent of its single-family-owner business in 2000 
to 45.3 percent in 2002 to 47.0 percent in 2003.
(iii) Disparities in Homeownership and Credit Access Remain
    HUD notes that there remain troublesome disparities in our housing 
and mortgage markets, even after the ``revolution in affordable 
lending'' and the growth in homeownership that has taken place since 
the mid-1990s. As noted previously in the discussion of the goals, the 
homeownership rate for African-American and Hispanic households remains 
25 percentage points below that of white households. In 2002, the 
mortgage denial rate for African-American borrowers was over twice that 
for white borrowers, even after controlling for the income of the 
borrower.
    HUD also notes that there is growing evidence that inner city 
neighborhoods are not always being adequately served by mainstream 
lenders. Some have concluded that a dual mortgage market has developed 
in our nation, with conventional mainstream lenders serving mainly 
white families living in the suburbs and FHA and subprime lenders 
serving minority families concentrated in inner city neighborhoods. In 
addition to the unavailability of mainstream lenders, families living 
in high-minority neighborhoods generally face many additional hurdles, 
such as lack of cash for a downpayment, credit problems, and 
discrimination.
    Immigrants and minorities are projected to account for almost two-
thirds of the growth in the number of new households over the next ten 
years. As emphasized throughout this preamble and the Appendices to 
this rule, changing population demographics will result in a need for 
the primary and secondary mortgage markets to meet nontraditional 
credit needs, respond to diverse housing preferences and overcome 
information and other barriers that many immigrants and minorities 
face. HUD finds that the GSEs must increase their efforts towards 
providing financing for these families.

[[Page 63606]]

(iv) There Are Ample Opportunities for the GSEs To Improve Their 
Performance in the Home Purchase Market
    Home purchase loans that qualify for the Housing Goals are 
available for the GSEs to purchase, which means they can improve their 
performance and lead the primary market in purchasing loans for lower-
income borrowers and properties in underserved areas. Three indicators 
of this have already been discussed.
    First, the affordable lending market has shown an underlying 
strength over the past few years that is unlikely to vanish (without a 
significant increase in interest rates or a decline in the economy). 
Since 1999, the shares of the home purchase market accounted for by the 
three Housing Goal categories are as follows: 16.3 percent for special 
affordable, 31.4 percent for underserved areas, and 44.1 percent for 
low- and moderate-income.
    Second, market share data reported in section G of Appendix A to 
this rule show that almost half of newly-originated loans that qualify 
for the Housing Goals are not purchased by the GSEs. As noted above, 
the situation is even more extreme for special sub-markets, such as the 
minority first-time homebuyer market where the GSEs have only a minimal 
presence. In terms of the overall mortgage market (both conventional 
and government), the GSEs funded only 24 percent of all first-time 
homebuyers and 17 percent of minority first-time homebuyers between 
1999 and 2001. Similarly, during the same period, the GSEs funded only 
40 percent of first-time homebuyers in the conventional conforming 
market, and only 33 percent of minority first-time homebuyers in that 
market.
    Finally, the GSEs' purchases that can count toward the Subgoal are 
not limited to new mortgages that are originated in the current 
calendar year. The GSEs can purchase loans from the substantial, 
existing stock of affordable loans held in lenders' portfolios, after 
these loans have seasoned and the GSEs have had the opportunity to 
observe their payment performance. In fact, based on Fannie Mae's 
recent experience, the purchase of seasoned loans is at present one 
strategy employed for purchasing Housing Goals-qualifying loans and 
meeting the goals.
    The current low homeownership rate of minorities and others living 
in inner cities suggests that there will be considerable growth in the 
origination of CRA loans in urban areas. For banks and thrifts, selling 
their CRA originations will free up capital to make new CRA loans. As a 
result, the CRA market segment provides an opportunity for the GSEs to 
expand their affordable lending programs. As explained in Appendix A to 
this rule, Fannie Mae and Freddie Mac have already started developing 
programs to purchase CRA-type loans on a flow basis as well as after 
they have seasoned.
    While the GSEs can choose any strategy for leading the market, this 
leadership role can likely be accomplished by building on the many 
initiatives and programs that the enterprises have already started, 
including: (1) Their outreach to underserved markets and their 
partnership efforts that encourage mainstream lenders to move into 
these markets; (2) their incorporation of greater flexibility into 
their purchase and underwriting guidelines, (3) their development of 
new products for borrowers with little cash for a downpayment and for 
borrowers with credit blemishes or non-traditional credit histories; 
(4) their targeting of important markets where they have had only a 
limited presence in the past, such as the markets for minority first-
time homebuyers; (5) their purchases of both newly-originated and 
seasoned CRA loans; and (6) their use of automated underwriting 
technology to qualify creditworthy borrowers that would have been 
deemed not creditworthy under traditional underwriting rules.
    The experience of Fannie Mae and Freddie Mac in the subprime market 
indicates that they have the expertise and experience to develop 
technologies and new products that allow them to enter new markets in a 
prudent manner. Given the innovativeness of Fannie Mae and Freddie Mac, 
other strategies will be available as well. In fact, a wide variety of 
quantitative and qualitative indicators suggest that the GSEs have the 
expertise, resources and financial strength to improve their affordable 
lending performance enough to lead the home purchase market for special 
affordable, low- and moderate-income, and underserved areas loans. The 
recent improvement in the affordable lending performance of the GSEs, 
and particularly Fannie Mae, further demonstrates the GSEs' capacity to 
lead the home purchase market.
c. Structure and Levels of the Home Purchase Subgoals
    Under this rule, performance on the Home Purchase Subgoals will be 
calculated as Housing Goal-qualifying percentages of the GSEs' total 
purchases of mortgages that finance purchases of single-family, owner-
occupied properties located in metropolitan areas, based on the owner's 
income and the location of the property. Specifically, for each GSE the 
following Subgoals would apply. (A ``home purchase mortgage'' is 
defined as a residential mortgage for the purchase of an owner-occupied 
single-family property.)
     45 percent of home purchase mortgages purchased by the GSE 
in metropolitan areas must qualify under the Low- and Moderate-Income 
Housing Goal in 2005, with this share rising to 46 percent in 2006 and 
47 percent in both 2007 and 2008;
     32 percent of home purchase mortgages purchased by the GSE 
in metropolitan areas must qualify under the Underserved Areas Housing 
Goal in 2005, with this share rising to 33 percent in both 2006 and 
2007 and 34 percent in 2008; and
     17 percent of home purchase mortgages purchased by the GSE 
in metropolitan areas must qualify under the Special Affordable Housing 
Goal in both 2005 and 2006, with this share rising to 18 percent in 
both 2007 and 2008.
    Calculation of performance under the Home Purchase Subgoals will be 
in terms of numbers of mortgages, not numbers of units. This is 
consistent with the basis of reporting in HMDA data, which were HUD's 
point of reference in establishing the Home Purchase Subgoal levels. 
HMDA data are reported in terms of numbers of mortgages in metropolitan 
areas.
    These Home Purchase Subgoals are shown in Table 3, along with 
information on what the GSEs' performance on the Subgoals would have 
been if they had been in effect for 1999-2003 (under the proposed 
counting rules for 2005-2008). Table 3 also presents HUD's estimates of 
the average shares of mortgages on owner-occupied single-family 
properties in metropolitan areas that were originated in 1999-2003 that 
would have qualified for these Home Purchase Subgoals.
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d. Counting Mortgages Toward the Home Purchase Subgoals
    The Department is amending 24 CFR 81.15 to add a new paragraph (i) 
that would clarify that the procedures in Sec.  81.15 generally govern 
the counting of home purchase mortgages toward the Home Purchase 
Subgoals in Sec. Sec.  81.12, 81.13 and 81.14. The new paragraph 
provides, however, that the numerator and denominator for purposes of 
counting performance under the Subgoals are comprised of numbers of 
home purchase mortgages in metropolitan areas, rather than numbers of 
dwelling units. Paragraph (i) also provides that, for purposes of 
addressing missing data or information for each Subgoal, the procedures 
in Sec.  81.15(d) shall be implemented using numbers of home purchase 
mortgages in metropolitan areas and not single-family, owner-occupied 
dwelling units. Finally, the new paragraph provides that where a single 
home purchase mortgage finances the purchase of two or more owner-
occupied units, the mortgage shall count once toward each Subgoal that 
applies to the GSE's mortgage purchase.
5. Low- and Moderate-Income Housing Goal, Sec.  81.12
    This section discusses the Department's consideration of the 
statutory factors in arriving at, and the comments received on, the new 
housing goal level for the Low- and Moderate-Income Housing Goal, which 
targets mortgages on housing for families with incomes at or below the 
area median income. After consideration of these factors, this final 
rule establishes the goal for the percentage of dwelling units to be 
financed by each GSE's mortgage purchases at 52 percent for 2005, 53 
percent for 2006, 55 percent for 2007, and 56 percent for 2008.
    Additional information analyzing each of the statutory factors is 
provided in Appendix A, ``Departmental Considerations to Establish the 
Low- and Moderate-Income Housing Goal,'' and Appendix D, ``Estimating 
the Size of the Conventional Conforming Market for each Housing Goal.''
a. Market Estimate for the Low- and Moderate-Income Housing Goal
    The Department estimates that dwelling units serving low- and 
moderate-income families will account for 51-56 percent of total units 
financed in the overall conventional conforming mortgage market during 
the period 2005 through 2008. HUD has developed this range, rather than 
a specific point estimate, to account for the projected effects of 
different economic and affordability conditions that can reasonably be 
anticipated. HUD estimates that the low-and-moderate-income share of 
the market averaged 57 percent between 1999 and 2002.
b. Past Performance of the GSEs Under the Low- and Moderate-Income 
Housing Goal
    A number of changes in goal-counting procedures were adopted as 
part of HUD's Housing Goals final rule published on October 31, 2000 
(65 FR 65044) (Housing Goals 2000 final rule). Thus, it is necessary to 
provide information using several different measures in order to track 
performance on the Low- and Moderate-Income Housing Goal over the 1996-
2003 period. Table 4 shows performance under these measures.\14\
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    \14\ The Freddie Mac 2002 figures in Table 4 differ from the 
corresponding figures in Table 3 in HUD's Proposed Rule. Subsequent 
to publication of the Proposed Rule, HUD discovered that HUD had 
credited some units toward Freddie Mac's Low- and Moderate-Income 
Housing Goal in 2002 that had been previously counted toward the 
goal in 2001. The units were associated with a large year-end 
Freddie Mac mortgage purchase transaction in 2002. Because HUD's 
regulations prohibit double counting, HUD has recalculated Freddie 
Mac's 2002 Low- and Moderate-Income Housing Goal performance. The 
recalculation also reflects correction of some coding errors 
discovered in HUD's recent review.

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[[Page 63610]]

    Specifically, the following changes were made in counting 
procedures for measuring performance on the Low- and Moderate-Income 
Housing Goal for 2001-2003. HUD:
    (1) Established ``bonus points'' (awarding double credit) for 
purchases of low- and moderate-income mortgages on small (5-50 unit) 
multifamily properties and, above a threshold level, mortgages on two-
to-four unit owner-occupied properties;
    (2) Established a ``temporary adjustment factor'' (1.35 units 
credit, as revised by Congress for 2001-2003 from HUD's 1.2 unit 
credits in the Housing Goals 2000 final rule) that applied to Freddie 
Mac's purchases (but not Fannie Mae's purchases) of low- and moderate-
income mortgages on large (more than 50-unit) multifamily properties; 
and
    (3) Revised procedures that HUD had instituted regarding the 
treatment of missing data on unit affordability, the use of imputed or 
proxy rents for determining goal credit for multifamily mortgages, and 
the eligibility for goals credit for certain qualifying government-
backed loans.
    Based on the counting rules in effect at that time for 1996-2000, 
as shown under ``official performance'' for 1996-2000 in Table 4, Low- 
and Moderate-Income Housing Goal performance for Fannie Mae was 
consistently in the 44-46 percent range over the 1996-1999 period, 
before jumping to a peak of 49.5 percent in 2000. Freddie Mac's 
performance started at a lower level, but then increased in several 
steps, from 41-43 percent in 1996-1998 to 46.1 percent in 1999, and a 
record level of 49.9 percent in 2000. That was the only year prior to 
2001 in which Freddie Mac's performance exceeded Fannie Mae's 
performance on this goal.
    Based on the then current counting rules, including the bonus 
points and TAF, as shown under ``official performance'' in Table 4, 
Low- and Moderate-Income Housing Goal performance was 51.5 percent for 
Fannie Mae in 2001, 51.8 percent in 2002, and 52.3 percent in 2003. For 
Freddie Mac, performance was 53.2 percent in 2001, 50.5 percent in 
2002, and 51.2 percent in 2003.
    Immediately beneath the official Low- and Moderate-Income Housing 
Goal performance percentages in Table 4 are figures showing the GSEs' 
low- and moderate-income purchase percentages on a consistent basis for 
the entire 1996-2003 period. The assumptions used were the counting 
rules established in HUD's Housing Goals 2000 final rule except that 
bonus points and the Freddie Mac TAF (which were terminated at the end 
of 2003) are not applied. These figures are termed the ``2001-2003 
baseline assumptions.'' For 1996-2000 these figures differ from the 
official performance figures because they incorporate the revised 
counting procedures described under point (c), above, which were not 
reflected in the official performance figures at that time. For 2001-
2003 both sets of figures incorporate the revised counting procedures, 
but the baseline does not incorporate the bonus points and the Freddie 
Mac TAF.
    In terms of the 2001-2003 baseline measure, both Fannie Mae's and 
Freddie Mac's low- and moderate-income performance reached its maximum 
in 2000 (Fannie Mae at 51.3 percent and Freddie Mac at 50.6 percent). 
Baseline performance fell somewhat for both GSEs in 2001, 2002, and 
2003. Fannie Mae's baseline performance last year exceeded the level 
attained in 1999, but Freddie Mac's performance fell to the lowest 
level since 1998.
    Overall, both GSEs' performance exceeded HUD's Low- and Moderate-
Income Housing Goals by significant margins in 1996-1999, and by wide 
margins in 2000. New, higher goals were established for 2001-2003, and 
despite somewhat lower performance than the level attained in 2000, 
both GSEs' official performance exceeded the new goal levels in each 
year 2001-2003, with the inclusion of the bonus points and the TAF.
    The decline in baseline performance in 2001-2003 can be attributed 
in large measure to the mortgage refinance wave that occurred in those 
years. Fannie Mae's overall volume of mortgage purchases (in terms of 
numbers of housing units) rose from 2.2 million in 2000 to 4.7 million 
in 2001, 6.4 million in 2002, and then to 10.1 million in 2003. 
Similarly, Freddie Mac's volume rose from 1.6 million in 2000 to 3.3 
million in 2001, 4.3 million in 2002, and then to 5.8 million in 2003. 
For each GSE the increase in volume each year can be largely attributed 
to increases in purchase volumes for refinance mortgages relative to 
home purchase mortgages. For each GSE, the fraction of mortgages that 
qualified as Low- and Moderate-Income was less for refinance mortgages 
than for home purchase mortgages.
    For 2005-2008, HUD is expanding the affordability estimation of 
units with missing affordability information. In addition to 
multifamily units, the GSEs will also be able to use estimates of 
affordability for single-family rental units with missing rents and 
owner-occupied units with missing borrower incomes for determining goal 
credit. HUD is also increasing the amount of the maximum allowed for 
affordability estimation for multifamily units.
    Beneath the 2001-2003 baseline figures in Table 4 is another row of 
figures designated ``With 2005 Assumptions.'' These figures show the 
effects of applying 2000 Census data and the new specification of MSAs 
released by OMB in 2003 to the measurement of Low- and Moderate-Income 
purchase percentages with the same counting rules that were used for 
the 2001-2003 baseline in Table 4. The effect is to reduce the Goal-
qualifying percentage by an average of 0.6 percentage points for Fannie 
Mae and 0.7 percentage points for Freddie Mac, over the 1999-2002 
period.
    However, for 2003, the effects are just the opposite--these 
assumptions increased Fannie Mae's performance by 0.8 percentage point 
(from 48.7 percent to 49.5 percent) and Freddie Mac's performance by 
0.3 percentage point (from 45.0 percent to 45.3 percent). The 
difference in the direction of this impact between 1999-2002 and 2003 
may be due to the need to apply estimation techniques in 1999-2002 but 
not in 2003. For 1999-2002 HUD had to estimate the effect based on data 
geocoded according to 1990 census tract definitions, while for 2003 the 
data were geocoded to 2000 census tracts. Further insight will be 
provided by analysis of data for 2004 and further years.
c. Low- and Moderate-Income Home Purchase Subgoal
    The Department has determined to establish a Subgoal of 45 percent 
for each GSE's purchases of home purchase mortgages on single-family 
owner-occupied properties in metropolitan areas which are for low- and 
moderate-income families in 2005, with this Subgoal rising to 46 
percent in 2006 and 47 percent in both 2007 and 2008.
    The purpose of this Subgoal is to encourage the GSEs to increase 
their acquisitions of home purchase loans for low- and moderate-income 
families, many of whom are expected to enter the homeownership market 
over the next few years. Table 5 provides basic information on both the 
GSEs' low-mod performance and the primary market's low-mod performance 
for the years 1999 to 2003. Since the same format will be followed for 
the other housing subgoals, several points are made about the 
information in the Table 5, prior to discussing the low-mod subgoal.
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    Average Performance Data. In addition to individual year data, 
various averages of annual performance are provided at the bottom of 
Table 5 (1999-2003, 2001-2003, and 2002-2003); these averages provide a 
useful context for examining the feasibility of the subgoals and the 
degree to which they call for performance that is above past market 
levels. This table provides a picture of how much the low-mod subgoal 
targets move the GSEs above past market levels and how much of a 
stretch each subgoal will be for each GSE (as compared with that GSE's 
past performance). As will become clear below, Fannie Mae and Freddie 
Mac have shown different past performances, which means that the 
subgoal targets will appear to have different impacts on these two 
institutions.
    Definitions of Primary Market. HUD's basic market definition is the 
conventional conforming market without B&C loans; in other words, the 
A-minus loans in the subprime market are included in the market 
definition but the more risky B&C portion is not included (see Appendix 
D of the final rule for further discussion of this). In its report for 
Freddie Mac, ICF indicated that small loans (those less than $15,000) 
should be excluded from any analysis that dealt with loans that might 
be available for purchase by the GSEs. Therefore, data are provided in 
Table 5 for (a) the market without B&C loans and (b) the market without 
both B&C and small loans less than $15,000. As shown in Table 5, 
dropping small loans reduces the low-mod share of the conventional 
conforming market by about one-half percentage point.
    Projected 2000-Based Data. Table 5 is based on projected data that 
incorporates both 2000 Census geography and the new OMB definitions. 
Thus, the goals-qualifying percentages in this table differ from those 
reported earlier in this Preamble, the latter being historical, 1990-
Census-based percentages. HUD had to reapportion the data for the years 
prior to 2003. For 2003, both HMDA and GSE data were defined in terms 
of 2000 Census geography, so no reapportionment was necessary; for this 
reason, the 2003 data are probably the most accurate. With these 
basics, the results for the low-mod subgoal can now be briefly 
summarized as follows:
    Low-Mod Subgoals Compared With Market. The 45-percent subgoal for 
the first year (2005) is approximately two percentage points above 
1999-2003 and 2001-2003 average market performance, one percentage 
point above 2002-2003 average market performance, and 0.6 percent 
(market without B&C loans) to 0.2 percent (market without both B&C and 
small loans) below peak market performance. The 46-percent subgoal for 
2006 would add one percentage point to these comparisons, while the 47-
percent subgoal for 2007 and 2008 would add two percentage points. For 
example, the 47-percent subgoal is approximately three percentage 
points above 2002-2003 average market performance, and 1.4 percent 
(market without B&C loans) to 1.8 percent (market without both B&C and 
small loans) above peak market performance.

    Low-Mod Subgoals Compared With Past Freddie Mac Performance. To 
reach the 45-percent 2005 subgoal, Freddie Mac would have to improve 
its performance by 3.0 percentage points over its 2001-2003 average 
low-mod performance of 42.0 percent, by 1.8 percentage points over 
its 2002-2003 average low-mod performance of 43.2 percent, and by 
0.8 percent over its previous peak performance of 44.2 percent in 
2003. To reach the 47-percent subgoal, Freddie Mac would have to 
improve its performance by 3.8 percentage points over its 2002-2003 
average low-mod performance, and by 2.8 percent over its previous 
peak performance.
    Low-Mod Subgoals Compared With Past Fannie Mae Performance. To 
reach the 45-percent 2005 subgoal, Fannie Mae would have to improve 
its performance by 0.7 percentage points over its 2001-2003 average 
low-mod performance of 44.3 percent; Fannie Mae would meet the 45-
percent subgoal based on its 2002-2003 average low-mod performance 
of 45.6 percent and its previous peak low-mod performance of 47.5 
percent in 2003. To reach the 47-percent subgoal, Fannie Mae would 
have to improve its performance by 2.7 percent over its 2001-2003 
average performance and by 1.4 percentage points over its 2002-2003 
average performance; Fannie Mae would meet the 47-percent subgoal 
based on its previous peak performance of 47.5 percent in 2003.

    The low-mod subgoal targets will be more challenging for Freddie 
Mac than Fannie Mae. The type of improvement needed to meet the new 
low-mod subgoal targets was demonstrated by Fannie Mae during 2001-
2003, as Fannie Mae increased its low-mod purchases from 40.1 percent 
of its single-family-owner business in 2000 to 43.6 percent in 2002 to 
47.5 percent in 2003, as shown in Table 5. The approach taken is for 
the GSEs to obtain their leadership position by staged increases in the 
subgoals; this will enable the GSEs to take new initiatives in a 
correspondingly staged manner to achieve the new subgoals each year. 
Thus, the increases in the housing subgoals are sequenced so that the 
GSEs can gain experience as they improve and move toward the new higher 
subgoal targets.
    Section 4.b. above of this preamble, and Section I.3 of Appendix A 
to this rule, discuss the reasons why the Department is establishing 
the Subgoal for low- and moderate-income loans, as follows: (1) The 
GSEs have the resources and the ability to lead the market in providing 
mortgage funding for low- and moderate-income families; (2) except for 
Fannie Mae's recent performance, the GSEs have historically (over 
periods such as 1993-2003, 1996-2003, and 1999-2003) not led the 
market, even though they have had the ability to do so; (3) troublesome 
disparities in our housing and mortgage markets indicate a continuing 
need for increased GSE activity; and (4) there are ample opportunities 
for the GSEs to improve their low- and moderate-income performance in 
the home purchase market.
    Although single-family owner-occupied mortgages comprise their 
principal line of business, Freddie Mac has always lagged behind the 
primary market in financing mortgages for low- and moderate-income 
families. Over the past three years Fannie Mae has closed its 
historical gap with the market and now leads the primary market in 
funding mortgages for low- and moderate-income families. Because home 
purchase loans account for a major share of the GSEs' purchases, the 
establishment of this Subgoal will aid their performance under the 
overall Low- and Moderate-Income Housing Goal.
    For the foregoing reasons, the Department believes that the GSEs, 
and particularly Freddie Mac, can do more to raise the share of their 
home loan purchases serving low- and moderate-income families. This can 
be accomplished by building on efforts that the enterprises have 
already started, including their new affordable lending products, their 
many partnership efforts, their outreach to inner city neighborhoods, 
their incorporation of greater flexibility into their underwriting 
guidelines, and their purchases of seasoned CRA loans. A wide variety 
of quantitative and qualitative indicators indicate that the GSEs have 
the resources and financial strength to improve their affordable 
lending performance enough to lead the market serving low- and 
moderate-income families.
d. Summary of Comments
    The majority of comments that addressed the housing goals focused 
on the highest goal in year 2008 for the Low- and Moderate-Income 
Housing Goal. While some commenters, such as affordable housing policy 
advocacy groups and housing and consumer coalitions, expressed support 
for more

[[Page 63613]]

aggressive goals, stating that the goals should be set to challenge the 
GSEs to do more, most commenters expressed concerns about possible 
adverse affects on middle-income borrowers, including the potential for 
higher costs and for unrealistic goals to lead to credit allocation to 
the lower end of the housing market, thereby hindering the GSEs' 
ability to serve all homebuyers. Other concerns included issues related 
to HUD's market share methodology analysis and the effects of single-
family refinance loans in high refinance years on the GSEs' ability to 
meet the higher goals. Many commenters recommended that HUD exempt 
refinances from the goals performance calculation. As described earlier 
in this rule, HUD is seeking public comments on how to address the 
effects of refinance loans when this annual volume is high. In 
addition, some expressed the belief that overly aggressive goals could 
weaken the FHA insurance program and could encourage over-investment in 
rental housing at a time when multifamily vacancy rates are high. HUD 
has addressed these concerns in earlier sections of this final rule 
preamble. Others felt that higher goal levels will encourage more 
investor-owned rental units that harm communities. Both Fannie Mae and 
Freddie Mac objected to the higher goal level for the Low- and 
Moderate-Income Goal. Each disputed HUD's market share analysis, citing 
the uncertainty of data, for example the size of the multifamily 
market, and the uncertainty about future economic conditions. Freddie 
Mac stated that HUD overestimated the low/mod market share by 4 
percent. Both GSEs also stated that it was inappropriate to base the 
goals at the high end of market share ranges. Freddie Mac stated that 
this approach ignores the year-to-year variability of the market. 
Appendix D to this rule responds to these market issues raised by the 
GSEs.
    With regard to the Low- and Moderate-Income Home Purchase Subgoal, 
most commenters did not address the subgoal levels proposed by HUD, and 
none specifically addressed the proposal levels for the Low- and 
Moderate-Income Subgoal. For those that did mention the subgoals, the 
comments were mixed with about half supportive of the subgoal proposals 
in general and half believing the subgoal levels were too high. Both 
GSEs commented on HUD's proposed subgoals. Fannie Mae stated that the 
levels were higher than any values observed in HMDA from 1999-2002, and 
that the concept was duplicative of the overall goal structure. Freddie 
Mac stated that HUD should withdraw the home purchase subgoals or HUD 
should re-estimate the market using reasonable assumptions and set both 
the goal and subgoal levels no higher than the midpoint of the 
resulting ranges.
e. HUD's Determination
    The Low- and Moderate-Income Housing Goal established in this final 
rule is reasonable and appropriate having considered the factors set 
forth in FHEFSSA. For 2001-2003, HUD set the level of the housing goal 
conservatively, relative to the Department's market share estimates, in 
order to accommodate a variety of economic scenarios. Moreover, current 
examination of the gaps in the mortgage markets, along with the 
estimated size of the market available to the GSEs, demonstrate that 
the number of mortgages secured by housing for low- and moderate-income 
families is more than sufficient for the GSEs to achieve the new goal.
    Therefore, having considered all the statutory factors including 
housing needs, projected economic and demographic conditions for 2005 
to 2008, the GSEs' past performance, the size of the market serving 
low- and moderate-income families, and the GSEs' ability to lead the 
market while maintaining a sound financial condition, HUD has 
determined that the annual goal for mortgage purchases qualifying under 
the Low- and Moderate-Income Housing Goal will be 52 percent for 2005, 
53 percent in 2006, 55 percent in 2007, and 56 percent in 2008. This 
reflects a reduction in the upper end of the market share range from 57 
percent to 56 percent since HUD's publication of its proposed rule, 
resulting from changes in estimating market share as described at the 
end of section 3 (a), above, and in section F of Appendix D to this 
rule.
    Further, the Department is establishing a Subgoal for each GSE's 
purchases of home purchase mortgages on single-family owner-occupied 
properties in metropolitan areas which are for low- and moderate-income 
families of 45 percent in 2005, with this Subgoal rising to 46 percent 
in 2006, and 47 percent in both 2007 and 2008. The reasons for 
increasing the Low- and Moderate-Income Housing Goal are discussed in 
sections a and b, above, and the reasons for establishing a Home 
Purchase Subgoal at the stated levels are set forth in section c.
    While the GSEs have lagged the primary market in financing owner 
and rental housing for low- and moderate-income families, they appear 
to have ample room to improve their performance in that market. A wide 
variety of quantitative and qualitative indicators demonstrate that the 
GSEs have the expertise, resources and financial strength to improve 
their low- and moderate-income lending performance, including lending 
for low- and moderate-income home purchases, and achieve the levels of 
the goals being established.
6. Central Cities, Rural Areas, and Other Underserved Areas Housing 
Goal, Sec.  81.13
    This section discusses the Department's consideration of the 
statutory factors in arriving at, and the comments received on, the new 
housing goal levels for the Central Cities, Rural Areas, and Other 
Underserved Areas Goal, which focuses on areas currently underserved by 
the mortgage finance system. After consideration of the factors and the 
comments received, this final rule establishes the goal for the 
percentage of dwelling units to be financed by each GSE's mortgage 
purchases at 37 percent in 2005, 38 percent in 2006 and 2007, and 39 
percent in 2008.
    The 1995 final rule provided that mortgage purchases count toward 
the Underserved Areas Housing Goal if such purchases finance properties 
that are located in underserved census tracts. At 24 CFR 81.2 of HUD's 
current regulations, HUD defines ``underserved areas'' for metropolitan 
areas (in central cities and other underserved areas) as census tracts 
where either: (1) The tract median income is at or below 90 percent of 
the area median income (AMI); or (2) the minority population is at 
least 30 percent and the tract median income is at or below 120 percent 
of AMI. The AMI ratio is calculated by dividing the tract median income 
by the MSA median income. The minority percentage of a tract's 
population is calculated by dividing the tract's minority population by 
its total population. For properties in non-metropolitan (rural) areas, 
mortgage purchases have counted toward the Underserved Areas Housing 
Goal where such purchases finance properties that are located in 
underserved counties. As discussed above under the heading 
``Definitions'' in this final rule, HUD is changing this specification 
from the county level to the census tract level. Mortgages will count 
toward the Underserved Areas Housing Goal where such purchases finance 
properties that are located in census tracts were either (1) the median 
income in the tract does not exceed 95 percent of the greater of the 
median incomes for the non-metropolitan portions of the state or the

[[Page 63614]]

non-metropolitan portions of the nation as a whole, or (2) minorities 
comprise at least 30 percent of the residents of the tract and the 
median income in the tract does not exceed 120 percent of the greater 
of the median incomes for the non-metropolitan portions of the state or 
the non-metropolitan portions of the nation as a whole.
    The level for the Underserved Areas Housing Goal is based on 2000 
Census data on area median incomes and minority percentages for census 
tracts, MSAs, and the non-metropolitan portions of states and of the 
entire nation. HUD's analysis, which is set forth below and described 
in greater detail in Appendix B to this rule, is based on 2000 census 
data. The effect of using 2000 census data rather than 1990 data to 
determine whether areas are underserved increases the percentage of the 
GSEs' mortgage purchases in underserved areas by an estimated average 
of 5 percentage points for Fannie Mae and 4 percentage points for 
Freddie Mac, based on the geographic locations of properties financed 
by the GSEs' mortgage purchases in 1999 through 2003. This change 
reflects geographical shifts in population concentrations by income and 
minority status from 1990 to 2000.
    After analyzing the statutory factors, HUD is: (a) establishing a 
Goal of 37 percent for the percentage of the total number of dwelling 
units financed by each GSE's mortgage purchases for properties located 
in underserved areas for 2005, 38 percent for 2006 and 2007, and 39 
percent for 2008; (b) establishing census tracts as the spatial basis 
for establishing whether properties in non-metropolitan (rural) areas 
count toward the Underserved Areas Housing Goal, in place of counties 
as in the definition stated above, for the reasons described below; and 
(c) also establishing a Subgoal of 32 percent of the total number of 
dwelling units financed by each GSE's purchases of home purchase 
mortgages in metropolitan areas for properties located in underserved 
areas of metropolitan areas for 2005, rising to 33 percent for 2006 and 
2007, and 34 percent for 2008.
    A short discussion of the statutory factors reviewed follows. 
Additional information analyzing each of the statutory factors is 
provided in Appendix B to this rule, ``Departmental Considerations to 
Establish the Underserved Areas Housing Goal,'' and Appendix D to this 
rule, ``Estimating the Size of the Conventional Conforming Market for 
each Housing Goal.''
a. Market Estimate for the Underserved Areas Housing Goal
    The Department estimates that dwelling units in underserved areas 
will account for 35-39 percent of total units financed in the overall 
conventional conforming mortgage market during the period 2005 through 
2008. HUD has developed this range, rather than a specific point 
estimate, to accommodate the projected effects of different economic 
and affordability conditions that can reasonably be anticipated. HUD 
estimates that the underserved areas market averaged 39 percent between 
1999 and 2002.
b. Past Performance of the GSEs Under the Underserved Areas Housing 
Goal
    As discussed above, a number of changes in goal-counting procedures 
were adopted as part of HUD's Housing Goals 2000 final rule. Thus it is 
necessary to provide information using several different measures in 
order to track changes in the GSEs' performance on the Underserved 
Areas Housing Goal over the 1996-2003 period. These are shown in Table 
6.\15\ The same changes in counting rules described for the Low- and 
Moderate-Income Housing Goal are applicable to the Underserved Areas 
Housing Goal.
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    \15\ The Freddie Mac 2002 figures in Table 6 differ from the 
corresponding figures in Table 4 in HUD's Proposed Rule. Subsequent 
to publication of the Proposed Rule, HUD discovered that HUD had 
credited some units toward Freddie Mac's Underserved Areas Housing 
Goal in 2002 that had been previously counted toward the goal in 
2001. The units were associated with a large year-end Freddie Mac 
mortgage purchase transaction in 2002. Because HUD's regulations 
prohibit double counting, HUD has recalculated Freddie Mac's 2002 
Underserved Areas Housing Goal performance. The recalculation also 
reflects correction of some coding errors discovered in HUD's recent 
review. With the recalculation, Freddie Mac fell slightly short of 
its 2002 Underserved Areas Housing Goal.
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    Based on the counting rules in effect at that time, as shown under 
``official performance'' for 1996-2000 in Table 6, Underserved Areas 
Housing Goal performance for Fannie Mae generally fluctuated between 27 
and 29 percent over the 1996-1999 period, before rising to a peak of 
31.0 percent in 2000. Freddie Mac's performance started at a lower 
level, but then increased in several steps, from 25-26 percent in 1996-
1998, to 27.5 percent in 1999, and a record level of 29.2 percent in 
2000. Freddie Mac's performance in 1999 was the only year prior to 2001 
in which it exceeded Fannie Mae's performance on this Goal.
    Based on counting rules in effect for 2001-2003, including the 
bonus points and the TAF, as shown under ``official performance'' in 
Table 6, Underserved Areas Housing Goal performance for Fannie Mae was 
32.6 percent in 2001, 32.8 percent in 2002, and 32.1 percent in 2003. 
Performance for Freddie Mac was 31.7 percent in 2001, slightly less 
than 31.0 percent in 2002, and 32.7 percent in 2003.
    Immediately beneath the official Underserved Areas Housing Goal 
performance percentages in Table 6 are figures showing the GSEs' 
purchase percentages under this Goal on a consistent basis for the 
entire 1996-2003 period. The assumptions used were the counting rules 
established in HUD's Housing Goals 2000 final rule, except that bonus 
points and the Freddie Mac TAF (which terminated at the end of 2003) 
are not applied. These figures are termed the ``2001-2003 baseline'' 
assumptions. For 1996-2000 these figures differ from the official 
performance figures because they incorporate the revised counting 
procedures, which were not reflected in the official performance 
figures at that time. For 2001-2003 both sets of figures incorporate 
the revised counting procedures, but the baseline does not incorporate 
the bonus points and Freddie Mac TAF.
    In terms of the 2001-2003 baseline measure, both Fannie Mae and 
Freddie Mac's Underserved Areas Housing Goal performance reached its 
maximum in 2000 (Fannie Mae at 31.0 percent and Freddie Mac at 29.2 
percent) before declining somewhat over the 2001-2003 period. Both 
GSEs' baseline performance in 2001-2003 exceeded the level attained in 
1999.
    Overall, both GSEs' official performance exceeded their Underserved 
Areas Housing Goal by significant margins in 1996-1999, and by wide 
margins in 2000. New, higher Goals were established for 2001-2003, and 
despite somewhat lower performance than the level attained in 2000 
(largely due to the 2001-2003 refinance wave), both GSEs' performance 
exceeded the new Goal levels in 2001 and 2003; Fannie Mae also exceeded 
its goal in 2002, while Freddie Mac fell slightly short.
    Appendix B to this rule includes a comprehensive analysis of the 
GSEs' performance in funding mortgages for single-family-owner 
properties in underserved areas. (The data reported there are based on 
2000 Census geography, which produces underserved area figures slightly 
over five percentage points higher than 1990-based geography.) Both 
GSEs have lagged the market in funding properties located in 
underserved neighborhoods. Between 1999 and 2003, 28.3 percent of 
Freddie Mac's purchases of home loans financed properties in 
underserved neighborhoods, as did 30.0 percent of Fannie Mae's 
purchases--compared with 31.4 percent of home purchase loans originated 
in the conventional conforming market (excluding B&C loans). Thus, 
Freddie Mac performed at 90 percent of the market level, while Fannie 
Mae performed at 96 percent of the market level. In 2003, underserved 
areas accounted for 29.0 percent of Freddie Mac's purchases, 32.0 
percent of Fannie Mae's purchases, and 32.5 percent of market 
originations.
    In evaluating the GSEs' past performance, it should be noted that 
while borrowers in underserved metropolitan areas tend to have much 
lower incomes than borrowers in other areas, this does not mean that 
GSE mortgage purchases in underserved areas must necessarily be 
mortgages on housing for lower income families. Between 1999 and 2001, 
housing for above median-income households accounted for nearly 60 
percent of the single-family owner-occupied mortgages that the GSEs 
purchased in underserved areas.
    Beneath the 2001-2003 baseline figures in Table 6 are two 
additional rows of figures designated ``2005 Assumptions.'' These 
figures show the effects of applying 2000 census data and the new 
specification of MSAs released by OMB in 2003 to the identification of 
underserved areas for purposes of measuring historical GSE goal 
performance. The second of the two rows also incorporates the effects 
of the Department's proposed change from counties to census tracts as 
the basis for identifying underserved areas outside of metropolitan 
areas beginning in 2005.
    HUD's determination of underserved areas for purposes of computing 
the GSEs' performance on the Underserved Areas Housing Goal has, 
through 2003, been based on area median incomes and area minority 
percentages from the 1990 Census. HUD applied the existing numerical 
thresholds for minority percentages and median incomes to 2000 Census 
data and ascertained that the proportion of underserved census tracts 
and the proportion of housing units in underserved census tracts in 
metropolitan areas both have increased significantly from 1990 levels: 
from 47.6 percent to 51.3 percent of census tracts underserved and from 
44.3 percent to 48.7 percent of population in underserved census tracts 
(including the effects of the 2003 re-specification of Metropolitan 
Statistical Areas).
    Comparable shifts at the county level in non-metropolitan areas 
were found to be of much smaller magnitude. Further, HUD estimated the 
spatial distribution of GSE mortgage purchases across metropolitan 
census tracts and non-metropolitan counties for recent years. The 
findings were that for 2000, 2001, 2002, and 2003, Fannie Mae's 
performance figures are an estimated 7.2 percentage points, 6.0 
percentage points, 5.5 percentage points, and 5.1 percentage points 
higher in terms of 2000 Census geography than with 1990 Census 
geography. The corresponding figures for Freddie Mac are 5.6 percentage 
points, 5.1 percentage points, 5.1 percentage points, and 3.9 
percentage points larger, respectively.
    With a further shift to tract-based definitions, the figures for 
Fannie Mae are reduced by 0.7 percentage point in 2000, 2001, and 2002, 
and for Freddie Mac by 0.7, 0.8, and 0.7 percentage point, 
respectively. The differences between county-based performance and 
tract-based performance were much smaller in 2003, with the latter 
falling below the former by only 0.2 percentage point for Fannie Mae 
and exceeding the former by 0.1 percentage point for Freddie Mac last 
year. As previously noted in the discussion of the Low- and Moderate-
Income Housing Goals, the smaller differences between these two 
approaches in 2003 than in 2000-2002 may be due to the need to apply 
estimation techniques in 2000-2002 but not in 2003.
c. Underserved Areas Home Purchase Subgoal
    The Department believes the GSEs can play a leadership role in 
underserved markets. To facilitate this leadership, the Department is 
establishing a Subgoal of 32 percent for each GSE's acquisitions of 
home purchase mortgages on properties located in the underserved census 
tracts of metropolitan areas for 2005, rising to 33 percent in 2006 and 
2007, and 34

[[Page 63617]]

percent in 2008. The purpose of this Subgoal is to encourage the GSEs 
to improve their purchases of mortgages for homeownership in 
underserved areas, thus providing additional credit and capital for 
neighborhoods that historically have not been adequately served. As 
discussed in Appendix A to this rule, the GSEs have the ability to lead 
the primary market for single-family-owner loans, which is their 
``bread-and-butter'' business. Both GSEs have been dominant players in 
the home purchase market for years, funding 61 percent of the single-
family-owner mortgages financed between 1999 and 2002. Through their 
many new product offerings and their various partnership initiatives, 
the GSEs have shown that they have the capacity to operate in 
underserved neighborhoods. Even though they have the ability to lead 
the market, they have not done so, as both GSEs have lagged behind the 
primary market in serving underserved areas. As shown in Table 7, 
underserved areas (based on 2000 Census geography) accounted for 29.4 
percent of Freddie Mac's purchases of home purchase mortgages in 2003, 
32.0 percent of Fannie Mae'' purchases, and 32.5 percent of market 
originations.\16\ The following points can be made about the data 
presented in Table 7 regarding the underserved areas subgoal:
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    \16\ HUD will begin defining underserved areas based on 2000 
Census geography and new OMB definitions of metropolitan areas in 
2005, the first year of the proposed rule. As explained in Appendix 
B of the proposed GSE Rule, the 2000-based definition of underserved 
areas includes 5,372 more census tracts in metropolitan areas than 
the 1990-based definition, which means the GSE-market comparisons 
had to be updated to incorporate tract designations from the 2000 
Census. Therefore, for the years 1999, 2000, 2001, and 2002, HUD 
used various apportionment techniques to re-allocate 1990-based GSE 
and HMDA data into census tracts as defined by the 2000 Census. 
(Since 2003 HMDA and GSE data were gathered in terms of 2000 Census 
geography, no apportionment was required for that year.) Switching 
to the 2000-based tracts increases the underserved area share of 
market originations by about five percentage points. Between 1999 
and 2002, 30.3 percent of mortgage originations (without B&C loans) 
were originated in underserved tracts based on 2000 geography, 
compared with 25.2 percent based on 1990 geography. As shown in 
Table B.8 of Appendix B of this Final Rule, the underserved areas 
share of each GSE's purchases also rises by approximately five 
percentage points. Thus, conclusions about the GSEs' performance 
relative to the market are similar whether the analysis is conducted 
in terms of 2000 Census geography or 1990 Census geography.
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    Underserved Areas Subgoals Compared With Market. The 32-percent 
subgoal for the first year (2005) is approximately one percentage point 
above 1999-2003 and 2001-2003 average market performance (based on the 
market defined without B&C and small loans) and approximately at the 
2002-2003 average market performance and the previous peak market 
performance. The 33-percent subgoal for 2006 and 2007 would add one 
percentage point to these comparisons, while the 34-percent subgoal for 
2008 would add two percentage points. For example, the 34-percent 
subgoal is approximately three percentage points above both 1999-2003 
and 2001-2003 average market performance, 1.8 percent (market without 
B&C loans) to 2.4 percent (market without both B&C and small loans) 
above 2002-2003 average market performance, and 1.5 percent (market 
without B&C loans) to 1.8 percent (market without both B&C and small 
loans) the market's previous peak performance in 2003.

    Underserved Areas Subgoals Compared With Past Freddie Mac 
Performance. To reach the 32-percent 2005 subgoal, Freddie Mac would 
have to improve its performance by 2.7 percentage points over its 
2001-2003 average underserved areas performance of 29.3 percent, by 
1.6 percentage points over its 2002-2003 average underserved areas 
performance of 30.4 percent, and by 0.3 percent over its previous 
peak performance of 31.7 percent in 2002. To reach the 34-percent 
subgoal, Freddie Mac would have to improve its performance by 3.6 
percentage points over its 2002-2003 average underserved areas 
performance, and by 2.3 percent over its previous peak performance. 
As noted in Table 7, Freddie Mac's performance jumped from 27.3 
percent in 2001 to 31.7 percent in 2002, only to fall back to 29.0 
percent in 2003. Thus, the 32-percent subgoal for 2005 is three 
percentage points above Freddie Mac's most recent experience (29.0 
percent). However, as noted above, Freddie Mac's 31.7-percent 
performance in 2002 is only 0.3 percentage points below the 32-
percent subgoal for 2005.
    Underserved Areas Subgoals Compared With Past Fannie Mae 
Performance. To reach the 32-percent 2005 subgoal, Fannie Mae would 
have to improve its performance by 0.6 percentage points over its 
2001-2003 average underserved areas performance of 31.4 percent; 
Fannie Mae would meet the 32-percent subgoal based on its 2002-2003 
average underserved areas performance of 32.2 percent and its 
previous peak underserved areas performance of 32.3 percent in 2002. 
To reach the 34-percent subgoal, Fannie Mae would have to improve 
its performance by 2.6 percent over its 2001-2003 average 
performance, by 1.8 percentage points over its 2002-2003 average 
performance, and by 1.7 percent over its previous peak performance 
of 32.3 percent in 2003.

    As with the other two home purchase subgoals, the underserved areas 
subgoal targets will be more challenging for Freddie Mac than Fannie 
Mae, particularly given Freddie Mac's low performance (29.0 percent) 
during the most recent year (2003). Again, the type of improvement 
needed to meet the new underserved areas subgoal targets was 
demonstrated by Fannie Mae during 2001-2003, as Fannie Mae increased 
its underserved areas purchases from 29.0 percent of its single-family-
owner business in 2000 to approximately 32 percent in both 2002 and 
2003. As noted above for the low-mod subgoals, staged increases in the 
underserved areas subgoal enable the GSEs to obtain their leadership 
position by gaining experience as they improve and move toward the new 
higher subgoal targets.
    The type of improvement needed to meet this new underserved area 
subgoal was demonstrated by Fannie Mae during 2001 and 2002. During 
2001, underserved area loans declined as a percentage of primary market 
originations (from 31.7 to 30.7 percent), but they increased as a 
percentage of Fannie Mae's purchases (from 29.0 to 29.8 percent); and 
during 2002, they increased further as a percentage of Fannie Mae's 
purchases (from 29.8 to 32.3 percent), placing Fannie Mae at the market 
level.
    Section 4.b. above of this preamble and Section I.4 of Appendix B 
to this rule discuss the reasons why the Department is establishing a 
Subgoal for home purchase mortgages in underserved areas, namely: (1) 
the GSEs have the resources and the ability to lead the market in 
providing funding in underserved neighborhoods; (2) the GSEs lag the 
underserved areas market, even though they have the ability to lead; 
(3) troublesome disparities in our housing and mortgage markets 
indicate a continuing need for increased GSE activity; and (4) there 
are ample opportunities for the GSEs to improve their underserved area 
performance in the home purchase market.
    Although single-family owner-occupied mortgages are the GSEs' 
principal line of business, the GSEs have lagged behind the primary 
market in financing properties in underserved areas. For the foregoing 
reasons, HUD believes that the GSEs can do more to raise the share of 
their home loan purchases in underserved areas. This can be 
accomplished by building on efforts that the GSEs have already started, 
including their new affordable lending products, their many partnership 
efforts, their outreach to inner city neighborhoods, their 
incorporation of greater flexibility into their underwriting 
guidelines, and their purchases of seasoned CRA loans.
    A wide variety of quantitative and qualitative indicators 
demonstrate that the GSEs have the resources and financial strength to 
improve their affordable lending performance enough to lead the market 
in underserved areas.
d. Summary of Comments
    The Department received no comments that specifically addressed the 
level of the Underserved Areas Goal. The majority of commenters that 
offered opinions on the level of the housing goals focused on the high 
year (2008) of the Low- and Moderate-Income Goal. Where commenters did 
mention the Underserved Area Goal, their remarks were in the context of 
better targeting through changes in the definition of underserved 
areas. HUD also received no comments specific to the Underserved Area 
Home Purchase Subgoal. Both Fannie Mae and Freddie Mac commented on the 
level of the Underserved Area Goal. Fannie Mae stated that its 
replication of HUD's market sizing assumptions did not justify an 
Underserved Area Goal of 38 or 40 percent. For example, Fannie Mae 
noted that in reaching a goal level of 40 percent, HUD relied on the 
most unlikely owner-occupied underserved share of 30 percent, a level 
reached only once in the past 11 years. With respect to the Underserved 
Area Subgoal, Fannie Mae stated generally that subgoals risk unintended 
consequences and that HUD has proposed subgoals in excess of the 
opportunity and business mix seen in the market. Freddie Mac commented 
in general that all the goals and subgoals were set beyond what the 
primary market is likely to originate. With respect to the underserved 
areas market share, Freddie Mac estimates that the core ranges are 3-4 
percentage points below the upper limits of the Department's projected 
ranges.
e. HUD's Determination
    The Underserved Areas Housing Goal established in this final rule 
is reasonable and appropriate having considered the factors set forth 
in FHEFSSA. For 2001-2003, HUD set the level of the housing goal 
conservatively, relative to the Department's market share estimates, in 
order to accommodate a variety of economic scenarios. Moreover, current 
examination of the gaps in the mortgage markets, along with the 
estimated size of the market available to the GSEs, demonstrate that 
the number of mortgages secured by housing in underserved areas is more 
than

[[Page 63620]]

sufficient for the GSEs to achieve the new goal.
    Therefore, having considered all the statutory factors including 
housing needs, projected economic and demographic conditions for 2005 
to 2008, the GSEs' past performance, the size of the market serving 
low- and moderate-income families, and the GSEs' ability to lead the 
market while maintaining a sound financial condition, HUD has 
determined that the annual goal for mortgage purchases qualifying under 
the Underserved Areas Housing Goal will be 37 percent for 2005, 38 
percent for 2006 and 2007, and 39 percent for 2008.
    Further, the Department is establishing a Subgoal of 32 percent for 
each GSE's acquisitions of home purchase mortgages on properties 
located in the underserved census tracts of metropolitan areas for 
2005, rising to 33 percent in 2006 and 2007, and 34 percent in 2008. 
This reflects a reduction in the upper end of the market share range 
from 35 percent to 34 percent since HUD's publication of its proposed 
rule, resulting from changes in estimating market share as described at 
the end of Section 3.a. above, and in Section G of Appendix D to this 
rule.
    The reasons for increasing the Underserved Areas Housing Goal are 
discussed in Sections a. and b. above, and for establishing a Home 
Purchase Subgoal at the stated levels in section c. While the GSEs have 
lagged the primary market in funding loans in underserved areas, they 
appear to have ample room to improve their performance in that market. 
A wide variety of quantitative and qualitative indicators demonstrate 
that the GSEs have the expertise, resources, and financial strength to 
improve their low- and moderate-income lending performance, including 
lending for home purchases in underserved areas, and achieve the levels 
of the goals being established.
7. Special Affordable Housing Goal, Sec.  81.14
    This section discusses the Department's consideration of the 
statutory factors in arriving at, and the comments received on, the new 
housing goal level for the Special Affordable Housing Goal, which 
targets mortgages on housing for very low-income families and low-
income families in low-income areas. After consideration of these 
statutory factors and the comments received, this final rule 
establishes the goal for the percentage of dwelling units to be 
financed by each GSE's mortgage purchases at 22 percent in 2005, 23 
percent in 2006, 25 percent in 2007, and 27 percent in 2008.
    After analyzing the statutory factors, HUD has determined to 
establish: (a) a Goal of 22 percent for the percentage of the total 
number of dwelling units financed by each GSE's mortgage purchases that 
are for special affordable housing, affordable to very low-income 
families and families living in low-income areas for 2005, rising to 23 
percent in 2006, 25 percent in 2007, and 27 percent in 2008; (b) a 
Subgoal of 17 percent of the total number of each GSE's purchases of 
home purchase mortgages in metropolitan areas that are for housing 
affordable to very low-income families and low-income families in low-
income areas for 2005 and 2006, rising to 18 percent in 2007 and 2008; 
and (c) a Subgoal of 1 percent of each GSE's combined annual average 
mortgage purchases in 2000, 2001, and 2002, for each GSE's special 
affordable mortgage purchases that are for multifamily housing in 2005-
2008.
    A short discussion of the statutory factors for establishing the 
Special Affordable Housing Goal follows. Additional information 
analyzing each of the statutory factors is provided in Appendix C, 
``Departmental Considerations to Establish the Special Affordable 
Housing Goal,'' and Appendix D, ``Estimating the Size of the 
Conventional Conforming Market for each Housing Goal.''
a. Market Estimate for the Special Affordable Housing Goal
    The Department estimates that dwelling units serving very low-
income families and low-income families living in low-income areas will 
account for 23-27 percent of total units financed in the overall 
conventional conforming mortgage market during the period 2005 through 
2008. HUD has developed this range, rather than a point estimate, to 
account for the projected effects of different economic conditions that 
can reasonably be anticipated. HUD also estimates that the special 
affordable market averaged 28 percent between 1999 and 2002.
b. Past Performance of the GSEs under the Special Affordable Housing 
Goal
    As discussed above, a number of changes in goal-counting procedures 
were adopted as part of HUD's Housing Goals 2000 final rule. Thus, it 
is necessary to provide information using several different measures in 
order to track changes in performance on the Special Affordable Housing 
Goal over the 1996-2003 period. These are shown in Table 8.\17\
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    \17\ The Freddie Mac 2002 figures in Table 8 differ from the 
corresponding figures in Table 5 in HUD's Proposed Rule. Subsequent 
to publication of the Proposed Rule, HUD discovered that HUD had 
credited some units toward Freddie Mac's Special Affordable Housing 
Goal in 2002 that had been previously counted toward the goal in 
2001. The units were associated with a large year-end Freddie Mac 
mortgage purchase transaction in 2002. Because HUD's regulations 
prohibit double counting, HUD has recalculated Freddie Mac's 2002 
Special Affordable Housing Goal performance. The recalculation also 
reflects correction of some coding errors discovered in HUD's recent 
review.
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    Based on the counting rules in effect at that time, as shown under 
``official performance'' for 1996-2000 in Table 8, Special Affordable 
Housing Goal performance for Fannie Mae generally fluctuated in the 
range between 14 and 17 percent over the 1996-1999 period, before 
rising to a peak of 19.2 percent in 2000. Freddie Mac's performance 
started at a lower level, but then increased in several steps, from 14-
16 percent in 1996-1998 to 17.2 percent in 1999, and to a record level 
of 20.7 percent in 2000. That was the only year prior to 2001 in which 
Freddie Mac's performance exceeded Fannie Mae's performance on the 
Special Affordable 9Housing Goal.
    Based on counting rules in effect for 2001-2003, as shown under 
``official performance'' in Table 8, Special Affordable Housing Goal 
performance for Fannie Mae was 21.6 percent in 2001, 21.4 percent in 
2002, and 21.2 percent in 2003. Official performance for Freddie Mac 
was 22.6 percent in 2001, 20.4 percent in 2002, and 21.4 percent in 
2003.
    Immediately beneath the official Special Affordable Housing Goal 
performance percentages in Table 8 are figures showing the GSEs' 
special affordable purchase percentages on a consistent basis for the 
entire 1996-2003 period. The assumptions used were the counting rules 
established in HUD's Housing Goals 2000 final rule, except that bonus 
points and the Freddie Mac TAF (which were terminated at the end of 
2003) are not applied. These are termed the ``2001-2003 baseline'' 
assumptions. In terms of this measure, both Fannie Mae and Freddie 
Mac's special affordable performance reached its maximum in 2000 
(Fannie Mae at 21.4, percent and Freddie Mac at 21.0 percent) before 
declining somewhat in 2001, and then declining further in 2002 and 
2003. Both GSEs' baseline performance in 2003 exceeded the level 
attained in 1999.
    Overall, both GSEs' performance exceeded HUD's Special Affordable 
Housing Goals by significant margins in 1996-1999, and by wide margins 
in 2000. New, higher Goals were established for 2001-2003, and despite 
somewhat lower performance than the level attained in 2000 (largely due 
to the 2001-2003 refinance wave, as discussed under the Low- and 
Moderate-Income Housing Goal), both GSEs' performance exceeded the new 
Goal levels in 2001-2003.
    The Special Affordable Housing Goal is designed, in part, to ensure 
that the GSEs maintain a consistent focus on serving the low- and very 
low-income portion of the housing market where housing needs are 
greatest. Appendices A and C to this rule use HMDA data and GSE loan-
level data for home purchase mortgages on single-family owner-occupied 
properties in metropolitan areas to compare the GSEs' performance in 
special affordable lending to the performance of depositories and other 
lenders in the conventional conforming market. There are two main 
findings with respect to the special affordable category.
    First, Freddie Mac and Fannie Mae have historically lagged 
depositories and the overall market in providing mortgage funds for 
special affordable borrowers over periods, such as 1993-2003, 1996-
2003, and 1999-2003. Between 1993 and 2003, 12.2 percent of Freddie 
Mac's mortgage purchases were for special affordable borrowers, 13.3 
percent of Fannie Mae's purchases, 15.4 percent of loans originated by 
depositories, and 15.5 percent of loans originated in the conventional 
conforming market (without estimated B&C loans). During the period 
between 1999 and 2003, the GSEs' performance was approximately 90 
percent of the market'special affordable loans accounted for 15.1 
percent of Fannie Mae's purchases, 14.5 percent of Freddie Mac's 
purchases, and 16.2 percent of loans originated in the conforming 
market. (See Table 9, which is based on 2000 Census geography.)
    Second, while both GSEs have improved their performance over the 
past few years, Fannie Mae has made more progress than Freddie Mac in 
erasing its gap with the market. During 2003, the special affordable 
share of Fannie Mae's purchases was 17.7 percent, which was above the 
market share of 16.8 percent. In 2003, the special affordable share of 
Freddie Mac's purchases was 16.2 percent.
    Section G in Appendix A to this rule discusses the role of the GSEs 
both in the overall special affordable market and in the different 
segments (single-family owner, single-family rental, and multifamily 
rental) of the special affordable market. The GSEs' special affordable 
purchases accounted for 41 percent of all special affordable owner and 
rental units that were financed in the conventional conforming market 
between 1999 and 2002. The GSEs' 41-percent share of the special 
affordable market was below their 55-percent share of the overall 
market. Even in the owner market, where the GSEs account for 61 percent 
of the market, their share of the special affordable market was only 52 
percent. As noted above, Fannie Mae led the primary market in funding 
special affordable home loans during 2003. On the other hand, Freddie 
Mac continued to lag that market in 2003. The data indicate that there 
is room for Freddie Mac to improve its performance in purchasing 
affordable home loans at the lower-income end of the market.
    The rental market (including both 1-to 4-family rental properties 
and multifamily rental properties) is especially important in the 
establishment of the Special Affordable Housing Goal for Fannie Mae and 
Freddie Mac because of the relatively high percentage of rental units 
meeting the Special Affordable Housing Goal. For example, between 1999 
and 2002, 51 percent of units financed by Fannie Mae's rental mortgage 
purchases met the Special Affordable Housing Goal, representing 46 
percent of units counted toward the Special Affordable Housing Goal, 
during a period when rental units represented only 18 percent of its 
total purchase volume. For Freddie Mac, 50 percent of units financed by 
rental mortgage purchases met the Special Affordable Housing Goal, 
representing 41 percent of units counted toward the Special Affordable 
Housing Goal, during a period when rental units represented only 16 
percent of its total purchase volume.
c. Special Affordable Home Purchase Subgoal
    The Department believes the GSEs can play a leadership role in the 
special affordable market generally, and the home purchase special 
affordable market in particular. Thus, the Department is establishing a 
Subgoal of 17 percent for each GSE's purchases of home purchase 
mortgages for special affordable housing located in metropolitan areas 
for 2005 and 2006, rising to 18 percent in 2007 and 2008.
    The purpose of this Subgoal is to encourage the GSEs to improve 
their purchases of home purchase mortgages on special affordable 
housing, thus expanding homeownership opportunities for very-low-income 
borrowers and low-income borrowers in low-income areas, including 
minority first-time homebuyers who are expected to enter the housing 
market over the next few years. Table 9 provides information needed to 
compare the special affordable subgoal targets with past market and GSE 
performance.
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    Special Affordable Subgoals Compared With Market. The 17-percent 
subgoal for the first year (2005) is approximately one percentage point 
above the 1999-2003, 2001-2003, and 2002-2003 average market 
performance. The 17-percent subgoal is at the previous peak market 
performance (the 1999, 2000, and 2003 markets without B&C loans were 
about 17 percent) or slightly below the previous peak market 
performance (based on 2003 market without both B&C and small loans). 
The 18-percent subgoal for 2007 and 2008 would add one percentage point 
to these figures. Thus, the 18-percent subgoal is approximately two 
percentage points above the 1999-2003, 2001-2003, and 2002-2003 average 
market performance of approximately 16 percent. The 18-percent subgoal 
is one percentage point above the previous peak market performance (the 
1999, 2000, and 2003 markets without B&C loans were about 17 percent) 
or 1.5 percentage points above the previous peak market performance 
based on the 2003 market without both B&C and small loans.
    Special Affordable Subgoals Compared With Past Freddie Mac 
Performance. To reach the 17-percent 2005 subgoal, Freddie Mac would 
have to improve its performance by 1.9 percentage points over its 2001-
2003 average special affordable performance of 15.1 percent, by 1.3 
percentage points over its 2002-2003 average special affordable 
performance of 15.7 percent, and by 0.8 percent over its previous peak 
performance of 16.2 percent in 2003. To reach the 18-percent subgoal, 
Freddie Mac would have to improve its performance by 2.9 percentage 
points over its 2001-2003 average special affordable performance, 2.3 
percent over its 2002-2003 average performance, and by about 1.8 
percent over its previous peak performance.
    Special Affordable Subgoals Compared With Past Fannie Mae 
Performance. To reach the 17-percent 2005 subgoal, Fannie Mae would 
have to improve its performance by 0.9 percentage points over its 2001-
2003 average special affordable performance of 16.1 percent; Fannie Mae 
would essentially meet the 17-percent subgoal based on its 2002-2003 
average special affordable performance of 16.8 percent and would 
surpass the 17-percent subgoal based on its peak special affordable 
performance of 17.7 percent in 2003. To reach the 18-percent subgoal, 
Fannie Mae would have to improve its performance by 1.9 percent over 
its 2001-2003 average performance and by 1.2 percentage points over its 
2002-2003 average performance; Fannie Mae would meet the 18-percent 
subgoal based on its peak performance of 17.7 percent in 2003.
    As with the low-mod and underserved areas subgoals, the special 
affordable subgoal targets will be more challenging for Freddie Mac 
than Fannie Mae. But, as with other goals, the type of improvement 
needed to meet the new special affordable subgoal targets was 
demonstrated by Fannie Mae during 2001-2003, as Fannie Mae increased 
its special affordable purchases from 13.4 percent of its single-
family-owner business in 2000, to 15.8 percent in 2002, to 17.7 percent 
in 2003, as shown in Table 9. This subgoal is designed to encourage 
Fannie Mae and Freddie Mac to lead the special affordable market. As 
noted earlier, the approach taken is for the GSEs to obtain their 
leadership position by staged increases in the subgoals to enable the 
GSEs to gain experience as they improve and move toward the new higher 
subgoal targets.
    The section above on considerations in establishing the Low- and 
Moderate-Income Home Purchase Subgoal and Section D of Appendix C to 
this rule further discuss reasons why the Department set the Subgoal 
for special affordable loans.
    Both Fannie Mae and Freddie Mac questioned HUD's authority under 
FHEFSSA to establish any subgoals within the Special Affordable Housing 
Goal. The GSEs noted that both sections establishing the Low- and 
Moderate-Income and the Underserved Areas Housing Goals include 
language that HUD ``may establish separate specific subgoals within the 
goal under this section and such subgoals shall not be enforceable * * 
* .'' No such language appears in the section establishing the Special 
Affordable Housing Goal. The GSEs asserted that this omission is an 
indication that Congress intended to prohibit HUD from establishing any 
subgoals within the Special Affordable Housing Goal.
    HUD has also considered the GSEs' claim that HUD lacks the 
statutory authority to impose any subgoals within the Special 
Affordable Housing Goal. These same arguments were presented by the 
GSEs during HUD's 1995 rulemaking establishing the housing goals. (See 
Housing Goals 1995 proposed rule published on February 16, 1995 at 60 
FR 9154, and the final rule published on December 1, 1995 at 60 FR 
1846.)
    At that time, HUD stated that the absence of a similar subgoal 
provision under the Special Affordable Housing Goal section ``is not an 
indication that subgoals or subcategories within the overall goal are 
prohibited; rather, such omission indicates that to the extent that 
subgoals or subcategories are promulgated for the Special Affordable 
Housing Goal, no bar exists to enforcing them.'' (60 FR 61860.) The 
1995 Housing Goals final rule established an enforceable subgoal for 
multifamily mortgages within the Special Affordable Housing Goal; this 
subgoal has been in place each year since then. This final rule does 
not change this longstanding agency interpretation.
d. Special Affordable Housing Goal: Multifamily Subgoals
    Based on the GSEs' past performance on the Special Affordable 
Multifamily Subgoals, and on the outlook for the multifamily mortgage 
market, HUD proposed that these Subgoals be retained for the 2005-2008 
period.
    Unlike the overall Goals, which are expressed in terms of minimum 
Goal-qualifying percentages of total units financed, these Subgoals for 
2001-2003 and in prior years have been expressed in terms of minimum 
dollar volumes of Goal-qualifying multifamily mortgage purchases. 
Specifically, each GSE's special affordable multifamily Subgoal is 
currently equal to 1.0 percent of its average total (single-family plus 
multifamily) mortgage volume over the 1997-1999 period. Under the 
proposal, the GSEs' purchases of mortgages financing dwelling units in 
multifamily housing for calendar years 2005-2008 will be 1.0 percent of 
the GSEs' average annual dollar volume of mortgage purchases in the 
calendar years 2000, 2001, and 2002. The proposal would increase the 
subgoal levels by roughly 90 percent compared to their current levels. 
Specifically, Fannie Mae's total eligible multifamily mortgage purchase 
volume increased from $4.6 billion in 1993 to $12.5 billion in 1998, 
and then jumped sharply to $18.7 billion in 2001, $18.3 billion in 
2002, and $33.3 billion in 2003. As shown in Table 8, special 
affordable multifamily mortgage purchases followed a similar path, 
rising from $1.7 billion in 1993 to $3.5 billion in 1998 and $4.1 
billion in 1999, and also jumping sharply to $7.4 billion in 2001, $7.6 
billion in 2002, and $12.2 billion in 2003. As a result of its strong 
performance, Fannie Mae's purchases have been at least twice its 
minimum subgoal in every year since 1997--247 percent of the Subgoal in 
that year, 274 percent in 1998, 315 percent in 1999, 294 percent in 
2000, and, under the new Subgoal level, 258 percent in 2001, 266 
percent in 2002, and 426 percent in 2003.
    Freddie Mac's total eligible multifamily mortgage purchase volume 
increased even more sharply, from $0.2

[[Page 63625]]

billion in 1993 to $6.6 billion in 1998, and then jumped further to 
$11.8 billion in 2001, $18.3 billion in 2002, and $21.5 billion in 
2003. As shown in Table 8, special affordable multifamily mortgage 
purchases followed a similar path, rising from $0.1 billion in 1993 to 
$2.7 billion in 1998, and also jumping sharply to $4.6 billion in 2001, 
$5.2 billion in 2002, and $8.8 billion in 2003. As a result of its 
strong performance, Freddie Mac's purchases have also been at least 
twice its minimum Subgoal in every year since 1998--272 percent of the 
Subgoal in that year, 228 percent in 1999, 242 percent in 2000, and, 
under the new Subgoal level, 220 percent in 2001, 247 percent in 2002, 
and 417 percent in 2003.
    The Special Affordable Multifamily Subgoals set forth in this final 
rule are reasonable and appropriate based on the Department's analysis 
of this market. The Department's decision to retain these Subgoals is 
based on HUD's analysis, which indicates that multifamily housing still 
serves the housing needs of lower-income families and families in low-
income areas to a greater extent than single-family housing. By 
retaining the Special Affordable Multifamily Subgoal, the Department 
ensures that the GSEs continue their activity in this market, and that 
they achieve at least a minimum level of special affordable multifamily 
mortgage purchases that are affordable to lower-income families.
e. Summary of Comments
    Comments regarding the Special Affordable Goal were received from 
numerous public advocacy groups and one trade association; however, 
only one public advocacy group commented on the level of the goal. The 
commenting group recommended that the 2004 Special Affordable Goal be 
maintained for the years 2005-2008.
    No comments specific to the Special Affordable Home Purchase 
Subgoal were received from the public. Fannie Mae provided an analysis 
as part of its comments that illustrated, for the years 1999 through 
2002, that the market did not perform up to the level of HUD's proposed 
Special Affordable Home Purchase Subgoal.
    Regarding the Multifamily Special Affordable Subgoal, neither GSE 
objected to HUD's proposed subgoal levels for 2005-2008. One trade 
organization suggested that the subgoal has outlived its original 
purpose and should be discontinued. This organization stated that the 
subgoal was established to induce the GSEs to purchase multifamily 
loans at a time when heavy credit losses had caused them to back away 
from this market, and that the situation had changed greatly since 
then. The organization stated that the overall goals now provided 
sufficient incentive for the GSEs to focus on multifamily mortgage 
purchases. One multifamily lender expressed concern that increasing the 
Multifamily Special Affordable Subgoal will push the GSEs to extend 
credit to unqualified borrowers with poor quality properties that 
should not be eligible for long-term, low-cost financing. However, 
other commenters, including multiple public advocacy groups and a local 
government official, recommended that HUD increase the level of this 
subgoal. Several commenters specifically recommended that HUD set this 
subgoal between 2.5 percent and 3 percent of the GSEs' purchases in 
preceding years. They noted that the GSEs have far exceeded the subgoal 
levels in recent years and said that a higher subgoal level is needed 
to promote additional multifamily lending.
f. HUD's Determination
    HUD concludes that the Special Affordable Housing Goal established 
in this final rule is reasonable and appropriate having considered the 
factors set forth in FHEFSSA. Current examination of the gaps in the 
mortgage markets, along with the estimated size of the market available 
to the GSEs, demonstrates that the number of mortgages secured by 
special affordable housing is more than sufficient for the GSEs to 
achieve the new goal.
    Therefore, having considered all the statutory factors including 
housing needs, projected economic and demographic conditions, the GSEs' 
past performance, the size of the market serving low- and moderate-
income families, and the GSEs' ability to lead the market while 
maintaining a sound financial condition, HUD has determined that the 
Special Affordable Housing Goal will be 22 percent for 2005, 23 percent 
for 2006, 25 percent for 2007, and 27 percent for 2008. This reflects a 
reduction in the upper end of the market share range from 28 percent to 
27 percent since HUD's publication of its proposed rule, resulting from 
changes in estimating market share as described at the end of section 
3.a, above, and in Section H of Appendix D to this rule.
    The reasons for increasing the Special Affordable Housing Goal are 
discussed above in this preamble. Since the GSEs have historically 
lagged the primary market in purchasing loans on owner and rental 
properties that qualify as special affordable, they have ample room to 
improve their performance in that market. The GSEs' mortgage purchases 
between 1999 and 2002 accounted for 55 percent of the total (single-
family and multifamily) conforming mortgage market, but they accounted 
for only 41 percent of the special affordable market. A wide variety of 
quantitative and qualitative indicators demonstrate that the GSEs have 
the expertise, resources, and financial strength to improve their 
special affordable lending performance and to close their gap with the 
market.
    Further, the Department is establishing a Subgoal of 17 percent for 
each GSE's acquisitions of home purchase mortgages for special 
affordable housing in 2005 and 2006, rising to 18 percent in 2007 and 
2008. The special affordable home purchase subgoal will ensure that 
Freddie Mac improves its performance enough not only to close its 
current gap with the primary market but also to place itself in a 
leadership position. The subgoal will also encourage Fannie Mae to 
improve further its current market-leading performance. A wide variety 
of quantitative and qualitative indicators demonstrate that the GSEs 
have the expertise, resources, and financial strength to improve their 
special affordable lending performance, including lending for home 
purchases for special affordable housing, and to achieve the levels of 
the subgoals being established.
    Finally, the Department is establishing each GSE's Special 
Affordable Multifamily Subgoal at 1.0 percent of its average annual 
dollar volume of total (single-family and multifamily) mortgage 
purchases over the 2000-2002 period. In dollar terms, the level of the 
subgoal is $5.49 billion per year in special affordable multifamily 
mortgage purchases for Fannie Mae and $3.92 billion per year in special 
affordable multifamily mortgage purchases for Freddie Mac. These 
Subgoals would be less than the actual special affordable multifamily 
mortgage purchase volume in 2001-2003 for both GSEs. Thus, the 
Department believes that they would be feasible for the 2005-2008 
period.
    HUD believes that the proposed increase in the dollar level of the 
Special Affordable Multifamily Subgoal balances the need to promote GSE 
activity in this segment with the need to provide some protection in 
the event of a decline in overall mortgage market activity. Because 
this goal is set as a dollar amount rather than as a share of business, 
overall declines in residential mortgage lending would make this goal 
harder to achieve. Setting the subgoal level based on the GSEs' record

[[Page 63626]]

multifamily loan purchases during 2000-2002 sets an appropriately high 
level for the next several years, in the Department's view. In recent 
years Fannie Mae and Freddie Mac have each purchased multifamily 
mortgages in at least twice the subgoal amount. The increase in that 
subgoal dollar level should serve to provide a more meaningful floor to 
the level of multifamily lending during the 2005-2008 period.
8. Missing Data/No-Doc Loans
    Overview. Accurate measurement of the GSEs' performance under the 
three Housing Goals depends on the completeness of data on borrower 
income (or, in the case of non-owner-occupied units, the rent) and 
property location. With respect to property location data, there was a 
less than one percent incidence of missing or incomplete geographical 
data between 2000 and 2002 for mortgages purchased by the GSEs. The 
incidence of missing borrower income data has been greater--on the 
order of several percent each year.
    One reason for the increase in missing income data is the market's 
recent increased use of mortgages, commonly called low documentation 
(Low Doc) and no documentation (No Doc) loans. These loans do not 
require the borrower to provide income information. In some cases, the 
borrower provides information on assets but not income because of 
circumstances that make assets easier to document. In other instances, 
mortgages are originated entirely on the basis of a credit report, 
property appraisal, and cash for the downpayment. These mortgages 
typically require relatively large downpayments and may also require a 
higher interest rate than fully documented mortgages.
    The Housing Goals 2000 Final Rule provided that the GSEs may 
exclude from the denominator owner-occupied units which lack mortgagor 
income data and which are located in low- or moderate-income census 
tracts, i.e., tracts whose median income is no greater than the median 
income of the metropolitan area, or for properties located outside of 
metropolitan areas, the larger of the median incomes of the county or 
the statewide non-metropolitan area (see 24 CFR 81.15(d)).\18\
---------------------------------------------------------------------------

    \18\ For rental units, the 2000 Housing Goals Final Rule also 
established counting rules that allow the GSEs to estimate rents or 
exclude units from the denominator when rent data are missing. See 
24 CFR 81.15(e)(6)(i) on the rules applicable to multifamily units 
and 24 CFR 81.15(e)(6)(ii) on the rules for single-family rental 
units.
---------------------------------------------------------------------------

    In view of the increasing use of loans made without obtaining 
income information from the borrower, there is a question whether HUD's 
existing counting rules for missing-data situations are adequately 
reliable and create no more than a negligible statistical bias in the 
GSEs' Housing Goals performance figures relative to the values that 
they would have if complete income data could be obtained, and whether 
a more precise method for imputing incomes could be employed. For this 
reason, HUD requested comments from the public about the desirability 
and feasibility of implementing a standard econometrically based method 
for imputing the income distribution of mortgages purchased by each GSE 
that lack income data, based on known characteristics of the loan and 
the census tract.
    Summary of Comments. Fannie Mae supported expanding affordability 
estimation to single-family rental and owner-occupied goal performance 
calculations and favored a more complex econometrically based 
affordability estimation methodology. For owner-occupied units Fannie 
Mae suggested a method based on the probability of mortgages/units 
qualifying for a goal based on census tract location. Fannie Mae stated 
that the multifamily affordability estimation methodology could also be 
applied to single-family rental units. Fannie Mae commented that if HUD 
were to adopt an econometrically based methodology, no limit should be 
placed on its implementation. With the current methodology, Fannie Mae 
requested that the limit for rental units be increased to 10 percent of 
total rental unit acquisitions.
    Freddie Mac commented that HUD should adopt a simpler approach to 
missing data. For example, HUD should allow the GSEs to remove units 
with missing incomes from the calculation of the housing goals. Freddie 
Mac reasoned that the market numbers used in establishing the Housing 
Goals omit missing data and that omitting missing data from a GSE's 
performance would be consistent. Also, Freddie Mac stated that it 
historically has had a lower missing data rate than the market and that 
it has sufficient business related incentives to reduce missing data. 
Freddie Mac commented that any limits on adjustments for missing data 
should be related to overall missing data rates in the market, 
estimation parameters should be available at the beginning of the 
performance year, and estimation procedures should be simple and 
straightforward to implement.
    Several other organizations endorsed a standardized procedure for 
estimating affordability for those units missing rent or income data, 
including an econometrically based methodology. Two commenters stated 
that HUD should require only actual data for determining whether a unit 
is affordable or not. In addition, some commenters strongly recommended 
that HUD disallow goals credit for all no-documentation subprime loans 
because such loans are likely to be predatory.
    HUD's Determination. Having considered the comments received, HUD 
has determined that permitting some level of estimation for 
affordability data is reasonable and consistent with statutory intent 
that the GSEs serve the affordable housing needs of families even if 
actual data are not available. With regard to some commenters' 
objections that HUD should not permit the use of estimated data for--or 
even allow goals credit for--any loans that were underwritten for 
approval without borrower income data due to the potential for these 
loans to have predatory features, the Department does not find that 
these loans are inherently predatory in nature. Also, both GSEs have 
publicly announced that they will not finance any loans with predatory 
features, and the Department expects that they will continue to 
vigorously enforce these policies. Accordingly, this final rule 
implements several changes to the treatment of missing data. The first 
change amends Sec.  81.15(d) of the General Requirements to provide an 
alternative treatment for single-family owner-occupied units where the 
mortgagor's income is missing. As provided in Sec.  81.15(d), the GSEs 
may continue to exclude such units from the denominator as well as the 
numerator when they are located in census tracts with median income 
less than or equal to area median income according to the most recent 
census, up to a ceiling of one percent of total eligible units. 
Purchases in excess of the ceiling will be included in the denominator 
and excluded from the numerator if they are missing data.
    However, in lieu of using this procedure, HUD is making available 
to the GSEs in Sec.  81.15(d) an alternative method for missing income 
treatment that provides the GSEs with the ability to apply a HUD-
approved affordability estimation methodology to all single-family 
owner-occupied units with missing borrower income data up to a 
specified maximum. This alternative provision specifies an approach 
that recognizes the distribution of borrower incomes within census 
tracts in determining how to treat loans with

[[Page 63627]]

missing income data. Goal-qualifying units, by census tract, are 
estimated by multiplying the number of single-family owner-occupied 
units with missing borrower income information in properties securing 
mortgages purchased by the GSE, by the percentage of all single-family 
owner-occupied units from originations that would count toward 
achievement of the goal, as determined by HUD based on the most recent 
HMDA data available, for each census tract where the GSE acquired 
mortgage units. In establishing the maximum number of units where 
borrower income may be estimated under this alternative provision, HUD 
will apply two factors. The first of these is the rate of missing 
borrower income data for each census tract. This is calculated using 
HMDA data for the most recent years for which comparable data are 
available. The second factor is the number of single-family owner-
occupied units purchased by a GSE during the performance year, by 
census tract. The maximum is calculated by multiplying the HMDA 
percentage of missing income data by the number of units that a GSE 
purchased in each tract. This number is summed up for all tracts to 
obtain the overall nationwide maximum for that GSE. HUD will provide 
each GSE with a dataset containing applicable tract-based HMDA missing 
income rates prior to the start of each year. The GSEs may choose which 
provision of Sec.  81.15(d) they will use in any year. However, they 
may not combine the options available under this provision. If the 
maximum on missing single-family owner-occupied unit incomes is 
exceeded, the estimated goal-qualifying units will be adjusted by the 
ratio of the maximum amount divided by the total number of units with 
missing income information. Under each provision of Sec.  81.15(d), 
units in excess of the specified maximum as well as units where 
affordability information is not available will remain in the 
denominator when calculating goal performance.
    HUD is also in this final rule revising Sec.  81.15(e)(6) to change 
the current maximum on the use of HUD-approved multifamily rent 
estimation data from 5 percent to 10 percent. In analyzing the GSEs' 
multifamily purchases for the past several years, HUD has determined 
that this change is statistically insignificant and will serve to 
promote further the financing of rental units that would otherwise be 
eligible for credit under the Housing Goals. In this final rule, HUD is 
also specifying a methodology that may be used to estimate 
affordability data for multifamily properties with missing rent data. 
This methodology is the same methodology that has been used in past 
years to estimate affordability data for multifamily properties with 
missing rent data.
    With regard to single-family one-to-four unit rental properties 
financed with loans that are missing affordability data, the Department 
finds that a lack of data should not act as a disincentive for the GSEs 
to serve markets that historically are important sources of affordable 
housing. Under HUD's 2000 Rule, Sec.  81.15(e)(6)(ii) permits the GSEs 
to exclude these units from both the numerator and the denominator when 
neither income nor rental data are available. While this provision does 
not penalize the GSEs for financing these properties by requiring that 
they be counted in the denominator towards goal calculation, it also 
does not allow them to obtain Housing Goals credit for financing 
mortgages that tend disproportionately to serve affordable housing. In 
this final rule, HUD is retaining the exclusion provision at Sec.  
81.15(e)(6)(ii) but is also adding an alternative provision that will 
permit the use of the same estimation methodology now used for 
multifamily loans with missing rent data. However, HUD is imposing 
separate maximum rates for the new provision as follows: a 5 percent 
maximum on unseasoned single-family rental units originated in the 
current year and a 20 percent maximum for seasoned loan units, that is, 
for loans that were originated more than 365 days prior to the date of 
acquisition by the GSE. HUD recognizes the greater difficulty of 
obtaining rent information on units from mortgages originated a year or 
more prior to acquisition by the GSE. Therefore, HUD is allowing the 
higher maximum on affordability estimation for these units. As with the 
estimating provisions permitted under Sec.  81.15(d), the GSEs may use 
only one of the provisions permitted under Sec.  81.15(e)(6)(ii) in any 
year.
    In addition to the changes described herein, HUD is adding a 
provision to Sec. Sec.  81.15(d)(2)(i), 81.15(e)(6)(i) and (ii) that 
permits the use of such other data source or methodology as may be 
approved by HUD. HUD is also clarifying that owner occupied units that 
exceed the maximum established under Sec.  81.15(d)(2) for using any 
estimation methodology will remain in the denominator of the respective 
goal calculation.
9. Double Counting of Seasoned Mortgages
    In addition to the preceding changes being made at this final rule 
stage, HUD is making a technical change to Sec.  81.16(c)(6) for 
purposes of clarity. Paragraph (c)(6) addresses the treatment of 
seasoned mortgages. The paragraph, as currently codified, is a long 
one-sentence paragraph. HUD believes that dividing this paragraph into 
two subparagraphs would improve comprehensibility and clarity. This 
change is intended to clarify the restriction on double counting of 
seasoned mortgages in Sec.  81.16(c)(6), i.e., the restriction that 
prohibits the counting of a GSE's purchase of a seasoned mortgage 
toward a goal where such mortgage has already been counted by the GSE 
toward the goal. This change makes clear that the restriction applies 
to all seasoned mortgages, regardless of whether any other counting 
rules under Sec.  81.16(c) also apply. Section 81.16(c)(6) in this 
final rule reflects this technical change.
10. Bulk Purchases/Counting of Seasoned Loans
    Overview. In its May 3, 2004, proposed rule, HUD sought comment on 
whether its current definition of a ``mortgage purchase'' should be 
revised to ensure that transactions, especially large transactions, are 
appropriately counted under the law and in accordance with the purposes 
of FHEFSSA and the GSEs' charter acts. HUD also sought comment on 
whether it should amend its counting rules at 24 CFR 81.15 and 81.16 to 
ensure that the GSEs' large-scale transactions further the requirements 
and purposes of the Housing Goals.
    For example, HUD asked if commenters believe the current counting 
rules are specific enough to determine which seasoned mortgage 
transactions, including large-scale transactions, are substantially 
equivalent to mortgage purchases. HUD sought these comments primarily 
in response to certain large-scale transactions of seasoned loans 
undertaken by both GSEs in late 2003 for the purpose of meeting the 
2003 Housing Goals. HUD questioned whether such transactions furthered 
the purposes of FHEFSSA, especially since the transactions, including a 
transaction between Freddie Mac and Washington Mutual Bank (WaMu), 
contained an option for dissolution in the following year. HUD sought 
public comment on its counting rules and definitions to ascertain the 
effect of the GSEs' bulk purchases, including those with special

[[Page 63628]]

terms or conditions, on the market and on affordable housing.
    Summary of Comments. HUD received several suggestions for revising 
its current definitions and counting rules. A trade association 
commented that HUD should specify the definition of mortgage purchase 
so as not to count transactions that are goals-oriented in form but not 
in substance. Some organizations commented that seasoned loans should 
be excluded from counting towards the goals altogether because they do 
not directly fund new housing supply. Likewise, some commenters 
believed that these transactions are contrary to the Charter 
requirement that the GSEs provide assistance to the secondary market on 
an on-going basis.
    One policy group asked that HUD exclude loans with recourse clauses 
because these purchases do not alleviate risk from the market. Other 
commenters took the opportunity to request that the definitions and 
counting rules more closely match CRA loan definitions. These 
commenters did not suggest specific regulatory language for the 
definitions.
    HUD also received comments that supported counting bulk purchases 
that occur late in the year towards the goals. One trade association 
described the efficiencies gained from large-scale transactions. For 
example, the market for multifamily units is large and fragmented, and 
seasoned portfolio transactions are an efficient means for the GSEs to 
acquire smaller loans in the under 50-unit segment of the market. Some 
commenters cautioned that changing the definition of mortgage purchase 
or the counting rules to clarify the treatment of large-scale seasoned 
mortgage transactions could have negative unintended consequences.
    The GSEs responded to this issue with detailed comments. Fannie Mae 
stated that every mortgage purchase, whether executed through flow, 
large or seasoned transactions, contributes to its housing mission, and 
therefore, HUD should not change the qualification of mortgage 
purchases either for the size of the transaction or for the amount of 
seasoning involved. Fannie Mae also stated that large-scale mortgage 
purchases lower transactions costs for both the buyers and sellers of 
mortgages. Some lenders offer to sell the GSEs mortgages on a flow 
basis, but others prefer to bundle mortgages together and sell to the 
GSEs from their portfolios. Bulk transactions also serve the business 
needs of lenders who do not have a direct relationship with Fannie Mae. 
Fannie Mae said that two-thirds of its bulk purchases between 2001 and 
2003 were not for seasoned loans. Fannie Mae characterized the purchase 
of seasoned loans as an important component of the liquidity of current 
mortgages. Knowing that there is a ready market allows financial 
institutions to hold some of their assets in the form of mortgages, and 
affords them the opportunity to sell these mortgages later to manage 
liquidity, improve profitability, strengthen their capital position, 
and manage certain risks.
    In addition to the market benefits of seasoned mortgages, Fannie 
Mae also discussed the practical relationship of seasoned loan 
treatment and goals performance. The GSEs need bulk purchases of 
seasoned loans to meet the goals in years when the mix of business in 
the primary market deviates from the business mix anticipated at the 
time the goals were set. Fannie Mae pointed out that HUD cited late-
year purchases of seasoned loans in the proposed rule as a useful 
method to meet the goals when market conditions change unexpectedly. 
Fannie Mae also discussed the attributes of dissolvable securities, 
stating that lenders sometimes request the option to dissolve 
securities swapped with the GSEs. Fannie Mae said that dissolution 
options are common terms in the marketplace because dissolution options 
grant lenders greater control over their balance sheets, capital 
position, and other financial concerns. Fannie Mae indicated that 
lenders request these options because they obtain more favorable rates 
and can make more loans.
    Freddie Mac made many of the same points about bulk purchases of 
seasoned purchases as Fannie Mae and also discussed its recent bulk 
transaction with WaMu. For example, Freddie Mac commented that bulk 
purchases and dissolution options are common industry practices. 
Freddie Mac also stated that counting seasoned loans increased the 
value and liquidity of current loans. Knowledge that the GSEs stand 
ready to purchase mortgages under all market conditions gives other 
investors greater confidence because they have a viable exit strategy 
when providing funds to the real estate market.
    Freddie Mac indicated that bulk purchases are an essential means of 
achieving the goals when market conditions take an unexpected turn, 
such as the conditions leading to its transaction with WaMu in 2003. 
Freddie Mac pointed out that, unlike FHA, which can manage its business 
to the cap on insurance commitments set annually by Congress, Freddie 
Mac instead must respond to a dynamic market in which the nature and 
magnitude of loan originations are volatile. In real time, it is 
extremely difficult to predict the volume and ``mix'' or proportion of 
goals-eligible mortgages those markets will produce. Market refinance 
forecasts for 2003 by Economy.com and Freddie Mac were off by over $2 
trillion. Large transactions of mortgage purchases are essential 
because forecasts are not precise.
    With respect to its transaction in 2003 with WaMu, Freddie Mac 
stated that it engaged in this transaction because HUD took a number of 
steps to strongly encourage the GSEs to participate in the small 5-50 
multifamily mortgage market, including bonus points. The GSEs can only 
purchase on terms that sellers are willing to accept. Freddie Mac 
further stated that goals that force the GSEs to stretch their business 
mix in uncertain market conditions must eventually cause the GSEs to 
value some mortgages more than sellers do. Under these conditions, 
sellers will negotiate for more favorable terms. Freddie Mac stated 
that the seller ``put'' option in the WaMu transaction and a similar 
transaction with Citibank exemplify pro-seller terms and that these 
transactions advance the GSE's regulatory purposes as well as meet the 
letter of the law.
    In response to concerns about the options included in the swap, 
Freddie Mac stated that ``it is the GSE's affordable housing goal 
requirements, among other things, that give the sellers the negotiating 
power to obtain such options.'' Both Fannie Mae and Freddie Mac 
concluded that HUD's definition of a mortgage purchase and the counting 
rules should not be changed.
    HUD's Determination. HUD considered the comments received, with 
particular focus on the GSEs' comments regarding transactions that 
include dissolution options. HUD is concerned that transactions of this 
type, which both GSEs undertook in 2003 to achieve their affordable 
housing goals, are not fully consistent with the purposes of FHEFSSA, 
which are to award goals credit for mortgage purchases that increase 
market liquidity for affordable housing. When a seller can exercise its 
option to reverse or unwind a transaction and take back the mortgages 
within a specified time period, the transaction appears temporary in 
nature, and the liquidity that might result from the transaction also 
appears transitory.
    The drafters of FHEFSSA intended that the GSEs provide liquidity 
for affordable housing where such liquidity would otherwise not exist 
or where it would be less reliable. HUD is aware that even short-term 
liquidity, as may occur with dissolution options, can be of value to 
mortgage sellers, especially

[[Page 63629]]

for balance sheet management or other purposes, but sellers seeking 
such options are generally not constrained in locating short-term 
liquidity solutions, especially when these solutions are backed by 
seasoned mortgage loans.
    Further, HUD believes that placing no constraints on goals 
eligibility for transactions with dissolution options would have the 
effect of encouraging transactions that are so short-term as to be 
dissolvable almost immediately after they have been counted towards the 
housing goals. Such an outcome is clearly at odds with FHEFSSA.
    Therefore, HUD has determined to amend its counting rules to 
provide that for units acquired in transactions with seller dissolution 
options to count toward the housing goals, such options must provide 
for a lockout period that prohibits the exercise of the dissolution 
option for at least one year from the date on which the transaction was 
entered into and the transaction cannot be dissolved during the one-
year period. The Secretary may grant an exception to the minimum 
lockout period, in response to a written request from a GSE, if the 
Secretary determines that the transaction furthers the GSE's statutory 
purposes and the purposes of FHEFSSA. Where a mortgage purchase 
involving a seller dissolution option has been counted toward the 
housing goals under a transaction subject to this provision, the 
transaction may not be dissolved (either by the exercise of the seller 
dissolution option, or by separate agreement entered into by the GSE 
and the seller) during the one-year minimum lockout period. If the 
seller of the mortgages and the GSE dissolve the transaction before 
that time, the transaction may no longer be counted toward the housing 
goals and the GSE's performance must be adjusted in accordance with 
this rule.
    The Department defines seller dissolution option as an option for a 
seller of mortgages to the GSEs to dissolve or otherwise cancel a 
mortgage purchase agreement or loan sale. The Department, however, 
wishes to fully distinguish the arrangements established in these 
seller dissolution options from other types of agreements involving 
repurchases of securities or mortgages that involve the GSEs. For 
example, the GSE, as seller of a security, may agree to repurchase, or 
buy back, a previously sold mortgage-backed security on a negotiated 
basis from the holder of the security. HUD's regulation does not 
address that practice. Likewise, it does not address arrangements 
whereby a mortgage lender agrees to repurchase or replace a mortgage 
upon demand of the GSE if the mortgage defaults. The provision also 
does not apply to repurchase and resale agreements where the GSE is the 
purchaser of the security. Rather, the transactions addressed by HUD's 
regulation provide, as a term of the transaction, the mortgage lender/
seller--and not the GSE--with the option of dissolving the transaction 
and having the mortgages returned to the mortgage lender/seller.
    HUD believes the one-year lockout period will prevent potential 
misuse of these transactions but will still allow sellers of mortgages 
to manage their portfolios in the medium and long term. The limit on 
dissolution options applies to all transactions because it is the 
potential for misuse, not the size of the transaction that could 
conflict with FHEFSSA. HUD will continue to monitor the GSEs' use of 
dissolution options to ensure that the one-year minimum lockout 
requirement is accomplishing its intended purpose. If there is a 
question about whether a particular transaction complies with the one-
year minimum lockout requirement, HUD expects that the GSE will seek 
clarification from HUD regarding the appropriate treatment of that 
transaction under the counting rules.
    With regard to modifying its definition of a ``mortgage purchase,'' 
HUD has determined that defining mortgage purchases in terms of market 
effects would be cumbersome. The definition would have to be broad 
enough to encompass all of the statutory purposes, including market 
liquidity and market stability, and still narrow enough to exclude 
transactions that are legitimate in form but not in substance.
    Similarly, while some commenters suggested that HUD exclude 
seasoned mortgages from its definition or that HUD impose a credit risk 
threshold for awarding goals credit, HUD believes that these measures 
could have unintended consequences that could potentially harm market 
liquidity for affordable housing. For example, HUD has encouraged the 
GSEs to buy seasoned portfolios of CRA loans as an important source of 
liquidity for these loans.
11. Responses to Other Issues Raised by Commenters Relating to the 
Housing Goals
a. Feasibility Determinations
    Overview. Section 1336(b) of FHEFSSA, together with HUD's current 
regulations, provides a process for determining that one or more goal 
levels are infeasible. This process may be initiated either by HUD or 
by a GSE; nothing in FHEFSSA or in HUD's regulations limits a GSE's 
ability to request HUD to examine whether a particular goal may be 
infeasible. If HUD determines that a GSE has failed to meet a housing 
goal, or that there is a substantial probability that a GSE will fail 
to do so, HUD must notify the GSE and provide an opportunity for the 
GSE to respond. HUD must then determine whether or not the goal was 
feasible. If HUD determines that the goal was infeasible, then no 
further HUD action to enforce the goal is authorized.
    HUD's proposed rule did not make any changes to the process for 
determining whether a goal was or was not feasible. However, HUD still 
received comments from both Fannie Mae and Freddie Mac regarding those 
provisions.
    Summary of Comments. Fannie Mae commented that ``uncertainty 
regarding HUD's potential feasibility determination would lead Fannie 
Mae and Freddie Mac to engage in whatever means necessary to meet the 
goals, potentially resulting in market distortions.'' Fannie Mae 
recommended that the goals be set at levels that are more likely to be 
seen in the marketplace, rather than at the high end of market 
estimates.
    Freddie Mac commented that an after-the-fact finding of 
``infeasibility'' or an adjustment to the goals would not alleviate the 
burden imposed by unreasonable goals. Freddie Mac noted that it is very 
difficult to estimate the size and composition (or ``goal mix'') of the 
mortgage market in advance. Freddie Mac also expressed concern that an 
after-the-fact feasibility determination would require HUD to second-
guess innumerable business decisions made by the GSEs, with no 
certainty as to how HUD would make such determinations. Finally, 
Freddie Mac stated that its reputation would suffer great harm during 
the time HUD considered its feasibility determination, and that this 
harm could not be undone.
    HUD's Determination. The final rule does not make any changes to 
the process for determining whether a goal is infeasible for a 
particular year. Although HUD has never had to make a determination 
that a goal is infeasible, HUD believes that the process that is 
currently in place provides an effective framework for making a timely 
determination of infeasibility. If in the future it is necessary to 
make a determination of whether a goal is or was infeasible, HUD will 
make every effort to expedite the process in an effort to minimize any 
potential costs and uncertainty associated with the process.

[[Page 63630]]

b. Specification of Underserved Areas
    Summary of Comments. Several commenters suggested that HUD should 
redefine the Underserved Areas Goal. A consensus of these commenters 
stated that lowering the tract income criteria from 90 (120) percent to 
80 (100) percent would make the Underserved Areas Goal consistent with 
CRA. Several of the commenters also stated that the current definition 
is too broad and that lowering the tract income criteria to 80 percent 
or 100 percent when the minority population is greater than 50 percent 
(as opposed to 30 percent currently) of the tract would focus the goal 
on truly underserved areas. One commenter suggested including a 
borrower income criteria, such as less than 80 percent of area median 
income, in the Underserved Areas Goal to further focus the goal on the 
underserved.
    HUD's Determination. As discussed in Appendix B to this rule, HUD 
has determined not to go forward with redefining the Underserved Areas 
Goal at this time.
c. Reconciling the CRA and the Affordable Housing Goals
    Summary of Comments. Several commenters from trade associations and 
policy organizations suggested that HUD could more sharply focus GSE 
activity on low- and moderate-income homebuyers by encouraging greater 
purchases of CRA loans. According to these commenters, this could be 
accomplished by establishing a new CRA goal or by establishing CRA 
subgoals under each of the current Housing Goals.
    The CRA requires depository institutions to help serve the credit 
needs of their communities and authorizes federal regulators to examine 
the level of lending, investment, and service that these institutions 
provide. Commenters noted that under section 1335 of FHEFSSA, Fannie 
Mae and Freddie Mac are directed to ``take affirmative steps to assist 
insured depository institutions to meet their obligations under the CRA 
which shall include developing appropriate and prudent underwriting 
standards, business practices, repurchase requirements, pricing, fees, 
and procedures.'' These commenters noted, however, that under FHEFSSA, 
the definitions for key categories of borrowers served through 
affordable housing goals differ from those established for borrowers 
served under CRA.
    Under FHEFSSA, the definition for ``low income'' is a borrower at 
or below 80 percent of area median income, while for CRA purposes, the 
definition of ``low-income'' is a borrower at or below 50 percent of 
area median income. Similarly, the affordable housing goal definition 
of a ``moderate income'' borrower is at or below 100 percent of area 
median income, while for CRA purposes, ``moderate income'' is defined 
as at or below 80 percent of median area income.
    Commenters pointed out that these definitional discrepancies create 
a mismatch between the loans made by the primary market institutions 
and those purchased by the GSEs to meet affordable housing goals. The 
result is that the GSEs can meet their goals by purchasing loans to 
borrowers in higher income ranges than those mandated under CRA, which 
may result in less liquidity available to primary mortgage market 
lenders to make additional low and moderate income loans.
    These commenters recommended that HUD find a way to resolve the 
apparent contradiction between the definitions. One commenter suggested 
that HUD has the authority to align the affordable housing goals with 
the CRA definitions without additional legislation. This commenter 
recommended that HUD require the GSEs to report low-income loans in two 
categories--``low income'' and ``very low income''--and conform the 
definitions of low-income and moderate income to the CRA definitions.
    Other commenters however, indicated that legislative correction 
would be needed to accomplish such alignment. These commenters 
recommended that until that time, HUD should consult with federal bank 
and thrift regulators to determine the CRA-eligible market share and 
adjust the affordable housing goals for Fannie Mae and Freddie Mac 
accordingly.
    Several commenters recommended that HUD should consider 
establishing specific ``CRA loan sub-goals'' under the existing goals 
for the GSEs. One commenter suggested that HUD could create a new goal 
that requires the GSEs to purchase stated amounts of CRA-eligible home 
purchase mortgages, with low and moderate income subgoals based on the 
CRA measures.
    HUD's Determination. After close review of this issue, HUD has 
determined that full harmonization between affordable housing goals and 
CRA definitions will require legislative action. Income brackets for 
the goals under FHEFSSA and under CRA are statutorily defined, and CRA 
definitions allow for much greater discretion by examiners to determine 
CRA scoring. For example, under CRA, the distinction between home 
improvement loans and small business loans secured by housing may not 
match HUD's definitions of mortgage purchases. In contrast, HUD does 
not use a system of examiners to determine the goals eligibility of 
sellers dealing with the GSEs, and comparison areas are established 
through regulation.
    In light of these legal constraints, HUD will not make any changes 
to the housing goals to address CRA concerns at this time.
d. Predatory Lending
    Summary of Comments. Certain commenters urged the Department to 
adopt predatory lending safeguards in the final rule that would 
prohibit Housing Goals credit for purchases of loans that included 
mandatory arbitration clauses or loans with prepayment penalties beyond 
three years towards the goals. The GSEs did not specifically mention 
this issue in their comments to HUD. HUD's proposed rule did not 
suggest changes to its existing GSE regulations that address predatory 
lending practices.
    HUD's Determination. The Department continues to vigorously oppose 
specific lending practices that are predatory or abusive in nature. As 
stated in the 2000 rulemaking, the GSEs should seek to ensure that they 
do not purchase loans that actually harm borrowers and support unfair 
lending practices. In that rulemaking, the Department determined that 
the GSEs should not receive the incentive of goals credit for 
purchasing high cost mortgages, including mortgages with unacceptable 
features.
    The Department is authorized under 24 CFR 81.16 to determine 
whether to provide full, partial, or no credit toward achievement of 
any of the housing goals for any transaction. The Department's existing 
rules contain strong safeguards against abusive lending by excluding 
certain types of mortgages from counting towards the affordable housing 
goals. These include loans with excessive fees, and prepayment 
penalties in certain loans.
    The Department is aware that certain practices that were not 
enumerated in the regulations adopted in 2000, such as loans with 
prepayment penalties after three years and loans with mandatory 
arbitration clauses, often lock borrowers into disadvantageous loan 
products. The Department will rely on existing regulatory authorities 
to monitor the GSEs' performance in this area. Should the Department 
later determine that there is a need to specifically enumerate 
additional prohibited predatory practices, it will address such 
practices at a future time.

[[Page 63631]]

e. Minority Subgoals/Goals
    Summary of Comments. Among the many suggestions HUD received for 
subgoals and bonus points, several advocacy groups recommended that HUD 
directly target minority mortgage purchases such as those made to 
Native Americans. These groups note that homeownership rates are not 
equal across ethnic groups. Fewer Blacks and Hispanics own their own 
homes than the general population. Although the GSEs have made some 
progress in this area, the GSEs are still less likely to serve high 
minority areas than other lenders. In the view of these commenters, the 
absence of the GSEs has led to higher borrowing costs and harsher 
borrowing terms for minority borrowers because they are more likely to 
deal with nontraditional and predatory lenders.
    HUD's Determination. Under FHEFSSA, HUD does not have statutory 
authority to establish goals beyond those enumerated in the statute. 
FHEFSSA directs HUD to establish a goal for underserved areas, and 
HUD's goal includes census tracts with high concentrations of minority 
households (and with median income below a certain level) as one 
category of underserved area. The statute does not empower HUD to 
establish a goal based on the characteristics of borrowers, other than 
by income of borrower.
    Even without an explicit subgoal, HUD believes that the goals 
structure will address the concerns of minority borrowers. As discussed 
in the introduction, minorities and immigrants are a growing percentage 
of homebuyers and many more aspire to home ownership. Demographics 
dictate that these buyers will become increasing shares of the 
conventional conforming market. Requiring the GSEs to lead the market 
will encourage them to do even more to reach out to minorities.
f. Technical Change to Sec.  81.16(c)(7)
    In addition to the preceding changes being made at this final rule 
stage, HUD is making a technical change to Sec.  81.6(c)(7) to correct 
a cross-reference. Paragraph (c)(7) addresses the treatment of 
refinanced mortgages. The paragraph includes a reference to Sec.  
81.14(f), which is not related to refinanced mortgages. Section 
81.16(c)(7) in this final rule is revised to correct this cross-
reference.

D. Subpart I--Other Provisions

1. Overview--Verification and Enforcement To Ensure GSE Data Integrity
    HUD proposed to amend Sec.  81.102 (Independent Verification 
Authority) of its regulations to incorporate certain data integrity 
procedures designed to ensure the accuracy, completeness, and 
timeliness of housing goal information submitted by the GSEs to the 
Department. These procedures included: (1) A requirement that the GSEs 
provide a certification with their Annual Housing Activity Reports 
(AHAR) and such other reports, data submissions, and information that 
the Department may request in writing be certified; (2) a procedure to 
adjust current year-end errors, omissions, and discrepancies in data 
submissions to HUD; and (3) a procedure for correcting prior year 
overstatements of performance due to reporting errors, omissions, or 
discrepancies in a GSE's AHAR. HUD also restated in the proposed 
amendment to Sec.  81.102 the enforcement options and remedies under 
FHEFSSA and HUD's regulations that could result from a determination 
that a GSE's data submissions, information, or reports were not 
current, were incomplete, or otherwise contained an untrue statement of 
material fact.
    In addition to comments provided by the GSEs, HUD received comments 
from groups that included mortgage lenders, non-profit and policy 
advocacy organizations, and trade associations. Most commenters 
supported the data verification provisions of the proposed rule. 
However, one mortgage lender stated that the proposed certification 
would impose a severe burden on the GSEs and lenders. Another suggested 
that the data integrity process should include some leeway for 
unintentional mistakes so that it does not become burdensome. A trade 
association stated that HUD should not enact regulations that would put 
additional data integrity burdens on lenders. Fannie Mae and Freddie 
Mac provided detailed comments on each proposal. These comments are 
discussed more fully in the following sections.
2. Independent Verification Authority--Sec.  81.102(a)
    As it proposed, the Department is retaining and recodifying the 
provisions of the current Sec.  81.102(a) that provide that HUD may 
independently verify the accuracy and completeness of data, information 
and reports submitted by a GSE in addition to the Department's existing 
authority to conduct on-site verifications and performance reviews. HUD 
is redesignating this section, as HUD proposed, as Sec.  81.102(a).
3. Certification--Sec.  81.102(b)
    To ensure the highest degree of corporate accountability, and to be 
consistent with the customary practice of regulators of financial 
institutions, the Department proposed that the GSEs be required to 
provide a certification with their AHAR reports and such other 
report(s), data submission(s), or information for which HUD requests 
certification in writing. HUD proposed a certification that consisted 
of the following four parts: (1) The GSE Certifying Official has 
reviewed the particular AHAR, other report(s), data submission(s) or 
information; (2) to the best of the GSE Certifying Official's knowledge 
and belief, the particular AHAR, other report(s), data submission(s), 
or information are current, complete, and do not contain any untrue 
statement of a material fact; (3) to the best of the GSE Certifying 
Official's knowledge and belief, the AHAR or other report(s), data 
submission(s), and information fairly present in all material respects 
the GSE's performance, as required to be reported; and (4) to the best 
of the Certifying Official's knowledge and belief, the GSE has 
identified in writing any areas in which the GSE's particular AHAR, 
other report(s), data submission(s), or information may differ from 
HUD's written articulations of its counting rules including, but not 
limited to, the regulations under 24 CFR part 81, and any other areas 
of ambiguity.
    Summary of Comments. Fannie Mae and Freddie Mac commented on this 
proposal. Each expressed many similar objections to the certification 
language as proposed and offered many similar recommendations. For 
example, both GSEs stated that the certification language was overly 
broad and should be modified to the form authorized in FHEFSSA for 
submissions to OFHEO; namely, that the report is true and correct to 
the best of such officer's knowledge and belief. Each recommended that 
the words ``fairly present'' be deleted from the third proposed 
certification statement stating that these words are meaningful only in 
the context of Generally Accepted Accounting Practices (GAAP), which 
defines standards of determining ``fairness'' in financial reporting, 
but not performance reporting.
    In addition, both GSEs questioned HUD's authority to impose a 
certification requirement, but stated that to the extent HUD does 
impose this requirement, it should be the certification used by OFHEO. 
They also stated that the phrases ``errors, omissions, discrepancies, 
and ambiguities,'' ``written articulations of its counting rules,'' and 
``any other areas of ambiguity'' are vague and undefined,

[[Page 63632]]

and that this vagueness makes it possible for HUD to arbitrarily 
implement the certification provision by interpreting it in a way that 
is not known by the GSEs. Freddie Mac also stated that HUD's informal 
written articulations are not enforceable and that it may not know 
about all of HUD's informal articulations. Both GSEs also stated that 
it is difficult to certify to the accuracy of information that must be 
included in the reports that they receive from third parties.
    Freddie Mac suggested that the subject of the certification be 
limited to the year-end annual data tables and computerized loan-level 
data that it submits with its AHARs, and should not cover any narrative 
portions of the AHARs. Fannie Mae suggested that the certification 
should focus on the process it follows for generating its submissions 
and should cover only the final tables in the AHAR that it submits each 
year.
    Both GSEs stated that no certification should be required for 
reports-in-progress, such as the housing goals progress reports each 
submits to HUD on a quarterly basis.
    A policy advocacy group commented that the certification should be 
limited to reporting processes of the GSEs, not the accuracy of the 
underlying data obtained from individual lenders. A trade association 
commented that HUD should not put additional data integrity burdens on 
lenders.
    HUD's Determination. HUD has considered the comments received and 
has determined to modify its proposal. HUD's reasons for requiring a 
certification were not disputed by commenters. However, HUD has revised 
the proposed rule language to address commenters' concerns regarding 
clarity. HUD has also included alternative language in the final rule 
that would specifically define terms as well as eliminate the language 
that the GSEs and others found to be ambiguous. As a result, the final 
rule includes a simplified certification that is much closer to the 
certification used by OFHEO. Section 81.102(b) has been amended to 
require the senior officer of each GSE who is responsible for 
submitting to HUD the fourth quarter Annual Mortgage Report and the 
AHAR under sections 309(m) and (n) of the Fannie Mae Charter Act or 
sections 307(e) and (f) of the Freddie Mac Act, as applicable, or for 
submitting to the Secretary such other report(s), data submission(s), 
or information for which certification is requested in writing by the 
Secretary to state that: ``To the best of my knowledge and belief, the 
information provided herein is true, correct and complete.''
    The Department has also included language to clarify that it may 
pursue enforcement action against a GSE that fails to provide the 
certification required under Sec.  81.102(b). In addition, the 
Department may pursue enforcement action if a GSE submits the 
certification required under Sec.  81.102(b), but the Secretary later 
determines that the data, information or report(s) are not true, 
correct and complete. For data, information and report(s) subject to 
Sec.  81.102(c) or (d), the final rule makes clear that the Department 
will only pursue enforcement action against a GSE in connection with 
material errors, omissions or discrepancies, as those terms are defined 
therein.
    The GSEs have asserted that HUD may not require certification of 
any information they submit because the Department has no express 
statutory authority to do so. The Department's authority to require 
certification of information submitted by the GSEs is authorized under 
HUD's general regulatory power over the GSEs under section 1321 of 
FHEFSSA as well as its authority to monitor and enforce the GSEs' 
compliance with the housing goals under section 1336. (See the preamble 
of HUD's proposed rule at 69 FR 24247-24248 for a full discussion of 
HUD's authority to require certification.)
    In requiring this certification, HUD is fully aware that the GSEs 
collect millions of data elements from hundreds of sources and that the 
GSEs must depend upon these sources to provide accurate data. In 
requiring a certification, HUD intends that the GSEs will use and rely 
upon their internal controls and other due diligence processes and 
procedures for collecting, compiling, verifying the accuracy of, and 
reporting the data received from sellers. HUD will evaluate the 
sufficiency of this certification beginning with the 2005 fourth 
quarter Annual Mortgage Report and the AHAR to determine whether it is 
serving its function of providing adequate assurance as to the accuracy 
and completeness of information.
    With respect to the scope of the certification, HUD believes it is 
appropriate and reasonable that the certification statement apply to 
the entire AHAR submission, including the narrative text, data tables, 
and computerized loan-level data. Section 309(n) of Fannie Mae's 
Charter Act and section 307(f) of the Freddie Mac Act specify the types 
of information each GSE is required to report, including narrative 
descriptions as well as data. HUD expects that all of the required 
information, not just the data and data tables, will be subjected to 
appropriate internal review processes by the GSEs. A certification 
regarding the entire report helps to ensure the GSEs' accountability 
for the information that they are required to report accurately under 
their charters.
    Although Fannie Mae recommended that the certification should apply 
only to the tables in the AHARs and Freddie Mac recommended that the 
certification should apply only to the data tables in the AHAR and the 
loan-level data it submits with its AHAR, from time to time HUD 
requires one or both GSEs to submit other report(s), information, or 
data submission(s) that rise to a sufficient level of importance to 
HUD's oversight work that a certification statement is warranted. The 
final rule, therefore, retains this provision and further provides that 
the Secretary will issue a written notification to the GSE whenever 
such a certification is required. HUD expects that any additional 
certification requirements will be the exception rather than the rule 
to ensure that the routine and necessary flow of information is not 
impeded.
    Both GSEs recommended that HUD not impose a certification on any 
progress reporting, such as the quarterly housing goals performance 
reports each submits to HUD. HUD did not propose that such reports be 
certified and reiterates that certification statements will not be 
required for the GSEs' first three quarterly housing goals reports and 
any other report(s), data submission(s) or information that represent 
incomplete ``snapshots'' or information that is being gathered but 
which is not in final form. Certification will be required for the 
fourth quarter report, i.e., the Annual Mortgage Report.
4. Adjustment To Correct Current Year-end Errors, Omissions or 
Discrepancies--Sec.  81.102(c)
    HUD routinely conducts computerized consistency checks of loan-
level data received from the GSEs as part of their AHAR reporting. This 
data are received on March 15th of each year for the previous year's 
performance. These reviews verify that the GSEs have applied HUD's 
counting rules and goals eligibility standards appropriately in 
determining their year-end performance. A key procedure involves 
applying HUD's counting rules to the GSEs' loan-level data for the 
purposes of replicating the performance figures computed by the GSEs in 
their AHARs. Also, in conjunction with other reports provided by the 
GSEs, including a report that reconciles all adjusted mortgage 
purchases (the denominator) with the GSE's total business volume as

[[Page 63633]]

reported in the annual report to shareholders or other information 
filings, HUD's reviews also verify the completeness of the data. If HUD 
finds discrepancies between its results and those reported by the GSEs, 
HUD works with appropriate GSE staff to resolve the discrepancies after 
which HUD makes a final determination of year-end results and publishes 
these as HUD's official performance figures for the year.
    HUD's proposed rule provided for a timeframe within which the GSEs 
may comment or otherwise respond to HUD's findings of errors, 
omissions, or discrepancies with additional information. If a GSE did 
not respond with information to correct or explain the error, omission, 
or discrepancy to HUD's satisfaction within five working days of HUD's 
initial notification, then HUD would notify the GSE in writing and seek 
clarification or additional information. At this point, the GSE would 
have 10 working days in which to respond and could request an extension 
of an additional 20 working days from HUD. If the GSE still did not 
respond in a manner that corrected the error, omission, or discrepancy, 
then HUD would determine the appropriate adjustment to the numerator 
and denominator of the applicable goal and/or subgoal. Currently, there 
are no required time limits within which the GSEs must respond to HUD's 
inquiries for additional information, and there is no procedure by 
which HUD can bring the process of reviewing a GSE's current year 
submission to closure absent voluntary assistance from the GSEs. The 
practical effect of not codifying a timetable for completion of this 
process is that HUD could be delayed in fulfilling its responsibilities 
to issue a timely, official report on the GSEs' performance for the 
year most recently ended and to produce the public use database.
    Summary of Comments. In addition to the GSEs, many organizations, 
including policy advocates, trade associations, and one non-profit 
group, commented on the data verification provisions of HUD's proposed 
rule. Nearly all of these comments supported implementation of some 
type of data verification procedures. One trade group stated that data 
verification regulations should be enforced to get more accurate 
information. However, another trade group expressed concern that the 
data integrity process should include some leeway for unintentional 
mistakes to avoid becoming burdensome. Two advocacy organizations 
supported the proposed provisions regarding data verification but 
thought HUD should give the public the ability to comment on the GSEs' 
AHARs.
    Both GSEs commented in detail on HUD's proposal. Both expressed 
concerns about the scope of this provision and questioned what 
procedures, especially adjustment notification and enforcement 
procedures, would be associated with its implementation. Freddie Mac 
augmented its comments with a legal opinion from outside counsel.
    With respect to the words ``errors, omissions and discrepancies,'' 
the GSEs contended that these terms were vague and needed further 
definition. Freddie Mac stated that without such further definition, 
HUD could disallow counting of units based upon interpretations of its 
rules of which Freddie Mac was unaware, and thus violate the fair 
notice doctrine. Freddie Mac suggested that if HUD retained the use of 
these words in its regulation, it should explain how their meanings 
differ. Fannie Mae stated that potential adjustments should apply only 
to situations where the GSE failed to follow HUD's rules for data 
collection and reporting, and not where it failed to follow its own 
rules for procedures in data collection and reporting. Fannie Mae also 
contended that adjustments should be made only where the error, 
omission or discrepancy was in a data field that affected scoring and 
where it also had a material effect on compliance with a housing goal. 
Freddie Mac stated that adjustments should be made only for material 
errors or omissions. Fannie Mae stated that a GSE should be subject to 
additional enforcement action only when an error, omission or 
discrepancy is due to intentional or bad faith action.
    Both GSEs stated that HUD's regulations should provide that HUD 
will issue a written determination to a GSE when it determines that an 
adjustment is necessary, that HUD should specify which official within 
HUD is authorized to issue orders under proposed Sec.  81.102(c) and 
(d), and that the rule should provide for more lenient time frames for 
responding to HUD's inquiries. In addition, Freddie Mac commented that 
the regulations should state that an order requiring an adjustment 
constitutes ``final agency action'' for purposes of judicial review 
under the Administrative Procedure Act and that judicial review is 
immediately available.
    Fannie Mae also commented on the title of HUD's provision stating 
that a provision to correct ``current year end errors'' is confusing 
because HUD cannot correct errors for a current year when it does not 
receive the data about any current year until the next year.
    HUD's Determination. HUD has considered the comments and determined 
that a provision specifying what procedures HUD will use in developing 
its official performance numbers for the immediately preceding year is 
necessary. HUD notes that many of the concerns expressed by commenters, 
especially the GSEs, involve the lack of definition of the terms 
``errors, omissions or discrepancies'' and a lack of clarity regarding 
how the regulation will be enforced. Accordingly, in the final rule, 
HUD has added a paragraph that defines an ``error'' as a technical 
mistake, such as a mistake in coding or calculating data. Mistakes of 
this type may also include, but not be limited to, systems errors, such 
as those related to geocoding or misapplication of HUD's most current 
data regarding median income or underserved areas. An ``omission'' is 
defined as a GSE's failure to count units in the denominator. A 
``discrepancy'' is defined as any difference between HUD's analysis of 
data and the analysis contained in a GSE's submission of data, 
including a discrepancy in goal and/or Special Affordable subgoal 
performance.
    The Department also clarifies in Sec.  81.102(c)(5) of this final 
rule that an error, omission or discrepancy is ``material'' if it 
results in an overstatement of credit for a housing goal or Special 
Affordable subgoal and, without such overstatement, the GSE would have 
failed to meet such housing goal or Special Affordable subgoal for the 
immediately preceding year. Finally, the rule defines the term ``year-
end data'' to mean data that HUD receives from the GSEs related to 
housing goals performance in the immediately preceding year and 
covering data reported in the fourth quarter Annual Mortgage Report and 
the GSE's AHAR.
    With respect to procedures for notifying a GSE of any suspected 
error, omission or discrepancy, HUD is responding to the concerns 
raised by the commenters by amending the proposed rule to: (1) Provide 
that, with regard to each initial notification by HUD to a GSE, HUD 
may, in its own discretion, or upon a request by a GSE, extend the 
initial five working day response period for up to 20 additional 
working days; (2) establish that any person with delegated authority 
from the Secretary, or the Director of HUD's Financial Institution 
Regulation Division, or his or her designee, is responsible for issuing 
initial notifications regarding errors, omissions, or discrepancies, 
making determinations on the adequacy of responses received, approving 
any extensions of time permitted under this

[[Page 63634]]

provision, and generally managing the data verification process; (3) 
establish that the Secretary or his designee will inform a GSE in 
writing of HUD's determination of official performance figures, 
including any adjustments, five working days prior to HUD's release of 
its official performance figures to the public; (4) provide that during 
the five working days prior to such public release, a GSE may request 
reconsideration in writing of HUD's final determination of its 
performance in which case the Secretary will decide whether to grant 
the request for reconsideration, and if the request is granted, make a 
final determination on the request for reconsideration within 10 
working days of the Secretary's granting of the GSE's request for 
reconsideration; and (5) provide that, with the exception of the 
written determination of HUD's official performance figures, all other 
notifications under this provision may be by electronic mail.
    HUD has also clarified through its definitions of errors, omissions 
and discrepancies, that an ``adjustment'' will be made in situations 
where a GSE failed to follow correct procedures in data compilation and 
reporting and/or where it failed to comply with HUD's regulation for 
determining eligible units. As has been the case in the past, HUD 
expects that any adjustments that it may make to the numerator or 
denominator, that result in a difference between the GSE's performance 
as stated in the GSE's AHAR for the immediately preceding year and 
HUD's official performance figures, will be well understood by the GSE 
because adjustments of this type occur routinely during HUD's 
verification work.
    HUD is also clarifying that it intends to treat a GSE's material 
errors, omissions or discrepancies in, or failure to certify, data 
submissions under Sec.  81.102(c) as a failure to submit information 
that the GSE is required to submit under its charter. Accordingly, the 
Department may pursue the additional enforcement remedies authorized 
under Sec.  81.102(e).
    With respect to events that could trigger enforcement under this 
provision, HUD does not intend that routine technical errors or 
omissions would warrant such enforcement. In order to trigger the 
enforcement provision, errors, omissions or discrepancies discovered 
during review of the immediately preceding year's performance must be 
material, as HUD has defined that term. The error, omission or 
discrepancy also must be one that indicates to HUD a serious problem in 
the GSE's internal procedures. Examples of errors, omissions, or 
discrepancies that could rise to this level under these criteria 
include a GSE counting units that are not eligible under HUD's rules 
for goals credit or a GSE underreporting units in the denominator. With 
respect to Freddie Mac's suggestion that HUD's regulations should state 
that this determination is ``final agency action'' for purposes of the 
Administrative Procedure Act and is immediately subject to judicial 
review, FHEFSSA already provides that the GSEs may obtain judicial 
review in connection with proceedings to enforce the housing goals, and 
that those proceedings shall be governed by the Administrative 
Procedure Act. Therefore, the Department declines to adopt Freddie 
Mac's suggestion.
    To more clearly define the scope of this provision, HUD has renamed 
this provision in the final rule as Verification Procedure and 
Adjustment to Correct Errors, Omissions, or Discrepancies in AHAR Data 
for the Immediately Preceding Year.
5. Procedures for Prior Year Reporting Errors--Sec.  81.102(d)
    The annual data verification review for the immediately preceding 
year described in Sec.  81.102(c) was designed to ensure that reported 
goals performance was correctly calculated in accordance with HUD's 
regulations. Although these reviews can test for the reasonableness of 
some reported data, the reviews cannot generally determine the accuracy 
of the underlying loan-level data. To monitor data accuracy, HUD has 
implemented a second type of procedure, called performance reviews. 
Performance reviews are especially necessary because housing goals are 
calculated from information (e.g., number of dwelling units) that is 
not reported in the GSEs' financial statements and is, therefore, not 
subject to all GSE procedures designed to ensure the accuracy and 
completeness of reported financial information. HUD's performance 
reviews ensure that rigorous audit procedures, either similar or 
identical to those used to monitor the integrity of financial data, are 
also used in monitoring the accuracy, completeness, and timeliness of 
the data each GSE submits to HUD. Performance reviews include, but are 
not limited to, evaluating the GSEs' internal controls over the 
collection, management and reporting of loan-level mortgage data used 
in calculating housing goals performance. Performance reviews may also 
focus on the GSEs' quality control standards and procedures for 
information received from loan sellers and securities issuers and 
dealers and may include additional procedures to test random samples of 
data for accuracy and completeness. To supplement HUD's on-site 
performance review work, the Department has implemented specialized 
reporting by which each GSE informs HUD on a scheduled basis of key 
issues and findings relevant to goals reporting. For example, the GSEs 
report to HUD quarterly on the results of their own internal reviews 
and self-assessments related to housing goals. These reports cover all 
actions taken by the GSE to remove any findings related to weaknesses 
in controls or procedures, including those findings identified by HUD.
    Because of the complexity of each GSE's business, as well as the 
complexity of many of the transactions that the GSEs undertake to meet 
their housing goals, there is a possibility that HUD may discover, 
during a performance review, that a serious overstatement of credit 
towards one or more housing goals occurred in the reported prior year 
under review. Currently, HUD has no procedure for ensuring that any 
such overstatement is corrected or otherwise adjusted in some manner 
unless the overstatement is discovered in the review of the immediately 
past year's data during the replication review described in Sec.  
81.102(c). To remedy this, HUD proposed a procedure that would adjust a 
GSE's current year performance by deducting from the numerator of the 
relevant housing goal or subgoal the number of overstated units from a 
prior year. A prior year was any one of the two years preceding the 
current reporting year.
    Summary of Comments. Many organizations commented on HUD's data 
integrity provisions in general and nearly all of these organizations 
expressed support for data verification. The GSEs commented more 
specifically on HUD's proposals for adjustments to make up prior years' 
overstatements. The GSEs asserted that the Department does not have 
authority to either deduct credit from a current year's purchase that 
is entitled to credit under HUD's regulations or add to a current 
year's housing goal to compensate for the GSE's failure to meet its 
goals in a prior year. They also had other objections, including the 
objection that the only remedy provided in FHEFSSA for any failure to 
meet housing goals is the imposition of a housing plan, which may 
address only a probable failure to meet housing goals in the current 
year or actual failure to meet goals in a current year in the next 
calendar year.

[[Page 63635]]

The GSEs stated that the Congress intended the statute to provide no 
remedy for their failure to meet a prior year's housing goal and, 
therefore, that the Department has no authority to fashion such a 
remedy. Based on this line of reasoning, they concluded that HUD may 
not take any action against a GSE when it discovers that it failed to 
meet a housing goal in a prior year, even though HUD could have taken 
action if the failure had been discovered within one year after the 
year in which it occurred.
    Both GSEs also objected to the policy basis for HUD's proposal. For 
instance, Fannie Mae wanted the time period within which HUD might 
impose a prior-year correction shortened from up to 24 months to three 
months after HUD's receipt of AHAR loan-level data, which HUD receives 
on March 15th of each year. Fannie Mae cited OFHEO's ability to render 
a decision on its final capital classification within 90 days of the 
reporting quarter as evidence that complex determinations can be made 
within short time frames. Freddie Mac saw no reason why the necessary 
evaluations could not be accomplished within six months after the close 
of the immediately preceding year. Freddie Mac stated that HUD's policy 
justification does not support the proposal and that HUD did not point 
to any instance where the increasing complexity of transactions has led 
to overstatements in performance. Freddie Mac also commented that the 
Department already has the option of publicizing the discovery of any 
prior year mistakes--by press release, news conference or its Web site 
information--and of making Congress aware of these mistakes.
    Freddie Mac requested that HUD withdraw the proposal entirely. If 
HUD opted to proceed to implement the proposal, then Freddie Mac 
suggested that HUD amend the provision to: (1) Limit application of the 
rule to large prior year overstatements that affect a material number 
of units under a goal (e.g., five percent); (2) provide that HUD will 
apply the rule only when a GSE acted in bad faith; (3) provide that HUD 
will not apply the rule cumulatively; that is, that HUD will not 
accumulate several years' over-counts and then deduct a cumulative 
total from the current year; and (4) clarify in the final rule which 
official within HUD will make decisions under this provision and 
provide that the basis for decisions be explained.
    HUD's Determination. HUD has carefully considered both GSEs' 
comments, including their legal and policy arguments. The Department 
agrees that the only remedy Congress set out in FHEFSSA for failing to 
meet a housing goal is a housing plan under section 1336, and as the 
statute is written, the housing plan addresses only a current year's 
failure, either in that year or in the next calendar year. Therefore, 
the statute does not specifically address a GSE's failure to meet a 
housing goal in a prior year, i.e., a failure occurring in any one of 
the two years immediately preceding the latest year for which data on 
housing goals performance was reported to HUD. However, the Department 
does not agree that Congressional silence on this precise issue means 
either that Congress intended the GSEs to be allowed to fail to meet 
their housing goals as long as the Department does not discover that 
failure within a specific time or that the Department may not fashion a 
remedy to address this issue. This conclusion runs counter to 
Congress's purposes in enacting FHEFSSA, which directs HUD to establish 
and monitor the GSEs' compliance with the Housing Goals.
    Section 1336 of FHEFSSA provides that the Secretary shall ``monitor 
and enforce'' the GSEs'' compliance with the housing goals set by the 
Department. According to FHEFSSA's legislative history, in enacting 
FHEFSSA Congress intended ``to establish a comprehensive framework of 
goals, data collection, reporting requirements and enforcement 
provisions.'' S. Rep. No. 102-282, at 34 (1992)(emphasis added).
    When discussing the GSEs' duties to meet housing goals set for low- 
and moderate-income housing and housing in central cities and rural 
areas, Congress stated:

    The GSEs need to provide more leadership in all of these areas, 
and they have indicated a desire to do so. But direct and 
potentially forceful federal oversight is the only way to ensure 
that it will happen. Id. at 11.

    Under the GSEs' suggested construction of FHEFSSA, HUD's ability to 
enforce the housing goals is totally dependent upon only one factor, 
namely how quickly HUD discovers that a GSE has failed to meet a goal. 
In order to determine whether a GSE has failed a goal, HUD must 
receive, verify and analyze massive amounts of data, as described 
above. Under the GSEs' suggested construction of FHEFSSA, only if HUD 
discovers that a GSE has failed to meet a housing goal or subgoal in 
the nine month period that runs from March 15th, when the GSEs submit 
current year-end data, to the end of that year--may HUD enforce the 
housing goals for that year. Such a construction is not only 
unreasonable on its face but it is contrary to the plain intent of 
Congress as expressed in the FHEFSSA and its legislative history. 
FHEFSSA and its legislative history indicate that Congress established 
a comprehensive regulatory scheme under which HUD would establish and 
enforce the Housing Goals through strict and pervasive regulation.
    Furthermore, there is absolutely no statement in FHEFSSA or its 
legislative history to suggest that Congress intended that HUD must 
ignore or forgive a GSE's failure to meet its housing goals in any year 
for any reason, including the passage of a certain amount of time 
before HUD discovers this failure. The fact that FHEFSSA is silent on 
the issue of how to address a GSE's failure to meet a prior year's 
housing goal means that there is a gap in FHEFSSA's enforcement scheme 
regarding this precise issue. Under Chevron v. NRDC, 467 U.S. 837 
(1984), the Department has discretion to fashion an appropriate remedy 
to fill this gap, and it has done so in Sec.  81.102(d). Moreover, the 
Department has the discretion to fashion a remedy to correct prior year 
overstatements without which a GSE would have failed to meet a housing 
goal or Special Affordable subgoal under its general regulatory powers 
under section 1321 of FHEFSSA.
    However, in light of the objections raised to the proposed 
regulation in the comments discussed above, HUD has revised Sec.  
81.102(d) to remove provisions that either provide for deduction of 
Housing Goals credit in a current year from purchases that qualify for 
credit, or that add requirements to a current year's Housing Goals due 
to errors, omissions or discrepancies in a prior year's data 
submissions. The final rule provides instead that the Secretary may 
require the GSEs to make up any overstatements of goal performance 
without which a GSE would have failed to meet a prior year's Housing 
Goal, no later than the year following the year in which HUD first 
notifies the GSE of this failure. (The rule now defines the term 
``prior year'' to mean any one of the two years immediately preceding 
the latest year for which data on housing goals performance was 
reported to HUD.)
    In order to remedy this failure, the Secretary may require the GSEs 
to purchase additional mortgages that finance a number of units that 
either (a) equal the number of units overstated in the prior year's 
goal performance, or for the Special Affordable subgoals the number or 
dollar amount, as applicable, of mortgage purchases that the Secretary 
has determined were overstated, or (b) that equal the percentage of the 
overstatement in the prior year's goal

[[Page 63636]]

performance as applied to the most current year-end performance, 
whichever is less. Units purchased to remedy an overstatement must be 
eligible to qualify under the same goal or goals for which the 
overstatement occurred in the prior year. For example, a GSE may have 
overstated a prior year's performance by 5,000 units or .22 percent 
under the Low- and Moderate-Income Goal. To make up this overstatement, 
a GSE may purchase an additional 5,000 units that are eligible under 
the Low- and Moderate-Income Goal in the year immediately following the 
year in which HUD notifies the GSE of the overstatement or it may 
multiply the current year's total eligible purchases under the Low- and 
Moderate-Income Goal by the overstated percentage from a prior year 
(e.g., .22 percent) to determine the number of units that must be 
purchased, provided this number is less than 5,000 units. The same 
requirement also applies to the Special Affordable Home Purchase 
Subgoal. When an overstatement occurs under this Subgoal, the Secretary 
may require the GSE to make up the number of mortgages that were 
overstated using the lesser of the two procedures previously described. 
For overstatements under the Special Affordable Multifamily Subgoal, 
the GSE may be required to make up the dollar amount of overstatement 
by purchasing qualifying multifamily mortgages in an amount equal to 
the overstatement. The GSEs will not be required to make up any errors, 
omissions or discrepancies in prior years that were not material. As 
previously noted, the final rule provides that an error, omission or 
discrepancy is material if it results in an overstatement of credit for 
a housing goal or Special Affordable subgoal and, without such 
overstatement, the GSE would have failed to meet such housing goal or 
Special Affordable subgoal for the prior year.
    Also, corrections for overstatement of goals performance under this 
provision will not be counted or reported under the GSEs' Annual 
Housing Activity Report, including calculation of housing goal 
performance in any year, but rather will be managed separately from the 
housing goals as directed by HUD.
    If the GSE does not purchase a sufficient number of eligible units 
or mortgages, as described previously, then HUD may issue a notice that 
the GSE failed a housing goal or subgoal in a previous year, or seek 
additional enforcement remedies under Sec.  81.102(e) or any other 
civil or administrative remedies that are available under applicable 
law. The Department is treating a GSE's material errors, omissions or 
discrepancies in, or failure to certify, a prior year's data submission 
as a failure to submit information that the GSE is required to submit 
under its charter.
    Both GSEs also questioned the need for an adjustment period that 
could extend for up to 24 months from the close of a calendar year's 
performance, believing instead that any such review could be 
accomplished within six months of the close of the previous year, which 
is a time frame similar to that used by OFHEO to assess the adequacy of 
a GSE's capital. As HUD has stated previously, reviews conducted 
immediately upon receipt of a GSE's prior year loan-level data and 
pursuant to Sec.  81.102(c) cannot generally gauge the accuracy of the 
data and cannot always determine whether the transaction itself 
complies with HUD's regulations for counting units towards goals 
performance. Assessments of this type require the application of 
procedures, either in whole or in part, that are characteristic of 
audit engagements. For example, it is customary for audits of a 
previous year's financial statements to require up to one year or more 
for completion due to the number of procedures involved and the volume 
of information to be reviewed, especially for exceedingly large and 
complex organizations. Similarly, the relatively new field of 
performance data auditing, including reviews based on some or all of 
these procedures, also requires a substantial commitment of time and 
resources if meaningful results are to be obtained. For these reasons, 
performance reviews are not analogous to OFHEO's evaluations of capital 
adequacy. HUD believes that its original proposal of allowing for up to 
24 months after the close of the year under review is the appropriate 
time frame for completion of the performance review.
    The GSEs also expressed some concerns about the potential for HUD 
to make determinations of error after the fact and without any prior 
notice to a GSE that a type of transaction and/or housing unit would 
not be eligible for goals credit. HUD believes it is useful to more 
fully describe the types of errors likely to trigger a finding that 
units were overstated. In the context of performance reviews, the words 
``errors, omissions or discrepancies'' connote serious mistakes, such 
as those associated with violations of HUD's counting rules and other 
goals eligibility criteria as set forth in its regulations. HUD is 
aware that in collecting and reporting millions of data elements, some 
level of factual error is probably unavoidable. However, with regard to 
data accuracy in performance reviews, HUD is concerned with errors of a 
substantial nature, such as those that suggest a larger internal 
control problem, an example of which could be a pattern of incorrect 
rental data acquired from or generated by the same source. HUD is also 
concerned with types of transactions that are either expressly 
prohibited from goals eligibility, such as high cost mortgages, or for 
which HUD approval may have been required but not obtained prior to a 
GSE counting the units, such as the use of an affordability estimation 
methodology. Other similar types of problems may also trigger a HUD 
determination of error. In the event HUD supplements its regulations 
with letters to one or both GSEs regarding appropriate counting 
treatment, the GSE will be responsible for complying with only the 
specific directives it has received from HUD. In the final rule, HUD 
has reiterated that this procedure will apply only in those instances 
where an overstatement was material in nature; that is, the overstated 
units enabled the GSE to meet a housing goal that it otherwise would 
not have met. In the event that HUD undertakes a performance review 
that covers a two-year period and determines that material 
misstatements of housing goals or Special Affordable subgoals 
performance occurred in both years, then HUD will apply the same 
procedures as described previously for making up the overstatements. 
Upon a written request from a GSE, the Secretary may, in his 
discretion, determine to grant an extension of additional time to 
correct or compensate for the overstatement. For example, if 
overstatements were discovered for years 2005 and 2006 and the GSE is 
notified of the overstatements for both years in 2007, then the GSE 
could be required to make up the overstatements for both years in 2008. 
Similarly, if the overstatement was discovered for one year, 2005, and 
the GSE was notified of the overstatement in 2006, then the GSE could 
be required to make up the overstated units or mortgages in 2007. In 
both examples, upon receipt of a GSE's written request for an extension 
of time, the Secretary may grant an extension for completing make up of 
the overstated units or mortgages.
    With regard to HUD's reasons for implementing a procedure that 
provides a mechanism by which overstated units of a material nature 
from a prior year can be made up in a subsequent year following the 
year a GSE is first notified of the overstated units, for reasons 
stated above, it is the Department's view

[[Page 63637]]

that it has authority to do so, and that the procedure is needed at 
this time. The procedure is the only tool by which HUD can meet its 
statutory responsibility to assure the integrity of all of the housing 
goal data reported to the public, including the data reported in the 
GSE public use database and its duty to enforce the housing goals.
6. Additional Enforcement Option Sec.  81.102(e)
    The Department proposed a new Sec.  81.102(e) that would provide 
HUD with additional enforcement options in the event it determines that 
a GSE has submitted data, information, or report(s) that are not 
current, are incomplete, or otherwise contain an untrue statement of 
material fact. Section 81.102(e) identified the data, information, or 
report(s) that would be subject to HUD's additional enforcement 
authority as those required under section 307(e) and (f) of the Freddie 
Mac Act, section 309(m) or (n) of the Fannie Mae Charter Act, or under 
24 CFR part 81, subpart E.
    The Department indicated in proposed Sec.  81.102(e) that it could 
make a determination--either under its independent verification 
authority in Sec.  81.102(a) or by ``other means''--that such data, 
information or report(s) are not current, are incomplete, or otherwise 
contain an untrue statement of material fact. This reference to ``other 
means'' was intended to encompass the Secretary's authority under the 
three other provisions in Sec.  81.102 that were also being proposed to 
ensure the accuracy, truthfulness and completeness of GSE submissions 
to HUD: (1) The proposed GSE certification in Sec.  81.102(b); (2) the 
proposed procedure established in Sec.  81.102(c) to verify the 
accuracy and completeness of the GSE's current year-end data; and (3) 
the proposed procedure established in Sec.  81.102(d) to ensure the 
accuracy and completeness of the GSE's prior years' data.
    The Department further provided in Sec.  81.102(e) that the 
Secretary could regard a GSE's submission of data, information or 
report(s) that he or she determines under Sec.  81.102(a), or by 
``other means'' (i.e., pursuant to paragraphs (b), (c) or (d) of Sec.  
81.102), are not current, are incomplete, or that otherwise contain an 
untrue statement of material fact to be equivalent to the GSE's failure 
to submit such data. As a result of such failure of submission, 
proposed Sec.  81.102(e) provided that the Department could initiate 
against the GSE, in accordance with the procedures in 24 CFR part 81, 
subpart G, an order to cease and desist, an action to seek civil money 
penalties, or any other remedies or penalties that may be available to 
the Secretary as a result of the GSE's failure to provide data 
submissions, information, and/or report(s) in accordance with Sec.  
81.102.
    Summary of Comments. Several organizations commented, generally, on 
HUD's proposed requirements in Sec.  81.102 for ensuring the accuracy 
and integrity of GSE data and other submissions, and almost all 
expressed support for HUD's proposals relating to data verification. 
The GSEs commented more specifically on HUD's proposal in Sec.  
81.102(e) relating to additional enforcement options.
    Fannie Mae asserted that HUD's proposed additional enforcement 
options were overly broad, and exceeded the Department's authority 
under FHEFSSA to issue cease and desist orders, impose civil money 
penalties, and to punish GSE noncompliance by requiring the adoption of 
a housing plan. Fannie Mae stated that, if HUD decided to retain Sec.  
81.102(e), this provision should be redrafted more narrowly.
    Freddie Mac, through a legal opinion prepared by outside counsel, 
asserted that sections 1341 and 1345 of FHEFSSA provide a two-step 
process before a GSE's failure to submit a housing plan, or its failure 
to comply with a feasible housing plan, could result in the 
Department's initiating an action for a cease and desist order or civil 
money penalties. Freddie Mac asserted that HUD's proposal expanded its 
enforcement authority beyond the FHEFSSA statutory limits by 
eliminating this two-step process. Freddie Mac also contended that 
HUD's enforcement powers under sections 1341 and 1345 of FHEFSSA extend 
only to instances of intentional non-compliance by the GSE, and that 
Sec.  81.102 should be narrowed to reflect this limitation.
    HUD's Determination. The Department has considered the GSEs' and 
other comments on Sec.  81.102(e) and is making several changes in this 
final rule in response to these comments. In addition, the Department 
is making a number of conforming changes to Sec.  81.102(e) to reflect 
changes that it has also decided to adopt in connection with the other 
provisions in Sec.  81.102 (primarily in paragraphs (b), (c) and (d)), 
and is also making minor editorial corrections.
    Specifically, the Department is providing in this final rule that:
    The Department may pursue additional enforcement remedies under 
paragraph (e) under either of the following circumstances: (1) When a 
GSE fails to submit the certification required by Sec.  81.102(b) in 
connection with data, information or report(s) required by section 
309(m) or (n) of the Fannie Mae Charter Act, section 307(e) or (f) of 
the Freddie Mac Act, or under 24 CFR part 81, subpart E; or (2) when a 
GSE submits the certification required by Sec.  81.102(b) in connection 
with such data, information or report(s), but the Secretary later 
determines that the data, information or report(s) are not ``true, 
correct and complete'' as provided in the certification. The final rule 
provides that, under either of the above two circumstances, the 
Secretary may regard a GSE's actions as tantamount to a failure to 
submit the data, information or report(s) which, in turn, authorizes 
the Secretary to take the additional enforcement remedies described in 
Sec.  81.102(e).
    The final rule also clarifies that for data, information or 
report(s) that are subject to Sec.  81.102(c) or (d), the Secretary may 
only pursue additional enforcement remedies in connection with material 
errors, omissions or discrepancies. Moreover, if the data, information 
or report(s) are subject to Sec.  81.102(d), the rule provides that the 
Secretary may only pursue additional enforcement remedies if the GSE 
has failed to purchase a sufficient amount or type of mortgages as 
required by the Secretary under Sec.  81.102(d)(4).
    It is the Department's view that Sec.  81.102(e) is needed so that 
it can take appropriate action to ensure the accuracy and completeness 
of the GSEs' submissions to HUD, and also to implement the 
certification that is now established at Sec.  81.102(b) of this final 
rule, while providing the Secretary with sufficient flexibility to 
exercise his or her discretion to determine whether enforcement action 
is appropriate in each instance.
    The final rule clarifies that the proposed rule's reference in 
paragraph (e)(1) to ``other means'' by which the Secretary may 
determine that a GSE's data submission(s), information or report(s) 
fail to meet the prescribed regulatory standards is meant to refer to 
the Secretary's determinations under paragraphs (b), (c) or (d) of 
Sec.  81.102 (i.e., the GSE certification in Sec.  81.102(b), the 
procedure established in Sec.  81.102(c) to verify the accuracy and 
completeness of the GSE's data for the immediately preceding year, and 
the procedure established in Sec.  81.102(d) to ensure the accuracy and 
completeness of the GSE's prior years' data). In the final rule, the 
Department has deleted the reference to ``other means'' and has 
included a specific reference to paragraphs (b), (c) or (d) of Sec.  
81.102.

[[Page 63638]]

    The final rule establishes a bifurcated approach with respect to 
the types of additional enforcement remedies that the Department may 
pursue under paragraph (e). This bifurcated approach recognizes that 
the Department's ability to pursue a cease and desist order, or to levy 
civil money penalties, applies specifically to data required by section 
309(m) or (n) of the Fannie Mae Charter Act or section 307(e) or (f) of 
the Freddie Mac Act. The rule nevertheless provides that the Department 
may pursue other types of remedies against a GSE in connection with 
data that the GSE is required to submit under 24 CFR part 81, subpart 
E, but that the GSE is not required to submit under section 309(m) or 
(n) of the Fannie Mae Charter Act or section 307(e) or (f) of the 
Freddie Mac Charter Act.
    The final rule provides that, in connection with either of the two 
remedial approaches now described in Sec.  81.102(e)(2), the Secretary 
may pursue any civil or administrative remedies or penalties against 
the GSE that may be available to the Secretary by virtue of either of 
the circumstances described in 81.102(e)(1). If the Department elects 
to pursue a cease-and-desist order or civil money penalties against a 
GSE under Sec.  81.102(e)(2)(i)(A) or (B), it will comply with the 
procedures applicable to such actions under 24 CFR part 81, subpart G. 
Alternatively, if the Department elects to pursue other civil or 
administrative remedies against a GSE under either Sec. Sec.  
81.102(e)(2)(i)(C) or 81.102(e)(2)(ii), it will pursue such remedies in 
accordance with applicable law.
    Finally, the Department is replacing in paragraph (e) each 
reference to ``HUD'' with a reference to ``the Secretary.'' This 
replacement is designed to ensure that any additional enforcement 
action that may be pursued under Sec.  81.102(e) will be considered at 
the highest levels within the Department.

III. Findings and Certifications

Executive Order 12866

    The Office of Management and Budget (OMB) reviewed this final rule 
under Executive Order 12866, Regulatory Planning and Review, which the 
President issued on September 30, 1993. This rule was determined to be 
economically significant under E.O. 12866. Any changes made to this 
rule subsequent to its submission to OMB are identified in the docket 
file, which is available for public inspection between 8 a.m. and 5 
p.m. weekdays in the Office of the Rules Docket Clerk, Office of 
General Counsel, Room 10276, Department of Housing and Urban 
Development, 451 Seventh Street, SW., Washington, DC. The Economic 
Analysis prepared for this rule is also available for public inspection 
in the Office of the Rules Docket Clerk and on HUD's Web site at http://www.hud.gov.

Congressional Review of Regulations

    This rule is a ``major rule'' as defined in Chapter 8 of 5 U.S.C. 
This rule will be submitted for Congressional review in accordance with 
this chapter.

Paperwork Reduction Act

    HUD's collection of information on the GSEs' activities has been 
reviewed and authorized by OMB under the Paperwork Reduction Act of 
1995 (44 U.S.C. 3501-3520), as implemented by OMB in regulations at 5 
CFR part 1320. The OMB control number is 2502-0514.

Environmental Impact

    This final rule does not direct, provide for assistance or loan and 
mortgage insurance for, or otherwise govern or regulate real property 
acquisition, disposition, leasing, rehabilitation, alteration, 
demolition, or new construction; or establish, revise, or provide for 
standards for construction or construction materials, manufactured 
housing, or occupancy. Accordingly, under 24 CFR 50.19(c)(1), this rule 
is categorically excluded from environmental review under the National 
Environmental Policy Act of 1969 (42 U.S.C. 4321).

Regulatory Flexibility Act

    The Secretary, in accordance with the Regulatory Flexibility Act (5 
U.S.C. 605(b)), has reviewed this rule before publication and by 
approving it certifies that this rule would not have a significant 
economic impact on a substantial number of small entities. This rule is 
applicable only to the GSEs, which are not small entities for purposes 
of the Regulatory Flexibility Act. Therefore, the rule does not have a 
significant economic impact on a substantial number of small entities 
within the meaning of the Regulatory Flexibility Act.

Executive Order 13132, Federalism

    Executive Order 13132 (``Federalism'') prohibits, to the extent 
practicable and permitted by law, an agency from promulgating a 
regulation that has federalism implications and either imposes 
substantial direct compliance costs on state and local governments and 
is not required by statute, or preempts state law, unless the relevant 
requirements of section 6 of the executive order are met. This rule 
does not have federalism implications and does not impose substantial 
direct compliance costs on state and local governments or preempt state 
law within the meaning of the executive order.

Unfunded Mandates Reform Act

    Title II of the Unfunded Mandates Reform Act of 1995 (12 U.S.C. 
1531-1538) (UMRA) establishes requirements for federal agencies to 
assess the effects of their regulatory actions on state, local, and 
tribal governments, and the private sector. This rule would not impose 
any federal mandates on any state, local, or tribal government, or on 
the private sector, within the meaning of UMRA.

List of Subjects in 24 CFR Part 81

    Accounting, Federal Reserve System, Mortgages, Reporting and 
recordkeeping requirements, Securities.


0
For the reasons discussed in the preamble, HUD is amending 24 CFR part 
81 as follows:

PART 81--THE SECRETARY OF HUD'S REGULATION OF THE FEDERAL NATIONAL 
MORTGAGE ASSOCIATION (FANNIE MAE) AND THE FEDERAL HOME LOAN 
MORTGAGE CORPORATION (FREDDIE MAC)

0
1. The authority citation for 24 CFR part 81 continues to read as 
follows:

    Authority: 12 U.S.C. 1451 et seq., 1716-1723h, and 4501-4641; 28 
U.S.C. 2461 note; 42 U.S.C. 3535(d) and 3601-3619.


0
2. In Sec.  81.2(b), revise the definitions of ``Metropolitan area'' 
and ``Minority,'' and paragraph (2) of the definition of ``Underserved 
area,'' and add a new definition of the term ``Home Purchase 
Mortgage,'' in alphabetical order, to read as follows:


Sec.  81.2  Definitions.

* * * * *
    (b) * * *
    Home Purchase Mortgage means a residential mortgage for the 
purchase of an owner-occupied single-family property.
* * * * *
    Metropolitan area means a metropolitan statistical area (``MSA''), 
or a portion of such an area for which median family income estimates 
are published annually by HUD.
    Minority means any individual who is included within any one or 
more of the following racial and ethnic categories:
    (1) American Indian or Alaskan Native--a person having origins in 
any of the original peoples of North and South America (including 
Central

[[Page 63639]]

America), and who maintains tribal affiliation or community attachment;
    (2) Asian--a person having origins in any of the original peoples 
of the Far East, Southeast Asia, or the Indian subcontinent, including, 
for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, 
the Philippine Islands, Thailand, and Vietnam;
    (3) Black or African American--a person having origins in any of 
the black racial groups of Africa;
    (4) Hispanic or Latino--a person of Cuban, Mexican, Puerto Rican, 
South or Central American, or other Spanish culture or origin, 
regardless of race; and
    (5) Native Hawaiian or Other Pacific Islander--a person having 
origins in any of the original peoples of Hawaii, Guam, Samoa, or other 
Pacific Islands.
* * * * *
    Underserved area means * * *
    (2) For purposes of the definition of ``Rural area,'' a whole 
census tract, a Federal or State American Indian reservation or tribal 
or individual trust land, or the balance of a census tract excluding 
the area within any Federal or State American Indian reservation or 
tribal or individual trust land, having:
    (i) A median income at or below 120 percent of the greater of the 
State non-metropolitan median income or the nationwide non-metropolitan 
median income and a minority population of 30 percent or greater; or
    (ii) A median income at or below 95 percent of the greater of the 
State non-metropolitan median income or nationwide non-metropolitan 
median income.
* * * * *

0
3. In Sec.  81.12, revise the last sentence of paragraph (b) and revise 
paragraph (c), to read as follows:


Sec.  81.12  Low- and Moderate-Income Housing Goal.

* * * * *
    (b) Factors. * * * A statement documenting HUD's considerations and 
findings with respect to these factors, entitled ``Departmental 
Considerations to Establish the Low- and Moderate-Income Housing 
Goal,'' was published in the Federal Register on November 2, 2004.
    (c) Goals. The annual goals for each GSE's purchases of mortgages 
on housing for low- and moderate-income families are:
    (1) For the year 2005, 52 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Low- and 
Moderate-Income Housing Home Purchase Subgoal, 45 percent of the total 
number of home purchase mortgages in metropolitan areas financed by 
that GSE's mortgage purchases shall be home purchase mortgages in 
metropolitan areas which count toward the Low- and Moderate-Income 
Housing Goal in the year 2005 unless otherwise adjusted by HUD in 
accordance with FHEFSSA;
    (2) For the year 2006, 53 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Low- and 
Moderate-Income Housing Home Purchase Subgoal, 46 percent of the total 
number of home purchase mortgages in metropolitan areas financed by 
that GSE's mortgage purchases shall be home purchase mortgages in 
metropolitan areas which count toward the Low- and Moderate-Income 
Housing Goal in the year 2006 unless otherwise adjusted by HUD in 
accordance with FHEFSSA;
    (3) For the year 2007, 55 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Low- and 
Moderate-Income Housing Home Purchase Subgoal, 47 percent of the total 
number of home purchase mortgages in metropolitan areas financed by 
that GSE's mortgage purchases shall be home purchase mortgages in 
metropolitan areas which count toward the Low- and Moderate-Income 
Housing Goal in the year 2007 unless otherwise adjusted by HUD in 
accordance with FHEFSSA;
    (4) For the year 2008, 56 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Low- and 
Moderate-Income Housing Home Purchase Subgoal, 47 percent of the total 
number of home purchase mortgages in metropolitan areas financed by 
that GSE's mortgage purchases shall be home purchase mortgages in 
metropolitan areas which count toward the Low- and Moderate-Income 
Housing Goal in the year 2008 unless otherwise adjusted by HUD in 
accordance with FHEFSSA; and
    (5) For the year 2009 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2009 and thereafter, 
the annual goal for each of those years shall be 56 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years. In addition, as a Low and Moderate 
Income Housing Home Purchase Subgoal, 47 percent of the total number of 
home purchase mortgages in metropolitan areas financed by that GSE's 
mortgage purchases shall be home purchase mortgages in metropolitan 
areas which count toward the Low- and Moderate-Income Housing Goal in 
each of those years unless otherwise adjusted by HUD in accordance with 
FHEFSSA.

0
4. In Sec.  81.13, revise the last sentence of paragraph (b) and revise 
paragraph (c), to read as follows:


Sec.  81.13  Central Cities, Rural Areas, and Other Underserved Areas 
Housing Goal.

* * * * *
    (b) Factors. * * * A statement documenting HUD's considerations and 
findings with respect to these factors, entitled ``Departmental 
Considerations to Establish the Central Cities, Rural Areas, and Other 
Underserved Areas Housing Goal,'' was published in the Federal Register 
on November 2, 2004.
    (c) Goals. The annual goals for each GSE's purchases of mortgages 
on housing located in central cities, rural areas, and other 
underserved areas are:
    (1) For the year 2005, 37 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 
32 percent of the total number of home purchase mortgages in 
metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
in the year 2005 unless otherwise adjusted by HUD in accordance with 
FHEFSSA;
    (2) For the year 2006, 38 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 
33 percent of the total number of home purchase mortgages in 
metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
in the year 2006 unless otherwise adjusted by HUD in accordance with 
FHEFSSA;
    (3) For the year 2007, 38 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas

[[Page 63640]]

Home Purchase Subgoal, 33 percent of the total number of home purchase 
mortgages in metropolitan areas financed by that GSE's mortgage 
purchases shall be home purchase mortgages in metropolitan areas which 
count toward the Central Cities, Rural Areas, and Other Underserved 
Areas Housing Goal in the year 2007 unless otherwise adjusted by HUD in 
accordance with FHEFSSA;
    (4) For the year 2008, 39 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 
34 percent of the total number of home purchase mortgages in 
metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
in the year 2008 unless otherwise adjusted by HUD in accordance with 
FHEFSSA; and
    (5) For the year 2009 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2009 and thereafter, 
the annual goal for each of those years shall be 39 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years. In addition, as a Central Cities, 
Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 34 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by that GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Central Cities, 
Rural Areas, and Other Underserved Areas Housing Goal in each of those 
years unless otherwise adjusted by HUD in accordance with FHEFSSA.
* * * * *

0
5. In Sec.  81.14, revise the last sentence of paragraph (b) and revise 
paragraph (c), to read as follows:


Sec.  81.14  Special Affordable Housing Goal.

* * * * *
    (b) * * * A statement documenting HUD's considerations and findings 
with respect to these factors, entitled ``Departmental Considerations 
to Establish the Special Affordable Housing Goal,'' was published in 
the Federal Register on November 2, 2004.
    (c) Goals. The annual goals for each GSE's purchases of mortgages 
on rental and owner-occupied housing meeting the then-existing, 
unaddressed needs of and affordable to low-income families in low-
income areas and very low-income families are:
    (1) For the year 2005, 22 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2005 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single-family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in accordance with FHEFSSA. In 
addition, as a Special Affordable Housing Home Purchase Subgoal, 17 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in the year 2005 unless otherwise adjusted by 
HUD in accordance with FHEFSSA;
    (2) For the year 2006, 23 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2006 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single-family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in accordance with FHEFSSA. In 
addition, as a Special Affordable Housing Home Purchase Subgoal, 17 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in the year 2006 unless otherwise adjusted by 
HUD in accordance with FHEFSSA;
    (3) For the year 2007, 25 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2007 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single-family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in accordance with FHEFSSA. In 
addition, as a Special Affordable Housing Home Purchase Subgoal, 18 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in the year 2007 unless otherwise adjusted by 
HUD in accordance with FHEFSSA;
    (4) For the year 2008, 27 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2008 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single-family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in accordance with FHEFSSA. In 
addition, as a Special Affordable Housing Home Purchase Subgoal, 18 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in the year 2008 unless otherwise adjusted by 
HUD in accordance with FHEFSSA; and
    (5) For the year 2009 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2009 and thereafter, 
the annual goal for each of those years shall be 27 percent of the 
total number of dwelling units financed by each GSE's mortgage 
purchases in each of those years. The goal for each such year shall 
include mortgage purchases financing dwelling units in multifamily 
housing totaling not less than 1.0 percent of the annual average dollar 
volume of combined (single-family and multifamily) mortgages purchased 
by the respective GSE in the years 2000, 2001, and 2002. In addition, 
as a Special Affordable Housing Home Purchase Subgoal, 18 percent of 
the total number of home purchase mortgages in metropolitan areas 
financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in each of those years unless otherwise 
adjusted by HUD in accordance with FHEFSSA.
* * * * *

[[Page 63641]]


0
6. In Sec.  81.15, revise paragraphs (d), (e)(6)(i), and (e)(6)(ii) and 
add a new paragraph (i), to read as follows:


Sec.  81.15  General requirements.

* * * * *
    (d) Counting owner-occupied units. (1) For purposes of counting 
owner-occupied units toward achievement of the Low- and Moderate-Income 
Housing Goal or the Special Affordable Housing Goal, mortgage purchases 
financing such units shall be evaluated based on the income of the 
mortgagors and the area median income at the time of origination of the 
mortgage. To determine whether mortgages may be counted under a 
particular family income level, i.e., especially low, very low, low or 
moderate income, the income of the mortgagors is compared to the median 
income for the area at the time of the mortgage application, using the 
appropriate percentage factor provided under Sec.  81.17.
    (2)(i) When the income of the mortgagor(s) is not available to 
determine whether an owner-occupied unit in a property securing a 
single-family mortgage originated after 1992 and purchased by a GSE 
counts toward achievement of the Low- and Moderate-Income Housing Goal 
or the Special Affordable Housing Goal, a GSE's performance with 
respect to such unit may be evaluated using estimated affordability 
information in accordance with one of the following methods:
    (A) Excluding from the denominator and the numerator single-family 
owner-occupied units located in census tracts with median incomes less 
than, or equal to, area median income based on the most recent 
decennial census, up to a maximum of one percent of the total number of 
single-family owner-occupied dwelling units eligible to be counted 
toward the respective housing goal in the current year. Mortgage 
purchases with missing data in excess of the maximum will be included 
in the denominator and excluded from the numerator;
    (B) For home purchase mortgages and for refinance mortgages 
separately, multiplying the number of owner-occupied units with missing 
borrower income information in properties securing mortgages purchased 
by the GSE in each census tract by the percentage of all single-family 
owner-occupied mortgage originations in the respective tracts that 
would count toward achievement of each goal, as determined by HUD based 
on the most recent HMDA data available; or
    (C) Such other data source and methodology as may be approved by 
HUD.
    (ii) In any calendar year, a GSE may use only one of the methods 
specified in paragraph (d)(2)(i) of this section to estimate 
affordability information for single-family owner-occupied units.
    (iii) If a GSE chooses to use an estimation methodology under 
paragraph (d)(2)(i)(B) or (d)(2)(i)(C) of this section to determine 
affordability for owner-occupied units in properties securing single-
family mortgage purchases eligible to be counted toward the respective 
housing goal, then that methodology may be used up to nationwide 
maximums for home purchase mortgages and for refinance mortgages that 
shall be calculated by multiplying, for each census tract, the 
percentage of all single-family owner-occupied mortgage originations 
with missing borrower incomes (as determined by HUD based on the most 
recent HMDA data available for home purchase and refinance mortgages, 
respectively) by the number of single-family owner-occupied units in 
properties securing mortgages purchased by the GSE for each census 
tract, summed up over all census tracts. If this nationwide maximum is 
exceeded, then the estimated number of goal-qualifying units will be 
adjusted by the ratio of the applicable nationwide maximum number of 
units for which income information may be estimated to the total number 
of single-family owner-occupied units with missing income information 
in properties securing mortgages purchased by the GSE. Owner-occupied 
units in excess of the nationwide maximum, and any units for which 
estimation information is not available, shall remain in the 
denominator of the respective goal calculation.
    (e) * * *
    (6) * * *
    (i) Multifamily. (A) When a GSE lacks sufficient information to 
determine whether a rental unit in a property securing a multifamily 
mortgage purchased by a GSE counts toward achievement of the Low- and 
Moderate-Income Housing Goal or the Special Affordable Housing Goal 
because neither the income of prospective or actual tenants, nor the 
actual or average rental data, are available, a GSE's performance with 
respect to such unit may be evaluated using estimated affordability 
information in accordance with one of the following methods:
    (1) Multiplying the number of rental units with missing 
affordability information in properties securing multifamily mortgages 
purchased by the GSE in each census tract by the percentage of all 
rental dwelling units in the respective tracts that would count toward 
achievement of each goal, as determined by HUD based on the most recent 
decennial census. For units with missing affordability information in 
tracts for which such methodology is not possible, such units will be 
excluded from the denominator as well as the numerator in calculating 
performance under the respective housing goal(s); or
    (2) Such other data source and methodology as may be approved by 
HUD.
    (B) In any calendar year, a GSE may use only one of the methods 
specified in paragraph (e)(6)(i)(A) of this section to estimate 
affordability information for multifamily rental units.
    (C) If a GSE chooses to use an estimation methodology under 
paragraph (e)(6)(i)(A) of this section to determine affordability for 
rental units in properties securing multifamily mortgage purchases 
eligible to be counted toward the respective housing goal, then that 
methodology may be used up to a nationwide maximum of ten percent of 
the total number of rental units in properties securing multifamily 
mortgages purchased by the GSE in the current year. If this maximum is 
exceeded, the estimated number of goal-qualifying units will be 
adjusted by the ratio of the nationwide maximum number of units for 
which affordability information may be estimated to the total number of 
multifamily rental units with missing affordability information in 
properties securing mortgages purchased by the GSE. Multifamily rental 
units in excess of the maximum set forth in this paragraph 
(e)(6)(i)(C), and any units for which estimation information is not 
available, shall be removed from the denominator of the respective goal 
calculation.
    (ii) Rental units in 1-4 unit single-family properties. (A) When a 
GSE lacks sufficient information to determine whether a rental unit in 
a property securing a single-family mortgage purchased by a GSE counts 
toward achievement of the Low- and Moderate-Income Housing Goal or the 
Special Affordable Housing Goal because neither the income of 
prospective or actual tenants, nor the actual or average rental data, 
are available, a GSE's performance with respect to such unit may be 
evaluated using estimated affordability information in accordance with 
one of the following methods:
    (1) Excluding rental units in 1-to 4-unit properties with missing 
affordability information from the denominator as well as the numerator 
in calculating performance under those goals;

[[Page 63642]]

    (2) Multiplying the number of rental units with missing 
affordability information in properties securing single family 
mortgages purchased by the GSE in each census tract by the percentage 
of all rental dwelling units in the respective tracts that would count 
toward achievement of each goal, as determined by HUD based on the most 
recent decennial census. For units with missing affordability 
information in tracts for which such methodology is not possible, such 
units will be excluded from the denominator as well as the numerator in 
calculating performance under the respective housing goal(s); or
    (3) Such other data source and methodology as may be approved by 
HUD.
    (B) In any calendar year, a GSE may use only one of the methods 
specified in paragraph (e)(6)(ii)(A) of this section to estimate 
affordability information for single-family rental units.
    (C) If a GSE chooses to use an estimation methodology under 
paragraph (e)(6)(ii)(A)(2) or (e)(6)(ii)(A)(3) of this section to 
determine affordability for rental units in properties securing single-
family mortgage purchases eligible to be counted toward the respective 
housing goal, then that methodology may be used up to nationwide 
maximums of five percent of the total number of rental units in 
properties securing non-seasoned single-family mortgage purchases by 
the GSE in the current year and 20 percent of the total number of 
rental units in properties securing seasoned single-family mortgage 
purchases by the GSE in the current year. If either or both of these 
maximums are exceeded, the estimated number of goal-qualifying units 
will be adjusted by the ratio of the applicable nationwide maximum 
number of units for which affordability information may be estimated to 
the total number of single-family rental units with missing 
affordability information in properties securing seasoned or unseasoned 
mortgages purchased by the GSE, as applicable. Single-family rental 
units in excess of the maximums set forth in this paragraph 
(e)(6)(ii)(C), and any units for which estimation information is not 
available, shall be removed from the denominator of the respective goal 
calculation.
* * * * *
    (i) Counting mortgages toward the Home Purchase Subgoals. (1) 
General. The requirements of this section, except for paragraphs (b) 
and (e) of this section, shall apply to counting mortgages toward the 
Home Purchase Subgoals at Sec. Sec.  81.12 through 81.14. However, 
performance under the subgoals shall be counted using a fraction that 
is converted into a percentage for each subgoal and the numerator of 
the fraction for each subgoal shall be the number of home purchase 
mortgages in metropolitan areas financed by each GSE's mortgage 
purchases in a particular year that count towards achievement of the 
applicable housing goal. The denominator of each fraction shall be the 
total number of home purchase mortgages in metropolitan areas financed 
by each GSE's mortgage purchases in a particular year. For purposes of 
each subgoal, the procedure for addressing missing data or information, 
as set forth in paragraph (d) of this section, shall be implemented 
using numbers of home purchase mortgages in metropolitan areas and not 
single-family owner-occupied dwelling units.
    (2) Special counting rule for mortgages with more than one owner-
occupied unit. For purposes of counting mortgages toward the Home 
Purchase Subgoals, where a single home purchase mortgage finances the 
purchase of two or more owner-occupied units in a metropolitan area, 
the mortgage shall count once toward each subgoal that applies to the 
GSE's mortgage purchase.

0
7. In Sec.  81.16, revise paragraphs (c)(6) and (c)(7), remove and 
reserve paragraphs (c)(10) and (c)(11), and add a paragraph (c)(14), to 
read as follows:


Sec.  81.16  Special counting requirements.

* * * * *
    (c) * * *
    (6) Seasoned mortgages. A GSE's purchase of a seasoned mortgage 
shall be treated as a mortgage purchase for purposes of these goals and 
shall be included in the numerator, as appropriate, and the denominator 
in calculating the GSE's performance under the housing goals, except 
where:
    (i) The GSE has already counted the mortgage under a housing goal 
applicable to 1993 or any subsequent year; or
    (ii) HUD determines, based upon a written request by a GSE, that a 
seasoned mortgage or class of such mortgages should be excluded from 
the numerator and the denominator in order to further the purposes of 
the Special Affordable Housing Goal.
    (7) Purchase of refinanced mortgages. Except as otherwise provided 
in this part, the purchase of a refinanced mortgage by a GSE is a 
mortgage purchase and shall count toward achievement of the housing 
goals to the extent the mortgage qualifies.
* * * * *
    (14) Seller dissolution option. (i) Mortgages acquired through 
transactions involving seller dissolution options shall be treated as 
mortgage purchases, and receive credit toward the achievement of the 
housing goals, only when:
    (A) The terms of the transaction provide for a lockout period that 
prohibits the exercise of the dissolution option for at least one year 
from the date on which the transaction was entered into by the GSE and 
the seller of the mortgages; and
    (B) The transaction is not dissolved during the one-year minimum 
lockout period.
    (ii) The Secretary may grant an exception to the one-year minimum 
lockout period described in paragraph (c)(14)(i)(A) and (B) of this 
section, in response to a written request from an enterprise, if the 
Secretary determines that the transaction furthers the purposes of 
FHEFSSA and the GSE's charter act;
    (iii) For purposes of this paragraph (c)(14), ``seller dissolution 
option'' means an option for a seller of mortgages to the GSEs to 
dissolve or otherwise cancel a mortgage purchase agreement or loan 
sale.
* * * * *

0
8. Revise Sec.  81.102 to read as follows:


Sec.  81.102  Verification and enforcement to ensure GSE data 
integrity.

    (a) Independent verification authority. The Secretary may 
independently verify the accuracy and completeness of the data, 
information, and reports provided by each GSE, including conducting on-
site verification, when such steps are reasonably related to 
determining whether a GSE is complying with 12 U.S.C. 4541-4589 and the 
GSE's Charter Act.
    (b) Certification. (1) The senior officer of each GSE who is 
responsible for submitting to HUD the fourth quarter Annual Mortgage 
Report and the AHAR under sections 309(m) and (n) of the Fannie Mae 
Charter Act or sections 307(e) and (f) of the Freddie Mac Act, as 
applicable, or for submitting to the Secretary such other report(s), 
data, or information for which certification is requested in writing by 
the Secretary, shall certify such report(s), data or information.
    (2) The certification shall state as follows: ``To the best of my 
knowledge and belief, the information provided herein is true, correct 
and complete.''
    (3) If the Secretary determines that a GSE has failed to provide 
the certification required by paragraphs (b)(1) and (b)(2) of this 
section, or that a GSE has provided the certification

[[Page 63643]]

required by paragraph (b) in connection with data, information or 
report(s) that the Secretary later determines are not true, correct and 
complete, the Secretary may pursue the enforcement remedies under 
paragraph (e) of this section. For data, information or report(s) 
subject to paragraphs (c) or (d) of this section, the Secretary may 
pursue the enforcement remedies described in paragraph (e) only in 
connection with material errors, omissions or discrepancies as those 
terms are defined in Sec.  81.102(c) or (d).
    (c) Verification procedure and adjustment to correct errors, 
omissions or discrepancies in AHAR data for the immediately preceding 
year. (1) This paragraph (c) pertains to the GSEs' submission of year-
end data. For purposes of this paragraph, ``year-end data'' means data 
that HUD receives from the GSEs related to housing goals performance in 
the immediately preceding year and covering data reported in the fourth 
quarter Annual Mortgage Report and the GSE's AHAR. An ``error'' means a 
technical mistake, such as a mistake in coding or calculating data. An 
``omission'' means a GSE's failure to count units in the denominator. A 
``discrepancy'' means any difference between HUD's analysis of data and 
the analysis contained in a GSE's submission of data, including a 
discrepancy in goal or Special Affordable subgoal performance.
    (2) If HUD finds errors, omissions or discrepancies in a GSE's 
year-end data submissions relative to HUD's regulations, HUD will first 
notify the GSE by telephone or e-mail transmission of each such error, 
omission or discrepancy. The GSE must respond within five working days 
of each such notification. HUD may, in its discretion or upon a request 
by a GSE within the five working day period, extend the response period 
for up to an additional 20 working days. Information exchanges during 
the five working day period following initial notification, and any 
subsequent extensions of time that may be granted, may be by electronic 
mail. Any person with delegated authority from the Secretary, or the 
Director of HUD's Financial Institution Regulation Division, or his or 
her designee, shall be responsible for issuing initial notifications 
regarding errors, omissions, or discrepancies; making determinations on 
the adequacy of responses received; approving any extensions of time 
permitted under this provision; and managing the data verification 
process.
    (3) If each error, omission or discrepancy is not resolved to HUD's 
satisfaction during the initial five working day period from 
notification, and any extension period, the Secretary will notify the 
GSE in writing and seek clarification or additional information to 
correct the error, omission or discrepancy. The GSE shall have 10 
working days (or such longer period as the Secretary may establish, not 
to exceed 30 working days) from the date of the Secretary's written 
notice to respond in writing to the notice. If the GSE fails to submit 
a written response to the Secretary within this period, or if the 
Secretary determines that the GSE's written response fails to correct 
or otherwise resolve each error, omission or discrepancy in its 
reported year-end data to the Secretary's satisfaction, the Secretary 
will determine the appropriate adjustments to the numerator and the 
denominator of the applicable housing goal(s) and Special Affordable 
subgoal(s) due to the GSE's failure to provide the Secretary with 
accurate submissions of data.
    (4) The Secretary, or his or her designee, shall inform a GSE in 
writing, at least five working days prior to HUD's release of its 
official performance figures to the public, of HUD's determination of 
official goals performance figures, including any adjustments. During 
the five working days prior to such public release, a GSE may request, 
in writing, a reconsideration of HUD's final determination of its 
performance and must provide the basis for requesting the 
reconsideration. If the request is granted, the Secretary will consider 
the GSE's request for reconsideration of its determination of goals 
performance and make a final determination regarding the GSE's 
performance, within 10 working days of the Secretary's granting of the 
GSE's written request for reconsideration.
    (5) Should the Secretary determine that additional enforcement 
action against the GSE is warranted for material errors, omissions or 
discrepancies with regard to a housing goal or Special Affordable 
subgoal, it may pursue additional remedies under paragraph (e) of this 
section. An error, omission or discrepancy is material if it results in 
an overstatement of credit for a housing goal or Special Affordable 
subgoal, and, without such overstatement, the GSE would have failed to 
meet such housing goal or Special Affordable subgoal for the 
immediately preceding year.
    (d) Adjustment to correct prior year reporting errors, omissions or 
discrepancies. (1) General. The Secretary may require a GSE to correct 
a material error, omission or discrepancy in a GSE's prior year's data 
reported in the fourth quarter Annual Mortgage Report and the GSE's 
AHAR under sections 309(m) and (n) of the Fannie Mae Charter Act or 
sections 307(e) and (f) of the Freddie Mac Act, as applicable. An 
error, omission or discrepancy is material if it results in an 
overstatement of credit for a housing goal or Special Affordable 
subgoal and, without such overstatement, the GSE would have failed to 
meet such housing goal or Special Affordable subgoal for the prior 
year. A ``prior year'' for purposes of this section is any one of the 
two years immediately preceding the latest year for which data on 
housing goals performance was reported to HUD.
    (2) Procedural requirements. In the event the Secretary determines 
that a GSE's prior year's fourth quarter Annual Mortgage Report or AHAR 
contain a material error, omission or discrepancy, the Secretary will 
provide the GSE with an initial letter containing written findings and 
determinations within 24 months of the end of the relevant GSE 
reporting year. The GSE shall have an opportunity, not to exceed 30 
days from the date of receipt of the Secretary's initial letter, to 
respond in writing with supporting documentation, to contest the 
Secretary's initial determination that there was a material error, 
omission or discrepancy in a prior year's data. The Secretary shall 
then issue a final determination letter within 60 days of the date of 
HUD's receipt of the GSE's written response or, if no response is 
received, within 90 days of the date of the GSE's receipt of the 
Secretary's initial letter. The Secretary may extend the period for 
issuing a final determination letter by an additional 30 days and may 
grant the GSE an opportunity, for a period not to exceed 10 working 
days from the date of the GSE's receipt of the determination letter to 
request that the determination be reconsidered.
    (3) If the Secretary determines that a GSE's prior year's fourth 
quarter Annual Mortgage Report or AHAR contained a material error, 
omission or discrepancy, the Secretary may direct the GSE to correct 
the overstatement by purchasing mortgages to finance the number of 
units that HUD has determined were overstated in the prior year's goal 
performance (or, for the Special Affordable subgoal, the number or 
dollar amount, as applicable, of mortgage purchases that HUD has 
determined were overstated), or that equal the percentage of the 
overstatement in the prior year's goal or Special Affordable subgoal 
performance as applied to the most current year-end performance, 
whichever is less. Units or mortgages purchased to remedy an 
overstatement in the housing goals or

[[Page 63644]]

the Special Affordable subgoal must be eligible to qualify under the 
same goal or Special Affordable subgoal that HUD has determined were 
overstated in the prior year.
    (4) If a GSE does not purchase a sufficient amount or type of 
mortgages to meet the requirements set forth in paragraph (d)(3) of 
this section as directed by the Secretary by no later than the end of 
the calendar year immediately following the year in which the Secretary 
notifies the GSE of such overstatement (unless, upon written request 
from the GSE, the Secretary, in his or her discretion, determines that 
a grant of additional time is appropriate to correct or compensate for 
the overstatement) the Department may pursue any or all of the 
following remedies:
    (i) Issue a notice that the GSE has failed a housing goal or 
Special Affordable subgoal in the prior year;
    (ii) Seek additional enforcement remedies under paragraph (e) of 
this section;
    (iii) Pursue any other civil or administrative remedies as are 
available to it.
    (e) Additional enforcement options. (1) General. In the event the 
Secretary determines, either as a result of his or her independent 
verification authority described in paragraph (a) of this section, or 
by the authority set forth in paragraphs (b), (c) or (d) of this 
section, that any of the following circumstances has occurred with 
respect to data, information or report(s) required by sections 309(m) 
or (n) of the Fannie Mae Charter Act, sections 307(e) or (f) of the 
Freddie Mac Act, or subpart E of this part, the Secretary may regard 
this as a GSE's failure to submit such data, information or report(s) 
and, accordingly, the Secretary may take the additional enforcement 
actions authorized by paragraph (e)(2) of this section:
    (i) A GSE fails to submit the certification required by paragraphs 
(b)(1) and (b)(2) of this section in connection with such data, 
information or report(s); or
    (ii) A GSE submits the certification required by paragraph (b) of 
this section, but the Secretary later determines that the data, 
information or report(s) are not true, correct and complete. For data, 
information or report(s) subject to paragraphs (c) or (d) of this 
section, the Secretary may pursue the additional enforcement remedies 
under paragraph (e)(2) only in connection with material errors, 
omissions or discrepancies, as those terms are defined in Sec.  
81.102(c) or (d). In addition, the Secretary may only pursue such 
remedies in connection with material errors, omissions or discrepancies 
arising under paragraph (d) of this section if the GSE has failed to 
purchase a sufficient amount or type of mortgages, as provided in 
paragraphs (d)(3) and (d)(4) of this section.
    (2) Remedies. (i) Submissions required under the GSE's charter 
acts. After the Secretary makes a determination under paragraph (e)(1) 
of this section that any of the circumstances described in paragraphs 
(e)(1)(i) or (ii) has occurred with respect to data, information, or 
report(s) required by sections 309(m) or (n) of the Fannie Mae Charter 
Act, or by sections 307(e) or (f) of the Freddie Mac Act, the Secretary 
may pursue any or all of the following remedies in accordance with 
paragraph (e)(3), or applicable law, as appropriate:
    (A) A cease-and-desist order against the GSE for failing to submit 
the required data, information or report(s) in accordance with this 
section;
    (B) Civil money penalties against the GSE for failing to submit the 
required data, information or report(s) in accordance with this 
section;
    (C) Any other civil or administrative remedies or penalties against 
the GSE that may be available to the Secretary by virtue of the GSE's 
failing to submit or certify the required data, information or 
report(s) in accordance with this section.
    (ii) Submissions required under subpart E of this part. After the 
Secretary makes a determination under paragraph (e)(1) of this section 
that any of the circumstances described in paragraphs (e)(1)(i) or (ii) 
has occurred with respect to data, information or report(s) required 
under subpart E of this part (but that are not required by sections 
309(m) or (n) of the Fannie Mae Charter Act or by sections 307(e) or 
(f) of the Freddie Mac Act), the Secretary may pursue any civil or 
administrative remedies or penalties against the GSE that may be 
available to the Secretary. The Secretary shall pursue such remedies 
under applicable law.
    (3) Procedures. The Secretary shall comply with the procedures set 
forth in subpart G of this part in connection with any enforcement 
action that he or she may initiate against a GSE under paragraph (e) of 
this section.

    Dated: October 22, 2004.
John C. Weicher,
Assistant Secretary for Housing--Federal Housing Commissioner.

    Note: The Appendices will not appear in the Code of Federal 
Regulations.

Appendix A

Departmental Considerations To Establish The Low- and Moderate-Income 
Housing Goal

A. Introduction

    Sections 1 and 2 provide a basic description of the rule 
process. Section 3 discusses HUD's conclusions based on 
consideration of the factors.

1. Establishment of Low- and Moderate-Income Housing Goal

    In establishing the Low- and Moderate-Income Housing Goals for 
the Federal National Mortgage Association (Fannie Mae) and the 
Federal Home Loan Mortgage Corporation (Freddie Mac), collectively 
referred to as the Government-Sponsored Enterprises (GSEs), section 
1332 of the Federal Housing Enterprises Financial Safety and 
Soundness Act of 1992 (12 U.S.C. 4562) (FHEFSSA) requires the 
Secretary to consider:
    1. National housing needs;
    2. Economic, housing, and demographic conditions;
    3. The performance and effort of the enterprises toward 
achieving the Low- and Moderate-Income Housing Goal in previous 
years;
    4. The size of the conventional mortgage market serving low- and 
moderate-income families relative to the size of the overall 
conventional mortgage market;
    5. The ability of the enterprises to lead the industry in making 
mortgage credit available for low- and moderate-income families; and
    6. The need to maintain the sound financial condition of the 
enterprises.
    The Secretary also considered these factors in establishing a 
low- and moderate-income subgoal for home purchase loans on single-
family-owner properties in metropolitan areas.

2. Underlying Data

    In considering the statutory factors in establishing these 
goals, HUD relied on data from the 2001 American Housing Survey, the 
2000 Censuses of Population and Housing, the 2001 Residential 
Finance Survey (RFS), the 1995 Property Owners and Managers Survey 
(POMS), other government reports, reports submitted in accordance 
with the Home Mortgage Disclosure Act (HMDA), and the GSEs. In order 
to measure performance toward achieving the Low- and Moderate-Income 
Housing Goal in previous years, HUD analyzed the loan-level data on 
all mortgages purchased by the GSEs for 1993-2003 in accordance with 
the goal counting provisions established by the Department in the 
December 1995 and October 2000 rules (24 CFR part 81).

3. Conclusions Based on Consideration of the Factors

    The discussion of the first two factors covers a range of topics 
on housing needs and economic and demographic trends that are 
important for understanding mortgage markets. Information is 
provided which describes the market environment in which the GSEs 
must operate (for example, trends in refinancing activity). In 
addition, the severe housing problems faced by lower-

[[Page 63645]]

income families are discussed, as are the barriers that minorities 
face when attempting to become homeowners. This discussion serves to 
provide useful background information for the discussion of the 
Geographically Targeted and Special Affordable Housing Goals in 
Appendixes B and C, as well as for the Low- and Moderate-Income 
Housing Goal in this Appendix.
    The third factor (past performance) and the fifth factor 
(ability of the GSEs to lead the industry) are also discussed in 
some detail in this Appendix. With respect to home purchase 
mortgages, the past performance of the GSEs and their ability to 
lead the industry are examined for all three housing goals; that 
analysis provides the basis for establishing the three subgoals for 
the GSEs' acquisitions of home loans on single-family-owner 
properties.
    The fourth factor (size of the market) and the sixth factor 
(need to maintain the GSEs' sound financial condition) are mentioned 
only briefly in this Appendix. Detailed analyses of the fourth 
factor and the sixth factor are contained in Appendix D and in the 
economic analysis of this rule, respectively.
    The factors are discussed in sections B through H of this 
appendix. Section I summarizes the findings and presents the 
Department's conclusions concerning the Low- and Moderate-Income 
Housing Goal. Section I also gives the rationale for a low- and 
moderate-income subgoal for home purchase loans.
    The consideration of the factors in this Appendix has led the 
Secretary to the following conclusions:
     Changing population demographics will result in a need 
for primary and secondary mortgage markets to meet nontraditional 
credit needs, respond to diverse housing preferences, and overcome 
information and other barriers that many immigrants and minorities 
face. Growing housing demand from immigrants (both those who are 
already here and those projected to come) and non-traditional 
homebuyers will help to offset declines in the demand for housing 
caused by the aging of the population. Immigrants and other 
minorities--who accounted for more than a third of household growth 
since the 1990s--will be responsible for almost two-thirds of the 
growth in the number of new households over the next ten years. As 
these demographic factors play out, the overall effect on housing 
demand will likely be sustained growth and an increasingly diverse 
household population from which to draw new renters and homeowners.
     Despite the record national homeownership rate of 68.3 
percent in 2003, much lower rates prevailed for minorities, 
especially for African-American households (48.4 percent) and 
Hispanics (47.4 percent), and these lower rates are only partly 
accounted for by differences in income, age, and other socioeconomic 
factors.
     In addition to low incomes, barriers to homeownership 
that disproportionately affect minorities and immigrants include 
lack of capital for down payments and closing costs, poor credit 
history, lack of access to mainstream lenders, little understanding 
of the homebuying process, and continued discrimination in housing 
markets and mortgage lending.
     A HUD-published study of discrimination in the rental 
and owner markets found that while differential treatment between 
minority and white home seekers had declined over the past ten 
years, it continued at an unacceptable level in the year 2000. In 
addition, disparities in mortgage lending continued across the 
nation in 2002, when the loan denial rate was 7.8 percent for white 
mortgage applicants, but 20.1 percent for African Americans and 15.5 
percent for Hispanics.\1\
---------------------------------------------------------------------------

    \1\ Mortgage denial rates are based on 2002 HMDA data for home 
purchase loans; manufactured housing lenders are excluded from these 
comparisons.
---------------------------------------------------------------------------

     Americans with the lowest incomes face persistent 
housing problems. Recent HUD analysis reveals that in 2001, 5.1 
million households had ``worst case'' housing needs, defined as 
housing costs greater than 50 percent of household income or 
severely inadequate housing among unassisted very-low-income renter 
households. Among these households, 90 percent had a severe rent 
burden, 6 percent lived in severely inadequate housing, and 4 
percent suffered from both problems.
     Over the past ten years, there has been a ``revolution 
in affordable lending'' that has extended homeownership 
opportunities to historically underserved households. Fannie Mae and 
Freddie Mac have been a substantial part of this ``revolution in 
affordable lending''. During the mid-to-late 1990s, they added 
flexibility to their underwriting guidelines, introduced new low-
down-payment products, and worked to expand the use of automated 
underwriting in evaluating the creditworthiness of loan applicants. 
HMDA data suggest that the industry and GSE initiatives are 
increasing the flow of credit to underserved borrowers. Between 1993 
and 2003, conventional loans to low-income and minority families 
increased at much faster rates than loans to upper-income and non-
minority families.
     The Low- and Moderate-Income Goal was set at 50 percent 
beginning in 2001. Effective on January 1, 2001, several changes in 
counting requirements came into effect, including (1) ``bonus 
points'' (double credit) for purchases of mortgages on small (5-50 
unit) multifamily properties and, above a threshold level, mortgages 
on 2-4 unit owner-occupied properties; and (2) a ``temporary 
adjustment factor'' (1.35 units credit) for Freddie Mac's purchases 
of mortgages on large (>50 unit) multifamily properties. With these 
two counting rules, Fannie Mae's performance was 51.5 percent in 
2001, 51.8 percent in 2002 and 52.3 percent in 2003, and Freddie 
Mac's performance was 53.2 percent in 2001, 50.5 percent in 2002, 
and 51.2 percent in 2003; thus, both GSEs surpassed this higher goal 
in all three years.
     The bonuses and temporary adjustment factor expired at 
the end of 2003. Without these rules, Fannie Mae's performance would 
have been 51.3 percent in 2000, 49.2 percent in 2001, 49.0 percent 
in 2002, and 48.7 percent in 2003. Freddie Mac's performance would 
have been 50.6 percent in 2000, 47.7 percent in 2001, 46.1 percent 
in 2002, and 45.0 percent in 2003. Thus, both Fannie Mae and Freddie 
Mac would have surpassed the 50 percent goal in 2000 and fallen 
short in 2001, 2002, and 2003.
     This Appendix includes a comprehensive analysis of each 
GSE's performance in funding home purchase mortgages for borrowers 
and neighborhoods covered by the three housing goals--special 
affordable and low- and moderate-income borrowers and underserved. 
The GSEs' performance in funding first-time home buyers is also 
examined.
     While Freddie Mac has improved its affordable lending 
performance in recent years, it has consistently lagged the 
conventional conforming market in funding affordable home purchase 
loans for special affordable and low-moderate-income borrowers and 
underserved neighborhoods targeted by the housing goals.\2\ In 2003, 
its performance on the underserved areas goal was particularly low 
relative to both the performances of Fannie Mae and the market; in 
that year, underserved area loans accounted for only 24.0 percent of 
Freddie Mac's purchases compared with 26.8 percent of Fannie Mae's 
purchases and 27.6 percent of market originations. (These 
underserved area data are based on 1990 Census geography.)
---------------------------------------------------------------------------

    \2\ The ``affordable lending performance'' of Fannie Mae and 
Freddie Mae refers to the performance of the GSEs in funding loans 
for low-income and underserved borrowers through their purchase (or 
guarantee) of loans originated by primary lenders. It does not, of 
course, imply that the GSEs themselves are lenders originating loans 
in the primary market.
---------------------------------------------------------------------------

     In general, Fannie Mae's affordable lending performance 
has been better than Freddie Mac's. But like Freddie Mac, Fannie 
Mae's average performance during past periods (e.g., 1993-2003, 
1996-2003, 1999-2003) has been below market levels. However, it is 
encouraging that Fannie Mae markedly improved its affordable lending 
performance relative to the market during 2001, 2002, and 2003, the 
first three years under the higher housing goal targets that HUD 
established in the GSE Final Rule dated October 2000. Over this 
three-year period, Fannie Mae led the primary market in funding 
special affordable and low-mod loans but lagged the market in 
funding underserved areas loans. In 2003, Fannie Mae's increased 
performance placed it significantly above the special affordable 
market (a 17.1 percent share for Fannie Mae compared with a 15.9 
percent share for the market) and the low-mod market (a 47.0 percent 
share for Fannie Mae compared with a 44.6 percent share for the 
market). However, Fannie Mae continued to lag the underserved areas 
market in 2003 (a 26.8 percent share for Fannie Mae compared with a 
27.6 percent share for the market). In this case, which is referred 
to in the text as the ``purchase year'' approach, Fannie Mae's 
performance is based on comparing its purchases of all loans (both 
seasoned loans and newly-originated mortgages) during a particular 
year with loans originated in the market in that year. When Fannie 
Mae's

[[Page 63646]]

performance is measured on an ``origination year'' basis (that is, 
allocating Fannie Mae's purchases in a particular year to the year 
that the purchased loan was originated), Fannie Mae also led the 
2003 market in funding special affordable and low- and moderate-
income loans, and lagged the market in funding underserved area 
loans.
     Both Fannie Mae and Freddie Mac lag the conventional 
conforming market in funding first-time homebuyers, and by a rather 
wide margin. Between 1999 and 2001, first-time homebuyers accounted 
for 27 percent of each GSE's purchases of home loans, compared with 
38 percent for home loans originated in the conventional conforming 
market.
     The GSEs have accounted for a significant share of the 
total (government as well as conventional) market for home purchase 
loans, but their market share for each of the affordable lending 
categories (e.g., low-income borrowers and census tracts) has been 
less than their share of the overall market.
     The GSEs also account for a very small share of the 
market for important groups such as minority first-time homebuyers. 
Considering the total mortgage market (both government and 
conventional loans), it is estimated that the GSEs purchased only 14 
percent of loans originated between 1999 and 2001 for African-
American and Hispanic first-time homebuyers, or one-third of their 
share (42 percent) of all home purchase loans originated during that 
period. Considering the conventional conforming market and the same 
time period, it is estimated that the GSEs purchased only 31 percent 
of loans originated for African-American and Hispanic first-time 
homebuyers, or approximately one-half of their share (57 percent) of 
all home purchase loans in that market. The GSEs' small share of the 
first-time homebuyer market could be due to the preponderance of 
high (over 20 percent) downpayment loans in their mortgage 
purchases.
     This Appendix discusses the dynamic nature of the 
single-family mortgage market and the numerous changes that this 
market has undergone over the past few years. Some important trends 
that will likely factor into the GSEs' performance in meeting the 
needs of underserved borrowers include the growth of the subprime 
market, the increasing use of automated underwriting systems, and 
the introduction of risk-based pricing into the market.
     The long run outlook for the multifamily rental market 
is sustained, moderate growth, based on favorable demographics. The 
minority population, especially Hispanics, provides a growing source 
of demand for affordable rental housing. ``Lifestyle renters'' 
(older, middle-income households) are also a fast-growing segment of 
the rental population. Provision of affordable housing, however, 
will continue to challenge suppliers of multifamily rental housing 
and policy makers at all levels of government. Low incomes combined 
with high housing costs define a difficult situation for millions of 
renter households. Housing cost reductions are constrained by high 
land prices and construction costs in many markets. Government 
action--through land use regulation, building codes, and occupancy 
standards--are major contributors to those high costs.
     The market for financing multifamily apartments has 
grown to record volumes. Fannie Mae and Freddie Mac have been among 
those boosting volumes and introducing new programs to serve the 
multifamily market. Fannie Mae's multifamily purchases jumped from 
about $10 billion in 1999 and 2000 to $18.7 billion in 2001, $18.3 
billion in 2002, and $33.3 billion in 2003--the last three years 
were characterized by heavy refinancing activity.
     Freddie Mac has re-entered the multifamily market, 
after withdrawing for a time in the early 1990s. Concerns regarding 
Freddie Mac's multifamily capabilities no longer constrain its 
performance with regard to the housing goals. Freddie Mac's 
multifamily purchases increased from a relatively low $3 billion in 
1997 to approximately $7 billion during the next three years (1998 
to 2000), before rising further to $11.9 billion in 2001, $13.3 
billion in 2002, and $21.6 billion in 2003.
     The overall presence of both GSEs in the rental 
mortgage market falls short of their involvement in the single-
family owner market. Between 1999 and 2002, the GSEs' purchases 
totaled for 61 percent of the owner market, but only 37 percent of 
the single-family rental and multifamily rental market. Certainly 
there is room for expansion of the GSEs in supporting the nation's 
rental markets, and that expansion is needed if the GSEs are to make 
significant progress in closing the gaps between the affordability 
of their mortgage purchases and that of the overall conventional 
conforming market.
     Considering both owner and rental properties, the GSEs' 
presence in the goals-qualifying market has been significantly less 
than their presence in the overall conventional conforming mortgage 
market. Specifically, HUD estimates that the GSEs accounted for 55 
percent of all owner and rental units financed in the primary market 
between 1999 and 2002, but only 48 percent of units qualifying for 
the low-mod goal, 48 percent of units qualifying for the underserved 
areas goal, and 41 percent of units qualifying for special 
affordable goal.

B. Factor 1: National Housing Needs

    This section reviews the general housing needs of lower-income 
families that exist today and are expected to continue in the near 
future. Affordability problems that lower-income families face in 
both the rental and owner markets are examined. The section also 
describes racial disparities in homeownership and the causes of 
these disparities. It also notes some special problems, such as the 
need to rehabilitate our older urban housing stock, that are 
discussed throughout this appendix.

1. Homeownership Gaps

    Despite recent record homeownership rates, many Americans, 
including disproportionate numbers of racial and ethnic minorities, 
are shut out of homeownership opportunities. Although the national 
homeownership rate for all Americans was 68.3 percent in 2003, the 
rate for minority households was lower--for example, just 48.4 
percent of African-American households and 47.4 percent of Hispanic 
households owned a home.\3\ Differences in income and age between 
minorities and whites do not fully explain these gaps. The Joint 
Center for Housing Studies estimated that if minorities owned homes 
at the same rates as whites of similar age and income, a 
homeownership gap of 10 percentage points would still exist.\4\
---------------------------------------------------------------------------

    \3\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2004, p. 35.
    \4\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2003, p. 16.
---------------------------------------------------------------------------

a. Importance of Homeownership

    Homeownership is one of the most common forms of property 
ownership as well as savings.\5\ Historically, home equity has been 
the largest source of wealth for most Americans, and wealth gains in 
housing have been more widely distributed among the population than 
gains in the stock market.\6\ With stocks appreciating faster than 
home prices over the past decade, home equity as a share of all 
family assets fell from 38 percent in 1989 to 33 percent in 1998 and 
32 percent in 2001.\7\ However, many of the gains in the stock 
market were erased after 1999 and housing was once again a more 
significant asset in the household balance sheet than stocks in 
2001.\8\ Even with a bull market through most of the 1990s, 59 
percent of all homeowners in 1998 held more than half of their net 
wealth in the form of home equity.\9\ From 2001 to 2003, homes 
prices appreciated an average of 23 percent which meant $30,900 in 
housing equity accumulation for a typical homeowner.\10\ Moreover, 
unlike stock wealth, aggregate home equity has steadily increased 
over the past 40 years with only occasional small dips.\11\
---------------------------------------------------------------------------

    \5\ According to the National Association of Realtors, Housing 
Market Will Change in New Millennium as Population Shifts, November 
7, 1998. Forty-five percent of U.S. household wealth was in the form 
of home equity in 1998. Since 1968, home prices have increased each 
year, on average, at the rate of inflation plus two percentage 
points.
    \6\ Todd Buchholz, ``Safe At Home: The New Role of Housing in 
the U.S. Economy,'' a paper commissioned by the Homeownership 
Alliance, 2002.
    \7\ Federal Reserve Board, ``Recent Changes in U.S. Family 
Finances: Results from the 1998 and 2001 Survey of Consumer 
Finances,'' January 2003, p. 16.
    \8\ Mark Zandi, ``Housing's Rising Contribution,'' June 2002, p. 
5.
    \9\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 1998.
    \10\ Lawrence Yun, ``The Forecast,'' National Association of 
Realtors Real Estate Outlook, February 2004, p. 4.
    \11\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2004, p. 15.
---------------------------------------------------------------------------

    Among low-income homeowners (household income less than 
$20,000), home equity accounted for about 72 percent of household 
wealth, and approximately 55 percent for homeowners with incomes 
between $20,000 and $50,000. Median net wealth for low-income 
homeowners under 65

[[Page 63647]]

was twelve times that of a similar renter.\12\ Thus a homeownership 
gap continues to translate directly into a wealth gap. For this 
reason, President Bush issued the ``Homeownership Challenge'' in 
June 2002 to increase minority homeownership by 5.5 million by the 
end of the decade. By December of 2003, the Census estimated that 
the number of minority homeowners had increased by 1.53 million. 
Meaning that in the fourth quarter of 2003, for the first time ever, 
the majority of minority households are homeowners.\13\
---------------------------------------------------------------------------

    \12\ U.S. Department of Housing and Urban Development, 
``Economic Benefits of Increasing Minority Homeownership,'' p. 7.
    \13\ http://www.whitehouse.gov/infocus/homeownership/. Accessed 
July 28, 2004.
---------------------------------------------------------------------------

    High rates of homeownership support economic stability within 
housing and related industries, sectors that contributed nearly one-
third of the total gain in real GDP since the beginning of the 
decade.\14\ In addition, more than half of the refinancing mortgages 
in the first two years of the decade were cash-out, defined as 
refinancing procedures by which the mortgage balance is increased by 
more than five percent in order to tap into home equity. Cash-outs 
injected more than $300 billion into the economy between 2000 and 
2002 and were responsible for one-fifth of real GDP growth since 
during that period.\15\ In addition to economic benefits such as 
jobs and residential investment, studies show that the better living 
environment associated with owning a home has positive impacts on 
children, in terms of lower rates of teenage pregnancy and higher 
reading other test scores. The current literature substantiates that 
the benefits of homeownership extend beyond individual homeowners 
and their families to society at large. Homeownership promotes 
social and community stability by increasing the number of 
stakeholders and reducing disparities in the distributions of wealth 
and income. The empirical literature is generally supportive of a 
relationship between homeownership and greater investment in 
property.\16\ Homeownership is also associated with neighborhood 
stability (lower mobility), greater participation in voluntary and 
political activities,\17\ and links to entrepreneurship.\18\
---------------------------------------------------------------------------

    \14\ Homeownership Alliance, ``The Economic Contribution of the 
Mortgage Refinancing Boom,'' December 2002, p. 2.
    \15\ Homeownership Alliance, ``The Economic Contribution of the 
Mortgage Refinancing Boom,'' December 2002, p. 4-5.
    \16\ Robert Dietz and Donald Haurin, ``The Social and Private 
Consequences of Homeownership,'' May 2001, p. 51.
    \17\ William M. Rohe, George McCarthy, and Shannon Van Zandt, 
``The Social Benefits and Costs of Homeownereship,'' May 2000, p. 
31.
    \18\ U.S. Deparmtent of Housing and Urban Development, 
``Economic Beneifts of Increasing Minority Homeownership,'' p. 8-9.
---------------------------------------------------------------------------

b. Barriers to Homeownership \19\
---------------------------------------------------------------------------

    \19\ For a dicusssion of the causes of existing disparities in 
homeownership, see the various articles in Nicolas P. Retsinas and 
Eric S. Belsky (Eds), Low-Income Homeowernsip: Examining the 
Unexamined Goal, Washington, DC: Brookings Institution Press, 2002.
---------------------------------------------------------------------------

    Insufficient income, high debt burdens, and limited savings are 
obstacles to homeownership for younger families. As home prices 
skyrocketed during the late 1970s and early 1980s, real incomes also 
stagnated, with earnings growth particularly slow for blue collar 
and less educated workers. Through most of the 1980s, the 
combination of slow income growth and increasing rents made saving 
for home purchase more difficult, and relatively high interest rates 
required large fractions of family income for home mortgage 
payments. Thus, during that period, fewer households had the 
financial resources to meet down payment requirements, closing 
costs, and monthly mortgage payments.
    Economic expansion and lower mortgage rates substantially 
improved homeownership affordability during the 1990s. Many young, 
low-income, and minority families who were closed out of the housing 
market during the 1980s re-entered the housing market during the 
last decade. Even with an economic slowdown in 2000-2001 and 
climbing house appreciation in 2002-2003, after-tax mortgage 
payments fell in 2003 for buyers of median priced homes because of 
historically low interest rates.\20\ However, many households still 
lack the earning power to take advantage of today's home buying 
opportunities. Several trends have contributed to the reduction in 
the real earnings of young adults without college education over the 
last 15 years, including technological changes that favor white-
collar employment, losses of unionized manufacturing jobs, and wage 
pressures exerted by globalization. Over 42 percent of the nation's 
population between the ages of 25 and 34 had no advanced education 
in 2000\21\ and were therefore at risk of being unable to afford 
homeownership. African Americans and Hispanics, who have lower 
average levels of educational attainment than whites, are especially 
disadvantaged by the erosion in wages among less educated workers.
---------------------------------------------------------------------------

    \20\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2004, p. 15.
    \21\ U.S. Census Bureau, Current Population Survey, March 2000.
---------------------------------------------------------------------------

    Immigrants and other minorities, who accounted for nearly 40 
percent of the growth in the homeownership rate over the past five 
years, will be responsible for two-thirds of the growth in new 
households over the next ten years. These groups have unique housing 
needs and face numerous hurdles in becoming homeowners. In addition 
to low income, barriers to homeownership that disproportionately 
affect minorities and immigrants include:
    (1) Lack of capital for down payment and closing costs;
    (2) Poor credit history;
    (3) Lack of access to mainstream lenders;
    (4) Complexity and fear of the home buying process; and,
    (5) Continued discrimination in housing markets and mortgage 
lending.
    (i) Lack of Cash for Down Payment. In the 2002 Fannie Mae 
National Housing Survey, 40 percent of Hispanics reported not having 
enough money for a down payment as an obstacle to buying a home 
versus 32 percent of all Americans.\22\ A study by Gyourko, 
Linneman, and Wachter found significant racial differences in 
homeownership rates in ``wealth-constrained'' households while 
finding no racial differences in homeownership rates among 
households with wealth sufficient to meet down payment and closing 
costs.\23\ Minorities and immigrants are much less likely to receive 
gifts and inheritances from their parents to assist them in becoming 
a homeowner.
---------------------------------------------------------------------------

    \22\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 
11.
    \23\ Joseph Gyourko, Peter Linneman, and Susan Wachter. 
``Analyzing the Relationships among Race, Wealth, and Home Ownership 
in America,'' Journal of Housing Economics 8 (2), p. 63-89, as 
discussed in Thomas P. Boehm and Alan M. Schlottmann. ``Housing and 
Wealth Accumulation: Intergenerational Impacts,'' in Low-Income 
Homeownership: Examining the Unexamined Goal, Brookings Institution 
Press (2002), p. 408.
---------------------------------------------------------------------------

    (ii) Poor Credit History. Poor credit history also 
differentially affects minority households. In the same Fannie Mae 
survey, nearly a third of African-American respondents said their 
credit rating would be an obstacle to buying a home versus 23 
percent of all Americans.\24\ Because African-American and Hispanic 
borrowers are more likely than others to have little traditional 
credit history or a poorer credit history, they face increased 
difficulties in being accepted for mortgage credit. This is because 
credit history scores (such as a FICO score) are a major component 
of the new automated mortgage scoring systems. These systems are 
more likely to refer minority borrowers for more intensive manual 
underwriting, rather than to automatically accept them for the less 
costly, expedited processing. In these situations, there is the 
additional concern that ``referred'' borrowers may not always 
receive a manual underwriting for the loan that they initially 
applied for, but rather be directed to a high-cost subprime loan 
product.
---------------------------------------------------------------------------

    \24\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 
11.
---------------------------------------------------------------------------

    (iii) Lack of Access to Mainstream Lenders. Minorities face 
heightened barriers in accessing credit because of their often 
limited access to mainstream lenders. Access to lenders becomes 
difficult when mainstream financial institutions are not located in 
neighborhoods where minorities live. The growth in subprime lending 
over the last several years has benefited credit-impaired 
borrowers--those who may have blemishes in their credit record, 
insufficient credit history, or non-traditional credit sources. 
Subprime lenders have allowed these borrowers to access credit that 
they could not otherwise obtain in the prime credit market. However, 
studies by HUD, The Woodstock Institute and others have shown that 
subprime lending is disproportionately concentrated in low-income 
and minority neighborhoods.\25\ While these studies

[[Page 63648]]

recognize that differences in credit behavior explain some of the 
disparities in subprime lending across neighborhoods, they argue 
that the absence of mainstream lenders has also contributed to the 
concentration of subprime lending in low-income and minority 
neighborhoods. More competition by prime lenders in inner city 
neighborhoods could lower the borrowing costs of families who 
currently have only the option of a high-cost subprime loan. This 
issue of the lack of mainstream lenders in inner city neighborhoods 
is discussed further in subsection 2, below, in connection with 
disparities between neighborhoods.
---------------------------------------------------------------------------

    \25\ See Dan Immergluck, Stark Differences: The Explosion of the 
Subprime Industry and Racial Hypersegmentation in Home Equity 
Lending, Woodstock Institute, October 2000; and Daniel Immergluck 
and Marti Wiles, Two Steps Back: The Dual Mortgage Market, Predatory 
Lending, and the Undoing of Community Development, Woodstock 
Institute, Chicago, IL, November 1999. For a national analyses, see 
the HUD report Unequal Burden: Income and Racial Disparities in 
Subprime Lending in America, April 2000; and Randall M. Scheessele, 
Black and White Disparities in Subprime Mortgage Refinance Lending, 
Housing Finance Working Paper No. HF-114, Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, April 2002.
---------------------------------------------------------------------------

    (iv) Complexity and Fear of Homebuying Process. An additional 
barrier to homeownership is fear and a lack of understanding about 
the buying process and the risks of ownership. Many Americans could 
become homeowners if provided with information to correct myths, 
misinformation, and concerns about the mortgage process. Some 
potential homeowners, particularly minorities, are unaware that they 
may already qualify for a mortgage they can afford. The 2002 Fannie 
Mae survey revealed that 30 percent of Americans believe erroneously 
that they need to pay 20 percent of the cost of a home up-front. In 
addition, Fannie Mae reported that half of Americans are only 
``somewhat'' or ``not at all'' comfortable with mortgage terms.\26\ 
Freddie Mac reports that six of 10 Hispanics are uncomfortable with 
home buying terminology, and think they need ``perfect credit'' to 
buy; and less than four in 10 are aware that lenders are not 
required by law to give them the lowest interest rate possible.\27\ 
A study using focus groups with renters found that even among those 
whose financial status would make them capable of homeownership, 
many felt that the buying process was insurmountable because they 
feared rejection by the lender or being taken advantage of.\28\
---------------------------------------------------------------------------

    \26\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 9.
    \27\ See ``Immigration Changes Won't Hurt Housing,'' in National 
Mortgage News, January 27, 2003, p. 8.
    \28\ Donald S. Bradley and Peter Zorn, ``Fear of Homebuying: Why 
Financially Able Households May Avoid Ownership,'' Secondary 
Mortgage Markets, 1996.
---------------------------------------------------------------------------

    (v) Discrimination in the Housing and Mortgage Markets. Finally, 
differential treatment of minorities in the sales and rental markets 
and in the mortgage lending market has been well documented. The 
continued discrimination in these markets is discussed in the next 
section.

2. Disparities in Housing and Mortgage Markets

    Sales and Rental Markets. In 2002, HUD released its third 
Housing Discrimination Study (HDS) in the sale and rental of 
housing. The study, entitled Discrimination in Metropolitan Housing 
Markets: National Results from Phase I of The Housing Discrimination 
Study was conducted by the Urban Institute.\29\ This results of this 
HDS were based on 4,600 paired tests of minority and non-minority 
home seekers conducted during 2000 in 23 metropolitan areas 
nationwide. The report showed large decreases between 1989 and 2000 
in the level of discrimination experienced by Hispanics and African 
Americans seeking to buy a home. There has also been a modest 
decrease in discrimination toward African Americans seeking to rent 
a unit. This downward trend, however, has not been seen for Hispanic 
renters, who now are more likely to experience discrimination in 
their housing search than do African-American renters. But while 
generally down since 1989, the report found that housing 
discrimination still exists at unacceptable levels. The greatest 
share of discrimination for Hispanic and African-American home 
seekers can still be attributed to being told units are unavailable 
when they are available to non-Hispanic whites, and being shown and 
told about fewer units than comparable non-minority home seekers. 
Although discrimination is down on most areas for African-American 
and Hispanic homebuyers, there remain worrisome upward trends of 
discrimination in the areas of geographic steering for African 
Americans and, relative to non-Hispanic whites, the amount of help 
agents provide to Hispanics with obtaining financing. On the rental 
side, Hispanics were more likely in 2000 than in 1989 to be quoted a 
higher rent than their white counterpart for the same unit.
---------------------------------------------------------------------------

    \29\ Margery Austin Turner, Stephen L. Ross, George Galster, and 
John Yinger, ``Discrimination in Metropolitan Housing Markets,'' The 
Urban Institute Press, November 2002.
---------------------------------------------------------------------------

    Another HUD-sponsored study asked respondents to a nationwide 
survey if they ``thought'' they had ever been discriminated against 
when trying to buy or rent a house or an apartment.\30\ While the 
responses were subjective, they are consistent with the findings of 
the HDS. African Americans and Hispanics were considerably more 
likely than whites to say they have suffered discrimination--24 
percent of African Americans and 22 percent of Hispanics perceived 
discrimination, compared to only 13 percent of whites.
---------------------------------------------------------------------------

    \30\ Martin D. Abravanel and Mary K. Cunningham, How Much Do We 
Know? Public Awareness of the Nation's Fair Housing Laws. A report 
prepared for HUD by the Urban Institute, Washington, DC, April 2002.
---------------------------------------------------------------------------

    Mortgage Lending Market. Research based on Home Mortgage 
Disclosure Act (HMDA) data suggests pervasive and widespread 
disparities in mortgage lending across the Nation. For 2001, the 
mortgage denial rate for white mortgage applicants was 23 percent, 
while 36 percent of African-American and 35 percent of Hispanic 
applicants were denied.
    Two recent HUD-sponsored studies of paired-testing at the 
mortgage pre-application stage also points to discrimination by 
mortgage lenders. Based on its review of pair tests conducted by the 
National Fair Housing Alliance, the Urban Institute concluded that 
differential treatment discrimination at the pre-application level 
occurred at significant levels in at least some cities.\31\ 
Minorities were less likely to receive information about loan 
products, received less time and information from loan officers, and 
were quoted higher interest rates in most of the cities where tests 
were conducted. A second HUD-sponsored study by the Urban Institute 
used the paired testing methodology in Los Angeles and Chicago and 
found similar results. African Americans and Hispanics faced a 
significant risk of unequal treatment when they visited mainstream 
mortgage lending institutions to make pre-application inquiries.\32\
---------------------------------------------------------------------------

    \31\ Margery Austin Turner, John Yinger, Stephen Ross, Kenneth 
Temkin, Diane Levy, David Levine, Robin Ross Smith, and Michelle 
deLair, What We Know About Mortgage Lending Discrimination, The 
Urban Institute, contract report for the Department of Housing and 
Urban Development, December 1998.
    \32\ Margery Austin Turner, All Other Things Being Equal: A 
Paired Testing Study of Mortgage Lending Institutions, The Urban 
Institute Press, April 2002.
---------------------------------------------------------------------------

    Several possible explanations for these lending disparities have 
been suggested. A study by the Boston Federal Reserve Bank found 
that racial disparities cannot be explained by reported differences 
in creditworthiness.\33\ In other words, minorities are more likely 
to be denied than whites with similar credit characteristics, which 
suggests lender discrimination. In addition, loan officers, who may 
believe that race is correlated with credit risk, may use race as a 
screening device to save time, rather than devote effort to 
distinguishing the creditworthiness of the individual applicant.\34\ 
This violates the Fair Housing Act.
---------------------------------------------------------------------------

    \33\ Alicia H. Munnell, Geoffrey M.B. Tootell, Lynn E. Browne, 
and James McEneaney, ``Mortgage Lending in Boston: Interpreting HMDA 
Data,'' American Economic Review, 86, March 1996.
    \34\ See Charles W. Calomeris, Charles M. Kahn and Stanley D. 
Longhofer, ``Housing Finance Intervention and Private Incentives: 
Helping Minorities and the Poor,'' Journal of Money, Credit and 
Banking, 26, August 1994, pp. 634-74, for more discussion of this 
phenomenon, which is called ``statistical discrimination.''
---------------------------------------------------------------------------

    Underwriting rigidities may fail to accommodate creditworthy 
low-income or minority applicants. For example, under traditional 
underwriting procedures, applicants who have conscientiously paid 
rent and utility bills on time but have never used consumer credit 
would be penalized for having no credit record. Applicants who have 
remained steadily employed, but have changed jobs frequently, would 
also be penalized. As discussed in Section C below, lenders, private 
mortgage insurers, and the GSEs have been adjusting their 
underwriting guidelines to take into account these special 
circumstances of lower-income families. Many of the changes recently 
undertaken by the industry focused on finding alternative 
underwriting guidelines to establish creditworthiness that do not 
disadvantage creditworthy minority or low-income applicants. 
However, because of the enhanced roles of credit scoring and 
automated underwriting in the mortgage origination process, it is 
unclear to what

[[Page 63649]]

degree the reduced rigidity in industry standards will benefit 
borrowers who have been adversely impacted by the traditional 
guidelines as discussed in section C.7, some industry observers have 
expressed a concern that the greater flexibility in the industry's 
written underwriting guidelines may not be reflected in the 
numerical credit and mortgage scores which play a major role in the 
automated underwriting systems that the GSEs and others have 
developed.
    Disparities Between Neighborhoods. Mortgage credit also appears 
to be less accessible in low-income and high-minority neighborhoods. 
As discussed in Appendix B, 2001 HMDA data show that mortgage denial 
rates are nearly twice as high in census tracts with low-income and/
or high-minority composition, as in other tracts (16.8 percent 
versus 8.7 percent). Numerous studies have found that mortgage 
denial rates are higher in low-income census tracts, even accounting 
for other loan and borrower characteristics.\35\ These geographical 
disparities can be the result of cost factors, such as the 
difficulty of appraising houses in these areas because of the 
paucity of previous sales of comparable homes. Sales of comparable 
homes may also be difficult to find due to the diversity of central 
city neighborhoods. The small loans prevalent in low-income areas 
are less profitable to lenders because up-front fees to loan 
originators are frequently based on a percentage of the loan amount, 
although the costs incurred are relatively fixed. As noted above, 
racial disparities in mortgage access may be due to the fact that 
mainstream lenders are not doing business in certain inner city 
neighborhoods. There is evidence that mainstream lenders active in 
white and upper-income neighborhoods are much less active in low-
income and minority neighborhoods--often leaving these neighborhoods 
to unregulated subprime lenders. Geographical disparities in 
mortgage lending are discussed further in Section C.8 below (which 
examines subprime lending) and in Appendix B (which examines the 
Geographically Targeted Goal).
---------------------------------------------------------------------------

    \35\ Robert B. Avery, Patricia E. Beeson and Mark E. Sniderman, 
Understanding Mortgage Markets: Evidence from HMDA, Working Paper 
Series 94-21, Federal Reserve Bank of Cleveland, December 1994.
---------------------------------------------------------------------------

3. Affordability Problems and Worst Case Housing Needs

    The severe affordability problems faced by low-income homeowners 
and renters are documented in HUD's ``Worst Case Housing Needs'' 
reports. These reports, which are prepared biennially for Congress, 
are based on the American Housing Survey (AHS), conducted every two 
years by the Census Bureau for HUD. The latest detailed report 
analyzes data from the 1999 AHS. Although it focuses on the housing 
problems faced by very-low-income renters, it also presents basic 
data on families and households in owner-occupied housing.\36\
---------------------------------------------------------------------------

    \36\ HUD has published an update on ``worst case housing 
needs,'' which found that the number of such households rose from 
4.86 million in 1999 to 5.07 million in 2001. However, detailed 
tables for 2001 have not been published.
---------------------------------------------------------------------------

    The ``Worst Case'' report measures three types of problems faced 
by homeowners and renters:
    1. Cost or rent burdens where housing costs or rent exceed 50 
percent of income (a ``severe burden'') or range from 31 percent to 
50 percent of income (a ``moderate burden'');
    2. The presence of physical problems involving plumbing, 
heating, maintenance, hallway, or the electrical system, which may 
lead to a classification of a residence as ``severely inadequate'' 
or ``moderately inadequate;'' and,
    3. Crowded housing, where there is more than one person per room 
in a residence.
    The study reveals that in 2001, 5.1 million very low income 
renter households had ``worst case'' housing needs, defined as 
housing costs greater than 50 percent of household income or 
severely inadequate housing among unassisted very-low-income renter 
households.\37\ Among the 5.1 million worst case needs renters, 4.8 
million (94 percent) had a severe rent burden and 10 percent of 
renters lived in housing that was severely inadequate.
---------------------------------------------------------------------------

    \37\ This does not constitute a significant difference from the 
1999 figure of 4.9 million households. However, when the focus is 
narrowed to renters with incomes below 50 percent of AMI, a 
statistically significant change emerges; there were 4 percent fewer 
units affordable to this group in 2001 than there were in 1999.
---------------------------------------------------------------------------

a. Problems Faced by Owners

    Of the 68.8 million owner households in 1999, 5.8 million (8 
percent) confronted a severe cost burden and another 8.7 million 
(12.7 percent) faced a moderate cost burden. There were 870,000 
households with severe physical problems, 2 million with moderate 
physical problems and 905,000 that were overcrowded. The report 
found that 25 percent of American homeowners faced at least one 
severe or moderate problem.
    Not surprisingly, problems were most common among very low-
income owners.\38\ Almost a third of these households (31 percent) 
faced a severe cost burden, and an additional 22 percent faced a 
moderate cost burden. And 8 percent of these families lived in 
severely or moderately inadequate housing, while 2 percent faced 
overcrowding. Only 42 percent of very-low-income owners reported no 
problems.
---------------------------------------------------------------------------

    \38\ Very-low-income households are defined as those whose 
income, adjusted for household size, does not exceed 50 percent of 
HUD-adjusted area median income. This differs from the definition 
adopted by Congress in the GSE Act of 1992, which uses a cutoff of 
60 percent and which does not adjust income for family size for 
owner-occupied dwelling units.
---------------------------------------------------------------------------

    Over time the percentage of owners faced with severe or moderate 
physical problems has decreased, as has the portion living in 
overcrowded conditions. However, affordability problems have become 
more common--the shares facing severe (moderate) cost burdens were 
only 3 percent (5 percent) in 1978, but rose to 5 percent (11 
percent) in 1989 and 8 percent (13 percent) in 1999. The increase in 
affordability problems apparently reflects a rise in mortgage debt 
in the late 1980s and early 1990s, from 21 percent of homeowners' 
equity in 1983 to 36 percent in 1995.\39\ The Joint Center for 
Housing Studies also attributes this to the growing gap between 
housing costs and the incomes of the nation's poorest 
households.\40\ As a result of the increased incidence of severe and 
moderate cost burdens, the share of owners reporting no problems 
fell from 84 percent in 1978 to 78 percent in 1989 and 75 percent in 
1999.
---------------------------------------------------------------------------

    \39\ Edward N. Wolff, ``Recent Trends in the Size Distribution 
of Household Wealth,'' The Journal of Economic Perspectives, 12(3), 
(Summer 1998), p. 137.
    \40\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing: 2000, p. 24.
---------------------------------------------------------------------------

    Between 1999 and 2001, the number of low income owners with 
severe cost burdens (meaning those with incomes below 120 percent of 
AMI and spending more than half of their reported income on housing) 
shot up by one million. This increase proved to be the main cause of 
a highly significant nine percent jump in the overall number of low 
and moderate income owners and renters with critical housing needs. 
Part of this could be due to the heavy home equity borrowing that 
has characterized the housing market from the late 1990s to the 
present day, as well as the fact that increases in house prices have 
outpaced increases in household income. As a corollary, subprime 
lending, especially in minority communities, rose by about ten 
percentage points from the early 1990s to 2001.\41\
---------------------------------------------------------------------------

    \41\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2004. p. 1-2, 4.
---------------------------------------------------------------------------

b. Problems Faced by Renters

    Problems of all three types listed above are more common among 
renters than among homeowners. In 1999 there were 6.3 million renter 
households (19 percent of all renters) who paid more than 50 percent 
of their income for rent.\42\ Another 7.1 million faced a moderate 
rent burden. Thus in total 40 percent of renters paid more than 30 
percent of their income for rent.
---------------------------------------------------------------------------

    \42\ Rent is measured in this report as gross rent, defined as 
contract rent plus the cost of any utilities that are not included 
in contract rent.
---------------------------------------------------------------------------

    Among very-low-income renters, 71 percent faced an affordability 
problem, including 40 percent who paid more than half of their 
income in rent. Almost one-third (31 percent) of renters with 
incomes between 51 percent and 80 percent of area median family 
income also paid more than 30 percent of their income for rent.
    Affordability problems have increased over time among renters. 
The shares of renters with severe or moderate rent burdens rose from 
32 percent in 1978 to 36 percent in 1989 and 40 percent in 1999.
    The share of households living in inadequate housing in 1999 was 
higher for renters (11 percent) than for owners (4 percent), as was 
the share living in overcrowded housing (5 percent for renters, but 
only 1 percent for owners). Crowding and inadequate housing were 
more common among lower-income renters, but among even the lowest 
income group, affordability was the dominant problem. The prevalence 
of inadequate and crowded rental housing diminished over time until 
1995, while affordability problems grew.
    Other problems faced by renters discussed in the most recent 
detailed ``Worst Case'' report include a sharp decline (of 2.3 
million,

[[Page 63650]]

or 14 percent) between 1991 and 1999 in the number of rental units 
affordable to very-low-income families, and a worsening of the 
national shortage of units affordable and available to extremely-
low-income families (those with incomes below 30 percent of area 
median income). In 2001, the shortage for extremely-low-income 
families was approximately 5 million units, not statistically 
different from the 1999 number. However, between 1999 and 2001, the 
number of units available to renters with incomes below 50 percent 
of AMI dropped from 78 units to 76 units per 100 renters, in part 
because more of the units affordable to this group of renters were 
occupied by higher-income renters. Shortages of units affordable and 
available to extremely-low-income households were most pressing in 
the West and Northeast, especially in metropolitan areas in those 
regions. In 2001, the West was the only region to experience a 
significant decline in number of units affordable to renters with 
incomes below 50 percent of AMI. This decline occurred even in the 
wake of an increase in affordable units in the West during the 
1990s.

4. Rehabilitation and Other National Housing Needs

    In addition to the broad housing needs discussed above, there 
are additional needs confronting specific sectors of the housing and 
mortgage markets. One example of these specific needs concerns the 
rehabilitation of the nation's older housing stock. A major problem 
facing lower-income households is that low-cost housing units 
continue to disappear from the existing housing stock. Older 
properties are in need of upgrading and rehabilitation. These aging 
properties are concentrated in central cities and older inner 
suburbs, and they include not only detached single-family homes, but 
also small multifamily properties that have begun to deteriorate. 
But obtaining the funds to fix up older properties can be difficult. 
The owners of small rental properties in need of rehabilitation may 
be unsophisticated in obtaining financing. The properties are often 
occupied, and this can complicate the rehabilitation process. 
Lenders may be reluctant to extend credit because of a sometimes-
inaccurate perception of high credit risk involved in such loans. 
The GSEs and other market participants have recently begun to pay 
more attention to these needs for financing of affordable rental 
housing rehabilitation. However, extra effort is required, due to 
the complexities of rehabilitation financing, as there is still a 
need to do more.
    The rehabilitation of our aging housing stock is but one example 
of the housing and mortgage issues that need to be addressed. 
Several other examples will be provided throughout the following 
sections on the economic, housing, and demographic conditions in the 
single-family and multifamily markets, as well as in Appendices B-D. 
The discussion will cover a wide range of topics, such as subprime 
lending, predatory lending, automated underwriting systems, 
manufactured housing, the special needs of the single-family rental 
market, and challenges associated with producing affordable 
multifamily housing--just to name a few.

C. Factor 2: Economic, Housing, and Demographic Conditions: Single-
Family Mortgage Market

    This section discusses economic, housing, and demographic 
conditions that affect the single-family mortgage market. After a 
review of housing trends and underlying demographic conditions that 
influence homeownership, the discussion focuses on specific issues 
related to the single-family owner mortgage market. This subsection 
includes descriptions of recent market interest rate trends, 
refinance and home purchase activity, homebuyer characteristics, and 
the state of affordable lending. Other special topics examined 
include the growth in subprime lending, the increased use of 
automated underwriting, and the remaining homeownership potential 
among existing renters. Section D follows with a discussion of the 
economic, housing, and demographic conditions affecting the mortgage 
market for multifamily rental properties.

1. Recent Trends in the Housing Market

    While most other sectors of the economy were weak or declining 
during 2001 and 2002, the housing sector showed remarkable strength. 
Again in 2003, the housing market enjoyed an outstanding year. The 
numbers of single-family permits, starts, completions, new home 
sales, and existing home sales were record-breaking. Home ownership 
was also at an all-time high, and mortgage interest rates continued 
to stay under six percent on average. In addition, the prosperity of 
the market stimulated GDP, contributing 0.37 percent to its overall 
growth rate of 3.1 percent. Although the multifamily sector 
experienced high vacancies and low lease-up rates, the vitality of 
the single family market was strong enough to result in a 
spectacular peak in total permits and starts as well as builders' 
attitudes and housing affordability.\43\
---------------------------------------------------------------------------

    \43\ US Housing Market Conditions, 4th Quarter, 2003. HUD Office 
of Policy Development and Research.
---------------------------------------------------------------------------

    Single-Family Permits, Starts, and Completions. Builders took 
out 1,440,400 single-family permits in 2003, up 6 percent from 2002. 
The 2003 level was the highest number of single-family permits ever 
reported in the 44-year history of this series. Single-family starts 
totaled 1,498,500 housing units, up 10 percent from 2002, a new 
single-family record. Construction was completed on 1,386,200 
single-family housing units, up 5 percent from 2002.
    Sales of New and Existing Homes. After leveling out in 2000, 
housing sales have boomed in the past three years, reaching record 
highs in 2001, 2002, and again in 2003. New single family home 
sales, which increased an average 6.3 percent per year between 1992 
and 2002, reached a record high of 1,085,000 units in 2003, an 
increase of 12 percent over 2002 sales. The market for new homes has 
been strong in the Mid Atlantic, Midwest and Great Plains.
    The National Association of Realtors reported that 6.1 million 
existing homes were sold in 2003, overturning the old record set in 
2002 by almost 9 percent, and setting an all-time high in the 35-
year history of the series. Combined new and existing home sales set 
a national record of 6.2 million in 2002 and a record of almost 7.2 
million in 2003.
    One of the strongest sectors of the housing market in past years 
had been manufactured homes, but that sector has declined recently. 
Between 1991 and 1996, manufactured home shipments more than 
doubled, peaking in 1998 at 373,000. However, shipments fell more 
than 20 percent in both 2000 and 2001. In 2002, the industry shipped 
169,000 new manufactured homes, down 12.4 percent from 2001. This 
was the lowest number of manufactured home shipments since 1963. In 
2003, the number of new manufactured homes shipped plummeted to 
131,000, down 22.5 percent from 2002. Repossession has been cited as 
a cause for the sales drop-off, as has the popularity of 
conventional stick-built housing.
    Homeownership Rate. In 1980, 65.6 percent of Americans owned 
their own home, but due to the unsettled economic conditions of the 
1980s, this share fell to 63.8 percent by 1989. But since 1994, 
gains in the homeownership rate have occurred in each year, with the 
rate reaching another record mark of 68.3 percent in 2003.
    Gains in homeownership have been widespread over the last eight 
years.\44\ As a result, the homeownership rate rose from:
---------------------------------------------------------------------------

    \44\ Homeownership rates prior to 1993 are not strictly 
comparable with those beginning in 1993 because of a change in 
weights from the 1980 Census to the 1990 Census.
---------------------------------------------------------------------------

     42.0 percent in 1993 to 48.8 percent in 2003 for 
African American households,
     39.4 percent in 1993 to 46.7 percent in 2003 for 
Hispanic households,
     73.7 percent in 1993 to 79.1 percent in 2003 for 
married couples with children,
     65.1 percent in 1993 to 68.4 percent in 2003 for 
household heads aged 35-44, and
     48.9 percent in 1993 to 52.3 percent in 2003 for 
central city residents.

However, as these figures demonstrate, sizable gaps in homeownership 
remain.
    Economy/Housing Market Prospects. Job growth has been less 
robust in the recent recovery than some previous recoveries. 
However, the economy grew at a rate of 2.2 percent in 2002 and even 
faster in 2003.\45\ Although the Federal Reserve has recently begun 
raising short term interest rates, mortgage interest rates remain 
low, supporting housing affordability.
---------------------------------------------------------------------------

    \45\ National Association of Realtors, ``Near Record Homes Sales 
Projected for 2003,'' December 3, 2002.
---------------------------------------------------------------------------

    Fannie Mae expects existing home sales to reach 5.7 million in 
2004 and 2005.\46\ Projected at 1.84 million in 2003, the National 
Association of Home Builders expects housing starts to decline to 
1.77 million in 2004 and 1.71 million in 2005.\47\ The Mortgage 
Bankers Association forecasts that 2004 housing starts will total 
1.73 million units and the 30-year fixed mortgage

[[Page 63651]]

rate will average 6.1 percent.\48\ After more than doubling from a 
relative trough in 2000 to an estimated $2.6 trillion in 2002, 
Fannie Mae projected in December 2003 that mortgage originations 
will drop to $1.8 trillion in 2004 and $1.5 trillion in 2005.\49\
---------------------------------------------------------------------------

    \46\ Fannie Mae, ``Berson's Economic and Mortgage Market 
Development Outlook,'' December 2003. http://www.fanniemae.com/media/pdf/berson/monthly/2003/121203.pdf.
    \47\ http://www.nahb.org.
    \48\ Mortgage Bankers Association of America, Mortgage Finance 
Forecast, December 17, 2003. http://www.mbaa.org/marketdata/forecasts/mffore1103.pdf.
    \49\ Fannie Mae, ``Berson's Economic and Mortgage Market 
Development Outlook,'' December 2003.
---------------------------------------------------------------------------

2. Underlying Demographic Conditions

    Between 2000 and 2025, the U.S. population is expected to grow 
by an average of 2.5 million per year.\50\ This will likely result 
in at least 1.1 million new households per year.\51\ Recently 
revised increases in population projections by the Census Bureau 
push population figures higher with the Joint Center estimating new 
household growth at 13.3 million from 2005 to 2015.\52\ This section 
discusses important demographic trends behind these overall 
household numbers that will likely affect housing demand in the 
future. These demographic forces include the baby-boom, baby-bust 
and echo baby-boom cycles; immigration trends; non-traditional and 
single households; ``trade-up buyers;'' and the growing income 
inequality between people with different levels of education. HUD's 
Office of Policy Development and Research funded a study, Issue 
Papers on Demographic Trends Important to Housing, which analyzes 
effects of demographic conditions on the housing market. The 
findings are presented throughout the sections that follow.\53\
---------------------------------------------------------------------------

    \50\ U.S. Census Bureau, Population Projections Table NP-T1.
    \51\ Martha Farnsworth Riche, ``How Changes in the Nation's Age 
and Household Structure Will Reshape Housing Demand in the 21st 
Century,'' in Issue Papers on Demographic Trends Important to 
Housing, Urban Institute Final Report to the Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, September 2002, p. 5.
    \52\ Joint Center for Housing Studies at Harvard University, 
State of the Nation's Housing 2004, p.10-11.
    \53\ Barry Chiswick, Paul Miller, George Masnick, Zhu Xiao Di, 
and Martha Farnsworth Riche, Issue Papers on Demographic Trends 
Important to Housing. Urban Institute Final Report to the Office of 
Policy Development and Research, U.S. Department of Housing and 
Urban Development, September 2002.
---------------------------------------------------------------------------

    As explained below, the role of traditional first-time 
homebuyers, 25-to-34-year-old married couples, in the housing market 
will be smaller in the current decade due to the aging of the 
population. For the first time in history, the population will have 
roughly equal numbers of people in every age group. Between 2000 and 
2025, the Census Bureau projects that the largest growth in 
households will occur among householders 65 and over.\54\ Thus, an 
increasing percentage of the population will be past their home 
buying peak in the next two decades. However, because homeownership 
rates do not peak until population groups reach 65 to 74 years of 
age, this age cohort will continue to provide housing demand. 
According to Riche, the increasing presence of older households 
should increase the proportion of the population that owns, rather 
than rents housing.\55\
---------------------------------------------------------------------------

    \54\ Martha Farnsworth Riche, ``How Changes in the Nation's Age 
and Household Structure Will Reshape Housing Demand in the 21st 
Century,'' in Issue Papers on Demographic Trends Important to 
Housing. Urban Institute Final Report to the U.S. Department of 
Housing and Urban Development, September 2002, p. 4.
    \55\ Ibid. p. 6.
---------------------------------------------------------------------------

    Growing housing demand from immigrants and non-traditional 
homebuyers will help to offset declines in the demand for housing 
caused by the aging of the population. Riche's study estimates that 
minorities will account for two-thirds of the growth in U.S. 
households over the next 25 years,\56\ and by 2025, non-family 
households will make up a third of all households. The ``echo baby-
boom'' (that is, children of the baby-boomers) will also add to 
housing demand in the current and next decades. Finally, the growing 
income inequality between people with and without a post-secondary 
education will continue to affect the housing market.
---------------------------------------------------------------------------

    \56\ The National Association of Homebuilders estimates base 
housing demand will average 1.84 million units but increases that 
estimate to 2.19 million units with high immigration.
---------------------------------------------------------------------------

    The Baby-Boom Effect. The demand for housing during the 1980s 
and 1990s was driven, in large part, by the coming of home buying 
age of the baby-boom generation, those born between 1945 and 1964. 
Homeownership rates for the oldest of the baby-boom generation, 
those born in the 1940s, rival those of the generation born in the 
1930s. Due to significant house price appreciation in the late-1970s 
and 1980s, older baby-boomers have seen significant gains in their 
home equity and subsequently have been able to afford larger, more 
expensive homes. Circumstances were not so favorable for the middle 
baby-boomers. Housing was not very affordable during the 1980s, 
their peak home buying age period. As a result, the homeownership 
rate, as well as wealth accumulation, for the group of people born 
in the 1950s lags that of the generations before them.\57\
---------------------------------------------------------------------------

    \57\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 1998, p. 14.
---------------------------------------------------------------------------

    As the youngest of the baby-boomers (those born in the 1960s) 
reached their peak home buying years in the 1990s, housing became 
more affordable. While this cohort has achieved a homeownership rate 
equal to the middle baby-boomers, they live in larger, more 
expensive homes. As the baby-boom generation ages, demand for 
housing from this group is expected to wind down.\58\
---------------------------------------------------------------------------

    \58\ Ibid. p. 15.
---------------------------------------------------------------------------

    The baby-boom generation was followed by the baby-bust 
generation, from 1965 through 1977. Since this population cohort is 
smaller than that of the baby boom generation, it reduced housing 
demand in the preceding decade and is expected to do the same in the 
current decade, though, as discussed below, other factors kept the 
housing market very strong in the 1990s. However, the echo baby-boom 
generation (the children of the baby-boomers, who were born after 
1977), while smaller than the baby-boom generation, will reach peak 
home buying age later in the first decade of the millennium.
    Immigrant Homebuyers. Past, present, and future immigration will 
also contribute to gains in the homeownership rate. During the 
1990s, 9.8 million legal immigrants entered the United States, as 
compared to 6.3 million entering in the 1980s and 4.2 million during 
the 1970s. Overall, the increase in the immigrant population 
directly accounted for 35 percent of the nation's rise in population 
in the 1990s.\59\ As a result, the foreign-born population of the 
United States more than tripled from 9.6 million in 1970 to 31.1 
million in 2000. Immigrants who become citizens buy homes at rates 
nearly as high as their same-aged native-born counterparts and for 
those aged 25 to 34, the gap is virtually nonexistent.\60\ Moreover, 
U.S.-born children of immigrants often have higher homeownership 
rates than the same-age children of native-born parents.\61\ 
However, there are concerns about the assimilation into 
homeownership of recent Hispanic immigrants who are less educated 
than earlier cohorts of immigrants. Many immigrants also locate in 
high-priced housing markets, which makes it more difficult for them 
to achieve homeownership.
---------------------------------------------------------------------------

    \59\ Federation for American Immigration Reform, <http://www.fairus.org/html/042us604.htm#ins, site visited 
December 13, 2002.
    \60\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2004, p. 11-12.
    \61\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2002, pp. 16-17.
---------------------------------------------------------------------------

    Although net foreign immigration is projected to decline in the 
current decade after 2002, high levels of immigration in the late 
1980s and throughout the 1990s will have lasting positive effects on 
housing demand. New immigration in the current and next decades is 
projected to create 6.9 million net new households, but the majority 
of household growth in the period (16.9 million) will come from 
people already resident in the U.S. including the foreign-born 
population.\62\ While immigrants tend to rent their first homes upon 
arriving in the United States, homeownership rates are substantial 
for those that have lived here for at least 6 years. In 1996, the 
homeownership rate for recent immigrants was 14.7 percent while it 
was 66.9 percent for foreign-born naturalized citizens after six 
years.\63\ Higher-than-average foreign-born fertility rates and high 
rates of homeownership for immigrants living in the country for 
several years and among the children of immigrants suggest that past 
immigration will continue to create housing demand.
---------------------------------------------------------------------------

    \62\ George S. Masnick and Zhu Xiao Di, ``Projections of U.S. 
Households By Race/Hispanic Origin, Age, Family, Type, and Tenure to 
2020: A Sensitivity Analysis,'' in Issue Papers on Demographic 
Trends Important to Housing. Urban Institute Final Report to the 
U.S. Department of Housing and Urban Development, September 2002, p. 
5.
    \63\ Fred Flick and Kate Anderson, ``Future of Housing Demand: 
Special Markets,'' Real Estate Outlook, 1998, p. 6.
---------------------------------------------------------------------------

    Past and future immigration will lead to increasing racial and 
ethnic diversity, especially among the young adult

[[Page 63652]]

population. As immigrant minorities account for a growing share of 
first-time homebuyers in many markets, HUD and others will have to 
intensify their focus on removing discrimination from the housing 
and mortgage finance systems. The need to meet nontraditional credit 
needs, respond to diverse housing preferences, and overcome the 
information barriers that many immigrants face will take on added 
importance. In order to address these needs, the mortgage industry 
must offer innovative products and improve outreach efforts to 
attract minority homebuyers.
    Nontraditional and Single Homebuyers. While overall growth in 
new households has slowed down, nontraditional households have 
become more important in the homebuyer market. As the population 
ages both relatively and absolutely, the nation's households will 
become smaller and more diverse. Riche notes that in 2000, 
traditional family households represented fewer than one in four 
households and were surpassed by both single-person households and 
married couples without children. With later marriages and more 
divorces, single-parent and single-person households have increased 
rapidly. In fact, single-parent households grew from 4 percent of 
family households in 1950 to 12 percent in 2000. Single-person 
households are now the nation's second most numerous household type, 
accounting for over 25 percent of all households. In the future, 
longer life expectancies and the continuing preference for one or 
two children will make households without children even more 
numerous. Projected to compose 80 percent of all households by 2025, 
nontraditional family households will play an increasingly important 
role in the home buying market.\64\
---------------------------------------------------------------------------

    \64\ Riche, 2002, p. 1.
---------------------------------------------------------------------------

    Trade-up Buyers. Due to weak house price appreciation, 
traditional ``trade-up buyers'' stayed out of the market during the 
early 1990s. Their absence may explain, in part, the large 
representation of nontraditional homebuyers during that period. 
However, since 1995 home prices have increased more than 30 
percent.\65\ The greater equity resulting from recent increases in 
home prices should lead to a larger role for ``trade-up buyers'' in 
the housing market during the next 10 to 15 years. In addition, the 
growing number of higher-income, mid-life households will increase 
households' potential to ``trade up'' to more expensive housing.\66\
---------------------------------------------------------------------------

    \65\ Average new-home price: U.S. Census Bureau, <http://www.census.gov/const/uspriceann.pdf.
    \66\ Riche, 2002, p. 17.
---------------------------------------------------------------------------

    Growing Income Inequality. The Census Bureau reported that the 
top 5 percent of American households received 22.4 percent of 
aggregate household income in 2001, up from 21.4 percent in 1998 and 
up sharply from 16.1 percent in 1977. The share accruing to the 
lowest 80 percent of households fell from 56.5 percent in 1977 to 
50.8 percent in 1998 and again to 49.8 percent in 2001. The share of 
aggregate income accruing to households between the 80th and 95th 
percentiles of the income distribution was virtually unchanged from 
1977 to 2001.\67\
---------------------------------------------------------------------------

    \67\ All data in this paragraph are from the U.S. Census 
Bureau's Historical Income Table H2.
---------------------------------------------------------------------------

    The increase in income inequality over past decades has been 
especially significant between those with and those without post-
secondary education. The Census Bureau reports that by 1999, the 
annual earnings of workers with a bachelor's degree were 1.8 times 
the annual earnings of workers with a high school education.\68\ The 
inflation-adjusted median earnings of high school graduates were at 
the same level in 2001 as in 1991 while the earnings of bachelor 
degree-holders rose nearly 9 percent over the same period.\69\
---------------------------------------------------------------------------

    \68\ Jennifer Cheeseman Day and Eric C. Newburger, The Big 
Payoff: Educational Attainment and Synthetic Estimates of Work-Life 
Earnings, U.S. Bureau of the Census, Current Population Reports P23-
210, July 2002, p. 3.
    \69\ U.S. Census Bureau, Historical Income Table H13.
---------------------------------------------------------------------------

    So, while homeownership is highly affordable, those without 
post-secondary education often lack the financial resources to take 
advantage of the opportunity. As discussed earlier, the days of the 
well-paying unionized factory job have passed. They have given way 
to technological change that favors white-collar jobs requiring 
college degrees, and wages in the manufacturing jobs that remain are 
experiencing downward pressures from economic globalization. The 
effect of this is that workers without the benefit of a post-
secondary education find their demand for housing constrained. This 
is especially problematic for recent immigrants who are more likely 
to have limited educational attainment and English language 
proficiency.
    Summary. Over the next two-and-a-half decades, the number of 
U.S. households is projected to increase by nearly 27 million. Of 
these new households, non-Hispanic white and traditional households 
will contribute only one-third and one-tenth of the growth, 
respectively. As the baby-boomers aged out of their peak home buying 
stage and the baby-bust generation aged into their peak home buying 
stage in the late 1980s, demand for housing was dampened by 
demographic factors during the 1990s. (Of course, other factors such 
as low interest rates propelled the housing market to record levels 
during this period.) As the echo baby-boomers begin to enter their 
peak home buying age, housing demand should pick up again through 
the remainder of the current decade and into the next. As these 
demographic factors play out, the overall effect on housing demand 
will likely be sustained growth and an increasingly diverse 
household population from which to draw new homeowners. There are 
continuing concerns about the increasing income inequality of our 
population and those recent immigrants and other persons who have 
limited education.

3. Basic Trends in the Single-Family Mortgage Market

    Mortgage lending in the nation is growing at unprecedented 
levels. Residential mortgage originations soared to $2.5 trillion in 
2002, a 22 percent increase over the previous record of $2.06 
trillion set in 2001.\70\ Originations then jumped to $3.8 trillion 
in 2003, with refinances accounting for 66 percent (or $2.5 
trillion) of this total.
---------------------------------------------------------------------------

    \70\ ``Mortgage Originations Hit Record-Busting $2.5 Trillion in 
2002, IMF Numbers Reveal,'' Inside Mortgage Finance, January 24, 
2003, p. 3.
---------------------------------------------------------------------------

    This boom in lending over the past three years can be attributed 
to low mortgage interest rates and a record number of refinances. 
Approximately 40 percent of mortgage debt outstanding, or $2.5 
trillion, was refinanced during the 2001-02 refinance boom. Freddie 
Mac calculates total home equity cashed out in 2002 at 105.4 billion 
and estimates that number will increase to 138.8 billion in 
2003.\71\ This section focuses on recent interest rate trends, the 
refinance market, the home purchase market, and first-time 
homebuyers. The section concludes by examining the GSEs' 
acquisitions as a share of the primary single-family mortgage 
market, and provides mortgage market prospects.
---------------------------------------------------------------------------

    \71\ Freddie Mac ``Cash-Out Refi Report.''
---------------------------------------------------------------------------

a. Mortgage Characteristics

    Interest Rate Trends and Volatility. Historically low mortgage 
interest rates in the late 1990s and 2001-2003 helped maintain 
consumer confidence in the housing sector as the economy emerged 
from its first recession in almost a decade. After high and 
fluctuating mortgage rates in the 1980s and early 1990s, recent 
years have seen a period of lower and more stable rates. The 1980s 
began with interest rates on mortgages for new homes above 12 
percent but quickly rose to more than 15 percent.\72\ By 1987-88, 
rates dipped into single digits but were rising again by 1989-90. 
Rates declined in the early 1990s, reaching a low of 6.8 percent in 
late 1993. An upturn in rates in 1994 and 1995 peaked at 8.3 percent 
in early 1995. By 1998, 30-year fixed conventional mortgages 
averaged 6.95 percent, the lowest level since 1968 but saw a rise in 
1999 to 7.44 percent. Mortgage rates then continued to rise in 2000, 
averaging 8.05 percent for the year, before falling to a low of 6.62 
percent in October 2001 and averaging 6.97 percent for 2001 as a 
whole.\73\ Rates averaged 5.83 percent during 2003 \74\, reaching a 
low of 5.23 in June. Rates in 2004 have averaged 5.83 through 
August, reaching a low of 5.45 in March. \75\
---------------------------------------------------------------------------

    \72\ Interest rates in this section are effective rates paid on 
conventional home purchase mortgages on new homes, based on the 
Monthly Interest Rate Survey (MIRS) conducted by the Federal Housing 
Finance Board and published by the Council of Economic Advisers 
annually in the Economic Report of the President and monthly in 
Economic Indicators. These are average rates for all loan types, 
encompassing 30-year and 15-year fixed-rate mortgages and adjustable 
rate mortgages.
    \73\ U.S. Housing Market Conditions, 2nd Quarter 2002, August 
2002, Table 14.
    \74\ U.S. Housing Market Conditions, 4th Quarter 2003, February 
2004, pg.1.
    \75\ Mortgage Bankers Association website. MBA Weekly Survey of 
Mortgage Applications, Monthly Average Interest Rates On 30-Year 
Fixed-Rate Mortgages. http://www.mortgagebankers.org/marketdata/index.html.
---------------------------------------------------------------------------

    Other Loan Terms. When mortgage rates are low, most homebuyers 
prefer to lock in a fixed-rate mortgage (FRM). Adjustable-rate 
mortgages (ARMs) are more attractive when

[[Page 63653]]

rates are high, because they carry lower rates than FRMs and because 
buyers may hope to refinance to an FRM when mortgage rates decline. 
The Federal Housing Finance Board (FHFB) reports that the ARM share 
of the market fell from 20 percent in 1993 to a record low of 12 
percent in 1998, before rising back to 21 percent in 1999. The ARM 
share continued to rise to 24 percent in 2000, but then fell 
dramatically to a low of 12 percent in 2001 as mortgage rates 
decreased. However, in 2002 and 2003, there was a rebound in the ARM 
share of the market. Though it still is nowhere near the size it was 
in the mid to late 1990s, the past two years have seen the share 
climb to 17 and 19 percent, respectively.\76\
---------------------------------------------------------------------------

    \76\ http://www.fhfb.gov/mirs/mirs_t25.xls.
---------------------------------------------------------------------------

    In 2003, the term-to-maturity was 30 years for 80 percent of 
conventional home purchase mortgages, continuing to decline after 
steadily climbing to a high of 90 percent in 2000. The other major 
term of maturity in 2003 was 15 years (16 percent).\77\
---------------------------------------------------------------------------

    \77\ http://www.fhfb.gov/mirs/mirstbl5.xls; data for 2003 is 
average of May through December data.
---------------------------------------------------------------------------

    Low- and no-point mortgages continue to be a popular option for 
mortgage purchases. FHFB reports that average initial fees and 
charges (``points'') have decreased from 2.5 percent of loan balance 
in the mid-1980s to 2 percent in the late-1980s, 1.5 percent in the 
early 1990s, and less than 1 percent in 1995-97. The downward trend 
continued throughout the late 1990s with the average initial fees 
and charges reaching a low of one-half percent in 2001, staying 
there in 2002, and dipping even further down in 2003. Coupled with 
declining interest rates, these lower transactions costs have 
increased the propensity of homeowners to refinance their 
mortgages.\78\
---------------------------------------------------------------------------

    \78\ This is discussed in more detail in Paul Bennett, Richard 
Peach, and Stavros Peristani, Structural Change in the Mortgage 
Market and the Propensity to Refinance, Staff Report Number 45, 
Federal Reserve Bank of New York, September 1998.
---------------------------------------------------------------------------

    Another major change in the conventional home mortgage market 
has been the proliferation and then diminution of high loan-to-value 
ratio (LTV) mortgages. According to data from the Federal Housing 
Finance Board, loans with LTVs greater than 90 percent (that is, 
down payments of less than 10 percent) made up less than 10 percent 
of the market in 1989-91, but 25 percent of the market in 1994-97, 
gradually decreasing to an average of 20 percent of the market in 
2003. Loans with LTVs less than or equal to 80 percent fell from 
three-quarters of the market in 1989-91 to an average of 56 percent 
of the market in 1994-97, but then rose to an average of 63 percent 
of mortgages originated in 1998-2001, and rose again to an average 
of 70 percent of mortgages originated in 2002-2003.\79\ As a result, 
the average LTV rose from 75 percent in 1989-91 to nearly 80 percent 
in 1994-97, and then declined to 76.2 percent in 2001, 75.1 percent 
in 2002, and 73.5 percent in 2003.\80\
---------------------------------------------------------------------------

    \79\ http://www.fhfb.gov/mirs/mirs_t1.xls.
    \80\ Other sources of data on loan-to-value ratios such as the 
American Housing Survey and the Chicago Title and Trust Company 
indicate that high-LTV mortgages are somewhat more common in the 
primary market than the Finance Board's survey. However, the Chicago 
Title survey does not separate FHA-insured loans from conventional 
mortgages. In addition, the statistics cited above pertain only to 
home purchase mortgages. Refinance mortgages generally have shorter 
terms and lower loan-to-value ratios than home purchase mortgages.
---------------------------------------------------------------------------

b. Refinance Mortgages

    Over the past ten years, refinance booms occurred three times, 
during 1992-93, 1998, and 2001-03. Refinancing has fueled the growth 
in total mortgage originations, which were $638 billion in 1995 (a 
period of low refinance activity), but topped $2.5 trillion in 2002 
(a period of heavy refinance activity). The refinance share of total 
mortgage originations rose to 50 percent in 1998, then decreased to 
19 percent in 2000 before jumping to 57 percent in 2001, and 59 
percent in 2002. During the 2001-02 refinance boom, approximately 40 
percent of the $2.5 trillion in mortgage debt outstanding was 
refinanced. In 2003, the refinance share of total mortgage 
originations hit 66 percent, though late 2003 saw a steep drop-off 
from a 68 percent share in the third quarter to a 49 percent share 
in the fourth.\81\
---------------------------------------------------------------------------

    \81\ The source for the refinance share and total mortgage 
originations is the Mortgage Bankers Association (http://www.mortgagebankers.org/marketdata/forecasts/mffore1203.pdf, http://www.mortgagebankers.org/marketdata/forecasts/ffJUNE2004.pdf).
---------------------------------------------------------------------------

    In 1989-90 interest rates exceeded 10 percent, and refinancings 
accounted for less than 25 percent of total mortgage 
originations.\82\ The subsequent sharp decline in mortgage rates 
drove the refinance share over 50 percent in 1992 and 1993 and 
propelled total single-family originations to more than $1 trillion 
in 1993--twice the level attained just three years earlier.
---------------------------------------------------------------------------

    \82\ Refinancing data is taken from Freddie Mac's monthly 
Primary Mortgage Market Survey.
---------------------------------------------------------------------------

    The refinance wave subsided after 1993, because most homeowners 
who found it beneficial to refinance had already done so and because 
mortgage rates rose once again.\83\ Total single-family mortgage 
originations bottomed out at $638 billion in 1995, when the 
refinance share was only 21 percent. Total originations, driven by 
the volume of refinancings, amounted to $1.507 trillion in 1998, 
nearly 50 percent higher than the previous record level of $1.02 
trillion attained in 1993.
---------------------------------------------------------------------------

    \83\ There is some evidence that lower-income borrowers did not 
participate in the 1993 refinance boom as much as higher-income 
borrowers--see Paul B. Manchester, Characteristics of Mortgages 
Purchased by Fannie Mae and Freddie Mac: 1996-97 Update, Housing 
Finance Working Paper No. HF-006, Office of Policy Development and 
Research, Department of Housing and Urban Development, August 1998, 
pp. 30-32.
---------------------------------------------------------------------------

    The refinance wave from late 1997 through early 1999 reflected 
other factors besides interest rates, including greater borrower 
awareness of the benefits of refinancing, a highly competitive 
mortgage market, and the enhanced ability of the mortgage industry, 
utilizing automated underwriting and mortgage origination systems to 
handle an unprecedented volume of originations. The refinance share 
decreased to 19 percent in 2000 before jumping to a record 57 
percent in 2001.
    Historically low interest rates and declining mortgage 
transaction costs have driven the latest refinancing boom. Given 
these conditions, the after-tax cost saving on a new, lower-rate 
loan is much greater than the transaction costs of refinancing. In 
addition, the appreciation of housing prices has also contributed to 
the increase in refinancing. Over the past five years, the value of 
housing rose by approximately $5 trillion, and the rise in value has 
enabled lenders to service refinancing homeowners because of greater 
confidence in the creditworthiness of borrowers.\84\
---------------------------------------------------------------------------

    \84\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 4.
---------------------------------------------------------------------------

    Over the past few years, homeowners have become more willing to 
draw on the rising equity in their homes. According to Fannie Mae's 
2002 National Housing Survey, homeowners that refinanced during 2001 
withdrew about $110 billion in accumulated home equity wealth.\85\ 
Freddie Mac estimates that more than one-half of all refinance 
mortgages in the past two years involved cash-out refinancing.\86\
---------------------------------------------------------------------------

    \85\ Fannie Mae, 2002 Fannie Mae National Housing Survey. 
<http://www.fanniemae.com/global/pdf/media/survey/survey2002, September 4, 2002, p. 2.
    \86\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 4.
---------------------------------------------------------------------------

    The refinancing boom contributed to an estimated one-fifth of 
the national economy's real GDP growth since late 2000.\87\ During 
2001 and 2002, roughly $270 billion was raised in cash-out 
refinancing. Approximately one-half of cash from cash-out 
refinancing has enabled consumers to finance more spending for 
expenses such as home improvements, medical payments, education, and 
vehicles during a weakened economy. Roughly one-third of the cash 
from cash-out refinancing has allowed consumers to repay other 
debt.\88\ The remaining cash from cash-out refinancing has enabled 
consumers to invest in other assets. Refinancing households save 
approximately $10 billion in their annual interest payments on their 
mortgage and consumer installment liabilities.
---------------------------------------------------------------------------

    \87\ Mark M. Zandi, ``Refinancing Boom,'' Regional Finance 
Review, December 2002, p. 11.
    \88\ Ibid. p. 14.
---------------------------------------------------------------------------

    The refinancing boom will have lingering effects. Mortgage 
borrowers that were able to secure low long-term interest rates 
through fixed rate mortgages will have more of their budgets to 
spend on other items. Meanwhile, cash-out borrowers, who are just 
receiving their money, will spend this year. It must be noted there 
is some concern regarding the potential for increased credit risk 
stemming from mortgage debt from cash out borrowers. According to a 
2002 Regional Finance Review article, the mortgage liabilities of 
households have been growing at a rate more than double the growth 
in household incomes. However, this potential credit risk is 
moderated by the strong growth in housing values. The ratio of 
mortgage debt to housing

[[Page 63654]]

values, the aggregate loan-to-value ratio, has remained fairly 
stable for a decade.\89\
---------------------------------------------------------------------------

    \89\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 9.
---------------------------------------------------------------------------

c. Home Purchase Mortgages

    The volume of home purchase mortgages was $505 billion in 1995, 
rose to $848 billion in 1999, and remained in the $829-$873 billion 
range between 1999-2001 before jumping to $1.02 trillion in 2002 and 
$1.30 trillion in 2003. The Mortgage Bankers Association (MBA) 
forecasts that the home purchase volume will be $1.52 trillion in 
2004 as the home purchase share rises to 57 percent of all 
originations.\90\ The home purchase share of total mortgage 
originations was 79 percent in 1995, declined to 50 percent in 1998, 
rose to 81 in 2000, and sharply fell to 43 percent in 2001, 41 in 
2002, and 34 percent in 2003, as refinance mortgage volume grew. 
This section discusses the important issue of housing affordability 
and then examines the value of homeownership as an investment.
---------------------------------------------------------------------------

    \90\ Mortgage Bankers Association, ``Mortgage Finance 
Forecast'', September 17, 2004. http://www.mortgagebankers.org/marketdata/forecasts/mffore1203.pdf.
---------------------------------------------------------------------------

    The National Association of Realtors (NAR) has developed a 
housing affordability index, calculated as the ratio of median 
household income to the income needed to qualify for a median price 
home (the latter income is called the ``qualifying income''). In 
1993, NAR's affordability index was 133, which meant that the median 
family income of $37,000 was 33 percent higher than that income 
needed to qualify for the median priced home. Housing affordability 
remained at about 130 for 1994-97, with home price increases and 
somewhat higher mortgage rates being offset by gains in median 
family income.\91\ Falling interest rates and higher income led to 
an increase in affordability to 143 in 1998, reflecting the most 
affordable housing in 25 years. Affordability remained high in 1999, 
despite the increase in mortgage rates. NAR's affordability index 
declined from 140 in 1999 to 129 in 2000 as mortgage rates 
increased. The index turned upward to 136 in 2001 as mortgage rates 
fell and maintained this average in 2002, before rising further to 
140 in 2003.\92\
---------------------------------------------------------------------------

    \91\ Housing affordability varies markedly between regions, 
ranging in January 2004 from 194 in the Midwest to 107 in the West, 
with the South and Northeast falling in between.
    \92\ National Association of REALTORS. Housing Affordability 
Index, <http://www.realtor.org/Research.nsf/Pages/HousingInx>, 2003.
---------------------------------------------------------------------------

    Although the share of home purchase loans for lower-income 
households and/or households living in lower-income communities 
increased over the past decade, affordability still remains a 
challenge for many. The median sales price of existing single-family 
homes in the United States continues to rise, reaching $158,100 in 
2002 and $170,000 in 2003. The production of affordable housing and 
low interest rates could offset the negative impact of rising house 
prices, which undermine housing affordability for many Americans, 
particularly in several high-cost markets on the east and west 
coasts.
    As discussed earlier, barriers are preventing many potential 
homeowners from becoming homeowners, thus reducing the possible 
amount of home purchase loans. While the strong housing sector has 
provided financial security for many Americans, a 2002 Fannie Mae 
survey found that ``information barriers still keep many financially 
qualified families-particularly minority Americans from becoming 
homeowners or obtaining the lowest-cost financing available to 
them.'' \93\
---------------------------------------------------------------------------

    \93\ Fannie Mae, September 4, 2002, p.2.
---------------------------------------------------------------------------

    These homeownership barriers pose a serious problem for many 
Americans who view homeownership as a smart, safe, long-term 
investment, rating homeownership as a better investment than the 
stock market. Home equity is the single most important asset for 
approximately two-thirds of American households that are homeowners. 
Considering that half of all homeowners held at least 50 percent of 
their net wealth in home equity in 1998, increasing housing 
affordability is important for many Americans.\94\
---------------------------------------------------------------------------

    \94\ Ibid.
---------------------------------------------------------------------------

    First-time Homebuyers. First-time homebuyers are a driving force 
in the nation's mortgage market. The recent low interest rates have 
made it an opportune time for first-time homebuyers, which are 
typically people in the 25-34 year-old age group that purchase 
modestly priced houses. As the post-World War II baby boom 
generation ages, the percentage of Americans in this age group 
decreased from 28.3 percent in 1980 to 25.4 percent in 1992.\95\ 
Even though this cohort is smaller, first-time homebuyers increased 
their share of home sales. According to Chicago Title data for major 
metropolitan areas, the first-time buyer share of the homebuyer 
market increased from roughly 40 percent in the beginning of the 
1990s to 45-47 percent during the-mid and late 1990s.\96\ Since the 
late 1990s, industry survey data suggest that the first-time 
homebuyer percentage has decreased slightly. In the first quarter of 
2003, the share of all home purchases by first-time homebuyers was 
40 percent compared to 42 percent in 2001.\97\
---------------------------------------------------------------------------

    \95\ U.S. Department of Commerce, Bureau of the Census, Money 
Income of Households, Families, and Persons in the United States: 
1992, Special Studies Series P-60, No. 184, Table B-25, October 
1993.
    \96\ Chicago Title and Trust Family of Insurers, Who's Buying 
Homes in America, 1998.
    \97\ National Association of Realtors. ``New NAR Survey of Home 
Buyers and Sellers Shows Growing Web Use in a Dynamic Housing 
Market.'' http://www.realtor.org.
---------------------------------------------------------------------------

    In the 1990s, lenders developed special programs targeted to 
first-time homebuyers and revised their underwriting standards to 
enhance homeownership opportunities for low-income families with 
special circumstances. The disproportionate growth in the number of 
first-time homebuyers and minority homebuyers largely drove the 
rising trend in total home purchases. Analysis of the American 
Housing Survey (AHS) indicates there were 1.3 million new first-time 
homebuyers during 1991, in comparison with over two million in each 
year between 1996 and 2001. In addition, first-time homebuyers 
comprised approximately 60 percent of all minority home purchases 
during the 1990s, compared with about 35 percent of all home 
purchases by non-Hispanic white families.
    In comparison to repeat homebuyers, first-time homebuyers are 
more likely to be younger, have lower incomes, and purchase less 
expensive houses. According to the AHS, more than one-half or first-
time homebuyers were below the age of 35, compared with less than 
one-quarter of repeat buyers in the 1990s. Thirty-nine percent of 
first-time buyers had incomes below 80 percent of the median 
compared to 30 percent of repeat buyers. Fifty-four percent of 
first-time buyers purchased homes priced below $100,000, compared to 
37 percent of repeat buyers. Minorities comprise a higher proportion 
of first-time buyers (32 percent) compared to repeat buyers (14 
percent). Compared to repeat buyers, first-time homebuyers are more 
likely to purchase a home in the central city and more likely to be 
a female-headed household.\98\
---------------------------------------------------------------------------

    \98\ U.S. Housing Market Conditions, 3rd Quarter 2001, November 
2001, Table 4.
---------------------------------------------------------------------------

    The National Association of Realtors reports that the average 
first-time homebuyer in the first quarter of 2003 was 32 years old 
with a household income of $54,800, compared to an average age of 46 
years and average household income of $74,600 for repeat buyers. The 
average first-time homebuyers made a downpayment of 6 percent on a 
home that cost $136,000 while the average repeat buyer made a 
downpayment of 23 percent on a home costing $189,000. In the NAR 
survey, 37 percent of first-time homebuyers were single compared to 
28 percent of repeat buyers.\99\
---------------------------------------------------------------------------

    \99\ National Association of Realtors. ``New NAR Survey of Home 
Buyers and Sellers Shows Growing Web Use in a Dynamic Housing 
Market.'' http://www.realtor.org.
---------------------------------------------------------------------------

    Many African Americans and Hispanics are likely to purchase 
homes in the coming years, contributing to the number of first-time 
home-buyers fueling growth in the housing sector. The number of 
homeowners will rise by an average of 1.1 million annually over the 
next two decades. The sizeable rise in the foreign-born population 
since the 1970's coupled with the increase in Latin American and 
Asian immigration will also contribute much to this growth.\100\
---------------------------------------------------------------------------

    \100\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2002, p. 2.
---------------------------------------------------------------------------

d. GSEs' Acquisitions as a Share of the Primary Single-Family Mortgage 
Market

    Purchases by the GSEs of single-family mortgages amounted to 
$519 billion during the heavy refinancing year of 1993, stood at 
$215 billion in 1995, and were at $618 billion during the heavy 
refinancing year of 1998. Purchases then fell to $395 billion in 
2000 before reaching record levels during the heavy refinancing 
years of 2001 ($961 billion) and 2002 ($1,090 billion). Purchases by 
Fannie Mae decreased from $316 billion in 1999 to $227 billion in 
2000, before rising to $568 billion in 2001, $800 billion in 2002, 
and $1.3 trillion in 2003. Freddie Mac's

[[Page 63655]]

single-family mortgage purchases followed a similar trend, falling 
from $233 billion in 1999 to $168 billion in 2000, and then rising 
to $393 billion in 2001 and $475 billion in 2002.\101\
---------------------------------------------------------------------------

    \101\ Office of Federal Housing Enterprise Oversight (OFHEO), 
Report to Congress, 2004, Tables 1 and 11.
---------------------------------------------------------------------------

    The Office of Federal Housing Enterprise Oversight (OFHEO) 
estimates that the GSEs' share of total originations in the 
conventional single-family mortgage market, measured in dollars, 
declined from 37 percent in 1996 to 32 percent in 1997--well below 
the peak of 51 percent attained in 1993. OFHEO attributes the 1997 
downturn in the GSEs' role to increased holdings of mortgages in 
portfolio by depository institutions and to increased competition 
with Fannie Mae and Freddie Mac by private label issuers. However, 
OFHEO estimates that the GSEs' share of the conventional market 
rebounded sharply in 1998-99, to 43-42 percent. The GSEs' share then 
decreased to approximately 30 percent of the single-family 
conventional mortgages originated in 2000, and then increased 
sharply to 40 percent in 2001. Total GSE purchases, including loans 
originated in prior years, amounted to 46 percent of conventional 
originations in 2001\102\ and approximately 38 percent of family 
home mortgage originations in 2002.\103\
---------------------------------------------------------------------------

    \102\ Office of Federal Housing Enterprise Oversight. ``Mortgage 
Markets and The Enterprises in 2001,'' August 2002, p. 13.
    \103\ http://www.financialservicesfacts.org/financial2/mortgage/mortgages/?table_sort_734796=4.
---------------------------------------------------------------------------

e. Mortgage Market Prospects

    The Mortgage Bankers Association (MBA) reports that mortgage 
originations in 2001 were $2.0 trillion, which is almost twice the 
volume of originations in 2000. Mortgage originations then increased 
to record levels of $2.5 trillion in 2002 and $3.8 trillion in 2003, 
with refinancings representing 66 percent of originations and the 
purchase volume amounting to $1.3 trillion. Estimates indicate that 
ARMs accounted for 19 percent of total mortgage originations in 
2003.\104\ In its September 17, 2004 forecast, MBA predicts that 
single-family mortgage originations will amount to $2.7 trillion in 
2004 and $1.8 trillion in 2005, with refinancings representing 43 
percent and 25 percent of originations respectively.
---------------------------------------------------------------------------

    \104\ Mortgage market projections from the MBA's MBA Mortgage 
Finance Forecast, December 17, 2003. 2000 and 2001 numbers from the 
MBA's MBA Mortgage Finance Forecast, January 10, 2002.
---------------------------------------------------------------------------

4. Affordable Lending in the Mortgage Market: New Products and Outreach

    Extending homeownership opportunities to historically 
underserved households has been a growing concern for conventional 
lenders, private mortgage insurers and the GSEs. The industry has 
responded in what some have called a ``revolution in affordable 
lending''. The industry has offered more customized mortgage 
products, more flexible underwriting, and expanded outreach so that 
the benefits of the mortgage market can be extended to those who 
have not been adequately served through traditional products, 
underwriting, and marketing.
    Fannie Mae and Freddie Mac have been a part of this ``revolution 
in affordable lending''. During the mid-to-late 1990s, they added 
flexibility to their purchase guidelines, they introduced new low-
down-payment products, and they worked to expand the use of credit 
scores and automated underwriting in evaluating the creditworthiness 
of loan applicants. These major trends reflect changes in the GSEs' 
underwriting that have impacted affordable lending. Through these 
trends, Fannie Mae and Freddie Mac have attempted to increase their 
capacity to serve low- and moderate-income homebuyers.
    This section summarizes recent initiatives undertaken by the 
GSEs and others in the industry to expand affordable housing. The 
end of this section will present evidence that these new industry 
initiatives are working, as increased mortgage credit has been 
flowing to low-income and minority families. The following section 
will continue the affordable lending theme by examining the 
performance of different market sectors (e.g., depositories, GSEs, 
etc.) in funding loans for low-income and minority families. That 
section will also discuss the important role that FHA plays in 
making affordable housing available to historically underserved 
groups as well as the continuing concern that participants in the 
conventional market could be doing even more to help underserved 
families.

a. Lowering Down Payments and Up-Front Costs

    Numerous studies have concluded that saving enough cash for a 
down payment and for up-front closing costs is the greatest barrier 
that low-income and minority families face when considering 
homeownership.\105\ To assist in overcoming this barrier, the 
industry (including lenders, private mortgage insurers and the GSEs) 
began offering in 1994 mortgage products that required down payments 
of only 3 percent, plus points and closing costs. Other industry 
efforts to reduce borrowers' up-front costs included zero-point-
interest-rate mortgages and monthly insurance premiums with no up 
front component. These new plans eliminated large up-front points 
and premiums normally required at closing.
---------------------------------------------------------------------------

    \105\ See Charles, K. K. and E. Hurst (2002). ``The Transition 
to Home Ownership and the Black-White Wealth Gap.'' The Review of 
Economics and Statistics, 84(2): 281-297; Mayer, C. and G. 
Engelhardt (1996). ``Gift Down Payments and Housing Affordability.'' 
Journal of Housing Research, 7(1): 59-77; and Quercia, R. G., G. W. 
McCarthy, et al. (2003). ``The Impacts of Affordable Lending Efforts 
on Homeownership Rates.'' Journal of Housing Economics, 12(1): 29-
59.
---------------------------------------------------------------------------

    During 1998, Fannie Mae introduced its ``Flexible 97'' and 
Freddie Mac introduced its ``Alt 97'' low down payment lending 
programs. Under these programs, borrowers were required to put down 
only 3 percent of the purchase price. The down payment, as well as 
closing costs, could be obtained from a variety of sources, 
including gifts, grants or loans from a family member, the 
government, a non-profit agency and loans secured by life insurance 
policies, retirement accounts or other assets. Fannie Mae continues 
to offer the ``Flexible'' line of products, and Freddie Mac 
continues to list ``Alt 97.''
    In 2000, Fannie Mae launched the ``MyCommunityMortgage'' suite 
of products, which provides high loan-to-value product options for 
low- and moderate-income borrowers. In 2003, Fannie Mae purchased or 
securitized more than $2.27 billion of MyCommunityMortgage products, 
which helped provide affordable housing solutions for 20,400 
households. In addition, Fannie Mae enhanced the MyCommunityMortgage 
to help lenders further expand affordable financing to underserved 
families. Examples of these enhancements included adding 
MyCommunityMortgage to Desktop Underwriter in order to provide 
lenders easier access to customized CRA-targeted loan products, 
adding new credit and income flexibilities for borrowers purchasing 
single family homes, Community HomeChoice which offers more flexible 
requirements for persons with disabilities, Community 2-4 FamilyTM 
to help make the purchase of 2-4 unit homes more affordable for 
first time homebuyers, and Community RenovationTM 1-4 Family Pilot 
to help borrowers with home improvement and housing preservation 
costs.\106\ Additionally, in 2003, Fannie Mae enhanced Community 2-4 
Family and Community Renovation 1-4 Family pilots. This product 
provides lower down payments and flexible parameters for owner-
occupants of 1-4 unit properties.\107\
---------------------------------------------------------------------------

    \106\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 8-9.
    \107\ Fannie Mae, ``Fannie Mae's Comments on HUD's Proposed 
Housing Goals for Fannie Mae and Freddie Mac for the years 2005-2008 
and Amendments to HUD's Regulation of Fannie Mae and Freddie Mac,'' 
July 16, 2004, p. I-58.
---------------------------------------------------------------------------

    Fannie Mae also expanded its ``Flexible'' product line with the 
``Flexible 100'' product, which eliminates the requirement for a 
down payment by providing 100 percent loan-to-value financing. The 
borrower is required to make either a minimum of 3% (of the lesser 
of the sales price or appraised value) from approved flexible 
sources or making a minimum contribution of $500 from their own 
funds. The 3% may come from a variety on sources such as gifts, 
grants, or unsecured loans from relatives, employers, public 
agencies, or nonprofits. In 2003, Fannie Mae purchased $13.7 billion 
in Flexible loans that benefited 100,866 households.\108\
---------------------------------------------------------------------------

    \108\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
p. 6.
---------------------------------------------------------------------------

    Fannie Mae has also developed products specifically geared 
toward populations with unique needs such as seniors, Native 
Americans and families living near public transit routes. Examples 
of these targeted products include the Home Equity Conversion 
Mortgage (HECM) which allows seniors to convert the equity in their 
homes to receive cash. In 2003, Fannie Mae purchased 27,644 HECM's 
for a total value of $1.87 billion. PaymentPowerTM allows 
borrowers with strong credit to skip their regularly scheduled 
monthly payment up to two times during a twelve-month period and up 
to ten times during the life of the loan. This pilot was launched in 
July 2002 and by year-end 2003, Fannie Mae purchased 963 
PaymentPowerTM mortgages totaling $126 million. Navajo 
Community Guaranty Initiative allows Navajo families to contribute

[[Page 63656]]

a minimum of $500 or 1% of the purchase price, whichever is lower. 
This initiative, announced in 2003, will provide $3 million in home 
financing to help 60 families currently living on a reservation. The 
Smart CommuteTM Initiative, which targets borrowers 
purchasing homes near a public transit route, recognizes that 
homebuyers will save commuting expenses and therefore have more 
disposable income to pay housing expenses. In 2003 Fannie Mae 
purchased approximately $5 million in Smart CommuteTM 
Initiative loans.\109\
---------------------------------------------------------------------------

    \109\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 9-10.
---------------------------------------------------------------------------

    In 2000, Freddie Mac introduced its ``Freddie Mac 100'' product, 
which is designed to assist borrowers who have good credit but lack 
the ability to provide a large down payment. ``Freddie Mac 100'' 
allows a 100 percent loan-to-value ratio with the condition that the 
borrower has the funds for closing costs. In 2003, a refinance 
option was added to Freddie Mac 100 and the cost of the loan was 
reduced through lower mortgage insurance coverage and a lower fee 
for the product. These changes have made the Freddie Mac 100 
available to borrowers who may not have been able to take advantage 
of the refinance boom as a result of low or no equity in their 
homes.\110\
---------------------------------------------------------------------------

    \110\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
62.
---------------------------------------------------------------------------

    Another Freddie Mac product, Affordable Gold[reg] 97 
permits borrowers to make 3% down payments from personal cash and to 
use other sources to cover their closing costs, and offers flexible 
ratio and reserves guidelines. In 2003 this product was enhanced 
with a refinance option allowing more borrowers to take advantage of 
the low rates in the market. The Affordable Gold[reg] 100 
provides 100 percent financing to low- and moderate-income borrowers 
for the purchase price of a home in California. Affordable 
Gold[reg] 100 combines mortgage insurance benefits 
provided by a state insurance fund, the secondary mortgage market, 
and a team of the nation's leading mortgage lenders.\111\
---------------------------------------------------------------------------

    \111\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
62.
---------------------------------------------------------------------------

    Additional Freddie Mac products include the Alt 97\SM\ for 
borrowers who have good credit but limited cash for a down payment. 
In 2003, this product was enhanced with a refinance option and 
reduced fees. The Two-Family 95 Percent LTV Program offers low down 
payment loans to purchasers of two-family properties when the 
borrowers occupy one of the units as their primary residence.\112\ 
Other initiatives include policies aimed at improving the 
homeownership rate among immigrant families and the Section 8 Rental 
to Homeownership program, which allows people currently receiving 
Section 8 rental subsidies to use them toward mortgage payments. 
\113\ Freddie Mac purchases loans in which the borrower's down 
payment consists of funds that have been matched through an 
Individual Development Account homebuyer savings program. And in 
2003, Freddie Mac provided increased liquidity for affordable 
housing through a series of targeted investments in Mortgage Revenue 
Bonds containing state and local housing finance agency 
mortgages.\114\
---------------------------------------------------------------------------

    \112\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
62-64.
    \113\ Freddie Mac Public Comment Letter on HUD's Proposed Goals, 
July 2004, p. 2.
    \114\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
62-64.
---------------------------------------------------------------------------

b. Partnerships--Fannie Mae

    In addition to developing new affordable products, lenders and 
the GSEs have been entering into partnerships with local governments 
and nonprofit organizations to increase mortgage access to 
underserved borrowers. Fannie Mae operates 55 partnership offices 
throughout the country, including the West Virginia Partnership 
Office, which opened in 2003. These offices coordinate Fannie Mae's 
programs with local governments, lenders, public officials, housing 
organizations, community nonprofits, real estate professionals, and 
other local stakeholders.\115\
---------------------------------------------------------------------------

    \115\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 22-24.
---------------------------------------------------------------------------

    Fannie Mae continues to reach out to national groups and work 
with local affiliates to expand homeownership. Fannie Mae has 
established multi-year partnerships to increase affordable housing 
opportunities with organizations such as: The Enterprise Foundation, 
The Neighborhood Reinvestment Corporation, ACORN Housing 
Corporation, The National Council of La Raza, and many others 
engaged in promoting affordable housing. In 2003, Fannie Mae 
financed $1.3 billion of mortgages with these national partners and 
participating lenders, which resulted in 9,597 loans. For example, 
Fannie Mae maintains a partnership with the National Urban League 
(NUL) and the JP Morgan Chase Bank to increase NUL's homeownership 
counseling capacity by providing the necessary technology and tools 
to support the effort, and to purchase $50 million in mortgage 
products over five years that are specifically targeted to increase 
homeownership among minorities. In 2003, approximately $6 million in 
loans were originated through this initiative. Another example is 
Fannie Mae's partnership with the AFL-CIO Housing Investment Trust 
(HIT) and Countrywide Home Loans, which launched ``HIT HOME'' in 
2001. HIT HOME is an affordable home mortgage initiative that 
targets 13 million union members in 35 cities throughout the nation 
to provide union members with a variety of affordable mortgage 
choices that enable them to qualify for competitively priced loans 
with new re-payment terms. In 2003, over $132 million worth of 
mortgages were originated through this partnership.\116\
---------------------------------------------------------------------------

    \116\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 13-16.
---------------------------------------------------------------------------

    In order to meet the needs of underserved and low- and moderate-
income populations, Fannie Mae has targeted specific populations for 
initiatives. These include the Section 8 Homeownership Initiative, 
which purchased 81 Section 8 loans and funded an additional 55 loans 
through a Community Development Financial Institution investment; 
the Native American Homeownership Initiative, which has committed to 
invest at least $350 million to support homeownership strategies for 
4,600 Native American families and to work with 100 tribes; the 
Minority- and Women-Owned Lenders Initiative, to reach underserved 
communities and to develop innovative solutions for increasing 
business opportunities for these lenders; The Employer-Assisted 
Housing Initiative, designed to assist employers in developing a 
company benefit that helps employees meet their housing needs; and 
the Initiative to Reduce Barriers to Affordable Housing, which has 
established local partnerships in seven new states and localities in 
2003. Additionally, Fannie Mae conducts various underwriting 
experiments aimed at eliminating obstacles faced by prospective 
homebuyers across the country. In 2003, Fannie Mae approved $222 
million worth of Housing and Community Development place-based 
commitments for a total of 55 experiments.\117\
---------------------------------------------------------------------------

    \117\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 17-22.
---------------------------------------------------------------------------

    Fannie Mae's American Dream Commitment is part of its National 
Minority Homeownership Initiative which has pledged to contribute at 
least $700 billion in private capital to serve 4.6 million families 
towards President George W. Bush's goal of expanding homeownership 
to 5.5 million new minority Americans by the end of the decade. 
Towards this goal, in 2003, Fannie Mae executed 17 new Housing and 
Community Development lender partnerships which seek to provide $394 
billion in affordable housing lending to minority families.\118\
---------------------------------------------------------------------------

    \118\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 16.
---------------------------------------------------------------------------

    Under the American Dream Commitment, Fannie Mae has committed to 
establishing 250 faith-based homeownership partnerships in 
communities across the country by the end of the current decade. The 
objective of this initiative is to build strong partnerships with 
national faith-based organizations in order to reach potential new 
homeowners, work with faith-based and nonprofit partners to help 
increase access to homeownership information and education, partner 
with lenders to increase access to mortgage financing, and provide 
faith-based organizations with the tools, training, and resources 
needed to advance their community development efforts. Fannie Mae's 
work under the Faith-Based Initiative in 2003 resulted in $125 
million in mortgage financing to underserved families across the 
country.\119\ Additionally, Fannie Mae attended more than 12 faith-
based symposiums providing training and technical assistance to over 
2,000 symposium attendees.\120\
---------------------------------------------------------------------------

    \119\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 17-18.
    \120\ Fannie Mae, ``Fannie Mae's Comments on HUD's Proposed 
Housing Goals for Fannie Mae and Freddie Mac for the years 2005-2008 
and Amendments to HUD's Regulation of Fannie Mae and Freddie Mac,'' 
July 16, 2004, p. I-60.

---------------------------------------------------------------------------

[[Page 63657]]

c. Partnerships--Freddie Mac

    Freddie Mac does not have a partnership office structure similar 
to Fannie Mae's, but it has undertaken a number of initiatives in 
specific metropolitan areas.\121\ Freddie Mac works with affordable 
housing lenders to design creative solutions to meet homeownership 
needs of specific populations in targeted areas; explore efficient 
use of public subsidies to make homeownership more affordable and 
develop homebuyer education/counseling and debt management 
assistance programs.\122\ In 2001, Freddie Mac joined the 
Congressional Black Caucus to launch a new initiative, ``With 
Ownership Wealth,'' designed to increase African-American 
homeownership with one million new families by 2005.\123\ Freddie 
Mac has partnered with the National Council of La Raza (NCLR), 20 
community based NCLR affiliated housing counseling organizations, 
the National Association of Hispanic Real Estate Professionals 
(NAHREP), EMT Applications and participating Freddie Mac Seller/
Servicers including Bank of America, U.S. Bank and Wells Fargo Home 
Mortgage on the ``En Su Casa'' initiative. This $200 million 
homeownership initiative combines technology tools with flexible 
mortgage products to meet the needs of Hispanic borrowers. Mortgage 
products include low down payments, flexible credit underwriting and 
debt-to-income ratios, and streamlined processing for resident alien 
borrowers.\124\
---------------------------------------------------------------------------

    \121\ Freddie Mac, News Release, January 15, 1999.
    \122\ Freddie Mac Public Comment Letter on HUD's Proposed Goals, 
July 2004, p. 3.
    \123\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
67.
    \124\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
66-67.
---------------------------------------------------------------------------

    In 2002, Freddie Mac joined with the City of Boston and the U.S. 
Conference of Mayors to make available the ``Don't Borrow Trouble'' 
predatory lending educational campaign to approximately 1,100 
cities. As of the end of 2003, the campaign has been launched in 
more than 30 localities. Additionally, in late 2003, Freddie Mac 
sponsored a national Don't Borrow Trouble summit. Attorneys, 
community activists and local leaders from 23 cities convened to 
share campaign experiences and to learn about emerging predatory 
lending trends from some of the nation's leading community lending 
experts.\125\
---------------------------------------------------------------------------

    \125\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
37-38.
---------------------------------------------------------------------------

    In addition, Freddie Mac joined with Rainbow/PUSH and the 
National Urban League to promote the CreditSmart[reg] financial 
educational curriculum that helps consumers understand, obtain and 
maintain good credit, thereby preparing them for homeownership and 
other personal financial goals. Rainbow/PUSH has organized 
CreditSmart[reg] classes with more than 80 churches across the 
nation, reaching more than 2,500 congregants. Bilingual curriculum 
was launched for this program in December 2002, and during 2003 
CreditSmart[reg] Espa[ntilde]ol conducted a total of 23 Train-the-
Trainer workshops for their partners and their local partners 
resulting in 326 trainers who are authorized to teach the 
CreditSmart[reg] Espa[ntilde]ol curriculum. Thus far 503 adults have 
been trained in the CreditSmart[reg] Espa[ntilde]ol financial 
literacy program.\126\ The CreditSmart[reg]/Homeownership 
Development Initiative with the National Urban League has nine 
affiliates located in Birmingham, AL; Charlotte, NC; Louisville, KY; 
Greenville, SC; Oklahoma City, OK; Springfield, IL; and Washington, 
DC; with Orlando, FL and Knoxville, TN added in 2003. Since the 
initiative's launch in early 2002, 41 CreditSmart[reg] financial 
literacy workshops have been presented to more than 600 minority 
participants. Those participants are proceeding to the next steps to 
achieving homeownership, and in 2003 313 loans have closed as a 
direct result.\127\
---------------------------------------------------------------------------

    \126\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
38-39.
    \127\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
39-40.
---------------------------------------------------------------------------

    In 2002 and 2003, Freddie Mac joined with the American Community 
Bankers, the Credit Union National Association, and the Independent 
Community Bankers of America in strategic alliances to better enable 
member banks and credit unions access to the secondary market.\128\
---------------------------------------------------------------------------

    \128\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
42-43.
---------------------------------------------------------------------------

    In June 2002, President George W. Bush challenged the nation's 
housing industry to invest more than $1 trillion to make 
homeownership a reality for 5.5 million more minority households for 
the decade. Freddie Mac responded to the challenge with Catch the 
Dream which is a comprehensive set of 25 high impact initiatives 
aimed at accelerating the growth in minority homeownership. The 
initiatives range from homebuyer education and outreach, to new 
technologies with innovative mortgage products. Freddie Mac has 
committed to purchase $400 billion in mortgages made to minority 
families by the end of the decade.\129\ Catch the Dream represents a 
collaborative effort with lenders, nonprofit housing and community-
based organizations, and other industry participants to expand 
homeownership opportunities for America's minorities.\130\ In 2003 
initiatives were implemented in Birmingham, Charlotte, Atlanta, 
DeKalb County (GA), Lansing, and San Antonio. In 2003, single-family 
owner occupied mortgage purchases financed homes for almost 700,000 
minority families, including mortgages for 133,000 African-American 
and 250,000 Hispanic families (this comprised 16% of Freddie Mac's 
single-family, owner-occupied mortgage purchases and 22.6% of their 
first-time homebuyer mortgage purchases).\131\
---------------------------------------------------------------------------

    \129\ Freddie Mac Public Comment Letter on HUD's Proposed Goals, 
July 2004, p. 4.
    \130\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
29-30.
    \131\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
30-34.
---------------------------------------------------------------------------

    The programs mentioned above are examples of the partnership 
efforts undertaken by the GSEs. There are more partnership programs 
than can be adequately described here. Fuller descriptions of these 
programs are provided in their Annual Housing Activity Reports.

d. Underwriting and GSE Purchase Guidelines

    Lenders, mortgage insurers, and the GSEs have also been 
modifying their mortgage underwriting standards to address the needs 
of families who have historically found it difficult to qualify 
under traditional guidelines. In addition to the changes in 
underwriting standards, the use of automated underwriting has 
dramatically transformed the mortgage application process. This 
section focuses on changes to traditional underwriting standards and 
recent GSE initiatives for credit-impaired borrowers. Subsequent 
sections will provide more details on the impact of automated 
underwriting.
    The GSEs modified their underwriting standards to address the 
needs of families who find qualifying under traditional guidelines 
difficult. The goal of these underwriting changes is not to loosen 
underwriting standards, but rather to identify creditworthiness by 
alternative means that more appropriately measures the unique 
circumstances of low-income, immigrant, and minority households. 
Examples of changes that the GSEs and others in the industry have 
made to their underwriting standards include the following:
     Using a stable income standard rather than a stable job 
standard (or a minimum period of employment). This particularly 
benefits low-skilled applicants who have successfully remained 
employed, even with frequent job changes.
     Using an applicant's history of rent and utility 
payments as a measure of creditworthiness. This measure benefits 
lower-income applicants who have not established a credit history.
     Allowing pooling of funds for qualification purposes. 
This change benefits applicants with extended family members. 
Freddie Mac, for example, allows income from relatives who live 
together to pool their funds to cover downpayment and closing costs 
and to combine their incomes for use in calculating the borrower's 
stable monthly income.
    These underwriting changes have been accompanied by 
homeownership counseling to ensure homeowners are ready for the 
responsibilities of homeownership. In addition, the industry has 
engaged in intensive loss mitigation to control risks.
    In 1999, HUD commissioned a study by the Urban Institute to 
examine the underwriting criteria that the GSEs use when purchasing 
mortgages from primary lenders.\132\ According to the study, while 
the GSEs had improved their ability to serve low- and moderate-
income borrowers, it did not

[[Page 63658]]

appear at that time that they had gone as far as some primary 
lenders to serve these borrowers. From the Urban Institute's 
discussion with lenders, it was found that primary lenders were 
originating mortgages to lower-income borrowers using underwriting 
guidelines that allow lower down payments, higher debt-to-income 
ratios and poorer credit histories than allowed by the GSEs' 
guidelines.
---------------------------------------------------------------------------

    \132\ Kenneth Temkin, Roberto Quercia, George Galster, and 
Sheila O'Leary, A Study of the GSEs' Single Family Underwriting 
Guidelines: Final Report. Washington DC: U.S. Department of Housing 
and Urban Development, April 1999.
---------------------------------------------------------------------------

    From this and other evidence, the Urban Institute concluded that 
the GSEs were lagging the market in servicing low- and moderate-
income and minority borrowers. Furthermore, the Urban Institute 
found ``that the GSEs' efforts to increase underwriting flexibility 
and outreach has been noticed and is applauded by lenders and 
community advocates. Despite the GSEs' efforts in recent years to 
review and revise their underwriting criteria, however, they could 
do more to serve low- and moderate-income borrowers and to minimize 
disproportionate effects on minorities.'' \133\ Since the Urban 
Institute study, Freddie Mac and Fannie Mae have been playing a 
larger role in financing low-income and minority borrowers. (See 
Section E.2.)
---------------------------------------------------------------------------

    \133\ Temkin, et al. 1999, p. 28.
---------------------------------------------------------------------------

    In addition to offering low-down-payment programs, the GSEs' 
recent efforts have also centered around their automated 
underwriting systems and their treatment of borrowers with blemished 
credit, the latter being perhaps the most controversial underwriting 
issue over the past few years. Freddie Mac has a variety of products 
and initiatives aimed at providing borrowers with impaired credit 
more mortgage choices. These products include: 
CreditWorksSM which helps borrowers with excessive debt 
and impaired credit to become eligible for a prime market rate 
mortgage faster than would otherwise be possible, Affordable Merit 
RateSM Mortgage which permits borrowers to qualify at an 
initial interest rate that in many cases is lower than the usual 
subprime rate, and LeasePurchase Plus Initiative, which provides 
closing cost and down payment assistance in addition to extensive 
counseling for borrowers who have had credit issues in the past or 
who have never established a credit history. During 2003, Freddie 
Mac entered into several new markets under the LeasePurchase Plus 
Initiative and purchased more than $16 million in loans.\134\
---------------------------------------------------------------------------

    \134\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, pp. 
36-37.
---------------------------------------------------------------------------

    According to Freddie Mac, its automated underwriting system, 
``Loan Prospector'' has reduced costs, made approving mortgages 
easier and faster, and increased the consistency of the application 
of objective underwriting criteria. In addition, Freddie Mac states 
that ``Loan Prospector'' extends the benefits of the mortgage 
finance system to borrowers with less traditional credit profiles 
and limited savings by more accurately measuring risk. Since its 
introduction in 1995, Freddie Mac reports that they have doubled 
their share of mortgage purchases with loan-to-value rations of 95 
percent or above.\135\ In 2003, lenders and brokers used Loan 
Prospector to evaluate 9.5 million loan applications and Loan 
Prospector has evaluated more than 35 million mortgage applications 
since its introduction in 1995.\136\ Freddie Mac reports that its 
automated underwriting system, Loan Prospector, has resulted in 
higher approval rates for minority borrowers than under traditional 
manual underwriting because of improved predictive powers. As 
mentioned in Section C.7, the 2000 version of LP approved 87.1 
percent of loans generated through affordable housing programs, 
compared to 51.6 percent approved by manual underwriting. The 
Freddie Mac study found automated mortgage scoring less 
discriminatory and more accurate in predicting risk. However, as 
noted below in the automated mortgage scoring section, there are 
concerns that the codification of certain underwriting guidelines 
could result in unintentional discrimination or disparate treatment 
across groups. In response to the potential disparate impact of 
automated underwriting, Freddie Mac have launched initiatives to 
make the mortgage process more transparent by disclosing both credit 
and non-credit factors that Loan Prospector consider when evaluating 
a loan application. In 2000, Freddie Mac has launched an initiative 
that published a list of all of the factors that Loan Prospector 
uses to analyze loans, and put the list on the Freddie Mac 
website.\137\
---------------------------------------------------------------------------

    \135\ Freddie Mac Public Comment Letter on HUD's Proposed Goals, 
July 2004, p. 5.
    \136\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
19.
    \137\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 57.
---------------------------------------------------------------------------

    In 2003, Fannie Mae released two versions of its automated 
underwriting service, ``Desktop Underwriter'' (DU), to expand its 
mortgage product offerings and to update underwriting guidelines. 
Desktop Underwriter[reg] 5.3 outlined new eligibility requirements 
for mortgages secured by manufactured homes. It also expanded the 
InterestFirstTM mortgage product line to offer borrowers 
greater purchasing power by allowing lower initial monthly payments 
than those available with traditional loan products. Desktop 
Underwriter[reg] 5.3.1 enhanced the Flexible 100 mortgage to allow 
borrowers to contribute as little as $500 of their own funds to the 
transaction. The remainder of the funds can come from flexible 
sources of funds and interested party contributions subject to 
Fannie Mae's standard contribution limit.\138\ In addition, Fannie 
Mae added MyCommunityMortgage to Desktop Underwriter[reg] in 2003, 
providing lenders easier access to customized CRA-targeted loan 
products.\139\ Automated mortgage scoring and the potential for 
disparate impacts on borrowers will be further discussed in a later 
section.
---------------------------------------------------------------------------

    \138\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 11-12.
    \139\ Fannie Mae, ``Fannie Mae's Comments on HUD's Proposed 
Housing Goals for Fannie Mae and Freddie Mac for the years 2005-2008 
and Amendments to HUD's Regulation of Fannie Mae and Freddie Mac,'' 
July 16, 2004, p. I-57.
---------------------------------------------------------------------------

5. Affordable Single-family Lending: Data Trends

a. 1993-2003 Lending Trends

    HMDA data suggest that the industry and GSE initiatives are 
increasing the flow of credit to underserved borrowers. Between 1993 
and 2003, conventional loans to low-income and minority families 
increased at much faster rates than loans to higher income and non-
minority families. As shown below, conventional home purchase 
originations to African Americans more than doubled between 1993 and 
2003 and those to Hispanic borrowers more than tripled. Home loans 
to low-income borrowers and to low-income and high-minority census 
tracts also more than doubled during this period.

------------------------------------------------------------------------
                                                            1993-2003
                                           1993-2003       Growth rate:
                                          Growth rate:     conventional
                                         all home loans     home loans
                                           (percent)        (percent)
------------------------------------------------------------------------
African-American Borrowers............              106              206
Hispanic Borrowers....................              235              357
White Borrowers.......................               44               64
Low-Income Borrower (Less than 80% of               101              150
 AMI).................................
Upper-Income Borrower (More than 120%                88              108
 of AMI)..............................
Low-Income Census Tract (only 1993-                  99              143
 2002)................................
Upper-Income Census Tract (only 1993-                64               78
 2002)................................
High-Minority Tract (only 1993-2002)                113              167
 (50% or more minority)...............
Predominantly-White Tract (only 1993-                53               64
 2002) (Less than 10% minority).......
------------------------------------------------------------------------


[[Page 63659]]

    GSE purchases showed similar trends, as indicated by the 
following 1993-to-2003 percentage point increases for metropolitan 
areas: African-American borrowers (199 percent), Hispanic borrowers 
(259 percent), and low-income borrowers (212 percent). While their 
annual purchases of all home loans increased by 60 percent between 
1993 and 2003, their purchases of mortgages that qualify for the 
three housing goals increased as follows: special affordable by 287 
percent; low- and moderate-income by 156 percent; and underserved 
areas by 121 percent.
    While low interest rates and economic expansion certainly played 
an important role in the substantial increase in conventional 
affordable lending in recent years, most observers believe that the 
efforts of lenders, private mortgage insurers, and the GSEs were 
also important contributors. In addition, many observers believe 
that government initiatives such as the GSE housing goals and the 
Community Reinvestment Act have also played a role in the growth of 
affordable lending over the past 10 years.

b. Affordable Lending Shares by Major Market Sector

    Section E below compares the GSEs' performance with the 
performance of primary lenders in the conventional conforming 
market. To provide a useful context for that analysis, this section 
examines the role of the conventional conforming market in funding 
low-income and minority families and their neighborhoods. 
Information on the mortgage market's funding of homes purchased by 
first-time homebuyers is also provided. In addition, this section 
compares the GSEs with other sectors of the mortgage market. The 
important role of FHA in the affordable lending market is 
highlighted and questions are raised about whether the conventional 
conforming market could be doing a better job helping low-income and 
minority borrowers obtain access to mortgage credit.
    Table A.1 reports borrower characteristics and Table A.2 reports 
neighborhood characteristics for home purchase mortgages insured by 
FHA, purchased by the GSEs, originated by depository institutions 
(mainly banks and thrift), and originated in the conventional 
conforming market and in the total market for owner-occupied 
properties in metropolitan areas.\140\ In this case, the ``total'' 
market consists of both the conventional conforming market and the 
government (mainly FHA and VA loans) market; ``jumbo'' loans above 
the conventional conforming loan limit are excluded from this 
analysis.\141\
---------------------------------------------------------------------------

    \140\ Table A.3 also provides the same average (1999 to 2003) 
information as Tables A.1 and A.2 but for total (both home purchase 
and refinance) loans. Thus, it provides a complete picture of 
overall mortgage activity.
    \141\ The ``Total Market'' is defined as all loans (including 
both government and conventional) below the conforming loan limit of 
$240,000 in 1999, $252,700 in 2000, $275,000 in 2001, $300,700 in 
2002 and $322,700 in 2003.
---------------------------------------------------------------------------

BILLING CODE 4210-27-P

[[Page 63660]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.010


[[Page 63661]]


[GRAPHIC] [TIFF OMITTED] TR02NO04.011


[[Page 63662]]


[GRAPHIC] [TIFF OMITTED] TR02NO04.012

BILLING CODE 4210-27-C

[[Page 63663]]

    HMDA is the source of the FHA, depository, and market data, 
while the GSEs provide their own data. Low-income, African-American, 
Hispanic, and minority borrowers are covered in Table A.1. Table A.2 
provides information on four types of neighborhoods--low-income 
census tracts, tracts where minorities (or African Americans) 
account for more than 30 percent of the census tract population, and 
underserved areas as defined by HUD. The average data reported in 
Tables A.1 and A.2 for the years 1999 to 2003 offer a good summary 
of recent lending to low-income and minority borrowers and their 
communities.\142\ Individual year data are also provided.
---------------------------------------------------------------------------

    \142\ The affordable market shares reported in Table A.1 for the 
``Conventional Conforming Market W/O B&C'' were derived by excluding 
the estimated number of B&C loans from the market data reported by 
HMDA. Because B&C lenders operate mainly in the refinance sector, 
excluding these loans from the conforming market has little impact 
on the home purchase percentages reported in Table A.1. It should be 
recognized that there exists some uncertainty regarding the number 
of B&C loans in the HMDA data. The adjustment assumes that the B&C 
loans represent one-half of the subprime market. The adjustment for 
home purchase loans is small because supbrime (B&C) loans are mainly 
refinance loans. The method for excluding B&C loans is explained in 
Section E below and Appendix D.
---------------------------------------------------------------------------

    The focus of different market sectors on affordable lending is 
summarized by the percentages reported in Tables A.1 and A.2. These 
percentages show each sector's ``distribution of business,'' defined 
as the share of loans originated (or, for the GSEs, purchased) that 
had a particular borrower or neighborhood characteristic. The 
interpretation of the ``distribution of business'' percentages can 
be illustrated using the FHA percentage for low-income borrowers: 
Between 1999 and 2003, 51.2 percent of all FHA-insured home purchase 
loans in metropolitan areas were originated for borrowers with an 
income less than 80 percent of the local area median income. These 
percentages are to be contrasted with ``market share'' percentages, 
which are presented below in Section E. A ``market share'' 
percentage is the share of loans with a particular borrower or 
neighborhood characteristic that was funded by a particular market 
sector (e.g., FHA-insured, GSEs, depositories). As will discussed 
below, FHA's ``market share'' for low-income borrowers during the 
1999-to-2003 period was estimated to be 24 percent which is 
interpreted as follows: Of all home purchase loans originated for 
low-income borrowers in metropolitan areas between 1999 and 2003, 24 
percent were FHA-insured loans. Thus, in this example, the 
``distribution of business'' percentage measures the importance (or 
concentration) of low-income borrowers in FHA's overall business 
while the ``market share'' percentage measures the importance of FHA 
to the market's overall funding of loans for low-income borrowers. 
Both concepts are important for evaluating performance--for an 
industry sector such as FHA or the GSEs to have a significant impact 
on lending to a targeted group, that sector's business must be 
concentrated on the targeted group and that sector must be of some 
size. The discussion below will focus on the degree to which 
different mortgage sectors concentrate on targeted groups, while 
Section E will also provide estimates of market shares.
    The main insights from the ``distribution of business'' 
percentages in Tables A.1 and A.2 pertain to four topics.
    (i) FHA-Insured Loans. FHA has traditionally been the mechanism 
used by borrowers who face difficulty obtaining mortgage financing 
in the private conventional market. FHA has long been recognized as 
the major source of funding for first-time, low-income and minority 
homebuyers who are not often able to raise cash for large 
downpayments.\143\ Tables A.1 and A.2 show that FHA places much more 
emphasis on affordable lending than the other market sectors. 
Between 1999 and 2003, low-income borrowers accounted for 51.2 
percent of FHA-insured loans, compared with 27.8 percent of the home 
loans purchased by the GSEs, 29.1 percent of home loans originated 
by depositories, and 29.2 percent of all originations in the 
conventional conforming market (see Table A.1). Likewise, 40.7 
percent of FHA-insured loans were originated in underserved census 
tracts, while only 24.1 percent of the GSE-purchased loans, 25.9 
percent of home loans originated by depositories, and 26.9 percent 
of conventional conforming loans were originated in these tracts 
(see Table A.2).\144\ As discussed in Section E, FHA's share of the 
minority lending market is particularly high. While FHA insured only 
16 percent of all home purchase mortgages originated below the 
conforming loan limit in metropolitan areas between 1999 and 2003, 
it is estimated that FHA insured 29 percent of all home loans 
originated for African-American and Hispanic borrowers.
---------------------------------------------------------------------------

    \143\ Almost two-thirds of the borrowers with an FHA-insured 
home purchase loan make a downpayment less than five percent, and 
over 80 percent are first-time home buyers. For discussions of the 
role of FHA in the mortgage market, see (a) Harold L. Bunce, Charles 
A. Capone, Sue G. Neal, William J. Reeder, Randall M. Scheessele, 
and Edward J. Szymanoski, An Analysis of FHA's Single-Family 
Insurance Program, Office of Policy Development and Research, U.S. 
Department of Housing and Urban Development, 1995; and (b) Office of 
Policy Development and Research, ``FHA's Impact on Homeownership 
Opportunities for Low-Income and Minority Families During the 
1990s'' Issue Brief IV, U.S. Department of Housing and Urban 
Development, December 2000. For data on the credit characteristics 
of FHA borrowers, see Harold L. Bunce, William J. Reeder and Randall 
Scheessele, ``Understanding Consumer Credit and Mortgage Scoring: A 
Work in Progress at HUD'', U.S. Department of Housing and Urban 
Development, Unpublished Paper, 1999.
    \144\ FHA, which focuses on low downpayment loans and also 
accepts borrowers with credit blemishes, experiences higher mortgage 
defaults than conventional lenders and the GSEs. Still, the FHA 
system is actuarially sound because it charges an insurance premium 
that covers the higher default costs. For the results of FHA's 
actuarial analysis, see Deloitte & Touche, Actuarial Review of MMI 
Fund as of FY 2000, report for the U.S. Department of Housing and 
Urban Development, January 2001.
---------------------------------------------------------------------------

    (ii) Conventional and GSE Minority Lending. The affordable 
lending shares for the conventional conforming sector are low for 
minority borrowers, particularly African-American and Hispanic 
borrowers. These borrowers accounted for only 15.2 percent of all 
conventional conforming loans originated between 1999 and 2003, 
compared with 34.4 percent of FHA-insured loans and 19.2 percent of 
all loans originated in the total (government and conventional 
conforming) market. Not surprisingly, the minority lending 
performance of conventional lenders has been subject to much 
criticism. Recent studies contend that primary lenders in the 
conventional market are not doing their fair share of minority 
lending which forces minorities, particularly African-American and 
Hispanic borrowers, to rely on more costly FHA and subprime 
loans.\145\ Thus, it appears that conventional lenders could be 
doing a better job helping minority borrowers obtain access to 
mortgage credit.
---------------------------------------------------------------------------

    \145\ See Green and Associates, Fair Lending in Montgomery 
County: A Home Mortgage Lending Study, a report prepared for the 
Montgomery County Human Relations Commission, March 1998; and Calvin 
Bradford, Crisis in D[eacute]j[agrave] vu: A Profile of the Racial 
Patterns in Home Purchase Lending in the Baltimore Market. Report 
for The Public Justice Center, May 2000; and The Patterns of GSE 
Participation in Minority and Racially Changing Markets Reviewed 
from the Context of Levels of Distress Associated with High Levels 
of FHA Lending, GSE Study No. 11, U.S. Department of Housing and 
Urban Development, September 2000. For analysis suggesting some 
minorities receiving FHA loans could qualify for conventional loans, 
see Anthony Pennington-Cross, Anthony Yezer, and Joseph Nichols, 
Credit Risk and Mortgage Lending: Who Uses Subprime and Why? Working 
Paper No. 00-03. Research Institute for Housing America, 2000. Also 
see the series of recent studies concerning the lack of mainstream 
lenders in minority neighborhoods.
---------------------------------------------------------------------------

     The GSEs' funding of minority loans can be compared 
with mortgages originated for minority borrowers in the conventional 
conforming market, although the latter may be a poor benchmark, as 
discussed above. Between 1999 and 2003, home purchase loans to 
African-American and Hispanic borrowers accounted for 10.4 percent 
of Freddie Mac's purchases, 14.0 percent of Fannie Mae's purchases, 
and 15.2 percent of loans originated in the conventional conforming 
market (or 14.3 percent if B&C loans are excluded from the market 
definition). Thus, since 1999, the African-American and Hispanic 
share of the GSEs' purchases has been lower than the corresponding 
share for the conventional conforming market.\146\
---------------------------------------------------------------------------

    \146\ For a comprehensive analysis of the GSEs' purchases of 
minority loans through 1999, see Harold L. Bunce, An Analysis of GSE 
Purchases of Mortgages for African-American Borrowers and their 
Neighborhoods, Housing Finance Working Paper No. 11, Office of 
Policy Development and Research, HUD, December 2000.
---------------------------------------------------------------------------

     As the above comparisons show, Fannie Mae has had a 
much better record than Freddie Mac in funding loans for minority 
families. And Fannie Mae significantly increased its purchases of 
loans for African-American and Hispanic borrowers during 2001, 
raising the share of its purchases to market levels--13.7 percent 
for both Fannie Mae and the conforming market (without B&C loans). 
In 2002, Fannie Mae surpassed

[[Page 63664]]

the conventional conforming market in funding African-American and 
Hispanic borrowers (a 15.8 percent share for Fannie Mae and a 15.0 
share for the market), but in 2003 fell slightly behind the market 
(a 16.6 percent share for Fannie Mae and a 16.9 percent share for 
the market). When all minority borrowers are considered, Fannie Mae 
has purchased mortgages for minority borrowers at a higher rate 
(years 2001, 2002 and 2003) than these loans were originated by 
primary lenders in the conventional conforming market (without B&C 
loans). Freddie Mac, on the other hand, lagged behind both the 
market and Fannie Mae in funding loans for minority borrowers during 
2001-2003, as well as during the entire 1999-to-2003 period. The 
share of Freddie Mac's purchases for African-American and Hispanic 
borrowers declined from 10.9 percent in both 2000 and 2001 to 10.1 
percent in 2002 before rising slightly to 10.7 percent in 2003.
     Considering the minority census tract data reported in 
Table A.2, Fannie Mae lagged behind the conforming market (without 
B&C loans) in high-minority neighborhoods and in high-African-
American neighborhoods during the 1999-to-2003 period. However, 
Fannie Mae improved its mortgage purchases in African-American 
neighborhoods after 2001 and essentially matched the market in 2001-
2003. And during 2001, 2002 and 2003, Fannie Mae also purchased 
loans in high-minority census tracts at a higher rate than loans 
were originated by conventional lenders in these tracts. While 
Freddie Mac has generally lagged the primary market in funding 
minority neighborhoods, note in Table A.2 that high African-American 
tracts increased from 3.9 percent of Freddie Mac's purchases in 2001 
to 5.3 percent in 2002, placing Freddie Mac above the conventional 
conforming market level (4.6 percent) in 2002. However, in 2003, 
Freddie Mac fell behind the market.
    (iii) Low-Income Lending by the GSEs. Information is also 
provided on the GSEs' purchases of home loans for low-income 
borrowers (A.1) and for families living in low-income neighborhoods 
(A.2). Historically, the GSEs have lagged behind the conventional 
conforming market in funding affordable loans for these groups. 
During the 1999-to-2003 period, low-income borrowers (census tracts) 
accounted for 27.4 (9.7) percent of Freddie Mac's purchases, 28.1 
(10.1) percent of Fannie Mae's purchases, 29.1 (11.2) percent of 
loans originated by depositories, and 29.1 (11.1) percent of home 
loans originated by conventional conforming lenders (without B&C 
loans). By the end of this period, Fannie Mae had significantly 
improved its performance relative to the market. In 2003, low-income 
borrowers accounted for 31.0 percent of Fannie Mae's purchases, 
compared with 29.2 percent for the conforming market. It is also 
interesting that even though Freddie Mac lagged the market in 
funding home loans for low-income borrowers during 2002 (28.6 
percent versus 29.1 percent), it surpassed the market in financing 
properties in low-income census tracts (11.3 percent versus 11.1 
percent). During 2003, Freddie Mac's performance was again below the 
market in low-income census tracts (a 10.3 share for Freddie Mac and 
a 11.5 percent share for the market). A more complete analysis of 
the GSEs' recent improvements in purchasing home loans that qualify 
for the housing goals is provided below in Section E.
    (iv) Depositories. Within the conventional conforming market, 
depository institutions (mainly banks and thrifts) are important 
providers of affordable lending for lower-income families and their 
neighborhoods.\147\ Between 1999 and 2003, underserved areas 
accounted for 26.9 percent of loans held in depository portfolios, 
which compares favorably with the underserved areas percentage (26.2 
percent) for the overall conventional conforming market.\148\ 
Depository lenders have extensive knowledge of their communities and 
direct interactions with their borrowers, which may enable them to 
introduce flexibility into their underwriting standards without 
unduly increasing their credit risk. The Community Reinvestment Act 
provides an incentive for banks and thrifts to initiate affordable 
lending programs with underwriting flexibility and to reach out to 
lower income families and their communities.\149\ Many of the CRA 
loans are held in portfolio by lenders, rather than sold to Fannie 
Mae or Freddie Mac.
---------------------------------------------------------------------------

    \147\ Tables A.1, A.2, and A.3 include data for all home loans 
originated by depositories as well as for the subset of loans 
originated but not sold, the latter being a proxy for loans held in 
depository portfolios. (See the notes to Table A.1 for definitions 
of the depository data.)
    \148\ However, as shown in Table A.1 , depository institutions 
resemble other conventional lenders in their relatively low level of 
originating loans for African-American, Hispanic and minority 
borrowers. Within the conventional conforming market, Fannie Mae has 
done a better job than depositories in funding minority borrowers, 
particularly Hispanic borrowers and minority borrowers as a group. 
During the last three years, Fannie Mae has also funded African-
American borrowers at a higher rate than have depository 
institutions.
    \149\ CRA loans are typically made to low-income borrowers 
earning less than 80 percent of area median income, and in moderate-
income neighborhoods. For a comprehensive analysis of CRA and its 
impact on affordable lending, see Robert E. Litan, Nicolas P. 
Retsinas, Eric S. Belsky and Susan White Haag, The Community 
Reinvestment Act After Financial Modernization: A Baseline Report, 
U.S. Department of Treasury, 2000.
---------------------------------------------------------------------------

    (v) First-time Homebuyers. As explained in Section E, market 
information on first-time homebuyers is not as readily available as 
the HMDA data reported in Tables A.1 and A.2 on the income and 
racial characteristics of borrowers and census tracts served by the 
mortgage market. However, the limited market data that are available 
from the American Housing Survey, combined with the first-time 
homebuyer data reported by FHA and the GSEs, indicate a rather large 
variation in the funding of first-time homebuyers across the 
different sectors of the mortgage market. Based on the American 
Housing Survey (AHS), it is estimated that first-time homebuyers 
accounted for 42.3 percent of all home purchase loans originated 
throughout the market between 1999 and 2001,\150\ and for 37.6 
percent of home loans originated in the conventional conforming 
market. The AHS defines a first-time homebuyer as someone who has 
never owned a home. Using a more liberal definition of a first-time 
homebuyer (someone who has not owned a home in the past three 
years), FHA reports that first-time homebuyers accounted for 80.5 
percent of all home loans that it insured between 1999 and 2001 and 
the GSEs report that first-time homebuyers accounted for 26.5 
percent of the home loans purchased by each GSE during that same 
period. Given FHA's low downpayment requirements, it is not 
surprising that FHA focuses on first-time homebuyers. The GSEs, on 
the other hand, fall at the other end of the continuum, with their 
first-time homebuyer share (26.5 percent) falling far short of the 
first-time homebuyer share (37.6 percent) of the conventional 
conforming market. Section E will include a more detailed comparison 
of the GSEs and the conventional conforming market in serving first-
time homebuyers. In addition, Section E will conduct a market share 
analysis that examines the funding of minority first-time 
homebuyers. Consistent with the earlier discussion, that analysis 
suggests that conventional lenders and the GSEs have played a 
relatively small role in the market for minority first-time 
homebuyers. One analysis reported in Section E estimates that 
mortgage purchases by the GSEs between 1999 and 2001 totaled 41.5 
percent of all home loans originated, but they accounted for only 
14.3 percent of home loans originated for first-time African-
American and Hispanic homebuyers.
---------------------------------------------------------------------------

    \150\ In this case, the market includes all government and 
conventional loans, including jumbo loans.
---------------------------------------------------------------------------

c. Community Reinvestment Act

    The Community Reinvestment Act (CRA) requires depository 
institutions to help meet the credit needs of their 
communities.\151\ CRA loans are typically made to low-income 
borrowers earning less than 80 percent of area median income, and in 
moderate-income neighborhoods. CRA provides an incentive for lenders 
to initiate affordable lending programs with underwriting 
flexibility. CRA loans are usually smaller than typical conventional 
mortgages and also are more likely to have a higher LTV, higher 
debt-to-income ratios and no payment reserves, and may not be 
carrying private mortgage insurance (PMI). Generally, at the time 
CRA loans are originated, many do not meet the underwriting 
guidelines required in order for them to be purchased by one of the 
GSEs. Therefore, many of the CRA loans are held in portfolio by 
lenders, rather than sold to Fannie Mae or Freddie Mac. Evidence is 
growing that CRA-type lending to low-income families can be 
profitable, particularly when combined with intensive loss 
mitigation efforts to control credit risk. In a recent survey 
conducted by the Federal

[[Page 63665]]

Reserve, lenders reported that most CRA loans are profitable 
although not as profitable as the lenders' standard products.\152\
---------------------------------------------------------------------------

    \151\ For a comprehensive analysis of CRA and its impact on 
affordable lending, see Robert E. Litan, Nicolas P. Retsinas, Eric 
S. Belsky and Susan White Haag, The Community Reinvestment Act After 
Financial Modernization: A Baseline Report, U.S. Department of 
Treasury, 2000.
    \152\ Board of Governors of the Federal Reserve System. The 
Performance and Profitability of CRA-Related Lending. Washington, 
DC, 2000.
---------------------------------------------------------------------------

    Some anticipate that the big growth market over the next decade 
for CRA-type lending will be urban areas. There has been some 
movement of population back to cities, consisting of aging Baby 
Boomers (so-called ``empty nesters''), the children of Baby Boomers 
(the Echo Boomers aged 18-25), and immigrants, particularly 
Hispanics but also Asians.\153\ The current low homeownership in 
inner cities (compared with the suburbs) also suggests that urban 
areas may be a potential growth market for lenders. Lenders are 
beginning to recognize that urban borrowers are different from 
suburban borrowers. A new or recent immigrant may have no credit 
history or, more likely, a loan-worthy credit history that can't be 
substantiated by the usual methods.\154\ Products for duplexes and 
four-plexes are not the same as a mortgage for a subdivision house 
in the suburbs. Programs are being implemented to meet the unique 
needs of urban borrowers. One program emphasizing urban areas was 
initiated by the American Community Bankers (ACB). Under the ACB 
program, which made $16.2 billion in loans in 2002, lenders 
originated a variety of affordable products for first-time 
homebuyers and non-traditional borrowers that are then sold to 
Fannie Mae, Freddie Mac, Countrywide, or other investors that are 
partnering with the ACB. It is reported that some lenders are making 
these non-traditional loans for the first time.
---------------------------------------------------------------------------

    \153\ This discussion of urban lending draws from Jeff Siegel, 
``Urban Lending Helps Increase Volume and Meet CRA Requirements,'' 
Secondary Marketing Executive, February 2003, pp. 21-23.
    \154\ Ibid.
---------------------------------------------------------------------------

    For banks and thrifts, selling their CRA loans will free up 
capital to make new CRA loans. As a result, the CRA market segment 
provides an opportunity for Fannie Mae and Freddie Mac to expand 
their affordable lending programs. Section E.3c below presents data 
showing that purchasing targeted seasoned loans has been one 
strategy that Fannie Mae has chosen to improve its goals 
performance. Fannie Mae has been offering CRA programs since mid-
1997, when it launched a pilot program, ``Community Reinvestment Act 
Portfolio Initiative,'' for purchasing seasoned CRA loans in bulk 
transactions, taking into account track record as opposed to relying 
just on underwriting guidelines. Fannie Mae also started another 
pilot program in 1998, involving purchases of CRA loans on a flow 
basis, as they are originated. As part of the American Dream 
Commitment, Fannie Mae has committed to investing $20 billion in 
CRA-targeted business, and funding $530 billion in CRA-eligible 
investments. One CRA-eligible product in 2003 included the 
MyCommunityMortgage TM suite, which provides flexible 
product options for low- to moderate-income families, including 
minorities, immigrants, first-time homebuyers, and underserved 
borrowers living in rural areas. MyCommunityMortgage is offered by 
over 300 lender partners nationwide, and marries targeted pricing 
with affordability features, such as 100 percent loan-to-value 
ratios with only $500 from the borrower's own funds.\155\ In 2003, 
Fannie Mae purchased or securitized more than $2.27 billion of 
MyCommunityMortgage products, which helped provide affordable 
housing solutions for 20,400 households.\156\
---------------------------------------------------------------------------

    \155\ Fannie Mae, ``Fannie Mae's Comments on HUD's Proposed 
Housing Goals for Fannie Mae and Freddie Mac for the years 2005-2008 
and Amendments to HUD's Regulation of Fannie Mae and Freddie Mac,'' 
July 16, 2004, p. I-59.
    \156\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
pp. 8-9.
---------------------------------------------------------------------------

    In addition, Freddie Mac is also purchasing seasoned affordable 
mortgage portfolios originated by depositories to help meet their 
CRA objectives. In 2003, Freddie Mac developed credit enhancements 
that enable depositories to profitably sell their loans to Freddie 
Mac--these transactions facilitate targeted affordable lending 
activity by providing immediate liquidity. Freddie Mac also 
increased its ability to purchase smaller portfolios opening this 
option to many community banks that otherwise would not have an 
outlet for their portfolios.\157\ The billions of dollars worth of 
CRA loans that will be originated, as well as the CRA loans being 
held in bank and thrift portfolios, offer both GSEs an opportunity 
to improve their performance in the single-family area.
---------------------------------------------------------------------------

    \157\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
64.
---------------------------------------------------------------------------

6. Potential Homebuyers

    While the growth in affordable lending and homeownership has 
been strong in recent years, attaining this Nation's homeownership 
goals will not be possible without tapping into the vast pool of 
potential homebuyers. Due to record low interest rates, expanded 
homeownership outreach, and new flexible mortgage products, the 
homeownership rate reached an annual record of 67.9 percent in 2002, 
reaching 68.6 percent in the fourth quarter of 2003.\158\ This 
section discusses the potential for further increases beyond those 
resulting from current demographic trends.
---------------------------------------------------------------------------

    \158\ U.S. Department of HUD, Office of Policy Development and 
Research, U.S. Housing Market Conditions, May 2004, p. 81.
---------------------------------------------------------------------------

    The potential homeowner population over the next decade will be 
highly diverse, as growing housing demand from immigrants (both 
those who are already here and those projected to come) and non-
traditional homebuyers will help to offset declines in the demand 
for housing caused by the aging of the population. As noted in the 
above discussion of CRA, many of these potential homeowners will be 
located in urban areas. As noted in the above discussion of 
underlying demographic conditions (section C.2.), immigrants and 
other minorities--who accounted for nearly 40 percent of the growth 
in the nation's homeownership rate over the past five years--will be 
responsible for almost two-thirds of the growth in the number of new 
households over the next ten years. This trend does not depend on 
the future inflow of new immigrants, as immigrants don't enter the 
housing market until they have been in this country for eleven 
years. As noted by Fannie Mae staff, ``there are enough immigrants 
already in this country to keep housing strong for at least six and 
perhaps even 10 more years''.\159\ As these demographic factors play 
out, the overall effect on housing demand will likely be sustained 
growth and an increasingly diverse household population from which 
to draw new homeowners.
---------------------------------------------------------------------------

    \159\ Ibid.
---------------------------------------------------------------------------

    Surveys indicate that these demographic trends will be 
reinforced by the fact that most Americans desire, and plan, to 
become homeowners. According to the 2002 Fannie Mae Foundation 
annual National Housing Survey, Americans rate homeownership as the 
best investment they can make, far ahead of 401Ks, retirement 
accounts, and stocks. The percentage of Americans who said it was a 
good time to buy a home was at its highest level since 1994 at 75 
percent, a jump of 21 percentage points since May 2001.\160\ In 
addition, the survey found that 27 percent of Americans report they 
are likely to buy in the next three years, and 23 percent of those 
have started to save or have saved enough money for a down 
payment.\161\
---------------------------------------------------------------------------

    \160\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 
6.
    \161\ Ibid. p. 8.
---------------------------------------------------------------------------

    Further increases in the homeownership rate depend on whether or 
not recent gains in the home owning share(s) of specific groups are 
maintained. Minorities accounted for 17 percent of owner households 
in 2001, but the Joint Center for Housing Studies reports that 
minorities were responsible for more than 40 percent (a total of 5.2 
million) of the net growth in homeowners between 1993 and 2002.\162\ 
As reported by the Fannie Mae survey, 42 percent of African-American 
families reported that they were ``very or fairly likely'' to buy a 
home in the next three years, up from 38 percent in 1998 and 25 
percent in 1997. Among Hispanics and Hispanic immigrants, the 
numbers reached 37 percent and 34 percent respectively. The 2002 
survey also reports that more than half of Hispanic renters cite 
homeownership as being ``one of their top priorities''. In addition, 
nearly a third (31 percent) of baby boomers said they are ``very or 
fairly likely'' to buy a home in the next three years.
---------------------------------------------------------------------------

    \162\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2003, p. 15.
---------------------------------------------------------------------------

    In spite of these trends, potential minority and immigrant 
homebuyers see more obstacles to buying a home, compared with the 
general public. These barriers to homeownership are discussed in 
detail in section B.1.b above and include: lack of capital for down 
payment and closing costs; poor credit history; lack of access to 
mainstream lenders; complexity and fear of the homebuying process; 
and, continued discrimination in housing markets and mortgage 
lending. To address the needs of the new group of potential 
homeowners, the mortgage industry will have to address these needs 
on several fronts, such as expanding education and outreach efforts, 
introducing new products, and adjusting current underwriting 
standards to better reflect the

[[Page 63666]]

special circumstances of these new households.
    Thus, the new group of potential homeowners will have unique 
needs. To tap this potential homeowner population, the mortgage 
industry will have to address these needs on several fronts, such as 
expanding education and outreach efforts, introducing new products, 
and adjusting current underwriting standards to better reflect the 
special circumstances of these new households.
    The Bush administration has outlined a plan to expand minority 
homeownership by 5.5 million families by the end of the decade. The 
Joint Center for Housing Studies has stated that if favorable 
economic and housing market trends continue, and if additional 
efforts to target mortgage lending to low-income and minority 
households are made, the overall homeownership rate could reach 70 
percent by 2010.\163\
---------------------------------------------------------------------------

    \163\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 1998, p. 20.
---------------------------------------------------------------------------

7. Automated Underwriting Systems and Mortgage Scorecards

    This, and the following two sections, discuss special topics 
that have impacted the primary and secondary mortgage markets in 
recent years. They are automated mortgage scoring, subprime loans, 
and risk-based pricing. The GSEs' use of automated underwriting and 
mortgage scoring systems was briefly discussed in the earlier 
section on underwriting standards. This section expands on issues 
related to automated underwriting, a process that has spread 
throughout the mortgage landscape over the past five years, due 
mainly to the efforts of Fannie Mae and Freddie Mac.
    Automated mortgage scoring was developed as a high-tech tool 
with the purpose of identifying credit risks in a more efficient 
manner. Automated mortgage scoring has grown as competition and 
decreased profit margins have created demands to reduce loan 
origination costs. As a result, automated mortgage scoring has 
become the predominant (around 60 to 70 percent) mortgage 
underwriting method. \164\
---------------------------------------------------------------------------

    \164\ John W. Straka, ``A Shift in the Mortgage Landscape: The 
1990s Move to Automated Credit Evaluations,'' Journal of Housing 
Research, 2000, (11)2: p. 207.
---------------------------------------------------------------------------

    According to Freddie Mac economists, automated mortgage scoring 
has enabled lenders to expand homeownership opportunities, 
particularly for underserved populations.\165\ There is growing 
evidence that automated mortgage scoring is more accurate than 
manual underwriting in predicting borrower risks. Mortgage 
scorecards express the probability that an applicant will default as 
a function of several underwriting variables such as the level of 
down payment, monthly-payment-to-income ratios, cash reserves, and 
various indicators of an applicant's creditworthiness or credit 
history. Mortgage scorecards are statistically estimated regression-
type equations, based on historical relationships between mortgage 
foreclosures (or defaults) and the underwriting variables. The level 
of down payment and credit history indicators, such as a FICO score, 
are typically the most important predictors of default in mortgage 
scoring systems.
---------------------------------------------------------------------------

    \165\ Peter M. Zorn, Susan Gates, and Vanessa Perry, ``Automated 
Underwriting and Lending Outcomes: The Effect of Improved Mortgage 
Risk Assessment on Under-Served Populations. Program on Housing and 
Urban Policy,'' Conference Paper Series, Fisher Center for Real 
Estate and Urban Economics. University of California Berkeley, 2001, 
p. 5.
---------------------------------------------------------------------------

    For example, HUD has developed FHA TOTAL Scorecard to evaluate 
the credit risk of FHA loans submitted to an automated underwriting 
system. The Scorecard works with Fannie Mae's Desktop 
Underwriter[reg] to provide a recommended level of underwriting and 
documentation for FHA loans and to determine a loan's eligibility 
for insurance with FHA. In 2003, Fannie Mae conducted a market test 
of the Scorecard with 18 FHA approved Desktop Underwriter[reg] 
lenders. Over 3,000 loans were submitted to the Total Scorecard 
through Desktop Underwriter[reg] during the market test period.\166\
---------------------------------------------------------------------------

    \166\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
p. 12.
---------------------------------------------------------------------------

    This increased accuracy in risk assessment of mortgage 
scorecards has allowed risk managers to set more lenient risk 
standards, and thus originate more loans to marginal applicants. 
Applicants who would otherwise be rejected by manual underwriting 
are being qualified for mortgages with automated mortgage scoring in 
part because the scorecard allows an applicant's weaker areas to be 
offset by stronger characteristics. Typically, applicants whose 
projected monthly debt payment (mortgage payment plus credit card 
payment plus automobile loan payment and so on) comprise a high 
percentage of their monthly income would be turned down by a 
traditional underwriting system that relied on fixed debt-to-income 
ratios (such as 36 percent). In a mortgage scoring system, these 
same applicants might be automatically accepted for a loan due to 
their stellar credit record or to their ability to raise more cash 
for a down payment. The entity funding or insuring the mortgage 
(i.e., a lender, private mortgage insurer, or a GSE) allows these 
positive characteristics to offset the negative characteristics 
because its confidence in the ability of the empirically-based 
mortgage scorecard to accurately identify those applicants who are 
more likely or less likely to eventually default on their loan. The 
mortgage score is in essence a recommendation to the lender to 
accept the application, or to refer it for further review through 
manual underwriting. Accepted loans benefit from reduced document 
requirements and expedited processing.
    In 2003, Fannie Mae conducted a study of automated underwriting 
systems and concluded that the production cost per loan decreased 
significantly as lenders moved automated underwriting closer to the 
point of sale. Specifically, retail lenders using an integrated 
automated underwriting system at the point of sale reported 
originations savings of more than $1,000 over manual 
underwriting.\167\ Freddie Mac also reported that Loan Prospector 
reduces the average time lenders spend underwriting most loans and 
reduces origination costs by about an average of $650 or more per 
loan.\168\ In addition, Freddie Mac analyzed about 1,000 loans 
originated in 1993 and 1994. Of the loans, manual underwriters rated 
52 percent accept, compared to a Loan Prospector accept rate of 87 
percent.\169\ In total, Freddie Mac reports that innovations in the 
originations process, including automated underwriting, have reduced 
mortgage transaction costs by more than 70 percent between 1990 and 
2003 from 1.87 points to 0.46 points--a decline of $1,410 per 
$100,000 borrowed.\170\
---------------------------------------------------------------------------

    \167\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
p. 36.
    \168\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
55.
    \169\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
54.
    \170\ Freddie Mac Public Comment Letter on HUD's Proposed Goals, 
July 2004, p. 5.
---------------------------------------------------------------------------

    As explained above, automated mortgage scoring allows tradeoffs 
between risk factors to be quantified more precisely, providing the 
industry more confidence in ``pushing the envelope'' of acceptable 
expected default rates. The GSEs' willingness to offer low-down-
payment programs was based on their belief that their scoring models 
could identify the more creditworthy of the cash-constrained 
applicants. The GSEs' new ``timely reward'' products for subprime 
borrowers (discussed later) are integrated with their mortgage 
scoring systems. Automated mortgage scoring presents the opportunity 
to remove discrimination from mortgage underwriting, to accept all 
applicants, and to bring fair, objective, statistically based 
competitive pricing, greatly reducing costs for all risk groups. 
Some institutions have sought to better model and automate marginal 
and higher-risk loans, which have tended to be more costly to 
underwrite and more difficult to automate.\171\
---------------------------------------------------------------------------

    \171\ Ibid. pp. 208-217.
---------------------------------------------------------------------------

    Along with the promise of benefits, however, automated mortgage 
scoring has raised concerns. These concerns are related to the 
possibility of disparate impact and the proprietary nature of the 
mortgage score inputs. The first concern is that low-income and 
minority homebuyers will not score well enough to be accepted by the 
automated underwriting system, resulting in their getting fewer 
loans. African-American and Hispanic borrowers, for example, tend to 
have a poorer credit history record than other borrowers, which 
means they are more likely to be referred (rather than automatically 
accepted) by automated mortgage scoring systems that rely heavily on 
credit history measures such as a FICO score. There is also a 
significant statistical relationship between credit history scores 
and the minority composition of an area, after controlling for other 
locational characteristics.\172\
---------------------------------------------------------------------------

    \172\ Robert B. Avery, Raphael W. Bostic, Paul S. Calem, and 
Glenn B. Canner, Credit Scoring: Issues and Evidence from Credit 
Bureau Files, mimeo, 1998, p. 24.
---------------------------------------------------------------------------

    The second concern relates to the ``black box'' nature of the 
scoring algorithm. The scoring algorithm is proprietary and 
therefore

[[Page 63667]]

it is difficult for applicants to know the reasons for their scores. 
However, it should be noted that the GSEs have taken steps to make 
their automated underwriting systems more transparent. Both Fannie 
Mae and Freddie Mac have published the factors used to make loan 
purchase decisions in Desktop Underwriter and Loan Prospector, 
respectively. In response to criticisms aimed at using FICO scores 
in mortgage underwriting, Fannie Mae's new versions of Desktop 
Underwriter (DU) 5.3 and 5.3.1 [the newest versions are 5.3 and 
5.3.1--they probably keep the following practices, but add no 
substantive underwriting practices, but rather lower downpayment 
options] replaces credit scores with specific credit characteristics 
and provides expanded approval product offerings for borrowers who 
have blemished credit. The specific credit characteristics include 
variables such as past delinquencies; credit records, foreclosures, 
and accounts in collection; credit card line and use; age of 
accounts; and number of credit inquiries.\173\
---------------------------------------------------------------------------

    \173\ Fannie Mae, September 4, 2002, p. 33.
---------------------------------------------------------------------------

    With automated mortgage scoring replacing traditional manual 
underwriting comes the fear that the loss of individual attention 
poses a problem for people who have inaccuracies on their credit 
report or for members of cultural groups or recent immigrants who do 
not use traditional credit and do not have a credit score. Some 
subprime lenders and underwriters have claimed that their manual 
underwriting of high-risk borrowers cannot be automated with 
mortgage scoring. Although automated mortgage scoring has greatly 
reduced the cost of many lower-risk loans that are easier to rate, 
the cost of manually underwriting gray-area and higher-risk 
applicants still remains high.\174\ There is also the fear that 
applicants who are referred by the automated system will not be 
given the full manual underwriting for the product that they 
initially applied for--rather they might be pushed off to higher 
priced products such as a subprime or FHA loan. In this case, the 
applicant may have had special circumstances that would have been 
clarified by the traditional manual underwriting, thus enabling the 
applicant to receive a prime loan consistent with his or her 
creditworthiness.
---------------------------------------------------------------------------

    \174\ Kenneth Temkin, Jennifer E.H. Johnson, and Diane Levy, 
Subprime Markets, The Role of GSEs, and Risk-Based Pricing, 
Washington: The Urban Institute. Report Prepared for the U.S. 
Department of Housing and Urban Development, 2002.
---------------------------------------------------------------------------

    Banking regulators and legal analysts acknowledge the value of 
automated mortgage scoring, although some skeptics have noted 
concerns regarding fair lending, potential fraud, privacy issues, 
and the ability of models to withstand changing economic 
conditions.\175\ With the rise of automated mortgage scoring, the 
great difference in Internet usage known as the ``digital divide'' 
could result in informational disadvantages for less educated and 
lower-income consumers. In addition to the digital divide, the lack 
of financial literacy in the United States may also result in a 
disparate impact on low-income and minority borrowers.\176\
---------------------------------------------------------------------------

    \175\ Allen J. Fishbein, ``Is Credit Scoring a Winner for 
Everyone?'' Stone Soup, 2000, 14(3): pp. 14-15. See also Fitch IBCA, 
Inc., Residential Mortgage Credit Scoring, New York, 1995 and Jim 
Kunkel, ``The Risk of Mortgage Automation,'' in Mortgage Banking, 
1995, 57(8): pp. 69-76.
    \176\ Zorn et al., 2001, pp. 19-20.
---------------------------------------------------------------------------

    2002 Urban Institute Study. The Urban Institute submitted a 
report to HUD in 2002 on subprime markets, the role of GSEs, and 
risk-based pricing.\177\ The study took a preliminary look at the 
use of automated underwriting systems for a small sample of lenders. 
After conducting interviews with both subprime and prime lenders, 
the report noted that all of the lenders in the study had 
implemented some type of automated underwriting system. These 
lenders stated that automated underwriting raised their business 
volume and streamlined their approval process. In addition, the 
lenders reported they were able to direct more underwriting 
resources to borderline applications despite an increase in business 
volume.
---------------------------------------------------------------------------

    \177\ Kenneth Temkin, Jennifer E.H. Johnson, and Diane Levy, 
Subprime Markets, The Role of GSEs, and Risk-Based Pricing, 
Washington: The Urban Institute. Report Prepared for the U.S. 
Department of Housing and Urban Development, 2002.
---------------------------------------------------------------------------

    Even with the use of automated mortgage scoring, the lenders in 
the study continued to conduct at least a cursory review to validate 
the application material. The majority of the lenders still used 
manual underwriting to originate loans not recommended for approval 
with automated mortgage scoring. The lenders reported they 
formulated their policies and procedures to make certain that 
borrowers receive the best mortgage, according to product 
eligibility. This study will be further referenced in a following 
section regarding subprime markets.
    2001 Freddie Mac Study. According to a Freddie Mac study 
published by the Fisher Center for Real Estate and Urban Economics 
at University of California at Berkeley, underserved populations 
have benefited from automated mortgage scoring because of the 
increased ability to distinguish between a range of credit risks. In 
this paper, Freddie Mac economists compared the manual and automated 
mortgage scoring approval rates of a sample of minority loans 
originated in 1993-94 and purchased by Freddie Mac. While manual 
underwriters rated 51 percent of the minority loans in the sample as 
accept, automated mortgage scoring would have rated 79 percent of 
the loans as accept. \178\
---------------------------------------------------------------------------

    \178\ Zorn, et al., 2001, pp. 14-15.
---------------------------------------------------------------------------

    In comparison to manual underwriting, this study found automated 
mortgage scoring not only less discriminatory but also more accurate 
in predicting risk. Two versions of Freddie Mac's automated 
underwriting system, Loan Prospector (LP), were used to review three 
groups of mortgage loans purchased by Freddie Mac.\179\ The study 
found that LP was a highly accurate predictor of mortgage default. 
The resulting improved accuracy translates into benefits for 
borrowers, who would otherwise be rejected by manual underwriting to 
qualify for mortgages.
---------------------------------------------------------------------------

    \179\ Ibid. p. 5.
---------------------------------------------------------------------------

    Analysis of the first group of loans showed that loans rated as 
``caution'' were four times more likely to default than the average 
for all loans. Minority borrowers whose loans were rated as 
``caution'' were five times more likely to default, and low-income 
borrowers whose loans were rated as ``caution'' were four times more 
likely to default than the average for all loans. The 2000 version 
of LP approved 87.1 percent of loans generated through affordable 
housing programs, compared to a 51.6 percent approval rate when the 
same loans were assessed using manual underwriting procedures. 
Further, the study found LP more accurate than manual underwriting 
at predicting default risk even with a higher approval rate. The 
study also demonstrated that Freddie Mac's year 2000 version of LP 
was more accurate in predicting risk than its 1995 version.
    Concluding Observations. Automated underwriting has enabled 
lenders to reach new markets and expand homeownership opportunities, 
as illustrated by the 2001 Freddie Mac study. Increased accuracy 
with automated mortgage scoring has led to the development of new 
mortgage products that would have been previously considered too 
risky. For example, Freddie Mac uses Loan Prospector to approve Alt 
A loans, which tend to have nontraditional documentation; A-minus 
loans, which pose a higher risk of default; and other higher-risk 
mortgages, like 100 percent LTV loans. Both GSEs have and continue 
to add new products to develop their automated underwriting systems 
to reach more marginal borrowers.
    Despite the gains in automated mortgage scoring and other 
innovations, minorities are still less likely to be approved for a 
loan. The difference in minority and non-minority accept rates may 
reflect greater social inequities in financial capacity and credit, 
which are integral variables in both manual and automated 
underwriting. In the future, the accuracy of automated mortgage 
scoring will hinge on updating the models and making them more 
predictive while reducing the disparate impact on low-income and 
minority borrowers.\180\ The fairness of automated scoring systems 
will also depend importantly on whether referred applicants receive 
a traditional manual underwriting for the loan that they initially 
applied for, rather than being immediately offered a higher priced 
loan that does not recognize their true creditworthiness.
---------------------------------------------------------------------------

    \180\ Ibid. pp. 18-19.
---------------------------------------------------------------------------

    In addition to using automated underwriting systems as a tool to 
help determine whether a mortgage application should be approved, 
the GSEs' automated underwriting systems are being further adapted 
to facilitate risk-based pricing. With risk-based pricing, mortgage 
lenders can offer each borrower an individual rate based on his or 
her risk. The division between the subprime and the prime mortgage 
market will begin to fade with the rise of risk-based pricing, which 
is discussed in the next section on the subprime market.

[[Page 63668]]

8. Subprime Lending

    The subprime mortgage market provides mortgage financing to 
credit-impaired borrowers--those who may have blemishes in their 
credit record, insufficient credit history, or non-traditional 
credit sources. This section examines several topics related to 
subprime lending including (a) the growth and characteristics of 
subprime loans, (b) the neighborhood concentration of subprime 
lending, (c) predatory lending, and (d) purchases of subprime 
mortgages by the GSEs. Section C.9 follows with a discussion of 
risk-based pricing.

a. The Growth and Characteristics of Subprime Loans

    The subprime market has grown rapidly over the past several 
years, increasing from an estimated $35 billion in 1994 to $160 
billion in 1999 and $173.3 billion in 2001, before rising to $213 
billion in 2002. The subprime share of total market originations 
rose from 4.6 percent in 1994 to a high of 15 percent in 1999, and 
then fell to 8.5 percent in both 2001 and 2002.\181\ Various factors 
have led to the rapid growth in the subprime market: Federal 
legislation preempting state restrictions on allowable rates and 
loan features, the tax reform act of 1986 which encouraged tax-
exempt home equity financing of consumer debt, increased demand for 
and availability of consumer debt, a substantial increase in 
homeowner equity due to house price appreciation, and a ready supply 
of available funds through Wall Street securitization.\182\ It is 
important to note that subprime lending grew in the 1990s mostly 
without the assistance of Fannie Mae and Freddie Mac.
---------------------------------------------------------------------------

    \181\ Subprime origination data are from Inside Mortgage 
Finance. For the 2002 estimates, see ``Subprime Origination Market 
Shows Strong Growth in 2002,'' Inside B&C Lending, published by 
Inside Mortgage Finance, February 3, 2003, page 1.
    \182\ Temkin et. al., 2002, p. 1.
---------------------------------------------------------------------------

    Generally, there are three different types of products available 
for subprime borrowers. These include: Home purchase and refinance 
mortgages designed for borrowers with poor credit histories; ``Alt 
A'' mortgages that are usually originated for borrowers who are 
unable to document all of the underwriting information but who may 
have solid credit records; and high loan-to-value mortgages 
originated to borrowers with fairly good credit. Fannie Mae and 
Freddie Mac are more likely to serve the first two types of subprime 
borrowers.\183\
---------------------------------------------------------------------------

    \183\ Kenneth Temkin, Jennifer E.H. Johnson, Diane Levy, 
Subprime Markets, The Role of GSEs, and Risk Based Pricing, 
Washington: The Urban Institute. Report Prepared for the Department 
of Housing and Urban Development, 2002, p. 4.
---------------------------------------------------------------------------

    Borrowers use subprime loans for various purposes, which include 
debt consolidation, home improvements, and an alternative source of 
consumer credit. Between 1999 and 2001, about two-thirds of subprime 
loans were refinance loans. It has been estimated that 59 percent of 
refinance loans were ``cash out'' loans.\184\ According to a joint 
HUD-Treasury report, first liens accounted for more than three out 
of four loans in the subprime market.
---------------------------------------------------------------------------

    \184\ U.S. Department of Housing and Urban Development/U.S. 
Department of the Treasury, Curbing Predatory Lending Report, 2000, 
p.31.
---------------------------------------------------------------------------

    The subprime market is divided into different risk categories, 
ranging from least risky to most risky: A-minus, B, C, and D. While 
there are no clear industry standards for defining the subprime risk 
categories, Inside Mortgage Finance defines them in terms of FICO 
scores--580-620 for A-minus, 560-580 for B, 540-560 for C, and less 
than 540 for D. The A-minus share of the subprime market rose from 
61.6 percent in 2000 to 70.7 percent in 2001.\185\ For the first 
nine months of 2002, the A-minus share accounted for 74 percent of 
the market, while the B share accounted for 11 percent, the C share 
accounted for 7.2 percent, and the D share accounted for 7.9 percent 
of the market.\186\
---------------------------------------------------------------------------

    \185\ ``Wholesale Dominates Subprime Market Through 3rd Quarter 
'02,'' Inside B&C Lending, published by Inside Mortgage Finance, 
December 16, 2002, pp. 1-2.
    \186\ Inside B&C Lending, November 16, 2002, p.2.
---------------------------------------------------------------------------

    Delinquency rates by type of subprime loan are as follows: 3.36 
percent for A-minus loans, 6.67 percent for B, 9.22 percent for C, 
and 21.03 percent for D, according to the Mortgage Information 
Corporation.\187\ Because of their higher risk of default, subprime 
loans typically carry much higher mortgage rates than prime 
mortgages. Recent quotes for a 30-year Fixed Rate Mortgage were 8.85 
percent for A-minus (with an 85 percent LTV), 9.10 percent for B 
credit (with an 80 percent LTV), and 10.35 percent for C credit 
(with a 75 percent LTV).\188\ As the low loan-to-value (LTV) ratios 
indicate, one loss mitigation technique used by subprime lenders is 
a high down payment requirement. Some housing advocates have 
expressed concern that the perceptions about the risk of subprime 
loans may not always be accurate, for example, creditworthy 
borrowers in inner city neighborhoods may be forced to use subprime 
lenders because mainstream lenders are not doing business in their 
neighborhoods (see below).
---------------------------------------------------------------------------

    \187\ Mortgage Information Corporation, The Market Pulse, Winter 
2001, pp. 4-6.
    \188\ Inside B&C Lending, published by Inside Mortgage Finance, 
February 17, 2003, page 13.
---------------------------------------------------------------------------

    Subprime borrowers are much more likely to be low income and be 
a minority than other borrowers. Between 1999 and 2001, 43.1 percent 
of subprime loans in the conventional conforming market went to low-
income borrowers, compared with 29.5 percent of conventional 
conforming loans. During that same period, 19.9 percent of subprime 
loans were for African-American borrowers, compared with 6.5 percent 
of all conventional conforming loans. However, what distinguishes 
subprime loans from other loans is their concentration in African-
American neighborhoods.

b. The Neighborhood Concentration of Subprime Lending

    The growth in subprime lending over the last several years has 
benefited credit-impaired borrowers as well as those borrowers who 
choose to provide little documentation for underwriting. However, 
studies showing that subprime lending is disproportionately 
concentrated in low-income and minority neighborhoods have raised 
concerns about whether mainstream lenders are adequately serving 
these neighborhoods. A study of subprime lending in Chicago by The 
Woodstock Institute concluded that a dual, hyper-segmented mortgage 
market existed in Chicago, as mainstream lenders active in white and 
upper-income neighborhoods were much less active in low-income and 
minority neighborhoods-effectively leaving these neighborhoods to 
unregulated subprime lenders.\189\ As part of the HUD-Treasury Task 
Force on Predatory Lending, HUD's Office of Policy Development and 
Research released a national level study--titled Unequal Burden: 
Income and Racial Disparities in Subprime Lending in America--that 
showed families living in low-income and African-American 
neighborhoods in 1998 relied disproportionately on subprime 
refinance lending, even after controlling for neighborhood income. 
An update of that analysis for the year 2000 yields the following 
trends: \190\
---------------------------------------------------------------------------

    \189\ Daniel Immergluck, The Predatory Lending Crisis in 
Chicago: The Dual Mortgage Market and Local Policy, testimony before 
the Chicago City Council, April 5, 2000. Immergluck found that 
subprime lenders received 74 percent of refinance applications in 
predominantly black tracts compared to 21 percent in predominantly 
white tracts in 1998. According to Immergluck, these racial 
disparities provide evidence that the residential finance market in 
Chicago is hypersegmented, resulting in the increased likelihood 
that minorities receive mortgage credit from a subprime, rather than 
a prime, lender in Chicago. Also see Daniel Immergluck, Stark 
Differences: The Explosion of the Subprime Industry and Racial 
Hypersegmentation in Home Equity Lending, Woodstock Institute, 
October 2000
    \190\ See Randall M. Scheessele, Black and White Disparities in 
Subprime Mortgage Refinance Lending, Housing Finance Working Paper 
HF-014, Office of Policy Development and Research, U.S. Department 
of Housing and Urban Development, April 2002.
---------------------------------------------------------------------------

     In 2000, 36 percent of refinance mortgages in low-
income neighborhoods were subprime, compared with only 16 percent in 
upper-income neighborhoods.
     Subprime lending accounted for 50 percent of refinance 
loans in majority African American neighborhoods--compared with only 
21 percent in predominantly white areas (less than 30 percent of 
population is African American).
     The most dramatic view of the disparity in subprime 
lending comes from comparing homeowners in upper-income African-
American and white neighborhoods. Among homeowners living in the 
upper-income white neighborhoods, only 16 percent turned to subprime 
lenders in 2000. But 42 percent of homeowners living in upper-income 
African-American neighborhoods relied upon subprime refinancing 
which is substantially more than the rate (30 percent) for 
homeowners living in low-income white neighborhoods.
     Similar results are obtained when the analysis is 
conducted for borrowers instead of neighborhoods. Upper-income 
African-American borrowers are twice as likely as low-income white 
borrowers to have subprime loans. Over one-half (54 percent) of

[[Page 63669]]

low-income African-American borrowers turn to subprime lenders, as 
does over one-third (35 percent) of upper-income African-American 
borrowers. By comparison, only 24 percent of low-income white 
borrowers and 12 percent of upper-income white borrowers, rely upon 
subprime lenders for their refinance loans.\191\
---------------------------------------------------------------------------

    \191\ For an update to 2001, see The Association of Community 
Organizers for Reform Now (ACORN), Separate and Unequal Predatory 
Lending in America, 2002. In 2001, subprime lenders originated 27.8 
percent of all conventional refinance loans for African-Americans, 
13.6 percent for Hispanic homeowners, and just 6.3 percent for white 
homeowners. Overall, African-Americans were 4.4 times more likely to 
use a subprime lender than whites, and Hispanics were 2.2 times more 
likely to do so.
---------------------------------------------------------------------------

    It does not seem likely that these high market shares by 
subprime lenders in low-income and African-American neighborhoods 
can be justified by a heavier concentration of households with poor 
credit in these neighborhoods. Rather, it appears that subprime 
lenders may have attained such high market shares by serving areas 
where prime lenders do not have a significant presence. The above 
finding that upper-income black borrowers rely more heavily on the 
subprime market than low-income white borrowers suggests that a 
portion of subprime lending is occurring with borrowers whose credit 
would qualify them for lower cost conventional prime loans. A lack 
of competition from prime lenders in low-income and minority 
neighborhoods has increased the chances that borrowers in these 
communities are paying a high cost for credit. As explained next, 
there is also evidence that the higher interest rates charged by 
subprime lenders cannot be fully explained solely as a function of 
the additional risks they bear. Thus, a greater presence by 
mainstream lenders could possibly reduce the high up-front fees and 
interest rates being paid by residents of low-income and minority 
neighborhoods.
    The Freddie Mac study presented evidence that subprime loans 
bear interest rates that are higher than necessary to offset the 
higher credit risks of these loans.\192\ The study compared (a) the 
interest rate on subprime loans rated A-minus by the lenders 
originating these loans with (b) the interest rates on prime loans 
purchased by Freddie Mac and rated A-minus by a Freddie Mac 
underwriting model. Despite the fact that both loan groups were 
rated A-minus, on average the subprime loans bore interest rates 
that were 215 basis points higher. Even assuming that the credit 
risk of the subprime loans was in fact higher than the prime loans, 
the study could not account for such a large discrepancy in interest 
rates. Assuming that default rates might be three to four times 
higher for the subprime loans would account for a 90 basis point 
interest rate differential. Assuming that servicing the subprime 
loans would be more costly would justify an additional 25 basis 
point differential. But even after allowing for these possible 
differences, the Freddie Mac researchers concluded that the subprime 
loans had an unexplained interest rate premium of 100 basis points 
on average.\193\
---------------------------------------------------------------------------

    \192\ Howard Lax, Michael Manti, Paul Raca, and Peter Zorn, 
``Subprime Lending: An Investigation of Economic Efficiency,'' 
February 25, 2000.
    \193\ It should also be noted that higher interest rates are 
only one component of the higher cost of subprime loans since 
borrowers also often face higher origination points. The Freddie Mac 
study did not find a large differential between prime and subprime 
loans in points paid, but the study notes that subprime loans often 
have points rolled into the loan principal, which cannot be 
identified with their data.
---------------------------------------------------------------------------

    Banking regulators have recognized the link between the growth 
in subprime lending and the absence of mainstream lenders and have 
urged banks and thrifts that lending in these neighborhoods not only 
demonstrates responsible corporate citizenship but also profitable 
lending. Ellen Seidman, former Director of the Office of Thrift 
Supervision, stated that, ``Many of those served by the subprime 
market are creditworthy borrowers who are simply stuck with subprime 
loans or subprime lenders because they live in neighborhoods that 
have too few credit or banking opportunities.''
    With respect to the question of whether borrowers in the 
subprime market are sufficiently creditworthy to qualify for more 
traditional loans, Freddie Mac has said that one of the promises of 
automated underwriting is that it might be better able to identify 
borrowers who are unnecessarily assigned to the high-cost subprime 
market. Freddie Mac has estimated that 10-30 percent of borrowers 
who obtain mortgages in the subprime market could qualify for a 
conventional prime loan through Loan Prospector, Freddie Mac's 
automated underwriting system.\194\ Fannie Mae has stated that half 
of all mortgage borrowers steered to the high-cost subprime market 
are in the A-minus category, and therefore are prime candidates for 
Fannie Mae.\195\
---------------------------------------------------------------------------

    \194\ Freddie Mac, We Open Doors for America's Families, Freddie 
Mac's Annual Housing Activities Report for 1997, March 16, 1998, p. 
23.
    \195\ Rommy Fernandez, ``Fannie Mae Eyes Half of the Subprime 
Market,'' in The American Banker, March 1, 2002. Also see ``Fannie 
Mae Vows More Minority Lending,'' Washington Post, March 16, 2000, 
p. EO1.
---------------------------------------------------------------------------

c. Predatory Lending

    Predatory lending has been a disturbing part of the growth in 
the subprime market. Although questions remain about its magnitude, 
predatory lending has turned homeownership into a nightmare for far 
too many households. The growing incidence of abusive practices has 
been stripping borrowers of their home equity, threatening families 
with foreclosure, and destabilizing neighborhoods. Also, in some 
cities, there are indications that unscrupulous realtors, mortgage 
brokers, appraisers, and lenders are duping some FHA borrowers into 
purchasing homes at an inflated price or with significant 
undisclosed repairs. The problems associated with home equity fraud 
and other mortgage abuses are not new ones, but the extent of this 
activity seems to be increasing. The expansion of predatory lending 
practices along with subprime lending is especially troubling since 
subprime lending is disproportionately concentrated in low- and 
very-low income neighborhoods, and in African-American 
neighborhoods.
    The term ``predatory lending'' is a short hand term that is used 
to encompass a wide range of abuses. While there is broad public 
agreement that predatory lending should have no place in the 
mortgage market, there are differing views about the magnitude of 
the problem, or even how to define practices that make a loan 
predatory. The joint HUD-Treasury report, Curbing Predatory Home 
Mortgage Lending, concluded that a loan can be predatory when 
lenders or brokers: charge borrowers excessive, often hidden fees 
(called ``packing fees''); successively refinance loans at no 
benefit to the borrower (called ``loan flipping''); make loans 
without regard to a borrower's ability to repay; and, engage in 
high-pressure sales tactics or outright fraud and deception. These 
practices are often combined with loan terms that, alone or in 
combination, are abusive or make the borrower more vulnerable to 
abusive practices. Vulnerable populations, including the elderly and 
low-income individuals, and low-income or minority neighborhoods, 
appeared to be especially targeted by unscrupulous lenders.
    One consequence of predatory lending is that borrowers are 
stripped of the equity in their homes, which places them at an 
increased risk of foreclosure. In fact, high foreclosure rates for 
subprime loans provide the most concrete evidence that many subprime 
borrowers are entering into mortgage loans that they simply cannot 
afford. The high rate of foreclosures in the subprime market has 
been documented by HUD and others in recent research studies.\196\ 
These studies have found that foreclosures by subprime lenders grew 
rapidly during the 1990s and now exceed the subprime lenders' share 
of originations. In addition, the studies indicate that foreclosures 
of subprime loans occur much more quickly than foreclosures on prime 
loans, and that they are concentrated in low-income and African-
American neighborhoods. Of course, given the riskier nature of these 
loans, a higher foreclosure rate would be expected. With the 
information available it is not possible to evaluate whether the 
disparities in foreclosure rates are within the range of what would 
be expected for loans prudently originated within this risk class. 
But findings from these studies about the high rate of mortgage 
foreclosure associated with subprime lending reinforce the concern 
that predatory lending can potentially have devastating effects for 
individual families and their neighborhoods.
---------------------------------------------------------------------------

    \196\ For an overview of these studies, see Harold L. Bunce, 
Debbie Gruenstein, Christopher E. Herbert, Randall M. Scheessele, 
Subprime Foreclosures: The Smoking Gun of Predatory Lending, 2000. 
Also see Abt Associates Inc., Analyzing Trends in Subprime 
Originations and Foreclosures: A Case Study of the Atlanta Metro 
Area, February 2000 and Analyzing Trends in Subprime Originations 
and Foreclosures: A Case Study of the Boston Metro Area, September 
2000; National Training and Information Center, Preying on 
Neighborhoods: Subprime Mortgage Lenders and Chicagoland 
Foreclosures, 2000; and the HUD study, Unequal Burden in Baltimore: 
Income and Racial Disparities in Subprime Lending, May 2000.
---------------------------------------------------------------------------

    At this time, there are open questions about the effectiveness 
of the different approaches being proposed for eradicating

[[Page 63670]]

predatory lending and the appropriate roles of different 
governmental agencies--more legislation versus increased enforcement 
of existing laws, long-run financial education versus mortgage 
counseling, Federal versus state and local actions. In its recent 
issuance of predatory lending standards for national banks, the 
Office of the Comptroller of the Currency (OCC) cited the efforts of 
Fannie Mae and Freddie Mac in reducing predatory lending.\197\ The 
OCC advised banks against abusive practices, such as rolling single-
premium life insurance into a loan. The agency cited guidelines 
developed by Fannie Mae and Freddie Mac as a ``useful reference'' or 
starting point for national banks. Following publication of HUD's 
proposed 2000 Rule inviting comments on disallowing goals credit for 
high cost mortgage loans, Fannie Mae and Freddie Mac told lenders 
they would no longer purchase loans with certain abusive practices, 
such as excessive fees and failing to consider a borrower's ability 
to repay the debt.
---------------------------------------------------------------------------

    \197\ ``OCC Cites Fannie, Freddie Predatory Lending Rules As 
Model,'' Dow Jones Business News, February 25, 2003.
---------------------------------------------------------------------------

    It is important to re-emphasize that predatory lending generally 
occurs in neighborhoods where borrowers have limited access to 
mainstream lenders. While predatory lending can occur in the prime 
market, it is ordinarily deterred in that market by competition 
among lenders, greater homogeneity in loan terms and greater 
financial information among borrowers. Thus, one solution to address 
this problem would be to encourage more mainstream lenders to do 
business in our inner city neighborhoods.
    Certain commenters urged the Department to adopt predatory 
lending safeguards in the final rule that would prohibit the GSEs 
from counting loans that included mandatory arbitration clauses or 
loans with prepayment penalties beyond three years towards the 
goals. In the 2000 rulemaking, the Department determined that the 
GSEs should not receive goals credit for purchasing high cost 
mortgages including mortgages with unacceptable features as 
explained in the preamble. The Department is aware that certain 
practices that were not enumerated in the regulations adopted in 
2000, such as loans with prepayment penalties after three years and 
loans with mandatory arbitration clauses, often lock borrowers into 
disadvantageous loan products. The Department will rely on existing 
regulatory authorities to monitor the GSEs' performance in this 
area. Should the Department later determine that there is a need to 
specifically enumerate additional prohibited predatory practices, it 
will address such practices in a future rulemaking.

d. Purchases of Subprime Mortgages by the GSEs

    Fannie Mae and Freddie Mac have shown increasing interest in the 
subprime market since the latter half of the 1990s. The GSEs entered 
this market by purchasing securities backed by non-conforming loans. 
Freddie Mac, in particular, increased its subprime business through 
structured transactions, with Freddie Mac guaranteeing the senior 
classes of senior/subordinated securities. The two GSEs also 
purchase subprime loans on a flow basis. Fannie Mae began purchasing 
subprime loans through its Timely Payment Reward Mortgage program in 
June 1999, and Freddie Mac rolled out a similar product, Affordable 
Merit Rate, in May 2000 (described below). In addition to purchasing 
subprime loans for borrowers with blemished credit, the GSEs also 
purchase another non-conforming loan called an Alternative-A or 
``Alt-A'' mortgage. These mortgages are made to prime borrowers who 
do not want to provide full documentation for loans. The GSEs' 
interest in the subprime market has coincided with a maturation of 
their traditional market (the conforming conventional mortgage 
market), and their development of mortgage scoring systems, which 
they believe allows them to accurately model credit risk. Although 
the GSEs account for only a modest share of the subprime market 
today, some market analysts estimate that they could purchase as 
much as half of the overall subprime market in the next few 
years.\198\
---------------------------------------------------------------------------

    \198\ Temkin et al., 2002, p. 1.
---------------------------------------------------------------------------

    Precise information on the GSEs' purchases of subprime loans is 
not readily available. Data can be pieced together from various 
sources, but this can be a confusing exercise because of the 
different types of non-conforming loans (Alt-A and subprime) and the 
different channels through which the GSEs purchase these loans 
(through securitizations and through their ``flow-based'' product 
offerings). Freddie Mac, which has been the more aggressive GSE in 
the subprime market, purchased approximately $12 billion in subprime 
loans during 1999--$7 billion of A-minus and alternative-A loans 
through its standard flow programs and $5 billion through structured 
transactions.\199\ In 2000, Freddie Mac purchased $18.6 billion of 
subprime loans on a flow basis in addition to another $7.7 billion 
of subprime loans through structured transactions.\200\ Freddie Mac 
securitized $9 billion in subprime and Alt-A product in 2001 and 
$11.1 billion in 2002.
---------------------------------------------------------------------------

    \199\ David A. Andrukonis, ``Entering the Subprime Arena,'' 
Mortgage Banking, May 2000, pp. 57-60.
    \200\ Subprime Lenders Mixed on Issue of GSE Mission Creep,'' 
Inside B and C Lending, March 19, 2001.
---------------------------------------------------------------------------

    Fannie Mae's anti-predatory lending strategy includes eight 
major components. These components include: establishing business 
guidelines that ensure that liquidity is provided for only 
responsible lenders; expanding the application of conventional 
conforming mortgage practices to more borrowers; advancing the 
Mortgage Consumer Bill of Rights Agenda; offering a broad range of 
alternative responsible products; leveraging technology and the 
Internet to expand markets and reduce costs for consumers; working 
with partners to keep borrowers in their homes; supporting the home-
buyer education industry to empower educators to reach more 
consumers; and supporting the Fannie Mae Foundation in consumer 
education and outreach.\201\
---------------------------------------------------------------------------

    \201\ Fannie Mae, ``Fannie Mae's Comments on HUD's Proposed 
Housing Goals for Fannie Mae and Freddie Mac for the years 2005-2008 
and Amendments to HUD's Regulation of Fannie Mae and Freddie Mac,'' 
July 16, 2004, p. I-59.
---------------------------------------------------------------------------

    In recent years, Freddie Mac has instituted measures designed to 
protect consumers from predatory lending. For example, Freddie Mac 
has announced that, effective August 1, 2004, they will no longer 
invest in subprime mortgages originated after that date that contain 
mandatory arbitration clauses. Since 2000, Freddie Mac has 
prohibited purchases of mortgages that impose a prepayment premium 
for a term of more than five years, and in March 2002, this 
prohibition was reduced to no more than three years. Freddie Mac 
does not purchase high-rate or high-fee loans that are covered by 
the Home Ownership and Equity Protection Act of 1994 (HOEPA); and 
they do not purchase mortgages containing a prepaid single-premium 
credit life, credit disability, credit unemployment or credit 
property insurance policy. Freddie Mac also requires all lenders 
servicing their loans to report monthly borrower mortgage payments 
to all four major credit repositories, and conducts onsite reviews 
of their customers and holds them accountable if their business 
practices do not meet Freddie Mac standards.\202\
---------------------------------------------------------------------------

    \202\ Freddie Mac Public Comment Letter on HUD's Proposed Goals, 
July 2004, p. 6.
---------------------------------------------------------------------------

    Fannie Mae initiated its Timely Payments product in September 
1999, under which borrowers with slightly damaged credit can qualify 
for a mortgage with a higher interest rate than prime borrowers. 
Under this product, a borrower's interest rate will be reduced by 
100 basis points if the borrower makes 24 consecutive monthly 
payments without a delinquency. Fannie Mae has revamped its 
automated underwriting system (Desktop Underwriter) so loans that 
were traditionally referred for manual underwriting are now given 
four risk classifications, three of which identify potential 
subprime (A-minus) loans.\203\ Fannie purchased about $600 million 
of subprime loans on a flow basis in 2000.\204\ Fannie Mae 
securitized around $0.6 billion in subprime mortgages in 2000, 
before increasing to $5.0 billion in 2001 and 7.3 billion in 
2002.\205\ In terms of total subprime activity (both flow and 
securitization activities), Fannie Mae purchased $9.2 billion in 
2001 and over $15 billion in 2002, the latter figure representing 
about 10 percent of the market, according to Fannie Mae staff.\206\
---------------------------------------------------------------------------

    \203\ See Lederman, et al., Op cit.
    \204\ Kenneth Temkin, Jennifer E. H. Johnson, and Diane K. Levy, 
``Subprime Markets, the Role of GSEs, and Risk-Based Pricing,'' 
Urban Institute, August 2001, p. 1.
    \205\ Inside Mortgage Finance's, ``Inside MBS & ABS,'' December 
15, 2000 and March 8, 2002.
    \206\ Statement by Mercy Jimenez of Fannie Mae in ``Fannie Mae: 
Forges Ahead in Subprime,'' Secondary Marketing Executive, February 
2003, p.15.
---------------------------------------------------------------------------

    A greater GSE role in the subprime lending market will most 
likely have a significant impact on the subprime market. Currently, 
the majority of subprime loans are not purchased by GSEs, and the 
numbers of lenders originating subprime loans typically do not issue 
a large amount of prime loans. Partly in response to higher 
affordable

[[Page 63671]]

housing goals set by HUD in its new rule set in 2000, the GSEs are 
increasing their business in the subprime market. In the 2000 GSE 
Rule, HUD identified subprime borrowers as a market that can assist 
Fannie Mae and Freddie Mac in reaching their higher affordable 
housing goals while also helping establish more standardization in 
the subprime market. According to an Urban Institute study in 2002, 
many subprime lenders believe that successful companies serving 
high-risk borrowers need to have specialized expertise in outreach, 
servicing, and underwriting, which is lacking among most prime 
lenders.\207\ These lenders do not believe the more standardized 
approaches of prime lenders and the GSEs will work with subprime 
borrowers, who require the more customized and intensive origination 
and loan servicing processes currently offered by experienced 
subprime lenders.
---------------------------------------------------------------------------

    \207\ Temkin et al., 2002, p. 1.
---------------------------------------------------------------------------

    As noted above, both Fannie Mae and Freddie Mac make the claim 
that the subprime market is inefficient, pointing to evidence 
indicating that subprime borrowers pay interest rates, points, and 
fees in excess of the increased costs associated with serving 
riskier borrowers in the subprime market.\208\ A recent Freddie Mac 
study found automated mortgage scoring less discriminatory and more 
accurate in predicting risk than manual systems such as those 
currently used by subprime lenders.\209\ According to Fannie Mae, 
although a high proportion of borrowers in the subprime market could 
qualify for less costly prime mortgages, it remains unclear why 
these borrowers end up in the subprime market.\210\ Fannie Mae and 
Freddie Mac believe they can bring more efficiency to the subprime 
market by creating standardized underwriting and pricing guidelines 
in the subprime market. An expanded GSE presence in the subprime 
market could be of significant benefit to lower-income and minority 
families if it attracted more mainstream lenders and competition to 
those inner-city neighborhoods that are currently served mainly by 
subprime lenders.
---------------------------------------------------------------------------

    \208\ See Lax et al., 2000.
    \209\ Zorn, et al., 2001, p. 5.
    \210\ Fannie Mae, Remarks Prepared for Delivery by Franklin 
Raines, Chairman and CEO of Fannie Mae to the National Community 
Reinvestment Coalition. Washington, D.C. March 20, 2000.
---------------------------------------------------------------------------

    Several commenters indicated that to obtain the higher housing 
goals the GSEs would increase their purchasing of subprime loans. 
While some industry commenters welcome the entrance of the GSEs into 
the subprime market because their presence brings stability and 
standardizes business practices, they are concerned that 
unrealistically high goals could force the GSEs to jump into the 
market in a manner that negatively distorts underwriting and 
pricing. These commenters report that the GSEs can bring capital and 
standards but must gradually and carefully enter the subprime market 
in order to have a positive effect.
    In the past, Fannie Mae and Freddie Mac have voluntarily decided 
not to purchases subprime loans with features such as single-premium 
life, HOEPA loans, and prepayment penalty terms that exceed three 
years. Freddie Mac indicated that the increased goals would limit 
its ability to influence subprime lending practices.
    Several commenters suggest that if the GSEs are pushed to serve 
more of the subprime market, they will skim a significant portion of 
the lower-risk borrowers from that market. The resulting smaller 
subprime market would be comprised of the neediest borrowers. 
Concerned was raised by commenters that these higher risk borrowers 
would pay more based on three factors. First lower risk borrowers 
would not be present to subsidize them. Second, the market's high 
fixed costs would be distributed across fewer borrowers. Finally, a 
significantly smaller subprime market for private lenders would 
drive some lenders out of business translating into less 
competition.

9. Risk-Based Pricing

    The expanded use of automated underwriting and the initial uses 
of risk-based pricing are changing the mortgage lending environment, 
often blurring the distinctions between the prime and subprime 
market. Prime lenders are now using automated underwriting systems 
that are being adapted to facilitate risk-based pricing. For some 
time, the majority of prime mortgage borrowers have received loan 
rates based on average cost pricing. Generally, borrowers receive 
roughly the same Annual Percentage Rate \211\ (APR), regardless of 
the risk of loss to the lender. The risk of all borrowers is 
averaged together, and the price is determined by the average risk.
---------------------------------------------------------------------------

    \211\ Annual Percentage Rate takes into account points, fees, 
and the periodic interest rate.
---------------------------------------------------------------------------

    In contrast, risk-based pricing enables mortgage lenders to 
offer each borrower an individualized interest rate based on his or 
her risk. Or, more broadly, to offer interest rates based on whether 
or not the borrower falls into a certain category of risk, such as 
specific loan-to-value and FICO score combination or specified 
mortgage score range. Lenders could also set the interest rate based 
on various factors including the probability of prepayment and 
characteristics of the underlying collateral, as well as the default 
risk of the borrower. Borrowers that pose a lower risk of loss to 
the lender would then be charged a comparatively lower rate than 
those borrowers with greater risk. Rather than lower risk borrowers 
cross-subsidizing higher risk borrowers like in average cost 
pricing, lower risk borrowers pay a relatively lower rate.
    In response to the expanded use of automated underwriting and 
pressures from the GSEs, other purchasers of loans, mortgage 
insurers, and rating firms, lenders are increasing their use of 
risk-based pricing.\212\ In today's markets, some form of 
differential pricing exists for the various subprime categories, for 
new products targeted at credit-impaired borrowers (such as Fannie 
Mae's Timely Payments product), and for private mortgage insurance 
across all credit ranges. For example, private mortgage insurers use 
FICO scores and ``Accept'' determinations from the GSEs'' automated 
underwriting systems to make adjustments to insurance premiums.\213\ 
Rating agencies vary subordination requirements based on the credit 
qualify of the underlying collateral.
---------------------------------------------------------------------------

    \212\ Temkin et al., 2002, p.29.
    \213\ For example, see Radian's product offerings at http://www.radiangroupinc.com.
---------------------------------------------------------------------------

    Many believe there is cross-subsidization within the crude risk 
categories used in today's market. For example, some of the better 
quality subprime borrowers in the A-minus category may be 
inappropriately assigned to the subprime market. The GSEs and others 
are attempting to learn more about the subprime market, and their 
initial efforts suggest that there will be an increase in the use of 
risk-based pricing within this market, although it is recognized 
that the expansion of risk-based pricing depends importantly on 
these parties gaining a better understanding of the subprime 
borrower and the ability of their mortgage scoring systems to 
predict risk within this market. It must be noted that the power of 
the underlying algorithm in automated underwriting systems 
determines the ability of these systems to accurately predict risk 
and set prices.
    If prime lenders adopted risk-based pricing, many would be 
willing to lend to riskier subprime borrowers because their risk 
would now be offset with an increase in price. In theory, the 
mortgage market should expand because all mortgages will be approved 
at a price commensurate with risk, rather than setting a risk floor 
and approving no one beneath the floor. Risk-based pricing could 
also expand the prime lenders' market by enabling them to reach a 
new group of underserved customers.\214\ Taking advantage of GSEs' 
lower cost of capital, GSEs may be able to offer borrowers who could 
not afford a rate in the subprime market a rate they can afford 
resulting from risk-based pricing.
---------------------------------------------------------------------------

    \214\ Vanessa Bush, ``Risk-Based Pricing Trend Could Make 
Mortgage Lending More Efficient,'' America's Community Banker, 
October 1, 1998.
---------------------------------------------------------------------------

    Risk-based pricing also poses challenges on the mortgage market 
because some of the more risky borrowers (who are currently cross-
subsidized by less risky borrowers) may not be able to afford their 
higher, risk-based interest rate. Also, the adoption of an automated 
risk-based pricing system may have an uncertain effect on minority 
groups, who tend to have lower credit scores, as discussed earlier. 
On the other hand, if minorities are eligible for prime financing, 
the cost of financing minorities may fall as will the potential for 
subprime lenders to draw minorities to their higher-priced products.
    As the GSEs become more comfortable with subprime lending, the 
line between what today is considered a subprime loan versus a prime 
loan will likely deteriorate, making expansion by the GSEs look more 
like an increase in the prime market. This melding of markets could 
occur even if many of the underlying characteristics of subprime 
borrowers and the market's evaluation of the risks posed by these 
borrowers remain unchanged. Increased involvement by the GSEs in the 
subprime market will result in more standardized underwriting 
guidelines and the increased participation of traditional lenders. 
In fact, there are indications that mainstream players are already 
increasing

[[Page 63672]]

their activity in this market. According to staff from Moody's 
Investors Service, the growing role of large mortgage aggregators in 
the subprime market has been a key factor in the improving credit 
qualify on deals issued in 2002.\215\ According to a representative 
from Washington Mutual, subprime credit qualify has also improved as 
lenders carve out new loan categories that fall somewhere between 
the large Alt A market and traditional subprime business.\216\ As 
the subprime market becomes more standardized, market efficiencies 
will reduce borrowing costs. Lending to credit-impaired borrowers 
will, in turn, increasingly make good business sense for the 
mortgage market.
---------------------------------------------------------------------------

    \215\ ``Improving Credit Quality, Maturing Business Stoke 
Confidence in Subprime MBS Market,'' Inside MBS & ABS, published by 
Inside Mortgage Finance, February 21, 2003.
    \216\ Ibid.
---------------------------------------------------------------------------

D. Factor 2: Economic, Housing, and Demographic Conditions: 
Multifamily Mortgage Market

1. Introduction

    At the time of the previous GSE rulemaking in 2000, the 
multifamily rental housing market was coming off several years of 
generally positive performance. Vacancies were low in most markets 
and rent increases were matching or exceeding economy-wide 
inflation. A key to this strong performance was the volume of new 
multifamily construction, which was at a level consistent with 
demand growth. Job growth and income gains helped many renters pay 
the higher rents without undue burden. As always, conditions varied 
from region to region, and across market segments, but the overall 
tone of the apartment market was quite healthy.
    Much has changed in the subsequent years. An economic slowdown 
reduced apartment demand, and with new multifamily construction 
about unchanged, vacancies rose and rents softened. Provision of 
decent housing affordable to households of moderate or low incomes 
is a challenge even in strong economic times, and with the 
unemployment rate rising above 6 percent before falling to about 5 
and a half percent, affordability problems increased for many, 
despite the softness in rents.
    Despite the recent weakness in the apartment property market, 
the market for financing of apartments has grown to record volumes. 
The favorable long-term prospects for apartment investments, 
combined with record low interest rates, has kept investor demand 
for apartments strong and supported property prices. Refinancings 
too have grown, and credit quality has remained very high. Fannie 
Mae and Freddie Mac have been among those boosting volumes and 
introducing new programs to serve the multifamily market.
    This section will review these market developments, interpret 
the performance of Fannie and Freddie within that market context, 
and discuss future prospects for the multifamily rental market, its 
financing, and the GSE role. The intention here is only to update 
the discussion from 2000. For general background information on the 
multifamily mortgage market and the GSEs, see the 2000 Rule and the 
HUD-sponsored research report, Study of Multifamily Underwriting and 
the GSEs' Role in the Multifamily Market (Abt Associates, 2001).

2. The Multifamily Rental Housing Market: 2000-2003

    The definition of ``good'' market conditions in multifamily 
rental housing depends on one's perspective. Investors and lenders 
like low vacancies, steady rent increases, and rising property 
values. Developers like strong demand for new construction and 
favorable terms on construction financing. Consumers, in contrast, 
prefer low rents and a wide selection of available apartments.
    The mid- to late-1990s were among the most successful of recent 
history, in that apartment market conditions were generally good for 
all of these interest groups. Investment returns were favorable, 
construction volumes were steady at sustainable levels, and many 
consumers had income gains in excess of their rent increases.
    Market conditions for multifamily rental housing began to weaken 
toward the end of 2000. Early warnings came from the publicly traded 
apartment companies, some of which reported easing in demand growth 
in the first months of 2001, coinciding with a slowdown in job 
growth to its lowest level since 1992.
    By 2003, rental units were experiencing record high vacancy 
rates and newly completed apartments faced record low absorption or 
ease-up rates. The rental sector vacancy rate averaged 9.8 percent 
in 2003, up 0.8 percent from 2002, and the highest annual vacancy 
rate I the more than 40-year history of the measure.\217\
---------------------------------------------------------------------------

    \217\ U.S. Department of HUD, Office of Policy Development and 
Research, U.S. Housing Market Conditions: 4th Quarter 2003, February 
2004, p. 3.
---------------------------------------------------------------------------

    Apartments--especially those serving the top end of the rental 
market--appear to have performed worse than other rental housing in 
the past four years, after several years of rent growth and 
occupancies surpassing the rental market averages. The multifamily 
(5+ units in structure) vacancy rate has increased more than the 
overall rental market vacancy rate in each of the years 2000, 2001, 
2002, and 2003. For example, the Census Bureau's estimate of a 0.9 
percentage point increase in vacancies for multi-family apartments 
in 2003 exceeds the overall rental vacancy rate of 0.6 percent.\218\ 
Similarly, while rent growth has decelerated slightly for all rental 
housing according to the CPI, industry surveys of apartment rents 
show year-over-year declines in rents in many local markets.\219\ In 
2003, asking rents remained flat nationally, as multifamily 
completions declined 5 percent.\220\
---------------------------------------------------------------------------

    \218\ U.S. Department of HUD, Office of Policy Development and 
Research, U.S. Housing Market Conditions: 4th Quarter 2003, February 
2004, p. 84.
    \219\ See, for example, Marcus & Millichap Research Services, 
National Apartment Report, January 2003.
    \220\ Marcus & Millichap Research Services, National Apartment 
Report, January 2004.
---------------------------------------------------------------------------

a. Apartment Demand and Supply

    The primary reason for the softening in the multifamily rental 
market has been a reduction in the growth of consumer demand for 
apartment housing. The general slowdown in economic activity meant 
fewer apartment customers, with less money, than if the economy were 
vigorously expanding. Persistent low interest rates have also 
enticed renters into the home purchase market as evidenced by the 
U.S. homeownership rate, which grew to 68.4 percent in 2003, further 
contributing to a weakness in rental demand.
    The reduced demand is most evident in the national statistics on 
employment. Job growth began decelerating in late 2000 and 
throughout 2001, turning negative late that year. The largest year-
over-year job loss of the economic downturn occurred in February 
2002, and year-over-year losses have continued through October 
2003.\221\ Apartment demand seems particularly sensitive to labor 
market conditions, given the importance of rental housing to mobile 
individuals and families accepting new jobs or transfers. Reis, 
Inc., a real estate market research firm, estimates that the total 
number of occupied apartments (in properties with 40+ units) 
actually declined in both 2001 and 2002 in the large markets 
nationwide that are monitored by the company.\222\ Job numbers 
showed some rebound in the subsequent period.
---------------------------------------------------------------------------

    \221\ U.S. Department of Labor, Bureau of Labor Statistics, 
``Bureau of Labor Statistics Data,'' Accessed July 31, 2004, http://data.bls.gov/servlet/SurveyOutputServlet?data_tool=latest_numbers&series_; id=LNS14000000.
    \222\ ``Apartment Landlords Gather to Dreary Outlook for 
Sector,'' Wall Street Journal, January 15, 2003, Section B.
---------------------------------------------------------------------------

    Households, not jobs, fill apartments, and for this reason 
household formations are a preferable indicator of demand for 
apartments as well as other types of housing. The Census Bureau 
estimates that the total number of renter households nationwide has 
been essentially unchanged at approximately 34.8 million since 1996. 
Yet during the late 1990s apartment demand was expanding, and 
apartments were apparently picking up market share from other rental 
housing. The past two or three years may have seen a reversal of 
that trend in share.
    Long-term demographic trends are expected to be favorable for 
rental housing demand.\223\ The maturing of the ``Baby Boom Echo'' 
generation will increase the number of persons under age 25 who will 
seek rental housing, immigration is expected to continue to fuel 
demand for rental housing, and minority populations, while 
increasing their homeownership rates, are growing and will 
contribute to higher absolute demand for rental housing. Thus 
demographic trends support an improvement in the long-run demand for 
rental demand, which is likely to include higher multifamily rental 
demand.
---------------------------------------------------------------------------

    \223\ Mortgage Bankers Association of America, ``MBA News Link: 
Rental Market Demographics ``Favorable,'' Report Says,'' January 
2003.
---------------------------------------------------------------------------

    Supply growth has been maintained, even though the current 
reduced multifamily demand warrants less new construction. Total 
multifamily starts (2+ units) have been running approximately 325-
to-350 thousand annually for the past six years, according to Census 
Bureau statistics, adding about 1 percent annually to the total 
multifamily stock. Most of these new units are built for rental use, 
with only about 20 percent in

[[Page 63673]]

recent years reported as being built as for-sale condominium units.
    The reduced short-term demand has shown through in absorption 
speeds for new apartments. The percentage of newly completed 
unfurnished apartments rented within three months of completion fell 
from 72 percent during 2000 to 63 percent during 2001 and to 59 
percent during 2002, the lowest level in the 33-year history of the 
data series, according to the Census Bureau. This percentage rose 
slightly to 60 percent in 2003.\224\
---------------------------------------------------------------------------

    \224\ U.S. Department of HUD, Office of Policy Development and 
Research, U.S. Housing Market Conditions: 4th Quarter 2003, February 
2004, p. 70.
---------------------------------------------------------------------------

b. Performance by Market Segments

    Some segments of the multifamily rental market have been more 
affected than others by the recent softening. As mentioned earlier, 
the top end of the apartment market seems especially hard hit, as 
measured by rising vacancies and reduced rent growth. This segment 
is particularly dependent on job growth and transfers for new 
customers, and is particularly vulnerable to losses of residents and 
prospective customers to home purchase. According to reports by 
apartment REITs and other investors, these top-end properties have 
not been getting the job-related in-movers, but have still been 
losing a lot of customers to home purchase. These properties 
generally have annual resident turnover rates of above 50 percent, 
and thus are particularly quickly influenced by changes in demand. 
Furthermore, this is the segment of the apartment market into which 
most of the new construction is built.
    Performance has varied geographically as well. Some of the 
coastal markets, especially in Northern California, saw the double-
digit rent increases of the late 1990s replaced by double-digit 
declines, before stabilizing more recently. ``Supply constrained 
markets'' had been preferred by apartment investors during the 
1990s, but recent market performance has reminded investors and 
analysts that all markets have their day. For example, Houston 
posted the biggest year-over-year rent increase of any major 
apartment market in 2001, despite a long-run history of moderate 
rent growth and few barriers to new apartment construction. Rent 
changes in the 27 metro markets for which estimates are available 
from the CPI ranged from a low of -0.3 percent to a high of 6.7 
percent in the first half of 2003 relative to a year earlier. And 
across the 75 metro areas for which rental vacancy rates (apartments 
plus other rentals combined) are available, rates for the year 2002 
ranged from 2.4 percent to 15.4 percent, according to the Census 
Bureau. In a historical context, this variation is moderate, 
although up somewhat since the late 1990s.
    Conditions in the ``affordable'' segment of the apartment market 
are harder to track than in the high-end segment because of lesser 
investor interest and analyst coverage. Data for the late 1990s 
analyzed by the National Housing Conference saw affordability 
problems continuing, although a study of apartment renters by the 
National Multi Housing Council saw some improvement in affordability 
during the strong economic growth of 1997-1999.\225\ Other work 
noted that rent to income ratios for the lowest income quintile of 
renters rose during the late 1990s even as these ratios were stable 
or declining for other renters.\226\ Harvard's State of the Nation's 
Housing report for 2002 highlighted the variability of the 
affordability problem from place to place.\227\
---------------------------------------------------------------------------

    \225\ Center for Housing Policy/National Housing Conference, 
``Housing America's Working Families: A Further Exploration,'' New 
Century Housing, Vol. 3, No. 1, March 2002; Mark Obrinsky and Jill 
Meron, ``Housing Affordability: The Apartment Universe,'' National 
Multi Housing Council, 2002.
    \226\ ``Housing Affordability in the United States: Trends, 
Interpretations, and Outlook,'' a report prepared for the Millennial 
Housing Commission by J. Goodman, November, 2001.
    \227\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing, 2002.
---------------------------------------------------------------------------

    Little research is available on affordability trends since 1999. 
However, tabulations from the 2001 American Housing Survey indicate 
that income growth between 1999 and 2001 in the lowest quintile of 
renter households continued to lag that of higher income renters, 
and fell short of the average rent increases during this period. 
Together, these statistics suggest that affordability has 
deteriorated early this decade among at least this group of very 
low-income renters. Other work using the AHS found that the number 
of low-to moderate-income working families with severe rental cost 
burdens increased 24 percent between 1999 and 2001.\228\
---------------------------------------------------------------------------

    \228\ Center for Housing Policy/National Housing Conference, 
``America's Working Families and the Housing Landscape 1997-2001,'' 
New Century Housing, Vol. 3, No. 2, November 2002
---------------------------------------------------------------------------

    The low-income housing tax credit (LIHTC) continues to finance 
much of the newly built multifamily rental housing that is 
affordable to households with moderate income. Restricted to 
households with incomes no greater than 60 percent of the local 
median, this program financed approximately 75,000 units in 2001, 
according to the National Council of State Housing Agencies, after 
running in the mid-to high-60 thousand range the previous three 
years. About 70 percent of these units are newly built, and the rest 
are renovations of existing units.
    Expenditures for improvements to existing rental apartments have 
grown in recent years. In 2001 the total of $11.3 billion was nearly 
twice the figure of three years earlier, according to the Census 
Bureau, and more than a third as large as construction spending for 
newly built multifamily structures, including owner-occupied condos. 
Many of these improvements are to older properties in high-demand 
neighborhoods. Improvements to the physical structures have external 
benefits. But often the renovations are in connection with re-
positionings that move the apartments into a higher rent range and 
bring changes in the demographic composition of the resident base.
    In 2002, expenditures on total improvements to existing 
apartments declined to $9.8 billion, while new construction spending 
increased $2 billion. This shift further suggests a re-positioning 
to apartments with a higher rent range. Excluding units financed 
with tax credits or other subsidies, most of the multifamily rental 
construction in recent years has been targeted on the upper end of 
the market, often the only segment for which unsubsidized new 
construction is economically feasible. The median asking rent on new 
unfurnished apartments completed in 2001 was $877, up 11 percent 
over the previous two years. In 2002 median asking rent for these 
properties was $905. Of those units brought to market in 2002, 45 
percent were at rents at or above $950.

3. Multifamily Financing Trends

    In contrast to the softening observed in the demand/supply 
balance for multifamily, mortgage financing of these properties has 
been at a record pace in the past three years.

a. Lending Volume

    Total multifamily mortgage debt outstanding increased 11 percent 
in 1999, 8.7 percent in 2000, 11.2 percent in 2001, 9.6 percent in 
2002, and 11.2 percent in 2003 according to the Federal Reserve's 
flow of funds accounts. The dollar volume for 2003, $544.2 billion, 
is above those of any previous year. The pace seems to have slowed 
for 2004, with the first quarter indicating an annualized growth of 
4.9 percent. Furthermore, a 2003 survey by the Mortgage Bankers 
Association of America show that of 48 member firms surveyed, 
representing all large mortgage banking firms an a cross section of 
smaller mortgage companies, multifamily origination volume increased 
21.5 percent in 2003--from $41 billion in 2002 to $49.8 billion in 
2003.
    The apparent inconsistency between current market fundamentals 
and financing can be explained by low interest rates. The same 
financial forces that lowered the mortgage rates for home purchasers 
to record lows by 2002 also reduced the financing costs of 
multifamily properties. The ten year Treasury yield, a common 
benchmark for multifamily loan pricing, fell to a 45-year low of 3.3 
percent in June 2003 from 6.3 percent as recently as the end of 
1999.
    Another feature boosting investor demand for apartment 
properties and the resulting demand for debt to finance those 
purchases has been the lack of attractive returns on many financial 
assets and other alternative investments. Despite the current weak 
performance of apartments, investors apparently are looking through 
to the long-run outlook for these assets, which is generally thought 
to be favorable, as indicated most recently by investor surveys 
fielded by the Urban Land Institute and by Lend Lease and 
PriceWaterhouseCoopers.\229\
---------------------------------------------------------------------------

    \229\ Urban Land Institute, The ULI Forecast, 2002; Lendlease 
and PriceWaterhouseCoopers, Emerging Trends in Real Estate, 2003.
---------------------------------------------------------------------------

    The net change in mortgage debt outstanding is defined as loan 
originations less repayments and charge offs. As discussed in 
Appendix D, net change is a lower bound on originations. By all 
accounts, originations--for which no single source of estimates is 
available--are much higher than net change in most years. High 
levels of refinancings of existing multifamily mortgages in recent 
years has been a factor in originations exceeding the net change in 
debt outstanding.

[[Page 63674]]

    Most mortgage lending is in the ``conventional'' market. 
Multifamily loan programs of the Federal Housing Administration 
accounted about $7 billion in new insured mortgages in fiscal year 
2003--up from $6 billion in fiscal year 2002 and $5 billion in 
fiscal 2001. Despite the recent increase in FHA originations, and 
the likely continued strong performance for FHA multifamily programs 
in the foreseeable future, \230\ FHA remains but a small portion of 
the total multifamily mortgage market. Outstanding FHA-insured 
multifamily mortgage debt was $55 billion at the end of the first 
quarter of 2003--only about 11 percent of all multifamily mortgage 
debt outstanding.
---------------------------------------------------------------------------

    \230\ Merrill Lynch, A New Look at FHA Prepayments and Defaults, 
September 2002.
---------------------------------------------------------------------------

    Multifamily lending has been spurred by new apartment 
construction, property sales, and refinancings. New multifamily 
construction was valued at $34.1 billion in 2003, according to the 
Census Bureau, up 21 percent from 2000.\231\ The number of new 
multifamily units completed over this period actually declined 12 
percent, and the increased expenditures reflect higher costs per 
unit. The increase in asking rents described earlier suggests higher 
property values and greater debt carrying capacity.
---------------------------------------------------------------------------

    \231\ Eight percent inflation adjusted.
---------------------------------------------------------------------------

b. Property Sales and Refinancings

    Sales of existing apartment properties tend to be procyclical. 
Increasing asset values bring buyers to the market and tempt sellers 
to realize their capital gains. In soft markets, in contrast, the 
bid-ask spread generally widens and the volume of sales declines, as 
sellers perceive current offers as beneath the property's long run 
value and buyers are reluctant to pay for past performance or the 
hope of future gains. Sales tend to increase mortgage debt, because 
the loan originated to finance the purchaser's acquisition is 
typically considerably larger than the mortgage retired by the 
seller.
    No source of apartment property sales statistics matches the 
comprehensive national coverage of the single-family market provided 
by the National Association of Realtors' monthly estimates. But 
surveys by the National Multi Housing Council and other apartment 
industry reports indicate that transactions volume dipped during 
2001 but since then have grown appreciably in both number of sales 
and aggregate dollar value.
    Mortgage lending volumes have recently been boosted by shifts in 
property ownership. Publicly traded real estate investment trusts 
had been the big gainers during most of the 1990s, and by 1999 owned 
nearly 6 percent of all apartments nationwide and a considerably 
larger share of all big (100+ unit) properties. But beginning in 
1999 capital market developments made private buyers more 
competitive. Since then the number of apartments owned by large 
REITs has declined about 5 percent, with diverse private interests 
apparently picking up market share.
    Private investors are able to use more leverage--greater debt--
in financing their transactions than the market permits the public 
REITs. As a result, the very low mortgage rates recently have given 
them an advantage in bidding on properties. In addition, equity 
funding costs of REITs rose as their stock prices flattened or moved 
down as part of the broader equity market correction.
    Refinancings have, by all accounts, also been strong. Despite 
the lockout provisions and yield maintenance agreements that 
constrain early refinancings of many multifamily loans, lenders 
reported very strong refinancing activity in 2001 and continuing 
into 2002. Although refinancing volume data for the entire market 
are not available, the trends in refinance volume for FHA and the 
GSEs show very strong increases in refinance activity during 2002 
and 2003. For example, FHA's Section 223(a)(7) program, which is 
limited to refinancing of FHA multifamily mortgages, experienced an 
increase in origination volume of 133 percent in Fiscal Year 2003 
and 181 percent in Fiscal Year 2002. ($1.73 billion in FY 2003, 
$0.74 billion in FY 2002, and $0.26 billion in FY 2001). Similarly, 
the GSEs increased their combined volume of refinances by 83 percent 
from 1999-2000 to 2001-2002, from $17.6 billion to $32.1 billion. 
Refinancings, especially when motivated by a desire to lower 
interest expense rather than to extract equity, do not add as much 
to debt outstanding as do purchase loans, which often are much 
larger than the seller's existing mortgage that is repaid at the 
time of sale. Nonetheless, refinancings represent a significant part 
of all multifamily mortgage lending.

c. Sources of Financing and Credit Quality

    The sources of funding of multifamily mortgages shifted somewhat 
in the past few years, judging from the Flow of Funds accounts. As 
shown in Table A.4, four categories of lenders have dominated 
multifamily mortgage lending since the mid-1990s. Of those four, 
commercial banks have played a lesser, although still substantial, 
role in recent years, providing 20 percent of the $86 billion in net 
additional funding of multifamily mortgages during 2000 and 2001. 
The portfolio holdings of the GSEs, by contrast, have been much more 
important than during the last half of the 1990s. Mortgage backed 
securities, both from the GSEs and especially from other issuers, 
accounted for proportionally less of the growth in 2000-01 than in 
1995-99, but between them still accounted for nearly half of all the 
net credit extensions. Some slight broadening of the base of 
multifamily lending in the past two years, as these four lender 
groups accounted for only 85 percent of the net credit extended in 
2000 and 2001, compared to all of it in the previous five-year 
period.

[[Page 63675]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.013

    The market values of apartment properties have generally held up 
well, although the most recent indicators suggest some flattening. 
Properties in the portfolios of pension funds continued to 
appreciate into the second half of 2002, according to the National 
Council of Real Estate Investment Fiduciaries, although at a reduced 
annual rate of less than 2 percent. And the sales price per square 
foot of ``Class A'' properties monitored by Global Real Analytics 
rose until turning down in early 2002, posting a 1.6 percent year 
over year decline in the second quarter.
    The continuing value of collateral has helped keep loan quality 
high on multifamily mortgages. Delinquency rates from all major 
reporters are at or near record lows, and well below the rates 
reported for single-family mortgages and commercial properties. At 
commercial banks, the FDIC reports a 0.38 non-current loan 
percentage in the second quarter of 2002. In life insurance company 
portfolios the only 0.05 percent of residential mortgages were 
overdue at the end of 2002, and as of the third quarter of 2002 the 
GSEs were both reporting similarly miniscule delinquency rates of 
below 0.1 percent; all of these rates are below those of a year 
earlier.
    Multifamily lenders have remained cautious in their underwriting 
and, together with their regulators; have avoided repeating the 
mistakes of the 1980s. Many of the senior loan officers surveyed 
quarterly by the Federal Reserve have reported tightening their 
terms on commercial mortgages, and that shift likely has occurred in 
their multifamily lending as well. Perhaps the best indicator of 
discipline in multifamily lending is the fact that, despite the 
strong apartment demand during the last half of the 1990s, 
construction never rose above its long-run sustainable level, unlike 
the rampant overbuilding that plagued the industry in the mid- and 
late-1980s.

4. Recent GSE Involvement in Multifamily Finance

    As the multifamily mortgage market has expanded since 1999, 
Fannie Mae and Freddie Mac have increased their lending, picked up 
market share, introduced new programs, and enhanced others.
    Beginning with their whole loans, the GSEs added 34 percent to 
their combined holdings of multifamily loans in 2001, and another 26 
percent in 2002 (see Table A.6 below). The growth in multifamily MBS 
volume was nearly as dramatic, increasing 26 percent in 2001 and 
another 14 percent in 2002. The gains resulted in the GSEs 
increasing their share (whole loans and securities combined) of all 
multifamily debt outstanding to 22.8 percent by the third quarter of 
2003, up from 19 percent at year-end 2001, 15 percent at year-end 
1999 and 11 percent at the end of 1995. By this combined measure of 
portfolio holdings and MBS outstanding, at year-end 2002 Fannie Mae 
had nearly twice ($65 billion versus $37 billion) the multifamily 
business of Freddie Mac, although Freddie was growing its 
multifamily business more rapidly (67 percent increase between 2000 
and 2002, compared to 46 percent increase for Fannie Mae). In 2003, 
Freddie Mac's multifamily business activities totaled $21.587 
billion ($14.894 billion of mortgage purchases and $6.693 billion in 
investment activities). These activities financed rental housing for 
549,083 families. Nearly 92 percent of these units were affordable 
to low- and moderate-income renters. Since 1993, Freddie Mac has 
purchased $75.5 billion in multifamily mortgages, financing housing 
for more than 2.2 million families.\232\
---------------------------------------------------------------------------

    \232\ Freddie Mac Public Comment Letter on HUD's Proposed Goals, 
July 2004, p.3.
---------------------------------------------------------------------------

    Measures that focus on new multifamily activity, specifically 
gross mortgage purchase volumes and new security issuance, vary 
across recent years and between the GSEs. For the GSEs combined, 
these measures of current business activity show sharp gains of over 
70 percent in 2001, following small decreases in activity in 2000. 
In 2002, the GSEs combined posted small declines for both measures. 
Measures of multifamily gross mortgage purchases and new security

[[Page 63676]]

issuance diverged for the two GSEs in 2002. Fannie Mae experienced 
declines in these balance sheet and new business indicators in 2002 
while Freddie Mac experienced gains, particularly in new security 
issuance. As discussed earlier, the credit quality of GSE 
multifamily loans has remained very high even with the large gains 
in loan volume.
    Despite the substantial pickup in GSE multifamily activity, the 
position of these companies in the multifamily mortgage market 
remains well below their dominance in single-family mortgage 
finance. At the end of 2002, the GSEs' market share of single family 
debt outstanding was 44 percent, twice the share of multifamily debt 
held or securitized by these two companies, according to Federal 
Reserve statistics. Furthermore, the multifamily share of all 
housing units financed by the GSEs combined has declined from its 
1997 level (Table A.5), although the annual statistics are heavily 
influenced by the volume of refinancings in the single-family 
market, which spiked in 1998 and again in 2001 and 2002 in response 
to the big decline in mortgage rates in those years. Because of 
lock-out agreements and other loan covenants, multifamily loans are 
not as prone to rate-induced refinancings as are single-family 
mortgages.
BILLING CODE 4210-27-P

[[Page 63677]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.014

a. Contrasting Business Models

    While both Fannie Mae and Freddie Mac have significantly 
increased their multifamily activities in recent years, they have 
pursued distinct business models in achieving that growth. As shown 
in Table A.6, most of Fannie Mae's multifamily growth has come in 
MBS products, whereas Freddie Mac has relied more on loans purchased 
and held in its portfolio. At the end of 2002, Fannie Mae had almost 
four dollars of outstanding MBSs for every dollar of portfolio 
holdings. Freddie

[[Page 63678]]

Mac, on the other hand, more than three times as much volume in 
portfolio as it had in MBS outstanding.
[GRAPHIC] [TIFF OMITTED] TR02NO04.015


[[Page 63679]]


    The differing emphasis on portfolio holdings and securities 
issuance is related to the GSEs' contrasting approaches to credit 
underwriting.\233\ Fannie Mae has long had risk-sharing arrangements 
with its multifamily loan originators, and currently has over 25 
Delegated Underwriters and Servicers who are authorized to originate 
loans meeting Fannie Mae's requirements for sale to the GSE without 
prior approval of individual transactions. These ``DUS'' lenders 
retain part of the credit risk on the loans sold to Fannie.
---------------------------------------------------------------------------

    \233\ ``No Mistaking GSEs for Twins in Multifamily,'' American 
Banker, October 2, 2002.
---------------------------------------------------------------------------

    Freddie Mac has taken a different approach to credit 
underwriting. In the wake of large credit losses on its multifamily 
business in the late 1980s and 1990, Freddie Mac essentially 
withdrew from the market. When it re-entered in late 1993, the 
company elected to retain all underwriting in-house and not delegate 
this function to the loan originators participating in Freddie Mac's 
Program Plus network. Because Freddie Mac assumes the entire credit 
risk on loans it purchases, some commercial banks and other 
financial institutions desiring to remove multifamily loans and all 
related liabilities from their books find Freddie Mac's program 
preferable.

b. Affordable Multifamily Lending

    Because most of the GSEs' multifamily lending is on properties 
affordable to households with low-or moderate incomes, financing of 
affordable multifamily housing by the GSEs has increased almost as 
much as their total multifamily lending. Approximately 87 percent of 
Fannie Mae's multifamily lending volume in 2003 qualified as 
affordable to low-or moderate income households, according to Fannie 
Mae's annual Housing Activity Report, as did 92 percent of Freddie 
Mac's multifamily units financed. For the entire multifamily rental 
market, HUD estimates that 90 percent of all housing units qualify 
as affordable to families at or below 100 percent of the area median 
income, the standard upon which the low- and moderate-income housing 
goal is defined.
    Owing to this high propensity to qualify as affordable lending, 
financing of multifamily rental housing is especially important for 
the GSEs attainment of their affordable housing goals. Less than 8 
percent of the units financed by the GSEs in 2002 were multifamily 
rentals, as described above. Yet 15 percent of the units qualifying 
as low- and moderate-income purchases were multifamily, according to 
Table 1 of the GSEs' activity reports for 2002.
    The GSEs increased the volume of their affordable multifamily 
lending dramatically in 2001, the first year of the new, higher 
affordable housing goals set for the GSEs. As measured by number of 
units financed, the total affordable lending (shown in the ``low-mod 
total'' rows of Table A.7) more than doubled from a year earlier, 
especially after application of the upward adjustment factor 
authorized for Freddie Mac in the 2000 Rule. In 2003 the GSEs 
maintained a high volume of affordable multifamily lending.\234\
---------------------------------------------------------------------------

    \234\ This change was a percentage decrease but a volume 
increase.

---------------------------------------------------------------------------

[[Page 63680]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.016

BILLING CODE 4210-27-C

[[Page 63681]]

    The figures in Table A.7 are exclusive of the ``Temporary 
Adjustment Factor (TAF)'' granted to Freddie Mac as part of the 2000 
Rule. The TAF was a response to Freddie Mac's limited opportunities 
for refinancing business because of its minimal involvement in the 
multifamily market in the early and mid-1990s.\235\ The TAF, which 
expired at the end of 2003, provided a 20 percent upward adjustment 
to multifamily units in properties with 50 or more units, for 
purposes of the affordable housing goals.
---------------------------------------------------------------------------

    \235\ For background information on the Freddie Mac TAF, see 
pages 65054 and 65067-65068 of the 2000 Rule.
---------------------------------------------------------------------------

    Multifamily financing made major contributions not only to the 
GSEs' attainment of the overall goal for affordable lending in 2002, 
but also to the ``underserved areas'' goal and ``special 
affordable'' goal. As shown in Table A.7, the 2001 increases in 
lending in each of these categories were substantial at both Fannie 
Mae and Freddie Mac, again leveling off for both in 2002. The GSEs 
also met the special multifamily affordable subgoal set in the 2000 
Rule in both 2001 and 2002.

c. Multifamily Initiatives of the GSEs

    Fannie Mae and Freddie Mac have taken a number of steps since 
2000 to expand their multifamily lending and to respond specifically 
to the goals established in the 2000 Rule. These initiatives are 
summarized in the annual activity reports filed by the GSEs.\236\
---------------------------------------------------------------------------

    \236\ Fannie Mae's 2002 Annual Housing Activities Report, pages 
24-27; Freddie Mac's Annual Housing Activities Report for 2002, 
pages 41-47.
---------------------------------------------------------------------------

    One focus of the 2000 Rule was on lending to small (5-to-50 
units) multifamily properties, which the Rule identified as an 
underserved market. HUD-sponsored research has found that the supply 
of mortgage credit to small properties was impeded by the 
substantial fixed costs of multifamily loan originations, by owners' 
insufficient documentation of property income and expense, and by 
the limited opportunities for fees for underwriting and servicing 
small loans.\237\ As a result, many multifamily lenders focus on 
larger properties, which were found to have more loan products 
available to them and to pay lower interest rates than did small 
properties.
---------------------------------------------------------------------------

    \237\ Abt Associates Inc., An Assessment of the Availability and 
Cost of Financing for Small Multifamily Properties, a report 
prepared for the U.S. Department of Housing and Urban Development, 
Office of Policy Development and Research, August 2001.
---------------------------------------------------------------------------

    In an attempt to promote the supply of credit to small 
properties, the 2000 Rule provided incentives for the GSEs to step 
up their involvement in this segment of the multifamily mortgage 
market. The incentives likely contributed to the huge increases in 
small property lending posted by both Fannie Mae and Freddie Mac in 
2001 and continuing into 2002 (Table A.7). The combined total of 
these units financed in 2001 and 2002 was almost 8 times those 
financed in the previous two years. This lifted the percentage of 
all GSE multifamily lending that was on small properties to their 
highest levels ever.
    During 2003, multifamily business activity at Fannie Mae topped 
$33 billion which financed over 809,703 multifamily units. Of this 
total, over 87% were affordable to families at or below the median 
income of their communities.\238\ Freddie Mac multifamily business 
activities totaled a record $21.587 billion which financed rental 
housing for 549,083 families. Nearly 92 percent of these apartment 
units were affordable to low- and moderate income renters.\239\
---------------------------------------------------------------------------

    \238\ Fannie Mae, 2003 Annual Housing Activities Report, March 
15, 2004, p. 26.
    \239\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
44.
---------------------------------------------------------------------------

    Programs introduced or enhanced by the GSEs in the past two 
years have contributed to these striking numerical results. 
Delegated Underwriting and Servicing (DUS) is Fannie Mae's principle 
product line for purchasing individual multifamily loans. This 
product line is offered through 26 lenders with expertise in 
financing multifamily properties. In 2003, 91% of the DUS loan 
activity served affordable housing needs, 42% of DUS loans in 
underserved markets, and 52% addressed ``special affordable'' 
needs.\240\ Believing that small multifamily properties are a vital 
part of the country's affordable housing stock, Fannie Mae has 
focused efforts on providing financing for these projects through 
the development of the MFlex Loan Product, the 3MaxExpress 
Streamlined Mortgage Loan Product and the Affordable Alliances Loan 
Product. The MFlex Loan Product was established in 2000 to target 
lending partners that serve small property borrowers and increase 
Fannie Mae's participation in the 5-50 unit property market. By 
2003, Fannie Mae had seven MFlex lending partners and had purchased 
$1.6 billion of these loans. Fannie Mae markets its specialized 
3MaxExpress Streamlined Mortgage Loan Product line for loans worth 
less than or equal to $3 million. In 2003, Fannie Mae provided $1 
billion in financing, which assisted over 34,000 families living in 
small multifamily properties. The Affordable Alliances Loan Product 
is responsible for debt investments in rental housing targeted to 
persons of low- and moderate-income and to rental markets that are 
underserved. During 2003, these financing initiatives provided 
affordable housing for 3,850 families. \241\ Fannie Mae additionally 
has federal Low-Income Housing Tax Credit (LIHTC) programs and 
special financing projects for special use properties such as 
Seniors Housing. In 2003, Fannie Mae committed over $1.6 billion in 
LIHTC equity properties to help make affordable rental housing 
possible for over 30,000 families.\242\
---------------------------------------------------------------------------

    \240\ Fannie Mae, 2003 Annual Housing Activities Report, March 
15, 2004, p. 27.
    \241\ Fannie Mae, 2003 Annual Housing Activities Report, March 
15, 2004, p. 28.
    \242\ Fannie Mae, 2003 Annual Housing Activities Report, March 
15, 2004, p. 29.
---------------------------------------------------------------------------

    During 2003, Freddie Mac used innovative financing structures 
combined with prudent, flexible multifamily lending practices, which 
enabled them to reach a record level of multifamily mortgage 
purchases.\243\ The GSEs face strong competition in this market from 
small banks and other depository institutions that prefer to hold 
these loans in their own portfolios.\244\
---------------------------------------------------------------------------

    \243\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
47.
    \244\ ``Fannie Courting Multifamily Sellers; Small Banks 
Balking,'' American Banker, January 13, 2003.
---------------------------------------------------------------------------

    In 2003, Freddie Mac continued to test initiatives through 
pilots, and implement enhancements to existing multifamily mortgage 
products which cover a broad array of eligible mortgage products. 
Freddie Mac's tax-exempt bond credit enhancements with synthetic 
fixed-rate financing continued to be popular. Freddie Mac's 
innovations to certain cash products including various combinations 
of fixed-rate, adjustable-rate and interest-only mortgages have been 
adopted by others in the industry. For example, the Fixed-to-Float 
execution provides borrowers with a reduced fixed interest rate and 
a one-year extension of the mortgage term at a floating rate. In 
2003, borrowers used Fixed-to-Float option for $4.0 billion in 
mortgages.\245\
---------------------------------------------------------------------------

    \245\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Repoert for 2003, March 15, 2004, p. 
47 & 49.
---------------------------------------------------------------------------

    In 2003, Freddie Mac purchased $6.6 billion in mortgages to 
finance more than 181,000 apartment units in 5-to 50-unit 
properties. Freddie Mac committed to invest $958 million to Low 
Income Housing Tax Credits (LIHTC). Altogether, the LIHTC 
investments made by Freddie Mac are approaching the $3.6 billion 
mark and have constructed or rehabbed more than 216,000 rental units 
for very-low and low income families in close to 3,000 projects. In 
2003, Freddie purchased $412 million in newly issued multifamily 
mortgage revenue bonds. These bonds, issued by state, county or city 
government agencies, finance the acquisition and rehabilitation of 
nonprofit borrowers or property owners who agree to keep rents at 
affordable levels. These multifamily bond purchases will finance 
6,100 estimated units of affordable housing with an estimate that 58 
percent of those units will be affordable to very low income 
families. In 2003, Freddie issued a record $7.7 billion of 
securities backed by multifamily mortgages through negotiated 
transactions. More than 85 percent of these securities financed 
mortgages for affordable housing.\246\
---------------------------------------------------------------------------

    \246\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
50-52.
---------------------------------------------------------------------------

    The 2000 Rule discussed other ways in which the GSEs might help 
promote financing of affordable multifamily housing. Two of those 
were lending for property rehabilitation and leadership in 
establishing standards for affordable multifamily lending. Many 
affordable properties are old and in need of capital improvements if 
they are to remain in the housing stock. Rehabilitation lending is a 
specialized field, and one in which the GSEs for a variety of 
reasons have not been major players. Less than 1 percent of all GSE 
multifamily lending in 2002 was for property rehabilitation. In 
2002, Fannie Mae hosted its first ever Preservation Advisory Meeting 
with leaders in the housing and real estate finance industry to 
identify best practices and formulate real

[[Page 63682]]

world solutions to this critical policy issue.\247\
---------------------------------------------------------------------------

    \247\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 27.
---------------------------------------------------------------------------

    Setting standards for affordable multifamily lending was 
identified in the 2000 Rule as another area where the GSEs could 
provide greater leadership. It was also noted, based on HUD-
sponsored research underway at that time,\248\ that market 
participants believe the GSEs to be conservative in their approaches 
to affordable property lending and underwriting. Actions described 
in the GSEs' annual activity reports for 2001, 2002 and 2003 
indicate attempts by the GSEs to promote market standards that will 
reduce the transactions costs of multifamily lending while also 
providing programs that have the flexibility needed to deal with 
unique circumstances.
---------------------------------------------------------------------------

    \248\ Abt Associates, ``Study of Multifamily Underwriting and 
the GSEs'' Role in the Multifamily Market,'' Final Report to the 
U.S. Department of Housing and Urban Development, Office of Policy 
Development and Research, August 2001.
---------------------------------------------------------------------------

5. Future Prospects

    The outlook for the multifamily rental housing market is marked 
by near-term risks and longer-run optimism, according to most 
observers. The prospects for the next few quarters are dominated by 
the macroeconomy. In particular, job growth, with its implications 
for formations of households, will be a key for the resumption of 
growth in apartment demand. Many forecasters would ascribe to the 
Federal Reserve's forecast of a slight increase in GDP growth to 4.3 
percent in 2004 \249\, while also agreeing with the Fed's warning 
that ``An unusual degree of uncertainty attends the economic outlook 
at present, in large measure, but not exclusively, because of 
potential geopolitical developments.'' \250\
---------------------------------------------------------------------------

    \249\ Federal Reserve, Survey of Professional Forecasters, 
November 2003.
    \250\ Board of Governors of the Federal Reserve System, Monetary 
Policy Report to the Congress, February 11, 2003, page 4.
---------------------------------------------------------------------------

    When consumer demand does pick up, recovery should be reasonably 
fast. While the recent production levels have outpaced demand, they 
have been near the middle of the long run historical range and very 
close to the average of the last half of the 1990s. Judging from the 
firm tone to rents and vacancies during that period, total 
multifamily completions production of 275,000 to 350,000 units is a 
sustainable level of annual production--that is, the level 
consistent with long run demographic trends and replacement of units 
lost from the stock.
    Because new construction has remained moderate, there is no 
massive overhang of product that will need to be absorbed. With 
increased demand, vacancies should fall and rents firm reasonably 
promptly. A key assumption behind this forecast for vacancies and 
rents is that new apartment construction will not rise appreciably 
from its current level.
    Recovery in the apartment market may also, perversely, be 
promoted by the recent unprecedented strength of the single-family 
market. Typically, economic recoveries bring strong growth in 
single-family housing demand, some of that coming from apartment 
renters seeking more space. With single-family activity already near 
record highs, boosted by historically low mortgage interests rates 
and despite the recently soft economy, it is uncertain how much 
higher single-family demand--and the accompanying losses of 
apartment customers to homeownership--can go.
    A stronger economy will put the multifamily rental market back 
onto a long-run path that appears to promise sustained, moderate 
growth. As discussed in the 2000 Rule, the demographic outlook is 
favorable for apartment demand. Even if the homeownership rate 
increases further and the total number of renter households grows 
only slowly, as described in the discussion of the single-family 
housing market earlier in this Rule, apartment demand can be 
expected to increase more rapidly than that for other rental 
housing, owing to the likely changes in age composition and 
reductions in average household size. One estimate projects the 
annual growth in apartment households to be one percent.\251\
---------------------------------------------------------------------------

    \251\ Jack Goodman, ``The Changing Demography of Multifamily 
Rental Housing,'' Housing Policy Debate, Winter 1999.
---------------------------------------------------------------------------

a. The Outlook for Multifamily Housing Supply

    Regarding supply, one of the secrets of the success of the 
multifamily sector during the 1990s was that production never rose 
above its long-run sustainable level. The discipline of developers, 
investors, and their lenders that brought that result needs to be 
continued if the apartment market is to maintain stability.
    Multifamily housing may benefit in the future from more 
favorable public attitudes and local land use regulation. Higher 
density housing is a potentially powerful tool for preserving open 
space, reducing sprawl, and promoting transportation alternatives to 
the automobile. The recently heightened attention to these issues 
may increase the acceptance of multifamily rental construction to 
both potential customers and their prospective neighbors.
    Provision of affordable housing will continue to challenge 
suppliers of multifamily rental housing and policy makers at all 
levels of governments. Low incomes combined with high housing costs 
define a difficult situation for millions of renter households. 
Housing cost reductions are constrained by high land prices and 
construction costs in many markets. Government action--through land 
use regulation, building codes, and occupancy standards--are major 
contributors to those high costs, as is widely recognized by market 
participants, including the leaders of the GSEs.\252\ Reflecting the 
preferences of the electorate, these regulated constraints are 
unlikely to change until voter attitudes change.
---------------------------------------------------------------------------

    \252\ Remarks by Franklin D. Raines, Chairman and CEO, Fannie 
Mae, to the Executive Committee of the National Association of Home 
Builders, January 18, 2003. See also Edward Glaeser and Joseph 
Gyourko, ``The Impact of Zoning on Housing Affordability,'' Working 
Paper 8835, National Bureau of Economic Research, March 2002.
---------------------------------------------------------------------------

b. The Future Role of the GSEs

    Regarding the mortgage financing of multifamily rental 
apartments, it is hard to anticipate events that might disrupt the 
flow or alter the sources of mortgage credit to apartments. In the 
past, certain events have triggered such changes--notably the 
savings and loan debacle of the 1980s and Freddie Mac's withdrawal 
from the market following large losses in the early 1990s--but these 
are, by definition, surprises. The current structure and performance 
of the multifamily mortgage market provide some comfort that the 
risks are slight. The lender base is not overly dependent on any one 
institution or lender type for either loan originations or funding. 
Lending discipline appears to have been maintained, given the low 
mortgage delinquency rates even during the weak economy of the past 
two years. The near term outlook of most market participants is for 
ample supply of mortgage financing at historically low interest 
rates.\253\ Yet complacency would be a mistake.
---------------------------------------------------------------------------

    \253\ ``Capital Markets Outlook 2003,'' Apartment Finance Today, 
Vol. 7, No. 1 (January/February 2003).
---------------------------------------------------------------------------

    Responding to both market incentives and their public charters, 
Fannie Mae and Freddie Mac can be expected to build on their recent 
records of increased multifamily lending and continue to be leaders 
in financing volumes, in program innovations, and in standards 
setting. Certainly there is room for expansion of the GSEs' share of 
the multifamily mortgage market, which, as mentioned earlier, is by 
the measure of dollar volume outstanding currently only about half 
the market share enjoyed by the GSEs in single-family lending. And 
from the perspective of units financed, the statistics from Table 
A.5 combined with data from the 2001 American Housing Survey 
indicate that, while the GSEs financed 7.2 percent of all the 
nation's year-round housing units that year, the percentage of 
multifamily rental units (that is renter-occupied units and vacant 
rental units in structures with at least five units) was only 5.7 
percent.
    The sharp gains since 2000 in small property lending by Fannie 
Mae and Freddie Mac demonstrate that it is feasible for this 
important segment of the affordable housing market to be served by 
the GSEs. Building on the expertise and market contacts gained in 
the past three years, the GSEs should be able to make even greater 
in-roads in small property lending, although the challenges noted 
earlier will continue.
    The GSEs' size and market position between loan originators and 
mortgage investors makes them the logical institutions to identify 
and promote needed innovations and to establish standards that will 
improve market efficiency. As their presence in the multifamily 
market continues to grow, the GSEs will have both the knowledge and 
the ``clout'' to push simultaneously for market standardization and 
for programmatic flexibility to meet special needs and 
circumstances, with the ultimate goal of increasing the availability 
and reducing the

[[Page 63683]]

cost of financing for affordable and other multifamily rental 
properties.

E. Factor 3: Performance and Effort of the GSEs Toward Achieving 
the Low- and Moderate-Income Housing Goal in Previous Years

    This section first discusses each GSE's performance under the 
Low- and Moderate-Income Housing Goal over the 1996-2003 
period.\254\ The data presented are ``official results--i.e., they 
are based on HUD's analysis of the loan-level data submitted to the 
Department by the GSEs and the counting provisions contained in 
HUD's regulations in 24 CFR part 81, subpart B. As explained below, 
in some cases these ``official results'' differ from goal 
performance reported by the GSEs in the Annual Housing Activities 
Reports (AHARs) that they submit to the Department.
---------------------------------------------------------------------------

    \254\ Performance for the 1993-95 period was discussed in the 
October 2000 rule.
---------------------------------------------------------------------------

    The main finding of this section concerning the overall housing 
goals is that both Fannie Mae and Freddie Mac surpassed the 
Department's Low- and Moderate-Income Housing Goals for each of the 
eight years during this period. Specifically:
     The goal was set at 40 percent for 1996; Fannie Mae's 
performance was 45.6 percent and Freddie Mac's performance was 41.1 
percent.
     The goal was set at 42 percent for 1997-2000. Fannie 
Mae's performance was 45.7 percent in 1997, 44.1 percent in 1998, 
45.9 percent in 1999, and 49.5 percent in 2000; and Freddie Mac's 
performance was 42.6 percent in 1997, 42.9 percent in 1998, 46.1 
percent in 1999, and 49.9 percent in 2000.
     In the October 2000 rule, the low- and moderate-income 
goal was set at 50 percent for 2001-03. As of January 1, 2001, 
several changes in counting provisions took effect for the low- and 
moderate-income goal, as follows: ``bonus points'' (double credit) 
for purchases of goal-qualifying mortgages on small (5-50 unit) 
multifamily properties and, above a threshold level, mortgages on 2-
4 unit owner-occupied properties; a ``temporary adjustment factor'' 
(1.20 units credit, subsequently increased by Congress to 1.35 units 
credit) for Freddie Mac's purchases of goal-qualifying mortgages on 
large (more than 50 units) multifamily properties; changes in the 
treatment of missing data; a procedure for the use of imputed or 
proxy rents for determining goal credit for multifamily mortgages; 
and eligibility of purchases of certain qualifying government-backed 
loans to receive goal credit. These changes are explained below. 
Fannie Mae's low-mod goal performance was 51.5 percent in 2001, 51.8 
percent in 2002, and 52.3 percent in 2003; Freddie Mac's performance 
was 53.2 percent in 2001, 50.5 percent in 2002, and 51.2 percent in 
2003, thus both GSEs surpassed this higher goal in all three years. 
This section discusses the October 2000 counting rule changes in 
detail below, and provides data on what goal performance would have 
been in 2001-03 without these changes.\255\
---------------------------------------------------------------------------

    \255\ To separate out the effects of changes in counting rules 
that took effect in 2001, this section also compares performance in 
2001 to estimated performance in 2000 if the 2001 counting rules had 
been in effect in that year.
---------------------------------------------------------------------------

    After the discussion of the overall housing goals in Sections 
E.1 to E.5, Sections E.6 to E.12 examine the role of the GSEs in 
funding home purchase loans for lower-income borrowers and for 
first-time homebuyers. A summary of the main findings from that 
analysis is given in Section E.6. Section E.13 then summarizes some 
recent studies on the GSEs' market role and section E.14 discusses 
the GSEs' role in the financing of single-family rental properties.

1. Performance on the Low- and Moderate-Income Housing Goal in 1996-
2003

    HUD's December 1995 rule specified that in 1996 at least 40 
percent of the number of units financed by each of the GSEs that 
were eligible to count toward the Low- and Moderate-Income Goal 
should qualify as low-or moderate-income, and at least 42 percent of 
such units should qualify in 1997-2000. HUD's October 2000 rule made 
various changes in the goal counting rules, as discussed below, and 
increased the Low- and Moderate-Income Goal to 50 percent for 2001-
03.
    Table A.8 shows low-mod goal performance over the 1996-2003 
period, based on HUD's analysis. The table shows that Fannie Mae 
surpassed the goals by 5.6 percentage points and 3.7 percentage 
points in 1996 and 1997, respectively, while Freddie Mac surpassed 
the goals by narrower margins, 1.1 and 0.6 percentage points. During 
the heavy refinance year of 1998, Fannie Mae's performance fell by 
1.6 percentage points, while Freddie Mac's performance rose 
slightly, by 0.3 percentage point. Freddie Mac showed a gain in 
performance to 46.1 percent in 1999, exceeding its previous high by 
3.2 percentage points. Fannie Mae's performance in 1999 was 45.9 
percent, which, for the first time, slightly lagged Freddie Mac's 
performance in that year.
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    Both GSEs exhibited sharp gains in goal performance in 2000--
Fannie Mae's performance increased by 3.6 percentage points, to a 
record level of 49.5 percent, while Freddie Mac's performance 
increased even more, by 3.8 percent percentage points, which also 
led to a record level of 49.9 percent. Fannie Mae's performance was 
51.5 percent in 2001, 51.8 percent in 2002, and 52.3 percent in 
2003; Freddie Mac's performance was 53.2 percent in 2001, 50.5 
percent in 2002, and 51.2 percent in 2003. However, as discussed 
below, using consistent accounting rules for 2000-03, each GSE's 
performance in 2001-03 was below its performance in 2000.
    The official figures for low-mod goal performance presented 
above differ from the corresponding figures presented by Fannie Mae 
and Freddie Mac in their Annual Housing Activity Reports to HUD by 
0.2-0.3 percentage point in both 1996 and 1997, reflecting minor 
differences in the application of counting rules. These differences 
also persisted for Freddie Mac for 1998-2000, but the goal 
percentages shown above for Fannie Mae for these three years are the 
same as the results reported by Fannie Mae to the Department. Fannie 
Mae reported its performance in 2001 as 51.6 percent and Freddie Mac 
reported its performance as 53.6 percent--both were slightly above 
the corresponding official figures of 51.5 percent and 53.4 percent, 
respectively. For 2002, Fannie Mae's reported performance was the 
same as reported by HUD (51.8 percent), while Freddie Mac's reported 
performance was 51.3 percent, slightly above HUD's official figure 
of 50.5 percent. For 2003, Fannie Mae's reported performance on this 
goal was 51.8 percent, somewhat below HUD's official figure of 52.3 
percent, while Freddie Mac's reported performance (51.1 percent) was 
essentially the same as HUD's official figure of 51.2 percent.
    Fannie Mae's performance on the Low- and Moderate-Income Goal 
was in the range between 44 percent and 46 percent between 1996 and 
1999, but jumped sharply in just one year, from 45.9 percent in 1999 
to 49.5 percent in 2000. Freddie Mac's performance was in the range 
between 41 percent and 43 percent between 1996 and 1998, and then 
rose to 46.1 percent in 1999 and 49.9 percent in 2000. As discussed 
above, official performance rose for both GSEs in 2001-02, but this 
was due to one-time changes in the counting rules--abstracting from 
counting rule changes, performance fell for both GSEs.
    Fannie Mae's performance on the Low- and Moderate-Income Goal 
surpassed Freddie Mac's in every year through 1998. This pattern was 
reversed in 1999, as Freddie Mac surpassed Fannie Mae in goal 
performance for the first time, though by only 0.2 percentage point. 
This improved relative performance of Freddie Mac was due to its 
increased purchases of multifamily loans, as it re-entered that 
market, and to increases in the goal-qualifying shares of its 
single-family mortgage purchases. Freddie Mac's performance also 
slightly exceeded Fannie Mae's performance in 2000, 49.9 percent to 
49.5 percent. Freddie Mac's official performance also exceeded 
Fannie Mae's official performance in 2001, but this reflected a 
difference in the counting rules applicable to the two GSEs that was 
enacted by Congress; if the same counting rules were applied to both 
GSEs (that is, Freddie Mac did not receive the 1.35 Temporary 
Adjustment Factor), Fannie Mae's performance would have exceeded 
Freddie Mac's performance, by 51.5 percent to 50.5 percent.
    In 2002, Freddie Mac's performance on the low mod-goal (50.5 
percent) fell short of Fannie Mae's performance (51.8 percent), even 
though Freddie Mac had the advantage of the Temporary Adjustment 
Factor. The gap would have been wider without this factor, and in 
fact Freddie Mac's performance would have been short of the goal, at 
49.2 percent. This same pattern prevailed in 2003, when Freddie 
Mac's performance on this goal (51.2 percent) was significantly 
below Fannie Mae's performance (52.3 percent), even though Fannie 
Mae did not have the advantage of the Temporary Adjustment Factor. 
The gap in performance between the GSEs would have been much wider 
without this factor, as Freddie Mac's performance would again have 
fallen short of the goal, at 48.4 percent.

2. Changes in the Goal Counting Rules for 2001-03

    A number of changes in the counting rules underlying the 
calculation of low- and moderate-income goal performance took effect 
beginning in 2001, as follows:
     Bonus points for multifamily and single-family rental 
properties. During the 2001-03 period the Department awarded ``bonus 
points'' (double credit in the numerator) for goal-qualifying units 
in small (5-50 unit) multifamily properties and, above a threshold, 
2-4 unit owner-occupied properties whose loans were purchased by the 
GSEs. By letters dated December 24, 2003, the Department notified 
the GSEs that these bonus points would not be in effect after 
December 31, 2003.
     Freddie Mac's Temporary Adjustment Factor. As part of 
the Consolidated Appropriations Act of 2000, Congress required the 
Department to award 1.35 units of credit for each unit financed in 
``large'' multifamily properties (i.e., those with 51 or more units) 
in the numerator in calculating performance on the housing goals for 
Freddie Mac for 2001-03.\256\ This ``temporary adjustment factor'' 
(TAF) did not apply to goal performance for Fannie Mae during this 
period. By letters dated December 24, 2003, the Department notified 
Freddie Mac that this factor would not be in effect after December 
31, 2003.
---------------------------------------------------------------------------

    \256\ See Congressional Record, December 15, 2000, pp. H12295-
96.
---------------------------------------------------------------------------

     Missing data for single-family properties. In the past, 
if a GSE lacked data on rent for rental units or on borrower income 
for owner-occupied units in single-family properties whose mortgages 
it purchased, such units were included in the denominator, but not 
in the numerator, in calculating goal performance. Since some of 
these units likely would have qualified for one or more of the 
housing goals, this rule lowered goal performance. Under the new 
counting rules for the low- and moderate-income goal and the special 
affordable goal that took effect in 2001, the GSEs are allowed to 
exclude loans with missing borrower income from the denominator if 
the property is located in a below-median income census tract. This 
exclusion is subject to a ceiling of 1 percent of total owner-
occupied units financed. The enterprises are also allowed to exclude 
single-family rental units with missing rental information from the 
denominator in calculating performance for these two goals; there is 
no ceiling or restriction to properties located in below-median 
income census tracts for this exclusion of single-family rental 
units. No single-family loans can be excluded from the denominator 
in calculating performance on the underserved areas goal--that is, 
if a GSE does not have sufficient information to determine whether 
or not a property is located in an underserved area, all units in 
such a property are included in the denominator, but not in the 
numerator, in calculating performance on this goal.
     Missing data and proxy rents for multifamily 
properties. In the past, if a GSE lacked data on rent for rental 
units in multifamily properties whose mortgages it purchased, such 
units were included in the denominator, but not in the numerator, in 
calculating goal performance. Since some of these units likely would 
have qualified for one or more of the housing goals, this rule 
lowered goal performance. Under the new counting rules that took 
effect in 2001, if rent is missing for multifamily units, a GSE may 
estimate ``proxy rents,'' and, up to a ceiling of 5 percent of total 
multifamily units financed, may apply these proxy rents in 
determining whether such units qualify for the low- and moderate 
income goal and special affordable goal. If such proxy rents cannot 
be estimated, these multifamily units are excluded from the 
denominator in calculating performance under these goals. No 
multifamily loans can be excluded from the denominator in 
calculating performance on the underserved areas goal--that is, if a 
GSE does not have sufficient information to determine whether or not 
a property is located in an underserved area, all units in such a 
property are included in the denominator, but not in the numerator, 
in calculating performance on this goal.
     Purchases of certain government-backed loans. Prior to 
2001, purchases of government-backed loans were not taken into 
account in determining performance on the GSEs' low- and moderate-
income and underserved area housing goals. That is, all such loans 
were excluded from both the numerator and the denominator in 
calculating goal performance on these two goals, and in accordance 
with Section 1333(b)(1)(A) of the Federal Housing Enterprises 
Financial Safety and Soundness Act of 1992, purchases of only 
certain government-backed loans were included in determining 
performance on the GSEs' special affordable goals. In October 2000 
the Department took steps to encourage the enterprises to play more 
of a role in the secondary market for several types of government-
backed loans where it appeared that greater GSE involvement could 
increase the liquidity of such mortgages. Home equity

[[Page 63686]]

conversion mortgages (HECMs) were developed in the late-1980s by the 
Federal Housing Administration (FHA); these mortgages allow senior 
citizens to draw on the equity in their homes to obtain monthly 
payments to supplement their incomes. Thus purchases of FHA-insured 
HECMs now count toward the low- and moderate-income housing goals if 
the mortgagor's income is less than median income for the area. 
Similarly, purchases of mortgages on properties on tribal lands 
insured under FHA's Section 248 program or HUD's Section 184 program 
may qualify for the GSEs' housing goals. And purchases of mortgages 
under the Rural Housing Service's Single Family Housing Guaranteed 
Loan Program may also count toward all of the housing goals.\257\
---------------------------------------------------------------------------

    \257\ Prior to the October 2000 rule, purchases of these 
government-backed mortgages were only eligible for credit under the 
special affordable goal.
---------------------------------------------------------------------------

3. Effects of Changes in the Counting Rules on Goal Performance in 
2001-03

    Because of the changes in the low- and moderate-income goal 
counting rules that took effect in 2001, direct comparisons between 
official goal performance in 2000 and 2001-03 are somewhat of an 
``apples-to-oranges comparison.'' For this reason, the Department 
has calculated what performance would have been in 2000 under the 
2001-03 rules; this may be compared with official performance in 
2001-03--an ``apples-to-apples comparison.'' HUD has also calculated 
what performance would have been in 2001-03 under the 1996-2000 
rules; this may be compared with official performance in 2000--an 
``oranges-to-oranges comparison.'' These comparisons are presented 
in Table A.9.
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    Specifically, Table A.9 shows performance under the low- and 
moderate-income goal in three ways. Baseline A represents 
performance under the counting rules in effect in 1996-2000. 
Baseline B incorporates the technical changes in counting rules--
changes in the treatment of missing data (including use of proxy 
rents), and eligibility for the goals of certain government-backed 
loans. Baseline C incorporates in addition to the technical changes 
the bonus points and, for Freddie Mac, the temporary adjustment 
factor. Baseline B corresponds to the counting approach proposed in 
this rule to take effect in 2005. Boldface figures under Baseline A 
for 1999-2000 and under Baseline C for 2001-03 indicate official 
goal performance, based on the counting rules in effect in those 
years--e.g., for Fannie Mae, 45.9 percent in 1999, 49.5 percent in 
2000, 51.5 percent in 2001, 51.8 percent in 2002, and 52.3 percent 
in 2003.
     Performance on the Low- and Moderate-Income Goal under 
1996-2000 Counting Rules Plus Technical Changes. If the ``Baseline 
B'' counting approach had been in effect in 2000-03 and the GSEs' 
had purchased the same mortgages that they actually did purchase in 
those years, both Fannie Mae and Freddie Mac would have surpassed 
the low- and moderate-income goal in 2000 and fallen short in 2001, 
2002, and 2003. Specifically, Fannie Mae's performance would have 
been 51.3 percent in 2000, 49.2 percent in 2001, 49.0 percent in 
2002, and 48.7 percent in 2003. Freddie Mac's performance would have 
been 50.6 percent in 2000, 47.7 percent in 2001, 46.1 percent in 
2002, and 45.0 percent in 2003.
     Performance on the Low- and Moderate-Income Goal under 
2001-2003 Counting Rules. If the 2001-03 counting rules had also 
been in effect in 2000 and the GSEs' had purchased the same 
mortgages that they actually did purchase in those years (i.e., 
abstracting from any behavioral effects of ``bonus points,'' for 
example), both GSEs would have substantially surpassed the low- and 
moderate-income goal in all four years, but both GSEs' performance 
figures would have deteriorated somewhat from 2000 to 2001, and, for 
Freddie Mac, from 2001 to 2002 and 2003. Specifically, Fannie Mae's 
``Baseline C'' performance would have been 52.5 percent in 2000, 
51.5 percent in 2001, 51.8 percent in 2002, and 52.3 percent in 
2003. Freddie Mac's performance would have been 55.1 percent in 
2000, surpassing its official performance level of 53.2 percent in 
2001, 50.5 percent in 2002, and 51.2 percent in 2003. Measured on 
this consistent basis, then, Fannie Mae's performance fell by 1.0 
percentage point in 2001, and Freddie Mac's by 1.9 percentage points 
in 2001 and an additional 2.0 percentage points in 2002-03. These 
reductions were primarily due to 2001-03 being years of heavy 
refinance activity.
    Details of Effects of Changes in Counting Rules on Goal 
Performance in 2001-03. As discussed above, counting rule changes 
that took effect in 2001 had significant positive impacts on the 
performance of both GSEs on the low- and moderate-income goal in 
that year--3.8 percentage points for Fannie Mae, and 6.0 percentage 
points for Freddie Mac. This section breaks down the effects of 
these changes on goal performance for both GSEs; results are shown 
in Table A.9.
     Freddie Mac. The largest impact of the counting rule 
changes on Freddie Mac's goal performance was due to the application 
of the temporary adjustment factor for purchases of mortgages on 
large multifamily properties, as enacted by Congress; this added 2.7 
percentage points to goal performance in 2001, as shown in Table 
A.9. Bonus points for purchases of mortgages on small multifamily 
properties added 1.5 percentage points to performance, and bonus 
points for purchase of mortgages on owner-occupied 2-4 unit rental 
properties added 1.4 percentage points to performance. The remaining 
impact (0.5 percentage point) was due to technical changes in 
counting rules--primarily, the exclusion of single-family units with 
missing information from the denominator in calculating goal 
performance. Credit for purchases of qualifying government-backed 
loans played a minor role in determining Freddie Mac's goal 
performance. These same patterns also appeared in 2002. But in 2003, 
bonus points for purchases of low-mod mortgages on single-family 
rental properties had a larger impact on Freddie Mae's low-mod goal 
performance than Freddie Mac's temporary adjustment factor.
     Fannie Mae. The temporary adjustment factor applies to 
Freddie Mac's goal performance, but not to Fannie Mae's performance, 
thus counting rule changes had less impact on its performance than 
on Freddie Mac's performance in 2001. The largest impact of the 
counting rule changes on Fannie Mae's goal performance was due to 
the application of bonus points for purchases of mortgages on owner-
occupied 2-4 unit rental properties, which added 1.6 percentage 
points to performance, and for purchases of mortgages on small 
multifamily properties, which added 0.7 percentage point to 
performance. The remaining impact (1.3 percentage points) was due to 
technical changes--primarily, the exclusion of single-family units 
with missing information from the denominator in calculating goal 
performance.\258\ Credit for purchases of qualifying government-
backed loans and the use of proxy rent for multifamily properties 
played a minor role in determining Fannie Mae's goal performance. 
These same patterns also appeared in 2002 for Fannie Mae, but for 
2003 bonus points for purchases of low-mod mortgages on small 
multifamily properties had more impact on performance than bonus 
points for single-family rental properties.
---------------------------------------------------------------------------

    \258\ Exclusion of loans with missing information had a greater 
impact on Fannie Mae's goal performance than on Freddie Mac's goal 
performance.
---------------------------------------------------------------------------

4. Bonus Points for the Low- and Moderate-Income Goal

    As discussed above, the Department established ``bonus points'' 
to encourage the GSEs to step up their activity in 2001-03 in two 
segments of the mortgage market--the small (5-50 unit) multifamily 
mortgage market, and the market for mortgages on 2-4 unit properties 
where 1 unit is owner-occupied and 1-3 units are occupied by 
renters. Bonus points did not apply to purchases of mortgages for 
owner-occupied 1-unit properties, for investor-owned 1-4 unit 
properties, and for large (more than 50 units) multifamily 
properties, although as also discussed above, a ``temporary 
adjustment factor'' applied to Freddie Mac's purchases of qualifying 
mortgages on large multifamily properties.
    Bonus points for small multifamily properties. Each unit 
financed in a small multifamily property that qualified for any of 
the housing goals was counted as two units in the numerator (and one 
unit in the denominator) in calculating goal performance for that 
goal. For example, if a GSE financed a mortgage on a 40-unit 
property in which 10 of the units qualified for the low- and 
moderate-income goal, 20 units would be entered in the numerator and 
40 units in the denominator for this property in calculating goal 
performance.
    Small multifamily bonus points thus encouraged the GSEs to play 
a larger role in this market, and also to purchase mortgages on such 
properties in which large shares of the units qualified for the 
housing goals. Some evidence may be gleaned from the data provided 
to HUD by the GSEs for 2001-03.
    Fannie Mae financed 37,403 units in small multifamily properties 
in 2001 that were eligible for the low- and moderate-income goal, 
58,277 such units in 2002, and 214,619 such units in 2003, as 
compared with only 7,196 such units financed in 2000. Small 
multifamily properties also accounted for a greater share of Fannie 
Mae's multifamily business in 2001-03--7.4 percent of total 
multifamily units financed in 2001, 13.2 percent in 2002, and 28.6 
percent in 2003, up from 2.5 percent in 2000. However, HUD's 2000 
rule reported information from the 1991 Residential Finance Survey 
that small multifamily properties accounted for 37 percent of all 
multifamily units, thus Fannie Mae was still less active in this 
market than in the market for large multifamily properties.\259\
---------------------------------------------------------------------------

    \259\ Federal Register, October 31, 2000, Footnote 145, p. 
65141.
---------------------------------------------------------------------------

    Within the small multifamily market, there was no evidence that 
Fannie Mae targeted affordable properties to a greater extent in 
2001-03 than in 2000. That is, 87 percent of Fannie Mae's small 
multifamily units qualified for the low- and moderate-income goal in 
2000; this fell to 75 percent in 2001, rose to 89 percent in 2002, 
and then declined to 82 percent in 2003.
    Freddie Mac financed 50,299 units in small multifamily 
properties in 2001 that were eligible for the low- and moderate-
income goal, 22,255 such units in 2002, and 177,561 such units in 
2003, as compared with only such units financed in 2000. Small 
multifamily properties also accounted for a significantly greater 
share of Freddie Mac's multifamily business in 2001-2003--16.1 
percent of total multifamily units financed in 2001, 7.5 percent in 
2002, and 25.4 percent in 2003, up from 1.8 percent in 2000.
    Within the small multifamily market, there was some evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001-2002 than in 2000. That is, 87 percent

[[Page 63689]]

of Freddie Mac's small multifamily units qualified for the low- and 
moderate-income goal in 2000; this rose to 96 percent in 2001, but 
declined back to 87 percent in 2002 and 2003.
    In summary, then, there is strong evidence that bonus points for 
small multifamily properties had an impact on Fannie Mae's role in 
this market in 2001-2003 and an even larger impact on Freddie Mac's 
role in this market. In addition, Fannie Mae has announced a program 
to increase its role in this market further in future years.\260\
---------------------------------------------------------------------------

    \260\ ``Fannie Courting Multifamily Sellers; Small Banks 
Balking,'' American Banker, January 13, 2003, p. 1.
---------------------------------------------------------------------------

    Bonus points for single-family rental properties. Above a 
threshold, each unit financed in a 2-4 unit property with at least 
one owner-occupied unit (referred to as ``OO24s'' below) that 
qualified for any of the housing goals was counted as two units in 
the numerator (and one unit in the denominator) in calculating goal 
performance for that goal in 2001-2003. The threshold was equal to 
60 percent of the average number of such qualifying units over the 
previous five years. For example, Fannie Mae financed an average of 
50,030 low- and moderate-income units in these types of properties 
between 1996 and 2000, and 101,423 such units in 2001. Thus Fannie 
Mae received 71,405 bonus points in this area in 2001--that is, 
101,423 minus 60 percent of 50,030. So 172,828 units were entered in 
the numerator for these properties in calculating low- and moderate-
income goal performance.
    Single-family rental bonus points thus encouraged the GSEs to 
play a larger role in this market, and also to purchase mortgages on 
such properties in which large shares of the units qualified for the 
housing goals. As for small multifamily bonus points, again some 
evidence may be gleaned from the data provided to HUD by the GSEs 
for 2001-03.
    Fannie Mae financed 175,103 units in OO24s in 2001 that were 
eligible for the low- and moderate-income goal, 229,632 such units 
in 2002, and 355,994 such units in 2003, well above the 77,930 units 
financed in 2000. However, with the refinance boom, Fannie Mae's 
total single-family business increased at approximately the same 
rate as its OO24 business in 2001-03, thus the share of its business 
accounted for by OO24s was the same in 2001-03 as in 2000--4 
percent.
    Within the OO24 market, there was no evidence that Fannie Mae 
targeted affordable properties to a greater extent in 2001-03 than 
in 2000. That is, approximately 55-60 percent of Fannie Mae's OO24 
units qualified for the low- and moderate-income goal in each of 
these three years.
    Freddie Mac financed 96,050 units in OO24s in 2001 that were 
eligible for the low- and moderate-income goal, 146,222 such units 
in 2002, and 154,535 such units in 2003, as compared with the 49,993 
units financed in 2000. However, Freddie Mac's total single-family 
business increased at approximately the same rate as its OO24 
business in 2001-02, thus the share of its business accounted for by 
OO24s was the same in 2002 as in 2000--4 percent. And its total 
single-family business increased at a faster rate than its OO24 
business in 2003, thus the share of its business accounted for by 
OO24s declined to 3 percent last year.
    As for Fannie Mae, within the OO24 market there was no evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001-03 than in 2000. That is, 68-69 percent of Fannie Mae's OO24 
units qualified for the low- and moderate-income goal in each year 
from 2000 through 2002; this decreased to 64 percent in 2003.

5. Effects of 2000 Census on Scoring of Loans Toward the Low- and 
Moderate-Income Housing Goal

    Background. Scoring of housing units under the Low- and 
Moderate-Income Housing Goal is based on data for mortgagors' 
incomes for owner-occupied units, rents for rental units, and area 
median incomes, as follows:
    For single-family owner-occupied units:
    The mortgagors' income at the time of mortgage origination.
    The median income of an area specified as follows: (i) For 
properties located in Metropolitan Statistical Areas (MSAs), the 
area is the MSA; and (ii) for properties located outside of MSAs, 
the area is the county or the non-metropolitan portion of the State 
in which the property is located, whichever has the larger median 
income, as of the year of mortgage origination (which may be for the 
current year or a prior year).
    For rental units in single-family properties with rent data are 
available (assuming no income data available for actual or 
prospective tenants):
    The unit rent (or average rent for units of the same type) at 
the time of mortgage origination.
    The area median income as specified for single-family owner-
occupied units.
    For rental units in multifamily properties where rent data are 
available:
    The unit rent (or the average rent for units of the same type) 
at the time of mortgage acquisition by the GSE.
    The area median income as specified for single-family owner-
occupied units, but as of the year the GSE acquired the mortgage.
    For rental units in multifamily properties where rent data are 
not available, the GSE may apply HUD-estimated rents which are based 
on the following area data:
    The median rent in the census tract where the property is 
located, as of the most recent decennial census.
    The area median income as specified for single-family owner-
occupied units, but as of the most recent decennial census.
    Thus, scoring loans under the Low- and Moderate-Income Goal 
requires a data series showing annual median incomes for MSAs, non-
metropolitan counties, and the non-metropolitan portions of states; 
and decennial census data on median incomes for census tracts.\261\
---------------------------------------------------------------------------

    \261\ In New England, MSAs were defined through mid-2003 in 
terms of Towns rather than Counties, and the portion of a New 
England county outside of any MSA was regarded as equivalent to a 
county in establishing the metropolitan or non-metropolitan location 
of a property. The MSA definitions established by the Office of 
Management and Budget (OMB) in June, 2003 defined MSAs in New 
England in terms of counties.
---------------------------------------------------------------------------

    For scoring loans purchased by the GSEs year-by-year from 1993 
through 2002, area median income estimates produced by HUD's 
Economic and Market Analysis Division were used. An example will 
illustrate the estimation procedure. To generate the area median 
income estimates that were used to score GSE loans in 2002, data 
from the 1990 census on 1989 area median incomes were adjusted to 
2002 using Bureau of Labor Statistics survey data on rates of cha 
nge in average incomes for MSAs and counties between 1989 and 1999, 
data from the Census Bureau's Current Population Survey on rates of 
change in median family incomes for the nine Census Divisions 
between 1989 and 2000, and an assumed 4.0 percent per year inflation 
factor between 2000 and 2002.\262\ \263\
---------------------------------------------------------------------------

    \262\ The procedure is explained in detail in annual releases 
entitled ``HUD Methodology for Estimating FY [year] Median Family 
Incomes'' for years 1993 through 2002, issued by the Economic and 
Market Analysis Division, Office of Economic Affairs, PD&R, U.S. 
Department of Housing and Urban Development.
    \263\ The procedure applicable to the decennial census data used 
to generate estimated rents is explained in connection with data 
used to define Underserved Areas in Appendix B.
---------------------------------------------------------------------------

    2005 Procedure. Relative to the above procedure, scoring of 
loans purchased by the GSEs in and after 2005 will be affected by 
two factors. First, the Economic and Market Analysis Division has 
begun to incorporate data from the 2000 census into its procedure 
for estimating annual area median incomes and American Community 
Survey data are becoming available at increasingly finer levels of 
geographical detail for use in annual updating. Beginning in 2005 
Bureau of Labor Statistics data on rates of inflation in average 
wages will not be used. For 2005, the procedure for estimating area 
median incomes will be to adjust 2000 census data on 1999 area 
median incomes to 2003 using data from the Census Bureau's American 
Community Survey (ACS) on rates of change in average incomes for 
States between 1999 and 2003, with a further adjustment to 2005 
based on an appropriate annual inflation factor.\264\ Increasingly 
more detailed ACS data will be available and will be used in 
subsequent years, as ACS estimates for metropolitan and micropolitan 
areas and counties become available.
---------------------------------------------------------------------------

    \264\ Transition from the 2002 methodology to the 2005 
methodology is occurring in stages in 2003 and 2004. To generate the 
area median income estimates used to score GSE loans in 2003, data 
from the 2000 census on 1999 area median incomes were adjusted to 
2001 using Bureau of Labor Statistics survey data on rates of change 
in average incomes for MSAs and counties between 1999 and 2000, data 
on rates of change in median incomes for the United States and 
individual States between 1999 and 2001 from Census Bureau's Current 
Population Survey and American Communities Survey, and an assumed 
3.5 percent per year inflation factor between 2001 and 2003. (See 
``HUD Methodology for Estimating FY 2003 Median Family Incomes,'' 
issued by the Economic and Market Analysis Division, op cit.) A 
similar procedure has been used to generate area median income 
estimates for scoring GSE loans in 2004.
---------------------------------------------------------------------------

    The second factor is the Office of Management and Budget's June, 
2003, re-

[[Page 63690]]

specification of MSA boundaries based on analysis of 2000 census 
data.\265\
---------------------------------------------------------------------------

    \265\ HUD has deferred application of the 2003 MSA specification 
to 2005, pending completion of the present rulemaking process.
---------------------------------------------------------------------------

    Analysis. For purposes of specifying the level of the Low- and 
Moderate-Income Housing Goal, HUD developed a methodology for 
scoring loans purchased by the GSEs in past years through 2002 as 
though the re-benchmarking of area median income estimates to the 
2000 census and the 2003 re-designation of MSAs had been in effect 
and HUD had been using an ACS-based estimation procedure at the time 
the estimates for these years were prepared. For this purpose, HUD 
created a series of annual estimates of median incomes for MSAs, 
non-metropolitan counties, and the non-metropolitan portions of 
states. For 2000, the estimates were 1999 census medians trended by 
three-fourths of the 4.0 percent annual trending factor (to adjust 
the figures from mid-1999 to April 1, 2000). For 2001, the estimates 
were based on one-and-three-fourths years of trending, since no data 
would have been available to use for updating. The 2002 estimates 
would have used one year of data and 1.75 years of trending. The 
2003 estimates would have used two years of data plus 1.75 years of 
trending. Area median incomes from 1989 to 1999 were estimated based 
on trend-lines between 1989 and 1999 census data. The 2003 OMB MSA 
designations were applied.
    The resulting estimates of area median incomes for MSAs, non-
metropolitan counties, and the non-metropolitan parts of States, 
were used to re-score loans purchased by the GSEs between 1999 and 
2002, and were used further in estimating the share of loans 
originated in metropolitan areas that would be eligible to score 
toward the Low- and Moderate-Income Housing Goal, from HMDA data. 
The results of the retrospective GSE analysis are provided in Table 
A.10. The results of the GSE-HMDA comparative analysis are presented 
in the next section.
    Table A.10 shows three sets of estimates for each GSE, based 
respectively on the counting rules in place in 2001-2002 (but 
disregarding the bonus points and Temporary Adjustment Factor), on 
the addition of 2000 census re-benchmarking, and finally on the 
addition of both 2000 census re-benchmarking and 2003 MSA 
specification. Re-benchmarking occurred to adjust for some 
differences between Census 1990 and Census 2000 tracts.
BILLING CODE 4210-27-P

[[Page 63691]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.019

BILLING CODE 4210-27-C

[[Page 63692]]

6. GSEs Compared With the Primary Conventional Conforming Mortgage 
Market

    This section and the next five sections (Sections E.7 to E.12) 
provide a detailed analysis of the extent to which the GSEs' loan 
purchases mirror or depart from the patterns found in the primary 
mortgage market. As in Section C.5, the GSEs' affordable lending 
performance is also compared with the performance of depository 
lenders such as commercial banks and thrift institutions. Dimensions 
of lending considered include the three ``goals-qualifying'' 
categories--special affordable borrowers, less-than-median income 
borrowers, and underserved areas. The special affordable category 
consists mainly of very-low-income borrowers, or borrowers who have 
an annual income less than 60 percent of area median income. Because 
this category is more targeted than the broadly-defined less-than-
median-income (or low-mod) category, the discussion below will often 
focus on the special affordable category as well as the underserved 
areas category which adds a neighborhood dimension (low-income and 
high-minority census tracts) to the analysis. This section will also 
compare the performance of Fannie Mae and Freddie Mac in funding 
first-time homebuyers with that of primary lenders in the 
conventional conforming market.
    The remainder of this introductory section E.6 provides a list 
of the major and specific findings which are presented in detail in 
the following Sections E.7 through 12. Sections 7 and 8 define the 
primary mortgage market and discuss some technical issues related to 
the use of the GSE and HMDA data. Sections 8 and 9 compare the GSEs' 
performance with market performance for home purchase and first-time 
homebuyer loans, while Section 10 does the same for total single 
family loans (that is, refinance loans and home purchase loans). 
Section 11 examines GSE purchases in individual metropolitan areas. 
Following these analyses, Section 12 examines the overall market 
share of the GSEs in important submarkets such as first-time 
homebuyers.

a. Main Findings on GSEs' Performance in the Single-family Market

    There are six main findings from this analysis concerning the 
GSEs' purchases of single-family-owner mortgages:
    1. While Freddie Mac has improved its affordable lending 
performance in recent years, it has consistently lagged the 
conventional conforming market in funding affordable home purchase 
loans for special affordable and low-moderate-income borrowers and 
underserved neighborhoods targeted by the housing goals.\266\ In 
2003, its performance on the underserved areas goal was particularly 
low relative to both the performances of Fannie Mae and the market; 
in that year, underserved area loans accounted for only 24.0 percent 
of Freddie Mac's purchases compared with 26.8 percent of Fannie 
Mae's purchases and 27.6 percent of market originations.
---------------------------------------------------------------------------

    \266\ The ``affordable lending performance'' of Fannie Mae and 
Freddie Mac refers to the performance of the GSEs in funding loans 
for low-income and underserved borrowers through their purchase (or 
guarantee) of loans originated by primary lenders. It does not, of 
course, imply that the GSEs themselves are lenders originating loans 
in the primary market.
---------------------------------------------------------------------------

    2. In general, Fannie Mae's affordable lending performance has 
been better than Freddie Mac's. But like Freddie Mac, Fannie Mae's 
average performance during past periods (e.g., 1993-2003, 1996-2003, 
1999-2003) has been below market levels. However, it is encouraging 
that Fannie Mae markedly improved its affordable lending performance 
relative to the market during 2001, 2002, and 2003, the first three 
years under the higher housing goal targets that HUD established in 
the GSE Final Rule dated October 2000.
    Over this three-year period, Fannie Mae led the primary market 
in funding special affordable and low-mod loans but lagged the 
market in funding underserved areas loans. In 2003, Fannie Mae's 
increased performance placed it significantly above the special 
affordable market (a 17.1 percent share for Fannie Mae compared with 
a 15.9 percent share for the market) and the low-mod market (a 47.0 
percent share for Fannie Mae compared with a 44.6 percent share for 
the market). However, Fannie Mae continued to lag the underserved 
areas market in 2003 (a 26.8 percent share for Fannie Mae compared 
with a 27.6 percent share for the market). In this case, which is 
referred to in the text as the ``purchase year'' approach, Fannie 
Mae's performance is based on comparing its purchases of all loans 
(both seasoned loans and newly-originated mortgages) during a 
particular year with loans originated in the market in that year. 
When Fannie Mae's performance is measured on an ``origination year'' 
basis (that is, allocating Fannie Mae's purchases in a particular 
year to the year that the purchased loan was originated), Fannie Mae 
also led the 2003 market in funding special affordable and low- and 
moderate-income loans, and lagged the market in funding underserved 
area loans.
    3. Both Fannie Mae and Freddie lag the conventional conforming 
market in funding first-time homebuyers, and by a rather wide 
margin. Between 1999 and 2001, first-time homebuyers accounted for 
27 percent of each GSE's purchases of home loans, compared with 38 
percent for home loans originated in the conventional conforming 
market.
    4. The GSEs have accounted for a significant share of the total 
(government as well as conventional) market for home purchase loans, 
but their market share for each of the affordable lending categories 
(e.g., low-income borrowers and census tracts) has been less than 
their share of the overall market.
    5. The GSEs also account for a very small share of the market 
for important groups such as minority first-time homebuyers. 
Considering the total mortgage market (both government and 
conventional loans), it is estimated that the GSEs purchased only 14 
percent of loans originated between 1999 and 2001 for African-
American and Hispanic first-time homebuyers, or less than half of 
their share (42 percent) of all home purchase loans originated 
during that period. Considering the conventional conforming market 
and the same time period, it is estimated that the GSEs purchased 
only 31 percent of loans originated for African-American and 
Hispanic first-time homebuyers, or about one-half of their share (57 
percent) of all home purchase loans in that market.
    6. The GSEs' small share of the first-time homebuyer market 
could be due to the preponderance of high (over 20 percent) 
downpayment loans in their mortgage purchases.

b. Specific Findings on GSE Performance in the Single-family Market

    This section presents 17 specific findings from the analyses 
reported in Sections E.7 through 12; they are grouped under the 
following five topic-headings:
    (b.1) Longer-term Performance of the GSEs;
    (b.2) Performance of the GSEs During Recent Years;
    (b.3) The GSEs' Funding First-time Homebuyer Loans;
    (b.4) Performance of the GSEs Based on Total (Home Purchase and 
Refinance) Loans;
    (b.5) GSE Market Shares; and,
    (b.6) Additional Findings.

(b.1) Longer-Term Performance of the GSEs

    The longer-run performance of the GSEs is examined between 1993 
and 2003 (which covers the period since the housing goals were put 
into effect) and between 1996 and 2003 (which covers the period 
under the current definitions of the housing goals). Of the two 
borrower-income goals, the analysis below will typically focus on 
the special affordable category, which is a more targeted category 
than the rather broadly defined low- and moderate-income category.
    (1) Since the early nineties, the mortgage industry has 
introduced new affordable lending programs and has allowed greater 
flexibility in underwriting lower-income loans. There is evidence 
that these programs are paying off in terms of more mortgages for 
low-income and minority borrowers. As noted earlier, Fannie Mae and 
Freddie Mac have played an active role in this upsurge of affordable 
lending, as indicated by the high growth rates of their goals-
qualifying business.
     Between 1993 and 2003, the GSEs' purchases of home 
loans in metropolitan areas increased by 60 percent.\267\ Their 
purchases of home loans for the three housing goals increased at 
much higher rates--287 percent for special affordable loans, 156 
percent for low- and moderate-income loans, and 121 percent for 
loans in underserved census tracts.
---------------------------------------------------------------------------

    \267\ Throughout this analysis, the terms ``home loan'' and 
``home mortgage'' will refer to a ``home purchase loan,'' as opposed 
to a ``refinance loan.'' As noted earlier, the mortgage data 
reported in this paper are for metropolitan areas, unless stated 
otherwise. Restricting the GSE data to metropolitan areas is 
necessary to make it comparable with the HMDA-reported conventional 
primary market data, which is more reliable for metropolitan areas. 
The analysis of first-time homebuyers in Sections E.9 and E.12 cover 
both metropolitan and non-metropolitan areas.
---------------------------------------------------------------------------

    (2) Both Fannie Mae and Freddie Mac have improved their 
purchases of affordable loans since the housing goals were put in 
place, as indicated by the increasing share of their business going 
to the three goals-qualifying categories. (See Table A.15 in Section 
E.9.)

[[Page 63693]]

     Between 1992 and 2003, the special affordable share of 
Fannie Mae's business almost tripled, rising from 6.3 percent to 
17.1 percent, while the underserved areas share increased more 
modestly, from 18.3 percent to 26.8 percent. The figures for Freddie 
Mac are similar. The special affordable share of Freddie Mac's 
business rose from 6.5 percent to 15.6 percent, while the 
underserved areas share also increased but more modestly, from 18.6 
percent to 24.0 percent.
    (3) While both GSEs improved their performance, they have lagged 
the primary market in providing affordable loans to low-income 
borrowers and underserved neighborhoods. Freddie Mac's average 
performance, in particular, fell far short of market performance 
during the 1990s. Fannie Mae's average performance was better than 
Freddie Mac's during the 1993-2003 period as well as during the 
1996-2003 period, which covers the period under HUD's currently-
defined housing goals.
     Between 1993 and 2003, 12.2 percent of Freddie Mac's 
mortgage purchases were for special affordable borrowers, compared 
with 13.3 percent of Fannie Mae's purchases, 15.4 percent of loans 
originated by depositories, and 15.5 percent of loans originated in 
the conventional conforming market (without estimated B&C 
loans).\268\
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    \268\ Unless otherwise noted, the conventional conforming market 
data reported in this section exclude an estimate of B&C loans; the 
less-risky A-minus portion of the subprime market is included in the 
market definition. See Section E.7 and Appendix D for a discussion 
of primary market definitions and the uncertainty surrounding 
estimates of the number of B&C loans in HMDA data. As noted there, 
B&C loans are much more likely to be refinance loans rather than 
home purchase loans.
---------------------------------------------------------------------------

     Considering the underserved areas category for the 
1996-2003 period, 22.0 percent of Freddie Mac's purchases financed 
properties in underserved neighborhoods, compared with 24.0 percent 
of Fannie Mae's purchases, 25.1 percent of loans originated by 
depositories, and 25.7 percent of loans originated in the 
conventional conforming market.

(b.2) Performance of the GSEs During Recent Years

    The recent performance of the GSEs is examined for the four-year 
period between 1999 and 2003 and then for 2001, 2002 and 2003, which 
were the first three years that the GSEs operated under the higher 
goal targets established by HUD in the 2000 Rule. As explained 
below, the most interesting recent trend concerned Fannie Mae, which 
improved its performance during 2001-2003, at a time when the 
conventional conforming market was showing little change in 
affordable lending.
    (4) During the recent 1999-to-2003 period, both Fannie Mae and 
Freddie Mac fell significantly below the market in funding 
affordable loans.
     Between 1999 and 2003, special affordable loans 
accounted for 15.1 percent of Fannie Mae's purchases, 14.7 percent 
of Freddie Mac's purchases, and 16.2 percent of loans originated in 
the market; thus, the ``Fannie-Mae-to-market'' ratio was 0.93 and 
the ``Freddie-Mac-to-market'' ratio was also 0.91.
     During the same period, underserved area loans 
accounted for 24.7 percent of Fannie Mae's purchases, 23.1 percent 
of Freddie Mac's purchases, and 26.2 percent of loans originated in 
the market; the ``Fannie-Mae-to-market'' ratio was 0.94 and the 
``Freddie-Mac-to-market'' ratio was only 0.88.\269\
---------------------------------------------------------------------------

    \269\ Fannie Mae had a particularly poor year during 1999. 
Therefore, the text also reports averages for 2000-2003, dropping 
the year 1999 (see Table A.13 in Section E.9).
---------------------------------------------------------------------------

    (5) After experiencing declines from 1997 to 1999, Fannie Mae's 
affordable lending performance improved between 2000 and 2003.
     After declining from 23.0 percent in 1997 to 20.4 
percent in 1999, the share of Fannie Mae's purchases financing 
properties in underserved areas jumped by three percentage points to 
23.4 percent in 2000, and then increased further to 26.7 percent in 
2002 and 26.8 percent in 2003.
     After declining from 13.2 percent in 1998 to 12.5 
percent in 1999, the share of Fannie Mae's purchases going to 
special affordable loans rebounded to 13.3 percent in 2000, 14.9 
percent in 2001, 16.3 percent in 2002 and 17.1 percent in 2003.
    (6) Freddie Mac's performance on the two borrower-income 
categories improved between 2000 and 2002, but not as much as Fannie 
Mae's performance. Freddie Mac's performance on the underserved 
areas category increased substantially between 2001 and 2002, but 
then declined between 2002 and 2003.
     The share of Freddie Mac's single-family-owner business 
going to special affordable home loans increased from 9.2 in 1997 to 
14.7 percent in 2000 before falling to 14.4 percent in 2001 and 
rising to 15.8 percent in 2002 and 15.6 percent in 2003.
     Freddie Mac's purchases of underserved area loans 
increased at a modest rate from 19.7 percent in 1997 to 22.3 percent 
in 2001, before jumping to 25.8 percent in 2002 and then dropping to 
24.0 percent in 2003.
    (7) The long-standing pattern of Fannie Mae outperforming 
Freddie Mac was reversed during 1999 and 2000. But that pattern 
returned in 2001-2003 when Fannie Mae outperformed Freddie Mac on 
all three goals-qualifying categories.
     Fannie Mae and Freddie Mac had practically the same 
performance in 1992 on the three housing goal categories--special 
affordable loans accounted for 6.3 percent of Fannie Mae's purchases 
and 6.5 percent of Freddie Mac's purchases, for a ``Fannie-Mae-to-
Freddie-Mac'' ratio of 0.97. The 1992 ratio for underserved areas 
was also 0.98 and that for low-mod, 1.02. Reflecting Fannie Mae's 
much better performance, the special affordable ``Fannie-Mae-to-
Freddie-Mac'' ratio had risen to 1.27 by 1997, the underserved area 
ratio to 1.17, and the low-mod ratio to 1.10.
     However, in 1999, the ``Fannie-Mae-to-Freddie-Mac'' 
ratio for each of the three goals-qualifying categories fell to 
slightly below one. 1999 was the first year since 1992 that Freddie 
Mac had outperformed Fannie Mae in purchasing affordable home loans 
(although only by a very slight margin).
     In 2000, Freddie Mac's sharper increases in special 
affordable and low-mod purchases further reduced the ``Fannie-Mae-
to-Freddie-Mac'' ratios for these two categories to 0.90 and 0.96, 
respectively. Fannie Mae's sharper increase in underserved areas 
funding resulted in the ``Fannie-Mae-to-Freddie-Mac'' ratio rising 
from slightly below one (0.98) in 1999 to 1.06 in 2000.
     Fannie Mae's stronger performance during 2001-2003 
returned the ``Fannie-Mae-to-Freddie-Mac'' ratios for special 
affordable and low-mod loans to above one (1.10 and 1.09 
respectively), indicating better performance for Fannie Mae in 2003. 
The ``Fannie-Mae-to-Freddie-Mac'' ratio for the underserved area 
category increased to 1.12 by 2003.
    (8) While Freddie Mac has consistently improved its performance 
relative to the market, it continued to lag the market in funding 
affordable home loans during 2001-2003.
     Unlike Fannie Mae, Freddie Mac had not made any 
progress through 1997 in closing its gap with the market. The 
``Freddie Mac-to-market'' ratio for the special affordable category 
actually declined from 0.63 in 1992 to 0.59 in 1996. But Freddie 
Mac's sharp improvement in special affordable purchases resulted in 
the ``Freddie-Mac-to-market'' ratio rising to 0.89 by 2000. After 
declining from 0.84 in 1992 to 0.79 in 1997, the ``Freddie-Mac-to-
market'' ratio for underserved areas had risen only modestly to 0.84 
by the year 2000. Thus, Freddie Mac's improvements prior to 2001 
allowed it to close its gap with the market, mainly for the special 
affordable category where its gap had been the widest.
     During 2001, 2002 and 2003, Freddie Mac continued to 
close its gap with the market on the special affordable and low-mod 
categories. By 2003, these ``Freddie-Mac-to-market'' ratios were 
higher than in 2000, although they both continued to fall below one: 
at 0.98 for both categories. Between 2002 and 2003, Freddie Mac's 
market ratio for underserved areas fell from 0.98 to 0.87 (24.0 
percent for Freddie Mac and 27.6 percent for Fannie Mae). Thus, 
during 2003, Freddie Mac lagged the market on all three goals-
qualifying categories.
    (9) Through 1998, Fannie Mae had significantly improved its 
performance relative to the market. But as a result of shifts in its 
purchases of affordable loans, Fannie Mae lagged the market even 
further in 2000 than it had in some earlier years. During 2001-2003, 
Fannie Mae again improved its performance relative to the market 
and, in 2003, Fannie Mae led the special affordable and low-mod 
markets but lagged the underserved areas market.
     The above analysis and the data reported under this 
specific finding (9) are based on the ``purchase year'' approach for 
measuring GSE activity. The purchase year approach assigns GSE 
purchases of both prior-year (seasoned) and newly-originated 
mortgages to the calendar year in which they were purchased by the 
GSE; this results in an inconsistency with the HMDA-reported market 
data, which covers only newly-originated mortgages. Sections E.9 and 
E.10

[[Page 63694]]

also report the results of an alternative ``origination year'' 
approach that assigns GSE purchases to their year of origination, 
placing them on a more consistent basis with the HMDA-reported 
market data. The findings from the origination-year approach are 
discussed under specific finding (10).
     Fannie Mae's decline in performance during 1999 
resulted in the ``Fannie-Mae-to-market'' ratio falling sharply to 
0.74 for special affordable, to 0.81 for underserved areas and to 
0.89 for low-mod. In 2000, Fannie Mae improved and reversed its 
declining trend, as the ``Fannie-Mae-to-market'' ratios increased to 
0.80 for special affordable purchases, to 0.89 for underserved area 
purchases, and to 0.93 for low-mod purchases.
     During 2001, Fannie Mae increased its special 
affordable percentage by 1.6 percentage points to 14.9 percent, 
which was only 0.7 percentage point below the market's performance 
of 15.6 percent. Fannie Mae increased its low-mod percentage from 
40.8 percent to 42.9 percent at the same time that the low-mod share 
of the primary market was falling from 43.9 percent to 42.9 percent, 
placing Fannie Mae at the market's performance. Similarly, Fannie 
Mae increased its underserved area percentage from 23.4 percent in 
2000 to 24.4 percent in 2001 while the underserved area share of the 
primary market was falling from 26.2 percent to 25.2 percent, 
placing Fannie Mae at 0.8 percentage point from the market's 
performance.
     During 2002, Fannie Mae continued to improve its 
performance on all three goals categories. Using the purchase-year 
approach to measure GSE performance, Fannie Mae slightly led the 
market on the special affordable category (16.3 percent for Fannie 
Mae and 16.1 percent for the market), led the market on the low-mod 
category (45.3 percent for Fannie Mae compared with 44.6 percent for 
the market), and led the market on the underserved area category 
(26.7 percent for Fannie Mae versus 26.3 percent for the market).
     During 2003, Fannie Mae's further improvement resulted 
in Fannie Mae leading the special affordable market (17.1 percent 
for Fannie Mae compared with 15.9 percent for the market) and 
continuing to lead the low-mod market (47.0 percent for Fannie Mae 
compared with 44.6 percent for the market). During 2003, Fannie Mae 
lagged behind the underserved areas market (26.8 percent for Fannie 
Mae compared with 27.6 percent for the market).
    (10) This analysis addresses several technical issues involved 
in measuring GSE performance. The above analysis was based on the 
``purchase year'' approach, as defined in (9) above. An alternative 
``origination year'' approach has also been utilized, which assigns 
GSE purchases to their year of origination, placing them on a more 
consistent basis with the HMDA-reported market data. While the 
average results (e.g., 1999-2003 GSE performance) are similar under 
the two reporting approaches, GSE performance in any particular year 
can be affected, depending on the extent to which the GSE has 
purchased goals-qualifying seasoned loans in that particular year.
     The choice of which approach to follow particularly 
affected conclusions about Fannie Mae's performance relative to the 
market in 2002 (but not in 2001). Under the origination-year 
approach, Fannie Mae lagged the market on all three housing goal 
categories during 2001 and on the underserved area category during 
2002. In 2002, Fannie Mae matched the market on the special 
affordable category and led the market on the low-mod category (45.5 
percent for Fannie Mae compared with 44.6 percent of the market).
     During 2003, the origination year approach gives the 
similar results as the purchase year approach--Fannie Mae led the 
special affordable and low-mod markets and lagged the underserved 
areas market.

(b.3) The GSEs' Funding of First-time Homebuyer Loans

    (11) The GSEs' funding of first-time homebuyers has been 
compared to that of primary lenders in the conventional conforming 
market. Both Fannie Mae and Freddie lag the market in funding first-
time homebuyers, and by a rather wide margin.
     First-time homebuyers account for 27 percent of each 
GSE's purchases of home loans, compared with 38 percent for home 
loans originated in the conventional conforming market.

(b.4) Performance of the GSEs Based on Total (Home Purchase and 
Refinance) Loans

    (12) The GSEs' acquisitions of total loans (including refinance 
loans as well as home purchase loans) were also examined. The main 
results indicate (a) Freddie Mac has improved its performance but 
has consistently lagged the market in funding loans (home purchase 
and refinance) that qualify for the housing goals; and (b) Fannie 
Mae has not only improved its performance but matched the low-mod 
market in 2001 and 2002 and led both the special affordable and low-
mod markets in 2003. Fannie Mae, however, lagged the primary market 
in funding underserved areas during 2003. (See Table A.20 of Section 
E.10, which is based on the purchase-year approach for measuring GSE 
activity.)
     1999-2003. During the recent 1999-to-2003 period, both 
Fannie Mae and Freddie Mac fell significantly below the market in 
funding affordable total (home purchase and refinance) loans. 
Between 1999 and 2003, special affordable loans accounted for 14.0 
percent of Fannie Mae's purchases, 13.2 percent of Freddie Mac's 
purchases, and 15.6 percent of loans originated in the market; thus, 
the ``Fannie-Mae-to-market'' ratio was 0.93 and the ``Freddie-Mac-
to-market'' ratio was 0.88 during this period.
     During the same period, underserved area loans 
accounted for 23.8 percent of Fannie Mae's purchases, 22.1 percent 
of Freddie Mac's purchases, and 25.2 percent of loans originated in 
the market; thus, the ``Fannie-Mae-to-market'' ratio was 0.94 and 
the ``Freddie-Mac-to-market'' ratio was 0.88.\270\
---------------------------------------------------------------------------

    \270\ As explained in Section E.9, deducting B&C loans from the 
market totals has more impact on the market percentages for total 
(both home purchase and refinance) loans than for only home purchase 
loans. The effects of excluding B&C loans from the total market can 
be seen by comparing the third and sixth columns of data in Table 
A.19 in Section E.10.
---------------------------------------------------------------------------

     2002 and 2003. During 2002, the first of these two 
years of heavy refinancing, Fannie Mae's performance was slightly 
above the market on the low-mod category and slightly below market 
performance on the special affordable and underserved areas 
categories; essentially, Fannie Mae matched the market on all three 
categories in 2002. In 2003, Fannie Mae led the market on the 
special affordable and low-mod categories and lagged the market on 
the underserved areas category. The 2003 ``Fannie-Mae-to-market'' 
ratios were 1.02 for special affordable loans, 1.03 for low-mod 
loans, and 0.97 for underserved area loans. In 2003, the ``Freddie-
Mac-to-market'' ratios were much lower: 0.86 for special affordable 
loans, 0.90 for low-mod loans, and 0.82 for underserved area loans.

(b.5) GSE Market Shares

    This analysis includes an expanded ``market share'' analysis 
that documents the GSEs'' contribution to important segments of the 
home purchase and first-time homebuyer markets.
    (13) The GSEs account for a significant share of the total 
(government as well as conventional conforming) market for home 
purchase loans. However, the GSEs' market share for each of the 
affordable lending categories is much less than their share of the 
overall market.
     The GSEs' purchases were estimated to be 46 percent of 
all home loans originated in metropolitan areas between 1999 and 
2003 but only 30 percent of loans originated for African-American 
and Hispanic borrowers, 38 percent of loans originated for low-
income borrowers, and 37 percent for properties in underserved 
areas. The GSEs' market share for the various affordable lending 
categories increased during 2001-2003, but the above-mentioned 
pattern remained.
     A study by staff from the Federal Reserve Board 
suggests that the GSEs have a much more limited role in the 
affordable lending market than is suggested by the data presented 
above.\271\ The Fed study, which combined market share, downpayment, 
and default data, concluded that the GSEs play a very minimal role 
in providing credit support and assuming credit risk for low-income 
and minority borrowers; for example, the study concluded that in 
1995 the GSEs provided only four percent of the credit support going 
to African-Americans and Hispanic borrowers.
---------------------------------------------------------------------------

    \271\ See Glenn B. Canner, Wayne Passmore, and Brian J. Surette, 
``Distribution of Credit Risk Among Providers of Mortgages to Lower-
Income and Minority Homebuyers' in Federal Reserve Bulletin, 82(12): 
1077-1102, December, 1996.
---------------------------------------------------------------------------

     Section V of this study begins to reconcile these 
different results by examining the role of the GSEs in the first-
time homebuyer market and the downpayment characteristics of 
mortgages purchased by the GSEs.
    (14) The market role of the GSEs appears to be particularly low 
in important market segments such as minority first-time homebuyers.

[[Page 63695]]

     Recent analysis has estimated that the GSEs' share of 
the market for first-time African-American and Hispanic homebuyers 
was only 14.3 percent between 1999 and 2001, or about one-third of 
their share (41.5 percent) of all home purchases during that period. 
This analysis includes the total market, including government and 
conventional loans.
     A similar market share analysis was conducted for the 
conventional conforming market. Between 1999 and 2001, the GSEs' 
purchases accounted for 56.6 percent of all home loans originated in 
the conventional conforming market of both metropolitan areas and 
non-metropolitan areas. Their purchases of first-time homebuyer 
loans, on the other hand, accounted for only 39.8 percent of all 
first-time homebuyer loans originated in that market.
     The GSEs have funded an even lower share of the 
minority first-time homebuyer market in the conventional conforming 
market. Between 1999 and 2001, the GSEs purchases of African-
American and Hispanic first-time homebuyer loans represented 30.9 
percent of the conventional conforming market for these loans. Thus, 
while the GSEs have accounted for 56.6 percent of all home loans in 
the conventional conforming market, they have accounted for only 
30.9 percent of loans originated in that market for African-American 
and Hispanic first-time homebuyers.
    (15) A noticeable pattern among the lower-income-borrower loans 
purchased by the GSEs is the predominance of loans with high 
downpayments. This pattern of purchasing mainly high downpayment 
loans is one factor explaining why the Fed study found such a small 
market role for the GSEs. It may be the explanation for the small 
role of Fannie Mae and Freddie Mac in the first-time homebuyer 
market. Further study of this issue is needed.
     During 2001 and 2002, approximately 50 percent of 
Fannie Mae's special affordable, low-mod, and underserved areas 
loans had downpayments of at least 20 percent, a percentage only 
slightly smaller that the corresponding percentage (53 percent) for 
all Fannie Mae's home loan purchases. Similar patterns of above-20-
percent downpayments on goals-qualifying loans were evident in 
Freddie Mac's 2001, 2002, and 2003 purchases, as well as in prior 
years for both GSEs. During 2003, Fannie Mae's high downpayment 
share of their special affordable purchases dropped to 45 percent 
while the patterns for Fannie Mae's low-mod and underserved area 
purchases did not change, remaining about 50 percent.

(b.6) Additional Findings

    This analysis examines two additional topics related to minority 
first-time homebuyers and the use of HMDA data for measuring the 
characteristics of loans originated in the conventional conforming 
market.
    (16) The share of the GSEs' purchases for minority first-time 
homebuyers was much less than the share of newly-originated 
mortgages in the conventional conforming market for those 
homebuyers.
     Between 1999 and 2001, minority first-time homebuyers 
accounted for 6.6 percent of Fannie Mae's purchases of home loans, 
5.8 percent of Freddie Mac's purchases, and 10.6 percent of home 
loans originated in the conventional conforming market. For this 
subgroup, Fannie Mae's performance is 62 percent of market 
performance, while Freddie Mac's performance is 55 percent of market 
performance.
    (17) Some studies have concluded that HMDA data overstate the 
share of market loans going to low-income borrowers and underserved 
areas. This analysis does not support that conclusion.
     This compares the low-income and underserved areas 
characteristics of the GSEs' purchases of newly-originated 
(``current-year'') loans as reported both by the GSEs'' own data and 
by HMDA data.\272\ For recent years, HMDA data on loans sold to the 
GSEs do not always have higher percentages of low-income and 
underserved areas loans than the GSEs' own data on their purchases 
of newly-originated mortgages. For example, from 1996-2003, both 
HMDA and Fannie Mae reported that special affordable loans accounted 
for about 13 percent of Fannie Mae's purchases of newly-originated 
loans. HMDA reported a 22.6 underserved areas percentage for Fannie 
Mae, which was rather similar to the underserved areas percentage 
(23.1 percent) reported by Fannie Mae itself. Given that similar 
patterns were observed for Freddie Mac's mortgage purchases, it 
appears that there is no upward bias in the HMDA-based market 
benchmarks used in this study.
---------------------------------------------------------------------------

    \272\ In this comparison, a higher special affordable percentage 
for HMDA-reported mortgage originations that lenders report as also 
being sold to the GSEs--as compared with the special affordable 
percentage for newly-originated mortgages that the GSEs report as 
being actually purchased by them--would suggest that HMDA market 
data are biased; that is, in this situation, the special affordable 
percentage for all mortgage originations reported in HMDA would 
likely be larger than the special affordable percentage for all new 
mortgage originations, including those not reported in HMDA as well 
as those reported in HMDA.
---------------------------------------------------------------------------

7. Definition of Primary Market

    Conventional Conforming Market. The market analysis section is 
based mainly on HMDA data for mortgages originated in the 
conventional conforming market of metropolitan areas during the 
years 1992 to 2003. Only conventional loans with a principal balance 
less than or equal to the conforming loan limit are included; the 
conforming loan limit was $322,700 in 2003--these are called 
``conventional conforming loans.'' The GSEs' purchases of FHA-
insured, VA-guaranteed, and Rural Housing Service loans are excluded 
from this analysis. The conventional conforming market is used as 
the benchmark against which to evaluate the GSEs because that is the 
market definition Congress requires that HUD consider when setting 
the affordable housing goals. However, as discussed in Section II, 
some have questioned whether lenders in the conventional market are 
doing an adequate job meeting the credit needs of minority 
borrowers, which suggests that this market provides a low 
benchmark.\273\
---------------------------------------------------------------------------

    \273\ The market definition in this section is narrower than the 
``Total Market'' data presented earlier in Tables A.1 and A.2, which 
included all home loans below the conforming loan limit, that is, 
government loans as well as conventional conforming loans. The 
market share analysis reported in Section E.12 also examine the 
GSEs' role in the overall market.
---------------------------------------------------------------------------

    Manufactured Housing Loans. Both GSEs have raised questions 
about whether loans on manufactured housing should be excluded when 
comparing the primary market with the GSEs. The GSEs purchase these 
loans, but they have not played a significant role in the 
manufactured housing loan market. As emphasized by HUD in its 2000 
GSE Rule, manufactured housing is an important source of home 
financing for low-income families and for that reason, should be 
included in any analysis of affordable lending. However, for 
comparison purposes, data are also presented for the primary market 
defined without manufactured housing loans. Because this analysis 
focuses on metropolitan areas, it does not include the substantial 
number of manufactured housing loans originated in non-metropolitan 
areas.
    Subprime Loans. Both GSEs also raised questions about whether 
subprime loans should be excluded when comparing the primary market 
with their performance. In its final 2000 GSE Rule, HUD argued that 
borrowers in the A-minus portion of the subprime market could 
benefit from the standardization and lower interest rates that 
typically accompany an active secondary market effort by the GSEs. 
A-minus loans are not nearly as risky as B&C loans and the GSEs have 
already started purchasing A-minus loans (and likely the lower ``B'' 
grade subprime loans as well). The GSEs themselves have mentioned 
that a large portion of borrowers in the subprime market could 
qualify as ``A credit.'' This analysis includes the A-minus portion 
of the subprime market, or conversely, excludes the B&C portion of 
that market.
    Unfortunately, HMDA does not identify subprime loans, much less 
separate them into their A-minus and B&C components.\274\ Randall M. 
Scheessele at HUD has identified approximately 200 HMDA reporters 
that primarily originate subprime loans and account for about 60-70 
percent of the subprime market.\275\ To adjust HMDA data for B&C 
loans, this analysis follows HUD's 2000 Rule which assumed that the 
B&C portion of the subprime market accounted for one-half of the 
loans originated by the subprime lenders included in Scheessele's 
list.\276\ As shown below, the effects of

[[Page 63696]]

adjusting the various market percentages for B&C loans are minor 
mostly because the analysis in this section focuses on home purchase 
loans, which historically have accounted for less than one quarter 
of the mortgages originated by subprime lenders--the subprime market 
is mainly a refinance market.\277\
---------------------------------------------------------------------------

    \274\ And there is some evidence that many subprime loans are 
not even reported to HMDA, although there is nothing conclusive on 
this issue. See Fair Lending/CRA Compass, June 1999, p. 3.
    \275\ The list of subprime lenders as well as Scheessele's list 
of manufactured housing lenders are available at http://www.huduser.org/publications/hsgfin.html.
    \276\ The one-half estimate is conservative as some observers 
estimate that B&C loans account for only 30-40 percent of the 
subprime market. However, varying the B&C share from 50 percent to 
30 percent does not significantly change the following analysis of 
home purchase loans because subprime loans are mainly for refinance 
purposes. Overstating the share of B&C loans in this manner also 
allows for any differences in HMDA reporting of different types of 
loans--for example, if B&C loans account for 35 percent of all 
subprime loans, then assuming that they account for 50 percent is 
equivalent to assuming that B&C loans are reported in HMDA at 70 
percent of the rate of other loans.
    \277\ The reductions in the market shares are more significant 
for total loans, which include refinance as well as home purchase 
loans; for data on total loans, see Table A.19 in Section 10. 
Subprime lenders have been focusing more on home purchase loans 
recently. The home purchase share of loans originated by the 
subprime lenders in Scheessele's list increased from 26 percent in 
1999 to 36 percent in 2000 before dropping to about 30 percent 
during the heavy refinancing years of 2001 and 2002.
---------------------------------------------------------------------------

    Lender-Purchased Loans in HMDA. When analyzing HMDA data, Fannie 
Mae includes in its market totals those HMDA loans identified as 
having been purchased by the reporting lender, above and beyond 
loans that were originated by the reporting lender.\278\ Fannie Mae 
contends that there are a subset of loans originated by brokers and 
subsequently purchased by wholesale lenders that are neither 
reported by the brokers nor the wholesale lenders as originations 
but are reported by the wholesale lenders as purchased loans. 
According to Fannie Mae, these HMDA-reported purchased loans should 
be added to HMDA-reported originated loans to arrive at an estimate 
of total mortgage originations.
---------------------------------------------------------------------------

    \278\ In 2001 (2002), lenders reported in HMDA that they 
purchased 851,735 (906,684) conventional conforming, home purchase 
loans in metropolitan areas; this compares with 2,763,230 
(2,929,197) loans that these same lenders reported that they 
originated in metropolitan areas.
---------------------------------------------------------------------------

    This rule's market definition includes only HMDA-reported 
originations; purchased loans are excluded from the market 
definition. While some purchased loans may not be reported as 
originations in HMDA (the Fannie Mae argument), there are several 
reasons for assuming that most HMDA-reported purchased loans are 
also reported in HMDA as market originations. First, Fed staff have 
told HUD that including purchased loans would result in double 
counting mortgage originations.\279\ Second, comparisons of HMDA-
reported FHA data with data reported by FHA supports the Fed's 
conclusion. For instance, FHA's own data indicate that during 2001 
FHA insured 752,319 home purchase loans in metropolitan areas; the 
sum of HMDA-reported purchased home loans and HMDA-reported 
originated home loans in metropolitan areas alone yields a much 
higher figure of 845,176 FHA-insured loans during 2001.\280\ While 
these calculations are for the FHA market (rather than the 
conventional market), they suggest that including HMDA-reported 
purchased loans in the market definition would overstate mortgage 
origination totals. Third, Abt Associates surveyed nine wholesale 
lenders and questioned them concerning their guidelines for 
reporting in HMDA loans purchased from brokers. Most of these 
lenders said brokered loans were reported as originations if they 
[the wholesale lender] make the credit decision; this policy is 
consistent with the Fed's guidelines for HMDA reporting. Abt 
Associates concluded that ``brokered loans do seem more likely to be 
reported as originations * * *.'' \281\
---------------------------------------------------------------------------

    \279\ See Randall M. Scheessele, HMDA Coverage of the Mortgage 
Market, Housing Finance Working Paper No. HF-007. Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, July, 1998.
    \280\ In this example, HMDA-reported purchased loans insured by 
FHA have been reduced from 411,930 to 100,251 by a procedure that 
accounts for missing data and overlapping purchased and originated 
loans. See Harold L. Bunce, The GSEs' Funding of Affordable Loans: A 
2000 Update, Working Paper HF-013, Office of Policy Development and 
Research, HUD, April 2002, for an alternative analysis showing that 
a market estimate based on adding HMDA-reported purchased loans to 
HMDA-reported originations would substantially overstate the volume 
of FHA mortgage originations in metropolitan areas.
    \281\ See Chapter III, ``Reporting of Brokered and Correspondent 
Loans under HMDA'', in Exploratory Study of the Accuracy of HMDA 
Data, by Abt Associates Inc. under contract for the Office of Policy 
Development and Research, HUD, February 12, 1999, page 18.
---------------------------------------------------------------------------

    Finally, it should be noted that including purchased loans in 
the market definition does not significantly change the goals-
qualifying shares of the market, mostly because borrower income data 
are missing for the majority of purchased loans. In addition, the 
low-income and underserved area shares for purchased and originated 
loans are rather similar. In 2001, the following differences in 
shares for the conventional conforming home purchase market were 
obtained for purchased and originated loans: Low-income (25.8 
percent for purchased loans, 28.3 percent for market originations), 
low-mod income (41.3 percent, 43.2 percent), and underserved areas 
(24.2 percent, 25.8 percent). The comparisons were also similar for 
2002.\282\
---------------------------------------------------------------------------

    \282\ The percentage shares for purchased loans are obtained 
after eliminating purchased loans without data and purchased loans 
that overlap with originated loans. The calculations included 
138,536 purchased loans for 2001 and 182,290 purchased loans for 
2002.
---------------------------------------------------------------------------

8. Technical Issues: Using HMDA Data To Measure the Characteristics of 
GSE Purchases and Mortgage Market Originations \283\
---------------------------------------------------------------------------

    \283\ Readers not interested in these technical issues may want 
to proceed to Section E.9, which compares GSE performance to the 
primary market.
---------------------------------------------------------------------------

    This section discusses important technical issues concerning the 
use of HMDA data for measuring the GSEs' performance relative to the 
characteristics of mortgages originated in the primary market. The 
first issue concerns the reliability of HMDA data for measuring the 
borrower income and census tract characteristics of loans sold to 
the GSEs. Fannie Mae, in particular, has contended that HMDA data 
understates the percentages of its business that qualify for the 
three housing goals. In its comments on the proposed 2000 Rule, 
Fannie Mae questioned HUD's reliance on HMDA data for measuring its 
performance. As discussed below, HMDA data on loans sold to the GSEs 
do not include prior-year (seasoned) loans that are sold to the 
GSEs. Since about one-fourth of GSE purchases in any particular year 
involve loans originated in prior years, HMDA data will not provide 
an accurate measure of the goals-qualifying characteristics of the 
GSEs' total purchases when the characteristics of prior-year loans 
differ from those of newly-originated, current-year loans.
    A related issue concerns the appropriate definition of the GSE 
data when making annual comparisons of GSE performance with the 
market. On the one hand, the GSE annual data can be expressed on a 
purchase-year basis, which means that all GSE purchases in a 
particular year would be assigned to that particular year. 
Alternatively, the GSE annual data can be expressed on an 
origination-year basis, which means that GSE purchases in a 
particular year would be assigned to the calendar year that the GSE-
purchased mortgage was originated; for example, a GSE's purchase 
during 2001 of a loan originated in 1999 would be assigned to 1999, 
the year the loan was originated. These two approaches are discussed 
further below.
    A final technical issue concerns the reliability of HMDA for 
measuring the percentage of goals-qualifying loans in the primary 
market. Both GSEs refer to findings from a study by Jim Berkovec and 
Peter Zorn concerning potential bias in HMDA data.\284\ Based on a 
comparison of the borrower and census tract characteristics between 
Freddie-Mac-purchased loans (from Freddie Mac's own data) and loans 
identified in 1993 HMDA data as sold to Freddie Mac, Berkovec and 
Zorn conclude that HMDA data overstate the percentage of 
conventional conforming loans originated for lower-income borrowers 
and for properties located in underserved census tracts. If HMDA 
data overstate the percentage of goals-qualifying loans, then HUD's 
market benchmarks (which are based on HMDA data) will also be 
overstated. The analysis below does not support the Berkovec and 
Zorn findings--it appears that HMDA data do not overstate the share 
of goals-qualifying loans in the market. The discussion below of the 
GSEs' purchases of prior-year and current-year loans also highlights 
the strategy of purchasing seasoned loans that qualify for the 
housing goals. The implications of this strategy for understanding 
recent shifts in the relative performance of Fannie Mae and Freddie 
Mac are discussed below in Section E.9.
---------------------------------------------------------------------------

    \284\ See Jim Berkovec and Peter Zorn, ``How Complete is HMDA? 
HMDA Coverage of Freddie Mac Purchases,'' The Journal of Real Estate 
Research, Vol. II, No. 1, Nov. 1, 1996.
---------------------------------------------------------------------------

a. GSEs' Purchases of ``Prior-Year'' and ``Current-Year'' Mortgages

    There are two sources of loan-level information about the 
characteristics of mortgages purchased by the GSEs--the GSEs 
themselves and HMDA data. The GSEs provide detailed data on their 
mortgage purchases to HUD on an annual basis. As part of their 
annual HMDA reporting responsibilities, lenders are required to 
indicate whether their new mortgage originations or the loans that 
they purchase (from affiliates and other institutions) are sold to 
Fannie Mae, Freddie Mac or some

[[Page 63697]]

other entity. There have been numerous studies by HUD staff and 
other researchers that use HMDA data to compare the borrower and 
neighborhood characteristics of loans sold to the GSEs with the 
characteristics of all loans originated in the market. One question 
is whether HMDA data, which is widely available to the public, 
provides an accurate measure of GSE performance, as compared with 
the GSEs' own data.\285\ Fannie Mae has argued that HMDA data 
understate its past performance, where performance is defined as the 
percentage of Fannie Mae's mortgage purchases accounted for by one 
of the goal-qualifying categories. As explained below, over the past 
six years, HMDA has provided rather reliable national-level 
information on the goals-qualifying percentages for the GSEs' 
purchases of ``current-year'' (i.e., newly-originated) loans, but 
not for their purchases of ``prior-year'' loans.\286\
---------------------------------------------------------------------------

    \285\ For another discussion of this issue, see Randall M. 
Scheessele, HMDA Coverage of the Mortgage Market, Housing Finance 
Working Paper HF-007, Office of Policy Development and Research, 
Department of Housing and Urban Development, July 1998. Scheessele 
reports that HMDA data covered 81.6 percent of the loans acquired by 
Fannie Mae and Freddie Mac in 1996. The main reason for the under-
reporting of GSE acquisitions is a few large lenders failed to 
report the sale of a significant portion of their loan originations 
to the GSEs. Also see the analysis of HMDA coverage by Jim Berkovec 
and Peter Zorn. ``Measuring the Market: Easier Said than Done,'' 
Secondary Mortgage Markets. McLean VA: Freddie Mac, Winter 1996, pp. 
18-21; as well as the Berkovec and Zorn study cited in the above 
footnote.
    \286\ Between 1993 and 1996, the GSEs' purchases of prior-year 
loans were not as targeted as they were after 1996; thus, during 
this period, HMDA provided reasonable estimates of the goals-
qualifying percentages of the GSEs' purchases of all (both current-
year and prior-year) loans, with a few exceptions (see Table A.11).
---------------------------------------------------------------------------

    In any given calendar year, the GSEs can purchase mortgages 
originated in that calendar year or mortgages originated in a prior 
calendar year. In 2001 and 2002, for example, purchases of prior-
year mortgages accounted for approximately 20 percent of the home 
loans purchased by each GSE.\287\ HMDA data provide information 
mainly on newly-originated mortgages that are sold to the GSEs--that 
is, HMDA data on loans sold to the GSEs will not include many of 
their purchases of prior-year loans. The implications of this for 
measuring GSE performance can be seen in Table A.11, which provides 
annual data on the borrower and census tract characteristics of GSE 
purchases, as measured by HMDA data and by the GSEs' own data. Table 
A.11 divides each of the GSEs' goals-qualifying percentages for a 
particular acquisition year into two components, the percentage for 
``prior-year'' loans and the percentage for ``current-year'' loans.
---------------------------------------------------------------------------

    \287\ The ``prior-year'' share dropped to 16 percent during the 
heavy refinancing year of 2003. During the 1990s, the GSEs increased 
their purchases of seasoned loans; see Paul B. Manchester, Goal 
Performance and Characteristics of Mortgages Purchased by Fannie Mae 
and Freddie Mac, 1998-2000, Housing Finance Working Paper No. HF-
015, Office of Policy Development and Research, HUD, May 2001.
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[[Page 63699]]


    Consider Fannie Mae's special affordable purchases in 2002. 
According to Fannie Mae's own data, 16.3 percent of its purchases 
during 2002 were special affordable loans. According to HMDA data, 
only 15.5 percent of loans sold to Fannie Mae fell into the special 
affordable category. In this case, HMDA data underestimate the 
special affordable share of Fannie Mae's purchases during 2002. What 
explains these different patterns in the GSE and HMDA data? The 
reason that HMDA data underestimate the special affordable 
percentage of Fannie Mae's 2002 purchases can be seen by 
disaggregating Fannie Mae's purchases during 2002 into their prior-
year and current-year components. Table A.11 shows that the overall 
figure of 16.3 percent for special affordable purchases is a 
weighted average of 18.8 percent for Fannie Mae's purchases during 
2002 of prior-year mortgages and 15.8 percent for its purchases of 
current-year purchases. The HMDA-reported figure of 15.5 percent is 
based mainly on newly-mortgaged (current-year) loans that lenders 
reported as being sold to Fannie Mae during 2002. The HMDA figure is 
similar in concept to the current-year percentage from the GSEs' own 
data. And the HMDA figure and the GSE current-year figure are 
practically the same in this case (15.5 versus 15.8 percent). Thus, 
the relatively large share of special affordable mortgages in Fannie 
Mae's purchases of prior-year mortgages explains why Fannie Mae's 
own data show an overall (both prior-year and current-year) 
percentage of special affordable loans that is higher than that 
reported for Fannie Mae in HMDA data.

b. Reliability of HMDA Data

    With the above explanation of the basic differences between GSE-
reported and HMDA-reported loan information, issues related to the 
reliability of HMDA data can now be discussed. Table A.12 presents 
the same information as Table A.11, except that the data are 
aggregated for the years 1993-5, 1996-2003, and 1999-2003. Comparing 
HMDA-reported data on GSE purchases with GSE-reported current-year 
data suggests that, on average, HMDA data have provided reasonable 
estimates of the goals-qualifying percentages for the GSEs' current-
year purchases (with the exception of Freddie Mac's underserved area 
loans, as discussed below). For example, Fannie Mae reported that 
13.7 percent of the current-year loans it purchased between 1996 and 
2003 were for special affordable borrowers. In their HMDA 
submissions, lenders reported a nearly identical figure of 13.4 
percent for the special affordable share of loans that they sold to 
Fannie Mae. The corresponding numbers for Freddie Mac were 12.8 
percent reported by them and 12.1 percent reported by HMDA. During 
the same period, both Fannie Mae and HMDA reported that 
approximately 23 percent of current-year loans purchased by Fannie 
Mae financed properties in underserved areas. However, Freddie Mac 
reported that 21.3 percent of the current-year loans it purchased 
between 1996 and 2003 financed properties in underserved areas, a 
figure somewhat higher than the 19.6 percent that HMDA reported as 
underserved area loans sold to Freddie Mac during that period.\288\
---------------------------------------------------------------------------

    \288\ Freddie Mac's underserved area figures for 2002 and 2003 
showed particularly large discrepancies. As shown in Table A.11, 
Freddie Mac reported that 25.0 (23.4) percent of the current-year 
loans it purchased during 2002 (2003) financed properties in 
underserved areas, a figure much higher than the 21.4 (20.3) percent 
that HMDA reported as underserved area loans sold to Freddie Mac 
during 2002. These discrepancies are the largest in Table A.11, and 
it is not clear what explains them. This downward bias for HMDA 
data, is the opposite of that suggested by Berkovec and Zorn, who 
argued that affordability percentages from HMDA data are biased 
upward.
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[[Page 63701]]

    The facts that the Fannie Mae and HMDA figures for special 
affordable, low-mod and underserved area loans are similar, and that 
the Freddie Mac discrepancies are the result of Freddie Mac 
reporting higher percentages than HMDA, suggest that the Berkovec 
and Zorn conclusions about HMDA being upward biased are wrong.\289\ 
For the 1996-to-2003 period, the discrepancies reported in Table 
A.11 as well as Table A.12 are mostly consistent with HMDA being 
biased in a downward direction, not an upward direction as Berkovec 
and Zorn contend.\290\ In particular, the Freddie-Mac-reported 
underserved area percentage (as well as its special affordable 
percentage) being larger than the HMDA-reported underserved area 
percentage suggests a downward bias in HMDA. The more recent and 
complete (Fannie Mae data as well as Freddie Mac data) analysis does 
not support the Berkovec and Zorn finding that HMDA overstates the 
goals-qualifying percentages of the market.\291\
---------------------------------------------------------------------------

    \289\ The data in Table A.12 that support Berkovec and Zorn are 
the 1993-95 special affordable and low-mod data (particularly for 
Freddie Mac) that show HMDA over reporting percentages by more than 
a half percentage point. Otherwise, the data in Table A.12, as well 
as Table A.11, do not present a picture of HMDA's having an upward 
bias in reporting targeted loans. In fact, the recent years' data 
suggest a downward bias in HMDA's reporting of targeted loans.
    \290\ Of course, on an individual year basis, the GSEs' current-
year data can differ significantly from the HMDA-reported data on 
GSE purchases. The other annual data reported in Table A.11 show a 
mixture of results--in some cases the HMDA percentage is larger than 
the GSE ``current year'' percentage (e.g., Fannie Mae's special 
affordable purchases in 2000) while in other cases the HMDA 
percentage is smaller than the GSE current year percentage (e.g., 
Freddie Mac's special affordable purchases in recent years). As 
noted in the text, the differential is typically in the opposite 
direction to that predicted by Berkovec and Zorn, particularly on 
the underserved areas category.
    \291\ Table A.12 also includes aggregates for the more recent 
period, 1999-2003. The ratios of HMDA-reported-to-GSE-reported 
averages for this sub-period are similar to those reported for 1996-
2003.
---------------------------------------------------------------------------

c. Purchase-Year Versus Origination-Year Reporting of GSE Data

    In comparing the GSEs' performance to the primary market, HUD 
has typically expressed the GSEs' annual performance on a purchase-
year basis. That is, all mortgages (including both current-year 
mortgages and prior-year mortgages) purchased by a GSE in a 
particular year are assigned to the year of GSE purchase. The 
approach of including a GSE's purchases of both ``current-year'' and 
``prior-year'' mortgages gives the GSE full credit for their 
purchase activity in the year that the purchase actually takes 
place; this approach is also consistent with the statutory 
requirement for measuring GSE performance under the housing goals. 
However, this approach results in an obvious ``apples to oranges'' 
problem with respect to the HMDA-based market data, which include 
only newly-originated mortgages (i.e., current-year mortgages). To 
place the GSE and market data on an ``apples to apples'' basis, HUD 
has also used an alternative approach that expresses the GSE annual 
data on an origination-year basis. In this case, all purchases by a 
GSE in any particular year would be fully reported but they would be 
allocated to the year that they were originated, rather than to the 
year they were purchased. Under this approach, a GSE's data for the 
year 2000 would not only include that GSE's purchases during 2000 of 
newly-originated mortgages but also any year-2000-originations 
purchased in later years (i.e., during 2001, 2002 and 2003 in this 
analysis). This approach places the GSE and the market data on a 
consistent, current-year basis. In the above example, the market 
data would present the income and underserved area characteristics 
of mortgages originated in 2000, and the GSE data would present the 
same characteristics of all year-2000-mortgages that the GSE has 
purchased to date (i.e., through year 2003).\292\
---------------------------------------------------------------------------

    \292\ Under the origination-year approach, GSE performance for 
any specific origination year (say year 2000) at the end of a 
particular GSE purchase year (say year 2003) is subject to change in 
the future years. Table A.16 (in Section E.9 below) reports that 
13.7 percent of year-2000 mortgage originations that Fannie Mae 
purchased through year 2002 qualify as special affordable; the 
special affordable share for the market was 16.6 percent in 2000, 
which indicates that, to date, Fannie Mae has lagged the primary 
market in funding special affordable mortgages originated during 
2000. However, Fannie Mae's special affordable performance could 
change in the future as Fannie Mae continues to purchase year-2000 
originations during 2004 and the following years. Of course, whether 
Fannie Mae's future purchases result in it ever leading the 2000-
year market is not known at this time.
---------------------------------------------------------------------------

    Below, results will be presented for both the purchase-year and 
origination-year approaches. Following past HUD studies that have 
compared GSE performance with the primary market, most of the 
analysis in this section reports the GSE data on a purchase-year 
basis; however, the main results are repeated with the GSE data 
reported on an origination-year basis. This allows the reader to 
compare any differences in findings about how well the GSEs have 
been doing relative to the market.

9. Affordable Lending by the GSEs: Home Purchase Loans

    This section compares the GSEs' affordable lending performance 
with the primary market for the years 1993-2003. The analysis in 
this section begins by presenting the GSE data on a purchase-year 
basis. As discussed above, the GSE data that are reported to HUD 
include their purchases of mortgages originated in prior years as 
well as their purchases of mortgages originated during the current 
year. The market data reported by HMDA include only mortgages 
originated in the current year. This means that the GSE-versus-
market comparisons are defined somewhat inconsistently for any 
particular calendar year. Each year, the GSEs have newly-originated 
loans available for purchase, but they can also purchase loans from 
a large stock of seasoned (prior-year) loans currently being held in 
the portfolios of depository lenders. One method for making the 
purchase-year data more consistent is to aggregate the data over 
several years, instead of focusing on annual data. This provides a 
clearer picture of the types of loans that have been originated and 
are available for purchase by the GSEs. This approach is taken in 
Tables A.14 and A.15, which are discussed below. Another method for 
making the GSE and market data consistent is to express the GSE data 
on an origination-year basis; that approach is taken in Table A.16, 
which is discussed after presenting the annual results on a 
purchase-year basis.

a. Longer-Term Performance, 1993-2003 and 1996-2003

    Table A.13 summarizes the funding of goals-qualifying mortgages 
by the GSEs, depositories and the conforming market for the ten-year 
period between 1993 and 2003. Data are also presented for two 
important sub-periods: 1993-95 (for showing how much the GSEs have 
improved their performance since the early-to-mid 1990s); and 1996-
2003 (for analyzing their performance since the current definitions 
of the housing goals were put into effect). Given the importance of 
the GSEs for expanding homeownership, this section focuses on home 
purchase mortgages, and the next section will examine first-time 
homebuyer loans. Section IV below will briefly discuss the GSEs' 
overall performance, including refinance and home purchase loans. 
Several points stand out concerning the affordable lending 
performance of Freddie Mac and Fannie Mae over the two longer-term 
periods, 1993-2003 and 1996-2003.
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[[Page 63703]]

    Freddie Mac lagged both Fannie Mae and the primary market in 
funding affordable home loans in metropolitan areas between 1993 and 
2003. During that period, 12.2 percent of Freddie Mac's mortgage 
purchases were for special affordable (mainly very-low-income) 
borrowers, compared with 13.3 percent of Fannie Mae's purchases, 
15.4 percent of loans originated by depositories,\293\ and 15.5 
percent of loans originated in the conforming market without B&C 
loans.\294\
---------------------------------------------------------------------------

    \293\ As shown in Table A.13, the depository percentage is 
higher (16.8 percent) if the analysis is restricted to those newly-
originated loans that depositories do not sell (the latter being a 
proxy for loans held in depositories' portfolios). Note that during 
the recent, 1999-to-2003 period (also reported in Table A.13), there 
is less difference between the two depository figures.
    \294\ Unless stated otherwise, the market in this section is 
defined as the conventional conforming market without estimated B&C 
loans.
---------------------------------------------------------------------------

    Although Freddie Mac consistently improved its performance 
during the 1990s, a similar pattern characterized the 1996-2003 
period. During that period, 40.3 percent of Freddie Mac's purchases 
were for low- and moderate-income borrowers, compared with 42.2 
percent of Fannie Mae's purchases, 43.1 percent of loans originated 
by depositories, and 43.6 percent of loans originated in the 
conventional conforming market. Over the same period, 22.0 percent 
of Freddie Mac's purchases financed properties in underserved 
neighborhoods, compared with 24.0 percent of Fannie Mae's purchases, 
25.1 percent of depository originations, and 25.7 percent of loans 
originated in the primary market.
    Fannie Mae's affordable lending performance was better than 
Freddie Mac's over the 1993 to 2003 period as well as during the 
1996 to 2003 period. However, Fannie Mae lagged behind depositories 
and the overall market in funding affordable loans during both of 
these periods (see above paragraph). Between 1996 and 2003, the 
``Fannie-Mae-to-market'' ratio was only 0.89 on the special 
affordable category, obtained by dividing Fannie Mae's performance 
of 14.1 percent by the market's performance of 15.9 percent. Fannie 
Mae's market ratio was 0.97 on the low-mod category and 0.93 on the 
underserved area category. The ``Freddie-Mac-to-market'' ratios for 
1996-2003 were lower--0.83 for special affordable, 0.92 for low-mod, 
and 0.86 for underserved areas.
    The above analysis has defined the market to exclude B&C loans, 
which HUD believes is the appropriate market definition. However, to 
gauge the sensitivity of the results to how the market is defined, 
Table A.14 shows the effects on the market percentages for different 
definitions of the conventional conforming market, such as excluding 
manufactured housing loans, small loans, and all subprime loans 
(i.e., the A-minus portion of the subprime market as well as the B&C 
portion). For example, the average special affordable (underserved 
area) market percentage for 1996-2003 would fall by about 1.6 (1.2) 
percentage points if both small loans (less than $15,000) and 
manufactured loans in metropolitan areas were also dropped from the 
market definition (see right-hand-side column in Table A.14). Except 
for Fannie Mae's relative performance on the low-mod category, the 
above findings with respect to the GSEs' longer-term performance are 
not much affected by the choice of market definition.

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b. Recent Performance, 1999-2003

    This and the next subsection focus on the average data for 1999-
2003 in Table A.13 and the annual data reported in Table A.14. As 
explained below, the annual data are useful for showing shifts in 
the relative positions of Fannie Mae and Freddie Mac that began in 
1999, and for highlighting the improvements made by Fannie Mae 
during 2001-2003 (which were the first three years under HUD's 
higher goal levels) and by Freddie Mac during 2002. Between 1993 and 
1998, Freddie Mac's performance fell below Fannie Mae's, but a sharp 
improvement in Freddie Mac's performance during 1999 pushed it pass 
Fannie Mae on all three goals-qualifying categories. In 2000, Fannie 
Mae improved its underserved areas performance enough to surpass 
Freddie Mac on that category, while Freddie Mac continued to out-
perform Fannie Mae on the borrower-income categories (special 
affordable and low-mod). By 2002, Fannie Mae had improved its 
performance enough to surpass Freddie Mac on all three goals-
qualifying categories and to lead the special affordable and low-mod 
markets, while lagging the underserved areas market.
    Consider first the average data for 1999-2003 reported in Table 
A.13. During this recent period, Freddie Mac's average performance 
was similar to Fannie Mae's performance for the special affordable 
category. Between 1999 and 2003, 14.7 percent of Freddie Mac's 
purchases and 15.1 percent Fannie Mae's mortgage purchases consisted 
of special affordable loans, compared with a market average of 16.2 
percent. During this period, Freddie Mac purchased low-mod loans 
lower than the rate of Fannie Mae--42.6 percent for Freddie Mac, 
43.6 percent for Fannie Mae, and 44.1 percent for the market. 
Freddie Mac (23.1 percent) also purchased underserved area loans at 
a lower rate than Fannie Mae (24.7 percent) and the primary market 
(26.2 percent). As these figures indicate, both Fannie Mae and 
Freddie Mac continued to lag the market during this recent four-year 
period. The GSEs' market ratios were 0.91-0.93 for special 
affordable loans and 0.97-0.99 for low-mod loans. Although less than 
one (where one indicates equal performance with the market), the 
``Fannie-Mae-to-market'' ratio (0.94) for the underserved area 
category was much higher than the ``Freddie-Mac-to-market'' ratio 
(0.88).
    Fannie Mae's performance in 1999 was significantly below its 
long run trend. Thus, averages for 2000-2003 are also presented in 
Table A.13, dropping 1999. These data show an increase in Fannie 
Mae's performance relative to the market. Between 2000 and 2003, 
special affordable (underserved area) loans accounted for 15.6 
percent (25.5 percent) of Fannie Mae's purchases, compared with 16.0 
percent (26.4 percent) for the market. During this 2000-2003 period, 
Fannie Mae slightly led the low-mod market (44.4 percent for Fannie 
Mae and 44.1 percent for the primary market).
    Table A.14 shows the effects on the market percentages for 1999-
2003 (as well as 2000-2003) of different definitions of the 
conventional conforming market. Excluding both small loans and 
manufactured housing loans (as well as B&C loans) in metropolitan 
areas would reduce the 1999-2003 market percentage for special 
affordable loans from 16.2 percent to 14.9 percent, which would 
place Fannie Mae slightly above the market and Freddie Mac close to 
the market. Similarly, excluding these loans would reduce the 1999-
2003 market percentage for underserved areas from 26.2 percent to 
25.2 percent, which would raise Fannie Mae's market ratio from 0.94 
to 0.98 and Freddie Mac's, from 0.88 to 0.92. As shown in Table 
A.14, Fannie Mae is even closer to the market averages if the year 
1999 is dropped--over the 2000-2003 period, Fannie Mae's performance 
on the underserved area category is practically at market levels 
under the above alternative definition of the market, and its 
performance on the special affordable and low-mod categories is 
above market levels.
    Finally, Tables A.13 and A.14 report GSE and market data for the 
even more recent period, 2001-2003, which represents the first three 
years under the current housing goal targets (put in place by HUD in 
its Final Rule dated October 30, 2000). These data show that Freddie 
Mac's average performance during this period was below the market on 
each of the three housing goals (with market ratios of 0.96 for 
special affordable, 0.98 for low-mod, and 0.91 for underserved areas 
and that Fannie Mae's average performance was above the market on 
the special affordable and low-mod categories (with a market ratio 
of 1.02 on each category) but below the market on the underserved 
areas category (with a market ratio of 0.98).

c. GSEs' Performance--Annual Data

    Freddie Mac's Annual Performance. As shown by the annual data 
reported in Table A.15, Freddie Mac significantly improved its 
purchases of goals-qualifying loans during the 1990s. Its purchases 
of loans for special affordable borrowers increased from 6.5 percent 
of its business in 1992 to 9.2 percent in 1997, and then jumped to 
14.7 percent in 2000 before falling slightly to 14.4 percent in 2001 
and rising again to almost 16 percent in 2002 and 2003. The 
underserved areas share of Freddie Mac's purchases increased at a 
more modest rate, rising from 18.6 percent in 1992 to 22.3 percent 
by 2001; it then jumped to 25.8 percent in 2002 but fell to 24.0 
percent in 2003.

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[[Page 63707]]

    With its improved performance, Freddie Mac closed its gap with 
the market in funding goals-qualifying loans. In 2003, special 
affordable loans accounted for 15.6 percent of Freddie Mac's 
purchases and 15.9 percent of loans originated in the conventional 
conforming market, which produces a ``Freddie-Mac-to-market'' ratio 
of 0.98 (15.6 divided by 15.9). Table A.15 shows the trend in the 
``Freddie-Mac-to-market'' ratio from 1992 to 2003 for each of the 
goals-qualifying categories. For the special affordable and low-mod 
categories, Freddie Mac's performance relative to the market 
remained flat (at approximately 0.60 and 0.80, respectively) through 
1997; by 2003, the ``Freddie-Mac-to-market'' ratios had risen to 
0.98 for both the special affordable and low-mod categories.
    Surprisingly, Freddie Mac did not make much progress during the 
1990s closing its gap with the market on the underserved areas 
category. The ``Freddie-Mac-to-market'' ratio for underserved areas 
was the same in 2000 (0.84) as it was in 1992 (0.84). While it rose 
to 0.88 in 2001, that was due more to a decline in the market level 
than to an improvement in Freddie Mac's performance. However, due to 
a substantial increase in Freddie Mac's underserved area percentage 
from 22.3 percent in 2001 to 25.8 percent in 2002, Freddie Mac's 
performance approached market performance (26.3 percent) during 
2002. \295\ In the ten years under the housing goals, the year 2002 
represented the first time that Freddie Mac's performance in 
purchasing home loans in underserved areas had ever been within two 
percentage points of the market's performance.\296\ But, as noted 
above, Freddie Mac's performance on the underserved areas goal fell 
to 24.0 percent in 2003, leaving it with a ``Freddie Mac-to-Market'' 
ratio of 0.87.
---------------------------------------------------------------------------

    \295\ Table A.14 reports annual market percentages that exclude 
the effects of manufactured housing, small loans, and subprime 
loans. Freddie Mac's performance is closer to the market average 
under the alternative market definitions, particularly during 2001 
and 2002.
    \296\ Prior to 2002, Freddie Mac's performance on the 
underserved areas category had not approached the market even under 
the alternative market definitions reported in Table A.14.
---------------------------------------------------------------------------

    Fannie Mae's Annual Performance. With respect to purchasing 
affordable loans, Fannie Mae followed a different path than Freddie 
Mac. Fannie Mae improved its performance between 1992 and 1998 and 
made much more progress than Freddie Mac in closing its gap with the 
market. In fact, by 1998, Fannie Mae's performance was close to that 
of the primary market for some important components of affordable 
lending. In 1992, special affordable loans accounted for 6.3 percent 
of Fannie Mae's purchases and 10.4 percent of all loans originated 
in the conforming market, giving a ``Fannie Mae-to-market'' ratio of 
0.61. By 1998, this ratio had risen to 0.86, as special affordable 
loans had increased to 13.2 percent of Fannie Mae's purchases and to 
15.4 percent of market originations. A similar trend in market 
ratios can be observed for Fannie Mae on the underserved areas 
category. In 1992, underserved areas accounted for 18.3 percent of 
Fannie Mae's purchases and 22.2 percent of market originations, for 
a ``Fannie Mae-to-market'' ratio of 0.82. By 1998, underserved areas 
accounted for 22.7 percent of Fannie Mae's purchases and 24.2 
percent of market originations, for a higher ``Fannie Mae-to-
market'' ratio of 0.94.\297\
---------------------------------------------------------------------------

    \297\ Freddie Mac, on the other hand, fell further behind the 
market during this period. In 1992, Freddie Mac had a slightly 
higher underserved areas percentage (18.6 percent) than Fannie Mae 
(18.3 percent). However, Freddie Mac's underserved areas percentage 
had only increased to 19.8 percent by 1998 (versus 22.7 percent for 
Fannie Mae). Thus, the ``Freddie Mac-to-market'' ratio fell from 
0.84 in 1992 to 0.82 in 1998.
---------------------------------------------------------------------------

    The year 1999 saw a shift in the above patterns, with Fannie Mae 
declining in overall performance while the share of goals-qualifying 
loans in the market increased. Between 1998 and 1999, the special 
affordable share of Fannie Mae's business declined from 13.2 percent 
to 12.5 percent while this type of lending in the market increased 
from 15.4 percent to 17.0 percent. For this reason, the ``Fannie-
Mae-to-market'' ratio for special affordable loans declined sharply 
from 0.86 in 1998 to 0.74 in 1999. The share of Fannie Mae's 
purchases in underserved areas also declined, from 22.7 percent in 
1998 to 20.4 percent in 1999, which lowered the ``Fannie-Mae-to-
market'' ratio from 0.94 to 0.81.
    After declining in 1999, Fannie Mae's performance rebounded in 
2000, particularly on the underserved areas category. Fannie Mae's 
underserved areas percentage jumped by three percentage points from 
20.4 percent in 1999 to 23.4 percent in 2000. The 2000 figure was 
similar to its level in 1997 but below Fannie Mae's peak 
performances of 24-25 percent during 1994 and 1995. Between 1999 and 
2000, the ``Fannie-Mae-to-market'' ratio for underserved areas 
increased from 0.81 to 0.89. Fannie Mae improved its performance on 
the special affordable goal at a more modest rate. Fannie Mae's 
special affordable percentage increased by 0.8 percentage points 
from 12.5 percent in 1999 to 13.3 percent in 2000. The 2000 figure 
was similar to its previous peak level (13.2 percent) in 1998. The 
``Fannie-Mae-to-market'' ratio for special affordable loans 
increased from 0.74 in 1999 to 0.80 in 2000, with the latter figure 
remaining below Fannie Mae's peak market ratio (0.86) in 1998.
    Fannie Mae continued its improvement in purchasing targeted home 
loans during 2001, at a time when the conventional conforming market 
was experiencing a decline in affordable lending; and again in 2002, 
at a time when the conventional conforming market was increasing 
enough to return approximately to its year-2000 level. Thus, during 
the 2000-to-2003 period, Fannie Mae significantly improved its 
targeted purchasing performance while the primary market originated 
targeted home loans at about the same rate in 2002 as it did in 
2000. As a result, Fannie Mae's performance during 2001 approached 
the market on the special affordable and underserved area categories 
and matched the market on the low-mod category. In 2002, Fannie Mae 
outperformed the market on all three areas categories.
    As shown in Table A.15, Fannie Mae increased its special 
affordable percentage by 1.6 percentage points, from 13.3 percent in 
2000 to 14.9 percent in 2001, and then increased it further to 16.3 
percent in 2002, the latter being slightly above the market's 
performance of 16.1 percent. The ``Fannie-Mae-to-market'' ratio for 
special affordable loans jumped from 0.80 in 2000 to 1.01 in 2002. 
In 2003, Fannie Mae's special affordable performance jumped to 17.1 
percent while the market declined slightly to 15.9 percent, 
increasing Fannie Mae's market ratio to 1.08.
    Between 2000 and 2001, Fannie Mae increased its low-mod 
percentage from 40.8 percent to 42.9 percent at the same time that 
the low-mod share of the primary market was falling from 43.9 
percent to 42.9 percent, placing Fannie Mae at the market's 
performance in 2001. During 2002, the low-mod share of Fannie Mae's 
purchases of home loans increased further to 45.3 percent, placing 
Fannie Mae 0.7 percentage points above the market performance of 
44.6 percent. Between 2002 and 2003 Fannie Mae's performance jumped 
to 47.0 percent, while the primary market remained at 44.6 percent, 
giving Fannie Mae a market ratio of 1.05 in 2003.
    Fannie Mae increased its underserved area percentage from 23.4 
percent in 2000 to 24.2 percent in 2001 while the underserved area 
share of the primary market was falling from 26.4 percent to 25.2 
percent, placing Fannie Mae at less than one percentage point from 
the market's performance. The ``Fannie-Mae-to-market'' ratio for 
underserved area loans was 0.97 in 2001. During 2002, the 
underserved area share of Fannie Mae's purchases of home loans 
increased further to 26.7 percent, placing Fannie Mae slightly ahead 
of market performance (26.3 percent). However, between 2002 and 
2003, Fannie Mae showed little improvement (rising to 26.8 percent) 
while the market increased to 27.6 percent, leaving Fannie Mae with 
a market ratio of 0.97.
    As noted earlier, Tables A.13 and A.14 summarize Fannie Mae's 
average performance over the 2001-2003 period. During these first 
three years under the current housing goal targets, Fannie Mae led 
the special affordable market (average performance of 16.2 percent 
versus 15.9 percent for the market) and the low-mod market (average 
performance of 45.2 percent versus 44.1 percent for the market) but 
lagged the underserved areas market (average performance of 26.0 
percent versus 26.4 percent for the market). Table A.14 also reports 
Fannie Mae's 2001-2003 performance under alternative definitions of 
the primary market. As shown there, the above findings of Fannie 
Mae's improvement relative to the market during 2001-2003 are 
further reinforced when lower market percentages are used. For 
example, Fannie Mae essentially matches the underserved areas market 
if manufactured housing loans in metropolitan areas (in addition to 
B&C loans) are excluded from the market definition (a Fannie Mae 
share of 26.0 percent and a market share of 26.1 percent).
    Changes in the ``Fannie-Mae-to-Freddie-Mac'' Performance Ratio. 
The above discussion documents shifts in the relative performance of 
Fannie Mae and Freddie Mac

[[Page 63708]]

over the past few years. To highlight these changing patterns, Table 
A.15 reports the ratio of Fannie Mae's performance to Freddie Mac's 
performance for each goals category for the years 1992 to 2003. As 
shown there, the ``Fannie-Mae-to-Freddie-Mac'' ratio for the special 
affordable category increased from approximately one in 1992 
(indicating equal performance) to over 1.3 during the 1994-97 
period, indicating that Fannie Mae clearly out-performed Freddie Mac 
during this period. Between 1997 and 2000, Freddie Mac substantially 
increased its special affordable share (from 9.2 percent to 14.7 
percent), causing the ``Fannie-Mae-to-Freddie-Mac'' ratio to fall 
from 1.27 in 1997 to 0.90 in 2000 (indicating Freddie Mac surpassed 
Fannie Mae). But Fannie Mae's stronger performance during 2001-2003 
returned the ratio to above one (1.03 in 2001 and 2002 and 1.10 in 
2003), indicating better performance for Fannie Mae (e.g., 17.1 
percent in 2002 versus 15.6 percent for Freddie Mac). The ``Fannie-
Mae-to-Freddie-Mac'' performance ratio for low-mod loans followed a 
similar pattern, standing at 1.07 in 2003 (47.0 percent for Fannie 
Mae versus 43.8 percent for Freddie Mac).
    Prior to 2000, the ``Fannie-Mae-to-Freddie-Mac'' ratio for 
underserved areas had also followed a pattern similar to that 
outlined above for special affordable loans, but at a lower overall 
level--rising from about one in 1992 (indicating equal performance) 
to approximately 1.2 during the 1994-97 period, before dropping to 
slightly below one (0.98) in 1999. However, Fannie Mae increased its 
underserved areas percentage from 20.4 percent in 1999 to 24.4 
percent in 2001 while Freddie Mac only increased its percentage from 
20.9 percent to 22.3 percent. This resulted in the ``Fannie-Mae-to-
Freddie-Mac'' ratio rising from 0.98 in 1999 to 1.09 in 2001. But 
during 2002, Freddie Mac's underserved area percentage jumped by 3.5 
percentage points to 25.8 percent, while Fannie Mae's increased at a 
more modest rate (by 2.3 percentage points) to 26.7 percent, with 
the result being that the ``Fannie-Mae-to-Freddie-Mac'' ratio for 
underserved area loans fell from 1.09 in 2001 to 1.03 in 2002. 
During 2003, Fannie Mae essentially maintained its performance (26.8 
percent), while Freddie Mac reduced its performance by 1.8 
percentage points to 24.0 percent. This increased the 2003 ``Fannie 
Mae-to-Freddie Mac'' ratio for underserved areas to 1.12.
    To conclude, while Freddie Mac ended the 1990s on a more 
encouraging note than Fannie Mae, the past four years (2000, 2001, 
2002 and 2003) have seen a substantial improvement in Fannie Mae's 
performance on all three goals-qualifying categories. Fannie Mae 
ended the 1990s with a decline in affordable lending performance at 
the same time that Freddie Mac was improving and the share of goals-
qualifying loans was increasing in the market. Both GSEs' 
performance during 2000 was encouraging--Freddie Mac continued to 
improve, particularly with respect to the borrower-income 
categories, while Fannie Mae reversed its declining performance, 
particularly with respect to underserved areas. During 2000, Freddie 
Mac outperformed Fannie Mae on the special affordable and low-mod 
categories, while Fannie Mae purchased a higher percentage of loans 
in underserved areas. During 2001, Fannie Mae continued to improve 
its performance while Freddie Mac's performance remained about the 
same and the market's originations of affordable loans declined 
somewhat. The result was that during 2001 Fannie Mae outperformed 
Freddie Mac on all three goals-qualifying categories, and even 
matched the market on the low-mod category. During 2002, both Fannie 
Mae and Freddie Mac again improved their performance; Fannie Mae 
continued to outperform Freddie Mac and outperformed the market on 
all three goals-qualifying categories. While Freddie Mac lagged the 
market on all three goals-qualifying categories during 2002, it had 
significantly closed its gap by the end of 2002, particularly on the 
underserved area category. During 2003, Fannie Mae made significant 
improvement in the special affordable and low-mod categories, 
allowing it to lead the primary market. Freddie Mac, on the other 
hand, simply maintained its 2002 performance in these two 
categories, which meant it lagged further behind Fannie Mae. On the 
underserved area category, Fannie Mae maintained its 2002 
performance during 2003 while Freddie Mac significantly reduced its 
performance, leaving both GSEs, but particularly Freddie Mac, behind 
the primary market on this category.
    GSE Purchases of Seasoned Loans. When the GSE data are expressed 
on a purchase-year basis (as in the above analysis), one factor 
which affects each GSE's performance concerns their purchases of 
seasoned (prior-year) loans. As shown in Table A.11, Fannie Mae 
followed a strategy of purchasing targeted seasoned loans between 
1996 and 1998, and again during 2000-2002--all years when Fannie Mae 
improved its overall affordable lending performance. For example, 
consider Fannie Mae's underserved area performance of 24.4 percent 
during 2001, which was helped by its purchases of seasoned mortgages 
on properties located in underserved neighborhoods. The underserved 
area percentage for Fannie Mae's purchases of newly-originated 
(current-year) mortgages was only 23.3 percent in 2001, or 1.9 
percentage points below the market average of 25.2 percent. Fannie 
Mae obtained its higher overall percentage (24.4 percent) by 
purchasing seasoned loans with a particularly high concentration 
(28.3 percent) in underserved areas. Similarly, during 2001, the 
special affordable share of Fannie Mae's purchases of newly-
originated mortgages was only 14.2 percent, or 1.4 percentage points 
below the market average of 15.6 percent. Again, Fannie Mae improved 
its overall performance by purchasing seasoned loans with a high 
percentage (18.1 percent) of special affordable loans, enabling 
Fannie Mae to reduce its gap with the market to 0.7 percentage 
points--14.9 percent versus 15.6 percent.
    As shown in Table A.11, Freddie Mac also followed a strategy of 
purchasing seasoned special affordable loans mainly after 1999. 
Prior to 2000, Freddie Mac had not pursued such a strategy, or at 
least not to the same degree as Fannie Mae. During the 1997-99 
period, Freddie Mac's purchases of prior-year mortgages and newly-
originated mortgages had similar percentages of special affordable 
(and low-mod) borrowers. Over time, there have been small 
differentials between Freddie Mac's prior-year and newly-originated 
mortgages for the underserved areas category but they have been 
smaller than the differentials for Fannie Mae (see Table A.11).

d. GSEs' Annual Purchases of Home Loans--Origination-Year Basis

    Table A.16 reports GSE purchase data for 1996 to 2003 on an 
origination-year basis. Recall that in this case, mortgages 
purchased by a GSE in any particular calendar year are allocated to 
the year that the mortgage was originated, rather than to the year 
that the mortgage was purchased (as in the above). This approach 
places the GSE and the market data on a consistent, current-year 
basis, as explained earlier.
BILLING CODE 4210-27-P

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[[Page 63710]]


    In general, the comparisons of Freddie Mac's and the market's 
performance are similar to those discussed in Sections E.9.a-c 
above, except for some differences on the special affordable 
category. The ``Freddie Mac to market'' ratios in Table A.16 show 
that Freddie Mac has improved its performance but has also 
consistently lagged the primary market in funding mortgages covered 
by the housing goals.
    The ``Fannie Mae to market'' ratios in Table A.16 show that 
Fannie Mae has improved its performance, has generally outperformed 
Freddie Mac, and led the market during 2003 on both the special 
affordable and low-mod goals. Under the origination-year approach, 
Fannie Mae lagged the market on all three housing goal categories 
during 2001 and on the underserved area category during 2002. Fannie 
Mae matched the market in funding special affordable loans during 
2002 and led the market in funding low-mod loans. During 2003, 
Fannie Mae led the primary market on both the special affordable and 
low-mod categories but lagged the market on the underserved area 
category. For instance in 2003, low- and moderate-income loans 
accounted for 47.0 percent of Fannie Mae's purchases and 44.6 
percent of the market originations, placing Fannie Mae 2.4 
percentage points above the market. On the other hand, underserved 
areas accounted for 26.3 percent of Fannie Mae's purchases during 
2003, which was 1.4 percentage points below market performance.

e. GSEs' Purchases of First-Time Homebuyer Mortgages--1999 to 2001

    While not a specific housing goal category, mortgages for first-
time homebuyers are an important component of the overall home loan 
market. Making financing available for first-time homebuyers is one 
approach for helping young families enter the homeownership market. 
Therefore, this section briefly compares the GSEs' funding of first-
time homebuyer loans with that of primary lenders in the 
conventional conforming market.
    During the past few years, the GSEs have increased their 
purchases of first-time homebuyer loans. For example, Fannie Mae's 
annual purchases of first-time homebuyer loans increased from 
approximately 287,000 in 1999 to 423,485 in 2003.\298\ However, 
since 1999, the first-time homebuyer share of the GSEs' purchases of 
home loans has remained relatively flat, varying within the 25-28 
percent range.\299\
---------------------------------------------------------------------------

    \298\ These figures include estimates of first-time homebuyer 
loans for those home purchase loans with a missing first-time 
homebuyer indicator; the estimates were obtained by multiplying the 
GSE's first-time homebuyer share (based only on data with a first-
time homebuyer indicator) by the number of loans with a missing 
first-time homebuyer indicator.
    \299\ The first-time homebuyer share for Fannie Mae was almost 
35 percent between 1996 and 1998; it then dropped to 30 percent in 
1998 and to 26 percent in 1999. The first-time homebuyer share for 
Freddie Mac was approximately 29 percent in 1996 and 1997 before 
dropping to about 25 percent in 1998 and 1999.
---------------------------------------------------------------------------

    Table A.17a compares the first-time homebuyer share of GSE 
purchases with corresponding share of home loans originated in the 
conventional conforming market. Readers are referred to recent work 
by Bunce and Gardner \300\ for the derivation of the estimates of 
first-time homebuyer market shares reported in Table A.17a. Between 
1999 and 2001, first-time homebuyers accounted for 26.5 percent of 
Fannie Mae's purchases of home loans, 26.5 percent of Freddie Mac's, 
and 37.6 percent of home loans originated in the conventional 
conforming market. Thus, both Fannie Mae and Freddie Mac fell 
substantially short of the primary market in financing first-time 
homebuyers during this time period. The GSEs' performance was only 
70.5 percent of market performance (26.5 percent divided by 37.6 
percent).
---------------------------------------------------------------------------

    \300\ See Harold L. Bunce and John L. Gardner, ``First-time 
Homebuyers in the Conventional Conforming Market: The Role of the 
GSEs'' (unpublished paper), January 2004. An update of this work to 
include data for 2002 and 2003 shows similar patterns as those 
reported in the text for 1999-2001. See Harold L. Bunce and John L. 
Gardner, ``First-time Homebuyers in the Conventional Conforming 
Market: The Role of GSEs: An Update'' (October, 2004).

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[[Page 63712]]


    Table A.17a also reports first-time homebuyer shares for African 
Americans and Hispanics and for all minorities. Between 1999 and 
2001, African-American and Hispanic first-time homebuyers accounted 
for 4.0 percent of Fannie Mae's purchases of home loans, 3.4 percent 
of Freddie Mac's purchases, and 6.9 percent of home loans originated 
in the conventional conforming market. for this subgroup, Fannie 
Mae's performance is 58 percent of market performance, while Freddie 
Mac's performance is 49 percent of market performance. The group of 
all minority first-time homebuyers accounted for 6.6 percent of 
Fannie Mae's purchases of home loans, 5.8 percent of Freddie Mac's 
purchases, and 10.6 percent of home loans originated in the 
conventional conforming market. In this case, Fannie Mae's 
performance is 62 percent of market performance, while Freddie Mac's 
performance is 55 percent of market performance.
    Section E.12 below will continue this examination of first-time 
homebuyers by presenting market share analysis that estimates the 
GSEs' overall importance in the funding of first-time homebuyers.

f. Low- and Moderate-Income Subgoal for Home Purchase Loans

    The Department is proposing to establishing a subgoal of 45 
percent for each GSE's purchases of home purchase loans for low- and 
moderate-income families in the single-family-owner market of 
metropolitan areas for 2005, with the subgoal rising to 46 percent 
for 2006 and 47 percent for 2007 and 2008. If the GSEs meet this 
subgoal, they will be leading the primary market by approximately 
one percentage point in 2005 and by three percentage points in 2007-
08, based on historical data (see below). This home purchase subgoal 
will encourage the GSEs to expand homeownership opportunities for 
lower-income homebuyers who are expected to enter the housing market 
over the next few years. As detailed in Section I, there are four 
specific reasons for establishing this subgoal: (1) The GSEs have 
the expertise, resources, and ability to lead the single-family-
owner market, which is their ``bread and butter'' business; (2) 
except for the recent performance of Fannie Mae, the GSEs have 
historically lagged the primary market for low- and moderate-income 
loans, not led it; (3) the GSEs can improve their funding of first-
time homebuyers and help reduce troublesome disparities in 
homeownership and access to mortgage credit; and (4) there are ample 
opportunities for the GSEs to expand their purchases in important 
and growing market segments such as the market for minority first-
time homebuyers. Sections E.9 and G of this appendix provide 
additional information on opportunities for an enhanced GSE role in 
the home purchase market and on the ability of the GSEs to lead that 
market.
    As shown in Tables A.13 and A.15, low- and moderate-income 
families accounted for an average of 44.1 percent of home purchase 
loans originated in the conventional conforming market of 
metropolitan areas between 1999 and 2003; the figure is 43.6 percent 
if the average is computed for the years between 1996 and 2003 or 
44.1 percent if the average is computed for the more recent 2001-
2003 period. Loans in the B&C portion of the subprime market are 
excluded from these market averages. To reach the 45-percent subgoal 
for 2005, Freddie Mac would have to improve its performance by one 
percentage point over its approximately 44 percent low-mod 
performance during 2002 and 2003, while Fannie Mae would have to 
maintain its performance of 45-47 percent over these two years. To 
reach the 47 percent subgoal in 2007-08, Freddie Mac would have to 
improve by three percentage points over its 2002-3 performance while 
Fannie Mae would have to maintain its 2003 performance of 47 
percent.
    As explained earlier, HUD will be re-benchmarking its median 
incomes for metropolitan areas and non-metropolitan counties based 
on 2000 Census median incomes, and will be incorporating the effects 
of the new OMB metropolitan area definitions. As shown in Table 17b, 
HUD projected the effects of these two changes on the low- and 
moderate-income shares of the single-family-owner market for the 
years 1999-2003. These estimates will be referred to as ``projected 
data'' while the 1990-based data reported in the various tables will 
be referred to as ``historical data.'' With the historical data, the 
average low-mod share of the conventional conforming market (without 
B&C loans) was 44.2 percent for home purchase loans (weighted 
average of 1999-2003 percentages in Table A.13); the corresponding 
average with the projected data was 43.5 percent, a differential of 
0.7 percentage points. However, note that in 2003, the projected 
data for both GSEs and the market exhibit higher low-mod shares than 
the corresponding historical data. For 2003, the low-mod shares for 
the projected and historical data are as follows: Fannie Mae (47.5 
percent for the projected data versus 47.0 percent for the 
historical data), Freddie Mac (44.2 percent versus 43.8 percent), 
and the market (45.6 percent versus 44.6 percent). Thus, based on 
2003 experience, it appears that the low-mod share for single-
family-owners in the conventional conforming market actually 
increase based on the re-benchmarking of area median incomes and the 
new OMB definitions of metropolitan areas. Thus, based on 2003 data, 
the 47-percent subgoal for 2007 is 2.4 percentage points above the 
2003 market.

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[[Page 63714]]


    In terms of projected data, Fannie Mae could meet both the 2005 
and 2007 subgoals by maintaining its projected 2003 low-mod 
performance of 47.5 percent. Freddie Mac's projected low-mod 
performance for 2003 was 44.2 percent, about 0.4 percentage points 
above its 2003 performance of 43.8 percent based on historical data. 
Thus, to reach the 45-percent subgoal for 2005, Freddie Mac would 
have to increase its 2003 projected performance by 0.8 percentage 
point, and to reach the 47-percent 2007 subgoal, Freddie Mac would 
have to increase its performance by 2.8 percentage points over its 
projected performance of 44.2 percent for 2003.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for non-metropolitan areas are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices B and C.
    It should be noted that the findings in sub-sections 9.a-e above 
concerning the performance of the GSEs relative to the home purchase 
market do not change when projected, rather than historical data, 
are used.

10. GSEs Purchases of Total (Home Purchase and Refinance) Loans

    Section E.9 examined the GSEs' acquisitions of home purchase 
loans, which is appropriate given the importance of the GSEs for 
expanding homeownership opportunities. To provide a complete picture 
of the GSEs' mortgage purchases in metropolitan areas, Tables A.18, 
A.19, A.20, and A.21 report the GSEs' purchases of all single-
family-owner mortgages, including both home purchase loans and 
refinance loans.\301\
---------------------------------------------------------------------------

    \301\ The GSE total (home purchase and refinance) data in Tables 
A.18-A.20 are presented on a purchase-year basis; Table A.21 
presents similar data on an origination-year basis.

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BILLING CODE 4210-27-C

[[Page 63719]]

    Table A.18 provides a long-run perspective on the GSEs' overall 
performance. Between 1993 and 2003, as well as during the 1996-2003 
period, the GSEs' performance was 81-91 percent of market 
performance for the special affordable category, 91-97 percent of 
market performance for the low-mod category, and 87-93 percent of 
market performance for the underserved areas category. For example, 
between 1996 and 2003, underserved areas accounted for 23.4 percent 
of Fannie Mae's purchases and 21.8 percent of Freddie Mac's 
purchases, compared with 25.2 percent for the conventional 
conforming market (without B&C loans). Similarly, for special 
affordable loans, both GSEs lagged the market during the 1996-2003 
period--Fannie Mae and Freddie Mac averaged approximately 13.0 
percent while the market was over two percentage points higher at 
14.8 percent.
    Similar to the patterns discussed for home purchase loans, 
Fannie Mae has tended to outperform Freddie Mac. This can be seen by 
examining the various ``Fannie-Mae-to-Freddie-Mac'' ratios in Table 
A.18, which are all equal to or greater than one. Over the recent 
1999-2003 period, Fannie Mae and Freddie Mac continued to lag the 
overall market on all three goals-qualifying categories. Special 
affordable (underserved area) loans averaged 14.0 (23.8) percent of 
Fannie Mae's purchases, 13.2 (22.1) percent of Freddie Mac's 
purchases, and 15.0 (25.2) percent of market originations. For 
Fannie Mae, the market ratio was 0.93 for special affordable loans, 
0.98 for low-mod loans, and 0.94 for underserved area loans. As with 
home purchase loans, dropping the year 1999 and characterizing 
recent performance by the 2000-2003 period improves the performance 
of both GSEs relative to the market, but particularly Fannie Mae. 
Over the 2000-2003 period, the ``Fannie-Mae-to-market'' ratio was 
0.97 for special affordable loans, 1.00 for low-mod loans, and 0.96 
for underserved area loans. Over the last three years (2001-2003), 
the ``Fannie-Mae-to-market'' ratios are even higher--1.00 for 
special affordable loans, 1.01 for low-mod loans, and 0.98 for 
underserved area loans. In other words, during the first three years 
under the current housing goal targets, Fannie Mae matched the 
special affordable market, led the low-mod market, and lagged the 
underserved areas market.
    The above analysis has defined the market to exclude B&C loans. 
Table A.19 shows the effects on the market percentages of different 
definitions of the conventional conforming market. For example, the 
average 1999-2003 market share for special affordable (underserved 
areas) loans would fall to 14.4 (24.8) percent if small loans and 
manufactured housing loans in metropolitan areas were excluded from 
the market definition along with B&C loans. In this case, the market 
ratio for Fannie Mae (Freddie Mac) would be was 0.97 (0.92) for 
special affordable loans, 1.00 (0.95) for low-mod loans, and 0.96 
(0.89) for underserved area loans.
    Shifts in performance occurred during 2001-2003, the first three 
years under HUD's higher housing goal targets. Table A.20 shows that 
both GSEs improved their overall performance between 1999 and 2000, 
but they each fell back a little during the heavy refinancing year 
of 2001. But the primary market (without B&C loans) experienced a 
much larger decline in affordable lending during the refinancing 
wave than did either of the GSEs. Fannie Mae stood out in 2001 
because of its particularly small decline in affordable lending. 
Between 2000 and 2001, Fannie Mae's special affordable lending fell 
by only 0.6 percentage points while Freddie Mac's fell by 2.8 
percentage points and the market's fell by 3.6 percentage points. 
The corresponding percentage point declines for the underserved 
areas category were 1.0 for Fannie Mae, 1.9 for Freddie Mac, and 3.8 
for the market. By the end of 2001, Fannie Mae led Freddie Mac in 
all three goals-qualifying categories, and had erased its gap with 
the low-mod market, but continued to lag the market on the special 
affordable and underserved areas categories.
    During the refinancing wave of 2002, Fannie Mae improved 
slightly on the special affordable and low-mod categories and 
declined slightly on the underserved area category. Freddie Mac 
showed slight improvement on the special affordable and underserved 
area categories and remained about the same on the low-mod category. 
The result of these changes can be seen by considering the market 
ratios in Table A.20. In 2002, special affordable loans accounted 
for 14.3 percent of Fannie Mae's purchases and 14.4 percent of loans 
originated in the non-B&C portion of the conventional conforming 
market, yielding a ``Fannie-Mae-to-market'' ratio of 0.99. Since 
Fannie Mae's market ratio for the special affordable category stood 
at 0.80 in 2000, Fannie Mae substantially closed its gap with the 
market during 2001 and 2002. During this period, Fannie Mae also 
mostly eliminated its market gap for the other two goals-qualifying 
categories. In 2002, underserved area loans accounted for 24.0 
percent of Fannie Mae's purchases and 24.2 percent of loans 
originated in the non-B&C portion of the conventional conforming 
market, yielding a ``Fannie-Mae-to-market'' ratio of 0.99, or 
approximately one. During 2002, low-mod loans accounted for 42.2 
percent of Fannie Mae's purchases and 42.0 percent of loans 
originated in the market, yielding a ``Fannie-Mae-to-market'' ratio 
of 1.00 (also note that Fannie Mae slightly outperformed the low-mod 
market during 2001). Thus, during 2002, Fannie Mae essentially 
matched the market on each of the three goals-qualifying categories.
    In 2003, Fannie Mae's continued to improve its performance on 
the special affordable and low-mod categories. In 2003, special 
affordable loans accounted for 14.3 percent of Fannie Mae's 
purchases and 14.0 percent of loans originated in the market, 
yielding a ``Fannie-Mae-to-market'' ratio of 1.02. During that year, 
low-mod loans accounted for 42.3 percent of Fannie Mae's purchases 
and 41.2 percent of total (home purchase and refinance) loans 
originated in the market, yielding a ``Fannie-Mae-to-market'' ratio 
of 1.03. On the underserved areas category, Fannie Mae continued to 
lag behind the market (a 23.7 percent share for Fannie Mae and a 
24.5 percent share for the market).
    Freddie Mac significantly lagged the single-family (home 
purchase and refinance loans combined) market during 2001-2003. In 
2003, the ``Freddie-Mac-to-market'' ratios were 0.86 for special 
affordable loans, 0.98 for low-mod loans, and 0.82 for underserved 
area loans.
    Subprime Loans. Table A.14 in Section E.9 showed that the goals-
qualifying shares of the home purchase market did not change much 
when originations by subprime lenders are excluded from the 
analysis; the reason is that subprime lenders operate primarily in 
the refinance market. Therefore, in this section's analysis of the 
total market (including refinance loans), one would expect the 
treatment of subprime lenders to significantly affect the market 
estimates and, indeed, this is the case. For the year 2001, 
excluding subprime loans reduced the goal-qualifying shares of the 
total market as follows: special affordable, from 15.0 to 13.9 
percent; low-mod, from 42.3 to 40.9 percent; and underserved areas, 
from 25.7 to 23.9 percent. (See Table A.19.) Similar declines take 
place in 2002 and 2003.
    As explained earlier, the comparisons in this appendix have 
defined the market to exclude the B&C portion of the subprime 
market. Industry observers estimate that A-minus loans account for 
about two-thirds of all subprime loans while the more risky B&C 
loans account for the remaining one-third. As explained earlier, 
this analysis reduces the goal-qualifying percentages from the HMDA 
data by half the differentials between (a) the market (unadjusted) 
and (b) the market without the specialized subprime lenders 
identified by Scheessele. As shown in Table A.19, accounting for B&C 
loans in this manner reduces the year 2001 HMDA-reported goal-
qualifying shares of the total (home purchase and refinance) 
conforming market as follows: special affordable, from 15.0 to 14.5 
percent; low-mod, from 42.3 to 41.6 percent; and underserved areas, 
from 25.7 to 24.9 percent. Obviously, the GSEs' performance relative 
to the market will depend on which market definition is used (much 
as it did with the earlier examples of excluding manufactured 
housing loans in metropolitan areas from the market definition). For 
example, defining the conventional conforming market to exclude 
subprime loans, rather than only B&C loans, would increase Fannie 
Mae's 2001 special affordable (underserved area) market ratio from 
0.96 to 1.00 (0.97 to 1.01). Similarly, it would increase Freddie 
Mac's special affordable (underserved area) market ratio from 0.92 
to 0.96 (0.90 to 0.94). For the broader-defined low-mod category, 
redefining the 2001 market to exclude subprime loans, rather than 
only B&C loans, would increase Fannie Mae's (Freddie Mac's) market 
ratio from 1.00 to 1.02 (0.97 to 0.98).
    Table A.21 reports GSE purchase data for total (home purchase 
and refinance) loans on an origination-year basis. The ``Freddie 
Mac-to-market'' ratios in Table A.21 show that Freddie Mac has 
lagged the primary market in funding mortgages covered by the 
housing goals. The ``Fannie Mae-to-market'' ratios in Table A.21 
show that Fannie Mae has always lagged the primary market in funding 
home purchase and refinance mortgages for

[[Page 63720]]

properties in underserved areas but, in 2002 and 2003, led the low-
mod market, and in 2003 led the special affordable market.
    11. GSE Mortgage Purchases in Individual Metropolitan Areas
    While the above analyses, as well as earlier studies, 
concentrate on national-level data, it is also instructive to 
compare the GSEs' purchases of mortgages in individual metropolitan 
areas (MSAs). In this section, the GSEs' purchases of single-family 
owner-occupied home purchase loans are compared to the market in 
individual MSAs. There are three steps. First, goals-qualifying 
percentages for conventional conforming mortgage originations 
(without B&C loans) are computed for each year and for each MSA, 
based on HMDA data. Second, corresponding goals-qualifying 
percentages are computed for each GSE's purchases for each year and 
for each MSA. These two sets of percentages are the same as those 
used in the aggregate analysis discussed in the above sections. 
Third, the ``GSE-to-market'' ratio is then calculated by dividing 
each GSE percentage by the corresponding market percentage. For 
example, if it is calculated that one of the GSEs' purchases of low- 
and moderate-income loans in a particular MSA is 40 percent of their 
overall purchases in that MSA, while 44 percent of all home loans 
(excluding B&C loans) in that MSA qualify as low-mod, then the GSE-
to-market ratio is 40/44 (or 0.91). The goals-qualifying ratios for 
Fannie Mae and Freddie Mac can be compared for each MSA in a similar 
manner.
    Tables A.22, A.23, and A.24 summarize the performance of the 
GSEs within MSAs for 2001, 2002 and 2003 originations of home 
purchase loans. A GSE's performance is determined to be lagging the 
market if the ratio of the GSE housing goal loan purchases to their 
overall purchases is less than 99 percent of that same ratio for the 
market. (The analysis was conducted where the ``lag'' determination 
is made at 98 percent instead of 99 percent and the results showed 
little change.) In the example given in the above paragraph, that 
GSE would be considered lagging the market. Tables A.22 (2001), A.23 
(2002) and A.24 (2003) report the number of MSAs in which each GSE 
under-performs the market with respect to each of the three housing 
goal categories. The following points can be made from this data:
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    Fannie Mae's improvement between 2001 and 2003 shows up in these 
tables. In 2001, Fannie Mae lagged the market in 264 (80 percent) of 
the 331 MSAs in the purchase of underserved area loans; this number 
decreased to 236 (71 percent) MSAs in 2002 and to 243 (73 percent) 
MSAs in 2003. Fannie Mae's improvement was even greater for special 
affordable and low-mod loans; in the latter case, Fannie Mae lagged 
the market in 51 (15 percent) MSAs in 2003, compared with 194 (59 
percent) MSAs in 2001.
    Freddie Mac's improvement between 2001 and 2003 was greater for 
underserved area loans. In 2001, Freddie Mac lagged the market in 
261 (79 percent) of the 331 MSAs in the purchase of underserved area 
loans; this number decreased to 168 (51 percent) MSAs in 2002 before 
rising to 222 (67 percent) MSAs in 2003. Freddie Mac's made less 
improvement on the special affordable and low-mod categories; in the 
former case, Freddie Mac lagged the market in 234 (71 percent) MSAs 
in 2003, compared with 279 (84 percent) MSAs in 2001.

12. GSE Market Shares: Home Purchase and First-Time Homebuyer Loans

    This section examines the role that the GSEs have played in the 
overall affordable lending market for home loans. There are two 
differences from the above analyses in Sections E.9 and E.10. The 
first difference is that this section focuses on ``market share'' 
percentages rather than ``distribution of business'' percentages. A 
``market share'' percentage measures the share of loans with a 
particular borrower or neighborhood characteristic that is funded by 
a particular market sector (such as FHA or the GSEs). In other 
words, a ``market share'' percentage measures a sector's share of 
all home loans originated for a particular targeted group. The 
``market share'' of a sector depends not only on the degree to which 
that sector concentrates its business on a targeted group (i.e., its 
``distribution of business'' percentage) but also on the size, or 
overall mortgage volume, of the sector. If an industry sector has a 
large ``market share'' for a targeted group, then that sector is 
making an important contribution to meeting the credit needs of the 
group. Both ``distribution of business'' and ``market share'' data 
are important for evaluating the GSEs' performance. In fact, given 
the large size of the GSEs, one would expect that a ``market share'' 
analysis would highlight their importance to the affordable lending 
market.
    The second difference is that this section also examines the 
role of the GSEs in the total market for home loans, as well as in 
the conventional conforming market. Such an approach provides a 
useful context for commenting on the contribution of Fannie Mae and 
Freddie Mac to overall affordable lending, particularly given 
evidence that conventional lenders have done a relatively poor job 
providing credit access to disadvantaged families, which renders the 
conventional market a poor benchmark for evaluating GSE performance. 
The analysis of first-time homebuyers conducts the market share 
analysis in terms of both the total market (Section E.12.b) and the 
conventional conforming market (Section E.12.c).
    While the GSEs have accounted for a large share of the overall 
market for home purchase loans, they have accounted for a very small 
share of the market for important groups such as minority first-time 
homebuyers. But as this section documents, the GSEs have been 
increasing their share of the low-income and minority market, which 
provides an optimistic note on which to go forward.
    Section E.12.a uses HMDA and GSE data to estimate the GSEs' 
share of home loans originated for low-income and minority borrowers 
and their neighborhoods. Sections E.12.b and E.12.c summarize recent 
research on the role of the GSEs in the first-time homebuyer market. 
Section E.12.d examines the downpayment characteristics of home 
loans purchased by the GSEs, a potentially important determinant of 
the GSEs' ability to reach first-time homebuyers.

a. GSEs' Share of Home Purchase Lending

    Table A.25 reports market share estimates derived by combining 
HMDA market data with GSE and FHA loan-level data. To understand 
these estimates, consider the GSE market share percentage of 46 
percent for ``All Home Purchase Loans'' at the bottom of the first 
column in the table. That market share percentage is interpreted as 
follows:
    It is estimated that home loans acquired by Fannie Mae and 
Freddie Mac during the years, 1999 to 2003, totaled 46 percent of 
all home loans originated in metropolitan areas during that period.
    It should be noted that ``all home loans'' refers to all 
government (FHA and VA) loans plus all conventional loans less than 
the conforming loan limit; in other words, only ``jumbo loans'' are 
excluded from this analysis.\302\ The analysis is restricted to 
metropolitan areas because HMDA data (the source of the market 
estimates) are reliable only for metropolitan areas. B&C 
originations are included in the market data, since the purpose here 
is to gauge the GSEs' role in the overall mortgage market. As 
discussed in Section E.9, excluding B&C loans, or even all subprime 
loans, would not materially affect this analysis of the home loan 
market since subprime loans are mainly for refinance purposes. The 
analysis below frequently combines purchases by Fannie Mae and 
Freddie Mac since previous sections have already compared their 
performance relative to each other.
---------------------------------------------------------------------------

    \302\ Following the purchase-year approach used in Sections E.9 
and E.10, the GSE purchase data include their acquisitions of 
``prior-year'' as well as ``current-year'' mortgages, while the 
market data include only newly-originated (or ``current year'') 
mortgages.

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[[Page 63726]]

    The GSE market share percentage for ``Low-Income Borrowers'' at 
the top of the first column of Table A.25 has a similar 
interpretation:
    It is estimated that home loans for low-income borrowers 
acquired by Fannie Mae and Freddie Mac between 1999 and 2003 totaled 
38 percent of all home loans originated for low-income borrowers in 
metropolitan areas.
    According to the data in Table A.25, the GSEs account for a 
major portion of the market for targeted groups. For example, 
purchases by Fannie Mae and Freddie Mac represented 38 percent of 
the low-income-borrower market and 36-38 percent of the markets in 
low-income, high-minority, and underserved census tracts. Thus, 
access to credit in these historically underserved markets depends 
importantly on the purchase activities of Fannie Mae and Freddie 
Mac. However, the data in Table A.25 show that the GSEs' role in 
low-income and minority markets is significantly less than their 
role in the overall home loan market. Fannie Mae and Freddie Mac 
accounted for 46 percent of all home loans but only 37 percent of 
the loans financing properties in underserved neighborhoods. Their 
market share was even lower for loans to African-American and 
Hispanic borrowers--30 percent, or 16 percentage points less than 
the GSEs' overall market share of 46 percent.
    An encouraging finding is that the GSEs have increased their 
presence in the affordable lending market during 2002 and 2003, when 
they accounted for 40-44 percent of the loans financing properties 
in low-income, high-minority, and underserved neighborhoods and for 
34 percent of loans for African-American and Hispanic borrowers. 
These market share figures for the GSEs are generally higher than 
their performance during the two earlier years, 2000 and 2001.
    To provide additional perspective, Table A.25 also reports 
market share estimates for FHA.\303\ During the 1999-2003 period, 
FHA's overall market share was less than half of the GSEs' market 
share, as FHA insured only 16 percent of all home mortgages 
originated in metropolitan areas. However, FHA's shares of the 
underserved segments of the market were much higher than its overall 
market share. For instance, between 1999 and 2003, FHA insured 24 
percent of all mortgages originated in low-income census tracts, 
even though it insured only 16 percent of all home loans. FHA's 
share of the market was particularly high for African-American and 
Hispanic borrowers, as FHA insured 29 percent of all home loans 
originated for these borrowers between 1999 and 2003--a figure only 
one percentage point higher than the GSEs' share of 30 percent.\304\ 
Thus, during the 1999-2003 period, FHA's overall market share (16.0 
percent) was about one-third of the GSEs' market share (45.6 
percent), but its share of the market for loans to African-Americans 
and Hispanics was almost equal to the GSEs' share of that market.
---------------------------------------------------------------------------

    \303\ As explained in Section E.7, the GSEs' affordable lending 
performance is evaluated relative to the conventional conforming 
market, as required by Congress in the 1992 GSE Act that established 
the housing goals. However, it is insightful to examine their 
overall role in the mortgage market and to contrast them with other 
major sectors of the market such as FHA. There is no intention here 
to imply that the GSEs should purchase the same types of loans that 
FHA insures.
    \304\ As explained in the notes to Table A.25, HMDA data are the 
source of the market figures. It is assumed that HMDA data cover 85 
percent of all mortgage originations in metropolitan areas. If HMDA 
data covered higher (lower) percentages of market loans, then the 
market shares for both the GSEs and FHA would be lower (higher).
---------------------------------------------------------------------------

    The data for the two recent years (2002 and 2003) indicate a 
larger market role for Fannie Mae and Freddie Mac relative to FHA. 
While the GSEs continued to have a much larger share of the overall 
market than FHA (47-49 percent for the GSEs versus 11-14 percent for 
FHA), their share of home loans for African-Americans and Hispanics 
jumped to 34 percent during 2002 and 2003, which was higher than the 
percentage share for FHA (17-25 percent). The differentials in 
market share between FHA and the GSEs on the other affordable 
lending categories listed in Table A.25 were also higher in 2002 and 
2003 than in earlier years.

b. The GSEs' Share of the Total First-Time Homebuyer Market

    This section summarizes two recent analyses of mortgage lending 
to first-time homebuyers; these two studies examine the total 
mortgage market, including both government and conventional loans 
originated throughout the U.S. (i.e., in both metropolitan areas and 
non-metropolitan areas). Section E.12.c will summarize a third study 
of first-time homebuyers that focuses on the conventional conforming 
market. All three studies are market share studies that examine the 
GSEs' role in the first-time homebuyer market.
    First, a study by Bunce concluded that the GSEs have played a 
particularly small role in funding minority first-time 
homebuyers.\305\ Because HMDA does not require lenders to report 
information on first-time homebuyers, Bunce used data from the 
American Housing Survey to estimate the number of first-time 
homebuyers in the market. Using American Housing Survey data on home 
purchases from 1997 to 1999, Bunce estimated that the GSEs' share of 
the market for first-time African-American and Hispanic homebuyers 
was only 10-11 percent, or less than one-third of their share (36 
percent) of all home purchases during that period. FHA's share of 
this market was 36 percent, or twice its share (18 percent) of all 
home purchases.\306\ These data highlight the small role that the 
GSEs have played in the important market for minority first-time 
homebuyers.
---------------------------------------------------------------------------

    \305\ See Harold L. Bunce, The GSEs' Funding of Affordable 
Loans: A 2000 Update, Housing Finance Working Paper No. HF-013, 
Office of Policy Development and Research, HUD, April 2002.
    \306\ Bunce explains numerous assumptions and caveats related to 
combining American Housing Survey data on homebuyers with FHA and 
GSE data on mortgages. For example, the American Housing Survey 
(AHS) data used by Bunce included both financed home purchases and 
homes purchased with cash. If only financed home purchases were 
used, the market shares of both FHA and the GSEs would have been 
slightly higher (although the various patterns would have remained 
the same). The AHS defines first-time homebuyers as buyers who have 
never owned a home, while FHA and the GSEs define a first-time 
homebuyer more expansively as buyers who have not owned a home in 
the past three years. If it were possible to re-define the FHA and 
GSE data to be consistent with the AHS data, the FHA and GSE first-
time homebuyer shares would be lower (to an unknown degree). For 
additional caveats with the AHS data, also see David A. 
Vandenbroucke, Sue G. Neal, and Harold L. Bunce, ``First-Time 
Homebuyers: Trends from the American Housing Survey'', November 
2001, U.S. Housing Market Condition, a quarterly publication of the 
Office of Policy Development and Research at HUD. In some years, 
home purchases as measured by the AHS declined while home purchases 
as measured by other data sources (e.g., HMDA) increased. In 
addition, the AHS home purchase data for separate minority groups 
(e.g., African-Americans, Hispanics) sometimes exhibited shifts 
inconsistent with other sources.
---------------------------------------------------------------------------

    Bunce, Neal and Vandenbroucke (BNV) recently updated through 
2001 the study by Bunce. In addition, BNV developed an improved 
methodology that combined industry, HMDA and AHS data to estimate 
the number of first-time homebuyers (by race and ethnicity) in the 
mortgage market during the years 1996 to 2001.\307\ BNV's analysis 
includes the total mortgage market, that is, the government, 
conventional conforming, and jumbo sectors of the mortgage market.
---------------------------------------------------------------------------

    \307\ BNV's methodology for estimating first-time borrowers 
consists of three steps: (1) estimate the total number of home 
purchase loans originated during a particular year using a mortgage 
market model that they develop; (2) disaggregate the home purchase 
loans in step (1) into racial and ethnic groups using HMDA data for 
metropolitan areas; and (3) for each racial and ethnic group in step 
(2), estimate the number of first-time homebuyers using mortgage and 
first-time homebuyer information from the American Housing Survey.
---------------------------------------------------------------------------

    Table A.26 presents the key market shares estimated by BNV for 
the GSEs and FHA. The first figure (40.7) in Table A.26 is 
interpreted as follows: purchases of home loans by Fannie Mae and 
Freddie Mac totaled 40.7 percent of all home loans financed between 
1996 and 2001. Going down the first column shows that the GSEs' 
share of the first-time homebuyer market was 24.5 percent during the 
1996-to-2001--a market share significantly lower than their overall 
market share of 40.7 percent.
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[[Page 63728]]


    FHA's greater focus on first-time homebuyers is also reflected 
in the market share data reported in Table A.26. While FHA insured 
only 16.6 percent of all home loans originated between 1996 and 
2001, it insured 30.9 percent of all first-time-homebuyer loans 
during that period. The GSEs, on the other hand, accounted for a 
larger share (40.7 percent) of the overall home purchase market but 
a smaller share (24.5 percent) of the first-time homebuyer market.
    Table A.26 also reports home purchase and first-time homebuyer 
information for minorities. During the more recent 1999-to-2001 
period, the GSEs' loan purchases represented 41.5 percent of all 
home mortgages but only 24.3 percent of home loans for African-
American and Hispanic families, and just 14.3 percent of home loans 
for African-American and Hispanic first-time homebuyers. During this 
period, the GSEs' role in the market for first-time African-American 
and Hispanic homebuyers was only one-third of their role in the 
overall home loan market (14.3 percent versus 41.5 percent).
    FHA, on the other hand, accounted for a much larger share of the 
minority first-time homebuyer market than it did of the overall 
homebuyer market. Between 1999 and 2001, FHA insured 46.5 percent of 
all loans for African-American and Hispanic first-time homebuyers--a 
market share that was almost three times its overall market share of 
16.4 percent.\308\ While FHA's market share was two-fifths of the 
GSEs' share of the overall home purchase market (16.4 percent versus 
41.5 percent), FHA's market share was over three times the GSEs' 
share of the market for first-time African-American and Hispanic 
homebuyers (46.5 percent versus 14.3 percent). This finding that the 
GSEs have played a relatively minor role in the first-time minority 
market is similar to the conclusion reached by the Fed researchers 
(see below) and Bunce (2002) that the GSEs have provided little 
credit support to this underserved borrower group.
---------------------------------------------------------------------------

    \308\ See Bunce, Neal, and Vandenbroucke, op. cit., for 
comparisons of various estimates of the market shares for FHA and 
the GSEs using different data bases and estimation methods. One can 
compare (a) the 1999-2001 market shares for FHA and the conventional 
conforming market in metropolitan areas calculated using the same 
methodology as Table A.25 with (b) the 1999-2001 market share 
estimates reported in Table A.25 for the entire mortgage market 
(including jumbo loans and covering non-metropolitan areas as well 
as metropolitan areas). The results are strikingly consistent. For 
the 1999-to-2001 period, the FHA share of the overall (African 
American and Hispanic) home loan market is estimated to be 19.0 
percent (35.8 percent) under (a) versus 16.4 percent (31.2 percent) 
under (b). Lower percentage shares are expected for (b) because (b) 
includes jumbo loans. For the same period, the GSE share of the 
overall (African American and Hispanic) home loan market is 
estimated to be 46.0 percent (25-28 percent) under (a) versus 41.5 
percent (24.3 percent) under (b).
---------------------------------------------------------------------------

    The results reported in Table A.26 for the year 2001 suggest 
some optimism concerning the GSEs' role in the first-time homebuyer 
market. As explained in earlier sections, both GSEs, but 
particularly Fannie Mae, improved their affordable lending 
performance during 2001, at a time when the overall market's 
performance was slightly declining. This improvement is reflected in 
the higher first-time market shares for the GSEs during the year 
2001, compared with the two previous years, 1999 and 2000 (not 
reported). The GSEs' share of the market for first-time African-
American and Hispanic homebuyers jumped from about 11-12 percent 
during 1999 and 2000 to 19.7 percent in 2001. Fannie Mae's share of 
this market almost doubled during this period, rising from 7.0 
percent in 1999 to 12.6 percent in 2001. Thus, while the GSEs 
continue to play a relatively small role in the minority first-time 
homebuyer market, during 2001 they improved their performance in 
this area.\309\
---------------------------------------------------------------------------

    \309\ For other analyses of the GSEs' market role, see the 
following study by economists at the Federal Reserve Board: Glenn B. 
Canner, Wayne Passmore, and Brian J. Surette, ``Distribution of 
Credit Risk among Providers of Mortgages to Lower-Income and 
Minority Homebuyers'' in Federal Reserve Bulletin, 82(12): 1077-
1102, December, 1996. This study considered several characteristics 
of the GSEs' loan purchases (such as amount of downpayment) and 
concluded that the GSEs have played a minimal role in providing 
credit support for underserved borrowers.
---------------------------------------------------------------------------

c. The GSEs' Share of the Conventional Conforming, First-time Homebuyer 
Market

    Bunce and Gardner (2004) recently conducted an analysis of 
first-time homebuyers for the conventional conforming market. The 
Bunce and Gardner analysis used a similar methodology to the study 
by Bunce, Neal, and Vandenbroucke of first-time homebuyers in the 
total mortgage market. Bunce and Gardner restricted their analysis 
to the funding of first-time homebuyers in the conventional 
conforming market, which is the market where Fannie Mae and Freddie 
Mac operate. Their market share results are summarized in Table 
A.27.

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[[Page 63730]]


    Between 1999 and 2001, the GSEs' purchases accounted for 56.6 
percent of all home loans originated in the conventional conforming 
market of both metropolitan areas and non-metropolitan areas. In 
other words, Fannie Mae and Freddie Mac funded almost three out of 
every five homebuyers entering the conventional conforming market 
between 1999 and 2001. Their purchases of first-time homebuyer 
loans, on the other hand, accounted for only 39.8 percent of all 
first-time homebuyer loans originated in that market. Thus, while 
the GSEs funded approximately two out of every five first-time 
homebuyers entering the conventional conforming market, their market 
share (39.8 percent) for first-time homebuyers was only 70 percent 
of their market share (56.6 percent) for all homebuyers.
    As shown in Table A.27, the GSEs have funded an even lower share 
of the minority first-time homebuyer market. Between 1999 and 2001, 
the GSEs purchases of African-American and Hispanic first-time 
homebuyer loans represented 30.9 percent of the conventional 
conforming market for these loans. Thus, while the GSEs have 
accounted for 56.6 percent of all home loans in the conventional 
conforming market, they have accounted for only 30.9 percent of 
loans originated in that market for African-American and Hispanic 
first-time homebuyers.
    The market share data in Table A.27 show some slight differences 
between the Freddie Mac and Fannie Mae in serving minority first-
time homebuyers. During the 1999-to-2001 period, Freddie Mac's share 
(11.9 percent) of the African-American and Hispanic first-time 
homebuyer market was only one-half of its share (24.0 percent) of 
the home loan market. On the other hand, Fannie Mae's share (19.0 
percent) of the African-American and Hispanic first-time homebuyer 
market was almost 60 percent of its share (32.5 percent) of the home 
loan market. Thus, while Fannie Mae performance in serving minority 
first-time homebuyers has been poor, it has been better than Freddie 
Mac's. This difference in performance between Fannie Mae and Freddie 
Mac was also seen in the portfolio percentages reported earlier in 
Table A.17a. Loans for African-American and Hispanic first-time 
homebuyers accounted for 6.9 percent of Fannie Mae's purchases of 
home loans between 1999 and 2001, a figure higher than Freddie Mac 
percentage of 5.3 percent. Loans for African-American and Hispanic 
first-time homebuyers accounted for 10.2 percent of all home loans 
originated in the conventional conforming market.

d. Downpayments on Loans Purchased by the GSEs

    The level of downpayment can be an important obstacle to young 
families seeking their first homes. Examining the downpayment 
characteristics of the mortgages purchased by the GSEs might help 
explain why they have played a rather limited role in the first-time 
homebuyer market
    Table A.28 reports the loan-to-value (LTV) distribution of home 
purchase mortgages acquired by the GSEs between 1997 and 2003. In 
Table A.29, LTV data are provided for the GSEs' purchases of home 
loans that qualify for the three housing goals--special affordable, 
low-mod, and underserved areas. Three points stand out.

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    First, the GSEs (and particularly Fannie Mae) have recently 
increased their purchases of home loans with low downpayments. After 
remaining about 4 percent of Fannie Mae's purchases between 1997 and 
2000, over-95-percent-LTV loans (or less-than-five-percent 
downpayment loans) jumped to 7.1 percent during 2001, 7.7 percent in 
2002 and 11.5 percent in 2003. It is interesting that this jump in 
less-than-five-percent downpayment loans occurred in the same years 
that Fannie Mae improved its purchases of loans for low-income 
homebuyers, as discussed in earlier sections. As a share of Freddie 
Mac's purchases, over-95-percent-LTV loans increased from 1.1 
percent in 1997 to 5.9 percent in 2000, before falling to 4.3 
percent in 2001, 4.8 percent in 2002 and 4.7 percent in 2003. If the 
low-downpayment definition is expanded to ten percent (i.e., over-
90-percent-LTV loans), Freddie Mac had about the same percentage (25 
percent) of low-downpayment loans during 2001 as Fannie Mae. In 
fact, under the more expansive definition, Freddie Mac had the same 
share of over-90-percent-LTV loans in 2001 as it did in 1997 (about 
25 percent), while Fannie Mae exhibited only a modest increase in 
the share of its purchases with low downpayments (from 23.2 percent 
in 1997 to 25.4 percent in 2001). The share of over-90-percent-LTV 
loans in Freddie Mac's purchases fell sharply from 25.0 percent in 
2001 to 21.9 percent in 2002 and 19.9 percent in 2003, while the 
share in Fannie Mae's purchases fell more modestly from 25.4 percent 
in 2001 to 24.2 percent in 2002 before rebounding to 25.3 percent in 
2003.
    Second, loans that qualify for the housing goals have lower 
downpayments than non-qualifying loans. In 2001 and 2002, over-95-
percent-LTV loans accounted for about 15 percent of Fannie Mae's 
purchases of special affordable loans, 13 percent of low-mod loans, 
and 12 percent of underserved area loans, compared with about 7.5 
percent of Fannie Mae's purchases of all home loans. (See Table 
A.29.) In 2003 these percentages increased to 23, 19 and 19 percent 
for special affordable, low-mod and underserved areas respectively. 
These low-downpayment shares for 2001, 2002 and 2003 were double 
those for 2000 when over-95-percent-LTV loans accounted for 8.4 
percent of Fannie Mae's purchases of special affordable loans and 
about 7 percent of its purchases of low-mod and underserved area 
loans. Fannie Mae's low-downpayment shares during 2001 were higher 
than Freddie Mac's shares of 12.3 percent for special affordable 
loans and about 9 percent for low-mod and underserved area loans. 
Between 2001 and 2003, Freddie Mac's over-95-percent-LTV shares fell 
sharply to 3-4 percent for the three housing goal categories, while 
Fannie Mae's shares increased to the 13-23 percent range. Under the 
more expansive, over-90-percent-LTV definition, almost one-third of 
Fannie Mae's goals-qualifying purchases during 2001 would be 
considered low downpayment, as would a slightly smaller percentage 
of Freddie Mac's purchases. However, during 2003, Freddie Mac's 
over-90-percent-LTV shares for the goals-qualifying loans fell to 
20-22 percent.
    Third, a noticeable pattern among goals-qualifying loans 
purchased by the GSEs is the predominance of loans with high 
downpayments. For example, 54.3 percent of special affordable home 
loans purchased by Freddie Mac during 2003 had a downpayment of at 
least 20 percent, a percentage not much lower than the high-
downpayment share (59.5 percent) of all Freddie Mac's home loan 
purchases. Similarly, 49.8 percent of the home loans purchased by 
Fannie Mae in underserved areas during 2003 had a twenty percent or 
higher downpayment, compared with 54.6 percent of all home loans 
purchased by Fannie Mae.
    Thus, the data in Tables A.28 and A.29 show a preponderance of 
high downpayment loans, even among lower-income borrowers who 
qualify for the housing goals. The past focus of the GSEs on high-
downpayment loans provides some insight into a study by staff at the 
Federal Reserve Board who found that the GSEs have offered little 
credit support to the lower end of the mortgage market.\310\ The 
fact that approximately half of the goals-qualifying loans purchased 
by the GSEs have a downpayment of over twenty percent is also 
consistent with findings reported earlier concerning the GSEs' 
minimal service to first-time homebuyers, who experience the most 
problems raising cash for a downpayment. On the other hand, the 
recent experience of Fannie Mae suggests that purchasing low-
downpayment loans may be one technique for reaching out and funding 
low-income and minority families who are seeking to buy their first 
home.
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    \310\ Canner, et al., op. cit.
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13. Other Studies of the GSEs' Performance Relative to the Market

    This section summarizes briefly the main findings from other 
studies of the GSEs' affordable housing performance. These include 
studies by the HUD and the GSEs as well as studies by academics and 
research organizations.
    Freeman and Galster Study.\311\ A recent study by Lance Freeman 
and George Galster uses econometric analysis to test whether the 
Government-Sponsored Enterprises (GSEs) Fannie Mae and Freddie Mac 
purchases of home mortgages in neighborhoods traditionally 
underserved by financial institutions stimulate housing market 
activity in those neighborhoods. Specifically, this study analyzes 
data of single-family home sales volumes and prices of mortgages 
originated from 1993-1999 in Cleveland, OH.
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    \311\ The Impact of Secondary Mortgage Market and GSE Purchases 
on Underserved Neighborhood Housing Markets: Final Report to HUD. 
July 2002.
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    The study concludes that aggressive secondary market purchasing 
behavior by non-GSE entities stimulated sales volumes and prices of 
homes in low-income and predominantly minority-occupied 
neighborhoods of Cleveland. The study results also showed a positive 
relationship between home transaction activity and the actions of 
the secondary mortgage market, and concludes that the secondary 
mortgage market (and the non-GSE sector in particular) purchases of 
mortgages had a positive effect on the number of sales transactions 
one year later. However, the study also concludes that although non-
GSE purchases of non-home purchase mortgages appeared to boost 
prices one and two years later, no consistent impacts of purchasing 
rates on sales prices could be observed. In addition, there was no 
robust evidence that GSE purchasing rates were positively associated 
with single-family home transactions volumes or sales prices during 
any periods.
    Urban Institute Rural Markets Study.\312\ A study by Jeanette 
Bradley, Noah Sawyer, and Kenneth Temkin uses both quantitative and 
qualitative data to explore the issue of GSE service to rural areas. 
The study first summarizes the existing research on rural lending 
and GSE service to rural areas. It then reviews the current 
underwriting guidelines of Fannie Mae, Freddie Mac, the USDA Rural 
Housing Service, and Farmer Mac, focusing on issues relevant to 
rural underwriting. The GSE public-use database is used to analyze 
GSE non-metro loan purchasing patterns from 1993-2000. Finally, the 
study presents the results of a series of discussions conducted with 
key national industry and lender experts and local experts in three 
rural sites in south-central Indiana, southwestern New Mexico and 
southern New Hampshire chosen for the diversity of their region, 
population, economic structures, and housing markets.
---------------------------------------------------------------------------

    \312\ GSE Service to Rural Areas, 2002.
---------------------------------------------------------------------------

    The authors of the study conclude that while Fannie Mae and 
Freddie Mac have increased their lending to rural areas since 1993, 
their non-metro loan purchases still lag behind their role in metro 
loan purchases, particularly in regard to the percentage of 
affordable loans. From the discussions with experts, the authors of 
the study make the following policy recommendations: Underserved 
populations and rural areas should be specifically targeted at the 
census-tract level; HUD should set manufactured housing goals; HUD 
should consider implementing a survey of small rural lenders or 
setting up an advisory group of small rural lenders in order to 
determine their suggestions for creating stronger relationships 
between the GSEs and rural lenders with the goal of increasing GSE 
non-metro purchase rates.
    Urban Institute GSE Impacts Study.\313\ A report by Thomas 
Thibodeau, Brent Ambrose, and Kenneth Temkin analyzes the extent to 
which the GSEs' responses to the Federal Housing Enterprises 
Financial Safety and Soundness Act's (FHEFSSA) affordable housing 
goals have had their intended effect of making low- and moderate-
income families better off. Specifically the report examines several 
methodologies determining that the conceptual model created by Van 
Order in 1996 \314\ provided the most complete description of how 
the primary and secondary markets interact. This model was then 
applied in a narrow scope to capital market outcomes which included 
GSE market shares and effective borrowing costs,

[[Page 63734]]

and housing market outcomes that include low- and moderate-income 
homeownership rates. Finally, metropolitan American Housing Survey 
(AHS) data for eight cities were used to conduct empirical analyses 
of the two categories of outcomes. These cities included areas 
surveyed in 1992, the year before HUD adopted the affordable housing 
goals, to provide the baseline for the analysis. Four metropolitan 
areas were surveyed in 1992 and again in 1996: Cleveland, 
Indianapolis, Memphis and Oklahoma City. Four cities were surveyed 
in 1992 and again in 1998: Birmingham, Norfolk, Providence and Salt 
Lake City.
---------------------------------------------------------------------------

    \313\ An Analysis of the Effects of the GSE Affordable Goals on 
Low- and Moderate-Income Families, 2001.
    \314\ Van Order, Robert. 1996. ``Discrimination and the 
Secondary Mortgage Market.'' In John Goering and Ronald Wienk, eds. 
Mortgage Discrimination, Race, and Federal Policy. The Urban 
Institute Press, Washington, DC: 335-363.
---------------------------------------------------------------------------

    The study's empirical analysis suggests that the GSE affordable 
goals have helped to make homeownership more attainable for target 
families. The assessment of the effects of the affordable goals on 
capital markets showed that the GSE share of the conventional 
conforming market has increased, especially for lower income 
borrowers and neighborhoods. The study also concludes that the 
affordable housing goals have an impact on the purchase decisions of 
Fannie Mae and Freddie Mac. The study also finds that interest rates 
are lower in markets in which Fannie Mae and Freddie Mac purchase a 
higher proportion of conventional loans. Finally, the study's 
analysis shows that overall lending volume in a metropolitan area 
increases when the GSEs purchase seasoned loans.
    Specifically, that homeownership rates increased at a faster 
rate for low-income families when compared to all families, and that 
in a subset of MSAs, minority homeownership rates also grew faster 
when compared to overall homeownership changes in those MSAs.
    Finally, the affordable housing goal effects were examined for 
80 MSAs in relation to the homeownership rate changes between 1991 
and 1997. The study found that the GSEs, by purchasing loans 
originated to low-income families, helped to reduce the disparity 
between homeownership rates for lower and higher income families, 
suggesting that the liquidity created when the GSEs purchase loans 
originated to low-income families is recycled into more lending 
targeted to lower income homebuyers.
    The authors of the study qualify their results by stating that 
they are based on available data that does not provide the level of 
detail necessary to conduct a fully controlled national assessment.
    Williams and Bond Study.\315\ Richard Williams and Carolyn Bond 
examine GSE leadership of the mortgage finance industry in making 
credit available for low- and moderate-income families. 
Specifically, it asks if the GSEs are doing relatively more of their 
business with underserved markets than other financial institutions, 
and whether the GSEs' leadership helps to narrow the gap in home 
mortgage lending that exists between served and underserved markets. 
The study uses HMDA data for metropolitan areas and the Public Use 
Data Base at HUD for compilations of GSE data sets for the entire 
nation (GSE PUDB File B) to conduct descriptive and multivariate 
analyses of nationwide lending between 1993 and 2000. Additionally, 
separate analyses are conducted that include and exclude loans from 
subprime and manufactured housing lenders.
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    \315\ Are the GSEs Leading, and if So Do They Have Any 
Followers? An Analysis of the GSEs' Impact on Home Purchase Lending 
to Underserved Markets During the 1990s. University of Notre Dame 
Working Paper and Technical Series Number 2003-2. 2002.
---------------------------------------------------------------------------

    The study concludes that the GSEs are not leading: They do not 
purchase relatively more underserved market loans than the primary 
market makes nor do they purchase as many of these loans as their 
secondary market competitors. Additionally, the study concludes that 
the disparities between the GSEs and the primary market are even 
greater once the growing role of subprime and manufactured housing 
is considered. The authors admit that there have been signs of 
progress, particularly in 1999 and 2000 when primary market lending 
to underserved markets increased and GSE purchases of underserved 
market loans increased even faster. Regardless, the study concludes 
that there continues to be significant racial, economic, and 
geographic disparities in the way that the benefits of GSE 
activities are distributed and that the benefits of GSE activities 
still go disproportionately to members of served rather than 
underserved markets.

14. The GSEs' Support of the Mortgage Market for Single-Family Rental 
Properties

    The 1996 Property Owners and Managers Survey reported that 49 
percent of rental units are found in the ``mom and pop shops'' of 
the rental market--``single-family'' rental properties, containing 
1-4 units. These small properties are largely individually-owned and 
managed, and in many cases the owner-managers live in one of the 
units in the property. They include many properties in older cities, 
in need of financing for rehabilitation. Single-family rental units 
play an especially important role in lower-income housing, over half 
of such units are affordable to very low-income families.
    There is not, however, a strong secondary market for single-
family rental mortgages. While single-family rental properties 
comprise a large segment of the rental stock for lower-income 
families, they make up a small portion of the GSEs' business. 
Between 1999 and 2002, single-family rental properties accounted for 
only 7.6 percent of total (both single-family and multifamily) units 
financed by the GSEs during this period. It follows that since 
single-family rentals make up such a small part of the GSEs 
business, they have not penetrated the single-family rental market 
to the same degree that they have penetrated the owner-occupant 
market. Table A.30 below shows that between 1999 and 2002, the GSEs 
financed 61 percent of owner-occupied dwelling units in the 
conventional conforming market, but only 40 percent of single-family 
rental units.
    There are a number of factors that have limited the development 
of the secondary market for single-family rental property mortgages 
thus explaining the lack of penetration by the GSEs. Little is 
collectively known about these properties as a result of the wide 
spatial dispersion of properties and owners, as well as a wide 
diversity of characteristics across properties and individuality of 
owners. This makes it difficult for lenders to properly evaluate the 
probability of default and severity of loss for these properties.
    Single-family rental properties could be important for the GSEs 
housing goals, especially for meeting the needs of lower-income 
families. Between 1999 and 2002, 87 percent of the GSEs' single-
family rental units qualified for the Low- and Moderate-Income Goal, 
compared with 40 percent of one-family owner-occupied properties. 
(See Table A.30.) This heavy focus on lower-income families meant 
that single-family rental properties accounted for 14 percent of the 
units qualifying for the Low- and Moderate-Income Goal, even though 
they accounted for 7.6 percent of the total units (single-family and 
multifamily) financed by the GSEs.
    Given the large size of this market, the high percentage of 
these units which qualify for the GSEs' housing goals, and the 
weakness of the secondary market for mortgages on these properties, 
an enhanced presence by Fannie Mae and Freddie Mac in the single-
family rental mortgage market would seem warranted.\316\ Single-
family rental housing is an important part of the housing stock 
because it is an important source of housing for lower-income 
households.
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    \316\ A detailed discussion of the GSEs' activities in this area 
is contained in Theresa R. Diventi, The GSEs' Purchases of Single-
Family Rental Property Mortgages, Housing Finance Working Paper No. 
HF-004, Office of Policy Development and Research, Department of 
Housing and Urban Development, (March 1998).
---------------------------------------------------------------------------

    Despite the size and importance of single-family rental 
properties for low-income people, HUD received several comments 
advocating exclusion of single-family rentals from goals 
consideration. These commenters pointed out that single-family 
owner-occupiers often maintain their properties more effectively 
than single-family absentee landlords or their tenants. HUD was 
asked to exclude single-family investor owned properties to reduce 
these neighborhood effects.
    Community associations raise an important issue for neighborhood 
development. However, they do not address the question of effective 
goals promotion for all segments of the housing market. They compare 
maintenance by owner-occupiers to maintenance by investors in the 
single-family market. This does not address the housing outcomes for 
tenants with access to single-family rental compared to tenants in 
multifamily rental. With nearly half of rental units in older cities 
composed of smaller single-family units, denial of goals eligibility 
for single-family investors would exclude a substantial proportion 
of housing units available to low income people.
    Furthermore, single-family investors provide additional market 
benefits to the housing system. The whole structure of the GSEs 
provides liquidity to the housing market by allowing investors 
additional channels to fund mortgages. The question is not always 
between single-family investors and single-family owner-occupiers. 
Sometimes, the question is between a single-

[[Page 63735]]

family investor and a property unable to be sold or even abandoned. 
Although the goals strongly support home ownership for low-income 
neighborhoods, investors in single-family properties also play an 
important role.

F. Factor 4: Size of the Conventional Conforming Mortgage Market 
Serving Low- and Moderate-Income Families Relative to the Overall 
Conventional Conforming Market

    The Department estimates that dwelling units serving low- and 
moderate-income families will account for 51-56 percent of total 
units financed in the overall conventional conforming mortgage 
market during 2005-2008, the period for which the Low- and Moderate-
Income Housing Goal will be effective. The market estimates exclude 
B&C loans and allow for much more adverse economic and market 
affordability conditions than have existed recently. The detailed 
analyses underlying these estimates are presented in Appendix D.

G. Factor 5: GSEs' Ability to Lead the Industry

    FHEFSSA requires the Secretary, in determining the Low- and 
Moderate-Income Housing Goal, to consider the GSEs' ability to 
``lead the industry in making mortgage credit available for low- and 
moderate-income families.'' Congress indicated that this goal should 
``steer the enterprises toward the development of an increased 
capacity and commitment to serve this segment of the housing 
market'' and that it ``fully expect[ed] [that] the enterprises will 
need to stretch their efforts to achieve [these goals].''\317\
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    \317\ Senate Report 102-282, May 15, 1992, p. 35.
---------------------------------------------------------------------------

    The Department and independent researchers have published 
numerous studies examining whether or not the GSEs have been leading 
the single-family market in terms of their affordable lending 
performance. This research, which is summarized in Section E, 
concludes that the GSEs have generally lagged behind primary lenders 
in funding first-time homebuyers, lower-income borrowers and 
underserved communities, although Fannie Mae's recent performance 
has placed it ahead of the special affordable and low-mod markets 
for single-family-owner loans. As required by FHEFSSA, the 
Department has produced estimates of the portion of the total 
(single-family and multifamily) mortgage market that qualifies for 
each of the three housing goals (see Appendix D). Congress intended 
that the Department use these market estimates as one factor in 
setting the percentage target for each of the housing goals. The 
Department's estimate for the size of the Low- and Moderate-Income 
market is 51-56 percent, which is higher than the GSEs' performance 
on that goal.
    This section provides another perspective on the GSEs' 
performance by examining the share of the total conventional 
conforming mortgage market and the share of the goal-qualifying 
markets (low-mod, special affordable, and underserved areas) 
accounted for by the GSEs' purchases. This analysis, which is 
conducted by product type (single-family owner, single-family 
rental, and multifamily), shows the relative importance of the GSEs 
in each of the goal-qualifying markets.

1. GSEs' Role in Major Sectors of the Mortgage Market

    Tables A.30 and A.31a compare GSE mortgage purchases with HUD's 
estimates of the numbers of units financed in the conventional 
conforming market. Table A.30 presents aggregate data for 1999-2002 
while Table A.31a presents more summary market share data for 
individual years 2000, 2001 and 2002.\318\ (As explained below, 
Tables A.31b and A.31c repeat this information but for lower 
multifamily shares of the mortgage market.) HUD estimates that there 
were 47,551,039 owner and rental units financed by new conventional 
conforming mortgages between 1999 and 2002. Fannie Mae's and Freddie 
Mac's mortgage purchases financed 26,118,927 of these dwelling 
units, or 55 percent of all dwelling units financed. As shown in 
Table A.30, the GSEs have played a smaller role in the goals-
qualifying markets than they have played in the overall market. 
Between 1999 and 2002, new mortgages were originated for 26,051,771 
dwelling units that qualified for the Low- and Moderate-Income Goal; 
the GSEs low-mod purchases financed 12,608,215 dwelling units, or 48 
percent of the low-mod market. Similarly, the GSEs' purchases 
accounted for 48 percent of the underserved areas market, but only 
41 percent of the special affordable market. Obviously, the GSEs did 
not lead the industry during this period in financing units that 
qualify for the three housing goals. They need to improve their 
performance and it appears that there is ample room in the non-GSE 
portions of the goals-qualifying markets for them to do so. For 
instance, the GSEs were not involved in three-fifths of the special 
affordable market during the 1999-to-2002 period.
---------------------------------------------------------------------------

    \318\ Tables A.30 and A.31 examine GSE purchases on a ``going 
forward basis by origination year''. Specifically, it considers GSE 
purchases of: (a) 2000 mortgage originations during 2000, 2001, 2002 
and 2003; (b) 2001 originations during 2001, 2002 and 2003; and (c) 
2002 originations during 2002 and 2003. In other words, this 
analysis looks at the GSEs' purchases of a particular origination 
year cohort through 2003. This approach contrasts with the approach 
that examines GSE purchases on a ``backward looking basis by 
purchase year'', for example, GSE purchases during 2000 of both new 
2000 originations and originations during previous years (the latter 
called ``prior-year'' or seasoned loans). Either approach is a valid 
method for examining GSE purchases; in fact, when analyzing 
aggregated data such as the combined 1999-2002 data in Table A.30, 
the two approaches yield somewhat similar results. HUD's methodology 
for deriving the market estimates is explained in Appendix D. B&C 
loans have been excluded from the market estimates in Tables A.30 
and A.31.
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    While the GSEs are free to meet the Department's goals in any 
manner that they deem appropriate, it is useful to consider their 
performance relative to the industry by property type. The GSEs 
accounted for 61 percent of the single-family owner market but only 
35 percent of the multifamily market and 40 percent of the single-
family rental market (or a combined 37 percent share of the rental 
market).
    Single-Family Owner Market. As stated in the 2000 Rule, the 
single-family-owner market is the bread-and-butter of the GSEs' 
business, and based on the financial and other factors discussed 
below, the GSEs clearly have the ability to lead the primary market 
in providing credit for low- and moderate-income owners of single-
family properties. However, the GSEs have historically lagged behind 
the market in funding single-family-owner loans that qualify for the 
housing goals and, as discussed in Section E, they have played a 
rather small role in funding minority first-time homebuyers. The 
market share data reported in Table A.30 for the single-family-owner 
market tell the same story. The GSEs' purchases of single-family-
owner loans represented 61 percent of all single-family-owner loans 
originated between 1999 and 2002, compared with 57 percent of the 
low-mod loans that were originated, 55 percent of underserved area 
loans, and 52 percent of the special affordable loans.
    The data in Table A.31a indicate the GSEs' growing market share 
during the heavy refinance years of 2001 and 2002. For example, the 
GSEs accounted for 74 percent of the overall single-family-owner 
market in 2002, and 67-69 percent of the markets covered by the 
three housing goal categories. While this improvement is an 
encouraging trend, there are ample opportunities for the GSEs to 
continue their improvement. Almost one-third of the goals-qualifying 
loans originated during 2002 remained available to the GSEs to 
purchase; there are clearly affordable loans being originated that 
the GSEs can purchase. Furthermore, the GSEs' purchases under the 
housing goals are not limited to new mortgages that are originated 
in the current calendar year. The GSEs can purchase loans from the 
substantial, existing stock of affordable loans held in lenders' 
portfolios, after these loans have seasoned and the GSEs have had 
the opportunity to observe their payment performance. In fact, based 
on Fannie Mae's recent experience, the purchase of seasoned loans 
appears to be one effective strategy for purchasing goals-qualifying 
loans.
    The data in Table A.31a show a strong upward trend from 2000 and 
2001 to 2002 in the GSE share of the single-family-owner market. 
Their share of 2000 financed units in the conventional conforming 
market totaled 48 percent. This increased to 55 percent in 2001 then 
to 74 percent in 2002. The large increase in 2002 can be attributed 
to the relatively low interest rates and heavy refinancing activity 
in 2003. During such a period, the share of fixed rate mortgage 
originations increases relative to adjustable rate mortgages. Due to 
the higher risk associated with fixed rate mortgages, less thrift 
institutions are willing to hold them, and, thus, more are sold to 
the GSEs. As a result, during low interest rate periods, the GSE 
share of mortgages increases.
    Single-Family Rental Market. Single-family rental housing is a 
major source of low-income housing. As discussed in Appendix D, data 
on the size of the primary market for mortgages on these properties 
is limited, but available information indicate that the GSEs are 
much less active in this market than in the single-family owner 
market. HUD estimates that GSE purchases between 1999 and 2002 
totaled only 40 percent of all newly-mortgaged single-family rental 
units that were affordable to low- and moderate-income families.
    As explained in the 2000 Rule, many of these properties are 
``mom-and-pop'' operations, which may not follow financing 
procedures consistent with the GSEs' guidelines. Much of the 
financing needed in this area is for rehabilitation loans on 2-4 
unit properties in older areas, a market in which the GSEs' have not 
played a major role. However, this sector could certainly benefit 
from an enhanced role by the GSEs, and the data in Table A.30 
indicate that there is room for such an enhanced role, as 
approximately two-thirds of this market remains for the GSEs to 
enter.
    Once again, Table A.31a shows a large increase in the GSE share 
of newly-mortgaged units financed in 2002 compared to those financed 
in 2000 and 2001. As described above for the single-family owner 
market, this large increase is due to the large share of fixed-rate 
mortgages, compared to adjustable rate mortgages, originated during 
2002.
    Multifamily Market. Fannie Mae is the largest single source of 
multifamily finance in the United States, and Freddie Mac has made a 
solid reentry into this market over the last nine years. However, 
there are a number of measures by which the GSEs lag the multifamily 
market. For example, the share of GSE resources committed to the 
multifamily purchases falls short of the multifamily proportion 
prevailing in the overall mortgage market. HUD estimates that newly-
mortgaged units in multifamily properties represented almost 15 
percent of all (single-family and multifamily) dwelling units 
financed between 1999 and 2002.\319\ As shown in Table A.30, 
multifamily acquisitions represented 9.5 percent of dwelling units 
financed by the GSEs between 1999 and 2002.
---------------------------------------------------------------------------

    \319\ Based on Table A.30, multifamily properties represented 
14.8 percent of total units financed between 1999 and 2002 (obtained 
by dividing 7,018,044 multifamily units by 47,551,039 ``Total 
Market'' units). Increasing the single-family-owner number in Table 
A.30 by 2,648,757 to account for excluded B&C mortgages increases 
the ``Total Market'' number to 50,199,796, which produces a 
multifamily share of 14.0 percent. See Appendix D for discussion of 
the B&C market.
---------------------------------------------------------------------------

    The GSEs' role in the multifamily market is significantly 
smaller than in single-family. As shown in Table A.30, GSE purchases 
have accounted for 35 percent of newly financed multifamily units 
between 1999 and 2002--a market share much lower than their 61 
percent share of the single-family-owner market. Stated in terms of 
portfolio shares, single-family-owner loans accounted for 83 percent 
of all dwelling units financed by the GSEs during this period, 
versus 75 percent of all units financed in the conventional 
conforming market.
    While it is recognized that the GSEs have been increasing their 
multifamily purchases, a further enlargement of their role in the 
multifamily market seems feasible and appropriate, particularly in 
the affordable (lower rent) end of the market. As noted in Section 
D.3, market participants believe that the GSEs have been 
conservative in their approaches to affordable multifamily lending 
and underwriting.\320\ Certainly the GSEs face a number of 
challenges in better meeting the needs of the affordable multifamily 
market. For example, thrifts and other depository institutions may 
sometimes retain their best loans in portfolio, and the resulting 
information asymmetries may act as an impediment to expanded 
secondary market transaction volume.\321\ However, the GSEs have 
demonstrated that they have the depth of expertise and the financial 
resources to devise innovative solutions to problems in the 
multifamily market. The GSEs can build on their recent records of 
increased multifamily lending and innovative products to make 
further in-roads into the affordable market. As explained in Section 
D.3, the GSEs have the expertise and market presence to push 
simultaneously for market standardization and for programmatic 
flexibility to meet the special needs and circumstances of the 
lower-income portion of the multifamily market.
---------------------------------------------------------------------------

    \320\ Abt Associates, op. cit. (August 2002).
    \321\ The problem of secondary market ``adverse selection'' is 
described in James R. Follain and Edward J. Szymanoski. ``A 
Framework for Evaluating Government's Evolving Role in Multifamily 
Mortgage Markets,'' Cityscape: A Journal of Policy Development and 
Research 1(2), 1995.
---------------------------------------------------------------------------

    As discussed in Appendix D, the GSEs questioned HUD's historical 
estimates of the multifamily market as too high. Section C of 
Appendix D discusses these comments and responds. As indicated in 
Table A.30, multifamily loans accounted for 14.8 percent of all 
financed units in the market, excluding B&C loans. As reported in 
Appendix D, HUD also conducted sensitivity analyses that reduced its 
1999-2002 multifamily shares for the market by approximately two 
percentage points. The results for these lower multifamily market 
shares are reported in Table A.31b (1999-2002 aggregate results) and 
Table A.31c (2000-2002 individual year results). In this case, 1999-
2002 multifamily units decreased from 7,018,044 units to 5,991,036 
units (reducing the multifamily share from 14.8 percent to 12.9 
percent). With these reduced multifamily market numbers, the GSEs' 
share of the multifamily market increased from 35 percent to 41 
percent. The GSEs also accounted for higher shares of the goals-
qualifying multifamily market: 42 percent for low-mod units, 34 
percent for underserved area units, and 37 percent for special 
affordable units. In this case, the GSEs' shares of the overall 
goals-qualifying markets increased as follows: low-mod--from 48 
percent (see right column of Table A.30) to 50 percent (see right 
column

[[Page 63741]]

of Table A.31b); underserved areas--from 48 percent to 49 percent; 
and special affordable--from 41 percent to 43 percent.
    Conclusions. While HUD recognizes that some segments of the 
market may be more challenging for the GSEs than others, the data 
reported in Table A.30 and Tables A.31a-c show that the GSEs have 
ample opportunities to purchase goals-qualifying mortgages. 
Furthermore, if a GSE makes a business decision to not pursue 
certain types of goals-qualifying loans in one segment of the 
market, they are free to pursue goals-qualifying owner and rental 
property mortgages in other segments of the market. As market 
leaders, the GSEs should be looking for innovative ways to pursue 
this business. Furthermore, there is evidence that the GSEs can earn 
reasonable returns on their goals business. The Regulatory Analysis 
that accompanies this final rule provides evidence that the GSEs can 
earn financial returns on their purchases of goals-qualifying loans 
that are only slightly below their return on equity from their 
normal business.

2. Qualitative Dimensions of the GSEs' Ability to Lead the Industry

    This section discusses several qualitative factors that are 
indicators of the GSEs' ability to lead the industry in affordable 
lending. It discusses the GSEs' role in the mortgage market; their 
ability, through their underwriting standards, new programs, and 
innovative products, to influence the types of loans made by private 
lenders; their development and utilization of state-of-the-art 
technology; the competence, expertise and training of their staffs; 
and their financial resources.

a. Role in the Mortgage Market

    The GSEs have played a dominant role in the single-family 
mortgage market. As reported in Section C.3, mortgage purchases by 
the GSEs reached extraordinary levels in 2001-2003. Purchases by 
Fannie Mae stood at $568 billion in 2001 and $848 billion in 2002. 
Freddie Mac's single-family mortgage purchases were $393 billion in 
2001 and $475 billion in 2002. The Office of Federal Housing 
Enterprise Oversight (OFHEO) estimates that the GSEs purchased 40 
percent of newly-originated conventional mortgages in 2001. Total 
GSE purchases, including loans originated in prior years, amounted 
to 46 percent of conventional originations in 2001.
    The dominant position of the GSEs in the mortgage market is 
reinforced by their relationships with other market institutions. 
Commercial banks, mutual savings banks, and savings and loans are 
their competitors as well as their customers--they compete to the 
extent they hold mortgages in portfolio, but at the same time they 
sell mortgages to the GSEs. They also buy mortgage-backed 
securities, as well as the debt securities used to finance the GSEs' 
portfolios. Mortgage bankers sell virtually all of their prime 
conventional conforming loans to the GSEs. Private mortgage insurers 
are closely linked to the GSEs, because mortgages purchased by the 
enterprises that have loan-to-value ratios in excess of 80 percent 
are normally required to be covered by private mortgage insurance, 
in accordance with the GSEs' charter acts.

b. Underwriting Standards for the Primary Mortgage Market

    The GSEs' underwriting guidelines are followed by virtually all 
originators of prime mortgages, including lenders who do not sell 
many of their mortgages to Fannie Mae or Freddie Mac. The guidelines 
are also commonly followed in underwriting ``jumbo'' mortgages, 
which exceed the maximum principal amount which can be purchased by 
the GSEs (the conforming loan limit)--such mortgages eventually 
might be sold to the GSEs, as the principal balance is amortized or 
when the conforming loan limit is otherwise increased. Changes that 
the GSEs have made to their underwriting standards in order to 
address the unique needs of low-income families were discussed in 
Section C.4 of this Appendix. The GSEs' market influence is one 
reason these new, more flexible underwriting standards have spread 
throughout the market. Because the GSEs' guidelines set the credit 
standards against which the mortgage applications of lower-income 
families are judged, the enterprises have a profound influence on 
the rate at which mortgage funds flow to low- and moderate-income 
borrowers and underserved neighborhoods.
    As discussed below, the GSEs' new automated underwriting systems 
are widely used to originate mortgages in today's market. As 
discussed in Sections C.7 and C.8, the GSEs have started adapting 
their underwriting systems for subprime loans and other loans that 
have not met their traditional underwriting standards.

c. State-of-the-Art Technology

    Both GSEs are in the forefront of new developments in mortgage 
industry technology. Automated underwriting and online mortgage 
processing are a couple of the new technologies that have impacted 
the mortgage market, expanding homeownership opportunities. This 
section provides an overview of these new technologies and the 
extent of their use.
    Each enterprise released an automated underwriting system in 
1995--Freddie Mac's ``Loan Prospector'' (LP) and Fannie Mae's 
``Desktop Underwriter'' (DU). During 2001 and 2002, roughly 60 
percent of all newly-originated mortgages the GSEs purchased were 
processed through these systems. Lenders and brokers used LP to 
evaluate 7.3 million loan applications in 2001, 8.2 million in 
2002,\322\ and 9.5 million in 2003. Similarly, DU was used to 
evaluate 8 million loans in 2001, over 10 million in 2002, and 14.8 
million loans in 2003. The GSEs' systems have also been adapted for 
FHA and jumbo loans. Automated underwriting systems are being 
further adapted to facilitate risk-based pricing, which enables 
mortgage lenders to offer each borrower an individual rate based on 
his or her risk. As discussed earlier, concerns about the use of 
automated underwriting and risk-based pricing include the disparate 
impact on minorities and low-income borrowers and the ``black box'' 
nature of the score algorithm.
---------------------------------------------------------------------------

    \322\ This section is based heavily on ``DU and LP Usage 
Continues to Rise,'' in Inside Mortgage Technology published by 
Inside Mortgage Finance, January 27, 2003, page 1-2.
---------------------------------------------------------------------------

    The GSEs are using their state-of-the-art technology in certain 
ways to help expand homeownership opportunities. For example, Fannie 
Mae has developed Fannie Mae Property GeoCoder a computerized 
mapping service offered to lenders, nonprofit organizations, and 
state and local governments to help them determine whether a 
property is located in an area that qualifies for Fannie Mae's 
community lending products designed to increase homeownership and 
revitalization in traditionally underserved areas. In addition, 
eFannieMae.com is Fannie Mae's business-to-business Web site where 
lenders can access product information and important technology 
tools, view upcoming events, and receive news about training 
opportunities. This site receives on average 80,000 visitors per 
week.\323\ Freddie Mac has introduced in recent years Internet-based 
debt auctions, debt repurchase operations, and debt exchanges. These 
mechanisms benefit investors by providing more uniform pricing, 
greater transparency and faster price discovery--all of which makes 
Freddie Mac debt more attractive to investors and reduces the cost 
of funding mortgages.\324\ In addition, Freddie Mac has provided 
automated tools for lenders to identify and work with borrowers most 
likely to encounter problems making their mortgage payments. 
EarlyIndicator has become the industry standard for default 
management technology. It can reduce the consequences of mortgage 
delinquency for borrowers, servicers and investors.\325\
---------------------------------------------------------------------------

    \323\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
pp. 10-11.
    \324\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
14.
    \325\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 52.
---------------------------------------------------------------------------

    The GSEs are also expanding homeownership opportunities through 
the use of the Internet in processing mortgage originations. New 
online mortgage originations reached $267.6 billion in the first 
half of 2002, compared with $97 billion for the first six months of 
2001. The 2002 six-month volume comprised 26.5 percent of the 
estimated $1.01 trillion in total mortgage originations for the same 
time period.\326\ Freddie Mac made Loan Prospector on the Internet 
service available to lenders for their retail operations. Freddie 
Mac also adopted the mortgage industry's XML (extensible markup 
language) data standard, which is integral to streamlining and 
simplifying Internet-based transactions. In addition, Congress 
enacted legislation that allows the use of electronic signature in 
contracts in 2001, making a completely electronic mortgage 
transaction possible. With the use of electronic signatures, 
electronic mortgages are expected to improve the mortgage process, 
further reducing origination and servicing costs. In October 2000, 
Freddie Mac

[[Page 63742]]

purchased its first electronic mortgage under the new law.
---------------------------------------------------------------------------

    \326\ Inside Mortgage Finance, ``Online Volume Comprises One-
Fourth of Total Originations in First Half '02,'' September 20, 
2002, p. 8.
---------------------------------------------------------------------------

    The GSEs also offer a variety of other online tools and 
applications that have the potential to make the mortgage loan 
process more cost effective and efficient for lenders. Freddie Mac, 
for example, has launched dontborrowtrouble.com, which contains 
information on local anti-predatory lending campaigns, consumer tips 
on avoiding predatory lending, and information on how to start a 
local campaign and obtain additional resources.\327\ Fannie Mae 
offers ``HomeBuyer Funds Finder,'' a one-stop online resource 
designed for lenders and other housing professionals, enables users 
to access a database of local housing subsidy programs available for 
low- and moderate-income borrowers. In 2002, the HomeBuyer Funds 
Finder Web site received over 24,500 hits.\328\ ``Home Counselor 
Online'' provides homeownership counselors with the necessary tools 
to help consumers financially prepare to purchase a home. In 2003, 
641 counselors representing over 2,000 organizations used Home 
Counselor Online.\329\ ``True Cost Calculator 2.0'' is designed to 
help homebuyers make informed home purchase decisions by helping 
them compare loan products and prices. Over 60 Fannie Mae partners 
officer the True Cost Calculator through their Web sites and a 
Spanish version is also available on Univision.com.\330\ A more 
complete list of Fannie Mae's online tool and applications can be 
found in its Annual Housing Activities Report. In 2002, Fannie Mae's 
total eBusiness volume was $1.1 trillion, up from $800 billion in 
2000.\331\
---------------------------------------------------------------------------

    \327\ Freddie Mac, Opening Doors for America's Families: Freddie 
Mac's Annual Housing Activities Report for 2003, March 15, 2004, p. 
38.
    \328\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 12.
    \329\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
p. 13.
    \330\ Fannie Mae, 2003 Annual Housing Activities Report, 2004, 
p. 13.
    \331\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 10.
---------------------------------------------------------------------------

d. Staff Resources

    Both Fannie Mae and Freddie Mac are well-known throughout the 
mortgage industry for the expertise of their staffs in carrying out 
their current programs, conducting basic and applied research 
regarding mortgage markets, developing innovative new programs, and 
undertaking sophisticated analyses that may lead to new programs in 
the future. The leaders of these corporations frequently testify 
before Congressional committees on a wide range of housing issues, 
and both GSEs have developed extensive working relationships with a 
broad spectrum of mortgage market participants, including various 
nonprofit groups, academics, and government housing authorities. 
Federal agencies and foreign governments and businesses seek them 
out for advice and consultation because of their expertise. The role 
that the GSEs have played in spreading the use of technology 
throughout the mortgage market reflects the enormous expertise of 
their staff.

e. Financial Strength

    Fannie Mae. The benefits that accrue to the GSEs because of 
their GSE status, as well as their solid management, have made them 
two of the nation's most profitable businesses. Fannie Mae's net 
income was $3.9 billion in 1999, $4.4 billion in 2000, $5.9 billion 
in 2001, $4.6 billion in 2002,\332\ and $7.9 billion in 2003.\333\ 
Fannie Mae's return on equity averaged 24.0 percent over the 1995-99 
period--far above the rates achieved by most financial corporations. 
Fannie Mae's return on equity was 26.0 percent in 2003, while this 
represented no change from 2002, it was an increase of 3 percent 
over 2001.\334\ In 2003, Fannie Mae's total stockholders' equity 
increased by 37% to $22.373 million, core business earnings grew by 
14 percent ($7.3 billion), credit losses increased by $42 million to 
$111 million with the resulting credit loss ratio at .006% 
(represents credit losses divided by average single family mortgage 
credit book of business) and taxable equivalent revenues grew by 24 
percent.\335\
---------------------------------------------------------------------------

    \332\ The 22% decrease in Fannie Mae's 2002 net income resulted 
primarily from a $4.508 billion increase in purchased options 
expense, which occurred due to an increase in the notional amount of 
purchased options outstanding and the declining interest rate 
environment. Recorded purchased options expense for 2001 was only 
$37 million by comparison. Fannie Mae 2002 Annual Report, 2003, p. 
23.
    \333\ Fannie Mae, 2003 Annual Report, ``Financial Highlights.''
    \334\ Fannie Mae, 2003 Annual Report, ``Financial Highlights.''
    \335\ Fannie Mae, 2003 Annual Report, ``Financial Highlights'' 
and United States Securities and Exchange Commission form 10-K, p. 
108.
---------------------------------------------------------------------------

    Fannie Mae's basic net earnings per common share increased from 
$3.75 in 1999 to $7.93 in 2003, dividends per common share have 
increased from $.96 in 1998 to $1.68 in 2003, a 27% increase over 
2002, and operating earnings per diluted common share increased from 
2002 to 2003 by 71% to $7.72.\336\
---------------------------------------------------------------------------

    \336\ Fannie Mae, 2003 Annual Report to Shareholders, Financial 
Highlights and Financial Information.
---------------------------------------------------------------------------

    Freddie Mac. Freddie Mac has shown similar trends. Freddie Mac's 
net income was $3.158 billion in 2001, $10.090 billion in 2002, and 
$4.891 billion in 2003, and total stockholder's equity increased by 
10% over 2002 to $31.562 billion. Freddie Mac's return on equity 
averaged 23.4 percent over the 1995-1999 period, also well above the 
rates achieved by most financial corporations. Credit losses 
increased by $8 million to $82 million with the resulting credit 
loss ratio at 0.7 (represents annualized credit losses divided by 
average total mortgage portfolio). Basic earnings per common share 
(after cumulative effect of change in accounting principles, net of 
taxes) was $4.25 in 2001, $14.23 in 2002 and $6.80 in 2003. 
Dividends per common share have increased from 0.80 in 2001 to $1.04 
in 2003, an 18% increase over 2002, and operating earnings per 
diluted common share (after cumulative effect of change in 
accounting principles, net of taxes) decreased from 2002 to 2003 by 
$7.39 to $6.79.\337\
---------------------------------------------------------------------------

    \337\ Freddie Mac, Consolidated Statements of Income 2003 and 
Freddie Mac Core Tables 2003.
---------------------------------------------------------------------------

    Other Indicators. Additional indicators of the strength of the 
GSEs are provided by various rankings of American corporations. 
Business Week has reported that among Standard & Poor's performance 
ranking of 500 companies in 2004, Fannie Mae was ranked 117, down 
from 91 in 2003 and Freddie Mac was listed as ``INC'' for 2004 and 
16th for 2003. Additionally, Fannie Mae was ranked as 29th in 
overall market value, 17th in sales and 9th in profits, and Freddie 
Mac was ranked 59th in market value and ``NR'' in sales and 
profits.\338\ According to Fortune's annual listing of the 500 
largest U.S. Corporations, Fannie Mae was ranked 20th in 2003, down 
from 16th in 2002, and Freddie Mac was ``displaced'' from the 
ranking in 2003, but ranked 32nd in 2002. Additionally, Fannie Mae 
ranked 11th for most profitable companies, 3rd for revenues per 
employee, and in the ``Diversified Financials'' category, they 
ranked 2nd out of 12 companies.\339\ And, according to Fortune's 
Global 500 listing of the world's largest corporations, Fannie Mae 
ranked 56th in 2003, (ranking 17th in highest profits) down from 
45th in 2002, and Freddie Mac ranked 104th in 2003, down from 90th 
in 2002.\340\
---------------------------------------------------------------------------

    \338\ ``The Standard and Poor's Five Hundred: Performance 
Ranking S&P 500'', Business Week, April 5, 2004, p. 127.
    \339\ ``Fortune 500 Largest U.S. Corporations,'' Fortune, April 
5, 2004, p. F-1.
    \340\ ``Fortune 500 Largest U.S. Corporations,'' Fortune, July 
26, 2004, p. 159.
---------------------------------------------------------------------------

f. Conclusion About Leading the Industry

    In light of these considerations, the Secretary has determined 
that the GSEs have the ability to lead the industry in making 
mortgage credit available for low- and moderate-income families.

H. Factor 6: The Need to Maintain the Sound Financial Condition of 
the GSEs

    HUD has undertaken a separate, detailed economic analysis of 
this final rule, which includes consideration of (a) the financial 
returns that the GSEs earn on low- and moderate-income loans and (b) 
the financial safety and soundness implications of the housing 
goals. Based on this economic analysis and the Office of Federal 
Housing Enterprise Oversight review, HUD concludes that the goals 
raise minimal, if any, safety and soundness concerns.

I. Determination of the Low- and Moderate-Income Housing Goals

    The annual goal for each GSE's purchases of mortgages financing 
housing for low- and moderate-income families is being established 
at 52 percent of eligible units financed in each of calendar years 
2005, 53 percent in 2006, 55 percent in 2007, and 56 percent in 
2008. This goal will remain in effect thereafter, unless changed by 
the Secretary prior to that time. In addition, a low- and moderate-
income subgoal of 45 percent in 2005, 46 percent in 2006, and 47 
percent in both 2007 and 2008 is being established for the GSEs' 
acquisitions of single-family-owner home purchase loans in 
metropolitan areas. This subgoal is designed to encourage the GSEs 
to lead the primary market in offering homeownership

[[Page 63743]]

opportunities to low- and moderate-income families. The Secretary's 
consideration of the six statutory factors that led to the choice of 
these goals is summarized in this section.

1. Housing Needs and Demographic Conditions

    Affordability Problems. Data from the 2000 Census and the 
American Housing Surveys demonstrate that there are substantial 
housing needs among low- and moderate-income families. Many of these 
households are burdened by high homeownership costs or rent payments 
and will likely continue to face serious housing problems. There is 
evidence of persistent housing problems for Americans with the 
lowest incomes. Since 1977, the percentage of U.S. households with 
worst case needs has hovered around five percent, with the worst 
year being 1983 (6.03 percent) and the best year being 1999 (4.72 
percent). The proportion in 2001 was 4.77 percent, which is not 
significantly different from the 1999 figure. HUD's analysis of 
American Housing Survey data reveals that, in 2001, 5.1 million 
unassisted very-low income renter households had ``worst-case'' 
housing needs, defined as housing costs greater than 50 percent of 
household income or severely inadequate housing. Among these 
households, 90 percent had a severe rent burden, 6 percent lived in 
severely inadequate housing, and 4 percent suffered from both 
problems. Among the 34 million renters in all income categories, 6.3 
million (19 percent) had a severe rent burden and over one million 
renters (3 percent) lived in housing that was severely inadequate.
    Demographic Trends. Changing population demographics will result 
in a need for the primary and secondary mortgage markets to meet 
nontraditional credit needs, respond to diverse housing preferences 
and overcome information and other barriers that many immigrants and 
minorities face. It is projected that there will be 1.2 million new 
households each year over the next decade. The aging of the baby-
boom generation and the entry of the baby-bust generation into prime 
home buying age will have a dampening effect on housing demand. 
However, the continued influx of immigrants will increase the demand 
for rental housing, while those who immigrated during the 1980s and 
1990s will be in the market for owner-occupied housing. Immigrants 
and other minorities--who accounted for nearly 40 percent of the 
growth in the nation's homeownership rate over the past five years--
will be responsible for almost two-thirds of the growth in the 
number of new households over the next ten years. Non-traditional 
households have become more important, as overall household 
formation rates have slowed. With later marriages, divorce, and non-
traditional living arrangements, the fastest growing household 
groups have been single-parent and single-person households. As 
these demographic factors play out, the overall effect on housing 
demand will likely be sustained growth and an increasingly diverse 
household population from which to draw new renters and homeowners. 
According to the National Association of Homebuilders, annual 
housing demand will average from 1.84 to 2.19 million units over the 
next decade.\341\
---------------------------------------------------------------------------

    \341\ National Association of Home Builder, 2004 Spring 
Construction Forecast Conference, April 21, 2004.
---------------------------------------------------------------------------

    Growth in Single-Family Affordable Lending. Many younger, 
minority and lower-income families did not become homeowners during 
the 1980s due to the slow growth of earnings, high real interest 
rates, and continued house price increases. Over the past ten years, 
economic expansion, accompanied by low interest rates and increased 
outreach on the part of the mortgage industry, has improved 
affordability conditions for these families. As this appendix has 
explained, there has been a ``revolution in affordable lending'' 
that has extended homeownership opportunities to historically 
underserved households. The mortgage industry has offered more 
customized mortgage products, more flexible underwriting, and 
expanded outreach to low-income and minority borrowers. Fannie Mae 
and Freddie Mac have been a big part of this ``revolution in 
affordable lending''. HMDA data suggest that the industry and GSE 
initiatives are increasing the flow of credit to underserved 
borrowers. Between 1993 and 2003, conventional loans to low-income 
and minority families increased at much faster rates than loans to 
upper-income and non-minority families. Thus, the 1990s and the 
early part of the current decade have seen the development of a 
strong affordable lending market.
    Disparities in Housing and Mortgage Markets. Despite this strong 
growth in affordable lending, serious disparities in the nation's 
housing and mortgage markets remain. The homeownership rate for 
African-American and Hispanic households is about 25 percentage 
points below that of white households. In addition to low income, 
barriers to homeownership that disproportionately affect minorities 
and immigrants include: lack of capital for down payment and closing 
costs; poor credit history; lack of access to mainstream lenders; 
little understanding of the homebuying process; and continued 
discrimination in housing markets and mortgage lending. With respect 
to the latter, a recent HUD-sponsored study of discrimination in the 
rental and owner markets found that while differential treatment 
between minority and white home seekers had declined over the past 
ten years, it continued at an unacceptable level in the year 2000. 
In addition, disparities in mortgage lending continued across the 
nation in 2003, when the loan denial rate for African-American 
applicants was almost three times that for white applicants, even 
after controlling for income of the applicant. HUD studies also show 
that African-Americans and Hispanics are subject to discriminatory 
treatment during the pre-qualification process of applying for a 
mortgage.
    Single-Family Mortgage Market. Heavy refinancing due to low 
interest rates increased single-family mortgage originations to 
record levels during 2001-2003. Demographic forces, industry 
outreach, and low interest rates also kept lending for home purchase 
at record levels as well. As noted above, the potential homeowner 
population over the next decade will be highly diverse, as growing 
demand from immigrants and minorities are expected to sustain the 
home purchase market, as our population ages. Single-family housing 
starts are expected to continue in the 1.65-1.70 million range over 
the next few years. Refinancing of existing mortgages, which 
accounted for about 60 percent of originations during 2001-2003 is 
expected to return to more normal levels. As this Appendix has 
explained, the GSEs will continue to play a dominant role in the 
single-family market and will both impact and be affected by major 
market developments such as the growth in subprime lending and the 
increasing use automated underwriting.
    Multifamily Mortgage Market. The market for financing of 
multifamily apartments has grown to record volumes. The favorable 
long-term prospects for apartments, combined with record low 
interest rates, have kept investor demand for apartments strong and 
supported property prices. As explained above, Fannie Mae and 
Freddie Mac have been among those boosting volumes and introducing 
new programs to serve the multifamily market. The long run outlook 
for the multifamily rental market is sustained, moderate growth, 
based on favorable demographics. The minority population, especially 
Hispanics, provides a growing source of demand for affordable rental 
housing. ``Lifestyle renters'' (older, middle-income households) are 
also a fast growing segment of the rental population. However, 
provision of affordable housing will continue to challenge suppliers 
of multifamily rental housing and policy makers at all levels of 
government. Low incomes combined with high housing costs define a 
difficult situation for millions of renter households. Housing cost 
reductions are constrained by high land prices and construction 
costs in many markets. Government action--through land use 
regulation, building codes, and occupancy standards--are major 
contributors to those high costs. In addition to fewer regulatory 
barriers and costs, multifamily housing would benefit from more 
favorable public attitudes. Higher density housing is a potentially 
powerful tool for preserving open space, reducing sprawl, and 
promoting transportation alternatives to the automobile. The 
recently heightened attention to these issues may increase the 
acceptance of multifamily rental construction to both potential 
customers and their prospective neighbors.

2. Past Performance of the GSEs

    This section reviews the low- and moderate-income performance of 
Fannie Mae and Freddie Mac. It first reviews the GSEs' performance 
on the Low- and Moderate-Income Goal, then reviews findings from 
Section E.2 regarding the GSEs' purchases of home loans for 
historically underserved families and their communities. Finally, it 
reviews findings from Section G concerning the GSEs' presence in 
owner and rental markets.

a. Housing Goals Performance

    In the October 2000 rule, the low- and moderate-income goal was 
set at 50 percent

[[Page 63744]]

for 2001-03. Effective on January 1, 2001, several changes in 
counting requirements came into effect for the low- and moderate-
income goal, as follows: (a) ``Bonus points'' (double credit) for 
purchases of mortgages on small (5-50 unit) multifamily properties 
and, above a threshold level, mortgages on 2-4 unit owner-occupied 
properties; (b) a ``temporary adjustment factor'' (1.35 units 
credit) for Freddie Mac's purchases of mortgages on large (more than 
50 units) multifamily properties; (c) changes in the treatment of 
missing data; and (d) a procedure for the use of imputed or proxy 
rents for determining goal credit for multifamily mortgages. Fannie 
Mae's performance was 51.5 percent in 2001, 51.8 percent in 2002, 
and 52.3 percent in 2003; Freddie Mac's performance was 53.2 percent 
in 2001, 50.5 percent in 2002, and 51.2 percent in 2003--thus both 
GSEs surpassed this higher goal in all three years.
    Counting requirements (a) and (b) expired at the end of 2003, 
while (c) and (d) will remain in effect after that. If this counting 
approach--without the bonus points and the ``temporary adjustment 
factor''--had been in effect in 2000 and 2001, and the GSEs had 
purchased the same mortgages that they actually did purchase in both 
years, then Fannie Mae's performance would have been 51.3 percent in 
2000, 49.2 percent in 2001, 49.0 percent in 2002, and 48.7 percent 
in 2003. Freddie Mac's performance would have been 50.6 percent in 
2000, 47.7 percent in 2001, 46.1 percent in 2002, and 44.6 percent 
in 2003. Thus, both Fannie Mae and Freddie Mac would have surpassed 
the low- and moderate-income goal of 50 percent in 2000 and fallen 
short in 2001 through 2003. (See Figure A.1.)
BILLING CODE 4210-27-P

[[Page 63745]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.044


[[Page 63746]]



b. Single-Family Affordable Lending Market

    The GSEs have played a major role in the single-family mortgage 
market over the past ten years. Their purchases of single-family-
owner mortgages accounted for 61 percent of all mortgages originated 
in the single-family conventional conforming market between 1999 and 
2002. Their underwriting and purchase guidelines are market 
standards, used in all segments of the mortgage market. The GSEs 
have worked to improve their affordable lending record--they have 
introduced new low-downpayment products targeted at lower-income 
families; they have customized their underwriting standards to 
recognize the unique needs of immigrant and minority families; and, 
they have entered into numerous partnerships with lenders and non-
profit groups to reach out to underserved populations. The 
enterprises' role in the mortgage market is also reflected in their 
use of cutting edge technology, such as the development of Loan 
Prospector and Desktop Underwriter, the automated underwriting 
systems developed by Freddie Mac and Fannie Mae, respectively. Both 
GSEs are also entering new and challenging fields of mortgage 
finance, such as purchasing subprime mortgages.
    Despite these efforts and the overall gains in goal performance, 
the Department remains concerned about the GSEs' support of home 
lending for the lower-income end of the market and for first-time 
homebuyers. The shares of the GSEs' purchases are too low, 
particularly for underserved areas and groups such as minority 
first-time homebuyers.
    This appendix included a comprehensive analysis of the GSEs' 
performance in funding home purchase mortgages for families and 
communities that historically have not been well served by the 
mortgage market. The following findings are offered with respect to 
the GSEs' acquisitions of home purchase loans that qualify for the 
three housing goals (special affordable and underserved areas as 
well as low- and moderate-income) and their acquisitions of first-
time homebuyer loans:
     Fannie Mae and Freddie Mac have both improved their 
support for the single-family affordable lending market over the 
past eleven years, but historically over past periods, such as 1993-
2003, 1996-2003, and 1999-2003, they have lagged the overall 
conventional conforming market in providing affordable loans to 
lower-income borrowers and underserved areas. This finding is based 
on HUD's analysis of GSE and HMDA data and on numerous studies by 
academics and research organizations.
     The GSEs have shown different patterns of mortgage 
purchases. Except for two years (1999 and 2000), Fannie Mae has 
performed better than Freddie Mac since 1993 on all three goals-
qualifying categories--low-mod, special affordable, and underserved 
areas. As a result, the percentage of Freddie Mac's purchases 
benefiting historically underserved families and their neighborhoods 
has been less than the corresponding shares of total market 
originations, while Fannie Mae's purchases have been somewhat closer 
to the patterns of originations in the primary market.
     The above patterns can be seen by the following 
percentage shares of home purchase loans that qualified for the 
three housing goals between 1996 and 2003:

------------------------------------------------------------------------
                                     Special                 Underserved
                                    affordable    Low-Mod       areas
                                    (percent)    (percent)    (percent)
------------------------------------------------------------------------
Freddie Mac......................         13.2         40.3         22.0
Fannie Mae.......................         14.1         42.2         24.0
Market (w/o B&C).................         15.9         43.6         25.7
------------------------------------------------------------------------

     During 2001-2003, Fannie Mae improved its performance 
enough to lead the special affordable and low-moderate income 
markets, although it continued to lag the underserved areas market. 
During 2001-2003, Freddie Mac lagged the conventional conforming 
market on all three goals-qualifying categories; see Figure A.2 for 
the low- and moderate-income shares for Fannie Mae, Freddie Mac and 
the market.

[[Page 63747]]

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[[Page 63748]]


     Both Fannie Mae and Freddie lag the conventional 
conforming market in funding first-time homebuyers, and by a rather 
wide margin. Between 1999 and 2001, first-time homebuyers accounted 
for 27 percent of each GSE's purchases of home loans, compared with 
38 percent for home loans originated in the conventional conforming 
market.
     The GSEs also account for a very small share of the 
market for important groups such as minority first-time homebuyers. 
Considering the total mortgage market (both government and 
conventional loans), it is estimated that the GSEs purchased only 14 
percent of loans originated between 1999 and 2001 for African-
American and Hispanic first-time homebuyers, or one-third of their 
share (42 percent) of all home purchase loans originated during that 
period. Considering the conventional conforming market and the same 
time period, it is estimated that the GSEs purchased only 31 percent 
of loans originated for African-American and Hispanic first-time 
homebuyers, or approximately one-half of their share (57 percent) of 
all home purchase loans in that market.
    To summarize, the Department's analysis suggests that, except 
for Fannie Mae's recent performance on the special affordable and 
low-moderate categories, the GSEs have not been leading the single-
family-owner market in purchasing goals-qualifying and first-time 
homebuyer loans. Freddie Mac, in participation, continues to lag the 
market on all categories considered. There is room for Freddie Mac, 
as well as Fannie Mae, to further improve their performance in 
purchasing affordable loans in the underserved portion of the 
market, particularly in the minority first-time homebuyer market. 
Evidence suggests that there is a significant population of 
potential homebuyers who might respond well to aggressive outreach 
by the GSEs--immigrants and minorities, in particular, are expected 
to be a major source of future homebuyers. Furthermore, studies 
indicate the existence of a large untapped pool of potential 
homeowners among the rental population. Indeed, the GSEs' recent 
experience with new outreach and affordable housing initiatives is 
important confirmation of this potential. To move the GSEs into a 
leadership position, the Department is establishing three subgoals 
for home purchase loans that qualify for the three housing goals. 
The low- and moderate-income subgoal is discussed in Section I.3 
below.

c. Overall Market Shares

    This appendix also included an analysis of the GSEs' role in the 
overall (owner and rental) conventional conforming mortgage market. 
While GSE mortgage purchases represented 55 percent of total 
dwelling units financed between 1999 and 2002, they represented 
smaller shares of the three goals-qualifying markets: 48 percent of 
housing units financed for both low- and moderate-income families 
and properties located in underserved areas; and 41 percent of units 
financed for the very-low-income and other families that qualify as 
special affordable. (See Figure A.3.) In other words, the GSEs 
accounted for approximately 50 percent or less of the single-family 
and multifamily units financed in the goals-qualifying markets. This 
market share analysis suggests that there is room for the GSEs to 
increase their purchases in these goals-qualifying markets.
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[[Page 63750]]

    The market analysis also examined the GSEs' presence in the 
owner-occupied home purchase mortgage and rental property sectors of 
the mortgage market: single-family owner (a 61 percent share for the 
GSEs between 1999 and 2002) and single-family rental and multifamily 
rental (a combined rental share of 37 percent). The GSEs, and 
particularly Freddie Mac, have historically played a smaller role in 
the market financing rental properties, as compared with their role 
in the owner market. Fannie Mae and Freddie Mac have recently 
increased their purchases of these mortgages, but their purchases 
totaled only 37 percent of the rental units that received financing 
between 1999 and 2002.\342\ A further increased presence by Fannie 
Mae and Freddie Mac would bring lower interest rates and liquidity 
to this market, as well as improve their housing goals performance.
---------------------------------------------------------------------------

    \342\ As shown in Table A.31b, the GSEs' share of the rental 
market increases to 41 percent when a lower multifamily share is 
assumed in the market analyses.
---------------------------------------------------------------------------

d. The GSEs' Purchases of Multifamily Mortgages

    Fannie Mae and, especially, Freddie Mac have rapidly expanded 
their presence in the multifamily mortgage market in the period 
since the passage of FHEFSSA. The Senate report on this legislation 
in 1992 referred to the GSEs' activities in the multifamily arena as 
``troubling,'' citing Freddie Mac's September 1990 suspension of its 
purchases of new multifamily mortgages and criticism of Fannie Mae 
for ``creaming'' the market.\343\
---------------------------------------------------------------------------

    \343\ Senate Report 102-282, May 15, 1992, p. 36.
---------------------------------------------------------------------------

    Freddie Mac has successfully rebuilt its multifamily acquisition 
program, as shown by the increase in its purchases of multifamily 
mortgages: from $27 million in 1992 to $3 billion in 1997 and then 
to approximately $7 billion during the next three years (1998 to 
2000), before rising further to $11.9 billion in 2001, $13.3 billion 
in 2002, and $21.6 billion in 2003. Multifamily properties accounted 
for 10.3 percent of all dwelling units (both owner and rental) 
financed by Freddie Mac during 2003. Concerns regarding Freddie 
Mac's multifamily capabilities no longer constrain their performance 
with regard to low- and moderate-income families.
    Fannie Mae never withdrew from the multifamily market, but it 
has also stepped up its activities in this area substantially, with 
multifamily purchases rising from $3.0 billion in 1992 to $9.4 
billion in 1999, $18.7 billion in 2001, $18.3 billion in 2002, and 
$33.3 billion in 2003. Multifamily units as a share of all dwelling 
units (both owner and rental) financed by Fannie Mae varied in the 
10-13 percent range between 1999 and 2001, before falling to 7.3 
percent during heavy refinancing year of 2002 and 8 percent in 2003.
    The increased purchases of multifamily mortgages by Fannie Mae 
and Freddie Mac have major implications for the Low- and Moderate-
Income Housing Goal, since a very high percentage of multifamily 
units have rents which are affordable to low- and moderate-income 
families. However, the potential of the GSEs to lead the multifamily 
mortgage industry has not been fully developed. As reported earlier 
in Tables A.30 and A.31b, the GSEs' purchases between 1999 and 2002 
accounted for 35-41 percent of the multifamily units that received 
financing during this period. Certainly there are ample 
opportunities and room for expansion of the GSEs' share of the 
multifamily mortgage market. The GSEs' size and market position 
between loan originators and mortgage investors makes them the 
logical institutions to identify and promote needed innovations and 
to establish standards that will improve market efficiency. As their 
role in the multifamily market continues to grow, the GSEs will have 
the knowledge and market presence to push simultaneously for 
standardization and for programmatic flexibility to meet special 
needs and circumstances, with the ultimate goal of increasing the 
availability and reducing the cost of financing for affordable and 
other multifamily rental properties.

3. Ability to Lead the Single-Family-Owner Market: A Low- and Moderate-
Income Subgoal

    As discussed in Section E, the Department is proposing to 
establish a subgoal of 45 percent for each GSE's purchases of home 
purchase loans for low- and moderate-income families in the single-
family-owner market of metropolitan areas for 2005, with the subgoal 
rising to 46 percent in 2006 and 47 percent in 2007 and 2008. The 
purpose of this subgoal is to encourage the GSEs to improve their 
acquisitions of home purchase loans for lower-income families and 
first-time homebuyers who are expected to enter the homeownership 
market over the next few years. If the GSEs meet this goal, they 
will be leading the primary market by approximately one percentage 
point in 2005 and by three percentage points in 2007 and 2008, based 
on the income characteristics of home purchase loans reported in 
HMDA. Between 2002 and 2003, HMDA data show that low- and moderate-
income families accounted for an (unweighted) average of 44.1 
percent of single-family-owner loans originated in the conventional 
conforming market of metropolitan areas. (The market and GSE data 
reported in this paragraph are based on ``projected'' data that 
account for new Census geography and the new OMB metropolitan area 
definitions; see Table A.17b.) Loans in the B&C portion of the 
subprime market are not included in these averages. To reach the 45-
percent (47-percent) subgoal, Freddie Mac would have to improve its 
performance by 0.8 (2.8) percentage points over its 2003 
performance. Fannie Mae would have to keep up its high level (47.5 
percent) of performance during 2003. The approach taken is for the 
GSEs to obtain their leadership position by staged increases in the 
low-mod subgoal; this will enable the GSEs to take new initiatives 
in a correspondingly staged manner to achieve the new subgoal each 
year. Thus, the increases in the low-mod subgoal are sequenced so 
that the GSEs can gain experience as they improve and move toward 
the new higher subgoal targets.
    As explained in Section E.9, the subgoal applies only to the 
GSEs' purchases in metropolitan areas because reliable market data 
for non-metropolitan areas are not available from HMDA. The 
Department is also setting home purchase subgoals for the other two 
goals-qualifying categories, as follows: 17-18 percent for special 
affordable loans and 32-34 percent for underserved area loans (also 
called Geographically Targeted loans).
    The Department considered the following factors when setting the 
subgoal for low- and moderate-income loans.
    (a) The GSEs have the ability to lead the market. The GSEs have 
the ability to lead the primary market for single-family-owner 
loans, which is the ``bread-and-butter'' of their business. They 
both have substantial experience in this market, which means there 
are no issues as whether or not the GSEs have yet penetrated the 
market, as there are with the single-family rental and multifamily 
markets. Both GSEs have not only been operating in the owner market 
for years, they have been the dominant players in that market, 
funding 61 percent of the single-family-owner mortgages financed 
between 1999 and 2002. As discussed in Section G, their underwriting 
guidelines are industry standards and their automated mortgage 
systems are widely used throughout the mortgage industry. Through 
their new downpayment and subprime products, and their various 
partnership initiatives, the GSEs have shown that they have the 
capacity to reach out to lower-income families seeking to buy a 
home. Both Fannie Mae and Freddie Mac have the staff expertise and 
financial resources to make the extra effort to lead the primary 
market in funding single-family-owner mortgages for low- and 
moderate-income mortgages, as well for special affordable and 
undeserved area mortgages.
    (b) GSEs' Performance Relative to the Market. Even though the 
GSEs have had the ability to lead the home purchase market, their 
past average performance (1993-2003, 1996-2003, and 1999-2003) has 
been below market levels. During 2002 and 2003, Fannie Mae improved 
its performance enough to lead the low-mod market for home purchase 
loans, but Freddie Mac, although it also improved its performance 
during this recent period, continues to lag behind the primary 
market. The subgoals will ensure that Fannie Mae maintains and 
further improves its above-market performance and that Freddie Mac 
not only erases its current gap with the market but also takes a 
leadership position as well. With respect to the GSEs' historical 
performance, low- and moderate-income mortgages accounted for 40.3 
(42.6) percent of Freddie Mac's purchases during 1996-2003 (1999-
2003), for 42.2 (43.6) percent of Fannie Mae's purchases, and for 
43.6 (44.1) percent of primary market originations (excluding B&C 
loans). The type of improvement needed for Freddie Mac to meet this 
new low-mod subgoal was demonstrated by Fannie Mae during 2001-2003, 
as Fannie Mae increased its low-mod purchases from 40.8 percent of 
its single-family-owner business in 2000 to 45.3 percent in 2002 
and47.0 percent in 2003. (As noted above, Fannie Mae's 2003 
performance was slightly higher at 47.5 percent when measured based 
on the new 2000 Census geography and new OMB definitions.)

[[Page 63751]]

    (c) Disparities in Homeownership and Credit Access Remain. There 
remain troublesome disparities in our housing and mortgage markets, 
even after the ``revolution in affordable lending'' and the growth 
in homeownership that has taken place since the mid-1990s. The 
homeownership rate for African-American and Hispanic households 
remains 25 percentage points below that of white households. 
Minority families face many barriers in the mortgage market, such as 
lack of capital for down payment and lack of access to mainstream 
lenders (see above). Immigrants and minorities are projected to 
account for almost two-thirds of the growth in the number of new 
households over the next ten years. As emphasized throughout this 
Appendix, changing population demographics will result in a need for 
the primary and secondary mortgage markets to meet nontraditional 
credit needs, respond to diverse housing preferences and overcome 
information and other barriers that many immigrants and minorities 
face. The GSEs have to increase their efforts in helping these 
families because so far they have played a surprisingly small role 
in serving minority first-time homebuyers. It is estimated that the 
GSEs accounted for 46.5 percent of all (both government and 
conventional) home loans originated between 1999 and 2001; however, 
they accounted for only 14.3 percent of home loans originated for 
African-American and Hispanic first-time homebuyers. Within the 
conventional conforming market, it is estimated that the GSEs 
purchased only 20 percent of loans originated for African-American 
and Hispanic first-time homebuyers, even though they accounted for 
57 percent of all home purchase loans in that market. A subgoal for 
home purchase loans should increase the GSEs' efforts in important 
sub-markets such as the one for minority first-time homebuyers.
    (d) There are ample opportunities for the GSEs to improve their 
performance. Low- and moderate-income loans are available for the 
GSEs to purchase, which means they can improve their performance and 
lead the primary market in purchasing loans for borrowers with less-
than-median income. Three indicators of this have already been 
discussed. First, Sections B and C of this appendix and Appendix D 
explain that the affordable lending market has shown an underlying 
strength over the past few years that are unlikely to vanish 
(without a significant increase in interest rates or a decline in 
the economy). The low-mod share of the home purchase market has 
averaged 43.6 percent since 1996 and annually has ranged from 42.1 
percent to 44.8 percent. Second, the market share data reported in 
Table A.30 of Section G demonstrate that there are newly-originated 
low- and moderate-income loans available each year for the GSEs to 
purchase. As noted above, the GSEs have only a minimal presence in 
special sub-markets such the minority first-time homebuyer market, 
which suggests there are ample opportunities available for the GSEs 
to increase their purchases of loans for low- and moderate-income 
families. Finally, the GSEs' purchases under the subgoal are not 
limited to new mortgages that are originated in the current calendar 
year. The GSEs can purchase loans from the substantial, existing 
stock of affordable loans held in lenders' portfolios, after these 
loans have seasoned and the GSEs have had the opportunity to observe 
their payment performance. In fact, based on Fannie Mae's recent 
experience, the purchase of seasoned loans appears to be one useful 
strategy for purchasing goals-qualifying loans.
    For the reasons given above, the Secretary believes that the 
GSEs can do more to raise the low- and moderate-income shares of 
their mortgages on these properties. This can be accomplished by 
building on various programs that the enterprises have already 
started, including (1) their partnership and outreach efforts, (2) 
their incorporation of greater flexibility into their underwriting 
guidelines, (3) their purchases of CRA loans, and (4) their 
targeting of important markets where they have had only a limited 
presence in the past, such as the market for minority first-time 
homebuyers. A wide variety of quantitative and qualitative 
indicators indicate that the GSEs' have the resources and financial 
strength to improve their affordable lending performance enough to 
lead the market for low- and moderate-income families. The recent 
experience of Fannie Mae indicates that the GSEs can lead the low- 
and moderate-income market.

4. Size of the Mortgage Market for Low- and Moderate-Income Families

    As detailed in Appendix D, the low- and moderate-income mortgage 
market accounts for 51 to 56 percent of dwelling units financed by 
conventional conforming mortgages. In estimating the size of the 
market, HUD excluded the effects of the B&C market. HUD also used 
alternative assumptions about future economic and market 
affordability conditions that were less favorable than those that 
existed over the last five years. HUD is well aware of the 
volatility of mortgage markets and the possible impacts of changes 
in economic conditions on the GSEs' ability to meet the housing 
goals. Should conditions change such that the goals are no longer 
reasonable or feasible, the Department has the authority to revise 
the goals.

5. The Low- and Moderate-Income Housing Goal for 2005-2008.

    The Low- and Moderate-Income Housing Goal is 52 percent of 
eligible units for 2005, 53 percent for 2006, 55 percent for 2007, 
and 56 percent for 2008. The market for the Low- and Moderate-Income 
Goal is estimated to be 51-56 percent. Under the new counting rules 
(i.e., 2000-Census income re-benchmarking and the new OMB 
metropolitan area definitions), Fannie Mae's low- and moderate-
income performance is estimated to have been 46.3 percent in 1999, 
51.2 percent in 2000, 48.7 percent in 2001, 47.9 percent in 2002, 
and 49.5 percent in 2003--for 2005, Fannie Mae would have to 
increase its performance by 3.3 percentage points over its average 
(unweighted) performance of 48.7 percent over these last five years, 
or by 0.8 percentage point over its previous peak performance (51.2 
percent in 2000). By 2008, Fannie Mae's performance would have to 
increase by 6.3 percentage points over average 1999-2003 
performance, and by 5.8 percentage points over its previous peak 
performance in 2000. Freddie Mac's performance is estimated to have 
been 46.0 percent in 1999, 50.2 percent in 2000, 47.0 percent in 
2001, 44.6 percent in 2002, and 45.3 percent in 2003--for 2005, 
Freddie Mac would have to increase its performance by 5.3 percentage 
points over its average (unweighted) performance of 46.7 percent 
over these last five years, or by 1.8 percentage points over its 
previous peak performance (50.2 percent in 2000). By 2008, Freddie 
Mac's performance would have to increase by 9.3 percentage points 
over average 1999-2003 performance, and by 5.8 percentage points 
over its previous peak performance. However, the low- and moderate-
income market is estimated to be 51-56 percent. Thus, the GSEs 
should be able to improve their performance enough to meet these 
goals of 52-56 percent.
    The objective of the Low- and Moderate-Income Goal is to bring 
the GSEs' performance to the upper end of HUD's market range 
estimate for this goal (51-56 percent), consistent with the 
statutory criterion that HUD should consider the GSEs' ability to 
lead the market for each Goal. To enable the GSEs to achieve this 
leadership, the Department is proposing modest increases in the Low- 
and Moderate-Income Goal for 2005 which will increase further, year-
by-year through 2008, to achieve the ultimate objective for the GSEs 
to lead the market under a range of foreseeable economic 
circumstances by 2008. Such a program of staged increases is 
consistent with the statutory requirement that HUD consider the past 
performance of the GSEs in setting the Goals. Staged annual 
increases in the Low- and Moderate-Income Goal will provide the 
enterprises with opportunity to adjust their business models and 
prudently try out business strategies, so as to meet the required 
2008 level without compromising other business objectives and 
requirements.
    Figure A.3 summarizes many of the points made in this section 
regarding opportunities for Fannie Mae and Freddie Mac to improve 
their overall performance on the Low- and Moderate-Income Goal. The 
GSEs' purchases provided financing for 26,118,927 (or 55 percent) of 
the 47,551,039 single-family and multifamily units that were 
financed in the conventional conforming market between 1999 and 
2002. However, in the low- and moderate-income part of the market, 
the 12,608,215 units that were financed by GSE purchases represented 
only 48 percent of the 26,051,771 dwelling units that were financed 
in the market. Thus, there appears to be ample room for the GSEs to 
increase their purchases of loans that qualify for the Low- and 
Moderate-Income Goal. Examples of specific market segments that 
would particularly benefit from a more active secondary market have 
been provided throughout this appendix.

6. Conclusions

    Having considered the projected mortgage market serving low- and 
moderate-income families, economic, housing and demographic 
conditions for 2005-08, and the GSEs' recent performance in 
purchasing mortgages for low- and moderate-income families, the 
Secretary has determined that

[[Page 63752]]

the goals of 52 percent of eligible units financed in 2005, 53 
percent in 2006, 55 percent in 2007, and 56 percent in 2008 are 
feasible. The Secretary is also establishing a subgoal of 45 percent 
for the GSEs' purchases of single-family-owner home purchase 
mortgages in metropolitan areas in 2005, increasing to 46 percent in 
2006 and 47 percent in 2007 and 2008. The Secretary has considered 
the GSEs' ability to lead the industry as well as the GSEs' 
financial condition. The Secretary has determined that the proposed 
goals and the proposed subgoals are necessary and appropriate.

Appendix B--Departmental Considerations To Establish the Central 
Cities, Rural Areas, and Other Underserved Areas Goal

A. Introduction

1. Establishment of Goal

    The Federal Housing Enterprises Financial Safety and Soundness 
Act of 1992 (FHEFSSA) requires the Secretary to establish an annual 
goal for the purchase of mortgages on housing located in central 
cities, rural areas, and other underserved areas (the ``Underserved 
Areas Housing Goal'').
    In establishing this annual housing goal, Section 1334 of 
FHEFSSA requires the Secretary to consider:
    1. Urban and rural housing needs and the housing needs of 
underserved areas;
    2. Economic, housing, and demographic conditions;
    3. The performance and effort of the enterprises toward 
achieving the Underserved Areas Housing Goal in previous years;
    4. The size of the conventional mortgage market for central 
cities, rural areas, and other underserved areas relative to the 
size of the overall conventional mortgage market;
    5. The ability of the enterprises to lead the industry in making 
mortgage credit available throughout the United States, including 
central cities, rural areas, and other underserved areas; and
    6. The need to maintain the sound financial condition of the 
enterprises.
    Organization of Appendix. The remainder of Section A first 
defines the Underserved Areas Housing Goal for both metropolitan 
areas and nonmetropolitan areas. Sections B and C address the first 
two factors listed above, focusing on findings from the literature 
on access to mortgage credit in metropolitan areas (Section B) and 
in nonmetropolitan areas (Section C). Separate discussions are 
provided for metropolitan and nonmetropolitan (rural) areas because 
of differences in the underlying markets and the data available to 
measure them. Section D discusses the past performance of the GSEs 
on the Underserved Areas Housing Goal (the third factor) and 
Sections E-G report the Secretary's findings for the remaining 
factors. Section H presents the Department's rules relating to the 
definition of underserved areas in nonmetropolitan areas. Section I 
summarizes the Secretary's rationale for establishing a subgoal for 
single-family-owner home purchase mortgages and for setting the 
level for the Underserved Areas Housing Goal.

2. HUD's Underserved Areas Housing Goal

    HUD's definition of the geographic areas targeted by this goal 
is basically the same as that used during 1996-2003. It is divided 
into a metropolitan component and a nonmetropolitan component. 
However, as explained below, switching to 2000 Census geography 
increases the number of census tracts defined as underserved, and 
this necessitates an adjustment of the goal level.
    Metropolitan Areas. This rule provides that within metropolitan 
areas, mortgage purchases will count toward the goal when those 
mortgages finance properties that are located in census tracts where 
(1) median income of families in the tract does not exceed 90 
percent of area (MSA) median income or (2) minorities comprise 30 
percent or more of the residents and median income of families in 
the tract does not exceed 120 percent of area median income.
    In this Rule, the underserved census tracts are defined in terms 
of the 2000 Census rather than the 1990 Census. As shown in Table 
B.1a, switching to 2000 Census data and re-specified MSA boundaries 
as of June 2003, increases the proportions of underserved census 
tracts, population, owner-occupied housing units, and population 
below the poverty line in metropolitan areas. The definition now 
covers 26,959 (51.3 percent) of the 52,585 census tracts in 
metropolitan areas, which include 48.7 percent of the population and 
38.0 percent of the owner-occupied housing units in metropolitan 
areas.\1\ The 1990-based definition covered 21,587 (47.5 percent) of 
the 45,406 census tracts in metropolitan areas, which included 44.3 
percent of the population and 33.7 percent of the owner-occupied 
units in metropolitan areas.
---------------------------------------------------------------------------

    \1\ This analysis excludes Puerto Rico. In addition, tracts are 
excluded if median income is suppressed in the underlying census 
data. There are 379 such tracts. When reporting analysis of mortgage 
loan denial, origination, and application rates later in this 
appendix, tracts are excluded if there are no purchase or refinance 
applications. Tracts are also excluded if: (1) Group quarters 
constitute more than 50 percent of housing units or (2) there are 
less than 15 home purchase applications in the tract and the tract 
denial rates equal 0 or 100 percent. Excluded tracts account for a 
small percentage of mortgage loan applications (1.4 percent). These 
tracts are not excluded from HUD's underserved areas if they meet 
the income and minority thresholds. Rather, the tracts are excluded 
to remove the effects of outliers from the analysis.
---------------------------------------------------------------------------

    The census tracts included in HUD's definition of underserved 
areas exhibit low rates of mortgage access and distressed 
socioeconomic conditions. Between 1999 and 2002, the unweighted 
average mortgage denial rate in these tracts was 17.5 percent, 
almost double the average denial rate (9.3 percent) in excluded 
tracts. The underserved tracts include 75.3 percent of the number of 
persons below the poverty line in metropolitan areas.
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[[Page 63754]]

    HUD's establishment of this definition is based on a substantial 
number of studies of mortgage lending and mortgage credit flows 
conducted by academic researchers, community groups, the GSEs, HUD 
and other government agencies. As explained in the 2000 Rule, one 
finding stands out from the existing research literature on mortgage 
access for different types of neighborhoods: High-minority and low-
income neighborhoods continue to have higher mortgage denial rates 
and lower mortgage origination rates than other neighborhoods. A 
neighborhood's minority composition and its level of income are 
highly correlated with access to mortgage credit.
    Nonmetropolitan Areas. In nonmetropolitan areas, mortgage 
purchases count toward the Underserved Areas Housing Goal for 
properties which are located in counties where (1) median income of 
families in the county does not exceed 95 percent of the greater of 
(a) state nonmetropolitan median income or (b) nationwide 
nonmetropolitan median income, or (2) minorities comprise 30 percent 
or more of the residents and median income of families in the county 
does not exceed 120 percent of the greater of (a) state 
nonmetropolitan median income or (b) nationwide nonmetropolitan 
median income.
    In 1995, two important factors influenced HUD's definition of 
nonmetropolitan underserved areas--lack of available data for 
measuring mortgage availability in rural areas and lenders' 
difficulty in operating mortgage programs at the census tract level 
in rural areas. Because of these factors, the 1995 Rule (as well as 
the 2000 Rule) used a more inclusive, county-based approach to 
designating underserved portions of rural areas. As discussed in a 
later section, HUD is now replacing the county-based definition with 
a tract-based definition.
    As shown in Table B.1b, switching from 1990 to 2000 Census data 
and incorporating the June, 2003 specification of metropolitan areas 
causes a slight decrease in underserved proportions of counties, 
population, owner-occupied housing units, and poverty population in 
non-metropolitan areas. In terms of the 2000 Census geography and 
June 2003 metropolitan area specification, the definition covers 
1,260 (61.4 percent) of the 2,052 counties in nonmetropolitan areas, 
which include 51.0 percent of the population, 50.7 percent of the 
owner-occupied housing units, and 64.3 percent of the population 
below the poverty level in non-metropolitan areas. The 1990-based 
definition covered 1,514 (65.5 percent) of the 2,311 counties in 
non-metropolitan areas, which included 54.6 percent of the 
population, 53.4 percent of the owner-occupied units, and 67.9 
percent of the poor in non-metropolitan areas.\2\
---------------------------------------------------------------------------

    \2\ Kalawao County, Hawaii, which has a very small population, 
is excluded from the analysis for 1990 but included for 2000.

---------------------------------------------------------------------------

[[Page 63755]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.048


[[Page 63756]]


    Data comparable to that in Table B.1b is presented in Table B.1c 
based on census tracts, rather than counties, in nonmetropolitan 
areas. As indicated, the tract-based definition includes 6,782 (54.9 
percent) of the 12,359 nonmetropolitan census tracts in the country. 
These tracts contain 52.5 percent of the nonmetropolitan population 
(comparable to the 51.0 percent using a county-based definition) and 
50.4 percent of owner-occupied housing units (close to the 
corresponding figure of 50.7 percent under the county-based 
approach). But the tract-based approach better targets families most 
in need, as shown, for example, by the fact that it includes 68.9 
percent of the population in poverty, exceeding the corresponding 
figure of 64.3 percent under the county-based definition of 
nonmetropolitan underserved areas.
[GRAPHIC] [TIFF OMITTED] TR02NO04.049

    GSE Performance. Table B.1d shows the increases in the GSEs' 
overall goals performance under the more expansive geography of the 
2000 Census. During 2000, Fannie Mae's performance would have been 
an estimated 37.5 percent if underserved areas were defined in terms 
of 2000 Census geography, compared with 31.0 percent under 1990 
Census geography. These results for Fannie Mae (adjusted to be 
comparable with the 2000 figures) are 35.7 percent and 30.4 percent 
for 2001; 35.0 percent and 30.2 percent for 2002; and 34.1 percent 
and 29.2 percent for 2003. The corresponding figures for Freddie Mac 
are 34.1 percent and 29.2 percent for 2000 performance; 32.5 percent 
and 28.2 percent for 2001 performance; 32.4 percent and 28.0 percent 
for 2002 performance; and 31.6 percent and 27.7 percent for 2003 
performance. (The 2001-03 housing goals percentages in the table are 
adjusted to exclude the effects of the bonus points and Freddie 
Mac's Temporary Adjustment Factor, which became applicable in 2001 
for scoring of loans toward the housing goals.)

[[Page 63757]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.050

BILLING CODE 4210-27-C

[[Page 63758]]

    Goal and Subgoal Levels. The Department establishes the 
Underserved Areas Housing Goal as 37 percent of eligible units 
financed for 2005, 38 percent for 2006 and 2007, and 39 percent for 
2008.
    HUD is establishing a subgoal of 32 percent for the share of 
each GSE's total single-family-owner mortgage purchases that finance 
single-family-owner properties located in underserved census tracts 
of metropolitan areas for 2005, with this subgoal rising to 33 
percent for 2006 and 2007 and 34 percent in 2008. In this case, 
subgoal performance for a particular calendar year would be 
calculated for each GSE by dividing (a) the number of mortgages 
purchased by the GSE that finance single-family-owner properties 
located in underserved areas (i.e., census tracts) of metropolitan 
areas by (b) the number of mortgages purchased by the GSE that 
finance single-family-owner properties located in metropolitan 
areas. As explained in Section H, the purpose of this subgoal is to 
encourage the GSEs to lead the primary market in funding mortgages 
in underserved census tracts.

B. Consideration of Factors 1 and 2 in Metropolitan Areas: The 
Housing Needs of Underserved Urban Areas and Housing, Economic, and 
Demographic Conditions in Underserved Urban Areas

    This section discusses differential access to mortgage funding 
in urban areas and summarizes available evidence on identifying 
those neighborhoods that have historically experienced problems 
gaining access to credit. Section B.1 provides an overview of the 
problem of unequal access to mortgage funding, focusing on 
discrimination and other housing problems faced by minority families 
and the communities where they live. Section B.2 examines mortgage 
access at the neighborhood level and discusses in some detail the 
rationale for the Underserved Areas Housing Goal in metropolitan 
areas. The most thorough studies available provide strong evidence 
that low-income and high-minority census tracts are underserved by 
the mortgage market. Section B.3 presents recent statistics on the 
credit characteristics and socioeconomic characteristics of 
underserved areas under HUD's definition. Readers are referred to 
the expansive literature on this issue, which is reviewed in some 
detail in Appendix B of HUD's 2000 Rule. This section focuses on 
some of the main studies and their findings.
    Three main points are made in this section:
     Both borrowers and neighborhoods can be identified as 
currently being underserved by the nation's housing and mortgage 
markets. Appendix A provided evidence of racial disparities in the 
sale and rental of housing and in the provision of mortgage credit. 
Partly as a result of this, the homeownership rate for minorities is 
substantially below that for whites.
     The existence of substantial neighborhood disparities 
in mortgage credit is well documented for metropolitan areas. 
Research has demonstrated that census tracts with lower incomes and 
higher shares of minority population consistently have poorer access 
to mortgage credit, with higher mortgage denial rates and lower 
origination rates for mortgages. Thus, the income and minority 
composition of an area is a good measure of whether that area is 
being underserved by the mortgage market.
     Research supports a targeted neighborhood-based 
definition of underservice. Studies conclude that characteristics of 
mortgage loan applicants and the neighborhood where the property is 
located are the major determinants of mortgage denial rates and 
origination rates.
    Once these characteristics are accounted for, other influences, 
such as location in a central city, play only a minor role in 
explaining disparities in mortgage lending.\3\
---------------------------------------------------------------------------

    \3\ In this appendix, the term ``central city'' is used to mean 
``OMB-designated central city.''
---------------------------------------------------------------------------

1. Discrimination in the Mortgage and Housing Markets--An Overview

    The nation's housing and mortgage markets are highly efficient 
systems, where most homebuyers can put down relatively small amounts 
of cash and obtain long-term funding at relatively small spreads 
above the lender's borrowing costs, even though transactions costs 
are still too high and too bundled. Unfortunately, this highly 
efficient financing system does not work everywhere or for everyone. 
Studies have shown that access to credit often depends on improper 
evaluation of characteristics of the mortgage applicant and the 
neighborhood in which the applicant wishes to buy. In addition, 
though racial discrimination has become less blatant in the home 
purchase market, studies have shown that it is still widespread in 
more subtle forms. Partly as a result of these factors, the 
homeownership rate for minorities is substantially below that of 
whites. Appendix A provided an overview of the homeownership gaps 
and lending disparities faced by minorities. This section briefly 
reviews evidence on lending discrimination as well as a recent HUD-
sponsored study of discrimination in the housing market.
    Mortgage Denial Rates. A quick look at mortgage denial rates 
reported by Home Mortgage Disclosure Act (HMDA) data reveals that in 
2002 minority denial rates were higher than those for white loan 
applicants. For lower-income borrowers, the denial rate for African 
Americans applying for conventional loans was 2.1 times the denial 
rate for white borrowers, while for higher-income borrowers, the 
denial rate for African Americans was 2.7 times the rate for white 
borrowers.\4\
---------------------------------------------------------------------------

    \4\ The actual denial rates were as follows: 23.6 percent for 
low-income (80% AMI or less) African Americans, 15.5 percent for 
upper-income (120% AMI or more) African Americans. 11.4 percent for 
low-income Whites, and 5.6 percent for upper-income Whites. The 
overall denial rate in the conventional conforming home purchase 
market was 9.7 percent in 2002. The data exclude applications to 
lenders that specialize in manufactured home lending.
---------------------------------------------------------------------------

    Differentials in denial rates, such as those reported above, are 
frequently used to demonstrate the problems that minorities face 
obtaining access to mortgage credit. However, an important question 
is the degree to which variations in denial rates reflect lender 
bias against certain kinds of borrowers relative to the degree to 
which they reflect the credit quality of potential borrowers (as 
indicated by applicants' available assets, credit rating, employment 
history, etc.). Without fully accounting for the creditworthiness of 
the borrower, racial differences in denial rates cannot be 
attributed to lender bias. Some studies of credit disparities have 
attempted to control for credit risk factors that might influence a 
lender's decision to approve a loan.
    Boston Fed Study. The best example of accounting for credit risk 
is the study of mortgage denial rates by researchers at the Federal 
Reserve Bank of Boston.\5\ This landmark study found that racial 
differentials in mortgage denial rates cannot be fully explained by 
differences in credit risk. To control for credit risk, the Boston 
Fed researchers included 38 borrower and loan variables indicated by 
lenders to be critical to loan decisions. For example, the Boston 
Fed study included a measure of the borrower's credit history, which 
is a variable not included in other studies. The Boston Fed study 
found that minorities' higher denial rates could not be explained 
fully by income and credit risk factors. The denial rate for African 
Americans and Hispanics was 17 percent, compared with 11 percent for 
Whites with similar characteristics. That is, African Americans and 
Hispanics were about 60 percent more likely to be denied credit than 
Whites, even after controlling for credit risk characteristics such 
as credit history, employment stability, liquid assets, self-
employment, age, and family status and composition. Although almost 
all highly-qualified applicants were approved, differential 
treatment was observed among borrowers with more marginal 
qualifications. That is, highly-qualified borrowers of all races 
seemed to be treated equally, but in cases where there was some flaw 
in the application, white applicants seemed to be given the benefit 
of the doubt more frequently than minority applicants. A subsequent 
refinement of the data used by the Federal Reserve Bank of Boston 
confirmed the findings of that study.\6\
---------------------------------------------------------------------------

    \5\ Alicia H. Munnell, Lynn E. Browne, James McEneaney, and 
Geoffrey M.B. Tootell, ``Mortgage Lending in Boston: interpreting 
HMDA Data,'' American Economic Review, March 1996.
    \6\ William C. Hunter, ``The Cultural Affinity Hypothesis and 
Mortgage Lending Decisions,'' WP-95-8, Federal Reserve Bank of 
Chicago, 1995. Hunter confirmed that race was a factor in denial 
rates of marginal applicants. While denial rates were comparable for 
borrowers of all races with ``good'' credit ratings, among those 
with ``bad'' credit ratings or high debt ratios, minorities were 
significantly more likely to be denied than similarly-situated 
whites. The study concluded that the racial differences in denial 
rates were consistent with a cultural gap between white loan 
officers and minority applicants, and conversely, a cultural 
affinity with white applicants.
---------------------------------------------------------------------------

    The Boston Fed study, as well as reassessments of that study by 
other researchers, concluded that the effect of borrower race on 
mortgage rejections persists even after controlling for legitimate 
determinants of lenders' credit decisions.\7\

[[Page 63759]]

Thus, these studies imply that variations in mortgage denial rates, 
such as those reported above, are not determined entirely by 
borrower risk, but reflect discrimination in the housing finance 
system. However, the independent race effect identified in these 
studies is still difficult to interpret. In addition to lender bias, 
access to credit can be limited by loan characteristics that reduce 
profitability \8\ and by underwriting standards that have disparate 
effects on minority and lower-income borrowers and their 
neighborhoods.\9\
---------------------------------------------------------------------------

    \7\ For a reassessment of the Boston Fed study, see Stephen Ross 
and John Yinger, The Color of Credit, MIT Press 2002, and other 
studies cited there.
    \8\ Since upfront loan fees are frequently determined as a 
percentage of the loan amount, lenders are discouraged from making 
smaller loans in older neighborhoods, because such loans generate 
lower revenue and are less profitable to lenders.
    \9\ Traditional underwriting practices may have excluded some 
lower income families that are, in fact, creditworthy. Such families 
tend to pay cash, leaving them without a credit history. In 
addition, the usual front-end and back-end ratios applied to 
applicants' housing expenditures and other on-going costs may be too 
stringent for lower income households, who typically pay larger 
shares of their income for housing (including rent and utilities) 
than higher income households.
---------------------------------------------------------------------------

    Paired-Testing Studies. As discussed in Appendix A, paired 
testing studies of the pre-qualification process have supported the 
findings of the Boston Fed study. Based on a review of paired tests 
conducted by the National Fair Housing Alliance, The Urban Institute 
concluded that differential treatment discrimination at the pre-
application level occurred at significant levels in at least some 
cities. Minorities were less likely to receive information about 
loan products, received less time and information from loan 
officers, and were quoted higher interest rates in most of the 
cities where tests were conducted.\10\ Another Urban Institute study 
used the paired testing methodology to examine the pre-application 
process in Los Angeles and Chicago. African Americans and Hispanics 
faced a significant risk of unequal treatment when they visited 
mainstream mortgage lending institutions to make pre-application 
inquiries.\11\
---------------------------------------------------------------------------

    \10\ Margery A. Turner and Felicity Skidmore, eds., Mortgage 
Lending Discrimination: A Review of Existing Evidence. The Urban 
Institute: Washington, DC, June 1999.
    \11\ Margery Austin Turner, All Other Things Being Equal: A 
Paired Testing Study of Mortgage Lending Institutions, The Urban 
Institute Press, April 2002.
---------------------------------------------------------------------------

    Sales and Rental Markets. In 2002, HUD released its third 
Housing Discrimination Study (HDS) in the sale and rental of 
housing. The study, entitled Discrimination in Metropolitan Housing 
Markets: National Results from Phase I of the Housing Discrimination 
Study (HDS), was conducted by the Urban Institute.\12\ The results 
of this HDS were based on 4,600 paired tests of minority and non-
minority home seekers conducted during 2000 in 23 metropolitan areas 
nationwide. The report showed large decreases between 1989 and 2000 
in the level of discrimination experienced by Hispanics and African 
Americans seeking to buy a home. There has also been a modest 
decrease in discrimination toward African Americans seeking to rent 
a unit. This downward trend, however, has not been seen for Hispanic 
renters, who now are more likely to experience discrimination in 
their housing search than are African American renters. But while 
generally down since 1989, the report found that housing 
discrimination still exists at unacceptable levels. The greatest 
share of discrimination for Hispanic and African American home 
seekers can still be attributed to being told units are unavailable 
when they are available to non-Hispanic whites and being shown and 
told about fewer units than a comparable non-minority. Although 
discrimination is down on most areas for African American and 
Hispanic homebuyers, there remain worrisome upward trends of 
discrimination in the areas of geographic steering for African 
Americans and, relative to non-Hispanic whites, the amount of help 
agents provide to Hispanics with obtaining financing. On the rental 
side, Hispanics are more likely in 2000 than in 1989 to be quoted a 
higher rent than their white counterpart for the same unit.
---------------------------------------------------------------------------

    \12\ Margery Austin Turner, Stephen L. Ross, George Galster, and 
John Yinger, Discrimination in Metropolitan Housing Markets, The 
Urban Institute Press, November 2002.
---------------------------------------------------------------------------

    Another HUD-sponsored study asked respondents to a nationwide 
survey if they ``thought'' they had ever been discriminated against 
when trying to buy or rent a house or an apartment.\13\ While the 
responses were subjective, they are consistent with the findings of 
the HDS. African Americans and Hispanics were considerably more 
likely than whites to say they have suffered discrimination--24 
percent of African Americans and 22 percent of Hispanics perceived 
discrimination, compared to only 13 percent of whites.
---------------------------------------------------------------------------

    \13\ How Much Do We Know? Public Awareness of the Nation's Fair 
Housing Laws, prepared for HUD by Martin D. Abravanel and Mary K. 
Cunningham of the Urban Institute, April 2002.
---------------------------------------------------------------------------

    Segregation in Urban Areas. Discrimination, while not the only 
cause, contributes to the pervasive level of segregation that 
persists between African Americans and Whites in our urban areas. 
The Census Bureau recently released one of the most exhaustive 
studies of residential segregation ever undertaken, entitled Racial 
and Ethnic Residential Segregation in the United States: 1980-
2000.\14\ The Census Bureau found that the United States was still 
very much racially divided. While African Americans have made modest 
strides, they remain the most highly segregated racial group. The 
authors said that residential segregation likely results from a 
variety of factors, including choices people make about where they 
want to live, restrictions on their choices, or lack of information. 
The fact that many mainstream lenders do not operate in segregated 
areas makes it even more difficult for minorities to obtain access 
to reasonable-priced mortgage credit.\15\ Section C.8 of Appendix A 
cited several studies showing that these inner city neighborhoods 
are often served mainly by subprime lenders. In addition, there is 
evidence that denial rates are higher in minority neighborhoods 
regardless of the race of the applicant. The next section explores 
the issue of credit availability in neighborhoods in more detail.
---------------------------------------------------------------------------

    \14\ U.S. Bureau of the Census, August 2002. The co-authors of 
the study were John Iceland and Daniel H. Wienberg. For a summary of 
the study, see ``Residential Segregation Still Prevalent'', National 
Mortgage News, January 6, 2003, page 1.
    \15\ See Randall M. Scheessele, Black and White Disparities in 
Subprime Mortgage Refinance Lending, Housing Finance Working Paper 
No. HF-14, Office of Policy Development and Research, U.S. 
Department of Housing and Urban Development, April 2002.
---------------------------------------------------------------------------

2. Evidence About Access to Credit in Urban Neighborhoods--An Overview

    HUD's Underserved Areas Housing Goal focuses on low-income and 
high-minority neighborhoods that are characterized by high loan 
application denial rates and low loan origination rates. As 
explained in Section B.3 below, the mortgage denial rate during 2001 
in census tracts defined as underserved by HUD was twice the denial 
rate in excluded (or ``served'') tracts. In addition to such simple 
denial rate comparisons, there is a substantial economics literature 
justifying the targeted neighborhood definition that HUD has used to 
define underserved areas. Appendix B of the 1995 and 2000 GSE Rules 
reviewed that literature in some detail; thus, this section simply 
provides an overview of the main studies supporting the need to 
improve credit access to low-income and high-minority neighborhoods. 
Readers not interested in this overview may want to proceed to 
Section B.3, which examines the credit and socioeconomic 
characterizes of the census tracts included in HUD's underserved 
area definition.
    As explained in HUD's 2000 Rule, the viability of 
neighborhoods--whether urban, rural, or suburban--depends on the 
access of their residents to mortgage capital to purchase and 
improve their homes. While neighborhood problems are caused by a 
wide range of factors, including substantial inequalities in the 
distribution of the nation's income and wealth, there is increasing 
agreement that imperfections in the nation's housing and mortgage 
markets are hastening the decline of distressed neighborhoods. 
Disparate denial of credit based on geographic criteria can lead to 
disinvestment and neighborhood decline. Discrimination and other 
factors, such as inflexible and restrictive underwriting guidelines, 
limit access to mortgage credit and leave potential borrowers in 
certain areas underserved.
    Data on mortgage credit flows are far from perfect, and issues 
regarding the identification of areas with inadequate access to 
credit are both complex and controversial. For this reason, it is 
essential to define ``underserved areas'' as accurately as possible 
based on existing data and evidence. There are three sets of studies 
that provide the rationale for the Department's definition of 
underserved areas: (1) Studies examining racial discrimination 
against individual mortgage applicants; (2) studies that test 
whether mortgage redlining exists at the neighborhood level; and (3) 
studies that support HUD's targeted approach to measuring areas that 
are underserved by the mortgage market. In combination, these 
studies provide strong support for the definition of underserved 
areas chosen by HUD. The main studies of discrimination against 
individuals have already been summarized in Section B.1 above. Thus, 
this section focuses on the neighborhood-based

[[Page 63760]]

studies in (2) and (3). As noted above, this brief overview of these 
studies draws from Appendix B of the 1995 GSE Rule; readers are 
referred there for a more detailed treatment of earlier studies of 
the issues discussed below.

a. Controlling for Neighborhood Risk and Tests of the Redlining 
Hypothesis

    In its deliberations leading up to FHEFSSA, Congress was 
concerned about geographic redlining--the refusal of lenders to make 
loans in certain neighborhoods regardless of the creditworthiness of 
individual applicants. During the 1980s and early 1990s, a number of 
studies using HMDA data (such as that reported in Tables B.2 and 
B.3, below) attempted to test for the existence of mortgage 
redlining. Consistent with the redlining hypothesis, these studies 
found lower volumes of loans going to low-income and high-minority 
neighborhoods.\16\ However, such analyses were criticized because 
they did not distinguish between demand, risk, and supply effects 
\17\--that is, they did not determine whether loan volume was low 
because families in high-minority and low-income areas were unable 
to afford homeownership and therefore were not applying for mortgage 
loans, or because borrowers in these areas were more likely to 
default on their mortgage obligations, or because lenders refused to 
make loans to creditworthy borrowers in these areas.\18\, \19\
---------------------------------------------------------------------------

    \16\ These studies, which were conducted at the census tract 
level, typically involved regressing the number of mortgage 
originations (relative to the number of properties in the census 
tract) on characteristics of the census tract including its minority 
composition. A negative coefficient estimate for the minority 
composition variable was often interpreted as suggesting redlining. 
For a discussion of these models, see Eugene Perle, Kathryn Lynch, 
and Jeffrey Horner, ``Model Specification and Local Mortgage Market 
Behavior,'' Journal of Housing Research, Volume 4, Issue 2, 1993, 
pp. 225-243.
    \17\ For critiques of the early HMDA studies, see Andrew Holmes 
and Paul Horvitz, ``Mortgage Redlining: Race, Risk, and Demand,'' 
The Journal of Finance, Volume 49, No. 1, March 1994, pp. 81-99; and 
Michael H. Schill and Susan M. Wachter, ``A Tale of Two cities: 
Racial and Ethnic Geographic Disparities in Home Mortgage Lending in 
Boston and Philadelphia,'' Journal of Housing Research, Volume 4, 
Issue 2, 1993, pp. 245-276.
    \18\ Like early HMDA studies, an analysis of deed transfer data 
in Boston found lower rates of mortgage activity in minority 
neihborhoods. The discrepancies held even after controlling for 
income, house values and other economic and non-racial factors that 
might explain differences differences in demand and housing market 
activity. The study concluded that ``the housing market and the 
credit market together are functioning in a way that has hurt 
African American neighborhoods in the city of Boston.'' Katherine L. 
Bradbury, Karl E. Case, and Constance R. Dunham, ``Geographic 
Patterns of Mortgage Lending in Boston, 1982-1987,'' New England 
Economic Review, September/October 1989, pp. 3-30.
    \19\ Using an analytical approach similar to that of Bradbury, 
Case, and Dunham, Anne Shlay found evidence of fewer mortgage loans 
originated in black census tracts in Chicago and Baltimore. See Anne 
Shlay, ``Not in That Neighborhood: The Effects of Population and 
Housing on the Distribution of Mortgage Finance within the Chicago 
SMSA,'' Social Sciene Research, Volume 17, No. 2, 1988, pp. 137-163; 
and ``Financing Community: Methods for Assessing Residential Credit 
Disparities, Market Barriers, and Institutional Reinvestment 
Performance in the Metropolis,'' Journal of Urban Affiars, Volume 
11, No. 3, 1989, pp. 201-223.
---------------------------------------------------------------------------

    More Comprehensive Tests of the Redlining Hypothesis. Recent 
statistical studies have sought to test the redlining hypothesis by 
more completely controlling for differences in neighborhood risk and 
demand. In these studies, the explanatory power of neighborhood race 
is reduced to the extent that the effects of neighborhood risk and 
demand are accounted for; thus, they do not support claims of 
racially induced mortgage redlining. Many of these studies find that 
the race of the individual borrower is more important than the 
racial composition of the neighborhood. However, these studies 
cannot reach definitive conclusions about redlining because 
segregation in inner cities makes it difficult to distinguish the 
impacts of geographic redlining from the effects of individual 
discrimination. The following are two good examples of these 
studies.
    Holmes and Horvitz examined variations in conventional mortgage 
originations across census tracts in Houston.\20\ Their model 
explaining census-tract variations in mortgage originations included 
the following types of explanatory variables: (a) The economic 
viability of the loan, (b) characteristics of properties in and 
residents of the tract (e.g., house value, income, age distribution 
and education level), (c) measures of demand (e.g., recent movers 
into the tract and change in owner-occupied units between 1980 and 
1990), (d) measures of credit risk (defaults on government-insured 
loans and change in tract house values between 1980 and 1990), and 
(e) the racial composition of the tract, as a test for the existence 
of racial redlining. Most of the neighborhood risk and demand 
variables were significant determinants of the flow of conventional 
loans in Houston. The coefficients of the racial composition 
variables were insignificant, which led Holmes and Horvitz to 
conclude that allegations of redlining in the Houston market could 
not be supported.
---------------------------------------------------------------------------

    \20\ Holmes and Horvitz, op. cit.
---------------------------------------------------------------------------

    Schill and Wachter include several individual borrower and 
neighborhood characteristics to explain mortgage acceptance rates in 
Philadelphia and Boston.\21\ They found that the applicant race 
variables--whether the applicant was African American or Hispanic--
showed significant negative effects on the probability that a loan 
would be accepted. Schill and Wachter stated that this finding does 
not provide evidence of individual race discrimination because 
applicant race is most likely serving as a proxy for credit risk 
variables omitted from their model (e.g., credit history, wealth and 
liquid assets). Schill and Wachter find that when their neighborhood 
risk proxies are included in the model along with the individual 
loan variables, the percentage of the census tract that was African 
American became insignificant. Thus, similarly to Holmes and 
Horvitz, Schill and Wachter stated that ``once the set of 
independent variables is expanded to include measures that act as 
proxies for neighborhood risk, the results do not reveal a pattern 
of redlining.''\22\
---------------------------------------------------------------------------

    \21\ Schill and Wachter, op. cit.
    \22\ Schill and Wachter, page 271. Munnell, et al. reached 
similar conclusions in their study of Boston. They found that the 
race of the individual mattered, but that once individual 
characteristics were controlled, racial composition of the 
neighborhood was insignificant.
---------------------------------------------------------------------------

    Other Redlining Studies. To highlight the methodological 
problems of single-equation studies of mortgage redlining, Fred 
Phillips-Patrick and Clifford Rossi developed a simultaneous 
equation model of the demand and supply of mortgages, which they 
estimated for the Washington, DC metropolitan area.\23\ Phillips-
Patrick and Rossi found that the supply of mortgages is negatively 
associated with the racial composition of the neighborhood, which 
led them to conclude that the results of single-equation models 
(such as the one estimated by Holmes and Horvitz) are not reliable 
indicators of redlining or its absence. However, Phillips-Patrick 
and Rossi noted that even their simultaneous equations model does 
not provide definitive evidence of redlining because important 
underwriting variables (such as credit history), which are omitted 
from their model, may be correlated with neighborhood race.
---------------------------------------------------------------------------

    \23\ Fred J. Phillips-Patrick and Clifford V. Rossi, 
``Statistical Evidence of Mortgage Redlining? A Cautionary Tale'', 
The Journal of Real Estate Research, Volume 11, Number 1, 1996, 
pp.13-23.
---------------------------------------------------------------------------

    A few studies of neighborhood redlining have attempted to 
control for the credit history of the borrower, which is the main 
omitted variable in the redlining studies reviewed so far. Samuel 
Myers, Jr. and Tsze Chan, who studied mortgage rejections in the 
state of New Jersey in 1990, developed a proxy for bad credit based 
on the reasons that lenders give in their HMDA reports for denying a 
loan.\24\ They found that 70 percent of the gap in rejection rates 
could not be explained by differences in Black and white borrower 
characteristics, loan characteristics, neighborhoods or bad credit. 
Myers and Chan concluded that the unexplained Black-white gap in 
rejection rates is a result of discrimination. With respect to the 
racial composition of the census tract, they found that Blacks are 
more likely to be denied loans in racially integrated or 
predominantly-white neighborhoods than in predominantly-Black 
neighborhoods. They concluded that middle-class Blacks seeking to 
move out of the inner city would face problems of discrimination in 
the suburbs.\25\
---------------------------------------------------------------------------

    \24\ Samuel L. Myers, Jr. and Tsze Chan, ``Racial Discrimination 
in Housing Markets: Accounting for Credit Risk'', Social Science 
Quarterly, Volume 76, Number 3, September 1995, pp. 543-561.
    \25\ For another study that uses HMDA data on reasons for denial 
to construct a proxy for bad credit, see Steven R. Holloway, 
``Exploring the Neighborhood Contingency of Race Discrimination in 
Mortgage Lending in Columbus, Ohio'', Annals of the Association of 
American Geographers, Volume 88, Number 2, 1998, pp. 252-276. 
Holloway finds that mortgage denial rates are higher for black 
applicants (particularly those who are making large loan requests) 
in all-white neighborhoods than in minority neighborhoods, while the 
reverse is true for white applicants making small loan requests.
---------------------------------------------------------------------------

    Geoffrey Tootell has authored two papers on neighborhood 
redlining based on the

[[Page 63761]]

mortgage rejection data from the Boston Fed study.\26\ Tootell's 
studies are important because they include a direct measure of 
borrower credit history, as well as the other underwriting, 
borrower, and neighborhood characteristics that are included in the 
Boston Fed data base; thus, his work does not have the problem of 
omitted variables to the same extent as previous redlining 
studies.\27\ Tootell found that lenders in the Boston area did not 
appear to be redlining neighborhoods based on the racial composition 
of the census tract or the average income in the tract. Consistent 
with the Boston Fed and Schill and Wachter studies, Tootell found 
that it is the race of the applicant that mostly affects the 
mortgage lending decision; the location of the applicant's property 
appears to be far less relevant. However, he did find that the 
decision to require private mortgage insurance (PMI) depends on the 
racial composition of the neighborhood. Tootell suggested that, 
rather than redline themselves, mortgage lenders may rely on private 
mortgage insurers to screen applications from minority 
neighborhoods. Tootell also noted that this indirect form of 
redlining would increase the price paid by applicants from minority 
areas that are approved by private mortgage insurers.
---------------------------------------------------------------------------

    \26\ See Geoffrey M. B. Tootell, ``Redlining in Boston: Do 
Mortgage Lenders Discriminate Against Neighborhoods?'', Quarterly 
Journal of Economics, 111, November, 1996, pp. 1049-1079; and 
``Discrimination, Redlining, and Private Mortgage Insurance'', 
unpublished manuscript, October 1995.
    \27\ Tootell notes that both omitted variables and the strong 
correlation between borrower race and neighborhood racial 
composition in segregated cities have made it difficult for previous 
studies to distinguish the impacts of geographic redlining from the 
effects of individual borrower discrimination. He can unravel these 
effects because he includes a direct measure of credit history and 
because over half of minority applicants in the Boston Fed data base 
applied for mortgages in predominately white areas.
---------------------------------------------------------------------------

    In a 1999 paper, Stephen Ross and Geoffrey Tootell used the 
Boston Fed data base to take a closer look at both lender redlining 
and the role of private mortgage insurance (PMI) in neighborhood 
lending.\28\ They had two main findings. First, mortgage 
applications for properties in low-income neighborhoods were more 
likely to be denied if the applicant did not apply for PMI. Ross and 
Tootell concluded that their study provides the first direct 
evidence based on complete underwriting data that some mortgage 
applications may have been denied based on neighborhood 
characteristics that legally should not be considered in the 
underwriting process. Second, mortgage applicants were often forced 
to apply for PMI when the housing units were in low-income 
neighborhoods. Ross and Tootell concluded that lenders appeared to 
be responding to CRA by favoring low-income tracts once PMI has been 
received, and this effect counteracts the high denial rates for 
applications without PMI in low-income tracts.
---------------------------------------------------------------------------

    \28\ Stephen L. Ross and Geoffrey M. B. Tootell, ``Redlining, 
the Community Reinvestment Act, and Private Mortgage Insurance'', 
unpublished manuscript, March 1999.
---------------------------------------------------------------------------

    Studies of Information Externalities. Another group of studies 
related to redlining and the credit problems facing low-income and 
minority neighborhoods focus on the ``thin'' mortgage markets in 
these neighborhoods and the implications of lenders not having 
enough information about the collateral and other characteristics of 
these neighborhoods. The low numbers of house sales and mortgages 
originated in low-income and high-minority neighborhoods result in 
individual lenders perceiving these neighborhoods to be more risky. 
It is argued that lenders do not have enough historical information 
to project the expected default performance of loans in low-income 
and high-minority neighborhoods, which increases their uncertainty 
about investing in these areas.
    This recent group of studies that focus on economies of scale in 
the collection of information about neighborhood characteristics has 
implications for the identification of underserved areas and 
understanding the problems of mortgage access in low-income and 
minority neighborhoods. William Lang and Leonard Nakamura argue that 
individual home sale transactions generate information which reduce 
lenders' uncertainty about property values, resulting in greater 
availability of mortgage financing.\29\ Conversely, appraisals in 
neighborhoods where transactions occur infrequently will tend to be 
more imprecise, resulting in greater uncertainty to lenders 
regarding collateral quality, and more reluctance by them in 
approving mortgage loans in neighborhoods with thin markets. As a 
consequence, ``prejudicial practices of the past may lead to 
continued differentials in lending behavior.''
---------------------------------------------------------------------------

    \29\ William W. Lang and Leonard I. Nakamura, ``A Model of 
Redlining,'' Journal of Urban Economics, Volume 33, 1993, pp. 223-
234.
---------------------------------------------------------------------------

    If low-income or minority tracts have experienced relatively few 
recent transactions, the resulting lack of information available to 
lenders will result in higher denial rates and more difficulty in 
obtaining mortgage financing, independently of the level of credit 
risk in these neighborhoods. A number of empirical studies have 
found evidence consistent with the notion that mortgage credit is 
more difficult to obtain in areas with relatively few recent sales 
transactions. Some of these studies have also found that low 
transactions volume may contribute to disparities in the 
availability of mortgage credit by neighborhood income and minority 
composition. Paul Calem found that, in low-minority tracts, higher 
mortgage loan approval rates were associated with recent sales 
transactions volume, consistent with the Lang and Nakamura 
hypothesis.\30\ While this effect was not found in high-minority 
tracts, he concludes that ``informational returns to scale'' 
contribute to disparities in the availability of mortgage credit 
between low-minority and high-minority areas. Empirical research by 
David Ling and Susan Wachter found that recent tract-level sales 
transaction volume does significantly contribute to mortgage loan 
acceptance rates in Dade County, Florida, also consistent with the 
Lang and Nakamura hypothesis.\31\
---------------------------------------------------------------------------

    \30\ Paul S. Calem, ``Mortgage Credit Availability in Low- and 
Moderate-Income Minority Neighborhoods: Are Information 
Externalities Critical?'' Journal of Real Estate Finance and 
Economics, Volume 13, 1996, pp. 71-89.
    \31\ David C. Ling and Susan M. Wachter, ``Information 
Externalities and Home Mortgage Underwriting,'' Journal of Urban 
Economics, Volume 44, 1998, pp. 317-332.
---------------------------------------------------------------------------

    Robert Avery, Patricia Beeson, and Mark Sniderman found 
significant evidence of economies associated with the scale of 
operation of individual lenders in a neighborhood.\32\ They 
concluded that ``The inability to exploit these economies of scale 
is found to explain a substantial portion of the higher denial rates 
observed in low-income and minority neighborhoods, where the markets 
are generally thin.'' Low-income and minority neighborhoods often 
suffer from low transactions volume, and low transactions volume 
represents a barrier to the availability of mortgage credit by 
making mortgage lenders more reluctant to approve and originate 
mortgage loans in these areas.
---------------------------------------------------------------------------

    \32\ Robert B. Avery, Patricia E. Beeson, and Mark S. Sniderman, 
``Neighborhood Information and Home Mortgage Lending,'' Journal of 
Urban Economics, Volume 45, 1999, pp. 287-310.
---------------------------------------------------------------------------

b. Geographic Dimensions of Underserved Areas--Targeted Versus Broad 
Approaches

    HUD's definition of metropolitan underserved areas is a targeted 
neighborhood definition, rather than a broad definition that would 
encompass entire cities. It also focuses on those neighborhoods 
experiencing the most severe credit problems, rather than 
neighborhoods experiencing only moderate difficulty obtaining 
credit. During the regulatory process leading to the 1995 rule, some 
argued that underserved areas under this goal should be defined to 
include all parts of all central cities, as defined by OMB. HUD 
concluded that such broad definitions were not a good proxy for 
mortgage credit problems--to use them would allow the GSEs to focus 
on wealthier parts of cities, rather than on neighborhoods 
experiencing credit problems. Appendix B of the 1995 and 2000 Rules 
reviewed findings from academic researchers that support defining 
underserved areas in terms of the minority and/or income 
characteristics of census tracts, rather than in terms of a broad 
definition such as all parts of all central cities. This section 
briefly reviews two of the studies. The targeted nature of HUD's 
definition is also examined in Section B.3 below, which describes 
the credit and socioeconomic characteristics of underserved census 
tracts.
    Shear, Berkovec, Dougherty, and Nothaft conducted an analysis of 
mortgage flows and application acceptance rates in 32 metropolitan 
areas that supports a targeted definition of underserved areas.\33\ 
They

[[Page 63762]]

found: (a) Low-income census tracts and tracts with high 
concentrations of African American and Hispanic families had lower 
rates of mortgage applications, originations, and acceptance rates; 
and (b) once census tract influences were accounted for, central 
city location had only a minimal effect on credit flows. These 
authors recognized that it is difficult to interpret their estimated 
minority effects--the effects may indicate lender discrimination, 
supply and demand effects not included in their model but correlated 
with minority status, or some combination of these factors. Still, 
they conclude that income and minority status are better indicators 
of areas with special needs than central city location.
---------------------------------------------------------------------------

    \33\ William Shear, James Berkovec, Ann Dougherty, and Frank 
Nothaft, ``Unmet Housing Needs: The Role of Mortgage Markets,'' 
Journal of Housing Economics, Volume 4 , 1996, pp. 291-306. These 
researchers regressed the number of mortgage originations per 100 
properties in the census tract on several independent variables that 
were intended to account for some of the demand and supply (i.e., 
credit risk) influences at the census tract level. See also Susan 
Wharton Gates, ``Defining the Underserved,'' Secondary Mortgage 
Markets, 1994 Mortgage Market Review Issue, 1995, pp. 34-48.
---------------------------------------------------------------------------

    Avery, Beeson, and Sniderman of the Federal Reserve Bank of 
Cleveland specifically addressed the issue of underserved areas in 
the context of the GSE legislation.\34\ Their study examined 
variations in application rates and denial rates for all individuals 
and census tracts included in the 1990 and 1991 HMDA data base. 
These authors found that the individual applicant's race exerts a 
strong influence on mortgage application and denial rates. African 
American applicants, in particular, had unexplainably high denial 
rates. Once individual applicant and other neighborhood 
characteristics were controlled for, overall denial rates for 
purchase and refinance loans were only slightly higher in minority 
census tracts than non-minority census tracts. For white applicants, 
on the other hand, denial rates were significantly higher in 
minority tracts. That is, minorities had higher denial rates 
wherever they attempted to borrow, but whites faced higher denials 
when they attempt to borrow in minority neighborhoods. In addition, 
Avery et al. found that home improvement loans had significantly 
higher denial rates in minority neighborhoods. Given the very strong 
effect of the individual applicant's race on denial rates, the 
authors noted that since minorities tend to live in segregated 
communities, a policy of targeting minority neighborhoods may be 
warranted. They also found that the median income of the census 
tract had strong effects on both application and denial rates for 
purchase and refinance loans, even after other variables were 
accounted for. Avery, Beeson and Sniderman concluded that a tract-
level definition is a more effective way to define underserved areas 
than using the list of OMB-designated central cities as a proxy.
---------------------------------------------------------------------------

    \34\ See Avery, et al.
---------------------------------------------------------------------------

c. Conclusions from the Economics Literature about Urban Underserved 
Areas

    The implications of studies by HUD and others for defining 
underserved areas can be summarized briefly. First, the existence of 
large geographic disparities in mortgage credit is well documented. 
Low-income and high-minority neighborhoods receive substantially 
less credit than other neighborhoods and fit the definition of being 
underserved by the nation's credit markets.
    Second, researchers are testing models that more fully account 
for the various risk, demand, and supply factors that determine the 
flow of credit to urban neighborhoods. The studies by Holmes and 
Horvitz, Schill and Wachter, and Tootell are examples of this 
research. Their attempts to test the redlining hypothesis show the 
analytical insights that can be gained by more rigorous modeling of 
this issue. However, the fact that urban areas are highly segregated 
means that the various loan, applicant, and neighborhood 
characteristics currently being used to explain credit flows are 
often highly correlated with each other, which makes it difficult to 
reach definitive conclusions about the relative importance of any 
single variable such as neighborhood racial composition. Thus, their 
results are inconclusive, and the need continues for further 
research on the underlying determinants of geographic disparities in 
mortgage lending.\35\
---------------------------------------------------------------------------

    \35\ Methodological and econometric challenges that researchers 
will have to deal with are discussed in Mitchell Rachlis and Anthony 
Yezer, ``Serious Flaws in Statistical Tests for Discrimination in 
Mortgage Markets,'' Journal of Housing Research, Volume 4, 1993, pp. 
315-336.
---------------------------------------------------------------------------

    Finally, much research strongly supports a targeted definition 
of underserved areas. Studies by Shear, et al. and Avery, Beeson, 
and Sniderman conclude that characteristics of both the applicant 
and the neighborhood where the property is located are the major 
determinants of mortgage denials and origination rates--once these 
characteristics are controlled for, other influences such as central 
city location play only a minor role in explaining disparities in 
mortgage lending.
    HUD recognizes that the mortgage origination and denial rates 
forming the basis for the research mentioned in the preceding 
paragraph, as well as for HUD's definition of underserved areas, are 
the result of the interaction of individual risk, demand and supply 
factors that analysts have yet to fully disentangle and interpret. 
The need continues for further research addressing this problem.

3. Characteristics of HUD's Underserved Areas

a. Credit Characteristics

    HMDA data provide information on the disposition of mortgage 
loan applications (originated, approved but not accepted by the 
borrower, denied, withdrawn, or not completed) in metropolitan 
areas. HMDA data include the census tract location of the property 
being financed and the race and income of the loan applicant(s). 
Therefore, this is a rich data base for analyzing mortgage activity 
in urban neighborhoods. HUD's analysis using HMDA data for 2003 
shows that high-minority and low-income census tracts have both 
relatively high loan application denial rates and relatively low 
loan origination rates.
    Table B.2 presents mortgage denial and origination rates by the 
minority composition and median income of census tracts in 
metropolitan areas. Two patterns are clear:
     Census tracts with higher percentages of minority 
residents have higher mortgage denial rates and lower mortgage 
origination rates than all-white or substantially-white tracts. For 
example, in 2003 the denial rate for census tracts that are over 90 
percent minority (20.6 percent) was 2.3 times that for census tracts 
with less than 10 percent minority (9.0 percent).
     Census tracts with lower incomes have higher denial 
rates and lower origination rates than higher income tracts. For 
example, in 2003 mortgage denial rates declined from 23.2 percent to 
7.2 percent as tract income increased from less than 40 percent of 
area median income to more than 150 percent of area median income.
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[[Page 63763]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.051

     Table B.3 illustrates the interaction between tract 
minority composition and tract income by aggregating the data in 
Table B.2 into nine minority and income combinations. The low-
minority (less than 30 percent minority), high-income (over 120 
percent of area median) group had a denial rate of 7.2 percent and 
an origination rate of 32.4 loans per 100 owner occupants in 2003. 
The high-minority (over 50 percent), low-income (under 90 percent of 
area median) group had a denial rate of 19.3 percent and an 
origination rate of only 17.8 loans per 100 owner occupants. The 
other groupings fall between these two extremes.

[[Page 63764]]

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[[Page 63765]]


    The advantages of HUD's underserved area definition can be seen 
by examining the minority-income combinations highlighted in Table 
B.3. The sharp differences in denial rates and origination rates 
between the underserved and remaining served categories illustrate 
that HUD's definition delineates areas that have significantly less 
success in receiving mortgage credit. In 2003 underserved areas had 
over one and a three-fourths times the average denial rate of served 
areas (15.9 percent versus 8.9 percent) and two-thirds the average 
origination rate per 100 owner occupants (20.1 versus 29.1). HUD's 
definition does not include high-income (over 120 percent of area 
median) census tracts even if they meet the minority threshold. The 
average denial rate (10.3 percent) for high-income tracts with a 
minority share of population over 30 percent is much less than the 
denial rate (15.9 percent) in underserved areas as defined by HUD.
    Figure B.1 compares underserved and served areas within central 
cities and suburbs. First, Figure B.1 shows that HUD's definition 
targets central city neighborhoods that are experiencing problems 
obtaining mortgage credit. The 16.8 percent denial rate in these 
neighborhoods in 2003 was almost twice the 8.9 percent denial rate 
in the remaining areas of central cities. A broad, inclusive 
definition of ``central city'' that includes all areas of all 
central cities would include these ``remaining'' portions of cities. 
Figure B.1 shows that these areas, which account for approximately 
36 percent of the population in central cities, appear to be well 
served by the mortgage market. As a whole, they are not experiencing 
problems obtaining mortgage credit.

[[Page 63766]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.053


[[Page 63767]]


    Second, Figure B.1 shows that HUD's definition also targets 
underserved census tracts in the suburbs as well as in central 
cities. The average denial rate in underserved suburban areas (14.8 
percent) is 1.7 times that in the remaining served areas of the 
suburbs (8.7 percent), and is almost as large as the average denial 
rate (16.8 percent) in underserved central city tracts. Low-income 
and high-minority suburban tracts appear to have credit problems 
similar to their central city counterparts. These suburban tracts, 
which account for 34 percent of the suburban population, are 
included in HUD's definition of other underserved areas.

b. Socioeconomic Characteristics

    The targeted nature of HUD's definition can be seen from the 
data presented in Table B.4, which show that families living in 
tracts within metropolitan areas that are underserved based on HUD's 
definition experience much more economic and social distress than 
families living in served areas. For example, the poverty rate in 
underserved census tracts is 18.5 percent, or over three times the 
poverty rate (5.7 percent) in served census tracts. The unemployment 
rate and the high-school dropout rate are also higher in underserved 
areas. In addition, there are nearly three times more female-headed 
households with children in underserved areas (30.0 percent) than in 
served areas (13.2 percent). Three-fourths of units in served areas 
are owner-occupied, while only one-half of units in underserved 
areas are owner-occupied.

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[[Page 63769]]



C. Consideration of Factors 1 and 2 in Nonmetropolitan Areas: The 
Housing Needs of Underserved Rural Areas and the Housing, Economic, 
and Demographic Conditions in Underserved Rural Areas

    Based on discussions with rural lenders in 1995, the definition 
of underserved rural areas was established at the county level, 
since such lenders usually do not make distinctions on a census 
tract basis. A nonmetropolitan county is classified as an 
underserved area if median income of families in the county does not 
exceed 95 percent of the greater of state nonmetropolitan or 
national nonmetropolitan median income, or minorities comprise 30 
percent or more of the residents and the median income of families 
in the county does not exceed 120 percent of the greater of state 
nonmetropolitan or national nonmetropolitan median income. For 
nonmetropolitan areas the median income component of the underserved 
definition is broader than that used for metropolitan areas. While 
tract income is compared with area income for metropolitan areas, in 
rural counties income is compared with the greater of state 
nonmetropolitan income and national nonmetropolitan income. This is 
based on HUD's analysis of 1990 census data, which indicated that 
comparing county nonmetropolitan income only to state 
nonmetropolitan income would lead to the exclusion of many lower-
income low-minority counties from the definition, especially in 
Appalachia. Based on 1990 census geography, underserved counties 
account for 57 percent (8,091 of 14,419) of the census tracts and 54 
percent of the population in rural areas. By comparison, the 
definition of metropolitan underserved areas encompassed 47 percent 
of metropolitan census tracts and 44 percent of metropolitan 
residents.
    The purchasing of loans from underserved areas by the GSEs is 
intended to induce greater homeownership among moderate, low, very 
low income, and poor families and minorities. For various reasons, 
including creditworthiness and lending discrimination, these groups 
experience greater difficulty in securing loans under fair and 
reasonable terms and in buying decent and affordable housing, and it 
is for them that the geographic goals were designed. The geographic 
goals, then, are meant to target places where these ``underserved'' 
populations live in order to stimulate local mortgage lending and, 
it is hoped, the availability of credit to those families who reside 
there who, otherwise, will have difficulty securing credit. This 
section addresses the basic question of whether and the extent to 
which HUD's definition of underservice in nonmetropolitan areas 
effectively targets areas that encompass large populations of 
socially and economically disadvantaged families.
    Table B.5 shows data on demographic and socioeconomic conditions 
of underserved and served nonmetropolitan areas based on HUD's 
definition applied at the county level using Census 2000 data. (A 
later section considers the effects of applying the definition of 
the census tract level.) Several variables are used to describe area 
demographic and socioeconomic conditions.

[[Page 63770]]

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BILLING CODE 4210-27-C

[[Page 63771]]

    On the national level, a few key results show that the 1995 
definition of underservice captures a potentially disadvantaged 
segment of the population. In examining the minority composition, 
one can see that the percentage of African Americans, Hispanics/
Latinos, and total minority population is higher in underserved 
nonmetropolitan areas as compared to served nonmetropolitan areas. 
Overall, the minority population of underserved areas is 25.8 
percent as compared with 9.3 percent in served areas. Other 
supporting results include median family income, poverty rate, 
unemployment rate, school dropout rate, and in-migration rate. 
Specifically we find:
     Median income is approximately $10,000 less in 
underserved areas than in served areas. This represents an average 
gap of 25 percent.
     Poverty in underserved areas is twice the rate in 
served areas (14.5 vs. 7.5 percent).
     Unemployment is 7.3 percent in underserved areas and 
5.2 percent in served areas.
     The school dropout rate is 28.1 percent in underserved 
areas and 18.7 percent in served areas.
     Migration into underserved areas is somewhat lower than 
in served areas: 7.4 vs. 8.0 percent.
    Table B.5 also includes data on homeownership rates, housing 
affordability, housing quality, and overcrowding. On several of 
these dimensions, housing conditions and needs in underserved areas 
are not substantially worse than in served areas. Although housing 
quality and crowding appear to be marginally worse in underserved 
areas, homeownership in the two areas is about the same and owning a 
home actually appears to be more affordable in underserved areas 
than in served areas. Specific findings include the following:
     Homeownership is slightly higher in underserved than in 
served nonmetropolitan counties: 74.3 percent vs. 73.7 percent. 
Removing manufactured homes lowers ownership rates slightly, because 
ownership of such homes is relatively high, but this does not affect 
the basic result.
     Owner-occupied and rental vacancy rates are both 
somewhat higher in underserved areas.
     Median housing unit values are significantly lower in 
underserved areas: $67,358 vs. $88,099.
     The value of a housing affordability index for owner-
occupied housing is slightly higher in underserved areas.\36\ On 
average, median income is 1.83 times higher than income required to 
qualify to buy a home of median value in underserved areas. The 
comparable factor for served areas is 1.78.
---------------------------------------------------------------------------

    \36\ The purchase affordability index assesses the extent to 
which a family with the median income of a given area would be able 
to afford a housing unit that carries the median purchase price of 
that area. For example, a purchase affordability index number less 
than 100 means that a family with the median income would not 
qualify for a mortgage on a unit with the median value; a purchase 
affordability index equal to 100 means that a family with the median 
income has exactly the level of income needed to qualify for a 
mortgage on a unit with the median value; and an index number 
greater than 100 means that a family with the median income has 20 
percent more than the level of income needed to qualify for a 
mortgage on a unit with the median value. The rental affordability 
index is similarly constructed.
---------------------------------------------------------------------------

     Rental affordability is approximately the same in 
underserved and served areas.
     While nearly all housing in served and underserved 
areas have complete plumbing and kitchens, the percentage of units 
with incomplete facilities in underserved is twice the percentage in 
served areas.
     Crowded units are a small share of all housing in 
nonmetropolitan areas, but the rate is higher for underserved areas: 
4.3 vs. 2.3 percent.
    Mikesell \37\ found using the 1995 American Housing Survey that 
while the rate of homeownership in nonmetropolitan areas is higher 
than metropolitan areas, the quality of housing is lower as compared 
to metropolitan areas. Results based on the 2000 Census show that 
the homeownership rate for nonmetropolitan areas was 74 percent (73 
percent without manufactured homes), and for metropolitan areas it 
was 64 percent, but both metropolitan and nonmetropolitan areas had 
approximately 97.5 percent of units with complete plumbing and 99 
percent with complete kitchens.
---------------------------------------------------------------------------

    \37\ J.J. Mikesell, ``Housing Problems across Types of Rural 
Households'', Rural Conditions and Trends, Volume 9, Number 2, pp. 
97-101, 1999.
---------------------------------------------------------------------------

D. Factor 3: Previous Performance and Effort of the GSEs in 
Connection With the Central Cities, Rural Areas and Other 
Underserved Areas Goal

    Section D.1 reports the past performance of each GSE with regard 
to the Underserved Areas Housing Goal. Section D.2 then examines the 
role that the GSEs are playing in funding single-family mortgages in 
underserved urban neighborhoods based on HUD's analysis of GSE and 
HMDA data. That section also discusses an underserved area subgoal 
for home purchase loans. Section D.3 concludes this section with an 
analysis of the GSEs' purchases in rural (nonmetropolitan) areas.
    The increased coverage of the Underserved Areas Housing goal due 
to switching to 2000 census geography is discussed throughout this 
section.

1. Past Performance of the GSEs

    This section discusses each GSE's performance under the 
Underserved Areas Housing Goal over the 1996-2003 period.\38\ As 
explained in Appendix A, the data presented are ``official HUD 
results'' which, in some cases, differ from goal performance 
reported by the GSEs in the Annual Housing Activities Reports 
(AHARs) that they submit to the Department.
---------------------------------------------------------------------------

    \38\ Performance for the 1993-95 period was discussed in the 
October 2000 rule.
---------------------------------------------------------------------------

    The main finding of this section is that Fannie Mae surpassed 
the Department's Underserved Areas Housing Goals for each of the 
seven years during this period. Freddie Mac surpassed the goal in 
six of the seven years, falling slightly short in 2002. 
Specifically:
     The goal was set at 21 percent for 1996; Fannie Mae's 
performance was 28.1 percent and Freddie Mac's performance was 25.0 
percent.
     The goal was set at 24 percent for 1997-2000. Fannie 
Mae's performance was 28.8 percent in 1997, 27.0 percent in 1998, 
26.8 percent in 1999, and 31.0 percent in 2000; and Freddie Mac's 
performance was 26.3 percent in 1997, 26.1 percent in 1998, 27.5 
percent in 1999, and 29.2 percent in 2000.
     In the October 2000 rule, the underserved areas goal 
was set at 31 percent for 2001-03. As of January 1, 2001, several 
changes in counting requirements came into effect for the undeserved 
areas goal, as follows: ``bonus points'' (double credit) for 
purchases of goal-qualifying mortgages on small (5-50 unit) 
multifamily properties and, above a threshold level, mortgages on 2-
4 unit owner-occupied properties; a ``temporary adjustment factor'' 
(1.20 units credit, subsequently increased by Congress to 1.35 units 
credit) for Freddie Mac's purchases of goal-qualifying mortgages on 
large (more than 50-unit) multifamily properties; and eligibility 
for purchases of certain qualifying government-backed loans to 
receive goal credit. These changes are explained below. Fannie Mae's 
performance was 32.6 percent in 2001, 32.4 percent in 2002, and 32.1 
percent in 2003; and Freddie Mac's performance was 31.7 percent in 
2001, slightly less than 31 percent in 2002, and 32.7 percent in 
2003, thus Fannie Mae surpassed this higher goal in all three years 
and Freddie Mac surpassed the goal in 2001 and 2003, but fell 
slightly short in 2002. This section discusses the October 2000 
counting rule changes in detail below, and provides data on what 
goal performance would have been in 2001-03 without these 
changes.\39\
---------------------------------------------------------------------------

    \39\ To separate out the effects of changes in counting rules 
that took effect in 2001, this section also compares performance in 
2001 to estimated performance in 2000 if the 2001 counting rules had 
been in effect in that year.
---------------------------------------------------------------------------

a. Performance on the Underserved Areas Housing Goal in 1996-2003

    HUD's December 1995 rule specified that in 1996 at least 21 
percent of the number of units financed by each of the GSEs that 
were eligible to count toward the Underserved Areas Goal should 
qualify as units in properties located in underserved areas, and at 
least 24 percent should qualify in 1997-2000. HUD's October 2000 
rule made various changes in the goal counting rules, as discussed 
below, and increased the Underserved Areas Goal to 31 percent for 
2001-03.
    Table B.6 shows performance on the underserved areas goal over 
the 1996-2003 period, based on HUD's analysis. The table shows that 
Fannie Mae surpassed the goals by 7.1 percentage points and 4.8 
percentage points in 1996 and 1997, respectively, while Freddie Mac 
surpassed the goals by narrower margins, 4.0 and 2.3 percentage 
points. In 1998 Fannie Mae's performance fell by 1.8 percentage 
points, while Freddie Mac's performance fell only slightly, by 0.2 
percentage point. Freddie Mac showed a gain in performance to 27.5 
percent in 1999, exceeding its previous high by 1.2 percentage 
points. Fannie Mae's performance in 1999 was 26.8 percent, which, 
for the first time, slightly lagged Freddie Mac's performance in 
that year.
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[[Page 63773]]


    Both GSEs exhibited sharp gains in goal performance in 2000--
Fannie Mae's performance increased by 4.2 percentage points, to a 
record level of 31.0 percent, while Freddie Mac's performance 
increased somewhat less, by 1.7 percentage points, which also led to 
a record level of 29.2 percent. Fannie Mae's performance was 32.6 
percent in 2001, 32.4 percent in 2002, and 32.1 percent in 2003; 
Freddie Mac's performance was 31.7 percent in 2001, slightly less 
than 31 percent in 2002, and 32.7 percent in 2003. However, as 
discussed below, using consistent accounting rules for 2000-03, 
under one method each GSE's performance in 2001-03 was below its 
performance in 2000.
    Fannie Mae's performance on the underserved areas goal surpassed 
Freddie Mac's in every year through 1998. This pattern was reversed 
in 1999, as Freddie Mac surpassed Fannie Mae in goal performance for 
the first time, though by only 0.7 percentage point. This improved 
relative performance of Freddie Mac was due to its increased 
purchases of multifamily loans, as it re-entered that market, and to 
increases in the goal-qualifying shares of its single-family 
mortgage purchases. However, Fannie Mae's performance once again 
exceeded Freddie Mac's performance in 2000, 31.0 percent to 29.2 
percent. Fannie Mae's official performance also exceeded Freddie 
Mac's official performance in 2001-02, despite the fact that Freddie 
Mac benefited from a difference in the counting rules applicable to 
the two GSEs as enacted by Congress; if the same counting rules were 
applied to both GSEs, Fannie Mae's performance would have exceeded 
Freddie Mac's performance. In fact, Freddie Mac would have just 
attained the goal, at 31.4 percent in 2003, and fallen short of the 
goal in 2001 and 2002.

b. Changes in the Goal Counting Rules for 2001-03

    Several changes in the counting rules underlying the calculation 
of underserved areas goal performance took effect beginning in 2001. 
These also applied to the low- and moderate-income goal and are 
discussed in Appendix A; only brief summaries of those changes are 
given here:\40\ Bonus points for multifamily and single-family 
rental properties. Each qualifying unit in a small multifamily 
property counted as two units in the numerator in calculating 
performance on all of the goals for 2001-03. And, above a threshold 
equal to 60 percent of the average number of qualifying rental units 
financed in owner-occupied properties over the preceding five years, 
each unit in a 2-4 unit owner-occupied property also counted as two 
units in the numerator in calculating goal performance.
---------------------------------------------------------------------------

    \40\ Unlike the low- and moderate-income and special affordable 
goals, there is no exclusion of units from the denominator for units 
with missing information about the area in which a property is 
located. That is, such units are counted in the denominator, but not 
in the numerator, in determining underserved areas goal performance.
---------------------------------------------------------------------------

    Freddie Mac's Temporary Adjustment Factor. Freddie Mac received 
a ``Temporary Adjustment Factor'' of 1.35 units of credit for each 
qualifying unit financed in ``large'' multifamily properties (i.e., 
those with 51 or more units) in the numerator in calculating its 
performance on the housing goals for 2001-03.\41\ This factor did 
not apply to units in large multifamily properties in underserved 
areas whose mortgages were financed by Fannie Mae during this 
period.
---------------------------------------------------------------------------

    \41\ See Congressional Record, December 15, 2000, pp. H12295-96.
---------------------------------------------------------------------------

    Purchases of certain government-backed loans. Prior to 2001, 
purchases of government-backed loans were not taken into account in 
determining performance on the GSEs' low- and moderate-income and 
underserved area housing goals. As discussed in Appendix A, the 2000 
rule established eligibility for FHA-insured home equity conversion 
mortgages (HECMs) for mortgagors in underserved areas, purchases of 
mortgages on properties on tribal lands insured under FHA's Section 
248 program or HUD's Section 184 program, and purchases of mortgages 
under the Rural Housing Service's Single Family Housing Guaranteed 
Loan Program to count toward the underserved area goal.

c. Effects of Changes in the Counting Rules on Goal Performance

    Because of the changes in the underserved areas goal counting 
rules that took effect in 2001, direct comparisons between official 
goal performance in 2000 and 2001-03 are somewhat of an ``apples-to-
oranges comparison.'' For this reason, the Department has calculated 
what performance would have been in 2000 under the 2001-03 rules; 
this may compared with official performance in 2001-03--an ``apples-
to-apples comparison.'' HUD has also calculated what performance 
would have been in 2001-03 under the 1996-2000 rules; this may be 
compared with official performance in 2000--an ``oranges-to-oranges 
comparison.'' These comparisons are presented in Table B.7a.

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    Specifically, Table B.7a shows performance under the underserved 
areas goal in three ways. Baseline A represents the counting rules 
in effect in 1996-2000. Baseline B incorporates the one minor 
technical change in counting rules pertaining to the underserved 
areas goal--eligibility of certain government-backed loans for goals 
credit. Baseline C incorporates in addition to that technical change 
the bonus points and, for Freddie Mac, the temporary adjustment 
factor. Boldface figures under Baseline A for 1999-2000 and under 
Baseline C for 2001-02 indicate official goal percentages based on 
the counting rules in effect in those years--e.g., for Freddie Mac, 
27.5 percent in 1999, 29.2 percent in 2000, 31.7 percent in 2001, 
slightly less than 31 percent in 2002, and 32.7 percent in 2003.
    Performance on the Underserved Areas Goal under 1996-2000 
Counting Rules Plus Technical Changes. If the ``Baseline B'' 
counting approach had been in effect in 2000-03 and the GSEs'' had 
purchased the same mortgages that they actually did purchase in 
those years, Fannie Mae would have just matched the underserved 
areas goal in 2000 and fallen short in 2001-03, while Freddie Mac 
would have fallen short of the goal in all four years, 2000-03. 
Specifically, Fannie Mae's performance would have been 31.0 percent 
in 2000, 30.4 percent in 2001, 30.2 percent in 2002, and 29.2 
percent in 2003. Freddie Mac's performance would have been 29.2 
percent in 2000, 28.2 percent in 2001, 28.0 percent in 2002, and 
27.7 percent in 2003.
    Performance on the Underserved Areas Goal under 2001-2003 
Counting Rules. If the 2001-03 counting rules had been in effect in 
2000-02 and the GSEs had purchased the same mortgages that they 
actually did purchase in those years (i.e., abstracting from any 
behavioral effects of ``bonus points,'' for example), both GSEs 
would have surpassed the underserved areas goal in all four years, 
and both GSEs' performance figures would have increased from 2000 to 
2002. Specifically, Fannie Mae's ``Baseline C'' performance would 
have been 32.3 percent in 2000, 32.6 percent in 2001, 32.4 percent 
in 2002, and 32.1 percent in 2003. Freddie Mac's performance would 
have been 31.4 percent in 2000, 31.7 percent in 2001, slightly less 
than 31.0 percent in 2002, and 32.7 percent in 2003. Measured on 
this consistent basis, then, Fannie Mae's performance increased by 
0.3 percentage point in 2001, fell by 0.7 percentage points in 2002, 
and increased by 1.3 percentage points in 2003. These increases were 
the effect of increased purchases of mortgages eligible to receive 
bonus points between 2000 and 2001-03.
    Details of Effects of Changes in Counting Rules on Goal 
Performance in 2001. As discussed above, counting rule changes that 
took effect in 2001 had significant impacts on the performance of 
both GSEs on the underserved areas goal in that year--2.2 percentage 
points for Fannie Mae, and 3.5 percentage points for Freddie Mac. 
This section breaks down the effects of these changes on goal 
performance for both GSEs; results are shown in Table B.7a along 
with figures for other years.
    Freddie Mac. The largest impact of the counting rule changes on 
Freddie Mac's goal performance was due to bonus points for purchases 
of mortgages on small multifamily properties; this added 1.3 
percentage points to goal performance in 2001, 0.5 percentage point 
in 2002, and 2.9 percentage points in 2003, as shown in Table B.7a. 
The application of the temporary adjustment factor for purchases of 
mortgages on large multifamily properties enacted by Congress added 
0.9 percentage points to goal performance in 2002 and 1.3 percentage 
points in 2003. Bonus points for purchase of mortgages on owner-
occupied 2-4 unit rental properties also added 1.1 percentage points 
to performance in 2001, 1.6 percentage points in 2002, and 0.9 
percentage point in 2003. Credit for purchases of qualifying 
government-backed loans played a minor role in determining Freddie 
Mac's goal performance.
    Fannie Mae. The temporary adjustment factor which applied to 
Freddie Mac's goal performance did not apply to Fannie Mae, thus 
overall counting rule changes had less impact on its performance 
than on Freddie Mac's performance in 2001-03. The largest impact of 
the counting rule changes on Fannie Mae's goal performance was due 
to the application of bonus points for purchases of mortgages on 
owner-occupied 2-4 unit rental properties, which added 1.7 
percentage points to performance in 2001, 1.8 percentage points in 
2002, and 1.7 percentage points in 2003, and for purchases of 
mortgages on small multifamily properties, which added 0.5 
percentage point to performance in 2001, 0.8 percentage point in 
2002, and 1.2 percentage points in 2003. Credit for purchases of 
qualifying government-backed loans also played a minor role in 
determining Fannie Mae's goal performance.

d. Bonus Point Incentives for the GSEs' Purchases in Underserved Areas

    The Department established ``bonus points'' for 2001-03 to 
encourage the GSEs to step up their activity in two segments of the 
mortgage market--the small (5-50 unit) multifamily mortgage market, 
and the market for mortgages on 2-4 unit properties where 1 unit is 
owner-occupied and 1-3 units are occupied by renters.
    Bonus points for small multifamily properties. Each unit 
financed in a small multifamily property that qualified for any of 
the housing goals was counted as two units in the denominator (and 
one unit in the numerator) in calculating goal performance for that 
goal.
    Fannie Mae financed 37,389 units in small multifamily properties 
in 2001 that were eligible for the underserved areas goal, an 
increase of more than 400 percent from the 7,196 units financed in 
2000. Further increases were recorded in 2002, to 77,382 units, and 
in 2003, to 230,290 units. As explained in Appendix A, small 
multifamily properties also accounted for a greater share of Fannie 
Mae's multifamily business in 2001--7.4 percent of total multifamily 
units financed, up from 2.5 percent in 2000, with this share rising 
to 16.8 percent in 2002 and 28.9 percent in 2003. However, HUD's 
Housing Goals 2000 Final Rule cited a Residential Finance Survey 
finding that small multifamily properties account for 37 percent of 
total units in multifamily mortgaged properties, thus Fannie Mae is 
still somewhat less active in this market than in the market for 
large multifamily properties.\42\
---------------------------------------------------------------------------

    \42\ 65 FR 65141 & n. 145 (2000).
---------------------------------------------------------------------------

    Within the small multifamily market, there was some evidence 
that Fannie Mae targeted properties in underserved areas to a 
greater extent in 2001 than in 2000. That is, 56 percent of Fannie 
Mae's small multifamily units qualified for the underserved areas 
goal in 2000, but this rose to 64 percent in 2001. The share of 
Fannie Mae's small multifamily units that qualified for the 
underserved areas goal was 65 percent in 2002 and 50 percent in 
2003.
    Freddie Mac financed 50,211 units in small multifamily 
properties in 2001 that were eligible for the underserved areas 
goal, an increase of more than 1500 percent from the small base of 
2,985 units financed in 2000. Financing of such units actually fell 
in 2002, to 22,195 units, but rebounded to 181,126 units in 2003. 
Small multifamily properties also accounted for a significantly 
greater share of Freddie Mac's multifamily business in 2001--16.1 
percent of total multifamily units financed, up from 1.8 percent in 
2000, with this share amounting to 7.1 percent in 2002 and 30.5 
percent in 2003.
    Within the small multifamily market, there was some evidence 
that Freddie Mac targeted properties in underserved areas to a 
greater extent in 2001 than in 2000. That is, 61 percent of Freddie 
Mac's small multifamily units qualified for the underserved areas 
goal in 2000; this rose to 86 percent in 2001. The share of Freddie 
Mac's small multifamily units that qualified for the underserved 
areas goal was 88 percent in 2002 and 87 percent in 2003.
    Bonus points for single-family rental properties. Above a 
threshold, each unit financed in a 2-4 unit property with at least 
one owner-occupied unit (referred to as ``OO24s'' below) that 
qualified for any of the housing goals was counted as two units in 
the denominator (and one unit in the numerator) in calculating goal 
performance for that goal in 2001-03. The threshold was equal to 60 
percent of the average number of such qualifying units over the 
previous five years. For example, Fannie Mae financed an average of 
47,100 underserved area units in these types of properties between 
1996 and 2000, and 105,946 such units in 2001. Thus in 2001 Fannie 
Mae received 77,688 bonus points in this area in 2001--that is, 
105,946 minus 60 percent of 47,100. So 183,629 units were entered in 
the numerator for these properties in calculating underserved area 
goal performance.
    Single-family rental bonus points thus encouraged the GSEs to 
play a larger role in this market, and also to purchase mortgages on 
such properties in which large shares of the units qualify for the 
housing goals. As for small multifamily bonus points, some evidence 
on the effects of such bonus points on the GSEs' operations may be 
gleaned from the data provided to HUD by the GSEs for 2001-2003.

[[Page 63776]]

    Fannie Mae financed 177,872 units in OO24s in 2001 that were 
eligible for the underserved areas goal, an increase of 116 percent 
from the 82,464 units financed in 2000. Further increases were 
recorded in 2002, to 231,581 units, and in 2003, to 353,916 units. 
However, as a result of the refinance boom Fannie Mae's total 
single-family business increased at approximately the same rate as 
its OO24 business in 2001-03, thus the share of its business 
accounted for by OO24s was the same in 2001 as in 2000--4 percent, 
with this share also amounting to 4 percent in 2002 and 2003.
    Within the OO24 market, there was no evidence that Fannie Mae 
targeted affordable properties to a greater extent in 2001 than in 
2000. That is, approximately 60 percent of Fannie Mae's OO24 units 
qualified for the underserved area goal in both 2000 and 2001. The 
share of Fannie Mae's OO24 units that qualified for the underserved 
areas goal was 62 percent in 2002 and 60 percent in 2003.
    Freddie Mac financed 96,983 units in OO24s in 2001 that were 
eligible for the underserved areas goal, an increase of 91 percent 
from the 50,868 units financed in 2000. Further increases were 
recorded in 2002, to 146,502 units, and in 2003, to 154,924 units. 
However, with the refinance boom, Freddie Mac's total single-family 
business increased at approximately the same rate as its OO24 
business in 2001-03, thus the share of its business accounted for by 
OO24s was the same in 2001 as in 2000--3 percent, with this share 
amounting to 3.7 percent in 2002 and 3.1 percent in 2003.
    As for Fannie Mae, within the OO24 market there was no evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001 than in 2000. That is, 60 percent of Fannie Mae's OO24 units 
qualified for the underserved areas goal in both 2000 and 2001. The 
share of Freddie Mac's OO24 units that qualified for the underserved 
areas goal was 61 percent in 2002 and 50 percent in 2003.

e. Effects of 2000 Census on Scoring of Loans Toward the Underserved 
Areas Housing Goal

    Background. Scoring of housing units under the Underserved Areas 
Housing Goal is based on decennial census data used to identify 
underserved areas, as follows: For properties in MSAs scoring is 
based on the median income of the census tract where the property is 
located, the median income of the MSA, and the percentage minority 
population in the census tract where the property is located. For 
properties located outside of MSAs scoring is based on the median 
income of the county, the median income of the non-metropolitan 
portion of the State in which the property is located or of the non-
metropolitan portion of the United States, whichever has the larger 
median income, and the percentage minority population in the county 
where the property is located. Thus, scoring loans under the 
Underserved Areas Housing Goal requires decennial census data on 
median incomes for metropolitan census tracts, MSAs, non-
metropolitan counties, the non-metropolitan portions of States, and 
the non-metropolitan portion of the United States. The determination 
has been based on 1990 census data through 2004, and beginning in 
2005 will be based on 2000 census data.43, 44 Under this 
rule, the basis for the determination outside of MSAs will change 
from counties to census tracts beginning in 2005.
---------------------------------------------------------------------------

    \43\ In New England, MSAs were defined through mid-2003 in terms 
of Towns rather than Counties, and the portion of a New England 
county outside of any MSA is regarded as equivalent to a county in 
establishing metropolitan or non-metropolitan location of a 
property. The MSA definitions established by the Office of 
Management and Budget (OMB) in June, 2003 defined MSAs in New 
England in terms of counties.
    \44\ The procedure used to generate estimated rents in 
connection with the Low- and Moderate Income and Special Affordable 
Housing Goals, as mentioned in Appendixes A and C, uses similar data 
series.
---------------------------------------------------------------------------

    2005 Procedure. Relative to the above procedure, Underserved 
Areas Housing Goals performance percentages for loans purchased by 
the GSEs in and after 2005 will be affected by three factors. First, 
2000 census data on median incomes and minority populations replace 
1990 census data. Second, the Office of Management and Budget in 
June, 2003, respecified MSA boundaries based on analysis of 2000 
census data. Third, the Department's re-specification of the 
Underserved Areas goal in terms of census tracts rather than 
counties in non-metropolitan areas will come into effect.\45\ Thus, 
for properties located outside of MSAs the basis of determination 
for non-metropolitan areas will be changed for properties located 
outside of MSAs to: The median income of the census tract where the 
property is located; the median income of the non-metropolitan 
portion of the State in which the property is located or of the non-
metropolitan portion of the United States, whichever is larger; and 
the percentage minority population in the census tract where the 
property is located.
---------------------------------------------------------------------------

    \45\ HUD has deferred application of the 2000 census data and 
2003 MSA designations to 2005, pending completion of the present 
rulemaking process.
---------------------------------------------------------------------------

    Analysis. HUD used 2000 census data to generate underserved area 
designations for census tracts as defined for the 2000 census with 
2003 MSA designations. Because Fannie Mae and Freddie Mac geocoded 
the mortgages they purchased prior to 2003 based on census tract 
boundaries as established for the 1990 census, GSE mortgages 
purchased prior to 2003 can be directly identified as being from a 
served or underserved area only where the property is located in a 
1990-defined census tract whose area consists entirely of whole 
2000-defined census tracts, or portions of such tracts, which are 
all designated either as served or as underserved. In the situation 
where the area of a 1990-defined census tract includes whole 2000-
defined census tracts, or portions of such tracts, some of which are 
served and some underserved, HUD calculated an ``underservice 
factor'' defined as the underserved percentage of the 1990-defined 
tract's population, based on population data from the 2000 
census.\46\ These factors were used in estimating underservice 
percentages for aggregated GSE purchases in and before 2003 based on 
the 2000 census.
---------------------------------------------------------------------------

    \46\ 8,717 tracts included both served and underserved area, out 
of a total of 61,493 tracts that could be classified as served or 
underserved or assigned an underservice factor.
---------------------------------------------------------------------------

    The resulting underserved areas file was used to re-score loans 
purchased by the GSEs between 1999 and 2003, and was used further in 
estimating the share of loans originated in metropolitan areas that 
would be eligible to score toward the Underserved Areas Housing 
Goal, from HMDA data. The results of the retrospective GSE analysis 
are provided in Table B.7b The results of the GSE-HMDA comparative 
analysis are presented in the next section.
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[[Page 63778]]


    Table B.7b shows four sets of estimates for each GSE, based 
respectively on the counting rules in place in 2001-2003 (but 
disregarding the bonus points and Temporary Adjustment Factor), on 
shifting from 1990 to 2000 census data on median incomes and 
minority concentrations, on the further addition 2003 MSA 
specification, and finally on shifting from counties to tracts as 
the basis for scoring loans in non-metropolitan areas.

2. GSEs' Mortgage Purchases in Metropolitan Neighborhoods

    Metropolitan areas accounted for about 85 percent of total GSE 
purchases under the Underserved Areas Housing Goal in 2001 and 2002. 
This section uses HMDA and GSE data for metropolitan areas to 
examine the neighborhood characteristics of the GSEs' mortgage 
purchases. In subsection 2.a, the GSEs' performance in underserved 
neighborhoods is compared with the overall market. This section 
therefore expands on the discussion in Appendix A, which compared 
the GSEs' funding of affordable loans with the overall conventional 
conforming market. A subgoal that the Department is establishing for 
each GSE's acquisitions of home purchase loans financing properties 
in the underserved census tracts of metropolitan areas is also 
discussed subsection 2a. In subsection 2.b., the characteristics of 
the GSEs' purchases within underserved areas are compared with those 
for their purchases in served areas.

a. Comparisons With the Primary Market

    Market Comparisons Based on 1990 Census Geography. Section E.8-
10 in Appendix A provided detailed information on the GSEs' funding 
of mortgages for properties located in underserved neighborhoods for 
the years 1993 to 2003. To take advantage of historical data going 
back to 1993, these comparisons were first made using 1990 Census 
tract geography. The findings with respect to the GSEs' funding of 
underserved neighborhoods are similar to those reported in Appendix 
A regarding the GSEs' overall affordable lending performance in the 
single-family-owner market. While both GSEs improved their 
performance, they historically lagged the conventional conforming 
market in providing affordable loans to underserved neighborhoods. 
The two GSEs themselves engaged in very different patterns of 
funding--Freddie Mac was less likely than Fannie Mae to fund home 
loans in underserved neighborhoods, as the following percentage 
shares for home purchase loans indicate:

----------------------------------------------------------------------------------------------------------------
                                                                    Freddie Mac     Fannie Mae     Market  (w/o
                              Year                                   (percent)       (percent)    B&C) (percent)
----------------------------------------------------------------------------------------------------------------
1996-2003.......................................................            22.0            24.0            25.7
1999-2003.......................................................            23.1            24.7            26.2
2001-2003.......................................................            24.1            26.0            26.4
----------------------------------------------------------------------------------------------------------------

    Between 1996 and 2003, 22.0 percent of Freddie Mac's purchases 
financed properties in underserved neighborhoods, compared with 24.0 
percent of Fannie Mae's purchases and 25.7 percent of home purchase 
loans originated in the conventional conforming market (excluding 
B&C loans). Thus, Freddie Mac performed at only 86 percent of the 
market (22.0 divided by 25.7), while Fannie Mae performed at 93 
percent of the market. Freddie Mac's recent performance has been 
slightly closer to the market. Over the past three years (2001 to 
2003), Freddie Mac performed at 91 percent of the market (24.1 
percent for Freddie Mac compared at 26.4 percent for the market). 
(See Tables A.13 to A.16 in Appendix A for complete data going back 
to 1993.)
    Fannie Mae has funded underserved areas at a higher level than 
Freddie Mac, as indicated above. And during 2001 and 2003, Fannie 
Mae average performance was only slightly below the market. In 2003, 
the share of Fannie Mae's purchases going to underserved areas was 
26.8 percent, compared with a market level of 27.6 percent. Like 
Freddie Mac, Fannie Mae's longer-term performance (since 1993 or 
1996) as well as its recent average performance (1999 to 2003) has 
consistently been below market levels. Still, it is encouraging that 
Fannie Mae significantly improved its 2001-2003 performance and 
closed its gap with the market during the first three years of HUD's 
higher housing goal levels.
    Market Comparisons Based on 2000 Census Geography. As explained 
in Section A.2 of this appendix, HUD will be defining underserved 
areas based on 2000 Census data beginning in 2005. The number of 
census tracts in metropolitan areas covered by HUD's definition will 
increase from 21,587 tracts (based on 1990 Census) to 26,959 tracts 
(based on 2000 Census and new OMB metropolitan area specifications). 
The increase in the number of tracts defined as underserved means 
that both GSE performance and the market estimates will be higher 
than reported above. This section provides an analysis of the 
performance of the GSEs in the single-family-owner market based on 
2000 census tract geography. For the years 1999, 2000, 2001, and 
2002, HUD used the apportionment technique to re-allocate 1990-based 
GSE and HMDA data into census tracts as defined by the 2000 Census. 
GSE and HMDA data for 2003 were already expressed in terms of 2000 
Census geography.
    The main results are provided in Table B.8, which compares the 
GSEs to the market using both the 1990 Census geography and the 2000 
Census geography. Switching to the 2000-based tracts increases the 
underserved area share of market originations by about five 
percentage points. Between 1999 and 2003, 31.4 percent of home 
purchase mortgages (without B&C loans) were originated in 
underserved tracts based on 2000 geography, compared with 26.2 
percent based on 1990 geography--a differential of 5.2 percentage 
points. As also shown in Table B.8, the underserved areas share of 
Fannie Mae's purchases rises by 5.3 percentage points, and the 
underserved areas share of Freddie Mac's purchases rises by 5.2 
percentage points. Thus, the conclusions reported above and in 
Appendix A about the GSEs' performance relative to the market about 
remain the same when the analysis is conducted based on 2000 Census 
geography.

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    It is interesting to repeat the earlier 1990-based analysis of 
home purchase loans but this time based on the 2000 Census 
geography. The following results are obtained for home purchase 
loans from Table B.8:

----------------------------------------------------------------------------------------------------------------
                                                                    Freddie Mac     Fannie Mae     Market  (w/o
                              Year                                   (percent)       (percent)    B&C) (percent)
----------------------------------------------------------------------------------------------------------------
1999............................................................            25.6            25.3            30.2
2000............................................................            27.3            29.0            31.7
2001............................................................            27.3            29.8            30.7
2002............................................................            31.7            32.3            31.8
2003............................................................            29.0            32.0            32.5
1996-2003 (estimate)............................................            27.2            29.3            30.9
1999-2003 (average).............................................            28.3            30.0            31.4
2001-2003 (average).............................................            29.4            31.4            31.7
----------------------------------------------------------------------------------------------------------------

    Between 1999 and 2003, 28.3 percent of Freddie Mac's purchases 
and 30.0 percent of Fannie Mae's purchases financed properties in 
underserved neighborhoods, compared with 31.4 percent home purchase 
loans originated in the conventional conforming market (excluding 
B&C loans). Thus, Freddie Mac performed at 90 percent of the market 
level, while Fannie Mae performed at 96 percent of the market 
level--both results similar to those reported above for underserved 
areas based on 1990 Census geography. The 2000 Census data show that 
the Fannie Mae has been much closer to the market during the recent 
2001-2003 period. The share of Fannie Mae's purchases going to 
underserved areas was 31.4 during 2001-2003, which placed it close 
to the market level of 31.7 percent. However, the 2000-based results 
show that, like Freddie Mac, Fannie Mae's longer-term performance 
(since 1996) as well as its recent average performance (1999 to 
2003) have consistently been below market levels. (Note that the 
1996-2003 averages reported above are estimated by adding the 
following 2000-Census versus 1990-Census differentials calculated 
for 1999-2003: 5.2 percentage points for Freddie Mac, 5.3 for Fannie 
Mae, and 5.2 for the market.)
    Underserved Area Subgoal for Home Purchase Loans. The Department 
is establishing a subgoal of 32 percent for each GSE's acquisitions 
of home purchase loans financing single-family-owner properties 
located in the underserved census tracts of metropolitan areas for 
2005, with this subgoal rising to 33 percent for 2006 and 2007, and 
to 34 percent in 2008. If the GSEs meet the 2008 subgoal, they will 
be leading the primary market by over two percentage points, based 
on historical data. This home purchase subgoal will encourage the 
GSEs to provide additional credit and capital to urban neighborhoods 
that historically have not been adequately served by the mortgage 
industry--but in the future may be the very neighborhoods where the 
growing population of immigrants and minorities choose to live. As 
detailed in Section I.5 of this appendix, there are four specific 
reasons for establishing this subgoal: (1) The GSEs have the 
expertise, resources, and ability to lead the single-family-owner 
market, which is their ``bread and butter'' business; (2) the GSEs 
have been lagging the primary market in underserved areas, not 
leading it; (3) the GSEs can help reduce troublesome neighborhood 
disparities in access to mortgage credit; and (4) there are ample 
opportunities for the GSEs to expand their purchases in low-income 
and high-minority neighborhoods. Sections E.9 and G of Appendix A 
provide additional information on the opportunities for an enhanced 
GSE role in underserved area segment of the home purchase market and 
on the ability of the GSEs to lead that market.
    As discussed above, underserved areas accounted for an average 
of approximately 31.5 percent of home purchase loans originated in 
the conventional conforming market of metropolitan areas (computed 
over 1999-2003 or over 2001-2003). To reach the 34-percent subgoal 
for 2008, both GSEs will have to improve over their earlier peak 
performances--Freddie Mac by 2.3 percentage points over its previous 
peak performance of 31.7 percent in 2002, and Fannie Mae by 1.7 
percentage points over its previous peak performance of 32.3 percent 
in 2003. To meet the 2008 subgoal, Freddie Mac will have to improve 
by 2.6 percentage points over its 2002-2003 average (unweighted) 
performance of 30.4 percent, while Fannie Mae will have to improve 
by 1.8 percentage points over its 2002-2003 average performance of 
32.2 percent.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for non-metropolitan counties are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices A and C.

b. Characteristics of GSEs' Purchases of Mortgages on Properties in 
Metropolitan Underserved Areas

    Several characteristics of loans purchased in 2003 by the GSEs 
in metropolitan underserved areas are presented in Table B.9. As 
shown, borrowers in underserved areas are more likely than borrowers 
in served areas to be first-time homebuyers, all female, all male 
and younger than 40. And, as expected, borrowers in underserved 
areas are more likely to have below-median income and to be members 
of minority groups. For example, first-time homebuyers make up 6.7 
percent of the GSEs' mortgage purchases in underserved areas and 4.2 
percent of their business in served areas. In underserved areas, 
53.7 percent of borrowers had incomes below the area median, 
compared with 36.4 percent of borrowers in served areas.
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[[Page 63782]]

    Minorities' share of the GSEs' mortgage purchases in underserved 
areas (33.2 percent) was greater than two times their share in 
served areas (13.9 percent). And the pattern was even more 
pronounced for African Americans and Hispanics, who accounted for 
23.1 percent of the GSEs' business in underserved areas, but only 
7.0 percent of their purchases in served areas.
    Other similarities in Fannie Mae and Freddie Mac purchases in 
served and underserved areas include the following. The GSEs are 
slightly more likely to purchase refinance loans in served areas 
than in underserved areas; mortgage purchases with loan-to-value 
ratios below 80 percent are more likely to be in underserved than in 
served areas; and seasoned mortgage purchases are more likely to be 
in underserved than in served areas.

3. GSE Mortgage Purchases in Nonmetropolitan Areas

    There are numerous studies that have evaluated the impact of the 
GSEs' purchases on metropolitan areas, but few address the impact on 
nonmetropolitan areas; therefore, our understanding of the GSEs and 
the nonmetropolitan markets is very limited.
    A study of the GSE market share in underserved counties \47\ 
found that location has a role in the accessibility of credit for 
some people in nonmetropolitan areas (low income, minority, and 
first-time homebuyers). West North Central counties (Minnesota, 
Missouri, South Dakota, Iowa, Kansas, Nebraska, and North Dakota) 
have much lower GSE activity than all other geographic regions, 
suggesting that the 1995 definition of underservice does not capture 
the specific characteristics of this region, leading to limited GSE 
activity.
---------------------------------------------------------------------------

    \47\ Heather MacDonald, ``Fannie Mae and Freddie Mac in 
Nonmetropolitan Housing Markets: Does Space Matter?'' Cityscape: A 
Journal of Policy Development and Research, Volume 5, 2001, pp. 219-
264.
---------------------------------------------------------------------------

    Additionally, The Urban Institute prepared a report for HUD that 
investigated the factors influencing GSE activity in nonmetropolitan 
areas.\48\ The authors found that Fannie Mae and Freddie Mac have 
increased their lending to nonmetropolitan areas since 1993; 
however, there are still weak areas in terms of the percentage of 
affordable loans being offered.\49\ They also established that GSE 
underwriting criteria was not a major barrier in nonmetropolitan 
areas.
---------------------------------------------------------------------------

    \48\ Jeanette Bradley, Noah Sawyer and Kenneth Temkin, Factors 
Influencing GSE Service to Rural Areas, The Urban Institute, 
prepared for U.S. Department of Housing and Urban Development, 2002.
    \49\ Affordable loans are defined as borrowers earning less than 
80 percent the Area Median Income.
---------------------------------------------------------------------------

    In nonmetropolitan areas, the financial market is often made up 
of locally owned community banks, manufactured home lenders, and 
subprime lenders. Industry representatives contacted by the Urban 
Institute researchers assessed that the barriers nonmetropolitan 
lenders faced were in the areas of availability of sales 
comparables, technology, and the type and number of lenders in the 
area. They also believed that for the GSEs' market share to improve 
in underserved nonmetropolitan areas, the GSEs would have to begin 
to build relationships with the community lenders and provide 
education/training on how to sell loans directly to the GSEs rather 
than using intermediaries.

a. Effects of 2000 Census Geography

    In order to compare served and underserved areas, either in 
terms of GSE performance or socioeconomic characteristics, it is 
first necessary to update current geographic (county) designations, 
which reflect 1990 census median income and minority population 
data, to reflect newly available 2000 census data. Table B.10 shows 
the impact on 2000, 2001, and 2002 GSE purchases. These are reported 
for total GSE purchases and separately for Fannie Mae and Freddie 
Mac. As above, the results also are shown separately for counties 
that change classification and those that do not. This analysis is 
limited to nonmetropolitan areas based on both the pre- and post-
June, 2003 OMB metropolitan area designations.
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    Applying 2000 census median income and minority population data 
results in a slight drop in the proportion of counties that are 
classified as underserved. Out of a total of 2,493 counties, 1,514 
(65.5 percent) are underserved based on 1990 data, and 1,260 (61.4 
percent) based on 2000 data. This small net change disguises a 
somewhat larger shift of counties, as about 11.2 percent of 
currently underserved counties are reclassified as served counties 
and 4.6 percent of currently served counties are reclassified as 
underserved.
    Comparing underserved and served nonmetropolitan areas in Table 
B.10, it is apparent that underserved nonmetropolitan areas make up 
a larger percentage of nonmetropolitan areas as a whole than do 
served nonmetropolitan areas, as shown by the number of counties 
(1,260 for underserved (61.4%); 792 for served (38.6%)). These 
relationships hold true also for the number of households (9.5 
million for underserved (50.5%); 9.3 million for served (49.5%)), 
and the population (24.9 million for underserved (51%); 23.9 million 
for served (49%)) as shown in Table B.5.
    Table B.10 shows that Fannie Mae's performance in 2002 (40.2 
percent) was somewhat higher than Freddie Mac's (36.3 percent). This 
gap widens slightly (1.8 percent) in applying 2000 census income and 
minority data and 2003 metropolitan area definitions.

b. Characteristics of GSEs' Purchases of Mortgages on Properties in 
Nonmetropolitan Underserved Areas

    Nonmetropolitan mortgage purchases made up 12.6 percent of the 
GSEs' total mortgage purchases in 2003. Mortgages in underserved 
counties made up 38.6 percent of the GSEs' business in 
nonmetropolitan areas.\50\
---------------------------------------------------------------------------

    \50\ Underserved areas make up about 56 percent of the census 
tracts in nonmetropolitan areas and 47 percent of the census tracts 
in metropolitan areas. This is one reason why underserved areas 
comprise a larger portion of the GSEs' single-family mortgages in 
nonmetropolitan areas (39 percent) than in metropolitan areas (23 
percent).
---------------------------------------------------------------------------

    Unlike the underserved areas definition for metropolitan areas, 
which is based on census tracts, the rural underserved areas 
definition is based on counties. Rural lenders argued that they 
identified mortgages by the counties in which they were located 
rather than the census tracts; and therefore, census tracts were not 
an operational concept in rural areas. Market data on trends in 
mortgage lending for metropolitan areas are provided by HMDA; 
however, no comparable data source exists for rural mortgage 
markets. The absence of rural market data is a constraint for 
evaluating credit gaps in rural mortgage lending and for defining 
underserved areas.
    One concern is whether the broad definition overlooks 
differences in borrower characteristics in served and underserved 
counties that should be included. Table B.11 compares borrower and 
loan characteristics for the GSEs' mortgage purchases in served and 
underserved areas.
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    Fannie Mae is slightly more likely and Freddie Mac is less 
likely to purchase loans for first-time homebuyers in underserved 
areas than in served areas. Mortgages to first-time homebuyers 
accounted for 4.3 percent of Fannie Mae's mortgage purchases in 
served counties, compared with 4.6 percent of its purchases in 
underserved counties. For Freddie Mac the corresponding figures are 
3.4 percent in served counties and 3.3 percent in underserved 
counties.
    The GSEs are more likely to purchase mortgages for high-income 
borrowers in underserved than in served counties. Surprisingly, 
borrowers in served counties were more likely to have incomes below 
the median than in underserved counties (39.6 percent compared to 
35.4 percent). These findings lend some support to the claim that, 
in rural underserved counties, the GSEs purchase mortgages for 
borrowers that probably encounter few obstacles in obtaining 
mortgage credit.
    The following similarities in Fannie Mae and Freddie Mac 
purchases in served and underserved counties in nonmetropolitan 
areas mirror those found for the GSEs in served and underserved 
census tracts in metropolitan areas. The GSEs are slightly more 
likely to purchase refinance loans in served than in underserved 
counties; mortgage purchases with loan-to-value ratios below 80 
percent are more likely to be in underserved than in served 
counties; and seasoned mortgage purchases are more likely to be in 
underserved than in served counties.

E. Factor 4: Size of the Conventional Conforming Mortgage Market 
for Underserved Areas

    HUD estimates that underserved areas account for 35-39 percent 
of the conventional conforming mortgage market. The analysis 
underlying this estimate is detailed in Appendix D.

F. Factor 5: Ability to Lead the Industry

    This factor is the same as the fifth factor considered under the 
goal for mortgage purchases on housing for low- and moderate-income 
families. Accordingly, see Section G of Appendix A for a discussion 
of this factor, as well as Section I.5 of this Appendix, which 
describes the home purchase subgoal which is designed to place the 
GSEs in a leadership role in the underserved market.

G. Factor 6: Need to Maintain the Sound Financial Condition of the 
Enterprises

    HUD has undertaken a separate, detailed economic analysis of 
this rule, which includes consideration of (a) the financial returns 
that the GSEs earn on loans in underserved areas and (b) the 
financial safety and soundness implications of the housing goals. 
Based on this economic analysis and reviewed by the Office of 
Federal Housing Enterprise Oversight, HUD concludes that the goals 
raise minimal, if any, safety and soundness concerns.

H. Defining Nonmetropolitan Underserved Areas

1. Whether to Adopt a Tract-Based Definition of Underserved Areas

    The current county-based definition for targeting GSE purchases 
to underserved nonmetropolitan areas was adopted in 1995 over 
alternative narrower definitions, such as census tracts, despite the 
use of census tracts in metropolitan areas. In the 1995 Final Rule, 
HUD found the merits of a county-based system of targeting 
outweighed a tract-based system. Now, with seven years of experience 
under a county-based system, the release of Census 2000 data, and 
improvements in information technology and systems, HUD can 
reexamine whether to switch to census tracts for defining 
underserved nonmetropolitan areas. This section compares impacts of 
the potential shift in definition for both served and underserved 
populations as determined by tract-based and county-based 
definitions using a number of common industry variables as focal 
points for analysis.
    The rationale for choosing counties in 1995 rested primarily on 
perceived shortcomings of census tracts.\51\ In particular, rural 
lenders did not perceive their market areas in terms of census 
tracts, but rather, in terms of counties. Another concern was a 
perceived lack of reliability in geocoding 1990 census tracts. At 
the same time, HUD found merit in using a tract-based geography for 
nonmetropolitan areas. Because tracts encompass more homogeneous 
populations than counties, they permit more precise targeting of 
underserved populations. In other words, more homogeneous geographic 
areas increase the potential for targeting the GSE mortgage 
purchases into areas where borrowers are more likely to face 
obstacles and other challenges in securing mortgage credit.
---------------------------------------------------------------------------

    \51\ 60 FR 61,925-58 (1995) (Appendix B).
---------------------------------------------------------------------------

    The criteria used for this analysis include the following:
    7. Do tracts provide a sharper delineation of served and 
underserved areas? Specifically, are underserved nonmetropolitan 
populations more clearly differentiated by adopting tracts vs. 
counties? Could service to the underserved nonmetropolitan 
populations be more comprehensive under tract-based definitions?
    8. What is the impact on GSE purchasing patterns if underserved 
areas are defined by tract?
    9. Applying the current criteria for identifying underserved 
areas to tracts would result in reclassifying approximately 23 
percent of all tracts, with 28 percent of tracts in served counties 
being redesignated as underserved and 19 percent of tracts in 
underserved counties being redesignated as served. Overall, roughly 
the same percentage of families (and population) would be 
reclassified. However, because underserved tracts are somewhat less 
densely populated than served tracts, the corresponding proportions 
of families that shift from served and underserved counties are 
closer: 25 vs. 21 percent.

a. Do Census Tracts Allow a Sharper Delineation of Served and 
Underserved Areas?

    This section compares the differences in housing need and 
economic, demographic, and housing conditions in served and 
underserved nonmetropolitan areas classified on, respectively, 
counties and tracts. Additionally, the ``efficiency'' with which 
counties and tracts cover the target populations is compared. That 
is, does tract-based targeting do a better job of capturing lower 
income households and excluding higher income households than 
county-based targeting?
    Table B.12 presents several indicators of socioeconomic and 
housing condition in served and underserved areas under both a 
tract-based and a county-based definition. In addition, served and 
underserved counties are subdivided into their served and 
underserved tract components. This allows a closer examination of 
the population and housing characteristics of the tracts that are 
reclassified (i.e., served to underserved or visa versa) under 
tract-based targeting. Thus, area characteristics of housing need 
and housing, economic, and demographic conditions can be compared, 
for the following four groups of tracts: (1) Tracts in served 
counties that would remain ``served'' classified as tracts; (2) 
tracts that remain ``underserved''; (3) tracts that shift from 
served to underserved; and (4) tracts that shift from underserved to 
served. In addition, we provide counts of tracts falling into each 
of these groups. If a tract-based classification of underserved 
areas improves geographic targeting, the regrouping of tracts would 
be more similar to one another than to the other tracts in their 
respective counties: e.g., formerly underserved areas that become 
served should be more similar to tracts that were and remain served 
than to underserved (unchanged).
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    Socioeconomic and Demographic Conditions. Table B.12 shows that 
in important socioeconomic and demographic characteristics, tract-
based targeting would more effectively distinguish underserved 
populations. Median family income, poverty, unemployment, school 
dropout rates, and minority population all exhibit greater 
differences between served and underserved areas using tracts. For 
example, the difference in median income between served and 
underserved counties is $9,579, or alternatively, between served and 
underserved tracts, the difference is $12,744. Similarly, there is a 
7-percentage point gap in poverty rates (7.5 vs. 14.5 percent 
poverty) using counties, which widens to 8.6 percentage points (6.6 
vs. 15.3 percent) using tracts. Minority population also is captured 
somewhat better with tracts, with the served/underserved gap 
increasing from 16.5 to 17.3 percentage points. In all cases, the 
levels of the indicators for underserved areas move in a direction 
consistent with targeting lower income households and areas with 
higher minority populations.
    The 4-way breakdown of served and underserved counties reveals 
some significant differences between the two component groups. In 
most respects, ``underserved tracts'' (i.e., those meeting the 
underserved criteria), whether located in an underserved or served 
county, are more alike than they are like served tracts. Using 
median income again to illustrate, the effect of reclassifying areas 
by tract characteristics is to put together two groups of 
underserved tracts: Tracts that were in previously underserved 
counties and are not reclassified and tracts that were in served 
counties but meet the underserved criteria. A new group of served 
tracts is similarly formed. In both cases, the difference in median 
incomes of the constituent groups is about $3,500. In contrast, the 
served and underserved counties now encompass ``served'' and 
``underserved'' groups of tracts whose respective median incomes 
differ by almost $11,000. Combined with the fact that a fairly large 
number of tracts are affected overall (i.e., switch), these results 
support an assessment that counties are relatively crude for 
targeting underserved populations.
    Housing Needs and Conditions. Table B.12 shows that tract-based 
targeting would produce modest gains in focusing GSE purchases on 
areas with relatively greater housing needs and conditions as 
measured by low owner-occupancy, higher vacancy rates, and crowding. 
For each of these indicators, measured need increases in underserved 
areas and the gap between served and underserved areas widens when 
tracts are used to classify areas. Most notably, the percent of 
owner-occupied housing units switches from being higher in 
underserved than served counties to being significantly lower among 
underserved tracts. With a shift to tracts overall ownership drops 
in underserved areas, from 74 to 72 percent, and increases in served 
areas from 74 to 77 percent. In contrast, the homeownership rate for 
tracts located in served counties that would be deemed underserved 
if judged separately is only 65 percent. In fact, this rate is much 
lower even than underserved tracts in underserved counties. Shifting 
these tracts from served to underserved largely accounts for the 
switching of homeownership rates.
    Results for other indicators of housing need and conditions are 
less clear-cut. No definitive patterns are apparent for two, 
admittedly weak, measures of housing quality--units with complete 
plumbing and units with complete kitchen facilities, as well as for 
crowding. Purchase affordability, as measured by the ratio of median 
housing value to the income necessary to qualify for a loan for the 
median valued unit, is higher in underserved areas than in served 
areas. However, the measure of purchase affordability presented here 
is influenced by many market and other economic factors, some of 
which do not relate to housing need. For example, a low 
affordability ratio may reflect abundant supply, but it may also 
reflect low demand stemming from, e.g., limited availability of 
credit or high interest rates.
    Coverage Efficiency. The coverage efficiency index measures the 
effect of adopting tract-based targeting. This index can be used to 
indicate how well underserved areas encompass populations deemed to 
be underserved (``sensitivity'') and to exclude populations that are 
deemed to be served (``specificity''). The index is computed for 
median income as the difference in two percentages: (1) The 
proportion of all families in nonmetropolitan areas that meet the 
applicable income threshold who live in underserved tracts minus (2) 
the proportion of all families in nonmetropolitan areas that do not 
meet the applicable underserved income threshold who live in 
underserved areas. This difference can range from 1 (perfect) to -1 
(bad; perverse). For example, a coverage efficiency index equal to 1 
implies that every family in need is living in an underserved area 
while there are no families who are not in need living in an 
underserved area; a coverage efficiency index equal to -1 implies 
that none of the families in need live in an underserved area, or 
equivalently, all families in underserved areas are not in need.
    Comparing coverage efficiency for counties and tracts indicates 
that tracts do a better job; capturing a higher percentage of 
nonmetropolitan families whose income falls below the applicable 
income threshold and excluding more families whose income exceeds 
the threshold.\52\ Overall, the efficiency index rises from 0.22 to 
0.274.
---------------------------------------------------------------------------

    \52\ In areas with 30 percent or greater minority population, 
all families with income in excess of 120 percent of the greater of 
State or national median income are counted as qualifying as ``in 
need'' for these computations. Similarly, in areas with less than 30 
percent minority, those minority (headed) families with income 
between 95 and 120 percent of the applicable median income are not 
classified as ``in need.''
---------------------------------------------------------------------------

    Given income thresholds that are not far away from median income 
in most places and the degree of income variation even with census 
tract boundaries, it should not come as a great surprise that 
neither the levels of coverage efficiency (0.22-0.27) nor 
improvement produced in applying tracts (5 percentage points) are 
not more dramatic. Nevertheless, tracts do produce better tracking 
of lower income, very low income, and minority families.

b. Does GSE Performance Vary Between Served and Underserved Tracts 
Within Underserved Counties?

    A similar analytical approach is used to examine how a shift to 
tracts would impact GSE purchases. Having applied income and 
minority thresholds from the 2000 census and updating census tract 
geography, Table B.13 compares, respectively, 2000, 2001, and 2002 
GSE purchases for served and underserved counties and tracts and 
also for the served and underserved tracts within county boundaries. 
On net there would be somewhat more tracts classified as underserved 
under a tract-based system than currently: 6,782 vs. 6,414. As noted 
above, however, 23.1 percent of all tracts are reclassified. Moving 
to tracts also would have a significant effect on the relative 
performance of the GSEs. In 2002, Fannie Mae's performance would 
drop 2.1 percentage points to 35.4 percent, while Freddie Mac's 
performance would increase by 0.9 percent to 32.7 percent.
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    Differences between qualifying purchases of single-family and 
multifamily loans are further increased when assessed at the tract 
level. Performance for single-family loans drops 0.7 percentage 
points to 35.2, but for multifamily increases by 2.5 percentage 
points to 46.8. These changes dramatically compound the results 
observed in updating to 2000 census data, resulting in a widening of 
the single- and multifamily performance difference from the current 
level of 7.0 percentage points to 11.6 percentage points.

2. Alternative Definitions of Underservice

    The current definition of underservice in nonmetropolitan areas 
was established in 1995 to be relatively broad, encompassing nearly 
twice as many underserved as served counties and somewhat more than 
half of the total nonmetropolitan population. This was done 
primarily to ensure that certain areas with low incomes and/or high 
minority populations, which might not be considered underserved in 
comparison to the rest of their State, would nevertheless be 
identified as underserved from a national perspective. This section 
summarizes a new analysis, based on 2000 census data, to evaluate 
the extent to which the current definition focuses GSE purchasing 
activity toward stimulating mortgage lending in areas with 
populations having greatest housing need. Alternative definitions of 
underservice are considered as follows: (1) Variations of the 
current thresholds; (2) applying only the State median income level 
for qualifying underserved counties and tracts; and (3) establishing 
different thresholds in micropolitan and ``outside of core'' 
nonmetropolitan areas. In each case the objective is to assess how 
redesignating served and underserved areas would affect relative 
conditions and needs and GSE purchasing performance. In 
distinguishing micropolitan and ``outside of core'' areas, it is of 
interest to determine whether it would be appropriate to establish 
different thresholds for underservice. The overarching criterion for 
evaluating and comparing definitions is their ability to serve very 
low-income, low-income and moderate-income households, households in 
poverty, first-time homebuyers, minorities, and households in remote 
locations.\53\
---------------------------------------------------------------------------

    \53\ A more comprehensive presentation of this analysis may be 
found in Economic Systems, Inc., Indicators of Mortgage Market 
Underservice in Non-Metropolitan Areas, Interim Report to HUD, March 
2003, Chapter 6.
---------------------------------------------------------------------------

    In the current definition, areas are classified as underserved 
if either the minority population share is greater than 30 percent 
and median income is less than 120 percent of the greater of State 
nonmetropolitan or national nonmetropolitan median income; or area 
median income is less than or equal to 95 percent of the greater of 
State nonmetropolitan or national nonmetropolitan median income. The 
greater of State nonmetropolitan or national median income is termed 
the ``reference income.'' Denoting the current thresholds as ``30/
120/95,'' the following set of alternative thresholds are evaluated:
     30/120/95 vs. 30/120/90 vs. 30/120/80--to examine the 
effect of lowering the general income threshold from 95 percent to 
90 percent to 80 percent.
     30/120/95 vs. 30/110/95 vs. 30/110/80--to examine the 
effect of lowering both the minority (from 120% to 110%) and general 
income (from 95% to 80%) thresholds; and
     30/120/95 vs. 50/120/95--to examine the effect of 
increasing the minority population threshold that must be attained 
before applying the minority income threshold.
    For each alternative, indicators of socioeconomic and housing 
conditions are calculated for served and underserved areas for each 
alternative and compare the results to the current definition. Of 
particular interest is whether certain thresholds of minority 
population and median income capture the differences in housing 
needs and conditions between served and underserved areas better 
than others. The ``coverage efficiency'' of each alternative 
relative to households below the poverty line, below 50, 70, and 95 
percent of area reference income, and below the alternative income 
level(s) used to define underservice, is also presented. GSE 
purchasing activity is also examined for each alternative 
definition, specifically, the percentage of eligible loans that 
qualify towards the goal for underserved areas defined by different 
thresholds. Each analysis is conducted both with counties and tracts 
as the geographic unit.
    County Results. The main effect of lowering the general income 
threshold from 95 to 90 to 80 percent of the reference income is to 
roughly halve the number of counties and population residing in 
underserved areas. Under the current definition, 11.6 million people 
reside in underserved areas as opposed to fewer than 10 million in 
served areas. With a general income threshold of 80 percent, 5.7 
million would be left in underserved areas. A 90 percent threshold 
would produce a shift of approximately half this amount.
    In terms of social, economic, demographic, and housing 
characteristics, lowering the income threshold from 95 to 80 percent 
would have the following notable consequences:
     Minority population in underserved areas would increase 
from 12.4 to 20.8 percent with no significant change in served 
areas.
     Median income would fall in both served and underserved 
areas with the difference remaining nearly constant at $10,000.
     Poverty, unemployment, school drop out rates all would 
be higher in both served and underserved areas. The gap would 
increase for each of these characteristics.
     Migration into underserved areas (from other States) 
would be relatively lower than into served areas with an 80 percent 
income threshold.
     Indicators of homeownership would decline somewhat in 
underserved areas relative to served areas. For all units, for 
example, ownership would decline from 74.3 to 72.9 percent in 
underserved areas and increase from 73.5 to 74.3 percent in served 
areas.
     Median housing values would fall in both served and 
underserved areas with a significant narrowing in the gap from 
approximately $25,000 to $19,000 at an 80 percent median income 
threshold.
     Housing affordability would decline in underserved 
areas, becoming nearly equal with affordability in served areas at 
80 percent.
     Crowding would be higher in underserved areas, 
absolutely and relative to served areas. Thus, more narrowly defined 
underserved areas would more strongly manifest conditions and needs 
associated with underservice: lower income, higher poverty, higher 
minority populations, lower homeownership, lower affordability, more 
crowding, etc. However, served areas would expand to encompass 
significant numbers of these same underserved and target 
populations.
    Use of the coverage efficiency index highlights one of the 
tradeoffs between using a low median income threshold versus a high 
median income threshold in redefining underservice. Coverage 
efficiency based on all variables examined, including 
``underserved,'' poor, very low income, low income and even moderate 
income families, declines sharply as the income threshold is lowered 
from 95 to 80 percent, becoming negative for most groups. Coverage 
for the ``underserved'' cohort declines from 22.0 to -1.0 percent, 
and for families with up to 95 percent of reference income, it 
declines from 17.2 to -10.0 percent. These changes result from 
losing almost half of the families in target income ranges without 
any appreciable gain in specificity, i.e., shrinking the proportion 
of people living in underserved counties with incomes above the 
respective target levels. Similar patterns are observed for families 
with below 70 percent of reference income, below 50 percent of 
reference income, and families in poverty.
    The second set of comparisons builds on the first set by 
lowering the income threshold applicable to areas with relatively 
high minority populations (30 percent) from 120 to 110 percent in 
addition to the general threshold. This change further shrinks, 
albeit, only marginally, the size and population of underserved 
areas. Minority underserved populations would be smaller and 
socioeconomic and housing conditions would be worse. Not 
surprisingly, coverage efficiencies and GSE purchase performance 
levels also would decline across the board, although the marginal 
effects of reducing the minority income threshold are quite small. 
The 30/110/80 alternative is the narrowest definition examined and 
produces the biggest losses in efficiency and GSE performance.
    The third variation of the current definition is an increase in 
the minority population threshold from 30 to 50 percent. Thus, if an 
area does not qualify as underserved against the general income 
threshold of 95 percent it could still qualify if its population is 
50 percent minority and median income is less than or equal to 120 
percent of the reference income level.
    Relatively few counties qualify solely under the current 
minority thresholds. Raising the population threshold would trim 
this number by an additional 73 counties (457 tracts). Not 
surprisingly, the percent minority in underserved areas would 
decrease. However, the areas being redesignated as served are 
apparently somewhat above average in terms of

[[Page 63791]]

socioeconomic and housing conditions in underserved areas and below-
average in terms of conditions in served areas. Coverage 
efficiencies for all cohorts would be lower than for the current 
definition of underservice and GSE performance overall would be 
approximately 90 percent of the current level.
    Using the State median income, alone, as the general reference 
income would reduce the number underserved counties relative to the 
current definition, and, although there would still be more 
underserved counties (1,274 vs. 1,064), the underserved population 
actually would become smaller than the served population. The effect 
of this alternative on differences in housing conditions and needs 
between served and underserved areas is generally small and 
ambiguous, but overall, results in less contrast. Consistent with 
the results for other alternatives, applying a State median income 
standard, alone, would result in lower coverage efficiency across 
all target groups.
    Census Tract Results. As discussed above, the adoption of a 
tract-based system would result in greater coverage efficiency of 
underserved populations and sharper distinctions in the 
socioeconomic, demographic and housing characteristics of served and 
underserved areas. That is, tracts more effectively carve out areas 
that exhibit characteristics that are associated with underservice, 
such as low income, large minority populations and low 
homeownership. The converse is true for served areas. In analysis at 
the tract level, these patterns tend to be maintained quite 
consistently. A tract-based system would improve the power to 
differentiate underserved and served populations. According to 
virtually every indicator of socioeconomic, demographic, and housing 
conditions, applying State median income, alone, with a tract-based 
geography would produce superior differentiation to the current 
county-based definition. In terms of coverage efficiency, we again 
see improvement with tracts, but not enough to offset the loss of 
eliminating the national median income threshold. For the 
underserved population, for example, coverage efficiency would be 
16.9 percent with tracts, still below 22 percent under the current 
definition.\54\
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    \54\ Note that, unlike the other panels in tables 6.3 and 6.8, 
``underserved population'' is defined according to the applicable 
definition. Thus, eliminating the national median income test, 
narrows the defined cohort of underserved families. Despite this, 
coverage falls.
---------------------------------------------------------------------------

I. Determination of the Underserved Areas Housing Goal

    The annual goal for each GSE's purchases of mortgages financing 
housing for properties located in geographically targeted areas 
(central cities, rural areas, and other underserved areas) is 37 
percent of eligible units financed in 2005, 38 percent in 2006 and 
2007, and 39 percent in 2008. The 2008 goal will remain in effect in 
subsequent years, unless changed by the Secretary prior to that 
time. The goal of 37 percent for 2005 is larger than the goal of 31 
percent for 2001-03 mainly because, compared with the 1990 Census, 
the 2000 Census includes a larger number of census tracts that meet 
HUD's definition of underserved area. The new 37 percent-39 percent 
goals are commensurate with recent market share estimates of 37-39 
percent for 1999-2002, presented in Appendix D.
    In addition, an Underserved Areas Housing Subgoal of 32 percent 
is established for the GSEs' acquisitions of single-family-owner 
home purchase loans in metropolitan areas in 2005, with the subgoal 
rising to 33 percent in 2006 and in 2007 and 34 percent in 2008. The 
subgoal is designed to encourage the GSEs to lead the primary market 
in providing mortgage credit in underserved areas.
    This section summarizes the Secretary's consideration of the six 
statutory factors that led to the Underserved Area Housing Goal and 
the subgoal for home purchase loans in metropolitan areas. This 
section discusses the Secretary's rationale for defining underserved 
areas and it compares the characteristics of such areas and 
untargeted areas. The section draws heavily from earlier sections 
which have reported findings from HUD's analyses of mortgage credit 
needs as well as findings from other research studies investigating 
access to mortgage credit.

1. Housing and Credit Disparities in Metropolitan Areas

    To identify areas underserved by the mortgage market, HUD 
focused on two traditional measures used in a number of studies 
based on HMDA data: Application denial rates and mortgage 
origination rates per 100 owner-occupied units. Tables B.2 and B.3 
in Section B of this Appendix presented detailed data on denial and 
origination rates by the racial composition and median income of 
census tracts for metropolitan areas. Aggregating this data is 
useful in order to examine denial and origination rates for broader 
groupings of census tracts: \55\
---------------------------------------------------------------------------

    \55\ Denial rates are computed for mortgage applications without 
manufactured housing loans. Origination rates equal home purchase 
and refinance mortgages (without subprime loans) per 100 owner 
occupants in a census tract.

------------------------------------------------------------------------
                                                         Denial
           Minority composition  (percent)                rate     Orig.
                                                       (percent)   rate
------------------------------------------------------------------------
0-30.................................................        9.6    26.7
30-50................................................       12.4    26.9
50-100...............................................       17.2    20.8
------------------------------------------------------------------------


------------------------------------------------------------------------
                                                         Denial
                     Tract income                         rate     Orig.
                                                       (percent)   rate
------------------------------------------------------------------------
Less than 90% of AMI.................................       16.9    18.1
90-120%..............................................       11.3    25.4
Greater than 120%....................................        7.8    32.7
------------------------------------------------------------------------

Two points stand out. First, high-minority census tracts have higher 
denial rates and lower origination rates than low-minority tracts. 
Specifically, tracts that are over 50 percent minority have nearly 
twice the denial rate and two-thirds the origination rate of tracts 
that are under 30 percent minority.\56\ Second, census tracts with 
lower incomes have higher denial rates and lower origination rates 
than higher income tracts. Tracts with income less than 90 percent 
of area median income have over twice the denial rate and almost 
half of the origination rate of tracts with income over 120 percent 
of area median income.
---------------------------------------------------------------------------

    \56\ The differentials in denial rates are due, in part, to 
differing risk characteristics of the prospective borrowers in 
different areas. However, use of denial rates is supported by the 
findings in the Boston Fed study which found that denial rate 
differentials persist, even after controlling for risk of the 
borrower. See Section B for a review of that study.
---------------------------------------------------------------------------

    In both the 1995 and the 2000 GSE Rules, HUD's research 
determined that ``underserved areas'' could best be characterized in 
metropolitan areas as census tracts where: (1) Median income of 
families in the tract does not exceed 90 percent of area (MSA) 
median income or (2) minorities comprise 30 percent or more of the 
residents and median income of families in the tract does not exceed 
120 percent of area median income. The earlier analysis was based on 
1990 Census data. HUD has now conducted the same analysis using 2000 
Census data and has determined that the above definition continues 
to be a good proxy for underserved areas in metropolitan areas. The 
income and minority cutoffs produce sharp differentials in denial 
and origination rates between underserved areas and adequately 
served areas. For example, in 2003 the mortgage denial rate in 
underserved areas (15.9 percent) was over one and three-fourths 
times that in adequately served areas (8.9 percent).
    These minority population and income thresholds apply in the 
suburbs as well as in central cities. The average denial rate in 
underserved suburban areas (14.8 percent) is 1.7 times that in the 
remaining served areas of the suburbs (8.7 percent), and is almost 
as large as the average denial rate (16.8 percent) in underserved 
central city tracts. Low-income and high-minority suburban tracts 
appear to have credit problems similar to their central city 
counterparts. Thus HUD uses the same definition of underserved areas 
throughout metropolitan areas--there is no need to define such areas 
differently in central cities and in the suburbs.
    This definition of metropolitan underserved areas based on 2000 
Census geography includes 26,316 of the 51,040 census tracts in 
metropolitan areas, covering 49.2 percent of the metropolitan 
population in 2000. (By contrast, the 1990-based definition included 
21,587 of the 45,406 census tracts in metropolitan areas, covering 
44.3 percent of the metropolitan population in 1990.) The 2000-based 
definition includes 75.7 percent of the population living in poverty 
in metropolitan areas. The unemployment rate in underserved areas is 
more than twice that in served areas, and owner units comprise only 
51.6 percent of total dwelling units in underserved tracts, versus 
75.9 percent of total units in served tracts. As shown in Table 
B.14, this definition covers most of the population in several 
distressed central cities including Bridgeport (100 percent), Newark 
(99

[[Page 63792]]

percent), and Detroit (93 percent). The nation's five largest cities 
also contain large concentrations of their population in underserved 
areas: New York (68 percent), Los Angeles (72 percent), Chicago (75 
percent), Houston (73 percent), and Phoenix (50 percent).
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[[Page 63793]]



2. Identifying Underserved Portions of Nonmetropolitan Areas

    Based on an exploration of alternative numerical criteria for 
identifying underserved nonmetropolitan areas using 2000 census 
data, HUD has concluded that the current definition of underservice 
is broad but efficacious and that any narrower definition of 
underservice would not serve congressional intent under FHEFSSA. 
Narrowing the definition of underservice potentially could promote 
more intense purchasing in needier communities, but this seems 
unlikely. On the contrary, the greatest marginal impact of GSE 
purchasing could be in the very areas that would be excluded under 
the alternatives.
    Research comparing a tract-based system for defining underserved 
areas with the current county-based system, using 2000 census data, 
indicates that a tract-based system would result in more effective 
geographic targeting of GSE purchases. Although the total number of 
tracts designated as served and underserved areas would change very 
little, 23 percent of all tracts would be reclassified, reassigning 
approximately equal numbers of families from served to underserved 
and from underserved to served.
    The main effect of the reclassification is to align tracts into 
more homogeneous and distinct groups as measured by differences in 
key socioeconomic and demographic characteristics such as median 
family income, poverty, unemployment, school dropouts, and minority 
population. As a result of reclassification, underserved areas stand 
out more as areas of lower income and economic activity and somewhat 
larger minority populations.
    Tract-based targeting would potentially focus GSE purchases in 
areas with relatively greater housing needs and conditions as 
measured by owner-occupancy, vacancy rates, and crowding. For each 
of these indicators, measured need increases in underserved areas 
and the gap between served and underserved areas widens when tracts 
are used to classify areas. Most notably, homeownership would be 
significantly lower in underserved areas relative to served areas 
under a tract-based system. Currently, and contrary to expectations, 
homeownership actually is slightly greater in underserved areas. 
Driving this reversal is the fact that tracts in served counties 
that would be reclassified as underserved tracts have an ownership 
rate of just 65 percent, which is much lower even than in the 
underserved tracts in underserved counties, where ownership is 73 
percent. Meanwhile, the served tracts in served and underserved 
counties have the same ownership rate of 77 percent, which is 
significantly higher than in underserved areas.
    Two groups of measures of housing conditions--housing quality 
and affordability--exhibit less clear-cut results from applying 
tracts. However, we conclude that these results are consistent with 
the ambiguous patterns discussed in chapter 4 above and do not 
undermine the overall conclusion that basing geographic targeting on 
tracts would more sharply define areas with greater housing need and 
adverse housing conditions.
    Not surprisingly, the results from analyzing housing, 
socioeconomic, and demographic characteristics are further 
reinforced in finding that a tract-based system would better capture 
underserved populations and exclude served populations from 
geographic targeting. Defining underserved families as those in any 
area whose income was less than 95 percent of the reference income 
(or in areas with a minority population of 30 percent or more, 
families with incomes below 120 percent of the reference income) the 
use of more refined tract geography results in a 5 percentage point 
increase in the coverage efficiency index, from 22 to 27 percent. 
This reflects two improvements under a tract system: Underserved 
areas would capture more of the nonmetropolitan ``underserved'' 
families (62 vs. 65 percent) and fewer ``served'' families 
(decreasing from 40 to 37 percent of families in underserved areas).

3. Past Performance of the GSEs

    Goals Performance. In the October 2000 rule, the underserved 
areas goal was set at 31 percent for 2001-03. Effective on January 
1, 2001, several changes in counting requirements came into effect 
for the undeserved areas goal, as follows: (a) ``Bonus points'' 
(double credit) for purchases of mortgages on small (5-50 unit) 
multifamily properties and, above a threshold level, mortgages on 2-
4 unit owner-occupied properties; (b) a ``temporary adjustment 
factor'' (1.35 units credit) for Freddie Mac's purchases of 
mortgages on large (more than 50 unit) multifamily properties; and 
(c) eligibility for purchases of certain qualifying government-
backed loans to receive goal credit. Under these counting rules, as 
shown in Table B.7a and Figure B.2, Fannie Mae's performance was 
32.6 percent in 2001, 32.4 percent in 2002, and 32.1 percent in 
2003, while Freddie Mac's performance was 31.7 percent in 2001, 
slightly less than 31 percent in 2002, and 32.7 percent in 2003; 
thus Fannie Mae surpassed the goal of 31 percent in all thee years, 
while Freddie Mac fell slightly short of the goal in 2002.

[[Page 63794]]

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BILLING CODE 4210-27-C
    Counting requirements (a) and (b) expired at the end of 2003, 
while (c) will remain in effect. If this counting approach--without 
the bonus points and the ``temporary adjustment factor''--had been 
in effect in 2000-03, and the GSEs' had purchased the same mortgages 
that they actually did purchase in both years, then Fannie Mae's 
performance would have been 31.0 percent in 2000, 30.4 percent in 
2001, 30.1 percent in 2002, and 29.2 percent in 2003. Freddie Mac's 
performance would

[[Page 63795]]

have been 29.2 percent in 2000, 28.2 percent in 2001, 28.0 percent 
in 2002, and 27.7 percent in 2003. Therefore, Fannie Mae would have 
just matched the underserved areas goal of 30 percent in 2000 and 
fallen short in 2001-03, while Freddie Mac would have fallen short 
of the goal in all four years, 2000-2003.
    The above performance figures are for underserved areas (census 
tracts in metropolitan areas and counties in non-metropolitan areas) 
defined in terms of 1990 Census geography. Switching to 2000 Census 
data increases the coverage of underserved areas, which increases 
the share of the GSEs' purchases in underserved areas by 
approximately 5 percentage points. Based on 2000 Census geography, 
and excluding counting requirements (a) and (b) then Fannie Mae's 
performance would have been 38.1 percent in 2000, 36.6 percent in 
2001, 35.9 percent in 2002, and 34.1 percent in 2003, as shown in 
Table B.7b. Freddie Mac's performance would have been 35.1 percent 
in 2000, 33.5 percent in 2001, 33.3 percent in 2002, and 31.6 
percent in 2003.
    Single-Family-Owner Home Purchase Mortgages. Sections E.9 of 
Appendix A and D.2 of this appendix compared the GSEs' funding of 
home purchase loans in underserved areas with originations by 
lenders in primary market. To take advantage of HMDA and GSE data 
going back to 1993, the analysis was conducted using 1990 Census 
tract geography. While both GSEs have improved their performance 
since 1993, they have both lagged the conventional conforming market 
in providing affordable loans to underserved areas. The 1990-based 
analysis shows that the two GSEs have engaged in very different 
patterns of funding--Freddie Mac has been much less likely than 
Fannie Mae to fund home loans in underserved neighborhoods. HUD will 
begin defining underserved areas based on 2000 Census geography and 
new OMB definitions of metropolitan areas in 2005, the first year of 
the rule. As noted above, the 2000-based definition of underserved 
areas includes 5,372 more census tracts in metropolitan areas than 
the 1990-based definition, which means the GSE-market comparisons 
need to be updated to incorporate tract designations from the 2000 
Census. Therefore, for the years 1999, 2000, 2001, and 2002, HUD 
used various apportionment techniques to re-allocate 1990-based GSE 
and HMDA data into census tracts as defined by the 2000 Census. The 
GSE and HMDA data for 2003 were already based on 2000 geography, so 
no apportionment was needed for that year. Switching to the 2000-
based tracts increases the underserved area share of market 
originations by 5.7 percentage points. Between 1999 and 2002, 31.4 
percent of mortgage originations (without B&C loans) were originated 
in underserved tracts based on 2000 geography, compared with 26.2 
percent based on 1990 geography. As shown in Table B.8 of Section 
D.2, the underserved areas share of each GSE's purchases also rises 
by approximately five percentage points. Thus, conclusions about the 
GSEs' performance relative to the market are similar whether the 
analysis is conducted in terms of 2000 Census geography or 1990 
Census geography.
    The analysis for home purchase loans based on 2000 Census 
geography will be summarized here (see Section D.2 of this appendix 
for a similar analysis using 1990-based geography):

----------------------------------------------------------------------------------------------------------------
                                                               Freddie Mac       Fannie Mae       Market  (w/o
                           Year                                 (percent)         (percent)      B&C)  (percent)
----------------------------------------------------------------------------------------------------------------
1999......................................................              25.6              25.3              30.2
2000......................................................              27.3              29.0              31.7
2001......................................................              27.3              29.8              30.7
2002......................................................              31.7              32.3              31.8
2003......................................................              29.0              32.0              32.5
1996-2003 (estimate)......................................              27.2              29.3              30.9
1999-2003 (average).......................................              28.3              30.0              31.4
2001-2003 (average).......................................              29.4              31.4              31.7
----------------------------------------------------------------------------------------------------------------

Between 1999 and 2003, 28.3 percent of Freddie Mac's purchases and 
30.0 percent of Fannie Mae's purchases financed properties in 
underserved neighborhoods, compared with 31.4 percent home purchase 
loans originated in the conventional conforming market (excluding 
B&C loans). Thus, Freddie Mac performed at 90 percent of the market 
level, while Fannie Mae performed at 96 percent of the market 
level--both results similar to those reported above for underserved 
areas based on 1990 Census geography. The 2000 Census data show that 
Fannie Mae has been much closer to the market during the recent 
2001-2003 period. The share of Fannie Mae's purchases going to 
underserved areas was 31.4 percent during 2001-2003, which placed it 
closer to the market level of 31.7 percent. However, the 2000-based 
results show that, like Freddie Mac, Fannie Mae's longer-term 
performance (since 1996) as well as its recent average performance 
(1999 to 2003) have consistently been below market levels. But, it 
is encouraging that Fannie Mae significantly improved its 
performance relative to the market during the first two years of 
HUD's higher housing goal levels. (See Section D.2 for the method of 
estimating the 1996-2003 average results.)

4. Ability To Lead the Single-Family-Owner Market: A Subgoal for 
Underserved Areas

    The Secretary believes the GSEs can play a leadership role in 
underserved markets. Thus, as discussed in Section D.2, the 
Department is establishing a subgoal of 32 percent for each GSE's 
acquisitions of home purchase loans for single-family-owner 
properties located in the underserved census tracts of metropolitan 
areas in 2005, rising to 33 percent in 2006 and 2007 and to 34 
percent in 2008. If the GSEs meet the 2008 subgoal, they will be 
leading the primary market by over two percentage points. As 
discussed above, underserved areas accounted for an average of 
approximately 31.5 percent of home purchase loans originated in the 
conventional conforming market of metropolitan areas (computed over 
1999-2003 or over 2001-2003). To reach the subgoal for 2008, both 
GSEs will have to improve over their earlier peak performances--
Freddie Mac by 2.3 percentage points over its previous peak 
performance of 31.7 percent in 2002, and Fannie Mae by 1.7 
percentage points over its previous peak performance of 32.3 percent 
in 2003. To meet the 2008 subgoal, Freddie Mac will have to improve 
by 2.6 percentage points over its 2002-2003 average (unweighted) 
performance of 30.4 percent, while Fannie Mae will have to improve 
by 1.8 percentage points over its 2002-2003 average performance of 
32.2 percent.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for nonmetropolitan counties are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices A and C.
    The approach taken is for the GSEs to obtain their leadership 
position by staged increases in the underserved areas subgoal; this 
will enable the GSEs to take new initiatives in a correspondingly 
staged manner to achieve the new subgoal each year. Thus, the 
increases in the underserved areas subgoal are sequenced so that the 
GSEs can gain experience as they improve and move toward the new 
higher subgoal targets.
    Appendix A discusses in some detail the factors that the 
Department considered when setting the subgoal for low- and 
moderate-income loans. Several of the considerations were general in 
nature--for example, related to the GSEs' overall ability to lead 
the single-family-owner market--while others were specific to the 
low-mod subgoal. Because the reader can refer to Appendix A, this 
appendix provides a briefer discussion of the more general factors. 
The specific

[[Page 63796]]

considerations that led to the subgoal for underserved areas can be 
organized around the following four topics:
    (1) The GSEs have the ability to lead the market. As discussed 
in Appendix A, the GSEs have the ability to lead the primary market 
for single-family-owner loans, which is their core business. Both 
GSEs have been dominant players in the home purchase market for 
years, funding 57 percent of the single-family-owner mortgages 
financed between 1999 and 2002. Through their many new product 
offerings and their various partnership initiatives, the GSEs have 
shown that they have the capacity to operate in underserved 
neighborhoods. They also have the staff expertise and financial 
resources to make the extra effort to lead the primary market in 
funding single-family-owner mortgages in underserved areas.
    (2) The GSEs have lagged the market. Even though they have the 
ability to lead the market, they have not done so, as discussed 
above. Fannie Mae demonstrated the type of improvement needed to 
meet this new underserved area subgoal during 2001 and 2002. During 
2001, underserved area loans declined as a percentage of primary 
market originations (from 31.7 to 30.7 percent), but they increased 
as a percentage of Fannie Mae's purchases (from 29.0 to 29.8 
percent); and during 2002, they increased further as a percentage of 
Fannie Mae's purchases (from 29.8 to 32.3 percent), placing Fannie 
Mae at the market level.
    (3) There are disparities among neighborhoods in access to 
mortgage credit. There remain troublesome neighborhood disparities 
in our mortgage markets, even after the substantial growth in 
conventional lending to low-income and minority neighborhoods that 
accompanied the so-called ``revolution in affordable lending''. 
There is growing evidence that inner city neighborhoods are not 
being adequately served by mainstream lenders. Some have concluded 
that a dual mortgage market has developed in our nation's financing 
system, with conventional mainstream lenders serving white families 
living in the suburbs and FHA and subprime lenders serving minority 
families concentrated in inner city neighborhoods.\57\ In addition 
to the unavailability of mainstream lenders, families living in 
these often highly-segregated neighborhoods face many additional 
hurdles, such as lack of cash for a down payment, credit problems, 
and discrimination. Immigrants and minorities, who 
disproportionately live in underserved areas, are projected to 
account for almost two-thirds of the growth in the number of new 
households over the next ten years. To meet the diverse and unique 
needs of these families, the GSEs must continue adjusting their 
underwriting guidelines and offering new products so that they can 
better serve these areas and hopefully attract more mainstream 
lenders into our inner city neighborhoods.
---------------------------------------------------------------------------

    \57\ See Dan Immergluck, Star Differences: The Explosion of the 
Subprime Industry and Racial Hypersegmentation in Home Equity 
Lending, Woodstock Institute, October 2000; and Daniel Immergluck 
and Marti Wiles, Two Steps Back: The Dual Mortgage Market, Predatory 
Lending, and the Undoing of Community Development, Woodstock 
Institute, Chicago, IL, November 1999. For a national analyses, see 
the HUD report Unequal Burden: Income and Racial Disparities in 
Subprime Lending in America, April 2000; and Randall M. Scheessele, 
Black and White Disparities in Subprime Mortgage Refinance Lending, 
Housing Finance Working Paper No. HF-114, Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, April 2002.
---------------------------------------------------------------------------

    (4) There are ample opportunities for the GSEs to improve their 
performance. Mortgages are available for the GSEs to purchase in 
underserved areas. They can improve their performance and lead the 
primary market in purchasing loans in these low-income and high-
minority neighborhoods. The underserved areas share of the home 
purchase market has consistently been around 31 percent since 1995 
(and 32 percent in the last two years), which suggests a degree of 
underlying strength in the market. According to the market share 
data reported in Table A.30 of Appendix A, the GSEs have been 
purchasing 48 percent of new originations in underserved areas, 
which means there are plenty of purchase opportunities left for them 
in the non-GSE portion of that market. In addition, the GSEs' 
purchases under the subgoal are not limited to new mortgages that 
are originated in the current calendar year. The GSEs can purchase 
loans from the substantial, existing stock of affordable loans held 
in lenders' portfolios, after these loans have seasoned and the GSEs 
have had the opportunity to observe their track record. In fact, 
both GSEs have often purchased seasoned loans that were used to 
finance properties in underserved areas (see Table A.11 in Appendix 
A).
    To summarize, although single-family-owner mortgages comprise 
the ``bread-and-butter'' of their business, the GSEs have lagged 
behind the primary market in financing properties in underserved 
areas. For the reasons given above, the Secretary believes that the 
GSEs can do more to raise the share of their home loan purchases in 
underserved areas. This can be accomplished by building on efforts 
that the enterprises have already started, including their new 
affordable lending products, their many partnership efforts, their 
outreach to inner city neighborhoods, their incorporation of greater 
flexibility into their underwriting guidelines, and their purchases 
of CRA loans. A wide variety of quantitative and qualitative 
indicators indicate that the GSEs have the resources and financial 
strength to improve their affordable lending performance enough to 
lead the market in underserved areas.

5. Size of the Mortgage Market for Underserved Areas

    As detailed in Appendix D, the market for mortgages in 
underserved areas is projected to account for 35-39 percent of 
dwelling units financed by conventional conforming mortgages; in 
estimating the size of the market, HUD used alternative assumptions 
about future economic and market conditions that were less favorable 
than those that existed over the last five years. HUD is well aware 
of the volatility of mortgage markets and the possible impacts on 
the GSEs' ability to meet the housing goals. Should conditions 
change such that the goals are no longer reasonable or feasible, the 
Secretary has the authority to revise the goals.

6. The Underserved Areas Housing Goal for 2005-2008

    The Underserved Areas Housing Goal for 2005 is 37 percent of 
eligible purchases, rising to 38 percent in 2006 and 2007 and 39 
percent in 2008. Five percent of the six percentage point increase 
in 2005 simply reflects the expanded coverage of HUD's definition in 
the 2000 Census tract data. The bonus points for small multifamily 
properties and owner-occupied 2-4 units, as well as Freddie Mac's 
Temporary Adjustment Factor, will no longer be in effect for goal 
counting purposes. It is recognized that neither GSE would have met 
the 37 percent target for 2005 in the past three years, and only 
Fannie Mae would have met this goal in 2000. Specifically, Fannie 
Mae's performance is projected to have been 37.5 percent in 2000, 
35.7 percent in 2001, 35.0 percent in 2002, and 34.1 percent in 2003 
under a 2000-based underserved area goal. On this basis, Freddie 
Mac's performance is projected to have been 34.1 percent in 2000, 
32.5 percent in 2001, 32.4 percent in 2002, and 31.7 percent in 
2003. However, GSE goal performance in 2001-03 was reduced by the 
heavy refinance wave of this period.
    The objective of HUD's Underserved Areas Housing Goal is to 
bring the GSEs' performance to the upper end of HUD's market range 
estimate for this goal (35-39 percent), consistent with the 
statutory criterion that HUD should consider the GSEs' ability to 
lead the market for each Goal. To enable the GSEs to achieve this 
leadership, the Department is modestly increasing the Underserved 
Areas Housing Goal for 2005 which will increase further through 
2008, to achieve the ultimate objective for the GSEs to lead the 
market under a range of foreseeable economic circumstances by 2008. 
Such a program of staged increases is consistent with the statutory 
requirement that HUD consider the past performance of the GSEs in 
setting the Goals. Staged increases in the Underserved Areas Housing 
Goal will provide the enterprises with opportunity to adjust their 
business models and prudently try out business strategies, so as to 
meet the required 2008 level without compromising other business 
objectives and requirements.
    The analysis of this section implies that there are many 
opportunities for Fannie Mae and Freddie Mac to improve their 
overall performance on the Underserved Areas Housing Goal. The GSEs 
provided financing for 55 percent of the single-family and 
multifamily units that were financed in the conventional conforming 
market between 1999 and 2002. However, in the underserved areas 
portion of the market, the GSE purchases represented only 48 percent 
of the dwelling units that were financed in the market. Thus, there 
appears to be ample room for the GSEs to increase their purchases of 
loans that qualify for the Underserved Areas Housing Goal. In 
addition, there are several market segments that would benefit from 
a greater secondary market role by the GSEs, and many of these 
market segments are concentrated in underserved areas.

[[Page 63797]]

7. Conclusions

    Having considered the projected mortgage market serving low- and 
moderate-income families, economic, housing and demographic 
conditions for 2005-08, and the GSEs' recent performance in 
purchasing mortgages in underserved areas the Secretary has 
determined that the annual goal of 37 percent of eligible units 
financed in 2005, 38 percent in 2006 and 2007, and 39 percent in 
2008 is feasible. The Secretary has also established a subgoal of 32 
percent for the GSEs' purchases of single-family-owner mortgages in 
metropolitan areas for 2005, rising to 33 percent in 2006 and 2007 
and 34 percent in 2008. The Secretary has considered the GSEs' 
ability to lead the industry as well as the GSEs' financial 
condition. The Secretary has determined that the goals and subgoals 
are necessary and appropriate.

Appendix C--Departmental Considerations To Establish the Special 
Affordable Housing Goal

A. Introduction

1. Establishment of the Goal

    The Federal Housing Enterprises Financial Safety and Soundness 
Act of 1992 (FHEFSSA) requires the Secretary to establish a special 
annual goal designed to adjust the purchase by each GSE of mortgages 
on rental and owner-occupied housing to meet the unaddressed needs 
of, and affordable to, low-income families in low-income areas and 
very-low-income families (the Special Affordable Housing Goal).
    In establishing the Special Affordable Housing Goal, FHEFSSA 
requires the Secretary to consider:
    1. Data submitted to the Secretary in connection with the 
Special Affordable Housing Goal for previous years;
    2. The performance and efforts of the GSEs toward achieving the 
Special Affordable Housing Goal in previous years;
    3. National housing needs of targeted families;
    4. The ability of the GSEs to lead the industry in making 
mortgage credit available for low-income and very-low-income 
families; and
    5. The need to maintain the sound financial condition of the 
enterprises.

2. The Goal and Subgoals

    Special Affordable Housing Goal. The rule provides that the 
Special Affordable Housing Goal will be 22 percent in 2005, 23 
percent in 2006, 25 percent in 2007, and 27 percent in 2008.
    Units That Count Toward the Goal. Units that count toward the 
Special Affordable Housing Goal include units occupied by low-income 
owners and renters in low-income areas, and very low-income owners 
and renters. Other low-income rental units in multifamily properties 
count toward the goal where at least 20 percent of the units in the 
property are affordable to families whose incomes are 50 percent of 
area median income or less, or where at least 40 percent of the 
units are affordable to families whose incomes are 60 percent of 
area median income or less.
    Multifamily Subgoal. HUD has established a special affordable 
subgoal for GSE purchases of multifamily mortgages. This subgoal is 
expressed in terms of a minimum annual dollar volume of multifamily 
mortgage purchases for units qualifying for the goal, rather than as 
a percentage of total units financed, as for the three housing 
goals. Both GSEs have consistently surpassed the multifamily subgoal 
since its establishment in 1996. The rule increases the subgoal such 
that, of the total Special Affordable mortgage purchases each year, 
each GSE must purchase special affordable multifamily mortgages in 
dollar amount equal to at least 1 percent of its combined (i.e., 
single-family and multifamily) annual average mortgage purchases 
over the 2000-2002 period. The level of this subgoal is $5.49 
billion per year for Fannie Mae and $3.92 billion per year for 
Freddie Mac.
    Single-Family-Owner Home Purchase Subgoal. The Department is 
establishing a subgoal of 17 percent for the share of each GSE's 
purchases of single-family-owner home purchase mortgages that 
qualify as special affordable and are originated in metropolitan 
areas in 2005 and 2006, with the subgoal rising to 18 percent in 
2007 and 2008.

B. Consideration of the Factors

    In considering the factors under FHEFSSA to establish the 
Special Affordable Housing Goal, HUD relied upon data gathered from 
the American Housing Survey through 2001, the Census Bureau's 1991 
and 2001 Residential Finance Surveys, the 1990 and 2000 Censuses of 
Population and Housing, Home Mortgage Disclosure Act (HMDA) data for 
1992 through 2003, and annual loan-level data from the GSEs on their 
mortgage purchases through 2003. Appendix D discusses in detail how 
these data resources were used and how the size of the conventional 
conforming market for this goal was estimated.
    The remainder of Section C discusses the factors listed above, 
and Section D provides the Secretary's rationale for establishing 
the Special Affordable Housing Goal.

Factors 1 and 2. Data submitted to the Secretary in connection with the 
Special Affordable Housing Goal for previous years, and the performance 
and efforts of the enterprises toward achieving the Special Affordable 
Housing Goal in previous years.

    The discussions of these two factors have been combined because 
they overlap to a significant degree.
    This section discusses each GSE's performance under the Special 
Affordable Housing Goal over the 1996-2003 period.\1\ As explained 
in Appendix A, the data presented are ``official HUD results'' 
which, in some cases, differ from goal performance reported by the 
GSEs in the Annual Housing Activities Reports (AHARs) that they 
submit to the Department.
---------------------------------------------------------------------------

    \1\ Performance for the 1993-95 period was discussed in HUD's 
Housing Goals 2000 Finale Rule.
---------------------------------------------------------------------------

    The main finding of this section is that both Fannie Mae and 
Freddie Mac surpassed the Department's Special Affordable Housing 
Goals for each of the seven years during this period. Specifically:
     The goal was set at 12 percent for 1996; Fannie Mae's 
performance was 15.4 percent and Freddie Mac's performance was 14.0 
percent.
     The goal was set at 14 percent for 1997-2000. Freddie 
Mac's performance was 15.2 percent in 1997, 15.9 percent in 1998, 
17.2 percent in 1999, and 20.7 percent in 2000; and Fannie Mae's 
performance was 17.0 percent in 1997, 14.3 percent in 1998, 17.6 
percent in 1999, and 19.2 percent in 2000.
     In HUD's Housing Goals 2000 Final Rule, the special 
affordable goal was set at 20 percent for 2001-03. As of January 1, 
2001, several changes in counting requirements took effect for the 
special affordable goal, as follows: ``bonus points'' (double 
credit) for purchases of goal-qualifying mortgages on small (5-50 
unit) multifamily properties and, above a threshold level, mortgages 
on 2-4 unit owner-occupied properties; a ``temporary adjustment 
factor'' (1.20 units credit, subsequently increased by Congress to 
1.35 units credit) for Freddie Mac's purchases of goal-qualifying 
mortgages on large (more than 50-unit) multifamily properties; 
changes in the treatment of missing data; a procedure for the use of 
imputed or proxy rents for determining goal credit for multifamily 
mortgages; and changes regarding the ``recycling'' of funds by loan 
originators. These changes are explained below. Fannie Mae's 
performance was 21.6 percent in 2001, 21.4 percent in 2002, and 21.2 
percent in 2003. Freddie Mac's performance was 22.6 percent in 2001, 
20.4 percent in 2002, and 21.4 percent in 2003. Both GSEs surpassed 
this higher goal in all years. This section discusses the October 
2000 counting rule changes in detail and provides data on what goal 
performance would have been in 2001-03 without these changes.\2\

    \2\ To separate out the effects of changes in counting rules 
that took effect in 2001, this section also compares performance in 
2001 to estimated performance in 2000 if the 2001 counting rules had 
been in effect in that year. Freddie Mac's goal performance in 2002 
has been revised due to coding errors that were discovered in HUD's 
review of 2002 data, as discussed in HUD's press release No. 04-105, 
October 15, 2004.
---------------------------------------------------------------------------

In addition, HUD has established a special affordable subgoal for 
GSE purchases of multifamily mortgages. This subgoal is expressed in 
terms of a minimum annual dollar volume of multifamily mortgage 
purchases for units qualifying for the goal, rather than as a 
percentage of total units financed, as for the three housing goals. 
As discussed below, both GSEs surpassed the multifamily subgoal in 
each of these years.

a. Performance on the Special Affordable Housing Goal in 1996-2003

    HUD's Housing Goals 1995 Final Rule specified that in 1996 at 
least 12 percent of the number of units financed by each of the GSEs 
that were eligible to count toward the Special Affordable Housing 
Goal should qualify for the goal (that is, be for very low-income 
families or low-income families in low-income areas), and at least 
14 percent should qualify in 1997-2000. HUD's October

[[Page 63798]]

2000 rule made various changes in the goal counting rules, as 
discussed below, and increased the Special Affordable Housing Goal 
to 20 percent for 2001-03.
    In the December 1995 rule, the minimum special affordable 
multifamily subgoals for 1996-2000 were set at 0.8 percent of the 
total dollar volume of each GSE's mortgage purchases in 1994, or 
$1.29 billion annually for Fannie Mae and $0.99 billion annually for 
Freddie Mac. These subgoals were increased for 2001-03 in the 
October 2000 rule, to $2.85 billion annually for Fannie Mae and 
$2.11 billion annually for Freddie Mac, or 1.0 percent of the 
average dollar volume of each GSE's mortgage purchases over the 
1997-99 period.
    Table C.1 and Figure C.1 show performance on the special 
affordable goal and the special affordable multifamily subgoal over 
the 1996-2003 period, based on HUD's analysis. The table shows that 
Fannie Mae surpassed the goals by 3.4 percentage points and 3.0 
percentage points in 1996 and 1997, respectively, while Freddie Mac 
surpassed the goals by narrower margins, 2.0 and 1.2 percentage 
points. In 1998 Fannie Mae's performance fell by 2.7 percentage 
points, while Freddie Mac's performance continued to rise, by 0.7 
percentage point, thus for the first time Freddie Mac outperformed 
Fannie Mae on this goal. Freddie Mac showed a gain in performance to 
17.2 percent in 1999, while Fannie Mae exhibited an even greater 
gain, to 17.6 percent
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[[Page 63801]]

    Both GSEs exhibited sharp gains in goal performance in 2000--
Fannie Mae's performance increased by 1.6 percentage points, to a 
record level of 19.2 percent, while Freddie Mac's performance 
increased even more, by 3.5 percentage points, which also led to a 
record level of 20.7 percent. Fannie Mae's performance was 21.6 
percent in 2001, 21.4 percent in 2002 and 21.3 percent in 2003; 
Freddie Mac's performance was 22.6 percent in 2001, 20.4 percent in 
2002, and 21.4 percent in 2003. However, as discussed below, using 
consistent accounting rules for 2000-03, each GSE's Special 
Affordable Housing Goal performance fell in every year from 2001 
through 2003--in total, by 2 percentage points for Fannie Mae and 
3.2 percentage points for Freddie Mac.
    With regard to the special affordable multifamily subgoal, 
Fannie Mae's purchases have exceeded the subgoal by wide margins in 
all years, with performance ranging from 184 percent of the goal in 
1996 to 315 percent of the goal in 1999. Fannie Mae's subgoal was 
more than doubled in the October 2000 rule, to a minimum of $2.85 
billion in each year from 2001 through 2003, but its qualifying 
purchases amounted to $7.36 billion, or 258 percent of the goal, in 
2001, and $7.57 billion, or 260 percent of the goal, in 2002; and 
$12.10 billion, or 425 percent of the subgoal, in 2003.
    Freddie Mac has also exceeded its special affordable multifamily 
subgoals in every year, albeit by smaller margins than Fannie Mae. 
In 1996 Freddie Mac's special affordable multifamily mortgage 
purchases amounted to $1.06 billion, or 107 percent of the goal. 
This ratio rose to 122 percent in 1997, and exceeded 200 percent for 
each year from 1998 through 2000. Freddie Mac's subgoal was more 
than doubled in the October 2000 rule, to a minimum of $2.11 in each 
year from 2001 through 2003, but its qualifying purchases amounted 
to $4.65 billion, or 220 percent of the goal, in 2001; $5.22 
billion, or 247 percent of the goal, in 2002; and $8.79 billion, or 
417 percent of the subgoal, in 2003.
    The official figures for Freddie Mac's special affordable goal 
performance presented above differ from the corresponding figures 
presented by Freddie Mac in its Annual Housing Activity Reports to 
HUD by 0.1-0.2 percentage point for 1996-2000, reflecting minor 
differences in the application of counting rules. The official 
figures for special affordable goal performance by both GSEs are the 
same as those submitted by the enterprises for both GSEs for 2001, 
and for Fannie Mae for 2002. However, for 1996-2000, HUD's official 
special affordable goal performance figures for Fannie Mae were 
approximately 1-3 percentage points lower than the corresponding 
figures reported by the enterprise. This was due to differences 
between HUD and Fannie Mae in the application of counting 
requirements applicable to purchases of portfolios of seasoned 
loans, based on a statutory requirement that the proceeds of such 
GSE purchases by the loan sellers should be ``recycled'' in order 
for the GSE to receive Special Affordable goal credit.\3\ This 
discrepancy did not persist in 2001-02 because of a change in 
counting requirements, described below. And for 2002, HUD's official 
goal performance figure was 20.4 percent, somewhat below the figure 
of 20.6 percent submitted to the Department by Freddie Mac. For 
2003, official performance on this goal for both GSEs was somewhat 
greater than that reported by the GSEs--official performance was 
21.2 percent for Fannie Mae (as compared with 20.9 percent reported 
by Fannie Mae to the Department) and 21.4 percent for Freddie Mac 
(as compared with 20.3 percent reported by Freddie Mac to the 
Department).
---------------------------------------------------------------------------

    \3\ During 1996-2000 Freddie Mac took steps to acquire 
representations and warranties from lenders to attest that they were 
``recycling'' the proceeds from the sales of qualifying loans. 
Fannie Mae did not take such steps; rather, Fannie Mae excluded such 
loans from the denominator in making its own calculations of its 
special affordable goal performance. In 1996-2000 HUD counted all 
eligible loans in the denominator, and, in the absence of measures 
to verify ``recycling'' by Fannie Mae, did not award credit in the 
numerator of the special affordable goal for most of Fannie Mae's 
seasoned mortgage purchases.
---------------------------------------------------------------------------

    Fannie Mae's performance on the Special Affordable Housing Goal 
surpassed Freddie Mac's in 1996-97. This pattern was reversed in 
1998, as Freddie Mac surpassed Fannie Mae in goal performance for 
the first time, though by only 0.2 percentage point. This improved 
relative performance of Freddie Mac was due to its increased 
purchases of multifamily loans, as it re-entered that market, and to 
increases in the goal-qualifying shares of its single-family 
mortgage purchases. However, Fannie Mae again surpassed Freddie Mac 
in special affordable goal performance in 1999, 17.6 percent to 17.2 
percent; Freddie Mac regained the lead in 2000, 20.7 percent to 19.2 
percent. Freddie Mac's official performance also exceeded Fannie 
Mae's official performance in 2001, but this reflected a difference 
in the counting rules applicable to the two GSEs that was enacted by 
Congress; if the same counting rules were applied to both GSEs, 
Fannie Mae's performance would have exceeded Freddie Mac's 
performance, by 21.6 percent to 21.1 percent.
    In 2002, Freddie Mac's performance on the special affordable 
goal was below Fannie Mae's performance (21.4 percent), even though 
Freddie Mac had the advantage of the Temporary Adjustment Factor 
(TAF), which did not apply to performance by Fannie Mae. Freddie 
Mac's performance would have trailed Fannie Mae's without this 
factor, and in fact Freddie Mac would have fallen short of the goal, 
at 19.3 percent. In 2003, Freddie Mac's performance (21.4 percent) 
slightly exceeded Fannie Mae's performance (21.2 percent), but this 
resulted from application of the TAF to Freddie Mac's performance--
without this, Freddie Mac's performance would have been 20.2 
percent, barely in excess of the 20 percent goal.

b. Changes in the Goal Counting Rules for 2001-03

    Several changes in the counting rules underlying the calculation 
of special affordable goal performance took effect beginning in 
2001. Most of these also applied to the low- and moderate-income 
goal and are discussed in Appendix A; only brief summaries of those 
changes are given here:
     Bonus points for multifamily and single-family rental 
properties. Each qualifying unit in a small multifamily property 
counted as two units in the numerator in calculating special 
affordable goal performance on all of the goals for 2001-03. And, 
above a threshold equal to 60 percent of the average number of 
qualifying rental units financed in owner-occupied properties over 
the preceding five years, each qualifying unit in a 2-4 unit owner-
occupied property also counted as two units in the numerator in 
calculating goal performance.
     Freddie Mac's Temporary Adjustment Factor. Freddie Mac 
received a ``Temporary Adjustment Factor'' of 1.35 units of credit 
for each qualifying unit financed in ``large'' multifamily 
properties (i.e., those with 51 or more units) in the numerator in 
calculating special affordable goal performance for 2001-03.\4\ This 
factor did not apply to special affordable units in large 
multifamily properties whose mortgages were financed by Fannie Mae 
during this period.
---------------------------------------------------------------------------

    \4\ See Congressional Record, December 15, 2000, pp. H12295-96.
---------------------------------------------------------------------------

     Missing data for single-family properties. The GSEs may 
exclude loans with missing borrower income from the denominator if 
the property is located in a below-median income census tract, 
subject to a ceiling of 1 percent of total owner-occupied units 
financed. The enterprises are also allowed to exclude single-family 
rental units with missing rental information from the denominator in 
calculating performance for the special affordable goal.
     Missing data and proxy rents for multifamily 
properties. If rent is missing for multifamily units, the GSEs may 
apply ``proxy rents,'' up to a ceiling of 5 percent of total 
multifamily units financed, in determining whether such units 
qualify for the special affordable goal. If such proxy rents cannot 
be estimated, these multifamily units are excluded from the 
denominator in calculating performance under these goals.
     Change in ``recycling'' requirements. Under Section 
1333(b)(1)(B) of FHEFSSA, if a GSE acquires a portfolio of mortgages 
originated in a previous year (that is, seasoned mortgages) that 
qualify under the Special Affordable Housing goal, the seller must 
be ``engaged in a specific program to use the proceeds of such sales 
to originate additional loans that meet such goal'' and such 
purchases or refinancings must ``support additional lending for 
housing that otherwise qualifies under such goal'' in order to 
receive credit toward the goal. This has been referred to as the 
``recycling requirement.'' The 2000 rule both clarified the 
conditions under which HUD would regard these statutory conditions 
to be satisfied and established certain categories of lenders that 
would be presumed to meet the recycling requirements. These included 
BIF-insured and SAIF-insured depository institutions that are 
regularly in the business of mortgage lending and which are subject 
to,

[[Page 63802]]

and have received at least a satisfactory Community Reinvestment Act 
performance evaluation rating under specified conditions.\5\
---------------------------------------------------------------------------

    \5\ The revised requirements are codified at 24 CFR 81.14(e)(4). 
The changes are discussed in detail in the rule preamble, 68 FR 
65074-76 (October 31, 2000).
---------------------------------------------------------------------------

c. Effects of Changes in the Counting Rules on Goal Performance

    Because of the changes in special affordable goal counting rules 
that took effect in 2001, direct comparisons between official goal 
performance in 2000 and 2001-03 are somewhat of an ``apples-to-
oranges comparison.'' For this reason, the Department has calculated 
what performance would have been in 2000 under the 2001-03 rules; 
this may be compared with official performance in 2001-03--an 
``apples-to-apples comparison.'' HUD has also calculated what 
performance would have been in 2001-03 under the 1996-2000 rules; 
this may be compared with official performance in 2000--an 
``oranges-to-oranges comparison.'' These comparisons are presented 
in Table C.2.
    Specifically, Table C.2 shows performance under the special 
affordable goal in three ways. Baseline A presents performance under 
the counting rules in effect for 1996-2000. Baseline B incorporates 
the technical changes in counting rules--changes in the treatment of 
missing data (including use of proxy rents), and changes in 
procedures related to the ``recycling'' requirement. Baseline C 
incorporates in addition to the technical changes the bonus points 
and, for Freddie Mac, the temporary adjustment factor. Baseline B 
corresponds to the counting approach used in this rule to take 
effect in 2005. Boldface figures under Baseline A for 1999-2000 and 
under Baseline C for 2001-03 indicate official goal performance 
based on the counting rules in effect in those years--e.g., for 
Freddie Mac, 17.2 percent in 1999, 20.7 percent in 2000, 22.6 
percent in 2001, 20.4 percent in 2002 and 21.4 percent in 2003.
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[[Page 63804]]

     Performance on the Special Affordable Housing Goal 
under 1996-2000 Counting Rules Plus Technical Changes. If the 
``Baseline B'' counting approach had been in effect in 2000-03 and 
the GSEs'' had purchased the same mortgages that they actually did 
purchase in those years, Fannie Mae would have surpassed the special 
affordable goal in both 2000 and 2001, but not in 2002 or 2003, 
while Freddie Mac would have surpassed the goal in 2000 but fallen 
short in 2001-2003. Specifically, Fannie Mae's performance would 
have been 21.4 percent in 2000, 20.2 percent in 2001, 19.9 percent 
in 2002, and 19.3 percent in 2003. Freddie Mac's performance would 
have been 21.0 percent in 2000, 19.3 percent in 2001, 18.1 percent 
in 2002, and 17.8 percent in 2003.
     Performance on the Special Affordable Housing Goal 
under 2001-2003 Counting Rules. If the 2001-03 counting rules had 
been in effect in 2000-03 and the GSEs' had purchased the same 
mortgages that they actually did purchase in that year (i.e., 
abstracting from any behavioral effects of ``bonus points,'' for 
example), both GSEs would have substantially surpassed the special 
affordable goal in all four years, but both GSEs' performance 
figures would have deteriorated somewhat between 2000 and 2003. 
Specifically, Fannie Mae's ``Baseline C'' performance would have 
been 22.2 percent in 2000, 21.6 percent in 2001, 21.4 percent in 
2002, and 21.2 percent in 2003. Freddie Mac's performance would have 
been 23.4 percent in 2000, 22.6 percent in 2001, 20.4 percent in 
2002 and 21.4 percent in 2003. Measured on this consistent basis, 
then, Fannie Mae's performance fell by 0.9 percentage point between 
2000 and 2003. Freddie Mac's ``Baseline C'' performance fell by 2.0 
percentage points between 2000 and 2003. These reductions were 
primarily due to 2001-03 being years of heavy refinance activity.
    Details of Effects of Changes in Counting Rules on Goal 
Performance in 2001-03. As discussed above, counting rule changes 
that took effect in 2001 had significant impacts on the performance 
of both GSEs on the special affordable goal in 2001--3.0 percentage 
points for Fannie Mae and 3.5 percentage points for Freddie Mac. 
This section breaks down the effects of these changes on goal 
performance for both GSEs; results are shown in Table C.2.
     Freddie Mac. The largest impact of the counting rule 
changes on Freddie Mac's goal performance was due to the application 
of the temporary adjustment factor for purchases of mortgages on 
large multifamily properties, as enacted by Congress; this added 1.4 
percentage points to goal performance in 2001, as shown in Table 
C.2. Bonus points for purchases of mortgages on small multifamily 
properties added 1.1 percentage points to performance, and bonus 
points for purchase of mortgages on owner-occupied 2-4 unit rental 
properties added 0.7 percentage point to performance. The remaining 
impact (0.2 percentage point) was due to technical changes in 
counting rules--primarily, the exclusion of single-family units with 
missing information from the denominator in calculating goal 
performance. Changes in the Department's counting rules related to 
``recycling'' did not play a role in Freddie Mac's performance on 
the special affordable goal. These same patterns also generally 
appeared in 2002. But in 2003 bonus points for financing special 
affordable unit in small multifamily properties had a greater impact 
on performance that the temporary adjustment factor.
     Fannie Mae. The temporary adjustment factor applied to 
Freddie Mac's goal performance, but not to Fannie Mae's performance, 
thus counting rule changes had less impact on its performance than 
on Freddie Mac's performance in 2001-03. The largest impacts of the 
counting rule changes on Fannie Mae's goal performance in 2001 were 
due to the application of bonus points for purchases of mortgages on 
owner-occupied 2-4 unit rental properties, which added 0.9 
percentage point to performance; bonus points for purchases of 
mortgages on small multifamily properties, which added 0.4 
percentage point to performance; and technical changes, which added 
1.6 percentage points to performance--the latter included the change 
in the Department's rules regarding ``recycling'' and the exclusion 
of single-family units with missing information from the denominator 
in calculating goal performance.\6\ The use of proxy rents for 
multifamily properties played a minor role in determining Fannie 
Mae's special affordable goal performance. These same patterns also 
generally appeared in 2002 and 2003.
---------------------------------------------------------------------------

    \6\ Exclusion of loans with missing information had a greater 
impact on Fannie Mae's goal performance than on Freddie Mac's goal 
performance.
---------------------------------------------------------------------------

d. Bonus Points for the Special Affordable Housing Goal

    As discussed above and in Appendix A, the Department established 
``bonus points'' to encourage the GSEs to step up their activity in 
2001-03 in two segments of the mortgage market--the small (5-50 
unit) multifamily mortgage market, and the market for mortgages on 
2-4 unit properties where 1 unit is owner-occupied and 1-3 units are 
occupied by renters. Bonus points did not apply to purchases of 
mortgages for owner-occupied 1-unit properties, for investor-owned 
1-4 unit properties, and for large (> 50-unit) properties, although 
as also discussed above, a ``temporary adjustment factor'' applied 
to Freddie Mac's purchases of goal-qualifying mortgages on large 
multifamily properties.
    Bonus points for small multifamily properties. Each unit 
financed in a small multifamily property that qualified for any of 
the housing goals was counted as two units in the numerator (and one 
unit in the denominator) in calculating goal performance for that 
goal. For example, if a GSE financed a mortgage on a 40-unit 
property in which 10 of the units qualified for the special 
affordable goal, 20 units would be entered in the numerator and 40 
units in the denominator for this property in calculating goal 
performance.
    Fannie Mae financed 37,449 units in small multifamily properties 
in 2001 that were eligible for the special affordable goal, 58,277 
such units in 2002, and 214,619 such units in 2003--this compares 
with only 7,196 such units financed in 2000. Small multifamily 
properties also accounted for a greater share of Fannie Mae's 
multifamily business in 2001-03--7.4 percent of total multifamily 
units financed in 2001, 13.2 percent in 2002, and 28.4 percent in 
2003, up from 2.5 percent in 2000. However, HUD's 2000 rule reported 
information from the 1991 Residential Finance Survey that small 
multifamily properties accounted for 37 percent of all multifamily 
units, thus Fannie Mae was still less active in this market than in 
the market for large multifamily properties. Within the small 
multifamily market, there was no evidence that Fannie Mae targeted 
affordable properties to a greater extent in 2001-03 than in 2000. 
That is, 61 percent of Fannie Mae's small multifamily units 
qualified for the special affordable goal in 2000; this fell to 46 
percent in 2001, 52 percent in 2002, and 42 percent in 2003.
    Freddie Mac financed 50,299 units in small multifamily 
properties in 2001 that were eligible for the special affordable 
goal, 22,255 such units in 2002, and 177,561 such units in 2003, as 
compared with only 2,996 such units financed in 2000. Small 
multifamily properties also accounted for a significantly greater 
share of Freddie Mac's multifamily business in 2001-03--16.0 percent 
of total multifamily units financed in 2001, 7.5 percent in 2002, 
and 30.0 percent in 2003, up from 1.8 percent in 2000.
    Within the small multifamily market, there was some evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001 than in 2000. That is, 55 percent of Freddie Mac's small 
multifamily units qualified for the special affordable goal in 2000; 
this rose to 73 percent in 2001, but declined to 60 percent in 2002 
and 54 percent in 2003.
    In summary, then, there is evidence that bonus points for small 
multifamily properties had an impact on Fannie Mae's role in this 
market in 2001-03 and an even larger impact on Freddie Mac's role in 
this market. In addition, Fannie Mae has announced a program to 
increase its role in this market further in future years.\7\
---------------------------------------------------------------------------

    \7\ ``Fannie Courting Multifamily Sellers; Small Banks 
Balking.'' American Banker, January 13, 2003, p.1.
---------------------------------------------------------------------------

    Bonus points for single-family rental properties. Above a 
threshold, each unit financed in a 2-4 unit property with at least 
one owner-occupied unit (referred to as ``OO24s'' below) that 
qualified for any of the housing goals was counted as two units in 
the numerator (and one unit in the denominator) in calculating goal 
performance for that goal in 2001-03. The threshold was equal to 60 
percent of the average number of such qualifying units over the 
previous five years. For example, Fannie Mae financed an average of 
24,780 special affordable units in these types of properties between 
1996 and 2000, and 55,118 such units in 2001. Thus Fannie Mae 
received 40,250 bonus points in this area in 2001--that is, 55,118 
minus 60 percent of 24,780. So 95,368 units were entered in the 
numerator for these properties in calculating special affordable 
goal performance.

[[Page 63805]]

    Fannie Mae financed 176,369 units in OO24s that were eligible 
for the special affordable goal in 2001, 229,827 such units in 2002, 
and 355,994 such units in 2003, as compared with 77,985 such units 
financed in 2000. However, Fannie Mae's total single-family business 
increased at approximately the same rate as its OO24 business over 
the 2001-03 period, thus the share of this business accounted for by 
OO24s was the same in 2001-03 as in 2000--4 percent.
    Within the OO24 market, there was no evidence that Fannie Mae 
targeted special affordable properties to a greater extent in 2001-
03 than in 2000. That is, approximately 30 percent of Fannie Mae's 
OO24 units qualified for the special affordable goal in each of 
these years.
    Freddie Mac financed 96,204 units in OO24s that were eligible 
for the special affordable goal in 2001, 146,242 such units in 2002, 
and 154,535 such units in 2003, as compared with 49,993 such units 
financed in 2000. However, Freddie Mac's total single-family 
business increased at approximately the same rate as its OO24 
business between 2000 and 2002, thus the share of this business 
accounted for by OO24s was the same in 2002 as in 2000--4 percent. 
And its overall single-family business increased more rapidly than 
its OO24 business in 2003, thus OO24 units accounted for 3 percent 
of all single-family units last year.
    As for Fannie Mae, within the OO24 market there was no evidence 
that Freddie Mac targeted special affordable properties to a greater 
extent in 2001-03 than in 2000. That is, approximately 32-36 percent 
of Freddie Mac's OO24 units qualified for the special affordable 
goal in each of these four years.

e. Effects of 2000 Census on Scoring of Loans Toward the Special 
Affordable Housing Goal

    Background. Scoring of housing units under the Special 
Affordable Housing Goal is based on data for mortgagors' incomes for 
owner-occupied units, rents for rental units, area median incomes, 
and, for units that are in the low-income but not the very low-
income range, decennial census data used to determine whether the 
median income for the area where the property is located is in the 
low-income range. Specifically, for single-family owner-occupied 
units scoring is based on.
     The mortgagors' income at the time of mortgage 
origination
     The median income of an area specified in the same way 
as for the Low- and Moderate-Income Housing Goal, that is: (i) For 
properties located in Metropolitan Statistical Areas (MSAs) the area 
is the MSA; and (ii) for properties located outside of MSAs, the 
area is the county or the non-metropolitan portion of the State in 
which the property is located, whichever has the larger median 
income, as of the year of mortgage origination (which may be for the 
current year or a prior year).
     Also, if the property is located in a Metropolitan 
Statistical Area (MSA), the determination for purposes of the 
Special Affordable Housing Goal involves data on median income of 
the MSA; or if the property is located elsewhere, the median income 
of the county or the non-metropolitan portion of the State in which 
the property is located, whichever is larger, as of the most recent 
decennial census.

Analogous specifications to those detailed in Appendix A for the 
Low- and Moderate-Income Housing Goal are applied in the case of the 
Special Affordable Housing Goal for rental units in single-family 
properties with rent data available (assuming no income data 
available for actual or prospective tenants), for rental units in 
multifamily properties where rent data are available, and for rental 
units in multifamily properties where rent data are not available.
    Thus, scoring loans under the Special Affordable Housing Goal 
requires a data series showing annual median incomes for MSAs, non-
metropolitan counties, and the non-metropolitan portions of states; 
decennial census data on median incomes for census tracts; and 
decennial census data on median incomes for MSAs, non-metropolitan 
counties, and the non-metropolitan portions of States.\8\
---------------------------------------------------------------------------

    \8\ In New England, MSAs were defined through mid-2003 in terms 
of Towns rather than Counties, and the portion of a New England 
county outside of any MSA was regarded as equivalent to a county in 
establishing the metropolitan or non-metropolitan location of a 
property. The MSA definitions established by the Office of 
Management and Budget (OMB) in June 2003 defined MSAs in New England 
in terms of counties.
---------------------------------------------------------------------------

    For scoring loans purchased by the GSEs year-by-year from 1993 
through 2003, area median income estimates produced by HUD's 
Economic and Market Analysis Division were used. The same median 
income data series described in Appendix A for the Low- and 
Moderate-Income Goal was used. The determination of low-income areas 
was based on 1990 census data.
    2005 Procedure. Relative to the above procedure, scoring of 
loans purchased by the GSEs in and after 2005 will be affected by 
two factors--first, re-benchmarking of area median incomes to the 
2000 census as described in Appendix A, with a shift from 1990 to 
2000 census data for identifying low-income areas, and second, the 
Office of Management and Budget's June, 2003, re-specification of 
MSA boundaries based on analysis of 2000 census data.\9\
---------------------------------------------------------------------------

    \9\ HUD has deferred application of the 2003 MSA specification 
to 2005, pending completion of the present rulemaking process.
---------------------------------------------------------------------------

    Analysis. For purposes of specifying the level of the Special 
Affordable Housing Goal, the HUD estimates of area median incomes 
for MSAs, non-metropolitan counties, and the non-metropolitan parts 
of States, as described in Appendix A, were used in conjunction with 
the data identifying low-income areas based on the 2000 census, to 
re-score loans purchased by the GSEs between 1999 and 2003. The same 
data series were used further in estimating the share of loans 
originated in metropolitan areas that would be eligible to score 
toward the Special Affordable Housing Goal, from HMDA data. The 
results of the retrospective GSE analysis are provided in Table C.3. 
The results of the GSE-HMDA comparative analysis are presented in 
the next section.
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    Table C.3 shows three sets of estimates for each GSE, based 
respectively on the counting rules in place in 2001-2003 (but 
disregarding the bonus points and Temporary Adjustment Factor), on 
the addition of 2000 census re-benchmarking and low-income areas, 
and finally on the further addition of 2003 MSA specification.

f. The GSEs' Multifamily Special Affordable Purchases

    Since 1996 each GSE has been subject to an annual dollar-based 
subgoal for Special Affordable multifamily mortgage purchases, as 
discussed above. This subgoal was established for 1996-2000 as 0.8 
percent of the total dollar volume of single-family and multifamily 
mortgages purchased by the respective GSE in 1994. Thus Fannie Mae's 
subgoal was $1.29 billion per year and Freddie Mac's subgoal was 
$988 million per year during that period. Fannie Mae surpassed the 
subgoal by $1.08 billion, $1.90 billion, $2.24 billion, $2.77 
billion, and $2.50 billion in 1996, 1997, 1998, 1999, and 2000 
respectively, while Freddie Mac exceeded the subgoal by $18 million, 
$220 million, $1.70 billion, $1.27 billion, and $1.41 billion.
    The subgoal was established for 2001-03 as 1.0 percent of the 
average annual volume of each GSE's total mortgage purchases over 
the 1997-99 period. Thus Fannie Mae's subgoal was established as 
$2.85 billion per year and Freddie Mac's as $2.11 billion per year. 
In 2001 Fannie Mae exceeded its subgoal by $4.51 billion and Freddie 
Mac exceeded its subgoal by $2.54 billion. In 2002, Fannie Mae 
exceeded its subgoal by $4.72 billion and Freddie Mac exceeded its 
subgoal by $3.11 billion. Both GSEs exceeded their subgoals in 2003 
by wide margins--Fannie Mae, with special affordable multifamily 
purchases of $12.11 billion (goal of $2.85 billion), and Freddie 
Mac, with purchases of $8.79 billion (goal of $2.11 billion.) Those 
subgoals are also in effect for 2004. Table C.1 includes figures on 
subgoal performance, and they are depicted graphically in Figure 
C.2.

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[[Page 63809]]



g. Characteristics of the GSEs' Special Affordable Purchases

    The following analysis presents information on the composition 
of the GSEs' Special Affordable purchases according to area income, 
unit affordability, tenure of unit and property type (single-or 
multifamily).
    Tables C.4 and C.5 show that each GSE's reliance on multifamily 
housing units to meet the special affordable goal has been variable 
from year to year since 1996. Fannie Mae's multifamily purchases 
were at 37.7 percent in 1996,28.8 percent in 2001, and 20.0 percent 
in 2002, with a high of 44.0 percent in 1997 and a low of 19.6 
percent in 2003. Freddie Mac's multifamily purchases represented 
29.4 percent of all purchases qualifying for the goal in 1996, 27.0 
percent in 2001, and 20.4 percent in 2002, with a high of 31.5 
percent in 1997 and a low of 20.4 percent in 2002. The two GSEs' 
purchase percentages for single-family owner properties exhibited a 
similar variability through this entire period, as did their 
purchases of mortgages financing single-family rental units from 
1996 through 2003. Both GSEs' high points for mortgages financing 
single-family rental units occurred in 2002: Fannie Mae's purchase 
percentage was 20.0 percent while Freddie Mac's was 18.1 percent.

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?>
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    Tables C.4 and C.5 also show the allocation of units qualifying 
for the goal as related to the family income and area median income 
criteria in the goal definition. Very-low-income families (shown in 
the two leftmost columns in the tables) accounted for 83.4 percent 
of Fannie Mae's units qualifying under the goal in 1997, rising to 
85.2 percent in 1999. For Freddie Mac, very-low-income families 
accounted for 81.9 percent of units qualifying under the goal in 
1997, rising to 84.9 percent in 1999. In contrast, mortgage 
purchases from low-income areas (shown in the first and third 
columns in the tables) accounted for 33.7 percent of Fannie Mae's 
units qualifying under the goal in 1997, compared to 35.5 percent in 
2001. The corresponding percentages for Freddie Mac were 38.3 
percent in 1997 and 35.5 percent in 2001. Thus given the definition 
of special affordable housing in terms of household and area income 
characteristics, both GSEs have consistently relied substantially 
more on low-income characteristics of households than low-income 
characteristics of census tracts to meet this goal.

h. The GSEs' Performance Relative to the Market

    Section E.9 in Appendix A uses HMDA data and GSE loan-level data 
for home purchase mortgages on single-family-owner properties in 
metropolitan areas to compare the GSEs' performance in special 
affordable lending to the performance of depositories and other 
lenders in the conventional conforming market. (See Tables A.13 to 
A.16 in Appendix A.). There were two main findings with respect to 
the special affordable category. First, Freddie Mac and Fannie Mae 
have historically lagged depositories and the overall market in 
providing mortgage funds for special affordable borrowers over 
periods, such as 1993-2003, 1996-2003 and 1999-2003. Between 1993 
and 2003, 12.2 percent of Freddie Mac's mortgage purchases were for 
special affordable borrowers, 13.3 percent of Fannie Mae's 
purchases, 15.4 percent of loans originated by depositories, and 
15.5 percent of loans originated in the conventional conforming 
market (without estimated B&C loans). For the recent years, the GSE-
market comparisons are as follows:

----------------------------------------------------------------------------------------------------------------
                                                                                                   Market  (w/o
                       Year  (in percent)                           Freddie Mac     Fannie Mae       B&C)  (in
                                                                   (in percent)    (in percent)      percent)
----------------------------------------------------------------------------------------------------------------
1999............................................................            12.8            12.5            17.0
2000............................................................            14.7            13.3            16.6
2001............................................................            14.4            14.9            15.6
2002............................................................            15.8            16.3            16.1
2003............................................................            15.6            17.1            15.9
1996-2003.......................................................            13.2            14.1            15.9
1999-2003.......................................................            14.7            15.1            16.2
2001-2003.......................................................            15.2            16.2            15.9
----------------------------------------------------------------------------------------------------------------

    During the period between 1999 and 2003, the GSEs' performance 
was slightly over 90 percent of the market--special affordable loans 
accounted for 15.1 percent of Fannie Mae's purchases, 14.7 percent 
of Freddie Mac's purchases, and 16.2 percent of loans originated in 
the conforming market.
    Second, while both GSEs have improved their performance over the 
past few years, Fannie Mae has been made more progress than Freddie 
Mac in erasing its gap with the market. During the first three years 
(2001, 2002, and 2003) of HUD's new housing goal targets, the 
average share of Fannie Mae's purchases going to special affordable 
loans was 16.2 percent, which was above the market average of 15.9 
percent. The share of Freddie Mac's purchases going to special 
affordable loans was 15.2 percent during this period.
    Section G in Appendix A discusses the role of the GSEs both in 
the overall special affordable market and in the different segments 
(single-family owner, single-family rental, and multifamily rental) 
of the special affordable market. The GSEs' special affordable 
purchases accounted for 41 percent of all special affordable owner 
and rental units that were financed in the conventional conforming 
market between 1999 and 2002. The GSEs' 41-percent share of the 
special affordable market was three-fourths of their 55-percent 
share of the overall market. Even in the owner market, where the 
GSEs account for 61 percent of the market, their share of the 
special affordable market was only 52 percent during this period. 
While the GSEs improved their market shares during 2001-2003, this 
analysis shows that there is room and ample opportunities for the 
GSEs, and particularly Freddie Mac, to improve their performance in 
purchasing affordable loans at the lower-income end of the market. 
Section C.3 of this appendix discusses a home purchase subgoal 
designed to place the GSEs in such a leadership position in the 
special affordable single-family-owner market.

Factor 3. National Housing Needs of Low-Income Families in Low-
Income Areas and Very-Low-Income Families

    This discussion concentrates on very-low-income families with 
the greatest needs. It complements Section C of Appendix A, which 
presents detailed analyses of housing problems and demographic 
trends for lower-income families which are relevant to the issue 
addressed in this part of Appendix C.
    Data from the American Housing Survey demonstrate that housing 
problems and needs for affordable housing continue to be more 
pressing in the lowest-income categories than among moderate-income 
families, as established in HUD's analysis for the 1995 and 2000 
Final Rules. Table C.6 displays figures on several types of housing 
problems--high housing costs relative to income, physical housing 
defects, and crowding-for both owners and renters. Figures are 
presented for households experiencing multiple (two or more) of 
these problems as well as households experiencing a severe degree of 
either cost burden or physical problems. Housing problems in 2001 
continued to be much more frequent for the lowest-income groups.\10\ 
Incidence of problems is shown for households in the income range 
covered by the special affordable goal, as well as for higher income 
households.
---------------------------------------------------------------------------

    \10\ Tabulations of the 2001 American Housing Survey by HUD's 
Office of Policy Development and Research. The results in the table 
categorize renters reporting housing assistance as having no housing 
problems.

---------------------------------------------------------------------------

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[[Page 63814]]


    This analysis shows that priority problems of severe cost burden 
or severely inadequate housing are noticeably concentrated among 
renters and owners with incomes below 60 percent of area median 
income: 30.5 percent of renter households and 34.9 percent of owner 
households had priority problems. In contrast, in the next higher 
income range, up to 80 percent of area median income, 2.5 percent of 
renter households and 7.3 percent of owner households had priority 
problems. The table demonstrates the significance of affordability 
problems: Sixty-five percent of very-low-income renter families had 
rent burden over 30 percent of income; 35 percent had rent burden 
over 50 percent of income. Thirteen percent had moderately or 
severely inadequate housing; 6 percent lived in crowded conditions, 
defined as more than one person per room.

Factor 4. The Ability of the Enterprises To Lead the Industry in 
Making Mortgage Credit Available for Low-Income and Very-Low-Income 
Families

    The discussion of the ability of Fannie Mae and Freddie Mac to 
lead the industry in Section G of Appendix A is relevant to this 
factor--the GSEs' roles in the owner and rental markets, their role 
in establishing widely-applied underwriting standards, their role in 
the development of new technology for mortgage origination, their 
strong staff resources, and their financial strength. Additional 
analyses of the potential ability of the enterprises to lead the 
industry in the low- and very-low-income market appears below in 
Section D, which explains the Department's rationale for the home 
purchase subgoal for Special Affordable loans.

Factor 5. The Need to Maintain the Sound Financial Condition of the 
GSEs

    HUD has undertaken a separate, detailed economic analysis of 
this final rule, which includes consideration of (a) the financial 
returns that the GSEs earn on special affordable loans and (b) the 
financial safety and soundness implications of the housing goals. 
Based on this economic analysis, HUD concludes that the housing 
goals in this final rule raise minimal, if any, safety and soundness 
concerns.

C. Determination of the Special Affordable Housing Goal

    Several considerations, many of which are reviewed in Appendixes 
A and B and in previous sections of this Appendix, led to the 
determination of the Special Affordable Housing Goal, the 
multifamily special affordable subgoal, and the special affordable 
subgoal for home purchase loans on single-family-owner properties in 
metropolitan areas.

1. Severe Housing Problems

    The data presented in Section C.3 demonstrate that housing 
problems and needs for affordable housing are much more pressing in 
the lowest-income categories than among moderate-income families. 
The high incidence of severe problems among the lowest-income 
renters reflects severe shortages of units affordable to those 
renters. At incomes below 60 percent of area median, 34.7 percent of 
renters and 21.6 percent of owners paid more than 50 percent of 
their income for housing. In this same income range, 65.6 percent of 
renters and 42.4 percent of owners paid more than 30 percent of 
their income for housing. In addition, 31.5 percent of renters and 
23.8 percent of owners exhibited ``priority problems'', meaning 
housing costs over 50 percent of income or severely inadequate 
housing. Homeownership gaps and other disparities in the housing and 
mortgage markets discussed in Section H of Appendix A also apply to 
Special Affordable housing and mortgages.

2. GSE Performance and the Market

a. The GSEs' Special Affordable Housing Goals Performance

    In the October 2000 rule, the special affordable goal was set at 
20 percent for 2001-03. Effective on January 1, 2001, several 
changes in counting requirements came into effect for the special 
affordable goal, as follows: (a)``bonus points'' (double credit) for 
purchases of mortgages on small (5-50 unit) multifamily properties 
and, above a threshold level, mortgages on 2-4 unit owner-occupied 
properties; (b) a ``temporary adjustment factor'' (1.35 unit credit) 
for Freddie Mac's purchases of mortgages on large (more than 50 
unit) multifamily properties; (c) changes in the treatment of 
missing data; (d) a procedure for the use of imputed or proxy rents 
for determining goal credit for multifamily mortgages; and (e) 
changes regarding the ``recycling'' of funds by loan originators.
    Counting requirements (a) and (b) expired at the end of 2003 
while (c)-(e) will remain in effect after that. If this counting 
approach--without the bonus points and the ``temporary adjustment 
factor''--had been in effect in 2000-2003, and the GSEs' had 
purchased the same mortgages that they actually did purchase in both 
years, then Fannie Mae's performance would have been 21.4 percent in 
2000, 20.2 percent in 2001, 19.9 percent in 2002, and 19.4 percent 
in 2003. Freddie Mac's performance would have been 21.0 percent in 
2000, 19.3 percent in 2001, 18.1 percent in 2002, and 17.8 percent 
in 2003. Fannie Mae would have surpassed the special affordable goal 
in both 2000 and 2001, but not in 2002 or 2003. Freddie Mac would 
have surpassed the goal in 2000 but fallen short in 2001-03.
    The above performance figures are for the special affordable 
goal defined in terms of 1990 Census geography. Switching to 2000 
Census data slightly increases the coverage of special affordable 
goal, which increases the special affordable share of the GSEs' 
purchases by up to one percentage point. Based on 2000 Census 
geography and adding 2003 MSAs, and excluding counting requirements 
(a) and (b), then Fannie Mae's performance would have been 21.7 
percent in 2000, 20.1 percent in 2001, 19.4 percent in 2002, and 
20.8 percent in 2003. Freddie Mac's performance would have been 20.8 
percent in 2000, 19.1 percent in 2001, 17.3 percent in 2002 and 19.0 
percent in 2003. See Table C.3.

b. Single-Family Market Comparisons in Metropolitan Areas

    The Special Affordable Housing Goal is designed, in part, to 
ensure that the GSEs maintain a consistent focus on serving the very 
low-income portion of the housing market where housing needs are 
greatest. Section C compared the GSEs' performance in special 
affordable lending to the performance of depositories and other 
lenders in the conventional conforming market for single-family home 
loans. The analysis showed that while both GSEs have been improved 
their performance, their past average performance (1993-2003, 1996-
2003, and 1999-2003) has been below market levels. During 2002 and 
2003, Fannie Mae improved its performance enough to lead the special 
affordable market for home purchase loans, but Freddie Mac, although 
it also improved its performance during this recent period, 
continues to lag behind the primary market. Between 1999 and 2003, 
special affordable borrowers accounted for 15.1 percent of the home 
loans purchased by Fannie Mae, 14.7 percent of Freddie Mac's 
purchases, 16.2 percent of home loans originated by depositories, 
and 16.2 percent of all home loans originated in the conventional 
conforming market (without B&C loans). As noted above, while both 
GSEs have improved their performance over the past few years, Fannie 
Mae has made more progress than Freddie Mac in closing its gap with 
the market. During 2003, the share of Fannie Mae's purchases going 
to special affordable loans was 17.1 percent, which was 1.2 
percentage points above the market average of 15.9 percent. The 
share of Freddie Mac's purchases going to special affordable loans 
had improved to 15.6 percent by 2003. (See Figure C.3.)

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[[Page 63816]]

3. Ability To Lead the Single-Family Owner Market: A Special Affordable 
Subgoal

    The Secretary believes the GSEs can play a leadership role in 
the special affordable market. Thus, the Department is establishing 
a subgoal of 17 percent for each GSE's purchases of home purchase 
loans for special affordable families in the single-family-owner 
market of metropolitan areas for 2005 and 2006, rising to 18 percent 
during 2007 and 2008. The purpose of this subgoal is to encourage 
the GSEs to improve their purchases of mortgages for very-low-income 
and minority first-time homebuyers who are expected to enter the 
housing market over the next few years. If the GSEs meet the 18-
percent subgoal, they will be leading the primary market by 
approximately two percentage points, based on the income 
characteristics of home purchase loans reported in HMDA. HMDA data 
show that special affordable families accounted for an average of 
16.2 (15.9) percent of single-family-owner loans originated in the 
conventional conforming market of metropolitan areas between 1999 
and 2003 (2001 and 2003). Loans in the B&C portion of the subprime 
market are not included in these averages. As explained in Appendix 
D, HUD also projected special affordable shares for the market for 
1999 to 2002 using the new 2000 Census geography and the new OMB 
specifications. For special affordable loans, the 2000-based Census 
data resulted in special affordable shares for the market and the 
GSEs that were similar to the 1990-based special affordable shares 
reported in Section C of this appendix.
    To reach the 18-percent subgoal for 2008, Freddie Mac would have 
to improve its performance by 2.4 percentage points over its special 
affordable share of 15.6 percent in 2003. Fannie Mae would have to 
improve its performance by 0.9 percentage point over its market-
leading special affordable share of 17.1 percent in 2003. The 
approach taken is for the GSEs to obtain their leadership position 
by staged increases in the special affordable subgoal; this will 
enable the GSEs to take new initiatives in a correspondingly staged 
manner to achieve the new subgoal each year. Thus, the increases in 
the special affordable subgoal are sequenced so that the GSEs can 
gain experience as they improve and move toward the new higher 
subgoal targets.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for non-metropolitan counties are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices A and B. Sections 
E.9 and G of Appendix A provide additional information on the 
opportunities for an enhanced GSE role in the special affordable 
segment of the home purchase market and on the ability of the GSEs 
to lead that market.
    The preamble and Appendix A discuss in some detail the factors 
that the Department considered when setting the subgoal for low- and 
moderate-income loans. Several of the considerations were general in 
nature--for example, related to the GSEs' overall ability to lead 
the single-family-owner market--while others were specific to the 
low-mod subgoal. Because the reader can refer to Appendix A, this 
appendix provides a briefer discussion of the more general factors. 
The specific considerations that led to the subgoal for special 
affordable loans can be organized around the following four topics:
    (1) The GSEs have the ability to lead the market. As discussed 
in Appendix A, the GSEs have the ability to lead the primary market 
for single-family-owner loans, which is their ``bread-and-butter'' 
business. Both GSEs have been dominant players in the home purchase 
market for years, funding 61 percent of the single-family-owner 
mortgages financed between 1999 and 2002. Through their many new 
product offerings and their various partnership initiatives, the 
GSEs have shown that they have the capacity to reach out to very-
low-income and other special affordable borrowers. They also have 
the staff expertise and financial resources to make the extra effort 
to lead the primary market in funding single-family-owner mortgages 
for special affordable borrowers.
    (b) GSEs' Performance Relative to the Market. Even though the 
GSEs have had the ability to lead the home purchase market, their 
past average performance (1993-2003, 1996-2003, and 1999-2003) has 
been below market levels. During 2003, Fannie Mae improved its 
performance enough to lead the special affordable market for home 
purchase loans, but Freddie Mac, although it also has improved its 
performance, continues to lag behind the primary market. The 
subgoals will ensure that Fannie Mae maintains and further improves 
its above-market performance and that Freddie Mac not only erases 
its current gap with the market but also takes a leadership position 
as well. With respect to the GSEs' historical performance, special 
affordable mortgages accounted for 13.2 (14.7) percent of Freddie 
Mac's purchases during 1996-2003 (1999-2003), for 14.1 (15.1) 
percent of Fannie Mae's purchases, and for 15.9 (16.2) percent of 
primary market originations (excluding B&C loans). The type of 
improvement needed for Freddie Mac to meet this new special 
affordable subgoal was demonstrated by Fannie Mae during 2001-2003, 
as Fannie Mae increased its special affordable performance from 14.9 
percent of its single-family-owner business in 2001 to 16.3 percent 
in 2002 to 17.1 percent in 2003.
    (3) Disparities in Homeownership and Credit Access Remain. There 
remain troublesome disparities in our housing and mortgage markets, 
even after the ``revolution in affordable lending'' and the growth 
in homeownership that has taken place since the mid-1990s. The 
homeownership rate for African-American and Hispanic households 
remains 25 percentage points below that of white households. 
Minority families face many barriers in the mortgage market, such as 
lack of capital for down payment and lack of access to mainstream 
lenders (see above). Immigrants and minorities--many of whose very-
low-income levels will qualify them as special affordable--are 
projected to account for almost two-thirds of the growth in the 
number of new households over the next ten years. As emphasized in 
Appendix A, changing population demographics will result in a need 
for the primary and secondary mortgage markets to meet 
nontraditional credit needs, respond to diverse housing preferences, 
and overcome information and other barriers that many immigrants and 
minorities face. The GSEs have to increase their efforts in helping 
special affordable families--but so far they have played a 
surprisingly small role in serving minority first-time homebuyers. 
It is estimated that the GSEs accounted for 46.5 percent of all 
(both government and conventional) home loans originated between 
1999 and 2001; however, they accounted for only 14.3 percent of home 
loans originated for African-American and Hispanic first-time 
homebuyers. A subgoal for special affordable home purchase loans 
should increase the GSEs' efforts in important sub-markets such as 
the one for minority first-time homebuyers.
    (4) There are ample opportunities for the GSEs to improve their 
performance. Special affordable mortgages are available for the GSEs 
to purchase, which means they can improve their performance and lead 
the primary market in purchasing loans for these very-low-income 
borrowers. Sections B, C, and I of Appendix A and Section H of 
Appendix D explain that the special affordable lending market has 
shown an underlying strength over the past few years that is 
unlikely to vanish (without a significant increase in interest rates 
or a decline in the economy). The special affordable share of the 
home purchase market has averaged approximately 16 percent since 
1996 and annually has been in the 15-17 percent range. Second, the 
market share data reported in Table A.30 of Appendix A demonstrate 
that there are newly originated loans available each year for the 
GSEs to purchase. The GSEs' purchases of single-family owner loans 
represented 61 percent of all single-family-owner loans originated 
between 1999 and 2002, compared with 52 percent of the special 
affordable loans that were originated during this period. Thus, half 
of the special affordable conforming market is not touched by the 
GSEs. As noted above, the situation is even more extreme for special 
sub-markets such the minority first-time homebuyer market where the 
GSEs have only a minimal presence. Between 1999 and 2001, the GSEs 
purchased only 33 percent of conventional conforming loans 
originated for minority first-time homebuyers, even though they 
purchased 57 percent of all home loans originated in the 
conventional conforming market during that period. But also 
important, the GSEs' purchases under the subgoal are not limited to 
new mortgages that are originated in the current calendar year. The 
GSEs can purchase loans from the substantial, existing stock of 
special affordable loans held in lenders' portfolios, after these 
loans have seasoned and the GSEs have had the opportunity to observe 
their payment performance. In fact, based on Fannie Mae's recent 
experience, the purchase of seasoned loans appears to be one useful 
strategy for purchasing goals-qualifying loans.
    For the reasons given above, the Secretary believes that the 
GSEs can do more to raise

[[Page 63817]]

the special affordable shares of the home loans they purchase on 
single-family-owner properties. This can be accomplished by building 
on efforts that the enterprises have already started, including 
their new affordable lending products aimed at special groups such 
as first-time homebuyers, their many partnership efforts, their 
outreach to inner city neighborhoods, their incorporation of greater 
flexibility into their underwriting guidelines, and their purchases 
of seasoned CRA loans. A wide variety of quantitative and 
qualitative indicators indicate that the GSEs' have the resources 
and financial strength to improve their special affordable 
performance enough to lead the market.

4. Size of the Overall Special Affordable Mortgage Market

    As detailed in Appendix D, single-family and multifamily special 
affordable mortgages are estimated to account for 23-27 percent of 
the dwelling units financed by conventional conforming mortgages; in 
estimating the size of the market, HUD used alternative assumptions 
about future economic and market affordability conditions that were 
less favorable than those that existed over the past several years. 
HUD is well aware of the volatility of mortgage markets and the 
possible impacts on the GSEs' ability to meet the housing goals. 
Should conditions change such that the goals are no longer 
reasonable or feasible, the Secretary has the authority to revise 
the goals.

5. The Special Affordable Housing Goal for 2005-2008

    The Special Affordable Housing Goal for 2005 is 22 percent of 
eligible purchases, a two percentage point increase over the current 
goal of 20 percent, with the goal rising to 23 percent in 2006, 25 
percent in 2007, and 27 percent in 2008. The bonus points for small 
multifamily properties and owner-occupied 2-4 unit properties, as 
well as Freddie Mac's Temporary Adjustment Factor, will no longer be 
in effect for goal counting purposes. It is recognized that neither 
GSE would have met the 22-percent target for 2005 in the past three 
years. Under the new counting rules, Fannie Mae's special affordable 
performance is estimated to have been 18.6 percent in 1999, 21.7 
percent in 2000, 20.1 percent in 2001, 19.4 percent in 2002, and 
20.8 percent in 2003. Fannie Mae would have to increase its 
performance in 2005 by 1.9 percentage points over its average 
(unweighted) performance of 20.1 percent over these last five years. 
By 2008 this increase relative to average 1999-2003 performance 
would be 6.9 percentage points. Freddie Mac's performance is 
projected to have been 17.4 percent in 1999, 20.8 percent in 2000, 
19.1 percent in 2001, 17.3 percent in 2002, and 19.0 percent in 
2003. Freddie Mac would have to increase its performance in 2005 by 
3.3 percentage points over its average (unweighted) performance of 
18.7 percent over these last five years. By 2008 this increase 
relative to average 1999-2002 performance would be 8.3 percentage 
points. However, GSE goal performance in 2001-03 was reduced by the 
heavy refinance wave of this period.
    The objective of HUD's Special Affordable Goal is to bring the 
GSEs' performance to the upper end of HUD's market range estimate 
for this goal (23-27 percent), consistent with the statutory 
criterion that HUD should consider the GSEs' ability to lead the 
market for each Goal. To enable the GSEs to achieve this leadership, 
the Department is establishing modest increases in the Special 
Affordable Goal for 2005, which will increase year-by-year through 
2008, to achieve the ultimate objective for the GSEs to lead the 
market under a range of foreseeable economic circumstances by 2008. 
Such a program of staged increases is consistent with the statutory 
requirement that HUD consider the past performance of the GSEs in 
setting the Goals. Staged annual increases in the Special Affordable 
Goal will provide the enterprises with opportunity to adjust their 
business models and prudently try out business strategies, so as to 
meet the required 2008 level without compromising other business 
objectives and requirements.
    Section C compared the GSEs' role in the overall market with 
their role in the special affordable market. The GSEs' purchases 
provided financing for 26,118,927 dwelling units, which represented 
55 percent of the 47,551,039 single-family and multifamily units 
that were financed in the conventional conforming market between 
1999 and 2002. However, in the special affordable part of the 
market, the 5,103,186 units that were financed by GSE purchases 
represented only 41 percent of the 12,413,759 dwelling units that 
were financed in the market. Thus, there appears to be ample room 
for the GSEs to improve their performance in the special affordable 
market. In addition, there are several market segments (e.g., first-
time homebuyers) that would benefit from a greater secondary market 
role by the GSEs, and special affordable borrowers are concentrated 
in these markets.

6. Multifamily Special Affordable Subgoals

    Based on the GSEs' past performance on the special affordable 
multifamily subgoals, and on the outlook for the multifamily 
mortgage market, HUD is establishing that these subgoals be retained 
and increased for the 2005-2008 period. Unlike the overall goals, 
which are expressed in terms of minimum goal-qualifying percentages 
of total units financed, these subgoals for 2001-03 and in prior 
years have been expressed in terms of minimum dollar volumes of 
goal-qualifying multifamily mortgage purchases. Specifically, each 
GSE's special affordable multifamily subgoal is currently equal to 
1.0 percent of its average total (single-family plus multifamily) 
mortgage volume over the 1997-99 period. Under this formulation, in 
October 2000 the subgoals were set at $2.85 billion per year for 
Fannie Mae and $2.11 billion per year for Freddie Mac, in each of 
calendar years 2001 through 2003. These represented increases from 
the goals for 1996-2000, which were $1.29 billion annually for 
Fannie Mae and $0.99 billion annually for Freddie Mac. These 
subgoals are also in effect for 2004.
    HUD's Determination. The multifamily mortgage market and both 
GSEs' multifamily transactions volume grew significantly over the 
1993-2003 period, indicating that both enterprises have provided 
increasing support for the multifamily market, and that they have 
the ability to continue to provide further support for the market.
    Specifically, Fannie Mae's total eligible multifamily mortgage 
purchase volume increased from $4.6 billion in 1993 to $12.5 billion 
in 1998, and then jumped sharply to $18.7 billion in 2001 and $18.3 
billion in 2002, and $33.3 billion in 2003. Its special affordable 
multifamily mortgage purchases followed a similar path, rising from 
$1.7 billion in 1993 to $3.5 billion in 1998 and $4.1 billion in 
1999, and also jumping sharply to $7.4 billion in 2001 and $7.6 
billion in 2002 and $12.2 billion in 2003. As a result of its strong 
performance, Fannie Mae's purchases have been at least twice its 
minimum subgoal in every year since 1997--247 percent of the subgoal 
in that year, 274 percent in 1998, 315 percent in 1999, 294 percent 
in 2000, and, under the new higher subgoal level, 258 percent in 
2001, 266 percent in 2002, and 426 percent in 2003.
    Freddie Mac's total eligible multifamily mortgage purchase 
volume increased even more sharply, from $0.2 billion in 1993 to 
$6.6 billion in 1998, and then jumped sharply in 2001 to $11.8 
billion and $13.3 billion in 2002, and $21.5 billion in 2003. Its 
special affordable multifamily mortgage purchases followed a similar 
path, rising from $0.1 billion in 1993 to $2.7 billion in 1998, and 
also jumping sharply to $4.6 billion in 2001 and $5.2 billion in 
2002, and $8.8 billion in 2003. As a result of its strong 
performance, Freddie Mac's purchases have also been at least twice 
its minimum subgoal in every year since 1998--272 percent of the 
subgoal in that year, 229 percent in 1999, 243 percent in 2000, and, 
under the new higher subgoal level, 220 percent in 2001, 247 percent 
in 2002, and 417 percent in 2003.
    The Special Affordable Housing Multifamily Subgoals set forth in 
this rule are reasonable and appropriate based on the Department's 
analysis of this market. The Department's decision to retain the 
multifamily subgoal is based on the fact that HUD's analysis 
indicates that multifamily housing still serves the housing needs of 
lower-income families and families in low-income areas to a greater 
extent than single-family housing. By retaining the multifamily 
subgoal, the Department ensures that the GSEs continue their 
activity in this market, and that they achieve at least a minimum 
level of special affordable multifamily mortgage purchases that are 
affordable to lower-income families. The Department establishes each 
GSE's special affordable multifamily subgoal as 1.0 percent of its 
average annual dollar volume of total (single-family and 
multifamily) mortgage purchases over the 2000-2002 period. In dollar 
terms, the Department's subgoal is $5.49 billion per year in special 
affordable multifamily mortgage purchases for Fannie Mae, and $3.92 
billion per year in special affordable multifamily mortgage 
purchases for Freddie Mac. These subgoals would be less than actual 
special affordable multifamily mortgage purchase volume in 2001-2003 
for both GSEs; thus the Department believes that they would be 
feasible for the 2005-2008 period.
    Some commenters advocated increasing the special affordable 
multifamily subgoals

[[Page 63818]]

from the levels in the rule. In light of the high levels of such 
purchases by both GSEs in 2003, HUD considered raising these 
subgoals, but decided not to do so because HUD believes that the 
overall special affordable goals established in this final rule will 
provide sufficient incentives for the GSEs to play a major role in 
the special affordable multifamily mortgage market, and that in all 
likelihood they will continue to exceed these subgoals by 
significant margins for 2005-08.

7. Conclusion

    HUD has determined that the Special Affordable Housing Goal in 
this rule addresses national housing needs within the income 
categories specified for this goal, while accounting for the GSEs' 
past performance in purchasing mortgages meeting the needs of very-
low-income families and low-income families in low-income areas. HUD 
has also considered the size of the conventional mortgage market 
serving very-low-income families and low-income families in low-
income areas. Moreover, HUD has considered the GSEs' ability to lead 
the industry as well as their financial condition. HUD has 
determined that a Special Affordable Housing Goal of 22 percent in 
2005, 23 percent in 2006, 25 percent in 2007, and 27 percent in 2008 
is both necessary and achievable. HUD has also determined that a 
multifamily special affordable subgoal for 2005-2008 set at 1.0 
percent of the average of each GSE's respective dollar volume of 
combined (single-family and multifamily) 1999-2002 mortgage 
purchases in is both necessary and achievable. Finally, HUD is 
establishing a subgoal of 17 percent for the GSEs' purchases of 
single-family-owner mortgages that qualify for the special 
affordable goal and are originated in metropolitan areas, for 2005, 
with this subgoal remaining at 17 percent in 2006, then rising to 18 
percent in both 2007 and 2008. The Secretary has considered the 
GSEs' ability to lead the industry as well as the GSEs' financial 
condition. The Secretary has determined that the goals, the 
multifamily subgoals, and the single-family-owner subgoals are 
necessary and appropriate.

Appendix D--Estimating the Size of the Conventional Conforming Market 
for Each Housing Goal

A. Introduction

    In establishing the three housing goals, the Secretary is 
required to assess, among a number of factors, the size of the 
conventional market for each goal. This appendix explains HUD's 
methodology for estimating the size of the conventional market for 
each of the three housing goals. Following this overview, Section B 
summarizes the main components of HUD's market-share model and 
identifies those parameters that have a large effect on the relative 
market shares. Sections C and D discuss two particularly important 
market parameters, the size of the multifamily market and the share 
of the single-family mortgage market accounted for by single-family 
rental properties. Section E provides a more systematic presentation 
of the model's equations and main assumptions. Sections F, G, and H 
report HUD's estimates for the Low- and Moderate-Income Goal, the 
Underserved Areas Goal, and the Special Affordable Housing Goal, 
respectively.
    HUD received numerous comments on the proposed rule relating to 
its market methodology and the size of its market ranges for each of 
the three goals. These comments, and HUD's responses to them, are 
discussed throughout this appendix.
    In developing this final rule, HUD has followed the same basic 
approach that it followed in the last two GSE final rules and the 
recent GSE proposed rule. HUD has carefully reviewed existing 
information on mortgage activity in order to understand the weakness 
of various data sources and has conducted sensitivity analyses to 
show the effects of alternative parameter assumptions. HUD is well 
aware of uncertainties with some of the data and much of this 
appendix is spent discussing the effects of alternative assumptions 
about data parameters and presenting the results of an extensive set 
of sensitivity analyses, many of the latter being directly related 
to comments received on the proposed rule.
    In an earlier critique of HUD's market share model, Blackley and 
Follain (1995, 1996) concluded that conceptually HUD had chosen a 
reasonable approach to determining the size of the mortgage market 
that qualifies for each of the three housing goals.\1\ Blackley and 
Follain correctly note that the challenge lies in getting accurate 
estimates of the model's parameters. In their comments on the 2000 
Proposed GSE Rule, both Fannie Mae and Freddie Mac stated that HUD's 
market share model (outlined in Section B below) was a reasonable 
approach for estimating the goals-qualifying (low-mod, special 
affordable, and underserved areas) shares of the mortgage market. 
Freddie Mac stated:
---------------------------------------------------------------------------

    \1\ Dixie M. Blackley and James R. Follain, ``A Critique of the 
Methodology Used to Determine Affordable Housing Goals for the 
Government Sponsored Housing Enterprises,'' unpublished report 
prepared for Office of Policy Development and Research, Department 
of Housing and Urban Development, October 1995; and ``HUD's Market 
Share Methodology and its Housing Goals for the Government Sponsored 
Enterprises,'' unpublished paper, March 1996.

We believe the Department takes the correct approach in the Final 
rule by examining several different data sets, using alternative 
methodologies, and conducting sensitivity analysis. We applaud the 
Department's general approach for addressing the empirical 
challenges.\2\
---------------------------------------------------------------------------

    \2\ See Freddie Mac, ``Comments on Estimating the Size of the 
Conventional Conforming Market for Each Housing Goal: Appendix III 
to the Comments of the Federal Home Loan Mortgage Corporation on 
HUD's Regulation of the Federal National Mortgage Association 
(Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie 
Mac)'', May 8, 2000, page 1.

* * *
Similarly, Fannie Mae stated that ``HUD has developed a reasonable 
model for assessing the size of the affordable housing market.'' \3\
---------------------------------------------------------------------------

    \3\ See Fannie Mae, ``Fannie Mae's Comments on HUD's Regulation 
of the Federal National Mortgage Association (Fannie Mae) and the 
Federal Home Loan Mortgage Corporation (Freddie Mac)'', May 8, 2000, 
page 53.

    However, in their comments on the proposed rule, both GSEs 
criticized HUD's implementation of its market methodology.\4\ As 
noted above, their major criticisms and HUD's responses to their 
criticisms can be found throughout this appendix. HUD recognizes 
that there is no single, perfect data set for estimating the size of 
the affordable lending market and that available data bases on 
different sectors of the market must be combined in order to 
implement its market share model (as outlined in Section B below). 
As this appendix will show, HUD has carefully combined various 
mortgage market data bases in a manner which draws on the strength 
of each in order to implement its market methodology and to arrive 
at a reasonable range of estimates for the three goals-qualifying 
shares of the mortgage market. In this appendix, HUD demonstrates 
the robustness of its market estimates by reporting the results of 
numerous sensitivity analyses that examine a range of assumptions 
about the relative importance of the rental and owner markets and 
the goals-qualifying shares of the owner portion of the mortgage 
market.
---------------------------------------------------------------------------

    \4\ See Freddie Mac, ``Comments of the Federal Home Loan 
Mortgage Corporation on HUD's Proposed Housing Goals for the Federal 
National Mortgage Association (Fannie Mae) and the Federal Home Loan 
Mortgage Corporation (Freddie Mac) for the Years 2005-2008 and 
Amendments to HUD's Regulation of Fannie Mae and Freddie Mac,'' July 
16, 2004; and Fannie Mae, ``Fannie Mae's Comments on HUD's Proposed 
Housing Goals for the Federal National Mortgage Association (Fannie 
Mae) and the Federal Home Loan Mortgage Corporation (Freddie Mac) 
for the Years 2005-2008 and Amendments to HUD's Regulation of Fannie 
Mae and Freddie Mac,'' July 16, 2004.
---------------------------------------------------------------------------

    This appendix reviews in some detail HUD's efforts to combine 
information from several mortgage market databases to obtain 
reasonable values for the model's parameters. The next section 
provides an overview of HUD's market share model.

B. Overview of HUD's Market Share Methodology \5\

1. Definition of Market Share

    The size of the market for each housing goal is one of the 
factors that the Secretary is required to consider when setting the 
level of each housing goal.\6\ Using the Low- and Moderate-Income 
Housing Goal as an example, the market share in a particular year is 
defined as follows:

    \5\ Readers not interested in this overview may want to proceed 
to Section C, which begins the market analysis by examining the size 
of the multifamily market.
    \6\ Sections 1332(b)(4), 1333(a)(2), and 1334(b)(4).
---------------------------------------------------------------------------

    Low- and Moderate-Income Share of Market: The number of dwelling 
units financed by the primary mortgage market in a particular 
calendar year that are occupied by (or affordable to, in the case of 
rental units) families with incomes equal to or less than the area 
median income divided by the total number of dwelling units financed 
in the conforming conventional primary mortgage market.
    There are three important aspects to this definition. First, the 
market is defined in terms of ``dwelling units'' rather than, for

[[Page 63819]]

example, ``value of mortgages'' or ``number of properties.'' Second, 
the units are ``financed'' units rather than the entire stock of all 
mortgaged dwelling units; that is, the market-share concept is based 
on the mortgage flow in a particular year, which will be smaller 
than total outstanding mortgage debt. Third, the low- and moderate-
income market is expressed relative to the overall conforming 
conventional market, which is the relevant market for the GSEs.\7\ 
The low- and moderate-income market is defined as a percentage of 
the conforming market; this percentage approach maintains 
consistency with the method for computing each GSE's performance 
under the Low- and Moderate-Income Goal (that is, the number of low- 
and moderate-income dwelling units financed by GSE mortgage 
purchases relative to the overall number of dwelling units financed 
by GSE mortgage purchases).
---------------------------------------------------------------------------

    \7\ So-called ``jumbo'' mortgages, greater than $333,700 in 2004 
for 1-unit properties, are excluded in defining the conforming 
market. There is some overlap of loans eligible for purchase by the 
GSEs with loans insured by the FHA and guaranteed by the Veterans 
Administration.
---------------------------------------------------------------------------

2. Three-Step Procedure

    Ideally, computing the low- and moderate-income market share 
would be straightforward, consisting of three steps:
    Step 1: Projecting the market shares of the four major property 
types included in the conventional conforming mortgage market, 
i.e.--
    (a) Single-family owner-occupied dwelling units (SF-O units);
    (b) Rental units in 2-4 unit properties where the owner occupies 
one unit (SF 2-4 units); \8\
---------------------------------------------------------------------------

    \8\ The owner of the SF 2-4 property is counted in (a).
---------------------------------------------------------------------------

    (c) Rental units in one-to-four unit investor-owned properties 
(SF Investor units); and,
    (d) Rental units in multifamily (5 or more units) properties (MF 
units).\9\
---------------------------------------------------------------------------

    \9\ Property types (b), (c), and (d) consist of rental units. 
Property types (b) and (c) must sometimes be combined due to data 
limitations; in this case, they are referred to as ``single-family 
rental units'' (SF-R units).
---------------------------------------------------------------------------

    Step 2: Projecting the ``goal percentage'' for each of the above 
four property types (for example, the ``Low- and Moderate-Income 
Goal percentage for single-family owner-occupied properties'' is the 
percentage of those dwelling units financed by mortgages in a 
particular year that are occupied by households with incomes below 
the area median).
    Step 3: Multiplying the four percentages in (2) by their 
corresponding market shares in (1), and summing the results to 
arrive at an estimate of the overall share of dwelling units 
financed by mortgages that are occupied by low- and moderate-income 
families.
    The four property types are analyzed separately because of their 
differences in low- and moderate-income occupancy. Rental properties 
have substantially higher percentages of low- and moderate-income 
occupants than owner-occupied properties. This can be seen in the 
top portion of Table D.1, which illustrates Step 3's basic formula 
for calculating the size of the low- and moderate-income market.\10\ 
In this example, low- and moderate-income dwelling units are 
estimated to account for 53.9 percent of the total number of 
dwelling units financed in the conforming mortgage market.
---------------------------------------------------------------------------

    \10\ The property shares and low-mod percentages reported here 
are based on one set of model assumptions; other sets of assumptions 
are discussed in Section E.

---------------------------------------------------------------------------

[[Page 63820]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.076

    To examine the other housing goals, the ``goal percentages'' in 
Step 2 would be changed and the new ``goal percentages'' would be 
multiplied by Step 1's property distribution, which remains 
constant. For example, the Underserved Areas Goal \11\ would be 
derived as illustrated in the bottom portion of Table D.1. In this 
example, units eligible under the Underserved Areas Goal are 
estimated to account for 31.4 percent of the total number of 
dwelling units financed in the conforming mortgage market.\12\
---------------------------------------------------------------------------

    \11\ This goal will be referred to as the ``Underserved Areas 
Goal''.
    \12\ The example in Table D.1 is based on 1990 Census tract 
geography. As explained in Section G, switching to 2000 Census tract 
geography (scheduled for 2005) increases the underserved areas 
market share by approximately five percentage points.
---------------------------------------------------------------------------

3. Data Issues

    Unfortunately, complete and consistent mortgage data are not 
readily available for carrying out the above three steps. A single 
data set for calculating either the property shares or the housing 
goal percentages does not exist. However, there are several major 
data bases that provide a wealth of useful information on the 
mortgage market. HUD combined information from the following 
sources: the Home Mortgage Disclosure Act (HMDA) reports, the 
American Housing Survey (AHS), HUD's Survey of Mortgage Lending 
Activity (SMLA), the Census Bureau's AHS-based Property Owners and 
Managers Survey (POMS), and the Census Bureau's recent 2001 
Residential Finance Survey (RFS). In addition, information on the 
mortgage market was obtained from the Mortgage Bankers Association, 
Fannie Mae, Freddie Mac and other organizations.
    Property Shares. To derive the property shares, HUD started with 
forecasts of single-family mortgage originations (expressed in 
dollars). These forecasts, which are available from the GSEs and 
industry groups such as the Mortgage Bankers Association, do not 
provide information on conforming mortgages, on owner versus renter 
mortgages, or on the number of units financed. Thus, to estimate the 
number of single-family units financed in the conforming 
conventional market, HUD had to project certain market parameters 
based on its judgment about the reliability of different data 
sources. Sections D and E report HUD's findings related to the 
single-family market.
    Total market originations are obtained by adding multifamily 
originations to the single-family estimate. Because of the wide 
range of estimates available, the size of the multifamily mortgage 
market turned out to be one of the most controversial issues raised 
during the initial rule-making process during 1995; this was also an 
issue that the GSEs focused on in their comments on the 2000 final 
rule and their comments on the 2004 proposed GSE rule. Because most 
renters qualify under the Low- and Moderate-Income Goal, the chosen 
market size for multifamily can have a substantial effect on the 
overall estimate of the low- and moderate-income market (as well as 
on the estimate of the special affordable market). Thus, it is 
important to consider estimates of the size of the multifamily 
market in some detail, as

[[Page 63821]]

Section C does. In addition, given the uncertainty surrounding 
estimates of the multifamily mortgage market, it is important to 
consider a range of market estimates, as Sections F-H do.
    Goal Percentages. To derive the goal percentages for each 
property type, HUD relied heavily on HMDA, AHS, POMS and RFS data. 
For single-family-owner originations, HMDA provides comprehensive 
information on borrower incomes and census tract locations for 
metropolitan areas. Unfortunately, it provides no information on the 
incomes of renters living in mortgaged properties (either single-
family or multifamily) or on the rents (and therefore the 
affordability) of rental units in mortgaged properties. The AHS, 
however, does provide a wealth of information on rents and the 
affordability of the outstanding stock of single-family and 
multifamily rental properties. An important issue here concerns 
whether rent data for the stock of rental properties can serve as a 
proxy for rents on newly-mortgaged rental properties. During the 
2000 rule-making process, POMS data were used to examine the rents 
of newly-mortgaged rental properties; thus, the POMS data 
supplements the AHS data. The recently released RFS provides 
information on property shares (e.g., the relative importance of 
rental versus owner properties) and several other important 
parameters in HUD's market model. The data base issues as well as 
other technical issues related to the goal percentages (such as the 
need to consider a range of mortgage market environments) are 
discussed in Sections F, G, and H, which present the market share 
estimates for the Low- and Moderate-Income Goal, the Underserved 
Areas Goal, and the Special Affordable Goal, respectively.

4. Conclusions

    HUD is using the same basic methodology for estimating market 
shares that it used in its 1995 and 2000 final rules and its 2004 
proposed rule. As demonstrated in the remainder of this appendix, 
HUD has attempted to reduce the range of uncertainty around its 
market estimates by carefully reviewing all known major mortgage 
data sources, by considering comments on the 2004 proposed rule, and 
by conducting numerous sensitivity analyses to show the effects of 
alternative assumptions. Sections C, D, and E report findings 
related to the property share distributions called for in Step 1, 
while Sections F, G, and H report findings related to the goal-
specific market parameters called for in Step 2. These latter 
sections also report the overall market estimates for each housing 
goal calculated in Step 3.
    In considering the levels of the goals, HUD carefully examined 
comments by the GSEs and others on the methodology used to establish 
the market share for each of the goals. Based on that thorough 
evaluation, as well as HUD's additional analysis for this final 
rule, HUD concludes that its basic methodology is a reasonable and 
valid approach to estimating market shares. As in the past, HUD 
recognizes the uncertainty regarding some of these estimates, which 
has led the Department to undertake a number of sensitivity and 
other analyses to reduce this uncertainty and also to provide a 
range of market estimates (rather than precise point estimates) for 
each of the housing goals.

C. Size of the Conventional Multifamily Mortgage Market \13\

    This Section C differs from the version published in the May 3, 
2004, Proposed Rule in the following ways: The estimates from the 
``HUD New'' and ``Flow of Funds'' methods discussed below in parts 2 
and 3 have been updated through 2003, and responses to comments 
received on those methods have been added to those sections. The 
part titled ``Most Likely Range'' has been revised in light of the 
2003 estimates and comments received. The discussion of ``Loan 
Amount per Unit,'' part 5, has been revised in response to comments 
and to newly available data from the GSEs and the 2003 American 
Housing Survey. The multifamily mix discussion, part 6, has been 
revised in accordance with other changes. Section C.7 has been added 
on the multifamily mix as estimated from the newly released 2001 
Residential Finance Survey (RFS). Lastly, Section C.8 discusses the 
multifamily mixes that will be examined in HUD's projection model 
for 2005-2008. Other than these changes and minor editorial 
corrections, the text in this section is identical to that in the 
Proposed Rule published May 3, 2004. Changes to Tables D.2 through 
D.5 are noted in the text and table notes. The old Table D.5 is now 
D.5a and Tables D.5b and D.5c have been added.
---------------------------------------------------------------------------

    \13\ This section is based on analysis by Jack Goodman under 
contract with the Urban Institute.
---------------------------------------------------------------------------

    This section provides estimates of (a) the annual dollar volume 
of conventional multifamily mortgage originations and (b) the annual 
average loan amount per unit financed. The estimates build on 
research reported in the Final Rule on HUD's Regulation of Fannie 
Mae and Freddie Mac as published in the Federal Register on October 
31, 2000, especially in Appendix D. That material from the 2000 Rule 
will not be repeated here but will be referenced or summarized where 
appropriate.
    This section uses the information on dollar volume of 
multifamily originations and average loan amounts to estimate the 
number of multifamily units financed each year as a percentage share 
of the total (both single-family and multifamily) number of dwelling 
units financed each year. This percentage share, called the 
``multifamily mix'', is an important parameter in HUD's projection 
model of the mortgage market for 2005-08 (see Section C.8 below)
    Estimating this ``multifamily mix'' is important because 
relative to its share of the overall housing market, the multifamily 
rental sector has disproportionate importance for the housing goals 
established for Fannie Mae and Freddie Mac. This is because most 
multifamily rental units are occupied by households with low or 
moderate incomes. Between 1999 and 2002, for example, the GSEs 
purchased mortgages on approximately 26.1 million housing units, of 
which only 9.5 percent were multifamily rental units. However, of 
the GSEs' purchases qualifying as mortgages on low- and moderate-
income housing during this period, 18 percent of the units financed 
were multifamily rental units. Of the GSEs' purchases qualifying as 
special affordable mortgages during this period, 25 percent of the 
units financed were multifamily rental units.
    The methods used in the 2000 Rule for estimating the size of the 
multifamily mortgage market and related variables were the product 
of extensive research by HUD and review by interested parties. The 
approach here is first to extend those estimates through 2002 using 
the same methods as in the 2000 Rule, and then to present 
alternative methods, along with commentary.

1. Data Sources

    The data sources available for estimating the size of the 
multifamily mortgage market are more limited in scope and timeliness 
than was the case for the 2000 Rule. Among the key sources described 
in detail in the 2000 Rule, the following are now less useful:
    Survey of Mortgage Lending Activity. This survey has been 
discontinued; estimates are available only through 1997.
    Residential Finance Survey: The 1991 Residential Finance Survey 
(RFS) is now 13 years out of date. (See Section C.7 for results from 
the 2001 RFS.)
    Urban Institute Statistical Model: This model, developed in 1995 
and calibrated using data from 1975-1990, is now even further 
removed from its calibration period and probably captures current 
market conditions less accurately.
    Estimates from the GSEs: As part of their comments on the 
proposed 2000 Rule, Fannie Mae and Freddie Mac shared with HUD their 
own estimates of the size of the multifamily mortgage market.

Fortunately, several key sources are available with the timeliness 
and quality comparable to the sources used during development of the 
2000 Rule. These sources are: The Home Mortgage Disclosure Act 
(HMDA); activity reports submitted to HUD and the Office of Federal 
Enterprise Oversight (OFHEO) by Fannie Mae and Freddie Mac; non-GSE 
mortgage-backed security issuance from the Commercial Mortgage Alert 
database; and multifamily mortgage activity by life insurance 
companies, as estimated by the American Council of Life Insurers 
(ACLI). For background information on each of these sources, readers 
are referred to Appendix D of the 2000 Rule.

2. Estimates Based on ``HUD New'' Methodology

    In the 2000 Rule, HUD developed a new methodology for estimating 
aggregate multifamily conventional loan originations. The method, 
here labeled ``HUD New'', was developed to make full use of the 
available data, and in particular the four sources listed above, 
which encompass most of the multifamily mortgage market.
    The advantages of HUD New are that it provides reasonably 
complete coverage of the market, produces those estimates within 
nine months of the end of the year, generally includes only current 
originations and avoids double counting. The main disadvantage of 
HUD New is that it produces a lower bound estimate. Some loan 
originators are missed, including pension funds, government entities

[[Page 63822]]

at the federal, state, and local levels, real estate investment 
trusts, and some mortgage bankers. Also, excluded are loans made by 
private individuals and partnerships. In addition to these 
exclusions, estimates from the covered lenders require some 
judgmental adjustments to conform to the definitions and time 
intervals of HUD New.
    Despite these limitations, HUD New is one sound way to estimate 
the size of the multifamily conventional mortgage market. Although 
the method requires unavoidable judgment calls on which analysts may 
differ, sensitivity analysis can be performed to show the effects of 
different multifamily origination volumes on the goals qualifying 
market estimates (see Sections F-H). Due to the reasonableness of 
the HUD New approach, the value of maintaining continuity in 
estimation methods, and the fact that no data has become available 
in the past few years that would argue for modifying HUD New, it is 
used here for the baseline estimate of the size of the conventional 
multifamily mortgage market in 2000, 2001, 2002 and 2003.
    The estimates from HUD New are presented in Table D.2. This 
table is the counterpart of Table D.5 in the 2000 Rule. The 
historical years have two columns each, one for the estimates 
presented in the 2000 Rule and one for estimates independently 
produced as part of this research. Footnotes to the table provide 
more complete descriptions of the components. Additional background 
on the calculations is provided in the 2000 Rule (Appendix D, 
Section C).
BILLING CODE 4210-27-P

[[Page 63823]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.077


[[Page 63824]]


    The revisions to the historical estimates (i.e., those in the 
2000 Final Rule) result from both revisions to some of the input 
data and recalculations. For the years 1995 through 1998, the 
revisions are small for the estimates of total originations. The 
only one of note is a 5 percent upward revision to the estimate for 
1995, prompted by a recalculation of the entry for life insurance 
companies. The revision to 1999 is larger, and results mostly from 
the substitution of the actual HMDA results for that year for the 
projected value used in the 2000 Rule. Surprisingly, the revised 
estimate for 2000 based on complete data for that year only varies 
slightly from the projection made at the time of the 2000 Rule. Most 
of the historical estimates produced in 2000 can be replicated or 
closely approximated, including those for Fannie and Freddie, CMBS, 
HMDA, and life insurance companies. The replicability of the CMBS 
figures is especially important, in light of all the selection 
criteria and hand calculations required to generate those estimates 
from the CMBS database. (In the 2000 Rule, the estimates for Freddie 
Mac and CMBS originations in 1997 appear to have been switched, and 
the revised estimates make this correction.)
    The revised figures for 1999 and 2000 indicate that total 
conventional originations dropped 8 percent in 1999 from 1998's very 
strong level and another 13 percent in 2000. However, the HUD New 
estimate indicates that total conventional originations then jumped 
40 percent in 2001 and further increased 15 percent in 2002. Judging 
from Survey of Mortgage Lending Activity estimates since 1970, the 
2002 number is a new record high. For 2002, most of the increased 
volume is due to increases by HMDA lenders and life insurance 
companies.
    One possible concern is that the significant increase in the 
HMDA number in 2002 was caused by the FFIEC relaxing its eligibility 
requirements between 2001 and 2002. This concern turns out to be 
unfounded. The FFIEC actually raised its eligibility requirements. 
The level of assets required by FFIEC to be reported to HMDA 
increased from $31 million in 2001 to $32 million in 2002. In 
addition, the number of HMDA reporters decreased from 7,771 in 2001 
to 7,638 in 2002.
    Compared with the version of Table D.2 in the Proposed Rule of 
May 3, 2004, the version here updates the estimates through 2003 and 
revises the 2001 and 2002 estimates slightly in response to newly 
available data. The data for 2003 point to a large, broad-based 
increase in the volume of multifamily lending. Total conventional 
originations, estimated at $89 billion, are up 32 percent from 2002, 
easily reaching a new record high. A large increase was observed in 
each of the five market segments listed in Table D.2.
    Several organizations commented on the HUD New method. Fannie 
Mae says it involves double counting of originations. However, the 
one example they offer--between life insurance company data and CMBS 
data--should not be subject to double counting because 
securitizations by life insurance companies are deleted from the 
CMBS totals, as noted in Table D.2 and in documentation included in 
the 2000 Rule. Freddie Mac, through its contractor, uses an approach 
similar to HUD New but uses different data sources. Inadequate 
details are provided on the tabulations and judgments applied to 
evaluate the method. Lastly, MBA expresses a preference for the 
estimates provided by HUD New and says, without providing detail, 
that estimates developed by their consultants are similar to those 
presented in HUD New.
    The comments received fail to note the point made repeatedly in 
the proposed rule text that the HUD New estimates are lower bounds 
on the volumes of originations. While HUD New is characterized in 
the proposed rule as providing ``* * * the baseline estimate of the 
size of the conventional multifamily mortgage market * * *'', other 
language in the rule makes clear that ``baseline'' is used in the 
sense of ``starting point.'' For example, the proposed rule also 
states that ``* * * unavoidable gaps in coverage make the resulting 
HUD New figures lower-bound estimates of actual originations rather 
than best `point' estimates'' (p. 24450).

3. An Alternative Method

    The HUD New method makes use of all the available sources of 
data on individual origination sources in attempting to estimate 
total conventional mortgage originations. However, as discussed in 
the 2000 Rule and summarized above, unavoidable gaps in coverage 
make the resulting HUD New figures lower-bound estimates of actual 
originations rather than best ``point'' estimates. In addition, even 
for those loans that are available, certain assumptions must be made 
to convert the available data into estimates corresponding to the 
desired definition and time periods. An alternative to the bottom-up 
approach of HUD New avoids some of the data problems. The Federal 
Reserve's Flow of Funds accounts provide the most complete and 
timely set of estimates of multifamily mortgage credit. The Flow of 
Funds statistics refer to net changes in credit outstanding rather 
than gross originations. Specifically, balance sheet estimates of 
mortgage assets of lenders are used to produce estimated changes in 
holdings of mortgages over time. An alternative label for the 
resulting time series is ``net change in mortgage debt 
outstanding.''
    The historical relationship between gross originations and net 
change can be used to estimate recent origination volume. Separate 
information on FHA multifamily activity can be used to convert the 
total originations to estimates of only conventional originations. 
The Flow of Funds method that is described in this section will be 
called ``FoF-based.''
    Flow of Funds estimates of mortgage debt outstanding are based 
on data from sources of varying accuracy and timeliness. Bank and 
thrift institution holdings, taken from regulatory filings, are by 
all accounts highly accurate, as are those from the government 
sponsored agencies and direct Federal government holdings. The 
private MBS data and the life insurance company figures, both taken 
from Wall Street sources, are also thought to be reasonably 
accurate. Less accurate are the estimates of loans made by private 
individuals and certain institutions, for which comprehensive data 
on loans outstanding is provided only once every ten years, through 
the Residential Finance Survey. Fortunately, the depository 
institutions, GSEs, and mortgage-backed securities account for the 
bulk of all holdings of mortgage debt (approximately 72 percent, 
according to the Flow of Funds estimates for year-end 2001). Thus, 
most of the Flow of Funds data are from highly accurate sources.
    The net change in mortgage debt outstanding in any year is the 
lower bound on originations. This is because the net change is 
defined as originations less the sum of principal repayments and 
charge offs. Historically loan originations have exceeded the net 
change by a considerable margin in both the multifamily and single-
family markets. There are several reasons why the relationship of 
originations to net change differs between the multifamily and 
single-family sectors, but the basic principles apply to both 
sectors.
    Table D.3 presents the annual estimates from the Flow of Funds. 
Also shown are the estimates of multifamily conventional 
originations as published in Table D.10 from the 2000 rule, and FHA 
originations from HUD administrative records.
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    The ratio of mortgage originations to net change should be 
positively correlated with the proportion of total originations that 
are refinancings, for which the net change in mortgage debt would be 
expected to be low relative to that on loans taken out in connection 
with a property acquisition. (This is the pattern observed in the 
single-family mortgage market.) Refinancings, in turn, would be 
expected to be prevalent relative to purchase loans at times when 
interest rates are low relative to their recent past.
    The historical evidence generally supports this expectation 
regarding the relationship of originations to net lending. As shown 
in Table D.3, total originations have been highest relative to net 
change when interest rates have been low relative to their recent 
past. [Note: Columns A1, B1, C1, and D1 are the figures appearing in 
the Proposed Rule version of this table. Owing to extensive 
revisions to the input data, new columns with the revised inputs and 
calculated values have been added to facilitate comparisons. These 
revised figures appear in Columns A2, B2, C2, and D2.] The ten-year 
Treasury yield, a common benchmark for pricing multifamily 
mortgages, has generally trended down since 1990. The early 1990s 
were all marked by high originations relative to net change, and 
these were also years in which interest rates were particularly low 
relative to their trailing five-year averages. In 1996 and 1997, by 
contrast, originations were less high relative to net change, and 
these were years in which interest rates were only slightly lower 
than their five-year trailing averages. In estimating conventional 
originations for 1999-2002, the 1998 experience is a useful 
benchmark. That year, total originations exceeded the net change by 
about 80 percent, as shown in Table D.3. There was also a big drop 
in interest rates in 1998 relative to the recent past, providing an 
incentive for refinancings. As shown in the table, interest rates 
rose slightly in 1999 and again in 2000, presumably diminishing the 
incentive to refinance. Nonetheless, the net change in mortgage debt 
was higher in 1999 and 2000 than it had been in 1998.
    Putting all this together, it seems that the appropriate ratio 
of total originations to net change to apply to 1999 and 2000 would 
be below that of 1998 and of most other years of the 1990s. Applying 
a ratio of 1.5 to the net change estimates in 1999 and 2000 results 
in a total originations estimate of approximately $56 billion. 
Subtracting the $4 billion in FHA originations results in estimates 
of $52 billion for conventional originations in each year. A 
subjective confidence band around this point estimate is at least +/
-$2 billion.
    Turning to the estimate for 2001, the first thing to note is 
that net change in mortgage debt jumped to $48 billion from $37 
billion of the previous two years. The second thing to note is that 
interest rates fell by nearly a percentage point in 2001 relative to 
their past average. For both of these reasons, total originations in 
2001 would be expected to have been higher than in 1999 or 2000. How 
much higher is a subjective judgment, but 1.5 would seem an 
appropriate multiple to apply to the net change number in 2001. This 
is the same multiple as in 1999 and 2000, despite the added 
refinancing incentive in 2001. By the beginning of 2001, there were 
relatively few properties ``at risk'' of refinancing. Many 
presumably had refinanced in one of the preceding years, and lock-
out provisions, yield maintenance agreements, and other loan 
conditions may have kept these properties from coming in for 
refinancings. Also, there may have been some short-run capacity 
problems in the multifamily loan origination industry in 2001 that 
further curtailed volume.
    Applying the 1.5 multiple to 2001's net change of $48 billion 
yields a total originations estimate of $71 billion. Subtracting FHA 
business results in a conventional originations estimate of $67 
billion, to which a subjective confidence band of at least $2 billion appears warranted.
    As seen in Table D.3, the Flow of Funds methodology indicates 
that total conventional originations decreased 6.5% between 2001 and 
2002. In 2002, the net change in mortgage debt decreased slightly to 
$44 billion. Using the 1.5 multiple for 2002's net change of $44.2 
billion yields a total originations estimate of $67 billion. 
Subtracting $4.5 billion of FHA business results in a conventional 
originations estimate of $62 billion.
    This Flow of Funds estimate is over $5 billion less than the 
estimate from HUD New. This is surprising given that the HUD New 
method is supposed to serve as a lower boundary on the size of the 
multifamily market, while the Flow of Funds method is designed to 
produce a higher ``point'' estimate of the actual size of the 
market.
    Like the estimates for HUD New, those for the Flow of Funds 
method have been revised and updated through 2003 to incorporate new 
data. As with HUD New, the Flow of Funds method suggests a large 
increase in conventional mortgage lending in 2003. The estimate for 
conventional originations in 2003 is $75 billion, up 29 percent from 
the revised estimate for 2002. In percentage terms, the increase in 
2003 almost matches that of the HUD New method's estimates of Table 
D.2.
    The originations estimates for earlier years, and especially 
2000-2002, have been revised downward in response to revisions by 
the Federal Reserve to the Flow of Funds accounts and by an update 
to HUD's FHA estimate for 2002. The downward revision was largest 
for 2000, for which year the new figure of $44 billion of 
conventional originations is $8 billion less than the earlier 
estimate.
    The big increase in estimated originations in 2003 is largely 
the result of the Federal Reserve's estimate of a large increase 
that year in net change in mortgage debt outstanding, shown in 
column A2 of Table D.3 The increase in 2003 in the Flow of Funds 
accounts is likely to be fairly accurate, because almost all of it 
is attributable to holder types for which the Fed has reliable 
statistics, specifically depository institutions and GSE mortgage 
securities. As in 1999-2002, in 2003 the net change was converted 
into total originations by applying a multiplier of 1.5, under the 
assumption that the continued decline in interest rates provided 
even stronger incentives for refinancing. As shown in the last 
columns of Table D.3, ten-year Treasury yields in 2003 averaged 
about 60 basis points below those of 2002, and approximately 130 
basis points below the average of the previous five years.
    Comments on the Flow of Funds method for estimating multifamily 
originations focused on the approach to converting net change into 
loan originations. Fannie Mae argued that it was preferable to 
convert by applying a liquidation rate to the stock of mortgage debt 
and deriving originations as net change plus estimated liquidations. 
A trade organization noted the historical instability of the ratio 
of originations to net change and argued that the ``HUD New'' 
approach to estimating originations was superior. Freddie Mac and 
its consultant, while not commenting directly on the Flow of Funds 
method, expressed a preference for a modified version of HUD New, as 
described in the previous part of this section.
    The most recent data suggest that originations may in fact have 
been higher than estimated in the Flow of Funds approach and that 
the 1.5 multiplier used to convert net change into originations is 
too low. The reason is that in both 2002 and 2003, the 1.5 
multiplier results in estimated conventional originations that are 
less than those produced by the HUD New method. As discussed 
earlier, HUD New provides a lower bound estimate. Fannie Mae's lower 
estimates of originations in recent years, relative to those in the 
proposed rule, result from the liquidation rate used in the 
calculation, which is that from Fannie Mae's own portfolio. But 
Fannie Mae's liquidation rate would be expected to fall below the 
market wide average, because Fannie Mae's multifamily business has 
been growing more rapidly than the market overall, and as a result 
its loans presumably on average are ``younger'' and consequently 
less likely to prepay or be retired than are the loans in the market 
as a whole. Lastly, regarding the historical instability of the 
ratio of originations to net change noted by a trade organization, 
Table D.3 of the proposed rule also presented the annual difference 
between originations and net change, which is considerably more 
stable. The differences corresponding to the 1.5 multiplier for the 
past several years are, as shown in D.3, below the historical 
averages. This is additional evidence that the 1.5 multiplier is 
perhaps too low.

4. Most Likely Range

    In the 2000 Rule, estimates of conventional multifamily loan 
originations from various sources and methods were evaluated in 
determining the most likely range of annual originations. Those 
estimates were summarized in Table D.10 in the 2000 Rule. Some of 
the estimates from that table are reproduced below, in Table D.4, 
along with updates and estimates from the Flow of Funds method.
    Both HUD New (column 4 in Table D.4) and FoF-based 
(column 9) indicate a surge in lending activity in 2001. 
Some corroboration of this jump is provided by other indicators, 
flawed though they may be. HMDA has well-documented coverage 
problems with multifamily loans, but it is

[[Page 63827]]

noteworthy that HMDA-estimated conventional originations stayed in 
the same general range ($26 to $31 billion) in 1998-2000 before 
jumping to $36 billion in 2001. The composite of 1.25 times HMDA 
originations plus life insurance commitments, described in the 2000 
Rule and updated here in column 5, also follows this basic 
path. Similarly, aggregate GSE multifamily purchases and 
securitizations stayed in the same general level in 1998-2000, 
before jumping in 2001, although this trend reflects changes in both 
market size and GSE market share. FHA originations (not shown) also 
rose substantially in 2001, but this too may indicate more than just 
market size trends.
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[[Page 63828]]


    Column 11 of Table D.4 gives the likely ranges of 
originations for each of the years. These are based on the estimates 
from all sources and interpretations of their strengths and 
weaknesses. In 1999, the $4 billion upward revision to the HUD New 
estimate from the preliminary figure reported in the 2000 Rule, 
together with the higher estimate produced by the FoF-based method, 
justify an upward revision to the $45-$48 range estimated in the 
2000 Rule. The revised range is set at $50-54 billion. In 2000, HUD 
New (revised and extended version) suggests that originations were 
somewhat lower than in 1999, but FoF-based has originations holding 
at $52 billion. Balancing these conflicting indicators, a range of 
$48-$52 billion is selected for 2000. Finally, all indicators point 
to a substantial pickup in 2001, and the range that seems to fit 
best with those indicators is $65-$69 billion.
    In 2002, the various methods of estimation give a mixed picture. 
HUD New indicates a surge in lending activity in 2002, while the 
flow of funds method shows a decrease in lending activity. Other 
methods also show divergent trends. The composite of 1.25 times HMDA 
originations plus life insurance commitments also shows a 
significant increase between 2001 and 2002. On the other hand, 
aggregate GSE multifamily purchases and securitizations showed a 
slight decrease between 2001 and 2002. FHA originations (not shown) 
also decreased slightly in 2002.
    While this is a subjective judgment, 1.5 may not be the 
appropriate multiple to apply to net mortgage debt outstanding in 
the flow of funds model in 2002. The difference between the flow of 
funds estimate and the HUD estimate cannot be reconciled without 
adjusting the FoF multiple. Given the low interest rates in 2002, 
and a refinancing boom in the single-family mortgage market, it 
could be that the multifamily market also had a significant amount 
of refinancing activity. In such a case, there could be an increase 
in the size of the multifamily market without a corresponding 
increase in net mortgage debt outstanding. A higher multiple would 
need to be applied to the Flow of Funds model to compensate for the 
increase in multifamily refinancings.
    Due to data limitations, the above remains a speculation. The 
largest increase in multifamily volume came from HMDA reporting 
lenders. The HMDA data do not allow for the separation of 
multifamily purchase originations from refinancings. Other data 
sources need to be explored to determine if an adjustment to the 
FoF-based model is appropriate.
    Both HUD New and the FoF-based method indicate a large increase 
in conventional multifamily loan originations in 2003. But the FoF 
estimates for each of the previous four years have been revised 
downward in light of revised input data. According to these updated 
and revised estimates, conventional multifamily originations by HUD 
New have exceeded the estimates of FoF in two of the past five 
years, and in the other three years FoF exceeded HUD New by only 
narrow margins. Because HUD New produces lower bound estimates of 
originations, whereas FoF is intended to provide best point 
estimates, the Department concludes that the 1.5 multiplier applied 
in the FoF method is too low, and as a result the FoF estimates 
understate originations in the past several years. In light of this 
probable underestimate of the multiplier, and after consideration of 
comments received, the Department believes that the likely ranges of 
conventional originations for 2002 and earlier years as published in 
the May, 2004, Proposed Rule continue to be reasonable estimates, 
although likely on the conservative side. As for 2003, the estimates 
from HUD New and FoF indicate a substantially higher likely range, 
which the Department has set at $85 billion to $100 billion. As 
explained in Section C.6 below, HUD will conduct sensitivity 
analyses in Sections F-H showing the effects of different 
multifamily mixes on the historical estimates of the goals-
qualifying shares of the mortgage market.

5. Loan Amount per Unit

    In determining the size of the conventional multifamily mortgage 
market for purposes of the GSE rules, the measure of market size is 
the annual number of conventionally financed multifamily rental 
housing units. The number of units is derived by dividing the 
aggregate annual originations by an estimate of the average loan 
amount per housing unit financed. For this reason, accuracy in the 
estimate of loan amount per unit is as important as accuracy in the 
dollar estimate of aggregate conventional originations. A 10 percent 
error in either will result in a 10 percent error in the estimate of 
market size.
    The 2000 Rule used estimates of loan amount per unit drawn from 
various sources. As summarized in Table D.9 of the 2000 Rule and the 
accompanying text, the estimates for 1993-1998 were taken from the 
GSEs and for 1999 from CMBS data. ``Unpaid Principal Balance'' or 
UPB--a balance sheet measure which for current year loan 
originations will differ little from the initial loan amount--is 
used to calculate aggregate originations of loans bought or 
securitized by the GSEs or pooled into non-GSE mortgage-backed 
securities. The figures from Table D.9 of the 2000 Rule are 
reproduced below in Table D.5a, along with updated estimates from 
all three sources for 2000, 2001 and 2002. The estimates that are 
new since the 2000 Rule appear in italics.
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[[Page 63830]]

    Several options are available for developing estimates for 2000, 
2001 and 2002. The first is to use the UPB (unpaid principal 
balance) per unit estimates from the GSEs. These estimates, taken 
from the Fannie Mae and Freddie Mac annual activity reports to HUD, 
are as follows, computed as in the 2000 Rule as a unit-weighted 
average of the unpaid principal balance (UPB) per multifamily unit 
in Fannie Mae's and Freddie Mac's portfolios:

1997........................................................     $27,266
1998........................................................      31,041
1999........................................................      35,038
2000........................................................      37,208
2001........................................................      37,258
2002........................................................      39,787
 

    The figure for 2002 is approximately 46 percent higher than in 
1997. Both Fannie Mae and Freddie Mac's portfolios generate 
estimates of between $39,000 and $40,000 for 2002.
    Several alternative approaches to estimating loan amount per 
unit are available. The first is to base the estimate on CMBS data, 
as was done for 1999 in the 2000 Rulemaking. As shown in the last 
column of Table D.5, the estimates of UPB/unit from this source are 
somewhat below those of the GSEs and indicate less increase since 
the late 1990s.
    In the first 10 months of 2002, CMBS properties showed a UPB/
unit of $37,038, a nearly 14 percent jump over the previous year. 
Although slightly below the UPB/unit for the GSEs, the CMBS numbers 
are closer to the GSE calculations than in previous years.
    Another approach is to move the 1999 estimate of UPB/unit 
forward by some justifiable index. The 2001 estimates use the change 
in average rent on multifamily rental units from the American 
Housing Survey. Because AHS data are not available for 2002, the 
2002 estimate uses the consumer price index for rent of primary 
residence. Both AHS and CPI rent estimates are listed below:

------------------------------------------------------------------------
                   Year                      Median     Mean       CPI
------------------------------------------------------------------------
1999......................................      $550      $592     177.5
2001......................................       590       647     192.1
2002......................................       N/A       N/A     199.7
------------------------------------------------------------------------

    There is some variation between the two measures. In the AHS, 
median rent rose 7.3 percent over this two-year period, and mean 
rent increased 9.3 percent. Meanwhile, the CPI showed an increase of 
8.2 percent. In 2001, using the AHS produces an estimate of $34,000. 
The CPI yields a smaller estimate for 2001; applying the 8.2 percent 
increase from the CPI results in a 2001 estimate of $33,200. Since 
the AHS data are unavailable in 2002, the CPI provides a 2002 
estimate of approximately $35,000.
    In 2001, the rent-adjusted 1999 estimate was in between the 
estimates from the CMBS and GSE data, and was a fair estimate of the 
actual size of the market. In 2002, however, the rent-adjusted 
number is below both the CMBS and GSE calculations. The rent-
adjusted number could be underestimating the 2002 UPB/unit. Either 
the CMBS or GSE calculations, or an average of the various methods 
could be used. Sections F-H will report the results of sensitivity 
analyses showing the effects of the different multifamily mortgage 
estimates and different per unit amounts on the goals-qualifying 
shares for the year 2002. Under the various estimates, the 
multifamily mix (defined below) for 2002 varies from 9.5 percent-11 
percent.
    Since the proposed rule was issued by the Department, data for 
2003 have become available that permit updates of some of the 
sources of UPB/unit estimates. The GSEs' experience, shown in the 
bottom row of Table D.5a, was mixed. Fannie Mae's UPB/unit increased 
about 4 percent from 2002, but Freddie Mac's dropped 9 percent. The 
volume-weighted average UPB/unit for the GSEs in 2003 was $39,082, 
off about 2 percent from the 2002 average of $39,787 shown in the 
text table above.
    The most recent rent estimates from the American Housing Survey 
also suggest limited or negative recent growth in UPB/unit. The 
median and mean rents for 2003 that correspond to those in the table 
above are $609 and $671. Given the logic of this method as described 
in the proposed rule, it seemed most appropriate to use the percent 
increase in AHS rents from 1999 to 2003 to update the 1999 UPB/unit 
($30,719) to a 2003 figure. Using the 13.3 percent increase in mean 
rent between 1999 and 2003 (the increase in median was only 10.7 
percent) and moving the baseline UPB/unit from 1999 forward to 2003 
by this proportion brings the 2003 UPB/unit to $34,805. That is the 
number appearing in Table D.5a. For comparison, the CPI rent index 
rose 15.8 percent between 1999 and 2003.
    In commenting on HUD's UPB/unit estimates for 2000-2002, as 
published in the May 2004 Proposed Rule, both Fannie Mae and Freddie 
Mac expressed the view that the estimates were too low. They cited 
both their own experience and other evidence and argued that HUD's 
reliance on CMBS and rent data, and switching of benchmark years, 
resulted in UPB/unit estimates that were substantially below the 
actual market averages.
    In reviewing the comments and in light of these new data HUD has 
concluded that the estimates in the proposed rule likely were too 
low. The more difficult determination is where to set the estimates. 
The Department has not revised its estimate of UPB/unit for 2002 and 
earlier years, because of this uncertainty. The situation is similar 
to that discussed in the previous part of this section in discussing 
the likely range of conventional multifamily originations, where the 
new data lead the Department to think the Flow of Funds estimates 
may be too low, but no adjustments were made to the likely range as 
reported in Table D.4. If adjustments were made to the historical 
estimates of originations and UPB per unit, the revisions would be 
at least partially offsetting, with little net effect on the 
historical estimates of number of multifamily units financed. As for 
2003, weighing all available information, the Department has set the 
UPB/unit at $39,082, the weighted average of the GSEs' actual UPB/
unit for that year. As explained in the next section, goals-
qualifying estimates for 1995-2002 are reported in Sections F-H that 
include multifamily mixes approximately two-three percentage points 
lower that the multifamily mixes suggested by the most likely range 
of multifamily dollar estimates and the UPB/unit estimates.

6. Multifamily Mix During the 1990s

    This section uses the information on dollar volume of 
multifamily originations (Table D.4) and average loan amounts (Table 
D.5a) to estimate the number of multifamily units financed each year 
as a percentage share of the total (both single-family and 
multifamily) number of dwelling units financed each year. Because of 
the high goals-qualifying shares of multifamily housing, the 
multifamily mix is an important parameter in HUD's projection model 
for the overall market; other things equal, a higher multifamily mix 
(or conversely, a lower share of single-family loans) leads to a 
higher estimate of goals-qualifying loans in the overall mortgage 
market. This percentage share, or ``multifamily mix'', is reported 
in the last two columns of Table D.4 for the years 1991 to 2002.\14\ 
The ``minimum'' (``maximum'') multifamily mix figure reflects the 
low (upper) end of the ``likely range'' of multifamily dollar 
originations, also reported in Table D.4. Because they will be 
compared with other estimates of the MF mix, these ``likely range'' 
data are reproduced in the first two columns of Table D.5b.
BILLING CODE 4210-27-P
---------------------------------------------------------------------------

    \14\ 1990 is excluded from this calculation because of the 
unusually high multifamily mix that year. Also, the estimated 
multifamily mix from the HUD New Method is also provided for 2002 
since it was greater than the estimate from the Flow of Funds 
method.

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[[Page 63832]]

    Table D.5b includes several averages of the MF mix for different 
time periods between 1991 and 2002. Based on the ``likely range'' of 
annual conventional multifamily origination volume, multifamily 
units have represented 15.3 percent (the average of the ``minimum'' 
figures) to 16.6 percent (the average of the ``maximum'' figures) of 
units financed each year between 1991 and 2002. Considering the mid-
points of the ``likely range'', the multifamily mix averaged 15.9 
percent during this period. Notice that the multifamily mix is lower 
during years of heavy refinancing when single-family originations 
dominate the mortgage market; the multifamily mix was only 13-14 
percent during 1993, 1998, and 2001, and 11 percent (or less) during 
2002.\15\ As discussed in Sections F-H, record single-family 
originations ($3.8 trillion) during 2003 likely resulted in that 
year having a lower multifamily mix than any of the years between 
1991 and 2002. Sensitivity analyses are conducted to show the 
effects of multifamily mixes less than the previous lows of 11 
percent in 1992 and 2002.
---------------------------------------------------------------------------

    \15\ The projection model for 2002 showed the following 
multifamily mixes for 2002: 11.1 percent for the HUD New multifamily 
estimate ($67.4 billion); 10.5 percent for the top end ($64 billion) 
of the Flow of Funds multifamily range ($60-64 billion), 10.3 
percent for the mid-point ($62 billion), and 9.9 percent for the low 
end ($60 billion). In Sections F-H, HUD will consider multifamily 
mixes as low as 9.5 percent for 2002.
---------------------------------------------------------------------------

    As discussed earlier, several commented that HUD had understated 
the UPB/unit, which caused HUD to overstate the share of newly-
mortgage multifamily dwelling units. Section C.5 explains that HUD's 
UPB/unit estimates for recent years are likely too low but that 
could be offset by low estimates of originations. To allow for 
different views about the volume of mortgage originations and the 
UPB/unit, Sections F-H will conduct sensitivity analyses with lower 
multifamily mixes than suggested by the mid-points of the likely 
ranges in Table D.5b. The third column of Table D.5b lists the 
``mid-point'' MF mixes while the fourth column of Table D.5b lists 
the lower MF mixes used in Sections F-H. Over the 1995-2002 period, 
the average MF mix ranged from 13.9 percent (the lower MF mix 
approach) to 16.2 percent (the mid-point MF mix approach).\16\ Over 
the more recent period, the averages have ranged from 12.6 percent 
to 14.5 percent for 1999-2002, from 15.1 percent to 17.5 percent for 
recent home purchase years, and from 11.2 percent to 12.9 percent 
for the refinance years of 1998, 2001, and 2002.
---------------------------------------------------------------------------

    \16\ For purposes of sensitivity analysis, the lower MF mixes 
were derived as follows: three percentage points were subtracted 
from the 1995-1997 mid-point MF mixes, which were in the high 18-to-
21-percent range; two percentage points were subtracted from the 
1998-2000 mid-point MF mixes, which were in the 14-to-17-percent 
range; and 1.5 percentage points were subtracted from the 2001-2002 
mid-point MF mixes, which were less than 13 percent.
---------------------------------------------------------------------------

    The impact of the lower MF mix on the UPB/unit assumption can be 
illustrated for the case of 2001, which assumed a loan-amount-per-
unit figure of $34,000. Reducing the MF mix from 13.5 percent to 
12.0 percent is consistent with increasing the UPB/unit from $34,000 
to $39,075 (holding constant mortgage originations at $67 billion). 
Of course, the lower MF mix of 12.0 percent is consistent with a 
lower volume of mortgage originations if the initial UPB/unit of 
$34,000 is retained.
    Fannie Mae (op.cit., page I-29) developed three sets of UPB-per-
unit figures for 1997 to 2002; below Fannie Mae's estimates are 
compared with the UPB-per-unit figures that result from HUD's model 
that uses the lower MF mixes.

----------------------------------------------------------------------------------------------------------------
                                                              Fannie Mae's Estimates              HUD's Lower MF
                                                 ------------------------------------------------       Mix
                                                                                                 ---------------
                                                       High             Low          Baseline          Model
----------------------------------------------------------------------------------------------------------------
1997............................................         $35,063         $28,488         $31,776         $33,582
1998............................................          40,155          32,626          36,390          37,492
1999............................................          42,430          33,992          38,211          36,260
2000............................................          45,797          37,210          41,504          38,142
2001............................................          48,363          39,295          43,829          39,075
2002............................................          53,507          43,474          48,491          44,009
Average.........................................          44,219          35,847          40,033          38,093
----------------------------------------------------------------------------------------------------------------

    Three points stand out. First, there is a rather large 
differential between Fannie Mae's Low and High UPB-per-unit figures, 
reflecting the lack of available data. Second, HUD's UPB-per-unit 
estimates based on its lower MF mix model are in between Fannie 
Mae's Low and Baseline estimates. Third, the differentials between 
HUD's and Fannie Mae's Baseline estimates are largest during the two 
heavy refinance years of 2001 and 2002.
    HUD's conducting its market share analysis with the lower MF 
mixes (as well as with the mid-point MF mixes) recognizes different 
views about the size of the mortgage market and the UPB/unit. This 
does not mean that the HUD's range of MF mixes includes estimates as 
low as those suggested by ICF (Freddie Mac's contractor) and Fannie 
Mae.
    ICF's estimates of multifamily shares for the 1994-2002 were 
lower than those that HUD used (as reported in Table D.5b). ICF's 
Best Estimates and Lower Bound Estimates were as follows:\17\
---------------------------------------------------------------------------

    \17\ HUD estimated ICF's MF mixes by including subprime loans in 
the data that ICF reported on pages 58-60 of its Appendix (for the 
Best Estimate) and on pages 63-65 of its Appendix (for the Lower 
Bound Estimate). To the extent that ICF also excluded other single-
family loans (in addition to subprime SF loans), the estimates 
reported in the text overstate ICF's initial MF mixes.

------------------------------------------------------------------------
                                                                Lower
                                                    Best        bound
                                                 estimates    estimates
                                                 (percent)    (percent)
------------------------------------------------------------------------
1994..........................................         17.2         14.0
1995..........................................         16.5         14.0
1996..........................................         13.7         11.5
1997..........................................         14.4         12.3
1998..........................................         11.3          9.9
1999..........................................         12.3         10.7
2000..........................................         13.8         11.7
2001..........................................         10.8          9.0
2002..........................................         10.2          8.5
------------------------------------------------------------------------

    Various averages of ICF's Best Estimates are calculated in Table 
D.4b. Over the 1995-2002 period, ICF's Best Estimates averaged 12.9 
percent, while HUD's mid-point estimates averaged 16.2 percent and 
HUD's lower MF mix estimates averaged 13.9 percent. Thus, the 
average of ICF's Best Estimates is slightly lower (one percentage 
point) than the average of HUD's lower MF mixes. Over the more 
recent 1999-2002 period, ICF's Best Estimates averaged 11.8 percent, 
while HUD's mid-point estimates averaged 14.5 percent and its lower 
MF mix estimates averaged 12.6 percent.
    ICF also produces lower bound estimates of the multifamily share 
of the market (see above list for 1994 to 2002). ICF's lower bound 
estimates for the multifamily mix averaged 11.3 percent between 1994 
and 2002. It is interesting that ICF's lower bound estimates are in 
some cases either similar or less than the multifamily shares of 
Fannie Mae's business. The multifamily share of Fannie Mae's 
business was 9.9 percent in 1999 (versus ICF's lower bound estimate 
for the market of 10.7 percent), 13.3 percent in 2000 (versus ICF's 
lower bound of 11.7 percent), and 10.9 percent in 2001 (versus ICF's 
lower bound market estimate of 9.0 percent). Even though these 
Fannie Mae data include both their seasoned and current-year 
purchases, it is surprising that ICF's market estimates would be 
similar or less than Fannie Mae's multifamily shares, given that 
Fannie Mae purchased practically no small (less-than-50-unit-
property) multifamily loans during this period.
    In its comments, Fannie Mae also provided various historical 
estimates of the MF mix

[[Page 63833]]

(see its Appendix I, pages I-29 and I-30). First, without giving the 
details of its analysis, Fannie Mae asserts that ``Fannie Mae's 
analysis shows an average multifamily share of 10.2 percent for the 
1997-2002 period, compared with HUD's 14 to 15 percent range'' (page 
I-30). Fannie Mae's estimate of 10.2-percent is below ICF's Best 
Estimate (12.1 percent), HUD's lower MF mix estimate (13.1 percent), 
and HUD's mid-point MF mix estimate (15.2 percent). (See Table 
D.5b.) Fannie Mae's estimate of 10.2 percent is practically the same 
as ICF's Lower Bound Estimate, which averaged 10.4 percent between 
1997 and 2002; of course, this raises the same issue mentioned above 
with respect to ICF's Lower Bound Estimates.
    Fannie Mae also provided various estimates of UPB per unit (see 
above) and applied its ``Low UPB per Unit Assumption'' and its 
``High UPB per Unit Assumption'' to HUD's likely range of MF 
mortgage originations (as reported in column 11 of Table D.4). For 
the period 1997-2002, Fannie Mae obtained: (A) a range of 12.7-13.8 
percent using its ``Low UPB per Unit Assumption'' and (B) a range of 
10.5-11.5 percent using its ``High UPB per Unit Assumption.'' (See 
Fannie Mae's Table I.6 on page I-30.) Fannie Mae's (A) results are 
similar to HUD's lower MF mix estimates, which averaged 13.1 percent 
over the 1997-2002 period; its (B) results are slightly higher than 
ICF's Lower Bound Estimates, which averaged 10.4 percent over the 
1997-2002 period.
    Finally, Fannie Mae notes that its baseline analysis shows that 
the multifamily share dropped to 5.6 percent in 2003 and that HUD's 
MF assumptions (e.g., 13.5 percent) clearly overstate typical 
multifamily shares and therefore the likely market opportunity for 
the GSEs (page I-30). HUD recognizes that the MF mix will be lower 
during heavy refinance years such as 2003, making it more difficult 
for the GSEs to achieve the housing goals; HUD's Advance Notice of 
Proposed Rulemaking (described in the Preamble) seeks proposals on 
how to treat heavy refinance years in the goals determination 
process. The range of MF mixes (13.5-15.0-16.0 percent) in HUD's 
projection model apply to a home purchase environment, not a heavy 
refinance environment.
    As discussed in Section C.8 below, HUD will continue to use a 15 
percent MF Mix as its baseline. In their comments on the proposed 
rule, both Fannie Mae and Freddie Mac expressed the view that HUD's 
15 percent baseline estimate of the multifamily share of the 
conventional mortgage market was too high. As described earlier in 
this section, those organizations argued that HUD's estimates of 
multifamily loan originations were too high, that HUD's estimates of 
multifamily UPB/unit were too low, and that these two errors 
together combined to produce an estimate multifamily market share 
that was one to four percentage points too high. A trade 
organization reached similar conclusions in their comments on the 
multifamily mix.
    The Department has carefully considered these comments and the 
analysis supporting them. But HUD's conclusion is that the 15.0-
percent baseline multifamily mix appropriately reflected the 
estimates and analysis appearing in the May 2004 Proposed Rule. The 
Department's responses to critiques of the individual components of 
the multifamily mix calculation appear earlier in this section. In 
addition, the Department's confidence that a 15 percent estimate for 
multifamily's share of conventionally financed is not too high is 
bolstered by data from the newly released 2001 Residential Finance 
Survey (RFS). As discussed in the next section, the RFS indicates a 
long-run market share for multifamily that is considerably higher 
than 15 percent. After presenting the RFS results, Section C.8 will 
return to the discussion of the baseline MF mix used in HUD's 
projection model.

7. Evidence on the Multifamily Mix from the 2001 Residential Finance 
Survey

    Subsequent to the Department issuing the proposed rule in May, 
2004, the Census Bureau released the 2001 Residential Finance Survey 
(RFS). The RFS provides new information on the size and composition 
of the residential mortgage market. As noted by Fannie Mae, Freddie 
Mac, and other organizations commenting on the draft rule, the RFS 
is an important and unique data source of data, because it is 
designed to provide comprehensive, nationally representative 
estimates on the volume and characteristics of single-family and 
multifamily mortgage loans and the properties they finance. Some 
organizations urged that the Rule not be finalized until data from 
the RFS has been analyzed.
    The RFS data suggest a mortgage market somewhat different in 
size and composition from that estimated by most analysts based on 
partial data. Beginning with multifamily lending, the multifamily 
mortgage market is considerably larger than most analysts have 
thought, according to the RFS. For example, the RFS estimate of 
total mortgage debt outstanding on properties with five of more 
housing units is $608 billion dollars. The only other comprehensive 
estimate comes from the Federal Reserve Board's ``Flow of Funds'' 
accounts, which draw on data from multiple sources and on judgments 
by the Fed staff. The Flow of Funds estimate of multifamily debt 
outstanding as of 2002Q2 (the quarter most comparable to reporting 
dates of RFS respondents) was only $457 billion. In other words, the 
RFS estimates a stock of multifamily mortgage debt 32 percent larger 
than Federal Reserve.
    As with debt outstanding, multifamily loan originations in the 
RFS exceed most other estimates. Over the period 1998-2001, annual 
originations averaged $66 billion according to the RFS, and 
conventional originations (total less FHA insured) averaged $61 
billion. HUD's estimates of conventional multifamily originations 
for these years, as summarized in Table D.2 of the proposed rule, 
averaged only $56 billion. In commenting on the proposed rule, 
Fannie Mae and Freddie Mac offered estimates of market size 
considerably below these.\18\
---------------------------------------------------------------------------

    \18\ The multifamily origination data in this paragraph reflect 
a recent release of the RFS; other single-family and multifamily 
data in this section draw from an earlier version of the RFS. HUD 
will continue its analysis of the RFS data as new versions are 
released by the Census Bureau.
---------------------------------------------------------------------------

    The single-family mortgage estimates from the 2001 RFS, like the 
multifamily estimates, are at odds with those from some other 
sources. For example, total mortgage debt on 1-to-4 family 
residences, according to the RFS, was $5.032 trillion, whereas the 
Flow of Funds estimate for 2002Q1 was a much higher $6.546 billion.
    In summary, the RFS estimates a somewhat smaller residential 
mortgage market than the Flow of Funds--19 percent smaller as 
measured by total debt outstanding. Furthermore, multifamily debt is 
a much larger part of the total residential market in the RFS than 
in the Flow of Funds.
    The RFS also records the number of housing units at each 
surveyed property, providing an opportunity to measure directly the 
number of housing units financed instead of relying on indirect 
methods. The RFS estimates indicate that, as with debt outstanding, 
the mix of mortgage lending by the measure of units financed is more 
heavily multifamily than previously thought. This is shown in Table 
D.5c, where units financed are presented for the loan origination 
years 2000 and 2001. These are the years for which the estimates are 
least likely to be biased by refinancing between the loan 
origination date and the survey. The estimates for 2001 are 
incomplete, because approximately 10 percent of the survey 
respondents reported as of dates prior to December 31, 2001 and 
loans subsequently originated on those properties would not be 
included. This undercount should affect single-family and 
multifamily reporting about proportionally, with little effect on 
the market share calculations.
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[[Page 63835]]

    By the housing goals' metric of number of conventionally 
financed, conforming housing units, the 2001 Residential Finance 
Survey indicates a multifamily market share substantially above the 
pre-RFS estimates of HUD and GSEs. As detailed in Table D.5b, the 
multifamily share estimated for 2001 is 0.197, or 19.7%, and the 
share for 2000 is a striking 0.254, or 25.4%. These high figures are 
particularly noteworthy because the year 2001 was marked by high 
levels of refinancings, which have been viewed as boosting single-
family lending proportionally more than multifamily. HUD's estimate 
of the multifamily share for 2000, for example, was only 13%-14%, as 
derived elsewhere in this rule.
    There are several reasons for accepting the RFS estimates as an 
accurate portrayal of the residential mortgage market. First, the 
estimates are generated from a national representative sample of 
properties as drawn by experts at the U.S. Census Bureau. Second, 
the survey forms were designed in consultation with industry 
experts. Third, participation in the survey was mandatory, because 
it was conducted in conjunction with the 2000 Census. And fourth, 
data processing and editing at the Census Bureau prior to public 
release of census and survey results is meticulous.
    Nonetheless, for the specific reasons noted, results from the 
RFS should be interpreted cautiously. First, loan originations for 
any year will be understated, because the RFS will record only those 
loans still outstanding as of the late 2001 or early 2002 survey 
date. Loans originated in, for example, 1998, will be recorded only 
if those loans have not been refinanced, repaid, or charged off 
prior to the RFS survey date. For this reason, the RFS unit count 
and especially the market share estimates for 2001 are more reliable 
than those for 2000 and earlier years. Second, some of the results 
of the RFS are substantially at odds with other evidence and 
industry perceptions, as noted already. Another example of a 
surprising RFS finding is the time path of multifamily loan 
originations. According to the RFS, originations were roughly 50 
percent greater in 1998-1999 than in 2000-2001, whereas most other 
evidence points to originations in 2000-2001 that at least equaled, 
and likely exceeded, the volume of 1998-1999.
    Lastly, in response to user feedback and its own data checks, 
the Census Bureau has revised the RFS estimates three times since 
the initial data release in early July 2004. The possibility remains 
that additional errors will be found and that the resulting 
revisions to the data will significantly change the RFS portrayal of 
the multifamily mortgage market. HUD will continue its analysis of 
the RFS as new versions are released.
    On balance, the Department views the RFS as providing strong 
additional evidence that the Department's baseline multifamily mix 
percentage of 15% is not an overestimate. The RFS data, weighed 
alone, would have that percentage set much higher.

8. Multifamily Mix in HUD's Model--Further Discussion

    As noted above, the ``multifamily mix'' is the number of 
multifamily units financed each year as a percentage share of the 
total (both single-family and multifamily) number of dwelling units 
financed each year. Because of the high goals-qualifying shares of 
multifamily housing, the multifamily mix is an important parameter 
in HUD's projection model for the overall market; other things 
equal, a higher multifamily mix (or conversely, a lower share of 
single-family loans) leads to a higher estimate of goals-qualifying 
loans in the overall mortgage market.
    The multifamily share of the conforming conventional market (or 
``multifamily mix'') is utilized below as part of HUD's analysis of 
the share of units financed each year meeting each of the housing 
goals. The proposed rule considered multifamily mixes of 13.5 
percent, 15.0 percent, and 16.5 percent, as well as even lower 
multifamily mixes for heavy refinance environments such as 2001-03. 
The 15.0 percent level was considered as the baseline based on 
analysis of multifamily shares during home purchase environments of 
the 1990s. In the market sections below, HUD continues to focus on 
the baseline 15.0 percent but also considers a range of estimates, 
including those provided by commenters on the proposed rule. 
Comments by Fannie Mae and ICF are summarized below.
    In its projection model, Fannie Mae uses a multifamily mix of 
12.3 percent (see Table 1.6 on page 11). As noted in Section C.6 
above, Fannie Mae estimated an average multifamily mix of only 10.2 
percent over the 1997-2002 period. Fannie Mae notes that HUD's 13.5-
16.5 range is ``well above the range of estimates suggested by an 
examination of all available data and is inconsistent with the 
current weak fundamentals in the multifamily market.'' (Fannie Mae, 
p. 15) Fannie Mae's views about the future mortgage market were 
discussed on pages I-14 to I-17 in its Appendix I (``Comments on 
HUD's Analysis of the Statutory Factors'') to its comments. As 
discussed earlier, Fannie Mae's somewhat pessimistic views about the 
future market were driven by the current high vacancy rates for 
multifamily properties and the fact that the high-renter age group 
(the so-called ``echo boom'' aged 20-34) will not begin to increase 
until after 2007. Fannie Mae also emphasized that the recent spike 
in multifamily originations (beginning in 2001) means that a large 
portion of today's holders of multifamily mortgages have already 
refinanced and therefore will have only limited ability and 
incentive to refinance over the next several years, due to yield 
maintenance provisions on their existing multifamily mortgages. 
According to Fannie Mae, these loans will not begin to exit their 
yield maintenance periods until sometime between 2008 and 2010, with 
the result being that the 2005-2008 period appears to have 
relatively limited prospects for multifamily refinancing. Fannie Mae 
notes that single-family lending is not subject to these constraints 
and is more likely to undergo modest refinance waves as a result of 
interest rate fluctuations. Based on its analysis, Fannie Mae 
concludes that a multifamily share of 12.3 percent is ``consistent 
with reasonable estimates'' of the multifamily market (Fannie Mae 
Appendix, Table I.15, p. I-42).
    Based on its analysis of the multifamily market, ICF, Freddie 
Mac's contractor, offered higher projections of the MF mix. 
Specifically, ICF provided the following estimates of the 
multifamily mix during the projection period, 2005-08, as follows:

------------------------------------------------------------------------
                                                            ICF MF Mix
                                                             (percent)
------------------------------------------------------------------------
2005....................................................            13.7
2006....................................................            14.5
2007....................................................            14.7
2008....................................................            13.9
average.................................................            14.2
------------------------------------------------------------------------

    Thus, ICF's 14.2-percent average estimate is a little less than 
HUD's baseline (15.0 percent), standing at the mid-point of HUD's 
13.5 and 15.0 figures. For a discussion of ICF's methodology for 
estimating the multifamily mix, and their actual use of their 
estimated multifamily mixes in projecting overall market estimates 
for the three housing goal categories, see pages 126-140 of their 
technical appendix, entitled ``Analysis of the Proportion of the 
Mortgage Market that Meets the GSEs'' Affordable Housing Goals: 
Issues of Variability and Uncertainty: Technical Appendix'' (July 
15, 2004). According to ICF, they projected the number of 
multifamily (MF) units based on the existing number of units likely 
to be refinanced (rollover) and the expected number of MF units that 
would be added to the housing stock (new completions). The amount of 
rollover was estimated as the average of the number of units 
financed 8, 9, and 10 years ago. ICF used these time periods because 
10-year balloon mortgages are the most common MF mortgages, and MF 
loans typically include a yield maintenance period to limit 
prepayments.\19\ In their basic report, they state that they view 
the above estimates from their MF projection model as ``our core, or 
our most likely forecast for 2005 through 2008'' (ICF Report, p. 
40). While they state that ``our [ICF] multifamily projections for 
2005 through 2008 have a sound empirical basis owing to the nature 
of multifamily mortgages and new multifamily construction,'' ICF 
also reminds readers of the uncertainty of its MF projections when 
it states ``while we believe the core range is the best and most 
likely estimate of the future market, we [ICF] recognize that it is 
possible that the actual outcomes may be outside this range, either 
higher or lower'' (ICF Report, p. 40). The ICF basic report is 
entitled ``Analysis of the Proportion of the Mortgage Market that 
Meets the GSEs'' Affordable Housing Goals: Issues of Variability and 
Uncertainty: Technical Appendix'' (July 15, 2004). Because the basic 
report and the appendix are paginated differently, they will be 
referenced separately--ICF's basic report will be referred to as the 
``ICF Report'', while their appendix will be referred to as the 
``ICF Appendix''.
---------------------------------------------------------------------------

    \19\ Estimates of new MF units were created by comparing the 
historical estimates of numbers of units added by HUD and REIS, 
creating a ratio, and then applying that ratio to the REIS' future 
projections.
---------------------------------------------------------------------------

    As discussed earlier, the 2001 RFS provides higher estimates of 
the MF mix for

[[Page 63836]]

1999-2001 than either Fannie Mae or ICF. The RFS data suggest that 
15.0 percent is a reasonable baseline, particularly for a home 
purchase environment. Thus, the market analysis of the housing goals 
in Sections F-H will continue to use 15.0 percent as the baseline MF 
mix. To reflect the uncertainty with the MF data, market projections 
will also be provided for alternative MF mixes of 12.25 percent 
(approximating Fannie Mae's projection of 12.3 percent), 13.5 
percent (the low-end projection for a home purchase environment used 
in HUD's 2004 proposed rule), 14.25 percent (approximating the 12.2 
percent average of ICF's best projections of MF mixes between 2005 
and 2008), and 16.0 percent (a half percentage point below the high-
end projection for a home purchase environment used in HUD's 2004 
proposed rule). Based on ICF's best projection and HUD's analysis of 
the 2001 RFS, the bottom end of the range probably should not go 
below 13.5 percent for a home purchase environment. However, results 
are provided for the 12.25 percent in order to show the sensitivity 
of the market sizing to the assumption made by Fannie Mae in its 
analysis. Of course, it is recognized that the multifamily mix will 
be significantly lower during heavy refinancing periods such as 
2001-2003. Therefore, additional sensitivity analyses will be 
conducted to show the effects of even lower multifamily mixes. But 
as explained in the Preamble of this Final Rule, in its goals 
scoring, HUD will reduce refinance loans so they account for not 
more than 40 percent of combined home purchase and refinance loans. 
This addresses the problem of a low MF mix during a heavy 
refinancing period reducing the ability of the GSEs to meet the new 
goal targets.

D. Single-Family Owner and Rental Mortgage Market Shares

1. Available Data on Investor Share

    As explained later, HUD's market model will also use projections 
of mortgage originations on single-family (1-4 unit) properties. 
Current mortgage origination data combine mortgage originations for 
the three different types of single-family properties: Owner-
occupied, one-unit properties (SF-O); 2-4 unit rental properties (SF 
2-4); and 1-4 unit rental properties owned by investors (SF-
Investor). The fact that the goal percentages are much higher for 
the two rental categories argues strongly for disaggregating single-
family mortgage originations by property type. This section 
discusses available data for estimating the relative size of the 
single-family rental mortgage market.
    The Residential Finance Survey (RFS) and HMDA are the data 
sources for estimating the relative size of the single-family rental 
market. The 2001 RFS provides mortgage origination estimates for 
each of the three single-family property types, as it includes 
mortgages originated during 2001, as well as surviving mortgages 
that were originated in earlier years such as 1999 and 2000. HMDA 
divides newly-originated single-family mortgages into two property 
types:\20\
---------------------------------------------------------------------------

    \20\ The HMDA data reported in this section ignore HMDA loans 
with ``non-applicable'' for owner type.
---------------------------------------------------------------------------

    (1) Owner-occupied originations, which include both SF-O and SF 
2-4.
    (2) Non-owner-occupied mortgage originations, which include SF 
Investor.
    The percentage distributions of single-family mortgages from 
HMDA and the 2001 RFS are provided in Table D.6a and D.6b. HMDA data 
will be discussed first. Because HMDA combines the first two 
categories (SF-O and SF 2-4), the comparisons between the data bases 
must necessarily focus on the SF investor category. The following 
points stand out from Table D.6.a:
     The investor share of all single-family loans has 
ranged from 5.7 percent (1993) to 9.1 percent (2000), with an 
average of 7.8 percent. Over the more recent 1999-2003 period, the 
investor share has averaged 8.3 percent.
     The investor share is much higher for home purchase 
loans than for refinance loans. The investor share of home purchase 
loans averaged 9.6 percent between 1993 and 2003, as compared with a 
6.8 percent average for refinance loans.
     The investor share for home purchase loans recently 
increased, rising from slightly above 9.0 percent during 1999 to 
around 10.0 percent during 2000-2001 to 12.0-13.0 percent during 
2002 and 2003. The average investor share for home purchase loans 
was 11.2 percent between 1999 and 2003.
     In its comments, Fannie Mae noted that HUD should 
deduct subprime loans from investor loans. As shown in the middle 
portion of Table D.6a, deducting investor subprime loans reduces the 
overall investor share by approximately one-half percentage point 
(e.g., 1999-2003 average is reduced from 8.3 percent to 7.7 
percent).\21\
---------------------------------------------------------------------------

    \21\ These data without subprime loans are presented merely to 
provide a sense of the likely changes if one excludes subprime 
investor loans. Three comments should be made about them. First, 
HUD's procedure is to drop one-half of subprime loans as a proxy for 
B&C loans, which one reduce the one-half percentage point 
differential mentioned in the text to a one-quarter point percentage 
differential. Second, the comparisions in Table D.6a do not deduct 
single-family owner subrpime loans; doing that would raise the 
investor shares from those in middle portion of the table. Third, 
HUD's model starts with investor and owner property shares that 
include subprime loans (such as those in the top portion of Table 
D.6a) and then excludes the subprime loans as part of the 
derivations within the model. See Section F for an explanation of 
this procedure.
---------------------------------------------------------------------------

     HMDA data for metropolitan areas (bottom portion of 
Table D.6.a) show a slightly lower investor share than HMDA data for 
both metropolitan and non-metropolitan areas (top portion of Table 
D.6a). Between 1993 and 2003, the investor share in metropolitan 
areas averaged 7.5 percent, as compared with 7.8 percent for the 
U.S. as a whole. During the more recent 1999-2003 period, the 
differential was slightly higher, 7.8 percent versus 8.3 percent.
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[[Page 63839]]


    Table D.6b provides information on investor loans from the 2001 
RFS. During 2001, investors accounted for 13.4 percent of all new 
single-family mortgages. Similar to the pattern in HMDA, the RFS-
reported investor share of home purchase loans (15.7 percent) was 
higher than the investor share (9.0 percent) of refinance loans (see 
Table D.6b). The RFS-based investor shares were similar for single-
family mortgages originated in earlier years that had also survived 
(i.e., not prepaid) until the time of the RFS survey in 2001; for 
example, the investor share was 13.0 percent for surviving 1999 
mortgages and 14.0 percent for surviving year 2000 mortgages.
    For comparison purposes, Table D.6c provides investor shares of 
the single-family mortgages purchased by the GSEs. Between 1999 and 
2003, the investor share of Fannie Mae's single-family mortgage 
purchases ranged from 4.2 percent (1999) to 7.8 percent (2000). 
Freddie Mac's investor share has been lower, ranging from 3.0 
percent (2003) to 4.8 percent (2000). The low figure for 2003 was 
due to the heavy refinancing of owner loans in that year.

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[[Page 63841]]

    The RFS investor share of 13.4 percent in 2001 is substantially 
larger than the corresponding HMDA investor share of 7.8 percent. In 
their comments on the 2004 proposed rule, as well as in their 
comments on HUD's earlier 1995 and 2000 GSE rules, the GSEs have 
argued that HUD should use the HMDA-reported SF investor share. In 
its 1995 and 2000 rules and the 2004 proposed GSE rule, HUD's 
baseline model assumed a 10 percent share for the SF investor 
group--only slightly higher than the HMDA-based estimates; 
alternative models assuming 8 percent and 12 percent were also 
considered. At that time, HUD argued that its baseline projection of 
10 percent was probably quite conservative; however, given the 
uncertainty around the data, it was difficult to draw firm 
conclusions about the size of the single-family investor market, 
which necessitated that HUD conduct sensitivity analyses using 
investor shares (e.g., 8 percent) less than 10 percent. HUD's 
argument that its 10 percent baseline work was probably conservative 
was based on earlier work by Blackley and Follain. It is interesting 
to briefly review their work because they focused on the differences 
between RFS and HMDA data.

2. Blackley and Follain Analysis of Investor Market Share

    As mentioned, during the 1995 rule-making, HUD asked the Urban 
Institute to analyze the differences between the RFS and HMDA 
investor shares and determine which was the more reasonable. The 
Urban Institute's analysis of this issue is contained in reports by 
Dixie Blackley and James Follain.\22\ Blackley and Follain provide 
reasons why HMDA should be adjusted upward as well as reasons why 
the RFS should be adjusted downward. They find that HMDA may 
understate the investor share of single-family mortgages because of 
``hidden investors'' who falsely claim that a property is owner-
occupied in order to more easily obtain mortgage financing. RFS may 
overstate the investor share of the market because units that are 
temporarily rented while the owner seeks another buyer may be 
counted as rental units in the RFS, even though rental status of 
such units may only be temporary. The RFS's investor share should be 
adjusted downward in part because the RFS assigns all vacant 
properties to the rental group, but some of these are likely 
intended for the owner market, especially among one-unit properties. 
Blackley and Follain's analysis of this issue suggests lowering the 
investor share from the 1991 RFS-reported investor share of 17.3 
percent to about 14-15 percent.
---------------------------------------------------------------------------

    \22\ Dixie M. Blackley and James R. Follain, ``A Critique of the 
Methodology Used to Determine Affordable Housing Goals for the 
Government Sponsored Housing Enterprises,'' report prepared for 
Office of Policy Development and Research, Department of Housing and 
Urban Development, October 1995; and ``HUD's Market Share 
Methodology and its Housing Goals for the Government Sponsored 
Enterprises,'' unpublished paper, March 1996.
---------------------------------------------------------------------------

    Finally, Blackley and Follain note that a conservative estimate 
of the SF investor share is advisable because of the difficulty of 
measuring the magnitudes of the various effects that they analyzed. 
In their 1996 paper, they conclude that 12 percent is a reasonable 
estimate of the investor share of single-family mortgage 
originations.\23\ Blackley and Follain caution that uncertainty 
exists around this estimate because of inadequate data.
---------------------------------------------------------------------------

    \23\ Blackley and Follain (1996), p. 20.
---------------------------------------------------------------------------

3. GSE Comments on SF Rental Shares in the Proposed Rule

    Fannie Mae, Freddie Mac, and ICF thought that the investor share 
should be lower than the 10 percent used by HUD. While they agreed 
with HUD that the RFS provided the most accurate estimate of the 
true investor share of the market, they emphasized that lender 
reporting of investor loans to the GSEs was best proxied by HMDA 
data (which, of course, are based on lender reports). That is, the 
actual opportunities available to the GSEs in the SF investor market 
are best measured by data that lenders report based on information 
from actual loan applications. Based on this argument, they 
concluded that HUD's market sizing analysis should rely on HMDA 
data, not RFS data.
    For example, Fannie Mae argued that the most valid measure of 
the single-family rental market is the same measure (lender-reported 
data to HMDA) against which the GSEs' performance is measured. 
Fannie Mae points out that that two (10 percent and 12 percent) of 
the three scenarios that HUD uses exceed the highest investor share 
ever reported in HMDA. Fannie rejects HUD's justification (the 1991 
RFS and the Blackley-Follain analysis) for using the higher 
scenarios because the lender reporting to the GSEs is closer to HMDA 
data than to the reporting in the RFS. Fannie Mae argues that the 
1995 Blackley and Follain analysis bolsters its case against the RFS 
measures. Fannie Mae notes that both HUD and Blackley and Follain 
conclude that there is a reporting bias in the HMDA data that is not 
present in the RFS. The bias is in part due to hidden investors. At 
the time of origination, the property may be owner-occupied or may 
be intended to be owner-occupied. In fact, the property may become 
rental shortly after origination. As a result, the RFS reports a 
more accurate higher percentage of rental housing because it is a 
snapshot of housing, not a collection of information at mortgage 
origination. Fannie Mae says HUD uses the RFS because it is the more 
accurate measure of the rental market at any moment in time. 
However, Fannie Mae argues that the same bias in HMDA also exists in 
its own reporting when it acquires mortgages. According to Fannie 
Mae, an apples to apples comparison would make sure that the GSE 
goals contain the same biases that the GSE reports contain, rather 
than no bias. Finally, Fannie says that even HMDA overstates the 
investor share of the single-family market because of second homes. 
Second homes are reported in HMDA as ``not owner occupied'' to 
determine investor status but are not goals eligible. Therefore, 
according to Fannie Mae, HUD's use of HMDA would overestimate the 
goals-eligible share of the single-family market. As a result of 
these data and methodology issues, Fannie believes HUD miscalculates 
the mix of units in the rental market and overstates the size of the 
goals-eligible portion of the rental market.
    Similarly, Freddie Mac concluded that HUD overestimated the SF 
investor share of the market because it relied on the RFS rather 
than HMDA. Freddie Mac says investor-owners have an incentive to 
claim falsely they are owner-occupants because of higher 
underwriting standards and higher interest rates on investor-owner 
properties. According to Freddie Mac, these incentives likely result 
in HMDA's undercounting SF investor loans relative to the more 
accurate counts of investor loans from the RFS. Freddie Mac 
concludes as follows:
    This undercounting [on the part of HMDA], however, is exactly 
what is desired when estimating the goal share available to the 
GSEs. Because the GSEs' information on their loans has the same 
``bias'' as does the HMDA data. * * * The HMDA data, therefore, are 
more appropriate to estimating the market for goal setting than are 
the RFS data. (p.II-6)
    Essentially, Freddie Mac concludes that HUD's market estimates 
should measure opportunities in the marketplace that are actually 
available to the GSEs. Such opportunities are best measured by 
lender-reported HMDA data, not the more accurate RFS data. ICF 
reaches a similar conclusion, as it states that ``HMDA data, or its 
equivalent, are what the GSEs' performance will be measured against 
and is therefore the appropriate metric for estimating market goal 
shares'' (ICF Report, p.20).

4. SF Investor Shares in the Final Rule

    In this final Rule, HUD has switched to a HMDA-based system and 
provides overall market share estimates for a range of single-family 
investor shares. For each year between 1993 and 2003, the top-right-
hand-side portion of Table D.6a shows the projected investor share 
in a ``home purchase environment'' assuming a refinance share of 35 
percent, 40 percent, and 45 percent. Refinance shares greater than 
35 percent are included here because single-family investor loans 
typically have higher refinance shares than single-family-owner 
loans. As shown in Table D.6a, the average 1993-2003, HMDA-based 
investor share would have been 8.5 (8.4) percent if the investor 
refinance share had been 40 (45) percent during this period. During 
the more recent 1999-2003 period, which was characterized by 
particularly high HMDA-reported investor shares for home purchase 
loans, the average investor share would have been 9.4 (9.2) percent 
if the investor refinance share had been 40 (45) percent during this 
period. As noted earlier, the HMDA-reported investor shares for 
metropolitan areas are slightly lower than those for the entire U.S. 
As shown in the bottom-right-hand portion of Table D.6a, the average 
1999-2003, HMDA-based investor share for metropolitan areas would 
have been 8.9 (8.7) percent if the investor refinance share had been 
40 (45) percent during this period.
    The above analysis suggests that the HMDA-reported investor 
share of a future home purchase market will probably be around 8.5-
9.0 percent, or possibly higher if the recent figures for home 
purchase loans hold up (in this case, around 9.5 percent).

[[Page 63842]]

Thus, HUD's analysis of market shares in Sections F-H will report 
overall market estimates for a range of SF investor shares--8.0 
percent, 8.5 percent, 9.0 percent, and 10.5 percent.

5. Single-Family Market in Terms of Unit Shares

    The market share estimates for the housing goals need to be 
expressed as percentages of units rather than as percentages of 
mortgages. Since a SF 2-4 and a SF-investor mortgage finances more 
than one dwelling unit, adjustments reflecting units-per-mortgage 
have to be made in order to arrive at the distribution of newly-
financed single-family dwelling units. From HMDA, one can obtain the 
share of investor mortgages (those reported in Table D.6a) and the 
share of owner mortgages (obtained by subtracting the share of 
investor mortgages from 100 percent). HMDA does not disaggregate the 
SF-owner (SF-O) mortgage category into its two components: SF-O 1-
Unit mortgages and SF-O 2-4 mortgages. To arrive at shares of SF 
financed dwelling units, two sets of adjustments have to be made to 
the HMDA data.
    First, the owner-occupied HMDA data have to be disaggregated 
between SF-O 1-Unit and SF 2-4 mortgages. HUD's 2004 proposed GSE 
rule assumed that SF 2-4 mortgages accounted for 2.0 percent of all 
single-family mortgages. Based on the 2001 RFS data, this percentage 
is reduced to about 1.6 percent in this Final Rule. In 2001, the RFS 
shows the following distribution across the three single-family 
mortgage types: (a) 85.1 percent for SF-O 1-Unit mortgages; (b) 1.5 
percent for SF-O 2-4 mortgages; and (c) 13.4 percent for SF-Investor 
mortgages (see Table D.6b). Thus, according to 2001 RFS data, SF 2-4 
mortgages represent 1.73 percent of all single-family-owner 
mortgages (obtained by dividing (b) by the sum of (a) and (b)). In 
the market projection models, the SF-investor mortgage share is 
assumed to be lower than the RFS-reported figure of 13.4 percent. If 
the SF-investor share is 8.5 percent, then the SF-O share is 91.5 
percent, which is split as follows: 1.58 percent for SF-O 2-4 
mortgages (obtained by multiplying 0.0173 by 91.5 percent) and 89.92 
percent for SF-O 1-Unit mortgages (obtained by subtracting 1.58 
percent for the overall SF-O share of 91.5 percent). Thus, in this 
scenario, the distribution across SF mortgage types would be as 
follows: (d) 89.92 percent for SF-O 1-Unit mortgages; (b) 1.58 
percent for SF-O 2-4 mortgages; and (c) 8.50 percent for SF-Investor 
mortgages. Table D.6d shows the distribution of SF mortgages under 
the various assumptions assumed in Sections F-H. For comparison 
purposes, the SF-O 2-4 shares for the GSEs are reported in Table 
D.6c. The 1999 to 2003 shares for Fannie Mae are approximately 2.0 
percent while those for Freddie Mac are approximately 1.5 percent. 
Thus, the Fannie Mae shares are consistent with the 2.0 percent 
assumption used in the 2004 proposed rule while the Freddie Mac 
shares are consistent with the 1.6 percent assumption used in this 
Final Rule. Sensitivity analyses in Sections F-G will show the 
effects of using the 2.0 percent assumption (as compared with the 
1.6 percent baseline).
BILLING CODE 4210-27-P

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[[Page 63844]]


    Second, the resulting mortgage-based distributions have to be 
shifted to unit-based distributions by applying the unit-per-
mortgage assumptions. The 2004 proposed GSE rule assumed the 
following: 2.25 units per SF 2-4 property and 1.35 units per SF 
investor property. Based on RFS data, these numbers are reduced 
slightly to the following: 2.2 units per SF 2-4 property and 1.3 
units per SF investor property. These figures are based on 1999-2001 
averages from the RFS. The corresponding 2001 figures from the RFS 
were 2.1 and 1.4, respectively. As shown in Table D.6d, the GSE data 
has consistently been around the figures in the 2004 proposed GSE 
rule, which were 2.25 and 1.35, respectively. Thus, it was decided 
to use the 1999-01 RFS averages which drop each units-per-mortgage 
figure by 0.05. Sensitivity analysis shows that this issue (whether 
to use the 1999-01 combination of 2.2/1.3 or to use the 2001 
combination of 2.1/1.4) has little impact on the market sizing 
results.
    Based on these calculations, the percentage distribution of 
newly-mortgaged single-family dwelling units was derived for each of 
the various estimates of the investor share of single-family 
mortgages. The results are presented in Table D.6e for investor 
percentage shares of 8.0, 8.5, 9.0, and 9.5. Three points should be 
made about these data.

[[Page 63845]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.087


[[Page 63846]]


    First, notice that the rental categories represent a larger 
share of the unit-based market than they did of the mortgage-based 
market reported earlier. For example, when the SF-investor category 
represents 8.5 percent of all SF mortgages, it represents 10.6 
percent of all SF units financed. This, of course, follows directly 
from applying the loan-per-unit expansion factors.
    Second, notice that the ``All SF-Rental Units'' column 
highlights the share of the single-family mortgage market accounted 
for by all single-family rental units, for both SF-O 2-4 properties 
and SF-Investor properties. For example, when the investor mortgage 
share is 8.5 percent, single-family rental units (in SF 2-4 
properties as well as in SF investor properties) account for 12.4 
percent of all newly-mortgaged SF units. This single-family rental 
share compares with 15.1 percent under the baseline assumptions of 
the 2004 proposed GSE Rule; the 15.1 percent figure is reported in 
Table D.6b of the 2004 proposed GSE rule. If the single-family 
investor share is 9.0 (9.5) percent, then single-family rental units 
account for account for 13.0 (13.6) percent of all newly-mortgaged 
SF units.
    ICF projected that SF rental units would account for 12.0 
percent of all single-family-financed units during the 2005-2008 
projection period (ICF Appendix, p.126). Under the units-per-
mortgage and SF-O 2-4 share assumptions that ICF was using (2.25 for 
SF-O 2-4 and 1.35 for SF-Investor and a 2.0 percent share for SF-O 
2-4 mortgages), ICF's 12-percent assumption for single-family rental 
units translates back to an investor mortgage share of 7.5 
percent.\24\
---------------------------------------------------------------------------

    \24\ It should be mentioned that ICF's 12.0 percent assumption 
for the SF rental share seems at odds with ICF's Exhibit 6.4, which 
suggests that ICF's 1994-2002 average SF rental share is 14.9 
percent. A 14.9 percent SF rental share would be consistent with a 
12 percent investor mortgage share.
---------------------------------------------------------------------------

    In its projections, Fannie Mae assumes 8.0 percent for the 
investor share of mortgages, a figure Fannie Mae says is consistent 
with HMDA data (Fannie Mae Appendix I, Table 1.11, p. I-38). Under 
the 2001 RFS assumptions (see above), this translates into a single-
family rental share (on a units basis) of 11.8 percent. Under the 
units-per-loan and SF-O 2-4 assumptions of the proposed rule, this 
translates into a single-family rental share (expressed on a units 
basis) of 12.7 percent.
    Third, if the investor mortgage share were 13 percent (the 2001 
figure from the RFS), single-family rental units would account for 
over 17 percent of all newly-mortgaged single-family units.
    The unit distributions reported for the GSEs in Table D.6f will 
be discussed in the next section.

[[Page 63847]]

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BILLING CODE 4210-27-C

[[Page 63848]]

E. HUD's Market Share Model

    This section integrates findings from the previous two sections 
about the size of the multifamily mortgage market and the relative 
distribution of single-family owner and rental mortgages into a 
single model of the mortgage market. The section provides the basic 
equations for HUD's market share model and identifies the remaining 
parameters that must be estimated.
    The output of this section is a unit-based distribution for the 
four property types discussed in Section B.\25\ Sections F-H will 
apply goal percentages to this property distribution in order to 
determine the size of the mortgage market for each of the three 
housing goals.
---------------------------------------------------------------------------

    \25\ The property distribution reported in Table D.1 is an 
example of the output of the market share model. Thus, this section 
completes Step 1 of the three-step procedure outlined above in 
Section B.
---------------------------------------------------------------------------

1. Basic Equations for Determining Units Financed in the Mortgage 
Market

    The model first estimates the number of dwelling units financed 
by conventional conforming mortgage originations for each of the 
four property types. It then determines each property type's share 
of the total number of dwelling units financed.

a. Single-Family Units

    This section estimates the number of single-family units that 
will be financed in the conventional conforming market, where 
single-family units (SF-UNITS) are defined as:

SF-UNITS = SF-O + SF 2-4 + SF-INVESTOR

    First, the dollar volume of conventional conforming single-
family mortgages (CCSFM$) is derived as follows:

(1) CCSFM$ = CONV% * CONF% * SFORIG$
where

CONV% = conventional mortgage originations as a percent of total 
mortgage originations; estimated to be 88%.\26\
---------------------------------------------------------------------------

    \26\ According to estimates by the Mortgage Bankers Association 
of America (MBAA), the conventional share of the 1-4 family market 
was between 86 and 88 percent of the market from 1993 to 1999, with 
a one-time low of 81 percent in 1994. Calculated from ``1-4 Family 
Mortgage Originations'' tables (Table 1--Industry and Table 2--
Conventional Loans) from ``MBAA Mortgage and Market Data,'' at 
www.MBAAa.org/marketkdata/ as of July 13, 2000. More recent 
unpublished estimates by MBAA are slightly higher. As discussed in 
the text, the market sizing shares are affected by parameters other 
than this one, such as the multifamily share of newly-mortgaged 
dwelling units.
---------------------------------------------------------------------------

CONF% = conforming mortgage originations (measured in dollars) as a 
percent of conventional single-family originations; forecasted to be 
80% by industry.
SFORIG$ = dollar volume of single-family one-to-four unit mortgages; 
$1,700 billion is used here as a starting assumption to reflect 
market conditions during the years 2005-2008.\27\ While alternative 
assumptions will be examined, it must be emphasized that the 
important concept for deriving the goal-qualifying market shares is 
the relative importance of single-family versus multifamily mortgage 
originations (the ``multifamily mix'' discussed in Section C) rather 
than the total dollar volume of single-family originations 
considered in isolation.

    \27\ In its August 17, 2004 forecast, Fannie Mae projected 
approximately $1.6 billion for 2005 and 2006 while the MBAA 
projected $1.8 billion for 2005 in its August 13, 2004 forecast. As 
discussed later, single-family originations could differ from $1,700 
billion during the 2005-2008 period that the goals will be in 
effect. As recent experience shows, market projections often change. 
For example, in January 2003, the MBAA projected $1,246 billion for 
2003; of course, actual 2003 mortgage originations were triple the 
latter amount. (See http://www.MBAAa.org/marketdata/forecasts for 
January 2003 Mortgage Finance Forecasts.) While Sections F-H will 
report the effects on the market estimates of alternative estimates 
of single-family mortgage originations, it should be emphasized that 
the important parameter for the market sizing estimates is the share 
of single-family-owner units relative to the share of single-family 
and multifamily rental units, not the absolute level of single-
family originations.
---------------------------------------------------------------------------

    Substituting these values into (1) yields an estimate for the 
conventional conforming market (CCSFM$) of $1,197 billion.
    Second, the number of conventional conforming single-family 
mortgages (CCSFM) is derived as follows:

(2) CCSFM = (CCSFM$ * (1-REFI)/PSFLOAN$) + (CCSFM$ * REFI)/
RSFLOAN$)
where
REFI= the refinance rate, assumed to be 35 percent for the 
baseline.\28\
---------------------------------------------------------------------------

    \28\ The model requires an estimated refinance rate because 
purchase and refinance loans can have different shares of goals-
qualifying units. In 2003, the refinance rate was almost 70 percent. 
In its August 13, 2004 forecast, the MBAA projects 25 percent for 
2005, as did Fannie Mae in its August 17, 2004 forecast. The 
baseline model uses a higher refinance rate of 35 percent because 
conforming conventional loans tend to refinance at a higher rate 
than the overall market. Sensitivity analyses for alternative 
refinance rates are presented in Sections F-H.
---------------------------------------------------------------------------

PSFLOAN$ = the average conventional conforming purchase mortgage 
amount for single-family properties; estimated to be $146,000.\29\
---------------------------------------------------------------------------

    \29\ The average 2002 purchase loan amount is estimated at 
$135,060 for owner occupied units using 2002 HMDA average loan 
amounts for single-family home purchase loans in metropolitan areas. 
A small adjustment is made to this figure to account for a small 
number of two-to-four and investor properties (see Section D above). 
This produces an average purchase loan size of $133,458 for 2002 
which is then inflated 3 percent a year for three years and then 
rounded to arrive at an estimated $146,000 average loan size for 
home purchase loans in 2005.
---------------------------------------------------------------------------

RSFLOAN$ = the average conventional conforming refinance mortgage 
amount for single-family properties; estimated to be $131,000.\30\

    \30\ The average refinance loan amount is estimated by averaging 
the relationship between HMDA average purchase and refinance loan 
amounts for 1999 and 2000, which were non-refinance environments. 
Applying this average of 90 percent (refinance loan amount/purchase 
loan amount) to the $146,000 average loan amount for purchase loans 
gives a rounded estimate of $131,000 for average refinance loan 
amounts. When refinance environments are used, $146,000 average loan 
amounts are used for both purchase and refinance loans. This 
relationship is consistent with the observed relationship in past 
refinance years such as 1998, 2001, and 2002.
---------------------------------------------------------------------------

    Substituting these values into (2) yields an estimate of 8.5 
million mortgages.
    Third, the total number of single-family mortgages is divided 
among the three single-family property types. Using the 89.9/1.6/8.5 
percentage distribution for single-family mortgages (see Section D), 
the following results are obtained:

(3a) SF-OM = 0.899 * CCSFM = number of owner-
occupied, one-unit mortgages = 7.642 million.
(3b) SF-2-4M = 0.016 * CCSFM = number of owner-
occupied, two-to-four unit mortgages = 0.136 million.
(3c) SF-INVM = 0.085 * CCSFM = number of one-to-
four unit investor mortgages = 0.723 million.

    Fourth, the number of dwelling units financed for the three 
single-family property types is derived as follows:

(4a) SF-O = SF-OM + SF-2-4M = number of owner-
occupied dwelling units financed = 7.778 million.
(4b) SF 2-4 = 1.2 * SF-2-4M = number of rental units in 2-4 
properties where an owner occupies one of the units = 0.163 
million.\31\
---------------------------------------------------------------------------

    \31\ Based on the 2001 RFS, there is an average of 2.2 housing 
units per mortgage for 2-4 properties and 1.3 units per mortgage for 
single-family investor properties. See earlier discussion.
---------------------------------------------------------------------------

(4c) SF-INVESTOR= 1.3 * SF-INVM = number of single-family 
investor dwelling units financed = 0.940 million.

    Fifth, summing equations 4a-4c gives the projected number of 
newly-mortgaged single-family units (SF-UNITS):

(5) SF-UNITS = SF-O + SF 2-4 + SF-INVESTOR = 8.915 million

b. Multifamily Units

    The number of multifamily dwelling units (MF-UNITS) financed by 
conventional conforming multifamily originations is calculated by 
the following series of equations:

(5a) TOTAL = SF-UNITS + MF-UNITS
(5b) MF-UNITS = MF-MIX * TOTAL = MF-MIX * (SF-UNITS + MF-UNITS) = 
[MF-MIX/(1 - MF-MIX)] * SF-UNITS where
MF-MIX = the ``multifamily mix'', or the percentage of all newly-
mortgaged dwelling units that are multifamily; as discussed in 
Section C, alternative estimates of the multifamily market will be 
included in the analysis. As explained in Section C above, the 
baseline model assumes a multifamily mix of 15 percent; results are 
also presented in the basic market tables of Sections F-H for a 
higher (16.0 percent) multifamily mix and for lower (12.25 percent, 
13.5 percent and 14.25 percent) multifamily mixes. In addition, 
further sensitivity analyses are reported in those sections for even 
lower multifamily mixes that could occur during periods of heavy 
single-family refinancing activity.

    Assuming a multifamily mix of 15 percent and solving (5b) yields 
the following:


[[Page 63849]]


(5c) MF-UNITS = [0.15/0.85] * SF-UNITS = 0.176 * SF-UNITS = 1.6 
million.

c. Total Units Financed

    The total number of dwelling units financed by the conventional 
conforming mortgage market (TOTAL) can be expressed in three useful 
ways:

(6a) TOTAL = SF-UNITS + MF-UNITS = 10.6 million (or more precisely, 
10,632,145 units)
(6b) TOTAL = SF-O + SF 2-4 + SF-INVESTOR + MF- UNITS
(6c) TOTAL = SF-O + SF-RENTAL + MF-UNITS where SF-RENTAL equals SF-
2-4 plus SF-INVESTOR

2. Dwelling Unit Distributions by Property Type

    The next step is to express the number of dwelling units 
financed for each property type as a percentage of the total number 
of units financed by conventional conforming mortgage 
originations.\32\
---------------------------------------------------------------------------

    \32\ The share of the mortgage market accounted for by owner 
occupants is (SF-O)/TOTAL; the share of the market accounted for by 
all single-family rental units is SF-RENTAL/TOTAL; and so on.
---------------------------------------------------------------------------

    The projections used above in equations (1)-(6) produce the 
following distributions of financed units by property type:

------------------------------------------------------------------------
                                                                % Share
------------------------------------------------------------------------
SF-O........................................................        74.5
SF 2-4......................................................         1.5
SF INVESTOR.................................................         9.0
MF-UNITS....................................................        15.0
                                                             -----------
    Total...................................................       100.0
or
SF-O........................................................        74.5
SF-RENTER...................................................        10.5
MF-UNITS....................................................        15.0
                                                             -----------
Total.......................................................       100.0
------------------------------------------------------------------------

    Sections C and D discussed alternative projections for the mix 
of multifamily originations and the investor share of single-family 
mortgages. This appendix will report results for multifamily mixes 
of 13.5 percent, 15.0 percent, and 16.0 percent but sensitivity 
analyses for two other multifamily mix assumptions (e.g., the 12.3 
percent assumption used by Fannie Mae and the 14.2 assumption used 
by ICF) will also be reported. Under the baseline 15.0 percent 
multifamily mix, the newly-mortgaged unit distribution would be 74.5 
percent for Single-Family Owner, 10.5 percent for Single-Family 
Renter, and 15.5 percent for Multifamily-Units. The analysis in 
sections F-H will focus on goals-qualifying market shares for this 
property distribution as well as the ones noted above.
    As discussed in Section D, the basic tables providing the goals-
qualifying market estimates in this appendix will report results for 
the following investor shares of single-family mortgages--8 percent, 
8.5 percent, 9.0 percent, and 9.5 percent. For reasons discussed in 
Section D, these investor mortgage shares are lower than the range 
(8.0 percent, 10.0 percent, and 12.0 percent) considered in the 2004 
proposed GSE rule. The middle values (8.5 percent and 9.0 percent) 
are probably the ones that should be considered as ``baseline'' 
projections; the above example used a mortgage share of 8.5 percent, 
but 9.0 percent could also have been used to characterize a home 
purchase environment. However, HUD recognizes the uncertainty of 
projecting origination volume in markets such as single-family 
investor properties; therefore, the analysis in Sections F-H 
considers market assumptions other than these baseline assumptions.
    Table D.7 reports the unit-based distributions produced by HUD's 
market share model for different combinations of these projections. 
Unit-based distributions are reported for each combination of a 
multifamily mix (12.25, 13.5, 14.25, 15.0, and 16.0) and investor 
mortgage share (8.0, 8.5, 9.0, and 9.5). The effects of the 
different projections can best be seen by examining the owner 
category which varies by 4.8 percentage points, from a low of 72.6 
percent (multifamily mix of 16.0 percent coupled with an investor 
mortgage share of 9.5 percent) to a high of 77.4 percent 
(multifamily mix of 12.25 percent coupled with an investor mortgage 
share of 8.0 percent). The overall rental share is also highlighted 
in Table D.7, varying from 22.6 percent to 27.4 percent.
BILLING CODE 4210-27-P

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[[Page 63851]]


    The baseline projection of newly-mortgaged units in the 2004 
proposed GSE rule was 72.2 percent for owner units, 12.8 percent for 
single-family rental units, and 15.0 percent for multifamily units. 
In this Final Rule, the baseline projection is 74.5 percent for 
owner units, 10.5 percent for single-family rental units, and 15.0 
percent for multifamily units, if an investor mortgage share of 8.5 
percent is used. If an investor share of 9.0 percent is used, then 
the baseline projection is 74.0 percent for owner units, 11.0 
percent for single-family rental units, and 15.0 percent for 
multifamily units. Either way, compared with the 2004 proposed GSE 
rule, the rental share of financed dwelling units has dropped by 
approximately two percentage points due to the lower HMDA-based 
investor shares used in the Final Rule.
    The unit distribution in ICF's projection model for 2005-2008 
averaged 75.5 percent for owner units, 10.3 percent for single-
family rental units, and 14.2 percent for multifamily units, which 
produces an overall rental share of 24.5 percent, a figure closed to 
those reported above (25.5-26.0 percent). The unit distribution used 
by Fannie Mae was approximately 77.4 percent for owner units, 10.4 
percent for single-family rental units, and 12.3 percent for 
multifamily units, which produces an overall rental share of 22.6 
percent,\33\ a figure less than used by ICF (24.5 percent) or HUD 
(25.0-26.0 percent). Notice that Fannie Mae and ICF assume similar 
single-family rental shares (about 10.3 percent), but ICF assumes a 
larger multifamily mix than Fannie Mae (14.2 percent versus 12.3 
percent). HUD's single-family rental shares (10.5-11.0 percent) are 
slightly higher than the shares (about 10.3 percent) used by ICF and 
Fannie Mae. HUD's multifamily baseline share (15.0 percent) is 
slightly higher than the average (14.2 percent) of ICF's best 
estimate, and significantly higher than Fannie Mae's assumed 
multifamily mix (12.3).
---------------------------------------------------------------------------

    \33\ Because of rounding, the two rental component shares do not 
add to the overall rental share.
---------------------------------------------------------------------------

    As discussed in Sections C and D, the Residential Finance Survey 
is the only mortgage data source that provides unit-based property 
distributions directly comparable to those reported below. Based on 
RFS data for 2001, HUD estimated that, of total dwelling units in 
properties financed by recently acquired conventional conforming 
mortgages, 68.3 percent were owner-occupied units, 16.5 percent were 
single-family rental units, and 15.2 percent were multifamily rental 
units. Thus, the RFS presents a much lower owner share than does 
HUD's, ICF's, or Fannie Mae's models. See Sections C and D for 
further discussion of the RFS.
    Finally, it is interesting to compare the above market-based 
distributions of financed units with the distributions of units 
financed by mortgages purchased by Fannie Mae and Freddie Mac. As 
shown in Table D.6f, the 1993-2003 averages (unweighted) for Fannie 
Mae were 81.0 percent for owner units, 9.0 percent for single-family 
rental units, and 10.0 percent for multifamily units, which produces 
an overall rental share of 19.0 percent. During the year 2000, 
Fannie Mae's overall rental share did reach a peak of 24.1 percent. 
Freddie Mac's rental shares have been markedly lower than Fannie 
Mae's. The 1993-2003 averages (unweighted) for Freddie Mac were 84.3 
percent for owner units, 6.3 percent for single-family rental units, 
and 9.3 percent for multifamily units, which produces an overall 
rental share of 15.7 percent.\34\ Freddie Mac's rental share did 
peak at 17.5 percent in 2000. Still, it is clear that the market-
based distributions project much higher rental shares than Freddie 
Mac has been purchasing. For example, the HUD projection of a 25-
percent rental share is over nine percentage points higher than 
Freddie Mac's 1999-2003 average rental share (15.7 percent) and over 
seven percentage points higher than Freddie Mac's peak rental share 
(17.5 percent in 2000). The 31.7-percent rental share from the RFS 
is 16 percentage points higher than Freddie Mac's 1999-2003 average 
rental share (15.7 percent) and over 14 percentage points higher 
than Freddie Mac's peak rental share (17.5 percent in 2000).
---------------------------------------------------------------------------

    \34\ Because of rounding, the two rental component shares do not 
add to the overall rental share.
---------------------------------------------------------------------------

F. Size of the Conventional Conforming Mortgage Market Serving Low- 
and Moderate-Income Families

    This section estimates the size of the low- and moderate-income 
market by applying low- and moderate-income percentages to the 
property shares given in Table D.7. This section essentially 
accomplishes Steps 2 and 3 of the three-step procedure discussed in 
Section B.2.
    Technical issues and data adjustments related to the low- and 
moderate-income percentages for owners and renters are discussed in 
the first two subsections. Then, estimates of the size of the low- 
and moderate-income market are presented along with several 
sensitivity analyses. Based on these analyses, HUD concludes that 
51-56 percent is a reasonable estimate of the mortgage market's low- 
and moderate-income share for the four years (2005-2008) when the 
new goals will be in effect.

1. Low- and Moderate-Income Percentage for Single-Family-Owner 
Mortgages

a. HMDA Data

    The most important determinant of the low- and moderate-income 
share of the mortgage market is the income distribution of single-
family borrowers. HMDA reports annual income data for families who 
live in metropolitan areas and purchase a home or refinance their 
existing mortgage.\35\ The data cover conventional mortgages below 
the conforming loan limit, which was $322,700 in 2003. Table D.8a 
gives the percentage of mortgages originated for low- and moderate-
income families for the years 1992-2003. Data are presented for home 
purchase, refinance, and all single-family-owner loans. The 
discussion below will often focus on home purchase loans because 
they typically account for the majority of all single-family-owner 
mortgages.\36\ For each year, a low- and moderate-income percentage 
is also reported for the conforming market without B&C loans.
    Table D.8a also reports similar data for very-low-income 
families (that is, families with incomes less than 60 percent of 
area median income). As discussed in Section H, very-low-income 
families are the main component of the special affordable mortgage 
market.
---------------------------------------------------------------------------

    \35\ HMDA data are expressed in terms of number of loans rather 
than number of units. In addition, HMDA data do not distinguish 
between owner-occupied one-unit properties and owner-occupied 2-4 
properties. This is not a particular problem for this section's 
analysis of owner incomes.
    \36\ Sensitivity analyses will focus on how the results change 
during a heavy refinancing environment.

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    Two trends in the income data should be mentioned--one related 
to the growth in the market's funding of low- and moderate-income 
families during the 1990s (and particularly the growth since 1998 
which was the last year analyzed in HUD's 2000 GSE Rule); and the 
other related to changes in the borrower income distributions for 
refinance and home purchase mortgages. Throughout this appendix, 
``low- and moderate-income'' will often be referred to as ``low-
mod'.
    Recent Trends in the Market Share for Lower Income Borrowers. 
First, focus on the percentages in Table D.8a for the total (both 
home purchase and refinance) conforming market. After averaging 
about 30 percent during 1992-93, the percentage of borrowers with 
less than area median income jumped to 41.0 percent in 1994, and 
remained above 40 percent through 2003. Over the ten-year period, 
1994 to 2003, the low-mod share of the total market averaged 42.9 
percent (or 42.2 percent if B&C loans are excluded from the market 
totals).\37\ The share of the market accounted for by very-low-
income borrowers followed a similar trend, increasing from 6-7 
percent in 1992-93 to about 12 percent in 1994 and averaging 13.2 
percent during the 1994-to-2003 period (or 12.7 percent if B&C loans 
are excluded).
---------------------------------------------------------------------------

    \37\ The annual averages of the goals-qualifying mortgages 
reported in this appendix are unweighted averages; for analyses 
using weighted averages see Appendix A.
---------------------------------------------------------------------------

    Next, consider the percentages for home purchase loans. The 
share of the home loan market accounted for by less-than-median-
income borrowers increased from 34.4 percent in 1992 to 44.7 percent 
in 2003. Within the 1994-to-2002 period, the low-mod share of the 
home purchase market averaged 44.4 percent between 1999 and 2003, 
compared with 42.1 percent between 1994 and 1998. Similarly, the 
very-low-income share of the home purchase market was also higher 
during the 1999-to-2002 period than during the 1994-to-1998 period 
(14.1 percent versus 12.6 percent). Note that within the more recent 
period, the low-mod share for home purchase loans was particularly 
high during 1999 (45.2 percent) and 2000 (44.3 percent) before 
falling slightly in 2001 (43.2 percent), only to rebound again in 
2002 (44.8 percent) and 2003 (44.7 percent). As shown in Table D.8a, 
the low-mod shares do not change much when B&C home loans are 
excluded from the market definition; this is because B&C loans are 
mainly refinance loans.
    It appears that the affordable lending market for home purchase 
loans is even stronger today than when HUD wrote the 2000 Rule, 
which covered market data through 1998. The very-low-income and low-
mod percentages were higher during 1999 to 2003 than they were 
during the earlier period. In addition, when HUD wrote the 2000 
Rule, there had been five years (1994-98) of solid affordable 
lending for lower-income borrowers. Now, with five additional years 
of data for 1999-2003, there have been ten years of strong 
affordable lending.
    Of course, it is recognized that lending patterns could change 
with sharp changes in interest rates and the economy. However, the 
fact that lending to low-income families has remained at a high 
level for ten years demonstrates that the market has changed in 
fundamental ways from the mortgage market of the early 1990s. The 
numerous innovative products and outreach programs that the industry 
has developed to attract lower-income families into the 
homeownership and mortgage markets appear to be working and there is 
no reason to believe that they will not continue to assist in 
closing troubling homeownership gaps that exist today. As explained 
in Appendix A, the demand for homeownership on the part of 
minorities, immigrants and non-traditional borrowers should help to 
maintain activity in the affordable portion of the mortgage market. 
Thus, while economic recession or higher interest rates would likely 
reduce the low- and moderate-income share of mortgage originations, 
there is evidence that the low-mod market might not return to the 
low levels of the early 1990s. There is also evidence that the 
affordable lending market increased slightly since 1998, although it 
is recognized that this could be due to the recent period of 
historically low interest rates.
    Refinance Mortgages. In the 2000 Rule, HUD's market projection 
model assumed that low-mod borrowers represented a smaller share of 
refinance mortgages than they do of home purchase mortgages. 
However, as shown in Table D.8a, the income characteristics of 
borrowers refinancing mortgages seem to depend on the overall level 
of refinancing in the market. During the refinancing wave of 1992 
and 1993, refinancing borrowers had much higher incomes than 
borrowers purchasing homes. For example, during 1993 low- and 
moderate-income borrowers accounted for 29.3 percent of refinance 
mortgages, compared to 38.9 percent of home purchase borrowers. 
While this same pattern was exhibited during the two recent 
refinancing periods (1998 and 2001-2002-2003), the differentials 
were much smaller--during 2001-2002-2003 (1998), low-mod borrowers 
accounted for 41.5 (39.7) percent of refinance loans, compared with 
44.2 (43.0) percent of home purchase loans. However, the refinance 
effect was still evident, as can be seen by the almost ten 
percentage point drop in the low-mod percentage for refinance loans 
between 2000 (a low refinance year) and 2001 (a high refinance 
year).
    On the other hand, for recent years characterized by a low level 
of refinancing, the low-mod share of refinance mortgages has been 
about the same or even greater than that of home purchase mortgages. 
As shown in Table D.8a, there was little difference in the very-low-
income and low-mod shares of refinance and home purchase loans 
during 1995 and 1996. In 1997, 1999, and 2000, the two lower-income 
shares (i.e., very-low-income and low-mod shares) of refinance 
mortgages were significantly higher than the lower-income shares of 
home purchase loans. To a certain extent, this pattern was 
influenced by the growth of subprime loans, which are mainly 
refinance loans. If B&C loans are excluded from the market 
definition, the home purchase and refinance percentages are 
approximately the same in 1997 and 1999, as well as in 1995 and 
1996. (See Table D.8a.) Even after excluding all subprime loans from 
the market definition in 1997 and 1999, the very-low-income and low-
mod shares for refinance loans are only slightly less (about one 
percentage point) than those for home purchase loans.
    The year 2000 stands out because of the extremely high lower-
income shares for refinance loans. In that year, the low-mod (very-
low-income) share of refinance loans was 7.0 (4.4) percentage points 
higher than the low-mod (very-low-income) share of home purchase 
loans; this differential is reduced to 5.4 (3.3) percent if B&C 
loans are excluded from the market definition (see Table D.8a). The 
differential for 2000 is reduced further to 2.8 (1.5) percent if all 
subprime loans (both A-minus and B&C) are excluded from the market 
definition (not reported). While the projection model (explained 
below) for years 2005-08 will input low-mod percentages for the 
entire conforming market, the model will exclude the effects of B&C 
loans. Sensitivity analyses will also be conducted showing the 
effects on the overall market estimates of excluding all subprime 
loans as well as other loan categories such as manufactured housing 
loans.
    2000 Census Data and New OMB Metropolitan Area Definitions. 
Going forward, HUD will be re-benchmarking its median incomes for 
metropolitan areas and non-metropolitan counties based on 2000 
Census median incomes, and will be incorporating the effects of the 
new OMB metropolitan area definitions. Thus, under the new housing 
goals, the GSEs' performance will be scored based on 2000 Census 
data and new OMB definitions of metropolitan areas (labeled ``CBSA 
definitions''). One issue concerns whether the new data and the new 
definitions will result in lower or higher low-mod percentages 
relative to historical low-mod percentages based on the 1990 Census 
and earlier OMB definitions of metropolitan areas (labeled ``MSA 
definitions''). HUD projected the effects of these two changes on 
the low- and moderate-income shares of the single-family-owner 
market for the years 1999-2003. The middle portion of Table D.8b 
reports low-mod shares for single-family-owner loans under the MSA 
and CBSA approaches for the years 1999-2003. Except for 2003, the 
low-mod shares for both home purchase and total SFO loans are lower 
under the new CBSA approach than under the old MSA approach. Because 
the results for 1999-2002 differed from the results for 2003, these 
two periods are considered separately. Under the historical data, 
the average low-mod share of the conventional conforming market was 
44.4 percent for home purchase loans (unweighted average of 1999-
2002 percentages in Table D.8a); the corresponding average with the 
projected data was 43.2 percent, yielding a differential of 1.2 
percentage points. For total (both home purchase and refinance) 
loans, the average low-mod share of the conventional conforming 
market based on historical data was 44.6 percent (unweighted average 
of 1999-2002 percentages); the corresponding average with the 
projected data was 43.4

[[Page 63854]]

percent, again yielding a differential of 1.2 percentage points, 
with the same pattern exhibited for the annual differentials.\38\ It 
appears that the low-mod share for single-family-owners in the 
conventional conforming market will be at least one percentage point 
less due to the re-benchmarking of area median incomes and the new 
OMB definitions of metropolitan areas.
---------------------------------------------------------------------------

    \38\ Between 1999 and 2002, the average single-family-owner 
differential between the historical and projected low-mod 
percentages was 1.1 percentage point for Fannie Mae and 1.3 
percentage point for Freddie Mac.
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[[Page 63856]]

    Based on the above analysis of 1999-2002 data, it would appear 
the low-mod share of the conventional conforming market is about one 
percentage point less when based on projected data, as compared with 
historical data. However, the data for 2003 suggest a different 
picture. As shown in Table D.8b, the 2003 CBSA-based low-mod share 
for home purchase loans is 45.8 percent, which is 1.1 percentage 
points higher than the corresponding MSA-based percentage of 44.7 
percent. Similarly, the CBSA-based percentage is 1.1 percentage 
point higher when all owner loans are considered. Thus, the more 
recent 2003 data suggest that the GSEs will be scored higher than 
they have historically been scored.
    Table A.18 in Appendix A reported similar MSA and CBSA data for 
home purchase loans acquired by Fannie Mae and Freddie Mac. Again, 
the low-mod shares for the GSEs' purchases of both home purchase and 
total SFO loans were lower under the new CBSA approach than under 
the old MSA approach for 1999-2002, but not for 2003. The proposed 
GSE rule accounted for the 1999-2002 discrepancy by reducing the 
overall low-mod estimates by one percentage point. Given the 2003 
results, which show higher low-mod shares under the new CBSA 
approach, that procedure is questionable. This Final Rule follows a 
different procedure. The actual CBSA-based low-mod shares for owners 
(reported in Table D.8b) are incorporated directly into the 
analysis.
    The projection model will initially assume that refinancing is 
35 percent of the single-family mortgage market; this will be 
followed by projection models that reflect heavy refinance 
environments. Given the volatility of refinance rates from year to 
year, it is important to conduct sensitivity tests using different 
refinance rates. However, as explained in the preamble, HUD has 
included a provision in this Final Rule that eliminates the negative 
effects of heavy refinancing periods on the GSEs' goals performance.

b. Manufactured Housing Loans

    Because manufactured housing loans are such an important source 
of affordable housing, they are included in the mortgage market 
definition in this appendix--or at least that portion of the 
manufactured housing market located in metropolitan areas is 
included, as HMDA doesn't adequately cover non-metropolitan areas. 
The GSEs have questioned HUD's including these loans in its market 
estimates; therefore, following the same procedure used in the 2000 
Rule and the 2004 proposed GSE Rule, this Appendix will report the 
effects of excluding manufactured home loans from the market 
estimates. As explained later, the effect of manufactured housing on 
HUD's metropolitan area market estimate for each of the three 
housing goals is approximately one percentage point or less.
    As discussed in Appendix A, the manufactured housing market 
increased rapidly during the 1990s, as units placed in serviced 
increased from 174,000 in 1991 to 374,000 in 1998. However, due to 
various problems in the industry such as lax underwriting and 
repossessions, volume has declined in recent years, falling to 
192,000 in 2001, to 172,000 in 2002, and to 135,000 in 2003. Still, 
the affordability of manufactured homes for lower-income families is 
demonstrated by their average price of $48,800 in 2001, a fraction 
of the median price for new ($175,000) and existing ($147,800) 
homes. Many households live in manufactured housing because they 
simply cannot afford site-built homes, for which the construction 
costs per square foot are much higher.
    Although manufactured home loans cannot be identified in the 
HMDA data, Randy Scheessele at HUD identified 21 lenders that 
primarily originated manufactured home loans in 2001 and likely 
account for most of these loans in the HMDA data for metropolitan 
areas.\39\ HMDA data on home loans originated by these lenders 
indicate that: \40\
---------------------------------------------------------------------------

    \39\ See Randall M. Scheessele, 1998 HMDA Highlights, op. cit. 
and ``HUD Subprime and Manufactured Home Lender List'' at http://www.huduseer.org/datasets/manu.html.
    \40\ Since most HMDA data are for loans in metropolitan areas 
and a substantial share of manufactured homes are located outside 
metropolitan areas, HMDA data may not accurately state the goals-
qualifying shares for loans on manufactured homes in all areas.
---------------------------------------------------------------------------

     A very high percentage of these loans--75 percent in 
2001--would qualify for the Low- and Moderate-Income Goal,
     A substantial percentage of these loans--42 percent in 
2001--would qualify for the Special Affordable Goal, and
     Almost half of these loans--47 percent in 2001--would 
qualify for the Underserved Areas Goal (defined in terms of the 1990 
Census data).\41\
---------------------------------------------------------------------------

    \41\ While many fewer manufactured home loans were identified in 
the 2002 and 2003 HMDA data, the loans showed similar goals-
qualifying shares: low-mod (77.6 percent and 75.4 percent, 
respectively), special affordable (45.0 percent and 47.1 percent, 
respectively), and underserved areas (46.9 percent and 45.2 percent, 
respectively).
---------------------------------------------------------------------------

    Thus an enhanced presence in this market by the GSEs would 
benefit many lower-income families. It would also contribute to 
their presence in underserved rural areas, especially in the South.

2. Low- and Moderate-Income Percentage for Renter Mortgages

    Following the 2000 Rule, measures of the rent affordability of 
the single-family rental and the multifamily rental markets are 
obtained from the American Housing Survey (AHS) and the Property 
Owners and Managers Survey (POMS). As explained below, the AHS 
provides rent information for the stock of rental properties while 
the POMS provides rent information for flow of mortgages financing 
that stock. As discussed below, the AHS and POMS data provide very 
similar estimates of the low- and moderate-income share of the 
rental market.

a. American Housing Survey Data

    The American Housing Survey does not include data on mortgages 
for rental properties; rather, it includes data on the 
characteristics of the existing rental housing stock and recently 
completed rental properties. Current data on the income of 
prospective or actual tenants has also not been readily available 
for rental properties. Where such income information is not 
available, FHEFSSA provides that the rent of a unit can be used to 
determine the affordability of that unit and whether it qualifies 
for the Low- and Moderate-Income Goal. A unit qualifies for the Low- 
and Moderate-Income Goal if the rent does not exceed 30 percent of 
the local area median income (with appropriate adjustments for 
family size as measured by the number of bedrooms). Thus, the GSEs' 
performance under the housing goals is measured in terms of the 
affordability of the rental dwelling units that are financed by 
mortgages that the GSEs purchase; the income of the occupants of 
these rental units is not considered in the calculation of goal 
performance. For this reason, it is appropriate to base estimates of 
market size on rent affordability data rather than on renter income 
data.
    A rental unit is considered to be ``affordable'' to low- and 
moderate-income families, and thus qualifies for the Low- and 
Moderate-Income Goal, if that unit's rent is equal to or less than 
30 percent of area median income. Table D.14 of Appendix D in HUD's 
2000 Rule reported AHS data on the affordability of the rental 
housing stock for the survey years between 1985 and 1997. The 1997 
AHS showed that for 1-4 unit unsubsidized single-family rental 
properties, 94 percent of all units and of units constructed in the 
preceding three years had gross rent (contract rent plus the cost of 
all utilities) less than or equal to 30 percent of area median 
income. For multifamily unsubsidized rental properties, the 
corresponding figure was 92 percent. The AHS data for the other 
survey years were similar to the 1997 data.

b. Property Owners and Managers Survey (POMS)

    As discussed in the 2000 GSE Rule, there were concerns about 
using AHS data on rents from the outstanding rental stock to proxy 
rents for newly mortgaged rental units. HUD investigated that issue 
further using the POMS.
    POMS Methodology. The affordability of multifamily and single-
family rental housing backing mortgages originated in 1993-1995 was 
calculated using internal Census Bureau files from the American 
Housing Survey-National Sample (AHS) from 1995 and the Property 
Owners and Managers Survey from 1995-1996. The POMS survey was 
conducted on the same units included in the AHS survey, and provides 
supplemental information such as the origination year of the 
mortgage loan, if any, recorded against the property included in the 
AHS survey. Monthly housing cost data (including rent and 
utilities), number of bedrooms, and metropolitan area (MSA) location 
data were obtained from the AHS file.
    In cases where units in the AHS were not occupied, the AHS 
typically provides rents, either by obtaining this information from 
property owners or through the use of imputation techniques. 
Estimated monthly housing costs on vacant units were therefore 
calculated as the sum of AHS rent and utility costs estimated using 
utility allowances published by HUD as part of its regulation of the 
GSEs. Observations where neither

[[Page 63857]]

monthly housing cost nor monthly rent was available were omitted, as 
were observations where MSA could not be determined. Units with no 
cash rent and subsidized housing units were also omitted. Because of 
the shortage of observations with 1995 originations, POMS data on 
year of mortgage origination were utilized to restrict the sample to 
properties mortgaged during 1993-1995. POMS weights were then 
applied to estimate population statistics. Affordability 
calculations were made using 1993-95 area median incomes calculated 
by HUD.
    POMS Results. The rent affordability estimates from POMS of the 
affordability of newly-mortgaged rental properties are quite 
consistent with the AHS data on the affordability of the rental 
stock (discussed above). Ninety-six (96) percent of single-family 
rental properties with new mortgages between 1993 and 1995 were 
affordable to low- and moderate-income families, as were 96 percent 
of newly-mortgaged multifamily properties. Thus, these percentages 
for newly-mortgaged properties from the POMS are similar to those 
from the AHS for the rental stock.
    Further Results and Comments. The baseline projection from HUD's 
market share model assumes that 90 percent of newly-mortgaged, 
single-family rental and multifamily units are affordable to low- 
and moderate-income families.\42\ As noted above, the analysis of 
AHS and POMS data from the mid-1990s supports the use of a 90 
percent low-mod figure, and also supports using rental stock data 
from the AHS as a proxy for the affordability characteristics of new 
mortgages financing rental properties. Updating these results using 
the 2001 and 2003 AHS produced similar (over 90 percent) low-mod 
estimates for both the single-family rental stock and the 
multifamily rental stock. For example, using ICF's assumptions for 
an AHS analysis (see ICF Appendix, p. 45), the 2003 AHS showed that 
94 (93) percent of single-family (multifamily) rental units would 
qualify as being affordable to low- and moderate-income families. 
While ICF used 90 percent for multifamily, ICF concluded that 87.5 
percent should be used for single-family rentals. HUD's updated 
analysis of the AHS, which is explained in more detail in Section H 
below, does not support using ICF's 87.5 percent assumption, except 
for sensitivity analysis. Since single-family rental units account 
for approximately 10 percent all financed units in both ICF's and 
HUD's market share models, the effect on the overall low-mod goal of 
using 87.5 percent instead of 90.0 percent would be only 0.25 
percentage point. (the 2.5 percentage point low-mod differential 
multiplied by the 0.10 property share for single-family rental 
properties).
---------------------------------------------------------------------------

    \42\ In 2002, 75 percent of GSE purchases of single-family 
rental units and 89 percent of their purchases of multifamily units 
qualified under the Low- and Moderate-Income Goal, excluding the 
effects of missing data.
---------------------------------------------------------------------------

    Based on its analysis of the AHS (see Fannie Mae Appendix, I-31-
I-32), Fannie Mae concluded that the low-mod shares for both single-
family and multifamily properties had fallen from 90 percent in 1997 
to 86 percent in 2001. In its analysis, Fannie Mae provides a weight 
of 0.07 to the low-mod share (74.8 percent) of recently-constructed 
single-family rental units in the AHS, and the residual 0.93 weight 
to the low-mod share (91.8 percent) of the remaining existing units 
in the AHS. While Fannie Mae appears to use a low-mod share of 86 
percent for single-family rentals in its market sizing models, 
applying these weights to the 2001 AHS data (reported by Fannie Mae 
in Table I.7 on p. I-32) yields approximately 90 percent for the 
low-mod share of single-family rental properties. Similarly, for 
multifamily properties, Fannie Mae provides a weight of 0.11 to the 
low-mod share (75.3 percent) of recently-constructed multifamily 
rental units in the AHS, and the residual 0.89 weight to the low-mod 
share (91.3 percent) of the remaining existing units in the AHS. 
Again, while Fannie Mae appears to use a low-mod share of 86 percent 
for multifamily rentals in its market sizing models, applying the 
above weights to the 2001 AHS data also yields approximately 90 
percent for the low-mod share of multifamily rental properties. 
Since single-family and multifamily rental units combined account 
for about 25 percent of all financed units in the market sizing 
models, the effect on the overall low-mod share of using 86 percent 
instead of 90 percent would be about one percentage point. (the 4.0 
percentage point low-mod differential multiplied by the 0.25 
property share for single-family and multifamily rental 
properties).\43\ Fannie Mae expressed particular concern with HUD's 
Case 3, which assumed an even higher 95.0 percent low-mod share for 
rental properties; HUD has reduced this assumption to 92.5 percent 
in the Case 3 analysis below. HUD's Case 2 will also consider a low-
mod percentage of 87.5 percent.
---------------------------------------------------------------------------

    \43\ Applying Fannie Mae's weights to data from the 2003 AHS 
produces low-mod shares of slightly over 90 percent for both single-
family and multifamily rental properties.
---------------------------------------------------------------------------

    The low-mod characteristics of the GSEs' own purchases can also 
be examined. Between 1999 and 2003, 86.4 percent of Fannie Mae's 
single-family rental purchases qualified as low-mod, as did 87.3 
percent of Freddie Mac's purchases. During the same period, 90.7 
percent of Fannie Mae's multifamily rental purchases qualified as 
low-mod, as did 92.6 percent of Freddie Mac's purchases. One issue 
discussed below concerns the impact on the GSEs' low-mod performance 
of switching to 2000 Census data and the new OMB metropolitan area 
definitions. The above GSE percentages were recalculated after 
applying the new data and new OMB definitions back to 1999. Similar 
low-mod results were obtained for both single-family and multifamily 
rentals. Thus, the 2000 Census data and the new OMB metropolitan 
area definitions will have no impact on the low-mod scoring of the 
GSEs' rental purchases.
    Most of ICF's and the GSEs' concerns about HUD's estimates of 
the affordability of rental housing properties related to the sizing 
of the special affordable market. Therefore, more detail treatment 
of these issues will be provided in Section H below.

3. Size of the Low- and Moderate-Income Mortgage Market

    This section provides estimates of the size of the low- and 
moderate-income mortgage market. Subsection 3.a presents new 
estimates of the low-mod market while Subsection 3.b reports the 
sensitivity of the new estimates to changes in assumptions about 
economic and mortgage market conditions.

a. Estimates of the Low- and Moderate-Income Market

    This section provides HUD's estimates for the size of the low- 
and moderate-income mortgage market that will serve as a proxy for 
the four-year period (2005-2008) when the new housing goals will be 
in effect. The estimates are compared with recent experience in the 
low-mod market since 1999. As discussed in Sections C and D, market 
estimates will be presented for different combinations of the 
investor mortgage share (8.8, 8.5, 9.0, and 9.5) and the multifamily 
mix (12.25, 13.5, 14.25, 15.0, and 16.0). This range reflects 
uncertainty about the data and future conditions in these rental 
markets. As discussed in Section C, HUD continues to use a 
multifamily (MF) mix of 15.0 percent as its baseline for a home 
purchase environment; this is strongly supported by RFS analysis. 
While results are reported for Fannie Mae's MF mix of 12.3 percent, 
HUD does not believe the MF mix will fall to that level in a home 
purchase environment; rather, the results are reported to gauge the 
effects on the market size of alternative assumptions supported by 
Fannie Mae. Three alternative sets of projections about rental 
property low- and moderate-income percentages are given in Table 
D.9. Case 1 projections represent the baseline and intermediate 
case; for example, it assumes that the low-mod share of rental loans 
is 90 percent. Case 1 will be the focus of the market analysis in 
this section. Case 2 assumes slightly lower goals-qualifying shares 
(e.g., an 85 percent low-mod share) for rental properties while Case 
3 assumes slightly higher goals-qualifying shares (e.g., a 92.5 
percent low-mod share).
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    Because single-family-owner units account for about 75 percent 
of all newly mortgaged dwelling units, the low- and moderate-income 
percentage for owners is the most important determinant of the total 
market estimate. Thus, Table D.10 provides market estimates for 
different low-mod percentages for the owner market as well as for 
different MF mix percentages and investor mortgage shares. In a home 
purchase environment, the most likely MF mix is 15.0 percent and the 
most likely investor mortgage share is in the 8.5-9.0 percent range. 
For simplicity, the combination of a 15.0-percent MF mix and a 8.5-
percent investor share will be labeled the baseline when presenting 
the results below. Including a 9.0-percent investor mortgage share 
as the baseline would increase the low-mod market estimate by about 
0.2-0.3 percentage point. The low-mod market estimates in Table D.10 
exclude B&C loans, as explained below.
    Table D.10 assumes a refinance rate of 35 percent, which means 
that the table reflects home purchase or low-refinancing 
environments. After presenting these results, market estimates 
reflecting heavy refinance environments will be presented. Because 
of the increase in single-family mortgages, the multifamily share of 
the mortgage market typically falls during a heavy refinance 
environment; therefore, several sensitivity analyses using lower 
multifamily mixes are examined below.

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[[Page 63861]]

    In the 2000 Rule, HUD assumed that the low-mod share of 
refinance loans was three percentage points lower than the low-mod 
share of borrowers purchasing a home. However, as discussed earlier, 
the low-mod share of refinance loans has equaled or been greater 
than the low-mod share of home purchase loans during recent home 
purchase environments such as 1995-97 or 1999-2000; thus, the 
assumption of a lower low-mod shares for refinance loans is 
initially dropped for this analysis but will be reintroduced during 
the sensitivity analysis and during the discussion of heavy 
refinance environments.
    There are two ways to view the single-family-owner low-mod 
percentages reported in the first column of Table D.10. A first 
approach would be to view them as representing low-mod percentages 
of only the home purchase market. For example, a low-mod percentage 
for home purchase loans of 43 percent--combined with the assumption 
of an equal low-mod share for refinance loans (i.e., also 43 
percent) and with the other model assumptions (such as a multifamily 
mix of 15 percent and an investor share of 8.5 percent)--produces an 
estimate of 54.6 percent for the low-mod share of the overall (owner 
and rental) market, excluding B&C loans. Thus, the reader can view 
Table D.10 as showing the overall low-mod market estimate once the 
reader specifies his or her views about the low-mod share of the 
single-family home purchase market (given the other model 
assumptions). In this case, if the reader believes that the low-mod 
share of refinance loans should be lower than that for home purchase 
loans, the reader simply has to multiply the differential amount by 
0.35 (which is the refinance share of single-family-owner loans) and 
0.745 (which is the single-family-owner share of all dwelling units 
in the model that assumes a 15 percent multifamily mix and 8.5 
percent investor mortgage share). For example, applying the 
assumption in the 2000 Rule that the low-mod share is three 
percentage points lower for refinance loans would reduce the overall 
low-mod share of the market by 0.78 percentage points (3.0 times 
0.35 times 0.745); if the low-mod share of refinance loans is one 
percentage point below that of home purchase loans, then the overall 
low-mod market estimate falls by 0.26 percentage point. In this 
manner, the reader can easily adjust the market estimates reported 
in Table D.10 to incorporate his or her own views about differences 
in the low-mod share of home purchase and refinance loans.
    A second approach would be to view the low-mod percentages (in 
the first column of Table D.10) as representing low-mod shares for 
the overall single-family-owner market, including both home purchase 
and refinance loans. This approach does not specify separate low-mod 
percentages for home purchase and refinance loans, but rather 
focuses on the overall single-family-owner environments. Thus, it 
allows for mortgage market environments where the low-mod share of 
refinance loans is greater than the low-mod share for home purchase 
loans. For example, a low-mod percentage for single-family-owner 
loans of 47 percent would reflect the year 2000 environment, which 
had a low-mod home purchase percentage of 44.3 percent combined with 
a higher low-mod refinance percentage of 51.3 percent. Of course, 
the 47 percent low-mod share for the overall single-family-owner 
market could be consistent with other combinations of low-mod shares 
for home purchase and refinance loans. In this case, a 47 percent 
assumption for the overall single-family-owner market produces an 
estimate of 57.8 percent for the low-mod share of the overall (owner 
and rental) market, excluding B&C loans.
    While both approaches will be discussed below, most of the 
discussion will focus on the first approach. It should be noted that 
several low-mod percentages of the owner market are given in Table 
D.10 to account for different perceptions of that market. 
Essentially, HUD's approach throughout this appendix is to provide 
several sensitivity analyses to illustrate the effects of different 
views about the goals-qualifying share of the single-family-owner 
market. This approach recognizes that there is some uncertainty in 
the data and that there can be different viewpoints about the 
various market definitions and other model parameters.
    Market Estimates. Considering a 15.0-percent MF mix and a 8.5-
percent investor mortgage share, the low-mod market estimates 
reported in Table D.10 are: 55.7 percent if the owner percentage is 
44.4 percent (average home purchase share for 1999-2003); 56.2 
percent if the owner percentage is 45 percent (home purchase share 
for 1999, 2002, and 2003); 55.4 percent if the owner percentage is 
44 percent (home purchase share for 2000); 54.6 percent if the owner 
percentage is 43 percent (home purchase share for 1998 and 2001); 
and 53.8 percent if the owner percentage is 42 percent (home 
purchase average from 1994-97). Considering a range of 13.5-16.0 for 
the MF mix and a range of 8.5-9.0 for the investor mortgage share, 
the low-mod market estimates reported in Table D.10 are: 55.6-57.1 
percent if the owner percentage is 45 percent; 54.8-56.1 percent if 
the owner percentage is 44 percent; 54.0-55.3 percent if the owner 
percentage is 43 percent; and 53.1-54.5 percent if the owner 
percentage is 42 percent. If the low-mod percent is at its 1999-2003 
average (44.4 percent), the market range is 54.3-56.9 percent. If 
the low- and moderate income percentage for home purchase loans fell 
to 38 percent--or five percentage points from its 1994-2003 average 
level of 43 percent--then the overall market estimate would be about 
51 percent. Thus, 51 percent is consistent with a rather significant 
decline in the low-mod share of the single-family home purchase 
market. Under the baseline projection, the home purchase percentage 
can fall as low as 36 percent--about four-fifths of the 1994-2003 
average--and the low- and moderate-income market share would still 
be 49 percent.
    Table D.8b reported so-called ``CBSA-based'' low-mod shares for 
single-family owner loans that reflect the new 2000 Census data and 
the new OMB metropolitan area definitions. Since these differed 
slightly from the historical ``MSA-based'' low-mod shares, it is 
useful to repeat the above analysis in terms of these new data, 
which will serve as the basis for scoring the GSEs' performance 
under the new housing goals. As shown in Table D.8b, the CBSA-based 
low-mod shares of home purchase loans averaged almost 44 percent 
between 1999 and 2003, suggesting an overall low-mod goal of 55.4 
percent under the baseline, with a range from 54.8 percent to 56.1 
percent. The CBSA-based measures of the low-mod share varied from 
approximately 42 percent (41.8 percent in 2001) to almost 46 percent 
(45.8 percent in 2003). Under baseline assumptions, an owner share 
of 42 percent translates into a 53.8 percent overall low-mod share 
while a 46 percent owner figure translates into a 57.0 percent low-
mod share.
    Case 2 (see Table D.9) considered a smaller low- and moderate-
income percentage (85 percent) for both SF and MF rental properties, 
as compared with the baseline Case 1, which assumed 90 percent. 
Incorporating the Case 2 assumption reduces the low-mod market 
shares by about 1.3 percentage points. For example, if the SFO home 
purchase share is 45 percent, the overall low-mod market estimate is 
54.9 percent under Case 2, as compared with 56.2 percent under Case 
1 (see Table D.10). ICF considered a different option, as it reduced 
only the SF rental percentage from 90.0 percent to 87.5 percent. 
Since SF rental units account for about 10 percent of all financed 
units, this change reduces the overall low-mod market estimates by 
about 0.25 percentage points. As discussed earlier, the baseline 
Case 1 assumption of 90 percent is a reasonable approach for 
estimating the low-mod market shares.
    Multifamily Mix. The volume of multifamily activity is also an 
important determinant of the size of the low- and moderate-income 
market. HUD is aware of the uncertainty surrounding projections of 
the multifamily market and consequently recognizes the need to 
conduct sensitivity analyses to determine the effects on the overall 
market estimate of different assumptions about the size of that 
market. Section C of this appendix provided HUD's rationale for its 
baseline MF mix of 15.0 percent and for its 13.5-16.0 percent range 
of MF mixes. Assuming a 13.5 percent multifamily mix reduces the 
overall low-mod market estimates by 0.6-0.7 percentage points 
compared with a 15 percent mix, and by 1.0-1.2 percentage points 
compared with a 16.0 percent mix. For example, when the low-mod 
share of the home purchase market is at 44 percent (its CBSA-based 
average for 1999-2003), the low-mod share of the overall market is 
54.8 percent assuming a 13.5 percent multifamily mix, compared with 
55.4 (56.8) percent assuming a 15 (16.0) percent multifamily mix.
    As shown in Table D.10, ICF's MF mix of 14.2 percent produces 
results intermediate between HUD's 13.5 percent and 15.0 percent. 
Estimates of the low-mod market based on a MF mix of 14.2 percent 
are only 0.3-0.4 percentage points less than those based on a MF mix 
of 15.0 percent.
    Fannie Mae's model combined an even lower MF mix of 12.3 percent 
with an investor mortgage share of 8.0 percent. If the low-mod share 
of home purchase loans is 44 percent (the average for 1999-2003), 
then the estimate for the overall low-mod market is 54.0 percent 
based on Fannie Mae's

[[Page 63862]]

assumptions. In contrast, HUD's estimates (with a MF mix of 15.0 
percent and 8.5-9.0 percent investor share) are 55.4-55.7 percent--
about one and a half percentage points higher. If the low-mod share 
of home purchase loans is 45 percent (which is below the CBSA-based 
percentage of 45.8 for 2003), then Fannie Mae's assumptions result 
in a market estimate of 54.8 percent while HUD's assumptions (see 
previous sentence) result in market estimates of 56.2-56.5 percent.
    Investor Mortgage Share. As shown in Table D.10, increasing the 
investor mortgage share by one percentage point from 8.0 percent to 
9.0 percent increases the low-mod market estimate by approximately 
0.5-0.6 percentage point. If the 10.0 percent baseline from the 2004 
proposed GSE rule were used in this analysis, the market estimates 
would be approximately 0.6 (0.4) percentage points higher relative 
to the results reported in Table D.10 for a baseline of 8.5 (9.0) 
percent.
    Examples of Home Purchase Years. The above projection results 
for a home purchase environment can be compared with actual results 
for the two most recent home purchase years, 1999 and 2000, as well 
as results from earlier home purchase years (1995-1997). According 
to the Mortgage Bankers Association of America, the refinance rate 
was 21 percent in 1995, 29 percent in 1996 and 1997, 34 percent in 
1999, and 29 percent in 2000.
    For 1999, the baseline model assumed a multifamily mix of 16.0 
percent (see Section C) and a mortgage investor share of 8.2 percent 
(see Section D). Under these assumptions, the 1999 market estimate 
is 56.9 percent; if the 1999 MF mix was lower--for example, 15.0 
(14.0) percent instead of 16.0 percent--then the estimate of the 
1999 low-mod market share would be 56.4 (55.9) percent.
    The 2004 proposed rule (Table D.9 in Appendix D) reported a 
higher baseline market estimate for 1999 of 58.2 percent, as 
compared with the 56.9 percent reported in the previous paragraph. 
The difference is largely due to the treatment of single-family 
rental mortgages. For example, using the proposed rule's 10-percent 
assumption for the mortgage investor share (instead of the lower 8.2 
percent HMDA-based mortgage investor shares reported in the text) 
would increase the 1999 estimate to 57.7 percent, only 0.5 
percentage points lower than the 58.2 percent reported in the 
proposed rule. Other minor changes that lower the market estimate 
included: (a) Further reducing the SF mortgage investor share by 
excluding B&C investor loans from the HMDA data (see Section C); (b) 
using 1.6 percent (instead of 2.0 percent) for the mortgage share of 
single-family 2-4 property owners; and (c) using slightly lower 
dwelling-units-per-mortgage assumptions for SF 2-4 properties (2.20 
instead of 2.25) and for SF investor mortgages (1.30 instead of 
1.35).
    The above changes also affect the 1995-to-1997 estimates 
reported in Table D.9 of Appendix D of the proposed rule for the 
three home purchase environments prior to 1999. These estimates were 
57.3 percent for both 1995 and 1996 and 57.5 percent for 1997, with 
an average of 57.4 percent.\44\ Given (a)-(c) in the previous 
paragraph and the fact that the HMDA-reported mortgage investor 
share was approximately eight percent during these three years 
(instead of the assumed 10 percent), these estimates should be 
reduced by about one percentage point, placing their average at 
56.4. Allowing for a multifamily mix of three percentage points 
below the baseline estimates (similar to the approach used for 1999 
and 2000 above) would drop the 1995-1997 low-mod estimates by 
approximately 1.4 percentage points.\45\ Thus, the 1995-1997 average 
would range from about 55.0 percent (with a MF mix of three 
percentage points below the baseline estimate) to 56.4 percent (with 
the baseline MF mix).\46\
---------------------------------------------------------------------------

    \44\ These three estimates were initially reported in HUD's 2000 
Final Rule, and repeated in Table D.9 of Appendix D of the 2004 
proposed GSE rule.
    \45\ Given that the midpoints of the multifamily mixes for 1995-
1997 are in the high 18-20 percent range (see Table D.5b), three 
percentage points were dropped in the sensitivity analysis.
    \46\ To provide some confirmation for these 1995-1997 estimates, 
HUD went back and re-estimated the model for 1997. As shown in Table 
D.9 of the 2004 GSE Proposed Rule (as well as in Table D.15 of the 
2000 GSE Rule), HUD had earlier estimated a low-mod share of 57.5 
percent for 1997 (which was about the same as the 57.3-percent low-
mod share estimated for 1995 and 1996). With a lower investor share 
(8.4 percent instead of 10.0 percent) and other changes mentioned in 
the text, the new estimate for the 1997 low-mod market was 56.4 
assuming a multifamily mix of 19.3 percent. If the multifamily mix 
is reduced to 17.3 (16.3) percent, the low-mod share of the 1997 
market is 55.5 (55.0) percent. The 55.0-56.4 percent range for 1997 
is the same as the range reported in the text for 1995-1997.
---------------------------------------------------------------------------

    For 2000, the baseline model assumed a multifamily mix of 17.2 
percent and a mortgage investor share of 9.1 percent. Under these 
assumptions, the 2000 low-mod market is estimated to be 57.9 
percent. A lower MF mix--for example, 16.0 (15.0) percent instead of 
17.2 percent--would reduce the estimated 2000 low-mod market share 
to 57.4 (57.0) percent. The baseline 57.9 percent estimate for 2000 
is about one percentage point lower than the 59.1 percent share 
reported in Table D.9 of the proposed rule, mainly for the reasons 
discussed in the previous paragraph.
    The above market estimates for 1999 and 2000 are slightly lower 
if the projected CBSA data are used instead of the historical 1990-
based MSA data. The projected CBSA-based low-mod estimate was 56.2 
percent for 1999, or 0.7 percentage points lower than the 56.9 
percent estimate based on the historical MSA data. In this case, the 
low-mod estimate falls to 55.8 (55.4) percent if the MF mix is 15.0 
(14.0) percent. Incorporating the CBSA data lowered the estimate for 
2000 by 0.5 percentage points to 57.4 percent, and to 56.9 (56.5) 
percent if the MF mix is 16.0 (15.0) percent.
    To summarize, the historical MSA-based low-mod share for all 
recent home purchase environments (1995-97 and 1999-2000) averaged 
from 55.6 percent (with a two- to three-percentage point lower MF 
mix than the baseline) to 56.8 percent (with the baseline MF mix). 
The averages (56.5 to 57.4) for the two most recent home purchase 
years, 1999 and 2000, were higher than those (55.0 to 56.4) for the 
earlier home purchase years, 1995-1997. When the data are expressed 
on a CBSA basis, the average low-mod shares for 1999 and 2000 
decline slightly to 56.0 percent (with a two-percentage point lower 
MF mix than the baseline) and to 56.8 percent (with the baseline MF 
mix).
    By comparison, ICF's best (lower bound) estimates for these home 
purchase years were 52 (49) percent for 1996, 55 (52-53) percent for 
1997 and 1999, 56 (53) percent for 1995, and 57 (54) percent for 
2000 (ICF Appendix, p. 66). Emphasizing the variability of these 
estimates, ICF also reported numerous other low-mod shares for these 
years, based on various simulations and assumptions. Some seem 
rather strange, or suggested that their analysis simply reduced the 
various input parameters to show that low estimates of the low-mod 
market could be the output. For example, ICF reports an overall 
market share of 46.9 percent share for 2000 (p. 66), which is about 
the same as the HMDA-reported single-family-owner percentage of 47.0 
percent for 2000 (Table D.8a); it is difficult to imagine what 
scenario would result in the low-mod share of the rental market 
being in the less-than-fifty-percent range (although it is 
recognized that ICF was probably using an owner share less than 47 
percent). ICF's report is full of such low estimates (e.g., 46.4 
percent for 1996 on page 67, another 49.6 percent for 2000 on page 
61) without any attempt to justify them, other than to argue that 
everything is variable and possible--an approach that is not very 
convincing if it produces a 46.9 percent low-mod share for the year 
2000.
    Heavy Refinancing Environments. The low-mod share of the market 
will decline during a period of heavy refinancing due to (a) a 
decline in the low-mod share of single-family refinance mortgages as 
middle- and upper-income borrowers dominate the refinance market; 
(b) a decline in the relative importance of the subprime market; and 
(c) a decline in the share of multifamily mortgages. For example, 
during 2002, the refinance share of low-mod loans was 41.8 percent 
(compared with 47-51 percent during the two home purchase years of 
1999 and 2000); the subprime share of the single-family market was 
8.6 percent (compared with 13 percent during 1999 and 2000); and the 
multifamily share of the market was 11 percent or less (compared 
with 16 percent or more during 1999 and 2000). Although there is 
some uncertainty with the data, the multifamily mix for 2003 could 
have been as low as 6 or 7 percent.
    Table D.11 shows the impact on the low-mod market share under 
different assumptions about a refinancing environment. The table 
reports the results for a 65 percent refinance environment, which 
has been characteristic of recent (2002 and 2003) refinance waves. 
Refinancing environments are characterized by lower MF mixes because 
single owner properties dominate the market; therefore Table D.11 
considers MF mixes from 6 to 12 percent. Most likely, a MF mix of 
12-13 percent characterized 2001, 9-11 percent characterized 2002, 
and less than 7 percent characterized 2003; there is some 
uncertainty

[[Page 63863]]

with these estimates, as discussed in Section C of this appendix. In 
a refinancing wave, the low-mod percent is typically lower for 
refinance loans than home purchase loans, as middle- and high-income 
borrowers take advantage of reduced interest rates. With respect to 
the low-mod characteristics of SF owner loans, two scenarios were 
considered: (A) Scenario A represents the average low-mod 
percentages for the last four refinance years (1998, 2001, 2002, and 
2003)--43 percent for home purchase loans and 40 percent for 
refinance loans; and (B) Scenario B represents the average low-mod 
percentages for the two most recent refinance years (2002, and 
2003)--44.5 percent for home purchase loans and 40.5 percent for 
refinance loans. Thus, there is a 3-4 percentage point differential 
between home purchase loans and refinance loans in a heavy 
refinancing environment. This analysis assumed an investor mortgage 
share of 8.0 percent (average for these refinancing years) and a 
subprime market share of 8.5 percent (instead of the 12-percent 
assumption in the baseline model).
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    Under Scenario A, the low-mod shares varied by approximately 
three percentage points, from 51.6 percent with a 12 percent MF mix 
to 48.9 percent with a 6 percent MF mix. Under Scenario B, the low-
mod percentages are all 0.7 percent higher, and the pattern is from 
52.3 percent with a MF mix of 12 percent to 49.6 percent with a MF 
mix of 6 percent. Notice that under Scenario B, the low-mod share 
remains in the 50-51 percent range even if the MF mix falls to 6-8 
percent. These low-mod market shares are 4-7 percentage points lower 
than the low-mod shares reported in Table D.10 for HUD's baseline 
home purchase environment. In addition to higher-income borrowers 
dominating the single-family market, the share of the ``goals rich'' 
rental market declines in a refinancing wave, which tends to further 
reduce the low-mod share of market activity. The right-hand column 
of Table D.11 shows that the rental share falls to the 17-22 percent 
range, or 4-9 percentage points less that the almost 26-percent 
rental share in HUD's baseline model.
    Model estimates were also made for the recent refinancing years 
of 1998, 2001, 2002, and 2003. The Mortgage Bankers Association of 
America estimated that the refinance rate was 50 percent in 1998, 55 
percent in 2001, 59 percent in 2002, and 66 percent in 2003. The 
year 2003 stands out not only for its high rate of refinancing but 
also for the sheer volume of refinancing ($2.5 trillion), which led 
to record single-family mortgage originations ($3.8 trillion) that 
year.
    For 1998, the baseline model assumed a multifamily mix of 14.0 
percent (see Section C) and a mortgage investor share of 6.8 percent 
(see Section D). Under these assumptions, the 1998 market estimate 
is 51.9 percent. If the MF mix for 1998 had been 13.0 (12.0) 
percent, instead of the baseline of 14.0 percent, then the estimated 
low-mod market share for 1998 would be 51.3 (50.8) percent. For 
2001, the baseline model assumed a multifamily mix of 13.5 percent 
and a mortgage investor share of 7.8 percent. Under these 
assumptions, the 2001 market estimate is 53.4 percent. If the MF mix 
for 2001 had been 12.5 (12.0) percent, instead of the baseline of 
13.5 percent, then the estimated low-mod market share for 2001 would 
be 52.9 (52.7) percent. For 2002, the baseline model assumed a 
multifamily mix of slightly over 11.0 percent and a mortgage 
investor share of 7.8 percent. Under these assumptions, the 2002 
low-mod market is estimated to be 53.2 percent.\47\ A lower MF mix--
for example, 10.5 (9.5) percent instead of 11 percent--would reduce 
the estimated 2002 low-mod market share to 53.1 (52.5) percent.
---------------------------------------------------------------------------

    \47\ The baseline estimates for 1998 (51.9 percent), 2001 (53.4 
percent) and 2002 (53.2 percent) are lower than those (53.8 percent, 
54.9 percent and 54.1 percent, respectively) reported in Table D.9 
of Appendix D of the proposed rule. As explained earlier, the 
differences between the results in the proposed rule and this Final 
Rule are mainly due to the treatment of single-family rental 
mortgages. (In addition, the SF owner percentages for 2002 were also 
lowered by approximately 0.5 percentage point in the Final Rule.) 
Notice that in 1998, the investor mortgage share dropped to 6.8 
percent, or 3.2 percentage points lower than that assumed in the 
proposed rule; this differential accounts for the reduction of 1.9 
percentage points (53.8 percent to 51.9 percent) in the low-mod 
market estimate for 1998.
---------------------------------------------------------------------------

    Using the projected CBSA data (instead of the historical 1990-
based MSA data) lowered the 2001 and 2002 low-mod estimates by 
approximately one percentage point. The 2001 market estimates are 
reduced to 52.3 percent (13.5 MF mix), 51.8 percent (12.5 MF mix), 
and 51.6 percent (12.0 MF mix). The 2002 market estimates are 
reduced to 52.1 percent (11.1 MF mix), 52.0 (10.5 MF mix), and 51.4 
percent (9.5 MF mix).
    By comparison, ICF's best estimates for these refinancing years 
are one or two percentage points lower than the above estimates: 
49.7 percent for 1998, 51.1 percent for 2001, and 50.9 percent for 
2002; because of the unavailability of 2003 HMDA data, no estimate 
was provided by ICF for that year. (See ICF Appendix, p. 60). ICF's 
lower bound estimates for these three years were in the 47-48 
percent range. But as noted earlier, ICF also produces a number of 
even lower estimates without discussion of what circumstances might 
lead to them--examples include their 45.2 percent market estimate 
for 2001 when the SFO low-mod share was 42.3 percent (see Table 
D.8a) and their 44.9 percent estimate for 2002 when the SFO low-mod 
share was 42.7 percent. (See ICF Appendix, p. 66.)
    For the years 1999 to 2002, Fannie Mae estimated a low-mod 
market share of 52-53 percent. (This is their estimate assuming no 
missing data; see their Table I.9, page I-34.) This compares with 
HUD's estimate of 53.7 percent to 54.5 percent. As discussed in 
Section C.6, Fannie Mae assumes a rather low MF mix (approximately 
10 percent) in the model that generates its historical estimates.
    Given that HUD did not receive 2003 HMDA data until August 2004, 
it was not possible to develop a complete projection model for 2003. 
Still, HUD developed some rough projections for 2003. Given the huge 
volume of single-family originations ($3.8 trillion), the 1998 MF 
mix was likely rather low. In fact, Fannie Mae estimates the MF mix 
dropped to five percent in 2003. Thus, the estimates of the low-mod 
market share for 2003 are presented for different assumptions about 
the MF mix, recognizing that firm data on the 2003 multifamily 
market are not available. Combining an investor mortgage share of 
8.2 from HMDA (from HMDA) with different MF mixes produces the 
following estimates: 51.9 percent (MF mix of 8 percent); 51.4 
percent (MF mix of 7 percent); and 51.0 percent (MF mix of 6.0 
percent).
    As shown by both the simulation results and by the actual 
experience during 1998 and 2001-2003, the low-mod share declines 
when refinances dominate the mortgage market. The above estimates 
place the low-mod average during these four years of heavy 
refinancing at 52 percent, with practically all of the estimates of 
annual low-mod shares varying between 51 and 53 percent. As noted 
above, the estimates for 2003 (around 51 percent) are somewhat 
speculative.
    The various market estimates presented in Table D.10 for a home 
purchase environment and reported above for a refinance environment 
are not all equally likely. Most of them equal or exceed 51 percent. 
In the home purchase environment, estimates below 51 percent would 
require the low-mod share of the single-family-owner market for home 
purchase loans to drop to 38 percent, which would be five percentage 
points below the 1994-2003 average of 43 percent. Thus, 51 percent 
is consistent with a rather significant decline in the low-mod share 
of the single-family home purchase market. Sensitivity analyses of 
different refinance environments and model estimates for 1998, and 
2001-2003 suggest that it would require a particularly heavy period 
of refinancing to fall below a 51-percent low-mod market share.

b. Economic Conditions and the Feasibility of the Low- and Moderate-
Income Housing Goal

    Commenters expressed a general concern that the market share 
estimates and the housing goals failed to recognize the volatility 
of housing markets and the existence of macroeconomic cycles. There 
was particular concern that the market shares and housing goals were 
based on a period of economic expansion accompanied by record low 
interest rates and high housing affordability. This section 
continues the discussion of these issues, noting that the Secretary 
can consider shifts in economic conditions when evaluating the 
performance of the GSEs on the goals, and noting further that the 
market share estimates can be examined in terms of less favorable 
market conditions than have existed during the 1993 to 2003 period. 
As also explained below, HUD is publishing in the Federal Register 
an Advance Notice of Proposed Rulemaking that advises the public of 
HUD's intention to consider by separate rulemaking a provision that 
recognizes and takes into consideration the impact of high volumes 
of refinance transactions on the GSEs' ability to achieve the 
housing goals in certain years, and solicits proposals on how such a 
provision should be structured and implemented.
    Volatility of the Market. Changing economic conditions can 
affect the validity of HUD's market estimates as well as the 
feasibility of the GSEs' accomplishing the housing goals. The 
volatile nature of the mortgage market in the past few years 
suggests a degree of uncertainty around projections of the 
origination market. Large swings in refinancing, consumers switching 
between adjustable-rate mortgages and fixed-rate mortgages, and 
increased first-time homebuyer activity due to record low interest 
rates, have all characterized the mortgage market during the 
nineties. These conditions are beyond the control of the GSEs but 
they would affect their performance on the housing goals. A mortgage 
market dominated by heavy refinancing on the part of middle-income 
homeowners would reduce the GSEs' ability to reach a specific target 
on the Low- and Moderate-Income Goal, for example. A jump in 
interest rates would reduce the availability of very-low-income 
mortgages for the GSEs to purchase. But on the other hand, the next 
few years may be favorable to achieving the goals because of the 
high refinancing activity in 2001, 2002, and 2003. A period of low-
to-moderate interest rates would sustain affordability levels 
without causing the rush to refinance seen earlier in

[[Page 63866]]

1998 and 2001-2003. A high percentage of potential refinancers have 
already done so, and are less likely to do so again. However, these 
same predictions were made after the 1998 refinance wave, which 
indicates the uncertainty of making predictions about the mortgage 
market.
    Recent years have been characterized by record affordability 
conditions due to low interest rates and economic expansion. Thus, 
as Section F.3.a indicates, HUD also examined potential changes in 
the market shares under very different macroeconomic environments, 
including periods of recession, high interest rates, and heavy 
refinancing (accompanied by low interest rates). A recessionary 
environment would likely be characterized by a reduction in single-
family activity (or an increase in the multifamily share of the 
market) and a reduction in the low-mod shares of the single-family-
owner market. The home purchase percentage can fall as low as 36 
percent--about four-fifths of the 1994-2003 average--and the low- 
and moderate-income market share would still be 49 percent. If the 
low-mod share of the owner market were reduced more modestly to 39 
percent, the low-mod share for the overall market would fall to 51.5 
percent, assuming a multifamily mix of 15.0 percent. (See Table 
D.10.)
    As discussed in Appendix A, record low interest rates, a more 
diverse socioeconomic group of households seeking homeownership, and 
affordability initiatives of the private sector have encouraged 
first-time buyers and low-income borrowers to enter the market since 
the mid-1990s. Over the past eight years, the affordable lending 
market has demonstrated an underlying strength that suggests it will 
continue, particularly given demographic projections of increased 
minorities and immigrants in the mortgage market. However, a 
significant increase in interest rates over recent levels would 
reduce the presence of low-income families in the mortgage market 
and the availability of low-income mortgages for purchase by the 
GSEs. As noted above, the 51-56 percent range for the low-mod market 
share covers economic and market affordability conditions much less 
favorable than recent conditions of low interest rates and economic 
expansion. The low-mod share of the single-family home purchase 
market could fall to 38 percent, which is five percentage points 
lower than its 1995-2003 average level of 43 percent, and the low-
mod market share would only be slightly below 51 percent. The above 
analysis of 1998 and the 2001-2003 period suggests that 51 percent 
is a reasonable minimum low-mod share for years of heavy 
refinancing.
    Feasibility Determination. As stated in the 2000 Rule, HUD is 
well aware of the volatility of mortgage markets and the possible 
impacts on the GSEs' ability to meet the housing goals. FHEFSSA 
allows for changing market conditions.\48\ If HUD has set a goal for 
a given year and market conditions change dramatically during or 
prior to the year, making it infeasible for the GSE to attain the 
goal, HUD must determine ``whether (taking into consideration market 
and economic conditions and the financial condition of the 
enterprise) the achievement of the housing goal was or is 
feasible.'' This provision of FHEFSSA clearly allows for a finding 
by HUD that a goal was not feasible due to market conditions, and no 
subsequent actions would be taken. As HUD noted in both the 1995 and 
2000 GSE Rules, it does not set the housing goals so that they can 
be met even under the worst of circumstances. Rather, as explained 
above, HUD has conducted numerous sensitivity analyses for economic 
and market affordability environments much more adverse than has 
existed in recent years. If macroeconomic conditions change even 
more dramatically, the levels of the goals can be revised to reflect 
the changed conditions. FHEFSSA and HUD recognize that conditions 
could change in ways that require revised expectations.
---------------------------------------------------------------------------

    \48\ Section 1336(b)(3)(A).
---------------------------------------------------------------------------

    HUD received a number of public comments seeking a regulatory 
solution to the issue of the ability of the GSEs to meet the housing 
goals during a period when refinances of home mortgages constitute 
an unusually large share of the mortgage market. As explained in the 
Preamble, HUD is not addressing the refinance issue in this final 
rule. Elsewhere in this Federal Register, HUD is publishing an 
Advance Notice of Proposed Rulemaking that advises the public of 
HUD's intention to consider by separate rulemaking a provision that 
recognizes and takes into consideration the impact of high volumes 
of refinance transactions on the GSEs' ability to achieve the 
housing goals in certain years, and solicits proposals on how such a 
provision should be structured and implemented. HUD believes that it 
would benefit from further consideration and additional public input 
on this issue. HUD also notes (see above) that FHEFSSA provides a 
mechanism by which HUD can take into consideration market and 
economic conditions that may make the achievement of housing goals 
infeasible in a given year. (See 12 U.S.C. 1336(b)(e).)

c. Treatment of B&C Loans and Other Technical Market Issues

    B&C Mortgages. As discussed in Appendix A, the market for 
subprime mortgages has experienced rapid growth over the past 6-7 
years, rising from an estimated $65 billion in 1995 to $174 billion 
in 2001, $213 billion in 2002 and $332 billion in 2003.\49\ In terms 
of credit risk, subprime loans include a wide range of mortgage 
types. ``A-minus'' loans, which represent at least half of the 
subprime market, make up the least risky category.\50\ As discussed 
in Appendix A, the GSEs are involved in this market both through 
specific program offerings and through purchases of securities 
backed by subprime loans (including B&C loans as well as A-minus 
loans). The B&C loans experience much higher delinquency rates than 
A-minus loans.\51\
---------------------------------------------------------------------------

    \49\ Estimates of the subprime market for all years since 1995 
are as follows (dollar and market share): 1995 ($65 billion, 10 
percent); 1996 ($96.5 billion, 12.3 percent); 1997 ($125 billion, 15 
percent); 1998 ($150 billion, 10 percent; 1999 ($160 billion, 12.5 
percent); 2000 ($138 billion, 12.1 percent); 2001 ($174 billion, 8.5 
percent); 2002 ($213 billion, 8.6 percent), and 2003 ($332 billion, 
8.7 percent). The uncertainty about what these various estimates 
include should be emphasized; for example, they may include second 
mortgages and home equity loans as well as first mortgages, which 
are the focus of this analysis. The source for these estimates is 
Inside Mortgage Finance (various years).
    \50\ The one-half assumption for A-minus loans is conservative 
because it probably underestimates (overestimates) the share of A-
minus (B&C) loans. According to data obtained by the Mortgage 
Information Corporation (see next footnote), 57 percent of all 
subprime loans were labeled A-minus (as of September 30, 2000). 
According to Inside B&C Lending, which is published by Inside 
Mortgage Finance, the A-minus share of the subprime market was 61.6 
percent in 2000, 70.7 percent in 2001 (see March 11, 2002 issue), 75 
percent in 2002 (see the September 15, 2003 issue), and 82 percent 
during the first nine months of 2003 (see the December 8, 2003 
issue). A more recent analysis by Inside Mortgage Finance found that 
81.4 percent of subprime loans originated during the first quarter 
of 2002 were A-minus or better (see Inside B&C Lending, Vol. 9, 
Issue 12, June 14, 2004).
    \51\ The Mortgage Information Corporation (MIC) reports the 
following serious delinquency rates (either 90 days past due or in 
foreclosure) by type of subprime loan: 3.36 percent for A-minus; 
6.67 percent for B; 9.22 percent for C; and 21.03 percent for D. The 
D category accounted for only 2 percent of subprime loans and of 
course, is included in the ``B&C'' category referred to in this 
appendix. By comparison, MIC reports a seriously delinquent rate of 
3.63 percent for FHA loans. See MIC, The Market Pulse, Winter 2001, 
page 6.
---------------------------------------------------------------------------

    The market estimates reported in Section F.3.a-b exclude the B&C 
portion of the subprime market; or conversely, they include the A-
minus portion of the subprime market. This section explains how 
these ``adjusted'' market shares are calculated from ``unadjusted'' 
market shares that include B&C loans.
    There are two possible approaches for adjusting for the effects 
of B&C owner loans in the projection model. First, readers could 
choose a single-family low-mod percentage (that is, one of the 
percentages in the first column in Table D.10) that they believe is 
adjusted for B&C loans and then obtain a rough estimate of the 
overall market estimate from the second to fourth columns 
corresponding to different multifamily mixes. For instance, if one 
believes the appropriate single-family-owner percentage adjusted for 
B&C loans (or adjusted for any other market sectors that the reader 
thinks appropriate) is 44 percent, then the low-mod market estimate 
is 55.4 percent assuming a multifamily mix of 15 percent. While 
intuitively appealing, such an approach would provide inaccurate 
results, as explained next.
    Second, readers could choose a single-family-owner percentage 
directly from HMDA data that is unadjusted for B&C loans and then 
rely on HUD's methodology (described below) for excluding the 
effects of B&C loans. This is the approach taken in Table D.10. The 
advantage of the second approach is that HUD's methodology makes the 
appropriate adjustments to the various property shares (i.e., the 
owner versus rental percentages) that result from excluding single-
family B&C loans from the analysis. According to HUD's methodology, 
dropping B&C loans would reduce the various low-mod market estimates 
by less than half of a

[[Page 63867]]

percentage point. This minor effect is due to (a) the fact that the 
low-mod share of B&C loans is similar to that of the overall market; 
and (b) the offsetting effects of the increase in the rental market 
share when single-family B&C loans are dropped from the market 
totals.
    As noted above, if one assumes the single-family-owner 
percentages in the first column of Table D.10 are unadjusted for B&C 
loans, then the overall low-mod market estimates must be adjusted to 
exclude these loans. The effects of deducting the B&C loans from the 
projection model can be illustrated using an example of a low-mod 
percentage of 44 percent for single-family-owner loans. Again, as 
explained earlier, this 44 percent figure could reflect a mortgage 
market environment where home purchase and refinance loans had 
similar low-mod percentages (i.e., 44 percent) or a mortgage market 
environment where home purchase and refinance loans had different 
low-mod market percentages that together resulted in a 44 percent 
average for the single-family-owner market.
    As Table D.10 shows, a 44 percent low-mod share for owner 
mortgages translates into an overall low-mod market share of 55.4 
percent. It is assumed that the subprime market accounts for 12 
percent of all mortgages originated, which would be $204 billion 
based on $1,700 billion for the mortgage market. This $204 billion 
estimate for the subprime market is reduced by 20 percent to arrive 
at $163.2 billion for subprime loans that will be less than the 
conforming loan limit. Dividing this figure by the average loan 
amount for subprime loans gives 1,256,361 subprime loans in the 
conventional market. HMDA data indicate that six percent of these 
are SF investor loans (75,382) and the remaining ones are SF owner 
loans (1,180,979). Since this analysis retains half of subprime 
loans (i.e., the A-minus portion of that market), these figures are 
reduced by one-half to arrive at 590,489 owner B&C loans and 37,691 
investor B&C loans. The investor loans are placed on a unit basis by 
multiplying by 1.3 (units per mortgage), yielding 48,998 financed 
dwelling units in the investor B&C market.
    HMDA data was used to provide an estimate of the portion of the 
590,489 owner B&C loans that would qualify for each of the housing 
goals. HMDA data does not identify subprime loans, much less divide 
them into their A-minus and B&C components. As explained in Appendix 
A, Randall Scheessele in HUD's Office of Policy Development and 
Research has identified almost 200 HMDA reporters that primarily 
originate subprime loans. Based on 1999-2002 HMDA data, the goals-
qualifying percentages of loans originated by these subprime lenders 
were as follows: 58.6 percent qualified for the low-mod goal, 28.0 
percent for the special affordable goal, and 52.0 percent for the 
underserved areas goal.\52\ Applying the goals-qualifying 
percentages to the 590,489 owner B&C loans gives the following 
estimates of B&C owner loans that qualified for each of the housing 
goals: Low-mod (346,027), special affordable (165,337), and 
underserved areas 614,109. The process for the smaller number 
(48,998) of investor B&C loans is similar. It is assumed that 90 
percent (44,098) of these B&C rental units qualify for the low-mod 
goal, 58 percent (28,419) qualify for the special affordable goal, 
and 74 percent (36,259) qualify for the underserved areas goal 
(based on 2000 Census data).
---------------------------------------------------------------------------

    \52\ The goals-qualifying percentages for subprime lenders are 
much higher than the percentages for the overall single-family 
conventional conforming market; for example, the 1999-2003 average 
low-mod percentage for all single-family owner loans was 44 percent. 
For further analysis of subprime lenders, see Randall M. Scheessele, 
1998 HMDA Highlights, Housing Finance Working Paper No. HF-009. 
Office of Policy Development and Research, U.S. Department of 
Housing and Urban Development, October 1999.
---------------------------------------------------------------------------

    Adjusting HUD's model to exclude B&C owner loans and B&C 
financed rental units involves subtracting the above eight figures--
two for the overall owner and rental B&C market and six for B&C 
owner units and rental units that qualify for each of the three 
housing goals--from the corresponding figures estimated by HUD for 
the total single-family and multifamily market inclusive of B&C 
owner loans and B&C dwelling units. HUD's model projects that 
10,478,681 single-family and multifamily units will be financed; of 
these, 5,842,313 (55.8 percent) qualified for the low-mod goal, 
2,801,179 (26.7 percent) for the special affordable goal, and 
3,983,005 (38.0 percent) for the underserved areas goal. Deducting 
the B&C owner and rental market estimates produces the following 
adjusted market estimates: A total market of 9,839,193, of which 
5,452,188 (55.4 percent) qualified for the low-mod goal, 2,607,423 
(26.5 percent) for the special affordable goal, and 3,639,692 (37.0 
percent) for the 2000-based underserved areas goal.
    The low-mod market share estimate exclusive of B&C loans (55.4 
percent) is only slightly lower than the original market estimate 
(55.8 percent from above), as is also the special affordable market 
estimate (26.7 percent versus 26.5 percent). This occurs because the 
B&C owner loans that were dropped from the analysis have similar 
low-mod and special affordable percentages as the overall (both 
single-family and multifamily) market. For example, the low-mod 
share of B&C loans was projected to be 58.6 percent and HUD's market 
model (unadjusted for B&C loans) projected the overall low-mod share 
to be practically the same, 55.8 percent. Thus, dropping B&C owner 
loans from the market totals does not significantly reduce the 
overall low-mod share of the market. Because they qualify at such a 
high rate (e.g., 90 percent on low-mod), dropping B&C rental loans 
tends to reduce the market share estimates. However, they are 
relatively small in number--B&C owner loans dominate the results 
because they account for 92.3 percent (590,489 divided by 639,487) 
of the total B&C owner and rental units dropped from the market 
totals.
    The situation is different for the underserved areas goal. 
Underserved areas account for 52.0 percent of the B&C owner loans, 
which is a higher percentage than the underserved area share of the 
overall market (38.0 percent). Thus, dropping the B&C owner loans 
(as well as the smaller number of B&C rental units) leads to a 
reduction in the underserved areas market share of 1.0 percentage 
points, from 38.0 percent to 37.0 percent. (If this analysis were 
conducted in terms of 1990-Census data, the one-percentage point 
reduction would be from about 33.0 percent to 32.0 percent.)
    Dropping B&C loans from HUD's projection model changes the mix 
between rental and owner units in the final market estimate; rental 
units accounted for 26.7 percent of total units after dropping B&C 
loans compared with 25.6 percent before dropping B&C loans. Since 
practically all rental units qualify for the low-mod goal, their 
increased importance in the market partially offsets the negative 
effects on the goals-qualifying shares of any reductions in B&C 
owner loans. Thus, another way of explaining why the goals-
qualifying market shares are not affected so much by dropping B&C 
owner loans is that the rental share of the overall market increases 
as the B&C owner units are dropped from the market. Since rental 
units have very high goals-qualifying percentages, their increased 
importance in the market partially offsets the negative effects on 
the goals-qualifying shares of any reductions in B&C owner loans. In 
fact, this rental mix effect would come into play with any reduction 
in owner units from HUD's model.
    A similar analysis can be used to demonstrate the effects of 
deducting the remaining, A-minus portion of the subprime market from 
the market estimates. Of course, deducting A-minus loans as well as 
B&C loans is equivalent to deducting all subprime loans from the 
market. In the example given above (44 percent low-mod percentage 
for owners), deducting all subprime loans would further reduce the 
overall low-mod market estimate to 55.0 percent. Thus, the 
unadjusted low-mod market estimate is 55.8 percent, the estimate 
adjusted for B&C loans is 55.4 percent (reported in Table D.10), and 
the estimate adjusted for all subprime loans is 55.0 percent.
    As discussed in the 2000 Rule, there are caveats that should be 
mentioned concerning the above adjustments for the B&C market. The 
adjustment for B&C loans depends on several estimates relating to 
the single-family mortgage market, derived from various sources. 
Different estimates of the size of the B&C market or the goals-
qualifying shares of the B&C market could lead to different 
estimates of the goals-qualifying shares for the overall market. The 
goals-qualifying shares of the B&C market were based on HMDA data 
for selected lenders that primarily originate subprime loans; since 
these lenders are likely originating both A-minus and B&C loans, the 
goals-qualifying percentages used here may not be accurately 
measuring the goals-qualifying percentages for only B&C loans. The 
above technique of dropping B&C loans also assumes that the coverage 
of B&C and non-B&C loans in HMDA's metropolitan area data is the 
same; however, it is likely that HMDA coverage of non-B&C loans is 
higher than its coverage of B&C loans.\53\ Despite these caveats, it 
also

[[Page 63868]]

appears that reasonably different estimates of the various market 
parameters would not likely change, in any significant way, the 
above estimates of the effects of excluding B&C loans in calculating 
the goals-qualifying shares of the market. As discussed in other 
sections, HUD provides a range of estimates for the goals-qualifying 
market shares to account for uncertainty related to the various 
parameters included in its projection model for the mortgage market.
---------------------------------------------------------------------------

    \53\ Dropping B&C loans in the manner described in the text 
results in the goals-qualifying percentages for the non-B&C market 
being underestimated since HMDA coverage of B&C loans is less than 
that of non-B&C loans and since B&C loans have higher goals-
qualifying shares than non-B&C loans. For instance, the low-mod 
shares of the market reported in the text underestimate (to an 
unknown extent) the low-mod shares of the market inclusive of B&C 
loans; so reducing the low-mod owner shares by dropping B&C loans in 
the manner described in the text would provide an underestimate of 
the low-mod share of the non-B&C owner market. A study of 1997 HMDA 
data in Durham County, North Carolina by the Coalition for 
Responsible Lending (CRL) found that loans by mortgage and finance 
companies are often not reported to HMDA. For a summary of this 
study, see ``Renewed Attack on Predatory Subprime Lenders'' in Fair 
Lending/CRA Compass, June 9, 1999.
---------------------------------------------------------------------------

    Manufactured Housing Loans and Small Loans. HUD includes the 
effects of manufactured housing loans (at least those financing 
properties in metropolitan areas) in its market estimates. However, 
sensitivity analyses are conducted to determine the effects of 
excluding these loans. Excluding manufactured housing loans as well 
as small loans (loans less than $15,000) reduces the overall market 
estimates reported in Table D.10 by about one percentage point. This 
is estimated as follows. First, excluding these loans reduces the 
low-mod percentage for single-family-owner mortgages in metropolitan 
areas by about 1.9 percentage points, based on analysis of recent 
home purchase environments (1995-97 and 1999 and 2000). Multiplying 
this 1.9 percentage point differential by the property share (0.745) 
of single-family-owner units yields 1.4 percentage points, which 
serves as a proxy for the reduction in the overall low-mod market 
share due to dropping manufactured home loans from the market 
analysis. The actual reduction will be somewhat less because 
dropping manufactured home loans will increase the share of rental 
units, which increases the overall low-mod market share, thus 
partially offsetting the 1.4 percent reduction. The net effect is 
probably a reduction of about one percentage point.
    The effects can be considered separately. Dropping only 
manufactured housing loans would reduce the market estimates by 
approximately three-quarters of a percentage point. ICF argued that 
loans with less than $15,000 should be excluded. The impact of doing 
this on the market estimates would be less than half a percentage 
point. ICF also considered scenarios where one-half of manufactured 
loans would be dropped, as well as small loans less than $15,000. 
The impact of doing this on the market estimates would be less than 
three-quarters of a percentage point.
    The estimated reductions in goals-qualifying shares due to 
excluding manufactured housing would be even lower during the heavy 
refinance years such as 1998 and 2001-2003. It should also be 
mentioned that manufactured housing in non-metropolitan areas is not 
included in HUD's analysis due to lack of data; including that 
segment of the market would increase the goals-qualifying shares of 
the overall market. Thus, the analyses of manufactured housing 
reported above and throughout the this final rule pertain only to 
manufactured housing loans in metropolitan areas, as measured by 
loans originated by the 21 manufactured housing lenders identified 
by Randy Scheessele at HUD.
    The above analyses of the effects of less affordable market 
conditions, different assumptions about the size of the rental 
market, and dropping different categories of loans from the market 
definition suggest that 51-56 percent is a reasonable range of 
estimates for the low- and moderate-income market. This range covers 
markets without B&C and allows for market environments that would be 
much less affordable than recent market conditions. The next section 
presents additional analyses related to market volatility and 
affordability conditions.

d. Conclusions About the Size of Low- and Moderate-Income Market

    Based on the above findings as well as numerous sensitivity 
analyses, HUD concludes that 51-56 percent is a reasonable range of 
estimates of the mortgage market's low- and moderate-income share 
for the year 2005 and beyond. The range covers much more adverse 
economic and market affordability conditions than have existed 
recently, allows for different assumptions about the single-family 
and multifamily rental markets, and excludes the effects of B&C 
loans. HUD recognizes that shifts in economic conditions and 
refinancing could increase or decrease the size of the low- and 
moderate-income market during that period.

G. Size of the Conventional Conforming Market Serving Central 
Cities, Rural Areas, and Other Underserved Areas

    The following discussion presents estimates of the size of the 
conventional conforming market for the Central City, Rural Areas, 
and other Underserved Areas Goal; this housing goal will also be 
referred to as the Underserved Areas Goal. The first three sections, 
which analyze historical data going back to the early 1990's, 
necessarily used 1990 Census geography to define underserved census 
tracts and underserved counties. The first two sections focus on 
underserved census tracts in metropolitan areas, as Section 1 
presents underserved area percentages for different property types 
while Section 2 presents market estimates for metropolitan areas. 
Section 3 discusses B&C loans and rural areas. But as explained in 
Appendix B, HUD will be defining underserved areas based on 2000 
Census geography beginning in 2005, the first year covered by this 
final rule. Therefore, Section 4 repeats much of the analyses in 
Sections 1-3 but in terms of 2000 Census geography, rather than 1990 
Census geography

1. Underserved Areas Goal Shares by Property Type

    For purposes of the Underserved Areas Goal, underserved areas in 
metropolitan areas are defined as census tracts with:
    (a) Tract median income at or below 90 percent of the MSA median 
income; or
    (b) A minority composition equal to 30 percent or more and a 
tract median income no more than 120 percent of MSA median income.
    Owner Mortgages. The first set of numbers in Table D.12 are the 
percentages of single-family-owner mortgages that financed 
properties located in underserved census tracts of metropolitan 
areas between 1992 and 2003. There are several interesting patterns 
in these data. During 1999 and 2000, 28-30 percent of mortgages 
(both home purchase and refinance loans) financed properties located 
in these areas; this percentage fell to 25.7 percent in 2001, 25.0 
percent in 2002, and 25.3 percent in 2003, figures that were 
slightly below the average (26.8 percent) between 1994 and 1998. In 
1992 and 1993, the underserved areas share of single-family-owner 
mortgages was only 20 percent.
BILLING CODE 4210-27-P

[[Page 63869]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.095

    In most years, refinance loans are more likely than home 
purchase loans to finance properties located in underserved census 
tracts. Between 1994 and 2003, 27.3 percent of refinance loans were 
for properties in underserved areas, compared to 25.5 percent of 
home purchase loans. This 1.8 percentage point refinance-home-
purchase differential is mostly due to the influence of subprime 
loans. Excluding B&C (all subprime) loans and considering the same 
time period, 26.1 (24.9) percent of refinance loans were for 
properties in underserved areas, compared to 25.1 (24.6) percent of 
home purchase loans. Thus, excluding B&C (subprime) loans reduces 
the differential from 1.8 percentage points to 1.0 (0.3) percentage 
point. In the year (2000) with the largest differential,

[[Page 63870]]

excluding B&C (all subprime) loans reduced the refinance-home-
purchase differential from 8.1 percent to 6.9 (5.7) percent; in this 
case, a significant differential remained after excluding B&C 
(subprime) loans. In the heavy refinance years of 1998, 2001, 2002, 
and 2003 underserved areas accounted for about 25 percent of total 
(both home purchase and refinance) owner loans.
    The underserved areas share for home purchase loans has been in 
the 25-26 percent range since 1995, except for 2000 and 2002 when it 
increased to over 27 percent, and in 2003 when it increased to 28.5 
percent. Considering all (both home purchase and refinance) loans 
during recent ``home purchase'' environments, the underserved areas 
share was a high 28-30 percent during 1999-2000, compared with a 27 
percent average between 1995 and 1997; excluding B&C and other (i.e. 
A-minus) subprime loans places 1999 on par with the earlier years, 
with only the year 2000 showing a higher level of underserved area 
lending than occurred during 1995-97. These data indicate that the 
single-family-owner market in underserved areas has remained strong 
since the 2000 Rule was written. While it is recognized that 
economic and housing affordability conditions could change and 
reduce the size of the underserved areas market, it appears that the 
underserved market has certainly maintained itself at a high level 
over the past four years.
    Renter Mortgages. The second and third sets of numbers in Table 
D.12 are the underserved area percentages for single-family rental 
mortgages and multifamily mortgages, respectively. Based on HMDA 
data for single-family, non-owner-occupied (i.e., investor) loans, 
the underserved area share of newly-mortgaged single-family rental 
mortgages has averaged about 44 percent (over nine or ten years). 
HMDA data also show that about half of newly-mortgaged multifamily 
rental units are located in underserved areas. HUD's baseline 
assumes that 42.5 percent of single-family investor loans and 48 
percent of multifamily loans are located in underserved areas. The 
GSEs and ICF argued that HUD had overstated these underserved area 
percentages; Section G.4 below, which focuses on the 2000-based 
underserved area percentage, will discuss and respond to their 
concerns. Fannie Mae also said that subprime (or B&C) loans should 
be taken out of the SF investor loans. As shown in Table D.12, 
deducting B&C loans reduces the underserved area percentage for SF 
investor mortgages by almost one percentage point (the 1993-2003 
unweighted average falls from 44.0 percent to 43.1 percent). HUD's 
model excludes B&C investor loans in the same manner it excludes B&C 
owner loans (see earlier explanation).

2. Market Estimates for Underserved Areas in Metropolitan Areas

    Table D.13 reports HUD's estimates of the market share for 
underserved areas based on the projection model discussed earlier. 
The estimates in Table D.13 exclude the effects of B&C owner loans 
and B&C investor loans. The percentage of single-family-owner 
mortgages financing properties in underserved areas is the most 
important determinant of the overall market share for this goal. 
Therefore, Table D.13 reports market shares for different single-
family-owner percentages ranging from 30 percent (2000 level) to 20 
percent (1993 level) to 19 percent. Considering a 15.0-percent MF 
mix and a 8.5-percent investor mortgage share, the market share 
estimate is 31-32 percent if the overall (both home purchase and 
refinance) single-family-owner percentage for underserved areas is 
at its 1994-2003 HMDA average of 26.6 percent. The overall market 
share for underserved areas peaks at 35 percent when the single-
family-owner percentage is at its 2000 level of 30 percent.

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[[Page 63872]]

    The analysis can also be conducted in terms of the home purchase 
percentages reported in Table D.13. Again, considering a 15.0-
percent MF mix and an 8.5-percent investor mortgage share, the 
underserved area market estimates reported in Table D.13 are: 33.3 
percent if the owner percentage is 28.5 percent (home purchase share 
for 2003); 32.1 if the owner percentage is 27 percent (home purchase 
share in 2000 and 2002 slightly above the 1999-2003 average home 
purchase share of 26.8 percent); 31.3 percent if the owner 
percentage is 26 percent (home purchase share for 1999 and 2001); 
and 30.5 percent if the owner percentage is 25 percent (home 
purchase average from 1994-98). This analysis assumes that the 
underserved areas share of refinance loans is the same as those 
listed above for home purchase loans. But, as Table D.12 shows, the 
underserved areas share of refinance loans tends to be higher than 
that for home purchase loans. And in the year 2000, the overall 
underserved areas share for owner loans reached 30 percent; as noted 
in the previous paragraph, the overall market estimate is 34.6 
percent in this case. However, the next highest overall owner share 
is the 28.2 percent share in 1999, which yields a market estimate of 
approximately 33 percent.
    Sensitivity Analyses. Unlike the Low- and Moderate-Income and 
Special Affordable Goals, the market estimates differ only slightly 
as one moves from a 13.5 percent MF mix to 16.0 percent MF mix. For 
example, reducing the assumed multifamily mix from 16.0 percent to 
13.5 percent reduces the overall market projection for underserved 
areas by only 0.5-0.6 percentage points. This is because the 
underserved area differentials between owner and rental properties 
are not as large as the low- and moderate-income differentials 
reported earlier.
    Similarly, the market estimates differ only slightly with 
changes in the investor mortgage share. Reducing the investor mix 
from 9.5 percent to 8.0 percent reduces the overall market 
projection for underserved areas by only 0.2-0.3 percentage points.
    Case 2 (see Table D.9) considered slightly smaller underserved 
area percentages for rental properties (40 percent for SF rentals 
and 46 percent for MF rentals), as compared with the baseline Case 
1, which assumed 42.5 percent and 46.0 percent, respectively. 
Incorporating these Case 2 assumptions reduces the underserved areas 
market estimate by only 0.6 percentage points. For example, if the 
SFO home purchase share is 28 percent, then the overall underserved 
area estimate is 32.3 percent under Case 2, as compared with 32.9 
percent under Case 1 (see Table D.13).
    Examples of Home Purchase and Refinance Environments. The above 
projection results for a home purchase environment can be compared 
with actual results for two home purchase years, 1999 and 2000 (see 
earlier description of these two years in the low-mod section, 
F.3.a). For 1999, the baseline model assumed a multifamily mix of 
16.0 percent and a mortgage investor share of 8.2 percent. Under 
these assumptions, the projected 1999 market estimate (based on 
1990-Census data) is 33.1 percent; if the 1999 MF mix was lower at 
15.0 (14.0), then the estimate of the 1999 underserved areas market 
share would be only slightly lower at 32.9 (32.6) percent.\54\ For 
2000, the baseline model assumed a multifamily mix of 17.2 percent 
and a mortgage investor share of 9.1 percent. Under these 
assumptions, the 2000 underserved areas market is estimated to be 
34.9 percent. A lower MF mix of 16.0 (15.0) percent would reduce the 
estimated 2000 underserved areas market share slightly to 34.6 
(34.4) percent.\55\
---------------------------------------------------------------------------

    \54\ Table D.15 of the 2000 GSE Rule also reported underserved 
area shares of 33.9 percent for 1995 and 1997 and 33.4 percent for 
1996. These estimates, after adjustments for a lower HMDA-based 
mortgage investor share and a lower-than-baseline MF mix, would 
still remain in the 32-33 percent range. To provide some 
confirmation for this, HUD went back and re-estimated the model for 
1997. As shown in Table D.15 of the 2000 GSE Rule, HUD had earlier 
estimated an underserved areas share of 33.9 percent for 1997 (which 
was the same as the 33.9-percent underserved areas estimate for 1995 
and similar to the 33.4-percent estimate for 1996). With a lower 
investor share (8.4 percent instead of 10.0 percent) and other 
changes mentioned in the text, the new estimate for the 1997 
underserved areas market was 32.7 assuming a multifamily mix of 19.3 
percent. If the multifamily mix is reduced to 17.3 (16.3) percent, 
the underserved areas share of the 1997 market is 32.3 (32.0) 
percent. Thus, this 32.0-32.7 percent range for 1997 is consistent 
with a 32-33 percent range for 1995-1997.
    \55\ The baseline 34.9 percent estimate for 2000 is 0.4 
percentage points lower than the 35.3 percent share reported in 
Table D.9 of the proposed rule. The difference is mostly explained 
by the different treatment of single-family rental mortgages.
---------------------------------------------------------------------------

    The heavy refinance scenarios discussed for the low-mod market 
were also projected for the underserved areas market. Since the 
impact of a heavy refinancing period on the underserved areas market 
share will be covered in Section G.4, which incorporates 2000 Census 
data, there is no need for a detailed discussion in this section's 
analysis based on 1990 Census data. Still, it is useful to provide a 
quick review of the 1990-based underserved area estimates for three 
heavy refinancing environments (1998, 2001, 2002, and 2003). For 
1998, the baseline model assumed a multifamily mix of 14.0 percent 
and a mortgage investor share of 6.8 percent. Under these 
assumptions, the 1998 market estimate is 29.9 percent. If the MF mix 
for 1998 had been 12.0 percent, instead of the baseline of 14.0 
percent, then the estimated underserved area market share for 1998 
would be 29.4 percent. For 2001, the baseline model assumed a 
multifamily mix of 13.5 percent and a mortgage investor share of 7.8 
percent. Under these assumptions, the 2001 market estimate is 32.1 
percent, dropping to 31.7 percent if the MF mix was 12.0 percent. 
For 2002, the baseline model assumed a multifamily mix of slightly 
over 11.0 percent and a mortgage investor share of 7.8 percent. 
Under these assumptions, the 2002 underserved areas market is 
estimated to be 31.6 percent, dropping to 31.1 percent if the MF mix 
is 9.5 percent. This analysis suggests that the underserved areas 
market based on 1990 Census data will be about 29-32 percent range 
during periods of heavy refinancing.\56\
---------------------------------------------------------------------------

    \56\ For the years 1999 to 2002, Fannie Mae estimated an 
underserved areas share of 32-33 percent. (See their Table I.9, page 
I-34.) This compares with HUD's estimate of 32.5 percent to 32.9 
percent for the same period.
---------------------------------------------------------------------------

    Additional sensitivity analyses were conducted to reflect the 
volatility of the economy and mortgage market. Recession and high 
interest rate scenarios assumed a significant drop in the 
underserved area percentage for single-family-owner mortgages. The 
single-family-owner percentage can go as low as 24 percent--which is 
3 percentage points lower than the 1995-2003 average of 27 percent--
and the estimated market share for underserved areas remains at 
almost 30 percent. In a more severe case, the overall underserved 
market share would be 27.5 percent if the single-family-owner share 
fell to 21 percent (its 1992 level), which is 7-9 percentage points 
lower than its 1999-2000 levels.

3. Adjustments: B&C Loans, the Rural Underserved Areas Market, and 
Manufactured Housing Loans

    B&C Loans. The procedure for dropping B&C loans from the 
projections is the same as described in Section F.3.b for the Low- 
and Moderate-Income Goal. The underserved area percentage for B&C 
loans is 44.5 percent, which is much higher than the projected 
percentage for the overall market (which peaks at 35 percent as 
indicated in Table D.13). Thus, dropping B&C loans will reduce the 
overall market estimates. Consider the case of a single-family-owner 
percentage of 27 percent, which yields an overall market estimate 
for underserved areas of 33.1 percent, including B&C loans. When B&C 
loans are excluded from the projection model, the underserved areas 
market share falls by 0.9 percentage points to 32.2 percent, which 
is the figure reported in Table D.13.
    Non-metropolitan Areas. Underserved rural areas are non-
metropolitan counties with:
    (a) County median income at or below 95 percent of the greater 
of statewide non-metropolitan median income or nationwide non-
metropolitan income; or
    (b) A minority composition equal to 30 percent or more and a 
county median income no more that 120 percent of statewide non-
metropolitan median income.
    HMDA's limited coverage of mortgage data in non-metropolitan 
counties makes it impossible to estimate the size of the mortgage 
market in rural areas. However, all indicators suggest that 
underserved counties in non-metropolitan areas comprise a larger 
share of the non-metropolitan mortgage market than the underserved 
census tracts in metropolitan areas comprise of the metropolitan 
mortgage market. For instance, underserved counties within rural 
areas include 54 percent of non-metropolitan homeowners; on the 
other hand, underserved census tracts in metropolitan areas account 
for only 34 percent of metropolitan homeowners.
    During 1999-2003, 38.3 percent of the GSEs' single-family-owner 
(SFO) purchases in non-metropolitan areas were in underserved 
counties while 23.1 percent of their SFO purchases in metropolitan 
areas were in underserved census tracts. These figures suggest the 
market share for

[[Page 63873]]

underserved counties in rural areas is higher than the market share 
for underserved census tracts in metropolitan areas. Thus, using a 
metropolitan estimate to proxy the overall market for this goal, 
including rural areas, is conservative.\57\
---------------------------------------------------------------------------

    \57\ Between 1999 and 2001, the non-metropolitan portion of the 
Underserved Areas Goal contributed 1.1 to 1.4 (0.7 to 1.3) 
percentage points to Freddie Mac's (Fannie Mae's) overall 
performance (i.e., including both metro and non-metro loans), 
compared with a goals-counting system that only included 
metropolitan areas.
---------------------------------------------------------------------------

    The limited HMDA data available for non-metropolitan counties 
also suggest that the underserved areas market estimate would be 
higher if complete data for non-metropolitan counties were 
available. According to HMDA, underserved counties accounted for 
41.6 percent of SFO mortgages originated in non-metropolitan areas 
between 1999 and 2003. By contrast, underserved census tracts 
accounted for approximately 24.9 percent of SFO mortgages originated 
in metropolitan areas between 1999 and 2003.\58\ Since non-
metropolitan areas account for 13 percent of all single-family-owner 
mortgages \59\ and estimating that the single-family-owner market 
accounts for 74.5 percent of newly-mortgaged dwelling units, then 
the non-metropolitan underserved area differential of 16.7 percent 
would raise the overall market estimate by 1.6 percentage point--
16.7 percentage points times 0.13 (non-metropolitan area mortgage 
market share) times 0.745 (single-family owner mortgage market 
share). Based on this calculation, if the 16.7 point differential 
reflected actual market conditions, then the underserved areas 
market share estimated using metropolitan area data should be 
increased by 1.6 percentage points to account for the effects of 
underserved counties in non-metropolitan areas.\60\ A more 
conservative adjustment of 1.25 percentage points was made in Table 
D.13 for the 2005-2008 projection model. The non-metropolitan area 
issue will be discussed further in Section G.4 below, which 
incorporates the effects of the new 2000 Census data.
---------------------------------------------------------------------------

    \58\ These data do not include loans originated by lenders that 
specialize in manufactured housing loans, as well as estimated B&C 
loans.
    \59\ Federal Housing Finance Board data.
    \60\ Mortgage Interest Rate Survey (MIRS) data reported by the 
Federal Housing Finance Board separate conventional home purchase 
loans by their metropolitan and non-metropolitan location. The 
average non-metropolitan share between 1999 and 2002 was about 13 
percent.
---------------------------------------------------------------------------

    Small Loans and Manufactured Housing Loans. Excluding 
manufactured housing loans and small loans (less than $15,000) 
reduces the overall underserved area market estimates reported in 
Table D.13 by less than one percentage point. This is estimated as 
follows. First, excluding these loans reduces the unadjusted 
underserved areas percentage for single-family-owner mortgages in 
metropolitan areas by about 1.2 percentage points, based on analysis 
of recent home purchase environments (1995-97 and 1999 and 2000). 
Multiplying this 1.2 percentage point differential by the property 
share of single-family-owner units (74.5 percent) yields 0.9 
percentage points, which serves as a proxy for the reduction in the 
overall underserved area market share due to dropping manufactured 
home loans from the market analysis. The actual reduction will be 
somewhat less because dropping manufactured home loans will increase 
the share of rental units, which increases the overall underserved 
areas market share, thus partially offsetting the 0.8 percent 
reduction. The net effect is probably a reduction of about three-
quarters of a percentage point.
    The small loan and manufactured housing effects can be 
considered separately. Dropping only manufactured housing loans 
would reduce the market estimates by approximately three-fourths of 
a percentage point. ICF argued that loans with less than $15,000 
should be excluded. The impact of doing this on the market estimates 
would be about one-third of a percentage point. ICF also considered 
scenarios where one-half of manufactured loans would be dropped, as 
well as small loans less than $15,000. The impact of doing this on 
the market estimates would be three-fifths of a percentage point.
    The next section discusses changes as a result of switching from 
1990 to 2000 Census geography.

4. 2000-Based Underserved Area Market Shares

    The above analysis has concluded that 29-34 percent would be a 
reasonable market range for the Geographically Targeted Goal based 
on past origination activity in underserved areas and on scenarios 
that cover a variety of economic and mortgage market conditions. 
That analysis, which included historical data going back to the 
early 1990's, necessarily used 1990 Census geography to define 
underserved census tracts. As explained in Appendix B, HUD will be 
defining underserved areas based on 2000 Census geography beginning 
in 2005, the first year covered by this final rule. Appendix B also 
explains that the number of census tracts in metropolitan areas 
covered by HUD's underserved area definition will increase from 
21,587 tracts (based on 1990 Census) to 26,959 tracts (based on 2000 
Census and OMB's respecification of metropolitan areas). This 
increase in the number of tracts defined as underserved means that 
the market estimate for the Geographically Targeted Goal will be 
about five percentage points higher than the 1990-based market 
estimate. Thus, this section provides a new range of market 
estimates for underserved areas defined in terms of 2000 Census 
data.
    For the years 1999 to 2003, Table D.14a. reports the underserved 
areas share of the mortgage market for single-family-owner, investor 
(non-owner), and multifamily properties, with comparisons between 
1990-based and 2000-based measures of underserved areas. HMDA data, 
which is the source of the mortgage data, were reported in terms of 
1990 census tracts. For the years 1999 to 2002, HUD used various 
apportionment techniques to re-allocate 1990-based HMDA mortgage 
data into census tracts as defined by the 2000 Census; 2003 HMDA 
data were defined in terms of 2000 Census tracts, so no reallocation 
was required. The 1990-based underserved area market shares reported 
in Table D.14.a. are the same data reported earlier in Table D.12, 
while the 2000-based underserved area market shares result from re-
allocating 1999-2002 HMDA data into 2000 Census geography. In 
addition, the data are defined in terms of the new OMB metropolitan 
area definitions.
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[[Page 63875]]


    Single-Family-Owner Loans. First, consider the market shares for 
single-family-owner properties in the top portion of Table D.14a. In 
2002, the underserved area percentage for home purchase loans 
increases from 27.1 percent (1990-based) to 32.8 percent (2000-
based), an increase of 5.7 percentage points; the corresponding 
percentages for refinance loans were 24.2 percent (1990-based) and 
29.4 percent (2000-based), or an increase of 5.2 percentage points. 
Considering total owner loans (i.e., both home purchase and 
refinance owner loans), the weighted average of the ``Differences'' 
reported in Table D.14a. is 5.4 percentage points in 2002 for the 
conforming market. Between 1999 and 2003, 30.3 percent of mortgage 
originations were originated in underserved areas based on 2000 
geography, compared with 25.2 percent based on 1990 geography--
yielding the overall differential of 5.1 percentage points. (The 
unweighted 1999-2003 differential is 4.9 percent.)
    The first column of Table D.14a. reports the 2000-based 
underserved areas share for home purchase loans for the years, 1999 
to 2003. The share was about 31 percent in 1999 and 2001 and in the 
32.6-33.7 percent range during 2000, 2002, and 2003. Notice that the 
peak share (33.7 percent) for home purchase loans occurred in the 
most recent year, 2003. It should be recalled that there was no need 
to re-apportion the 2003 data from 1990-based tracts to 2000-based 
tracts, as these 2003 data were already defined in terms of 2000 
census geography. Whether this fact affects the various 
differentials between 2003 and earlier years is not clear. The years 
1999 and 2000 exhibited higher underserved area shares for refinance 
loans than for home purchase loans; as discussed earlier, this 
pattern was largely, but not entirely, due to subprime refinance 
loans.
    Single-Family Rental and Multifamily Loans. Next, consider the 
underserved area market shares reported for single-family rental (or 
non-owner) and multifamily properties in the middle and bottom 
portions of Table D.14a. In 2002, the underserved area percentage 
for home purchase investor loans increases from 42.0 percent (1990-
based) to 47.7 percent (2000-based), an increase of 5.7 percentage 
points; the corresponding percentages for refinance loans were 45.6 
percent (1990-based) and 50.8 percent (2000-based), or an increase 
of 5.3 percentage points. The multifamily differentials are somewhat 
higher at approximately 7-8 percentage points. Between 1999 and 
2003, 60 percent (unweighted average) of multifamily originations 
were originated in underserved areas based on 2000 geography, 
compared with 52.6 percent based on 1990 geography.
    In the 2004 proposed GSE Rule, HUD made the following 2000-based 
assumptions with respect to the underserved areas shares of single-
family rental properties: 52.0% for Case 1 (baseline), 50.0% for 
Case 2, and 54.0% for Case 3. With respect to multifamily 
properties, the following assumptions were made with respect to 
underserved areas shares: 58.0% for Case 1 (baseline), 56.0% for 
Case 2, and 59.0% for Case 3. ICF criticized HUD's baseline 
assumptions (52 percent for SF investors and 58 percent for MF 
rentals) as being too high.\61\ ICF's best estimate was 50 percent 
for SF investors and 55 percent for MF rentals.\62\ Since SF rentals 
account for 10.6 percent of financed units, reducing the underserved 
area share by two percentage points from HUD's 52 percent to ICF's 
50 percent would reduce the overall underserved areas goal by 0.21 
percentage point. Since MF rentals account for 15.0 percent of 
financed units (in HUD's baseline model), reducing the underserved 
area share by three percentage points from HUD's 58 percent to ICF's 
55 percent would reduce the overall underserved areas goal by an 
additional 0.45 percentage point. Thus, the combined effect of ICF's 
assumptions would be a 0.66 percentage point reduction in the 
underserved areas goal. Fannie Mae did not comment directly on this 
parameter other than to emphasize that HUD's Case 2 is the ``most 
likely set of assumptions'' for estimating the underserved areas 
share (Fannie Mae Appendix, p. I-38). HUD's Case 2 (see above) would 
drop the baseline underserved area share for both SF and MF by two 
percentage points; therefore, Fannie Mae's assumptions are similar 
to ICF's.
---------------------------------------------------------------------------

    \61\ ICF incorrectly said HUD's baseline underserved areas share 
for MF rentals was 60 percent, rather than 58 percent (ICF Appendix, 
p. 47).
    \62\ Freddie Mac says ``ICF estimates the multifamily 
underserved share to be just 56 percent and the single-family renter 
underserved area share to be just 50 percent'' (at Appendix IV-24). 
However, ICF uses a 50 percent share in its projection model (ICF 
Appendix, p. 133); therefore, 55 percent is used here as the ICF 
number. Also, ICF's lower (upper bound) projection was 47 (53) 
percent for SF rental properties and 56 (58) percent for multifamily 
properties.
---------------------------------------------------------------------------

    In this analysis supporting the Final Rule, HUD is retaining the 
same underserved areas shares for SF and MF rental properties that 
it used in the 2004 proposed GSE rule. HUD conducted several 
additional analyses that support its SF rental baseline of 52 
percent and its MF rental baseline of 58 percent. These analyses are 
summarized below.
    A report by Abt Associates \63\ calculated 1990-based 
underserved areas shares using the 1995 AHS and POMS data, for (a) 
all SF rental properties, (b) all SF rental properties with a 
mortgage, (c) all SF rental properties with a conventional 
conforming mortgage, (d) all SF Rental properties with a new first 
mortgage, and (e) all SF rental properties with a new conventional 
conforming first mortgage. The underserved areas share for each of 
the groups of SF rental properties was approximately 50 percent. 
Adding a five percent adjustment to reflect 2000-based geography 
(see Table D.14a) would increase these estimates to 55 percent. 
While this information is dated, it is consistent with HUD's 52.0 
percent baseline and its 54.0 percent assumption in Case 3. Abt 
Associates also reported similar data for MF rental categories (a)-
(c). In this case the underserved areas share ranged from 51-54 
percent; adding 7-8 percent adjustment to reflect 2000-based 
geography would increase these estimates to 55-62 percent, again 
providing support for HUD's baseline (58 percent) and Case 3 (59 
percent) assumptions.\64\
---------------------------------------------------------------------------

    \63\ ``Affordability and Geographic Distribution of the Housing 
Stock and the Use of Mortgage Finance,'' Abt Associates, October 22, 
2001.
    \64\ As shown in Table D.12, excluding B&C investor loans 
reduces the market's underserved area share for SF investor loans. 
An adjustment for B&C investor loans is made within HUD's model, 
along the same lines as that B&C owner loans are excluded from the 
analysis. See Section F.3.c for further explanation.
---------------------------------------------------------------------------

    HUD had Census Bureau staff use the geocoded 2003 AHS file to 
calculate the distribution of the rental housing stock across served 
and underserved areas. This analysis, which was conducted in terms 
of 1990-Census geography, showed that 55.8 percent of the SF rental 
housing stock was located in underserved areas, as was 51.4 percent 
of the MF rental housing stock. Adding a five (7-8) percent 
adjustment to reflect 2000-based geography would increase these SF 
(MF) rental estimates to 60.8 (58.4-59.4) percent.
    HUD also had Census Bureau staff use the geocoded, 2001 
Residential Finance Survey (RFS) to calculate the distribution of 
rental mortgages and financed units across served and underserved 
areas. (See Table D.14b.) Unlike the AHS analysis mentioned above, 
this analysis was conducted in terms of 2000 Census geography. In 
2001, 54.1 percent of newly-mortgaged SF rental units were located 
in underserved areas, as were 61.5 of newly mortgaged MF rental 
units. Similar underserved area percentages were obtained for SF 
investor and MF loans that were originated in 1999 and 2000 and 
still surviving at the time of the RFS survey in 2001. \65\
---------------------------------------------------------------------------

    \65\ It is encouraging that the RFS underserved area percentage 
(31.7 percent) for SF-owner mortgages originated in metropolitan 
areas during 2001 was similar to the corresponding percentage (31.0 
percent) reported by HMDA.

---------------------------------------------------------------------------

[[Page 63876]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.098

    Finally, HUD examined the GSEs' own data. Between 1999 and 2003, 
58 percent of the SF rental units financed by GSE purchases were 
located in underserved areas. Between 1999 and 2002, 57 percent of 
the multifamily units financed by GSE purchases were located in 
underserved areas.
    Based on the above analyses, HUD retained the assumptions from 
the 2004 GSE proposed rule concerning underserved areas location of 
SF and MF rental properties. Specifically, the baseline underserved 
area share for SF rental units is 52 percent and that for MF rental 
units is 58 percent.
    2000-Based Underserved Area Market Estimates. Table D.15 reports 
the results of the projection model assuming 2000 geography. Since 
Table D.15 has the same interpretation as Table D.13, there is no 
need for a detailed explanation of it. Considering a 15.0-percent MF 
mix and a 8.5-percent investor mortgage share, the market share 
estimate is 36.9 percent if the overall (both home purchase and 
refinance) single-family-owner percentage for underserved areas is 
31 percent, which is the estimated 1994-2003 HMDA average as well as 
the recent 1999-2003 HMDA average.\66\
---------------------------------------------------------------------------

    \66\ In this case, the 2000-based underserved area percentages 
for years prior to 1999 (i.e. 1994 to 1998 in this example) are 
estimated by adding 4.9 percent to the corresponding 1990-based 
underserved area percentages reported in Table D.12. The 4.9 percent 
is the unweighted difference of the 2000-based and 1990-based 
underserved area shares for total (home purchase and refinance) SFO 
owner loans reported in Table D.14. This procedure will be used 
throughout this section.

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BILLING CODE 4210-27-C

[[Page 63878]]

    The above results are based on averages across both home 
purchase and heavy refinance environments. The analysis can also be 
conducted in terms of home purchase environments, focusing on the 
underserved area percentages for home purchase loans reported in the 
first column of Table D.15. Again, considering a 15.0-percent MF mix 
and a 8.5-percent investor mortgage share, the underserved area 
market estimates reported in Table D.15 are: 37.8 percent if the SFO 
owner underserved area percentage is 32.3 percent (1999-2003 average 
home purchase share); \67\ 37.6 if the SF owner percentage is 31.8 
percent (estimated average home purchase share from 1994-2003); 36.9 
percent if the owner percentage is 31 percent (approximate home 
purchase share in 1999 and 2001); 38.0 percent if the owner 
percentage is 32.5 percent (approximate home purchase percentage in 
2000 and 2002); and 39.0 percent if the owner percentage is 33.7 
percent (home purchase percentage in 2003). This analysis assumes 
that the underserved areas share of refinance loans is the same as 
those listed above for home purchase loans. But, as Table D.14a 
shows, in recent home purchase environments, the underserved areas 
share of refinance loans has been higher than that for home purchase 
loans, largely but not totally due to subprime refinance loans (see 
earlier discussion). In the year 2000, for example, the overall 
underserved areas share for SFO owner loans reached 34.2 percent; in 
this case, the market estimate is 39.4 percent in this case. 
However, the next highest overall (both home purchase and refinance 
loans) owner share is the 31.9 percent share in 1999, which yields 
at an overall market estimate of approximately 37.5 percent.
---------------------------------------------------------------------------

    \67\ The market share estimates are interpolated from Table 
D.15. For example, the overall market estimate for a SFO percentage 
of 32.3 percent is obtained by adding [.3*(38.4 minus 37.6)] to 
37.6, to obtain the 37.6 figure reported in the text.
---------------------------------------------------------------------------

    Fannie Mae reports its estimates of the 2000-Census-based 
underserved areas market in Table I.13 on page I-40. For SFO 
percentages of 30 percent and 32 percent (obtained by adding five 
percentage points to Fannie Mae's 1990-Census-based SFO percentages 
of 25 percent and 27 percent, respectively), Fannie Mae projects 
underserved area market shares of 35.1 percent and 36.8 percent, 
respectively. (It is interesting that these are the exact same 
market shares projected by HUD in Table D.15 for the ``Fannie Mae 
assumptions'' of 12.2-percent MF mix and an 8.0-percent investor 
mortgage share--suggesting that Fannie Mae's model produces the same 
results as HUD's model when the input assumptions are the same.) 
Fannie Mae concluded that the higher 36.8 percent market share was 
not appropriate because the SFO percentage of 32 percent was too 
high. However, as shown in Table D.14a, the 2000-based underserved 
area percentage for SFO home loans was greater than 32 percent in 
2000, 2002, and 2003.
    Multifamily Mix. As discussed earlier, compared with the low-mod 
and special affordable market estimates, the underserved area market 
estimates exhibit less variation as one moves from a 13.5 percent MF 
mix to 16.0 percent MF mix. For example, reducing the assumed 
multifamily mix from 16.0 percent to 13.5 percent reduces the 
overall market projection for underserved areas by only 0.6-0.7 
percentage points. This smaller MF mix effect occurs because the 
underserved area differentials between owner and rental properties 
are not as large as the low- and moderate-income and special 
affordable differentials reported earlier. For example, the 1999-
2003 average SF-owner underserved areas share (30.3 percent in Table 
D.14a) is only 22 percentage points less than the baseline SF-Rental 
underserved areas share (52.0); on the other hand, the 1999-2003 
average SF-owner special affordable share (15.7 percent) is about 42 
percentage points less than the baseline SF-Rental special 
affordable share (58.0 percent).
    As shown in Table D.15, ICF's MF mix of 14.25 percent produces 
results intermediate between HUD's 13.5 percent and 15.0 percent. 
Estimates of the underserved areas based on a MF mix of 14.2 percent 
are only 0.2 percentage points less than those based on a MF mix of 
15.0 percent.
    Investor Mortgage Share. Similarly, the market estimates differ 
only slightly with changes the investor mortgage share. Reducing the 
investor mix from 9.5 percent to 8.0 percent reduces the overall 
market projection for underserved areas by only 0.2-0.4 percentage 
points. If the 10.0 percent baseline from the 2004 proposed GSE rule 
were used in this analysis, the market estimates would be 
approximately 0.3 (0.2) percentage points higher relative to the 
results reported in Table D.15 for a baseline of 8.5 (9.0) percent. 
Fannie Mae's model combined a MF mix of 12.3 percent with an 
investor mortgage share of 8.0 percent. If the underserved area 
share of home purchase loans is 32.3 percent (the average for 1999-
2003), then the estimate for the overall underserved areas market is 
37.0 percent based on Fannie Mae's assumptions. In contrast, HUD's 
estimates (with a MF mix of 15.0 percent and 8.5 percent investor 
share) are 37.8 percent--almost one percentage point higher. If the 
underserved areas share of home purchase loans is at its 2003 level 
(33.7 percent), then Fannie Mae's assumptions result in a market 
estimate of 38.3 percent while HUD's assumptions (see previous 
sentence) result in a market estimate of 39.0 percent. In its 
projection model, ICF assumed an underserved areas share of 31.5 
percent for SF owner loans and produced an estimate of almost 37 
percent for the overall underserved areas market during 2005-2008 
(ICF Appendix, p.133).
    Different Underserved Area Shares for Rental Properties. Case 2 
(see Table D.9) considered slightly smaller underserved area 
percentages for rental properties (50 percent for SF rentals and 56 
percent for MF rentals), as compared with the baseline Case 1, which 
assumed 52 percent and 58 percent, respectively. Case 2 includes 
ICF's assumption (50 percent) for SF Rentals and is close to ICF's 
assumption (55 percent) for MF Rentals. Incorporating these Case 2 
assumptions reduces the underserved areas market estimate by only 
0.5 percentage points. For example, if the SFO home purchase share 
is 33 percent, then the overall underserved area estimate is 37.9 
percent under Case 2, as compared with 38.4 percent under Case 1 
(see Table D.15). As discussed earlier, the baseline Case 1 
assumptions offer a reasonable approach for estimating the 
underserved area market shares.
    Examples of Home Purchase Years. The above projection results 
for a home purchase environment can be compared with actual results 
for two home purchase years, 1999 and 2000 (see earlier description 
of these two years in the low-mod section, F.3.a). For 1999, the 
baseline model assumed a multifamily mix of 16.0 percent (see 
Section C) and a mortgage investor share of 8.2 percent (see Section 
D). Under these assumptions, the projected 1999 market estimate 
(based on 2000-Census data) is 37.6 percent; lowering the MF mix to 
15.0 (14.0) percent instead of 16.0 percent reduces the estimate 
only slightly to 37.3 (36.9) percent. For 2000, the baseline model 
assumed a multifamily mix of 17.2 percent and a mortgage investor 
share of 9.1 percent. Under these assumptions, the 2000 underserved 
areas market is estimated to be 39.7 percent. A lower MF mix--for 
example, 16.0 (15.0) percent instead of 17.2 percent--would reduce 
the estimated 2000 underserved areas market share slightly to 39.4 
(39.2) percent.\68\
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    \68\ The baseline 39.7 percent estimate for 2000 is 0.7 
percentage points lower than the 40.4 percent share reported in 
Section G.4 of Appendix D of the proposed rule, mainly for the 
reasons discussed in the previous footnote. The difference is mostly 
explained (a) by the different treatment of single-family rental 
mortgages and (b) by a 0.4 percentage point decline in HUD's 
projections (in terms of the 2000 Census data) of the 2000 
underserved areas percentage for SF owners.
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    For 1999, the 2000-based underserved area estimate (37.6 
percent) is 4.8 percentage points greater than the earlier-reported 
1990 based estimate (32.8 percent); for the year 2000, the 
differential is 5.0 percentage points (39.7 versus 34.7). This 
approximately five percentage point differential can be used to 
obtain estimates of 2000-based underserved area shares for the 
earlier home purchase years, 1995 to 1997. Table D.9 of the proposed 
GSE rule reported 1990-based underserved area shares of 33.9 percent 
for 1995 and 1997 and 33.4 percent for 1996. These estimates, after 
adjustments for a lower HMDA-based mortgage investor share and a 
lower-than-baseline MF mix, would remain in the 32-33 percent range. 
Adding five percentage points would place these estimates in the 37-
38 percent range in terms of 2000 Census geography.\69\ ICF's best 
estimates were approximately 37 percent for 1994-1997 and 39 percent 
for 1999 (ICF Appendix, p. 77); its lower bound estimates were 
approximately 34 percent during 1994-1997 and 1999, and 37 percent 
in 2000 (ICF Appendix, p.82). As noted earlier, ICF fills its report 
with numerous minimums that often

[[Page 63879]]

appear unbelievable, such as the 32.8 percent projection for the 
overall underserved market in 2000 (ICF Appendix, p. 83), a time 
when the SF owner underserved areas percentage was 35.7 percent 
itself (see Table 14a)--in this case, the rental portion of the 
market was below the underserved share for owners, rather than the 
typical case where the rental portion is more ``goals rich'' than 
the owner portion.
---------------------------------------------------------------------------

    \69\ As explained earlier in Section G.2, HUD re-estimated the 
underserved areas share for 1997 under the new assumptions (e.g., a 
lower, HMDA-based mortgage share for investor loans), obtaining a 
range of 32.0 percent (with a 16.3 MF mix) to 32.7 percent (with a 
19.3 percent MF mix). These estimates assume 1990 Census geography. 
Adding five percentage points to reflect 2000 Census geography 
yields estimates of 37.0 percent to 37.7 percent for the 1997 
underserved areas market.
---------------------------------------------------------------------------

    Market Volatility. Additional sensitivity analyses were 
conducted to reflect the volatility of the economy and mortgage 
market. Recession and high interest rate scenarios assumed a 
significant drop in the underserved area percentage for single-
family-owner mortgages. The single-family-owner home purchase 
percentage can go as low as 29 percent--which is almost 2.8 
percentage points lower than the 1994-2003 average of 31.8 percent, 
3.3 percentage points lower than the 1999-2003 average of 32.3 
percent, and 4.7 percentage points lower than the underserved areas 
share of home purchase loans in 2003--and the estimated market share 
for underserved areas remains about 35 percent. In a more severe 
case, the overall underserved market share would be 33-34 percent if 
the single-family-owner home purchase share fell to 27 percent (its 
1992 level), which is 5.3 percentage points lower than its 1999-2002 
average.
    Table D.11 shows the impact on the underserved areas market 
share under different assumptions about a refinancing environment. 
See the earlier discussion of the low-mod goal in Section F.2b for 
an explanation of the various model assumptions necessary to 
simulate a heavy refinance environment. The discussion focuses on 
the 65-percent refinance rate since that has characterized recent 
refinance waves. With respect to the underserved area 
characteristics of SF owner loans, two scenarios were considered: 
(A) Scenario A represents the average underserved area percentages 
for the last four refinance years (1998, 2001, 2002, and 2003)--32 
percent for home purchase loans and 30 percent for refinance loans; 
and (B) Scenario B represents the average underserved percentages 
for the two most recent refinance years (2002, and 2003)--33 percent 
for home purchase loans and 29 percent for refinance loans. Thus, 
there is a 2-4 percentage point differential between home purchase 
loans and refinance loans in a heavy refinancing environment.
    Under Scenario A, the underserved areas market shares varied by 
almost two percentage points (i.e., 1.6 percent), from 36.0 percent 
with a 12 percent MF mix to 34.4 percent with a 6 percent MF mix. 
These underserved area market shares are 3-5 percentage points lower 
than the underserved areas shares reported in Table D.15 for HUD's 
baseline home purchase environment. (The results were similar for 
Scenario B.) Notice that under Scenario A, the underserved areas 
share remains in the 34-35 percent range even if the MF mix falls to 
6-8 percent. In addition to higher-income borrowers dominating the 
single-family market, the share of the ``goals rich'' rental market 
declines in a refinancing wave, which tends to further reduce the 
underserved areas share of market activity. The right-hand column of 
Table D.11 shows that the rental share falls to the 17-22 percent 
range, or 4-9 percentage points less than the almost 26-percent 
rental share in HUD's baseline model. This contributes to the 
underserved areas share of the market typically falling to 34-36 
percent during a heavy refinancing period.
    Model estimates were also made for the recent refinancing years 
of 2001, 2002, and 2003. For 2001, the baseline model assumed a 
multifamily mix of 13.5 percent and a mortgage investor share of 7.8 
percent. Under these assumptions, the 2001 market estimate is 36.9 
percent.\70\ If the MF mix for 2001 had been 12.5 (12.0) percent, 
then the estimated underserved areas market share for 2001 would be 
36.6 (36.4) percent. For 2002, the baseline model assumed a 
multifamily mix of slightly over 11.0 percent and a mortgage 
investor share of 7.8 percent. Under these assumptions, the 2002 
underserved areas market is estimated to be 36.2 percent.\71\ A 
lower MF mix--for example, 10.5 (9.5) percent instead of 11 
percent--would reduce the estimated 2002 underserved areas market 
share to 36.0 (35.7) percent. ICF's best estimates for 1998, 2001, 
and 2002 were in the 34-35 percent range while its lower-bound 
estimates were in the 32-33 percent range.\72\
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    \70\ The baseline 36.9 percent estimate for 2001 is 0.8 
percentage point lower than the 37.7 percent share reported in 
Section G.4 of Appendix D of the proposed rule. The difference is 
mostly explained (a) by the different treatment in this Final Rule 
of single-family rental mortgages and (b) by a 0.2 percentage point 
decline in HUD's projections (in terms of the 2000 Census data) of 
the 2001 underserved areas percentage for SF owners.
    \71\ The baseline 36.2 percent estimate for 2002 is one 
percentage point lower than the 37.2 percent share reported in 
Section G.4 of Appendix D of the proposed rule. The difference is 
mostly explained (a) by the different treatment in this Final Rule 
of single-family rental mortgages and (b) by a 0.4 percentage point 
decline in HUD's projections (in terms of the 2000 Census data) of 
the 2002 underserved areas percentage for SF owners.
    \72\ For the years 1999 to 2002, Fannie Mae estimated a 2000-
Census-based underserved areas share of 37-38 percent, obtained by 
adding five percentage points to Fannie Mae's 32-33 percent estimate 
for the underserved areas market based on 1990 Census data. (See 
their Table I.9, page I-34.) This compares with HUD's estimate of 
37.1 percent to 37.6 percent for the same period.
---------------------------------------------------------------------------

    As noted in Section F.3.b, HUD did not receive 2003 HMDA data 
until early August 2004 and therefore HUD has not been able to 
develop a complete projection model for 2003. Still, some rough 
projections for 2003 are provided here for different assumptions 
about the MF mix, recognizing that firm data on the 2003 multifamily 
market are not available. Combining an investor mortgage share of 
8.2 from HMDA with different MF mixes produces the following 
estimates of the underserved areas market for 2003: 35.1 percent (MF 
mix of 8 percent); 34.7 percent (MF mix of 7 percent); and 34.4 
percent (MF mix of 6.0 percent).
    As shown by both the simulation results in Table D.10 and by the 
actual experience during 2001-2003, the underserved area share 
declines when refinances dominate the mortgage market. The above 
estimates suggest that the underserved areas share will not likely 
fall below 35 percent, although, as noted above, the estimates for 
2003 (around 35 percent) are somewhat speculative.
    Similar to 1999 and 2000, the 2001 and 2002 differences between 
the 1990-based and 2000-based underserved area market estimates are 
about five percentage points. For 2001, the 2000-based baseline 
estimate (36.9 percent) is 5.0 percentage points greater than the 
earlier-reported 1990 based estimate of 31.9 percent); for the year 
2002, the differential is 4.9 percentage points (36.2 versus 
31.3).\73\
---------------------------------------------------------------------------

    \73\ The differentials reported in Table D.14 for the three 
individual property types tend to be greater than five percentage 
points, which raises the question of why the overall differential is 
only five percentage points. As explained later, the upward 
adjustment to account for underserved areas in non-metropolitan 
areas is about 0.65 percentage point less using the 2000-based 
Census data than it was using the 1990-based Census data.
---------------------------------------------------------------------------

    The analysis in this section suggests that a reasonable range 
for the overall market share for underserved areas based on 2000 
geography might be 35-39 percent, which is consistent with the 30-34 
percent range estimated earlier based on 1990-based geography.
    Feasibility of Underserved Areas Goal in a Period of Heavy 
Refinancing. HUD received a number of public comments seeking a 
regulatory solution to the issue of the ability of the GSEs to meet 
the housing goals during a period when refinances of home mortgages 
constitute an unusually large share of the mortgage market. As 
explained in the Preamble, HUD is not addressing the refinance issue 
in this final rule. Elsewhere in the Federal Register, HUD is 
publishing an Advance Notice of Proposed Rulemaking that advises the 
public of HUD's intention to consider by separate rulemaking a 
provision that recognizes and takes into consideration the impact of 
high volumes of refinance transactions on the GSEs' ability to 
achieve the housing goals in certain years, and solicits proposals 
on how such a provision should be structured and implemented. HUD 
believes that it would benefit from further consideration and 
additional public input on this issue. HUD also notes that FHEFSSA 
provides a mechanism by which HUD can take into consideration market 
and economic conditions that may make the achievement of housing 
goals infeasible in a given year. (See 12 U.S.C. 1336(b)(e).)
    B&C Loans. The procedure for dropping B&C loans from the 
projections is the same as described in Section F.3.c for the Low- 
and Moderate-Income Goal. The underserved areas percentage for B&C 
loans is 52.0 percent, which is larger than the projected 
percentages for the overall market given in Table D.15. Thus, 
dropping B&C loans (as well as all subprime loans) will appreciably 
reduce the overall market estimates. Consider the case of a single-
family-owner percentage of 32 percent, which yields an overall 
market estimate for the underserved areas of 38.6 percent if B&C 
loans are included in the analysis. Dropping B&C loans from the 
projection model reduces the market share by one percentage point to 
37.6 percent, as reported in Table D.15. Dropping all

[[Page 63880]]

subprime loans (A-minus as well as B&C) would reduce the underserved 
areas market projection to 37.4 percent.
    Non-metropolitan Areas. As explained in Section G.3, in order to 
account for the much larger coverage of underserved areas in non-
metropolitan areas, 1.25 percent was added to the market share based 
on metropolitan area data, in order to arrive at a nationwide 
estimate of the market share for underserved areas. According to 
HMDA, underserved counties accounted for 42.7 percent of single-
family-owner mortgages originated in non-metropolitan areas during 
the 1999-to-2002 period, based on 1990 geography. With 2000 
geography and the new tract-based definition of underserved areas in 
non-metropolitan areas, the market share falls by 2.3 percentage 
points to 39.6 percent. This 2000-based underserved areas percentage 
of 39.6 percent for non-metropolitan areas is about eight percentage 
points less than the comparable percentage for metropolitan 
areas.\74\ This eight-point differential is lower than the 16-point 
differential used in the earlier 1990-based Census analysis. 
Assuming that non-metropolitan areas account for 13 percent of all 
single-family-owner mortgages and estimating that the single-family-
owner market accounts for 74.5 percent of newly-mortgaged dwelling 
units, then the non-metropolitan underserved area differential of 8 
percent would raise the overall market estimate by 0.78 percentage 
point--8 percentage points times 0.13 (non-metropolitan area 
mortgage market share) times 0.745 (single-family owner mortgage 
market share). Based on this calculation, if the 8 point 
differential reflected actual market conditions, then the 
underserved areas market share estimated using metropolitan area 
data should be increased by 0.78 percentage point to account for the 
effects of underserved counties in non-metropolitan areas, based on 
2000 geography. A more conservative adjustment of 0.65 percentage 
points was made in Table D.15, which reports the results of the 
projection model.
---------------------------------------------------------------------------

    \74\ Between 1999 and 2002, 2000-based underserved census tracts 
accounted for 31.4 percent (unweighted annual average) of all 
mortgages in metropolitan areas. This 1999-02 average percentage for 
single-family owners in metropolitan area is lower than the 
underserved area percentage reported in previous paragraphs. To be 
comparable with the non-metropolitan data, these metropolitan area 
data do not include loans originated by lenders that specialize in 
manufactured housing loans and B&C loans, excluding these loans 
lowers the underserved areas share.
---------------------------------------------------------------------------

    Section G.3 reported that excluding manufactured housing loans 
(as well as small loans less than $15,000) reduced the overall 
underserved area market estimates based on 1990 geography by less 
than one percentage point (roughly three-quarters of a percentage 
point). Excluding manufactured housing loans leads to a similar 
reduction for the market estimates based on 2000 geography. As 
reported earlier, the small loan and manufactured housing effects 
can be considered separately. Dropping only manufactured housing 
loans would reduce the market estimates by approximately three-
fourths of a percentage point. ICF argued that loans with less than 
$15,000 should be excluded. The impact of doing this on the market 
estimates would be about one-third of a percentage point. ICF also 
considered scenarios where one-half of manufactured loans would be 
dropped, as well as small loans less than $15,000. The impact of 
doing this on the market estimates would be three-fifths of a 
percentage point.
    The above analyses of the effects of less affordable market 
conditions, different assumptions about the size of the rental 
market, and dropping different categories of loans from the market 
definition suggest that the 35-39 percent range described earlier is 
a reasonable range for the market estimate for underserved areas 
based on the projection model described earlier. This range 
incorporates market affordability conditions that are more adverse 
than have existed recently and it excludes B&C loans from the market 
estimates.

5. Conclusions

    Based on the above findings as well as numerous sensitivity 
analyses, HUD concludes that 35-39 percent is a reasonable estimate 
of mortgage market originations that would qualify toward 
achievement of the Geographically Targeted Goal if purchased by a 
GSE. The 35-39 percent range is higher than the market range in the 
2000 Rule mainly because it is based on 2000 Census geography which 
includes more underserved census tracts than 1990 Census geography. 
HUD recognizes that shifts in economic and housing market conditions 
could affect the size of this market; however, the market estimate 
allows for the possibility that adverse economic conditions can make 
housing less affordable than it has been in the last few years. In 
addition, the market estimate incorporates a range of assumptions 
about the size of the multifamily market and excludes B&C loans.

H. Size of the Conventional Conforming Market for the Special 
Affordable Housing Goal

    This section presents estimates of the conventional conforming 
mortgage market for the Special Affordable Housing Goal. The special 
affordable market consists of owner and rental dwelling units which 
are occupied by, or affordable to: (a) Very-low-income families; or 
(b) low-income families in low-income census tracts; or (c) low-
income families in multifamily projects that meet minimum income 
thresholds patterned on the low-income housing tax credit 
(LIHTC).\75\ HUD estimates that the special affordable market is 23-
27 percent of the conventional conforming market.
---------------------------------------------------------------------------

    \75\ There are two LIHTC thresholds: at least 20 percent of the 
units are affordable at 50 percent of AMI or at least 40 percent of 
the units are affordable at 60 percent of AMI.
---------------------------------------------------------------------------

    HUD is proposing to establish each GSE's special affordable 
multifamily subgoal as 1.0 percent of its average annual dollar 
volume of total (single-family and multifamily) mortgage purchases 
over the 2000-2002 period. In dollar terms, the Department's 
proposal is $5.49 billion per year in special affordable multifamily 
purchases for Fannie Mae, and $3.92 billion for Freddie Mac. The 
multifamily special affordable goal, as well as the special 
affordable home purchase subgoal, are discussed further in Appendix 
C.
    Section F described HUD's methodology for estimating the size of 
the low- and moderate-income market. Essentially the same 
methodology is employed here except that the focus is on the very-
low-income market (0-60 percent of Area Median Income) and that 
portion of the low-income market (60-80 percent of Area Median 
Income) that is located in low-income census tracts. Data are not 
available to estimate the number of renters with incomes between 60 
and 80 percent of Area Median Income who live in projects that meet 
the tax credit thresholds. Thus, this part of the Special Affordable 
Housing Goal is not included in the market estimate.

1. Special Affordable Shares by Property Type

    The basic approach involves estimating for each property type 
the share of dwelling units financed by mortgages that are occupied 
by very-low-income families or by low-income families living in low-
income areas. HUD combined mortgage information from HMDA, the 
American Housing Survey, the Property Owners and Managers Survey and 
the recently released 2001 Residential Finance Survey in order to 
estimate these special affordable shares.

a. Special Affordable Owner Percentages

    HMDA data for the percentage of single-family-owners that 
qualify for the Special Affordable Goal are reported in Table D.16. 
That table also reports data for the two components of the Special 
Affordable Goal--very-low-income borrowers and low-income borrowers 
living in low-income census tracts. Focusing first on home purchase 
loans, HMDA data show that the special affordable share of the 
market has followed a pattern similar to that discussed earlier for 
the low- and moderate-income loans. The percentage of special 
affordable borrowers increased significantly between 1992 and 1994, 
from 10.4 percent of the conforming market in 1992 to 12.6 percent 
in 1993, and then to 14.1 percent in 1994. Between 1995 and 1998, 
the special affordable market was in the 14-16 percent range, 
averaging 15.1 percent. Over the past five years (1999-2003), the 
special affordable share of the home purchase loans has averaged 
16.4 percent. It was about 17 percent during 1999 and 2000 and 16 
percent during the most recent three years, 2001 to 2003.
BILLING CODE 4210-27-P

[[Page 63881]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.100

    Considering all (home purchase and refinance) loans during 
recent ``home purchase'' environments, the special affordable share 
averaged 18.7 percent during 1999-2000, over three percentage points 
more than the 15.4 percent average between 1995 and 1997. Excluding 
B&C (all subprime) loans from the analysis reduces this differential 
only slightly to 2.8 (2.4) percentage points. As mentioned earlier, 
lending patterns could change with sharp changes in the economy, but 
the fact that there have been several years of strong affordable 
lending suggests that the special affordable market has changed in 
fundamental ways from the mortgage market of the early 1990s.
    Except for the four years of heavy refinancing (1998, 2001, 
2002, and 2003), the special affordable share of the refinance 
market has recently been higher than the special affordable share of 
the home purchase market--a pattern discussed in Section F for low-
mod and very-low-income loans. During 1999 (2000), for example, the 
special affordable share of the refinance market was 19.2 (22.6) 
percent, compared with 17.3 (16.9) percent for the home loan market. 
The higher special affordable percentages for refinance loans are 
reduced or even eliminated if subprime loans are excluded from the 
analysis. As shown in Table D.16, excluding B&C loans from the data 
practically eliminates the refinance-home-purchase differential for 
1999 and reduces the differential for 2000 to 4.2 percentage points 
(from 5.7 percentage points). Going further and excluding A-minus 
loans from the year 2000 data would reduce the differential to 2.7 
percentage points. HUD's projection model excludes B&C loans and 
sensitivity analyses will show the effects on

[[Page 63882]]

the overall special affordable market of excluding all single-family 
subprime loans.
    New 2000-Based Census Geography and New OMB Metropolitan Area 
Definitions. Going forward, HUD will be re-benchmarking its median 
incomes for metropolitan areas and non-metropolitan counties based 
on 2000 Census incomes, will be defining low-income census tracts 
(which are included in the definition of special affordable) in 
terms of the 2000 Census geography, and will be incorporating the 
effects of the new OMB metropolitan area definitions. As discussed 
earlier in Section F, HUD projected the effects of these three 
changes on the special affordable shares of the market for the years 
1999-2003; the results for special affordable loans are reported in 
the top portion of Table D.8b. Under the historical MSA-based data, 
the (unweighted) average special affordable share of the 
conventional conforming market was 16.4 (16.3) percent for home 
purchase (total) loans (see Table D.16); the corresponding average 
with the CBSA-based projected data was 16.4 (16.4) percent, or 
practically the same. Given these small differences there is no need 
to adjust the overall market estimates reported below to account for 
the new data. However, it should be noted that the most recent year 
of 2003 does show a rather larger difference--the special affordable 
share of home purchase loans under the projected CBSA approach is 
16.9 percent, which is a full percentage point higher than the 
special affordable share of 15.9 percent under historical data.\76\
---------------------------------------------------------------------------

    \76\ As noted earlier, this discrepancy could be due to mis-
measurement from the technique for apportioning 2003 data, which is 
defined in 2000-census geography, to a 1990-based geography.
---------------------------------------------------------------------------

    For the other two property types (single-family rental and 
multifamily), comparisons between projected and historical special 
affordable percentages were made using the GSEs' data. For single-
family rental mortgages, the weighted average of Fannie Mae's 
(Freddie Mac's) special affordable percentage for the years 1999 to 
2003 was 48.2 (48.7) percent using the historical data, compared 
with 49.6 (49.5) percent using the projected data. For multifamily 
mortgages, the weighted average of Fannie Mae's (Freddie Mac's) 
special affordable percentage for the years 1999 to 2003 was 50.9 
(48.7) percent using historical data, compared with 51.6 (51.5) 
percent using the projected data. These comparisons suggest little 
difference between the historical and projected special affordable 
shares for rental properties. HUD also projected the overall special 
affordable percentage for each GSE. For the overall special 
affordable goal (considering all three property types), the 
unweighted average of Fannie Mae's (Freddie Mac's) special 
affordable percentage for the years 1999 to 2002 was 20.0 (18.9) 
percent using the projected data, compared with 20.0 (18.9) percent 
using the historical data. There is little difference in the GSEs' 
average special affordable performance between the projected and 
historical data.

b. Very-Low-Income Rental Percentages

    Table D.14 in Appendix D of the 2000 Rule reported the 
percentages of the single-family rental and multifamily stock 
affordable to very-low-income families. According to the AHS, 59 
percent of single-family units and 53 percent of multifamily units 
were affordable to very-low-income families in 1997. The 
corresponding average values for the AHS's six surveys between 1985 
and 1997 were 58 percent and 47 percent, respectively. As discussed 
earlier in Section F, an important issue concerns whether rent data 
based on the existing rental stock from the AHS can be used to proxy 
rents of newly mortgaged rental units. HUD's analysis of POMS data 
during the 2000 rule-making process suggested that it could--
estimates from POMS of the rent affordability of newly-mortgaged 
rental properties are quite consistent with the AHS data on the 
affordability of the rental stock. Fifty-six (56) percent of single-
family rental properties with new mortgages between 1993 and 1995 
were affordable to very-low-income families, as were 51 percent of 
newly-mortgaged multifamily properties. These percentages for newly-
mortgaged properties from the POMS are similar to those reported 
above from the AHS for the rental stock. Based on this POMS 
analysis, HUD's baseline model in the 2004 proposed GSE rule assumed 
that 50 percent of newly-mortgaged, single-family rental units, and 
47 percent of multifamily units, were affordable to very-low-income 
families. (See further discussion of this issue in Section H.1.d)

c. Low-Income Renters in Low-Income Areas

    HMDA does not provide data on low-income renters living in low-
income census tracts. As a substitute, HUD used the POMS and AHS 
data. As explained in the 2000 GSE Rule, the share of single-family 
and multifamily rental units affordable to low-income renters at 60-
80 percent of area median income (AMI) and located in low-income 
tracts was calculated using the internal Census Bureau AHS and POMS 
data files.\77\ The POMS data showed that 8.3 percent of the 1995 
single-family rental stock, and 9.3 percent of single-family rental 
units receiving financing between 1993 and 1995, were affordable at 
the 60-80 percent level and were located in low-income census 
tracts. The POMS data also showed that 12.4 percent of the 1995 
multifamily stock, and 13.5 percent of the multifamily units 
receiving financing between 1993 and 1995, were affordable at the 
60-80 percent level and located in low-income census tracts.\78\ The 
baseline analysis in HUD's proposed GSE rule assumed that 8 percent 
of the single-family rental units and 11.0 percent of multifamily 
units are affordable at 60-80 percent of AMI and located in low-
income areas.
---------------------------------------------------------------------------

    \77\ Affordability was calculated as discussed earlier in 
Section F, using AHS monthly housing cost, monthly rent, number of 
bedrooms, and MSA location fields. Low-income tracts were identified 
using the income characteristics of census tracts from the 1990 
Census of Population, and the census tract field on the AHS file was 
used to assign units in the AHS survey to low-income tracts and 
other tracts. POMS data on year of mortgage origination were 
utilized to restrict the sample to properties mortgaged during 1993-
1995.
    \78\ During the 1995 rule-making process, HUD examined the 
rental housing stock located in low-income zones of 41 metropolitan 
areas surveyed as part of the AHS between 1989 and 1993. While the 
low-income zones did not exactly coincide with low-income tracts, 
they were the only proxy readily available to HUD at that time. 
Slightly over 13 percent of single-family rental units were both 
affordable at the 60-80 percent of AMI level and located in low-
income zones; almost 16 percent of multifamily units fell into this 
category.
---------------------------------------------------------------------------

    Combining the assumed very-low-income percentage of 50 percent 
(47 percent) for single-family rental (multifamily) units with the 
assumed low-income-in-low-income-area percentage of 8 percent (11 
percent) for single-family rental (multifamily) units yields the 
special affordable percentage of 58 percent (58 percent) for single-
family rental (multifamily) units. This was the baseline case in the 
2004 proposed GSE rule.

d. Comments on the Special Affordable Rental Share and Additional 
Analysis

    Both ICF and Fannie Mae commented that HUD overstated the 
special affordable share of the single-family rental and multifamily 
rental markets. They argued that updated 2001 AHS data showed that 
the affordability of the rental housing stock had declined since HUD 
had conducted its POMS and AHS analyses in 1995 and 1997, 
respectively. For both single-family (SF) and multifamily (MF) 
rentals, ICF used a special affordable range of 47-53 percent, with 
a baseline of 50 percent. ICF's special affordable range is much 
less than both HUD's 53-61 percent range (58 percent baseline) for 
single-family rentals and HUD's 54-62 percent range for multifamily 
rentals (also a 58 percent baseline). Since SF and MF rentals 
account for about 25 percent of financed units in HUD's model, 
reducing the SF and MF baselines from 58 percent (HUD's baseline) to 
50 percent (ICF's baseline) would reduce the overall special 
affordable market estimate by two percentage points. Thus, this is 
an important issue.
    Based on its analysis of the AHS (see Fannie Mae Appendix, I-31-
I-32), Fannie Mae concluded that the very-low-income share for 
single-family rental properties had fallen from 58.3 percent in 1997 
to 53.0 percent in 2001; similarly, the very-low-income (VLI) share 
of multifamily rental properties had fallen from 52.0 percent to 
44.9 percent over this same period. (By comparison, ICF estimated 
that 47 percent of the SF rental stock and 42 percent of the MF 
rental stock were affordable to VLI families.) In its analysis, 
Fannie Mae provides a weight of 0.07 to the VLI share (25.7 percent) 
of recently-constructed single-family rental units in the AHS, and 
the residual 0.93 weight to the VLI share (53.6 percent) of the 
remaining existing units in the AHS. While Fannie Mae uses a VLI 
share of 46 percent for single-family rentals in its market sizing 
models, applying these weights to the 2001 AHS data (reported by 
Fannie Mae in Table I.7 on p. I-32) yields approximately 52 percent 
for the VLI share of single-family rental properties. Similarly, for 
multifamily properties, Fannie Mae provides a weight of 0.11 to the 
VLI share (22.2 percent) of recently-constructed multifamily rental 
units in the AHS, and the residual 0.89 weight to the VLI share 
(45.7 percent) of the remaining existing units in the AHS. In this 
case,

[[Page 63883]]

applying the above weights to the 2001 AHS data yields 43 percent 
for the VLI share of multifamily rental properties--a figure similar 
to the 41-percent VLI share that Fannie Mae uses in its market 
sizing models. After computing a VLI share of 46 percent for SF 
rentals, Fannie Mae adds 8 percent to account for low-income renters 
living in low-income census tracts (the second component of the 
special affordable category); this yields 54 percent for the special 
affordable share of SF rentals. After computing a VLI share of 41 
percent for MF rentals, Fannie Mae adds 11 percent to account for 
low-income renters living in low-income census tracts; this yields 
52 percent for the special affordable share of MF rentals. Thus, 
Fannie Mae's estimates are intermediate between ICF's (50 percent) 
and HUD's (58 percent). Since SF rentals account for 10.6 percent of 
financed units in HUD's model, reducing the SF baseline from 58 
percent (HUD's baseline) to 54 percent (Fannie Mae's baseline) would 
reduce the overall special affordable market estimate by 0.42 
percentage points. Since MF rentals account for 15.0 percent of 
financed units in HUD's model, reducing the MF baseline from 58 
percent (HUD's baseline) to 52 percent (Fannie Mae's baseline) would 
reduce the overall special affordable market estimate by 0.90 
percentage points. Combining these two reductions yields a 1.32 
percentage point reduction in the overall special affordable market.
    HUD is retaining its baseline of 58 percent for the special 
affordable share of both SF and MF rentals. Several sets of analyses 
led to this decision.
    HUD updated its analysis with 2001 and 2003 AHS data. Using 
ICF's assumptions for an AHS analysis (see ICF Appendix, p. 45), the 
2003 AHS data showed that 57 percent (67 percent) of single-family 
(multifamily) rental units would qualify as being affordable to VLI 
families. This analysis of the 2003 AHS used a new geocoded file 
that identified the specific metropolitan area or county location 
for each observation in the AHS. This allowed HUD to link accurate 
area median incomes (used to determine affordability) to each AHS 
observation, which represents a substantial improvement over 
previous AHS analyses that did not have the specific household 
location and thus had to rely on estimates of area median income in 
order to compute affordability ratios. This more accurate approach 
appears to produce higher affordability estimates than earlier 
analyses based on the non-geocoded AHS.
    To derive an overall special affordable percentage, one must add 
the second component of the special affordable category--low-income 
renters living in low-income areas--to the VLI share. HUD's analysis 
of POMS data and its analysis of 2003 AHS geocoded data suggest that 
low-income SF renters in low-income areas account for 22 percent of 
all SF low-income renters; GSE data for 2001 and 2002 suggest a 
slightly higher percentage.\79\ With respect to MF properties, HUD's 
analysis of POMS data and its analysis of 2003 AHS geocoded data 
suggest that low-income MF renters in low-income areas accounted for 
24-25 percent of all MF low-income renters; GSE data for 2001 and 
2002 suggest a slightly lower percentage (21 percent). These shares 
can be applied to the 2003 AHS results for low-income renters. For 
SF rentals, the 22 percent share for low-income renters living in 
low-income census tracts can be multiplied by the 20 percent figure 
that the 2003 AHS produces for low-income SF renters, yielding 
estimate of 4.4 percent. This 4.4 percent is added to the VLI 
percentage of 67 percent for SF rentals to arrive at a special 
affordable estimate of 71 percent, based on the 2003 AHS. For MF 
rentals, the 25 percent share for low-income renters living in low-
income census tracts can be multiplied by the 27 percent figure that 
the 2003 AHS produces for low-income MF renters, yielding an 
estimate of 6.7 percent.\80\ This 6.7 percent is added to the VLI 
percentage of 57 percent for MF rentals to arrive at a special 
affordable estimate of 63 percent, based on the 2003 AHS. These 2003 
AHS special affordable shares--67 percent for SF rental units and 63 
percent for MF rental units--support HUD's use of a 58-percent 
baseline as the special affordable share of both SF and MF rental 
properties.
---------------------------------------------------------------------------

    \79\ Fannie Mae's data exhibited some variation, standing at 33 
percent in 2001 and 19 percent in 2001. Freddie Mac's percentage was 
29 percent in both years.
    \80\ These adjustments for low-income renters living in low-
income areas may be conservative. For SF (MF) rentals, the 2001 and 
2002 figures for the GSEs were in the nine (eight) percent range.
---------------------------------------------------------------------------

    It is interesting to compare HUD's 58-percent baseline with the 
actual performance of Fannie Mae and Freddie Mac. For single-family 
rental mortgages, the weighted average of both Fannie Mae's and 
Freddie Mac's special affordable percentage for the years 1999 to 
2003 was about 50 percent using projected CBSA data. For multifamily 
mortgages, the weighted average of Fannie Mae's special affordable 
percentage for the same years was 49 percent, while Freddie Mac's 
percentage was 52 percent. As ICF notes, the GSEs' below market 
performance may be due to their limited participation in the small 
multifamily market (ICF Appendix, p. 47).

2. Size of the Special Affordable Market

    The size of the special affordable market depends in large part 
on the size of the single-family rental and multifamily markets and 
on the special affordable percentages of both owners and renters. 
Therefore, this section conducts several sensitivity analyses around 
these market parameters. As in the previous sections, this section 
initially assumes a refinance rate of 35 percent, which means that 
it initially focuses on a home purchase or low-refinancing 
environments. After presenting these results, market estimates 
reflecting a heavy refinance environment will be presented. In the 
2000 GSE Rule, HUD assumed that the special affordable share of 
refinance loans was 1.4 percentage points lower than the special 
affordable share of borrowers purchasing a home. However, as 
discussed earlier, the special affordable share of refinance loans 
equaled or was greater than the special affordable share of home 
purchase loans during home purchase environments such as 1995-97 or 
1999-2000; thus, the assumption of a lower special affordable share 
for refinance loans is initially dropped from the analysis but will 
be reintroduced during the sensitivity analysis and the discussion 
of heavy refinancing environments. If the special affordable share 
of refinance loans were assumed to be one percentage point less than 
that of home purchase loans, then the market shares in Table D.17 
would be approximately one-quarter percentage point lower.\81\
---------------------------------------------------------------------------

    \81\ This is obtained by multiplying (a) 1.0 percentage point by 
(b) the refinance rate of 0.35 by (c) the 0.745 property share for 
SF owner loans.
---------------------------------------------------------------------------

    Considering a 15.0-percent MF mix and a 8.5-percent investor 
mortgage share, the special affordable market estimates reported in 
Table D.17 are: 27.3 percent if the owner percentage is 17 percent 
(home purchase share for 1999 and 2000); 26.8 if the owner 
percentage is 16.4 percent (average home purchase share from 1999-
2003); 26.5 percent if the owner percentage is 16 percent (home 
purchase share for 1998, 2001, 2002, and 2003); and 25.7 percent if 
the owner percentage is 15 percent (home purchase average from 1995-
97). Considering a range of 13.5-16.0 for the MF mix and a range of 
8.5-9.0 for the investor mortgage share, the special affordable 
market estimates reported in Table D.17 are: 26.7-27.9 percent if 
the owner percentage is 17 percent; 26.2-27.4 percent if the owner 
percentage is 16.4 percent; 25.9-27.1 percent if the owner 
percentage is 16 percent; and 25.1-26.3 percent if the owner 
percentage is 15 percent.
BILLING CODE 4210-27-P

[[Page 63884]]

[GRAPHIC] [TIFF OMITTED] TR02NO04.101

BILLING CODE 4210-27-C

[[Page 63885]]

    If the special affordable percentage for home purchase loans 
fell to 13 percent--or by three percentage points below its 1995-
2003 average level of approximately 16 percent--then the overall 
market estimate would be about 24 percent under the baseline 
assumptions. Thus, 24 percent is consistent with a rather 
significant decline in the special affordable share of the single-
family home purchase market. A 24 percent market estimate allows for 
the possibility that adverse economic and housing affordability 
conditions could keep special affordable families out of the housing 
market. On the other hand, if the special affordable home purchase 
percentage stays at its recent levels (15-17 percent), the market 
estimate is in the 26-27 percent range.
    Different Special Affordable Shares for Rental Properties. Case 
2 (see Table D.9) considered smaller special affordable percentages 
for rental properties (53 percent for SF rentals and 54 percent for 
MF rentals), as compared with the baseline Case 1, which assumed 58 
percent for both property types. Case 2 assumptions are close to 
Fannie Mae's assumptions--54 percent for SF Rentals and 52 for MF 
Rentals. Incorporating the Case 2 assumptions reduces the special 
affordable market estimate by 1.2 percentage points. For example, if 
the SFO home purchase share is 17 percent, then the overall special 
affordable estimate is 26.1 percent under Case 2, as compared with 
27.3 percent under Case 1 (see Table D.17).
    ICF's assumptions were even lower, 50 percent for both SF and MF 
rentals, a figure that is eight percentage points lower than HUD's 
baseline Case 1 assumption of 58 percent for each of these two 
property types. Given that these two property types account for 25 
percent of all financed dwelling units, using ICF's 50-percent 
assumption (instead of HUD's 58-percent assumption) would reduce the 
overall special affordable market shares in Table D.17 by two 
percentage points. As discussed above, HUD's baseline Case 1 
assumptions offer a reasonable approach for estimating the special 
affordable market shares.
    Multifamily Mix. The volume of multifamily activity is also an 
important determinant of the size of the special market. While 
Section C explained the rationale for HUD's 15.0 percent range, it 
is useful, given the uncertainty surrounding the size of the 
multifamily market, to consider the effects of lower multifamily mix 
assumptions, even in a home purchase environment. Assuming a 13.5 
percent MF mix reduces the overall special affordable market 
estimates by 0.4 percentage points compared with a 15 percent MF 
mix, and by 1.0 percentage point compared with a 16.0 percent mix. 
For example, when the special affordable share of the home purchase 
market is at 16.4 percent (its 1999-2003 average), the special 
affordable share of the overall market is 26.2 percent assuming a 
13.5 percent multifamily mix, compared with 26.8 (27.4) percent 
assuming a 15 (16.0) percent multifamily mix.
    As shown in Table D.17, the ICF's MF mix of 14.2 percent 
produces results intermediate between HUD's 13.5 percent and 15.0 
percent. Estimates of the special affordable market based on a MF 
mix of 14.2 percent are only 0.3 percentage points less than those 
based on a MF mix of 15.0 percent. Fannie Mae's model combined an 
even lower MF mix of 12.3 percent with an investor mortgage share of 
8.0 percent. If the special affordable share of home purchase loans 
is 16.4 percent (the 1999-2003 average), then the estimate for the 
overall special affordable market is 25.2 percent based on Fannie 
Mae's assumptions. In contrast, HUD's estimates (with a MF mix of 
15.0 percent and 8.5-9.0 percent investor share) are 26.8-27.0 
percent `` about one and a half percentage points higher. If the 
special affordable share of home purchase loans is 16 percent (its 
recent 2001-2003 level), then Fannie Mae's assumptions result in a 
market estimate of 25.2 percent while HUD's assumptions (see 
previous sentence) result in market estimates of 26.5-26.7 percent.
    Investor Mortgage Share. As shown in Table D.17, increasing the 
investor mortgage share by one percentage point from 8.0 percent to 
9.0 percent increases the special affordable market estimate by 
approximately 0.4-0.5 percentage point. If the 10.0 percent baseline 
from the 2004 proposed GSE rule were used in this analysis, the 
market estimates would be approximately 0.6 (0.4) percentage points 
higher relative to the results reported in Table D.15 for a baseline 
of 8.5 (9.0) percent.
    Examples of Home Purchase Years. The above projection results 
for a home purchase environment can be compared with actual results 
for two home purchase years, 1999 and 2000, which were characterized 
by refinance rates of 34 percent and 29 percent, respectively. For 
1999, the baseline model assumed a multifamily mix of 16.0 percent 
and a mortgage investor share of 8.2 percent. Under these 
assumptions, the 1999 market estimate is 27.9 percent; if the 1999 
MF mix was lower--for example, 15.0 (14.0) percent instead of 16.0 
percent--then the estimate of the 1999 special affordable market 
share would be 27.5 (27.2) percent.
    The 2004 proposed rule (Table D.9 in Appendix D) reported a 
higher baseline market estimate for 1999 of 29.2 percent, as 
compared with the 27.9 percent reported in the previous paragraph--a 
differential of 1.3 percentage points. The difference is largely due 
to the treatment of single-family rental mortgages. For example, 
using the proposed rule's 10-percent assumption for the mortgage 
investor share (instead of the lower 8.2 percent HMDA-based mortgage 
investor shares reported in the text) would increase the 1999 
estimate by 0.8 percentage points to 28.7 percent, only 0.5 
percentage points lower than the 29.2 percent reported in the 
proposed rule. Other more minor changes that lower market estimate 
included: (a) Further reducing the SF mortgage investor share by 
excluding B&C investor loans from the HMDA data (see Section C); (b) 
using 1.6 percent (instead of 2.0 percent) for the mortgage share of 
single-family 2-4 property owners; and (c) using slightly lower 
dwelling-units-per-mortgage assumptions for SF 2-4 properties (2.20 
instead of 2.25) and for SF investor mortgages (1.30 instead of 
1.35). These changes, leading to this 1.3 percentage point 
differential, also affect the estimates reported in Table D.9 of 
Appendix D of the proposed rule for the three home purchase 
environments prior to 1999--28.9 percent for 1995, 28.7 for 1996, 
and 28.8 percent for 1997.\82\ Given (a)-(c) and the fact that the 
HMDA-reported mortgage investor share was approximately eight 
percent during these three years (instead of the assumed 10 percent 
in the earlier 1995-97 analysis), these estimates should probably be 
reduced by the above-mentioned 1.3 percentage points, which would 
place them at 27-28 percent assuming no adjustment in the baseline 
MF mix, and at 26-27 percent assuming a MF mix three percentage 
points lower than the baseline MF mix.\83\
---------------------------------------------------------------------------

    \82\ These three estimates were initially reported in HUD's 2000 
Final Rule, and repeated in Table D.9 of Appendix D of the 2004 
proposed GSE rule.
    \83\ To provide some confirmation for these 1995-1997 estimates, 
HUD went back and re-estimated the model for 1997. As shown in Table 
D.9 of the 2004 GSE Proposed Rule (as well as in Table D.15 of the 
2000 GSE Rule), HUD had earlier estimated a special affordable share 
of 28.8 percent for 1997 (which was practically the same as the 
28.9-percent share estimated for 1995 and the 28.7-percent share 
estimated for 1996). With a lower investor share (8.4 percent 
instead of 10.0 percent) and other changes mentioned in the text, 
the new estimate for the 1997 special affordable market was 28.0 
assuming a multifamily mix of 19.3 percent. If the multifamily mix 
is reduced to 17.3 (16.3) percent, the special affordable share of 
the 1997 market is 27.1 (26.7) percent. The 26.7-28.0 percent range 
for 1997 is consistent with the 1995-1997 ranges reported in the 
text.
---------------------------------------------------------------------------

    For 2000, the baseline model assumed a multifamily mix of 17.2 
percent and a mortgage investor share of 9.1 percent. Under these 
assumptions, the 2000 special affordable market is estimated to be 
29.1 percent. A lower MF mix--for example, 15.0 percent instead of 
17.2 percent--would reduce the estimated 2000 low-mod market share 
to 28.2 percent.\84\
---------------------------------------------------------------------------

    \84\ Using the projected CBSA data (instead of the historical 
1990-based MSA data) did not change the special affordable market 
estimate in either 1999 or 2000.
---------------------------------------------------------------------------

    ICF's best estimates for the special affordable market were 25-
26 percent in 1995, 1997, 1999, and 2000, and a particularly low 23 
percent for 1996 (ICF Appendix, p. 94). Its lower bound estimates 
were 22-23 percent for 1997 and 1999, 24 percent for 1995 and 2000, 
and 21 percent for 1996 (ICF Appendix, p. 99). As discussed earlier, 
two percentage points of the HUD-ICF differential involves ICF's 
lower assumptions about the special affordable characteristics of 
rental loans. Given that the SFO percentage was 18-19 percent during 
1999 and 2000 (see Table D.16), ICF's 23-24 estimates for 1999 and 
2000 are in need of further explanation.
    Heavy Refinancing Environments. The special affordable share of 
the overall market declines when refinances dominate the market. 
Section F.3c, which presents the low-mod market estimates, explained 
the assumptions for incorporating a refinance environment into the 
basic projection model for 2005-08. Briefly, they are: the refinance 
share of single-family mortgages was increased to 65 percent (from 
35 percent); the multifamily mix was allowed to vary from 6 to 12 
percent; the market share for subprime

[[Page 63886]]

loans was reduced to 8.5 percent (from 12 percent); and the mortgage 
investor share was set at 8.0 percent (its average during recent 
refinancing waves). With respect to MF mixes, it is likely that an 
11-12 percent MF mix characterized 2001, 9-11 percent characterized 
2002, and less than 7 percent characterized 2003, although there is 
some uncertainty with these estimates. In a refinancing wave, the 
special affordable percent is typically lower for refinance loans 
than home purchase loans, as middle- and high-income borrowers 
dominate the market. With respect to the special affordable 
characteristics of SF owner loans, the refinancing analysis assumed 
16 percent for home purchase loans and 14 percent for refinance 
loans, which were the average special affordable percentage for the 
last four refinance years (1998, 2001, 2002, and 2003). There has 
been a two percentage point differential between home purchase loans 
and refinance loans during a heavy refinancing environment.
    As shown in Table D.11, the special affordable shares varied by 
over two percentage points, from 24.1 percent with a 12 percent MF 
mix to 21.7 percent with a 6 percent MF mix. These special 
affordable market shares are 3-5 percentage points lower than the 
special affordable shares reported in Table D.17 for HUD's baseline 
home purchase environment. Notice that the special affordable share 
remains in the 22-23 percent range even if the MF mix falls to 6-8 
percent. In addition to higher-income borrowers dominating the 
single-family market, the share of the ``goals rich'' rental market 
declines in a refinancing wave, which tends to further reduce the 
special affordable of market activity. The right-hand column of 
Table D.11 shows that the rental share falls to the 17-22 percent 
range, or 4-9 percentage points less that the almost 26-percent 
rental share in HUD's baseline model.
    Model estimates were also made for the recent refinancing years 
of 1998, 2001, 2002, and 2003. For 1998, the baseline model assumed 
a multifamily mix of 14.0 percent and a mortgage investor share of 
6.8 percent. Under these assumptions, the 1998 market estimate is 
24.0 percent. If the MF mix for 1998 had been 13.0 (12.0) percent 
then the estimated special affordable market share for 1998 would be 
23.5 (23.1) percent. For 2001, the baseline model assumed a 
multifamily mix of 13.5 percent and a mortgage investor share of 7.8 
percent. Under these assumptions, the 2001 market estimate for 
special affordable loans is 25.0 percent. If the MF mix for 2001 had 
been 12.0 percent, instead of the baseline of 13.5 percent, then the 
estimated special affordable market share for 2001 would be 24.4 
percent. For 2002, the baseline model assumed a multifamily mix of 
slightly over 11.0 percent and a mortgage investor share of 7.8 
percent. Under these assumptions, the 2002 special affordable market 
is estimated to be 24.3 percent.\85\ A lower MF mix--for example, 
10.5 (9.5) percent instead of 11 percent--would reduce the estimated 
2002 special affordable market share to 24.2 (23.7) percent. \86\ 
\87\
---------------------------------------------------------------------------

    \85\ The baseline estimates for 2001 (25.0 percent) and 2002 
(24.3 percent) are lower than those (26.5 percent and 25.8 percent, 
respectively) reported in Table D.9 of Appendix D of the proposed 
rule. As explained earlier, the differences between the results in 
the proposed rule and this Final Rule are mainly due to the 
treatment of single-family rental mortgages. In addition, the SF0 
percentage for home purchase loans originated during 2002 was 
lowered by approximately 0.2 percentage point in the Final Rule.
    \86\ Using the projected CBSA data (instead of the historical 
1990-based MSA data) resulted in only small changes in the special 
affordable market estimates for 2001 (a 0.1 percentage point 
decline) and 2002 (a 0.5 percentage point decline).
    \87\ For the years 1999 to 2002, Fannie Mae estimated a special 
affordable market share of 23-25 percent. (This is their estimate 
assuming no missing data; see their Table I.9, page I-34.) This 
compares with HUD's estimate of 25.9 percent to 26.6 percent. As 
discussed in Section C.6, Fannie Mae assumes a rather low MF mix 
(approximately 10 percent) in the model that generates its 
historical estimates.
---------------------------------------------------------------------------

    As explained in Section F.3b, HUD has not yet completed its 
analysis of 2003 data. However, HUD developed some rough projections 
for different assumptions about the MF mix. Combining an investor 
mortgage share of 8.2 from HMDA with different MF mixes (ranging 
from 6 percent to 8 percent) produced estimates of 22.6 percent (MF 
mix of 6 percent) to 23.5 percent (MF of 8 percent).
    As shown by both the simulation results in Table D.17 and the 
actual experience during 2001-2003, the special affordable share of 
the overall market declines when refinances dominate the market. The 
special affordable share was approximately 24 percent during 2001 
and 2002 and 23 percent in 2003 (although there is some uncertainty 
with the 2003 estimate).
    The various market estimates presented in Table D.17 for a home 
purchase environment and reported above for a refinance environment 
are not all equally likely. Most of them equal or exceed 23 percent. 
In the home purchase environment, estimates below 23 percent would 
require the special affordable share for home purchase loans to drop 
to 12 percent which would be 4 percentage points lower than the 
1995-2003 average for the special affordable share of the home 
purchase market. As shown in Table D.11, dropping below 23 percent 
would be more likely in a heavy refinance environment, particularly 
those characterized by extremely low MF mixes of 7 percent or less.
    As stated in Sections F and G above, HUD received a number of 
public comments seeking a regulatory solution to the issue of the 
ability of the GSEs to meet the housing goals during a period when 
refinances of home mortgages constitute an unusually large share of 
the mortgage market. As explained in the Preamble, HUD is not 
addressing the refinance issue in this final rule. Elsewhere in the 
Federal Register, HUD is publishing an Advance Notice of Proposed 
Rulemaking that advises the public of HUD's intention to consider by 
separate rulemaking a provision that recognizes and takes into 
consideration the impact of high volumes of refinance transactions 
on the GSEs' ability to achieve the housing goals in certain years, 
and solicits proposals on how such a provision should be structured 
and implemented. HUD believes that it would benefit from further 
consideration and additional public input on this issue. HUD also 
notes (see above) that FHEFSSA provides a mechanism by which HUD can 
take into consideration market and economic conditions that may make 
the achievement of housing goals infeasible in a given year. (See 12 
U.S.C. 1336(b)(e).)
    B&C Loans. The procedure for dropping B&C loans from the 
projections is the same as described in Section F.3.c for the Low- 
and Moderate-Income Goal. The special affordable percentage for B&C 
loans is 28.0 percent, which is similar to the projected percentages 
for the overall market given in Table D.17. Thus, dropping B&C loans 
(as well as all subprime loans) does not appreciably reduce the 
overall market estimates. Consider the case of a single-family-owner 
percentage of 16 percent, which yields an overall market estimate 
for Special Affordable Goal of 26.7 percent if B&C loans are 
included in the analysis. Dropping B&C loans from the projection 
model reduces the special affordable market share by 0.2 percentage 
points to 26.5, as reported in Table D.17. Dropping all subprime 
loans (A-minus as well as B&C) would reduce the special affordable 
market projection to 26.2 percent.
    Manufactured Housing Loans and Small Loans. Excluding 
manufactured housing loans and small loans (loans less than $15,000) 
reduces the overall market estimates reported in Table D.17 by less 
than one percentage point. This is estimated as follows. First, 
excluding these loans reduces the special affordable percentage for 
single-family-owner mortgages in metropolitan areas by about 1.5 
percentage points, based on analysis of recent home purchase 
environments (1995-97 and 1999 and 2000). Multiplying this 1.5 
percentage point differential by the property share (0.745) of 
single-family-owner units yields 1.1 percentage points, which serves 
as a proxy for the reduction in the overall special affordable 
market share due to dropping manufactured home loans from the market 
analysis. The actual reduction will be somewhat less because 
dropping manufactured home loans will increase the share of rental 
units, which increases the overall special affordable share, thus 
partially offsetting the 1.1 percent reduction. The net effect is 
probably a reduction of three-quarters to one percentage point.
    The effects can be considered separately. Dropping only 
manufactured housing loans would reduce the market estimates by 
approximately one-half of a percentage point. ICF argued that loans 
with less than $15,000 should be excluded. The impact of doing this 
on the market estimates would be about one-third to four-fifths of a 
percentage point. ICF also considered scenarios where one-half of 
manufactured loans would be dropped, as well as small loans less 
than $15,000. The impact of doing this on the market estimates would 
be three-fifths to three-quarters of a percentage point.
    The above analyses of the effects of less affordable market 
conditions, different assumptions about the size of the rental 
market, and dropping different categories of

[[Page 63887]]

loans from the market definition suggest that 23-27 percent is a 
reasonable range of estimates for the low- and moderate-income 
market. This range covers markets without B&C and allows for market 
environments that would be much less affordable than recent market 
conditions.
    Tax Credit Definition. Data are not available to measure the 
increase in market share associated with including low-income units 
located in multifamily buildings that meet threshold standards for 
the low-income housing tax credit. Currently, the effect on GSE 
performance under the Special Affordable Housing Goal is rather 
small. For instance, adding the tax credit condition increased 
Fannie Mae's performance as follows: 0.42 percentage point in 1999 
(from 17.20 to 17.62 percent); 0.59 percentage point in 2000 (from 
18.64 to 19.23 percent); and 0.43 percent point in 2001 (from 19.29 
to 19.72 percent). The increases for Freddie Mac have been lower 
(ranging from 0.24 to 0.38 percentage point during the same period).

3. Conclusions

    Sensitivity analyses were conducted for the market shares of 
each property type, for the very-low-income shares of each property 
type, and for various assumptions in the market projection model. 
These analyses suggest that 23-27 percent is a reasonable estimate 
of the size of the conventional conforming market for the Special 
Affordable Housing Goal. This estimate excludes B&C loans and allows 
for the possibility that homeownership will not remain as affordable 
as it has over the past six years. In addition, the estimate covers 
a range of projections about the size of the multifamily market.

[FR Doc. 04-24101 Filed 11-1-04; 8:45 am]
BILLING CODE 4210-27-P