[Federal Register Volume 65, Number 211 (Tuesday, October 31, 2000)]
[Rules and Regulations]
[Pages 65044-65229]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 00-27367]



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Part II





Department of Housing and Urban Development





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24 CFR Part 81



HUD's Regulation of the Federal National Mortgage Association (Fannie 
Mae) and the Federal Home Loan Mortgage Corporation (Freddie Mac); 
Final Rule

  Federal Register / Vol. 65, No. 211 / Tuesday, October 31, 2000 / 
Rules and Regulations  

[[Page 65044]]


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DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT

24 CFR Part 81

[Docket No. FR-4494-F-02]
RIN 2501-AC60


HUD's Regulation of the Federal National Mortgage Association 
(Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie 
Mac)

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

ACTION: Final rule.

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SUMMARY: This final rule 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 the ``GSEs'') for the years 2001 through 
2003. 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. Specifically, the final rule increases the 
Low- and Moderate-Income Housing Goal to 50 percent, the Geographically 
Targeted Goal to 31 percent, and the Special Affordable Housing Goal to 
20 percent of units backing each GSE's annual eligible mortgage 
transactions. The Special Affordable Multifamily Subgoal increases to 
one percent of each GSE's average annual total dollar mortgage 
purchases in 1997 through 1999. This rule also establishes new 
provisions and clarifies certain other provisions of HUD's rules for 
counting different types of mortgage purchases towards the goals, 
including provisions regarding the use of bonus points for mortgages 
that are secured by certain single family rental properties and small 
multifamily properties; and the disallowance of goals credit for 
mortgage loans with predatory characteristics.
    While Fannie Mae and Freddie Mac have been successful in providing 
stability and liquidity in the market for certain types of mortgages, 
their share of the affordable housing market is substantially smaller 
than their share of the total conventional, conforming mortgage market. 
There are several reasons for these disparities, related to the GSEs' 
purchase and underwriting guidelines; and to their relatively low level 
of activity in specific mortgage markets that provide financing for 
housing serving low- and moderate-income families, including small 
multifamily rental properties, single family owner-occupied rental 
properties, manufactured housing, and markets for seasoned mortgages on 
properties with affordable housing. As the GSEs continue to grow their 
businesses, the new goals will provide strong incentives for the two 
enterprises to more fully address the housing finance needs for very 
low-, low- and moderate-income families and residents of underserved 
areas and, thus, more fully realize their public purposes.
    In addition, as government sponsored enterprises and market 
leaders, Fannie Mae and Freddie Mac have a public responsibility to 
help eliminate predatory mortgage lending practices which are inimical 
to the home financing and homeownership objectives that the GSEs were 
established to serve. Fannie Mae and Freddie Mac have adopted policies 
stating that they will not purchase mortgage loans with certain 
predatory characteristics. This final rule affirms the GSEs' actions by 
disallowing housing goals credit for mortgages having features that the 
GSEs themselves have identified as unacceptable.

EFFECTIVE DATE: January 1, 2001.

FOR FURTHER INFORMATION CONTACT: Director, Office of Government 
Sponsored Enterprises Oversight, Office of Housing, Room 6182, 
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 8234, telephone (202) 
708-1464. For legal questions, contact Kenneth A. Markison, 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. Purpose

    This final rule revises existing regulations implementing the 
Department of Housing and Urban Development's (the ``Department'' or 
``HUD'') authority to regulate the GSEs. The authority exercised by the 
Department 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.); and
    (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).
    (4) Section 7(d) of the Department of Housing and Urban Development 
Act (42 U.S.C. 3535(d)), which provides that the Secretary may make 
such rules and regulations as may be necessary to carry out his 
functions, powers, and duties, and may delegate and authorize 
successive redelegations of such functions, powers, and duties to 
officers and employees of the Department.
    FHEFSSA substantially changed the Department's regulatory 
authorities governing the GSEs by establishing a separate safety and 
soundness regulator within the Department and clarified and expanded 
the Department's regulation of the GSEs' missions. Regulations first 
implementing the Department's authorities with respect to the GSEs' 
missions under FHEFSSA were issued on December 1, 1995 (24 CFR part 
81).
    This rule revises certain portions of those regulations concerning 
the GSEs' affordable housing goals and provisions related to how 
mortgage loans are treated in the calculation of performance under the 
housing goals. The remaining part of the preamble contains several 
endnotes. These endnotes appear at the end of the preamble.

B. Background

1. Fannie Mae and Freddie Mac
    Fannie Mae and Freddie Mac engage in two principal businesses: 
investing in residential mortgages and guaranteeing securities backed 
by residential mortgages. Fannie Mae and Freddie Mac are chartered by 
Congress as Government Sponsored Enterprises 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

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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.\1\
    Fannie Mae and Freddie Mac receive significant explicit benefits 
through their status as GSEs that are not enjoyed by any other 
shareholder-owned corporations in the mortgage market. These benefits 
include: (1) Conditional access to a $2.25 billion line of credit from 
the U.S. Treasury; \2\ (2) exemption from the securities registration 
requirements of the Securities and Exchange Commission and the States; 
\3\ and (3) exemption from all State and local taxes except property 
taxes.\4\
    Additionally, although the securities the GSEs guarantee and the 
debt instruments they issue are not backed by the full faith and credit 
of the United States, and nothing in this final rule should be 
construed otherwise, such securities and instruments trade at yields 
only a few basis points over those of U.S. Treasury securities and at 
yields lower than those for securities issued by comparable firms that 
are fully private but may be higher capitalized. The market prices for 
GSE debt and mortgage-backed securities, and the fact that the market 
does not require that those securities be rated by a national rating 
agency, suggest that investors perceive that the government implicitly 
backs the GSEs' debt and securities. This perception evidently arises 
from the GSEs' relationship to the Federal Government, including their 
public purposes, their Congressional charters, their potential direct 
access to U.S. Department of Treasury funds, and the statutory 
exemptions of their debt and mortgage-backed securities (MBS) from 
otherwise mandatory security laws. Consequently, each GSE enjoys a 
significant implicit benefit--its cost of doing business is 
significantly less than that of other firms in the mortgage market. 
According to a U.S. Department of Treasury 1996 study, the benefits of 
federal sponsorship are worth almost $6 billion annually to Fannie Mae 
and Freddie Mac. Of this amount, reduced operating costs (i.e., 
exemption from SEC filing fees and from state and local income taxes) 
represent approximately $500 million annually. These estimates are 
broadly consistent with estimates by the Congressional Budget Office 
and General Accounting Office. According to the Department of the 
Treasury, Fannie Mae and Freddie Mac appear to pass through part of 
these benefits to consumers through reduced mortgage costs and retain 
part for their own stockholders.\5\
    The GSEs have achieved an important part of their mission: 
providing stability and liquidity to large segments of the housing 
finance markets. As a result of the GSEs' activities, many home buyers 
have benefited from lower interest rates and increased access to 
capital, contributing, in part, to a record national homeownership rate 
of 66.8 percent in 1999. While the GSEs have been successful in 
providing stability and liquidity to certain portions of the mortgage 
market, the GSEs must further utilize their entrepreneurial talents and 
power in the marketplace and ``lead the mortgage finance industry'' to 
``ensure that citizens throughout the country enjoy access to the 
public benefits provided by these federally related entities.'' \6\
    Despite the record national homeownership rate in 1999, lower 
homeownership rates have prevailed for certain minorities, especially 
for African-American households (46.3 percent) and Hispanics (45.5 
percent). These gaps are only partly explained by differences in 
income, age, and other socioeconomic factors. Disparities in mortgage 
lending are a contributing factor to lower homeownership rates and are 
reflected in loan denial rates of minority groups when compared to 
white applicants. Denial rates for conventional (non-government-backed) 
home purchase mortgage loans in 1998 were 54 percent for African 
Americans, 53 percent for Native American applicants, 39 percent for 
Hispanic applicants, 26 percent for White applicants, and 12 percent 
for Asian applicants.\7\ Despite strong economic growth, low 
unemployment, low mortgage interest rates, and relatively stable home 
prices, housing problems continue to persist for low-income families 
and certain minorities.
    In addition to disparities across racial groups, populations who 
live in certain types of housing have not benefited to the same degree 
as have others from the advantages and efficiencies provided by Fannie 
Mae and Freddie Mac. The GSEs have been much less active in purchasing 
mortgages in markets where there is a need for additional financing to 
address persistent housing needs including financing for small 
multifamily rental properties, manufactured housing, single family 
owner-occupied rental properties, seasoned affordable housing 
mortgages, and older housing in need of rehabilitation.
    While HUD recognizes that the GSEs have played a significant role 
in the mortgage finance industry by providing a secondary market and 
liquidity for mortgage financing for certain segments of the mortgage 
market, it is this recognition of their ability, along with HUD's 
comprehensive analyses of the size of the mortgage market and the 
opportunities available, America's unmet housing needs, identified 
credit gaps, and HUD's consideration of the statutory factors under 
FHEFSSA that causes HUD to increase the level of the housing goals so 
that as the GSEs grow their businesses so they will address new markets 
and persistent housing finance needs.
2. Regulation of the GSEs
    In 1968, Congress assigned HUD general regulatory authority over 
Fannie Mae,\8\ and in 1989, Congress granted the Department essentially 
identical regulatory authority over Freddie Mac.\9\ Under the 1968 law, 
HUD was authorized to require that a portion of Fannie Mae's mortgage 
purchases be related to the national goal of providing adequate housing 
for low- and moderate-income families. Accordingly, the Department 
established two housing goals--a goal for mortgages on low- and 
moderate-income housing and a goal for mortgages on housing located in 
central cities--by regulation, for Fannie Mae in 1978.\10\ Each goal 
was established at the level of 30 percent of mortgage purchases. 
Similar housing goals for Freddie Mac were proposed by the Department 
in 1991 but were not finalized before October 1992, when Congress 
revised the Department's GSE regulatory authorities including 
requirements for new housing goals.
    In 1992, Congress enacted the Federal Housing Enterprises Financial 
Safety and Soundness Act (FHEFSSA) 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), which established the Office of 
Federal Housing Enterprise Oversight (OFHEO) as the GSEs' safety and 
soundness regulator and affirmed, clarified and expanded the Secretary 
of Housing and Urban Development's responsibilities for GSE mission 
regulation. FHEFSSA provided that, except for the specific authority of 
the Director of OFHEO, the Secretary retained general regulatory power 
over the GSEs.\11\ FHEFSSA also detailed and expanded the Department's 
specific

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powers and authorities, including the power to establish, monitor, and 
enforce housing goals for the GSEs' purchases of mortgages that finance 
housing for low-and moderate-income families; housing located in 
central cities, rural areas, and other underserved areas; and special 
affordable housing, affordable to very low-income families and low-
income families in low-income areas.\12\ The Department is required to 
establish each of the goals after consideration of certain prescribed 
factors relevant to the particular goal.\13\
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    \11\ 11. Sec. 1321.
    \12\ 12. See generally secs. 1331-34.
    \13\ 13. Secs. 1332(b), 1333(a)(2), 1334(b).
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    FHEFSSA provided for a transition period during 1993 and 1994 and 
required HUD to establish interim goals for the transition period (58 
FR 53048; October 13, 1993) (59 FR 61504; November 30, 1994). In 
November 1994, HUD extended the interim goals established for 1994 for 
both GSEs through 1995 while the Department completed its development 
of post transition goals.
    The Department issued proposed and final rules in 1995 establishing 
and implementing the housing goals for the years 1996 through 1999. The 
rule provided that the housing goals for 1999 would continue beyond 
1999 if the Department did not change the goals, and further provided 
that HUD may change the level of the goals for the years 2000 and 
beyond based upon HUD's experience and in accordance with HUD's 
statutory authority and responsibility.
    In addition to establishing the level of the housing goals, the 
1995 final rule included counting requirements for purposes of 
calculating performance under the housing goals. The new regulations 
also prohibited the GSEs from discriminating in any manner on any 
prohibited basis in their mortgage purchases, implemented procedures by 
which HUD exercises its authority to review new programs of the GSEs, 
required reports from the GSEs, established a public use data base on 
the GSEs' mortgage purchase activities while providing protections for 
confidential and proprietary information, and established enforcement 
procedures under FHEFSSA.

C. The Proposed Rule

    On March 9, 2000,\14\ HUD published a rule proposing new housing 
goal levels for Fannie Mae and Freddie Mac. The rule proposed to 
increase the level of the 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 
clarify HUD's guidelines for counting different types of mortgage 
purchases under the housing goals, including treatment of missing 
affordability data and purchases of seasoned mortgage loans; use of 
bonus points for goals credit for purchases of mortgages secured by 
single family rental and small multifamily properties; and providing 
greater public access to certain types of mortgage data on the GSEs' 
mortgage purchases in HUD's public use database. The rule also 
solicited public comments on several other issues related to the 
housing goals including the appropriate role of credit enhancements in 
furthering affordable housing lending and whether the use of credit 
enhancements should be considered in calculating housing goal 
performance.
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    \14\ 14. 65 FR 12632-12816
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D. This Final Rule

    In response to the proposed rule, HUD received over 250 comments. 
The comments came from the GSEs; individuals; representatives of 
lending institutions; non-profit organizations; community, consumer 
groups and civil rights organizations; local and State governments; and 
others. Following full consideration of the comments, HUD developed 
this final rule. The final rule is consistent with the approach 
announced in the proposed rule but does include some revisions adopted 
in light of the comments received. The final rule: (1) Increases the 
level of the housing goals for the years 2001 through 2003 as a result 
of HUD's review of the statutory factors under FHEFSSA to ensure that 
the GSEs continue and strengthen their efforts to carry out Congress' 
intent that the GSEs provide the benefits of the secondary market to 
families throughout the nation--the Low- and Moderate-Income Housing 
Goal increases to 50 percent, the Geographically Targeted Goal 
increases to 31 percent, the Special Affordable Housing Goal increases 
to 20 percent; and the Special Affordable Multifamily Subgoal increases 
to the respective average of one percent of each GSE's total mortgage 
purchases over 1997 through 1999; (2) establishes the use of bonus 
points for small multifamily properties with 5 to 50 units and for 
single family owner-occupied rental properties for the years 2001 
through 2003; (3) establishes a temporary adjustment factor for Freddie 
Mac's multifamily mortgage purchases for the years 2001 through 2003; 
(4) prohibits the counting of high cost mortgage loans with predatory 
features for goals credit; (5) provides or clarifies counting rules for 
the treatment of missing affordability data, purchases of seasoned 
mortgage loans, purchases of federally insured mortgage loans and 
purchases of mortgage loans on properties with expiring assistance 
contracts; (6) provides for HUD's review of transactions to determine 
appropriate goal treatment; and (7) includes certain definitional and 
technical corrections to the regulations issued in 1995.
    Specific changes included in the Final Rule from the provisions 
included in the Proposed Rule are as follows:
    (1) The period covered by the housing goals is 2001 through 2003 
and there is no transition year. The proposed rule had suggested the 
goals cover the period from 2000 through 2003 with 2000 serving as a 
transition year.
    (2) The Special Affordable Multifamily Subgoal uses the average of 
1997 through 1999 as the base period for establishing the level of the 
goal over the 2001 through 2003 period, rather than 1998 as the base 
period, as proposed. The subgoal remains a fixed dollar amount for each 
year of the period covered by the housing goals base equal to one 
percent of each GSE's average total mortgage purchases in 1997 through 
1999.
    (3) The final rule does not allow goals credit for predatory 
mortgage loans, and the rule describes specific characteristics, in 
addition to the HOEPA definition suggested in the proposed rule, to 
determine what types of loans are considered predatory. The final rule 
also identifies good lending practices with which mortgages should 
conform in order to count towards goals credit.
    (4) The proposed provisions for the treatment of missing 
affordability data are retained but the final rule includes a five 
percent ceiling on the use of estimated affordability information for 
multifamily units.
    (5) The guidance provided on how to determine if seasoned mortgage 
loan purchases meet the recycling requirements of the Special 
Affordable Housing Goal was expanded to (1) include additional types of 
lending organizations with affordable housing missions that are 
presumed to meet the recycling requirements; (2) adjust the Community 
Reinvestment Act (CRA) examination requirement for Federally regulated 
financial institutions to one ``Satisfactory'' rating for financial 
institutions with assets of $250 million or less to accommodate a less 
frequent examination schedule; and (3) specify requirements that a 
seller must meet for purposes of evaluating whether the seller meets 
the recycling requirements of 12 U.S.C. 4563(b)(1)(B).
    (6) The final rule does not make changes to the definition of 
underserved

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area other than the inclusion of tribal lands in underserved areas and 
does not address the public availability of mortgage data in the public 
use data base. As explained below, HUD will publish a decision on which 
data elements will be accorded proprietary and non-proprietary 
treatment by separate Order following publication of this final rule.
    The analysis of Fannie Mae's and Freddie Mac's affordable housing 
performance, which is the basis for many of the changes in the final 
rule, is primarily based on data from 1997, 1998 and 1999. The GSEs' 
actual performance is presented through 1999. However, Home Mortgage 
Disclosure Act (HMDA) data which provides data on the conventional, 
conforming market was not available for 1999 at the time HUD prepared 
its analysis supporting this final rule. As HMDA data for 1999 were not 
available, comparisons between the GSEs and the market as a whole for 
that year are not possible. Further, as 1998 was a year with a large 
percentage of refinance mortgage transactions, at times 1997 data is 
utilized as it presents a more normal year in terms of home purchase 
mortgage transactions.
    In finalizing these regulations, the Department is guided by and 
affirms the following principles established in the 1995 rulemaking:
    (1) To fulfill the intent of FHEFSSA, the GSEs should 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 goals and 
close the gap between the secondary mortgage market and the primary 
mortgage market. This approach is consistent with Congress' recognition 
that ``the enterprises will need to stretch their efforts to achieve'' 
the goals.\15\
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    \5\ 5. U.S. Department of Treasury, Government Sponsorship of 
the Federal National Mortgage Association and the Federal Home Loan 
Mortgage Corporation (1996), page 3.
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    (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 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 should allow the GSEs to maintain their flexibility and 
their ability to respond quickly to market opportunities. At the same 
time, the Department must ensure that the GSEs' strategies serve 
families in underserved markets and address unmet credit needs. The 
addition of bonus points to the regulatory structure provides an 
additional means of encouraging the GSEs' affordable housing activities 
to address identified, persistent credit needs while leaving the 
specific approaches to meeting these needs to the GSEs.
    (3) Discrimination in lending--albeit sometimes subtle and 
unintentional--has denied racial and ethnic minorities the same access 
to credit to purchase a home that has been available to similarly 
situated non-minorities. The GSEs have a central role and 
responsibility to promote access to capital for minorities and other 
identified groups and to demonstrate the benefits of such lending to 
industry and borrowers alike. The GSEs also have an integral role in 
eliminating mortgage lending practices that are predatory.
    (4) In addition to the GSEs' purchases of single family home loans, 
the GSEs also must continue to assist in the creation of an active 
secondary market for multifamily loans. Affordable rental housing is 
essential for those families who cannot afford or choose not to become 
homeowners. The GSEs must assist in making capital available to assure 
the continued development of rental housing.

II. Discussion of Public Comments

A. Overview

1. Public Comment
    Of the over 250 comments received, by far the most detailed were 
the submissions of the two directly affected GSEs--Fannie Mae and 
Freddie Mac. Each GSE's comments were in large measure supportive of 
the overall goal structure proposed by the Department. The GSEs, 
however, did provide extensive appendices questioning 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.
    Other commenters included national and regional industry related 
groups, non-profit organizations, state and local government officials, 
lenders, and individuals. In large measure, these commenters were also 
supportive of the Department's proposal to increase the affordable 
housing goals and the related provisions designed to streamline the 
counting rules used to calculate performance under the housing goals.
    Other than the goals framework, the areas generating the largest 
response from commenters were the treatment of high cost mortgages, the 
role of credit enhancements in affordable lending transactions, and the 
availability of data on the public use data base. It should be noted 
that in evaluating these comments a large number of comments were 
received that included substantially similar responses, in both 
language and tone, to those submitted by Fannie Mae.
    In addressing the appropriate goals treatment for high cost 
mortgages, one group of commenters, comprised primarily of non-profit 
and housing advocacy groups, felt the provisions included in the 
proposed rule disallowing credit for loans that meet the HOEPA 
definition should be strengthened. Other commenters, consistent with 
the comments provided by Fannie Mae, opposed any limitation of goals 
credit for predatory mortgage loans.
    With regard to credit enhancements, a substantial majority of 
commenters noted that credit enhancements are a critical component of 
many affordable housing transactions. There was little support for 
limiting goals credit for affordable housing transactions that include 
credit enhancements without a better understanding of how to ensure 
that there are not negative implications for affordable housing 
transactions.
    The Department received comments supporting both increased data 
availability and limited availability of data. One group of commenters, 
including non-profit organizations and academic researchers, felt the 
provisions included in the proposed rule should be adopted and, in some 
instances, expanded in order to fully understand and challenge the GSEs 
on their affordable housing activities. Again, another group of 
commenters, consistent with the comments provided by Fannie Mae, 
opposed the availability of additional data on the public use data 
base. This group of commenters included both lenders and non-profit 
organizations which felt the additional data would release confidential 
business information and could compromise the privacy of individuals, 
respectively. This final rule does not, however, address the 
availability of data on the public use data base.
    A discussion of the general and specific comments on the rule 
follows in subsequent sections. While comments are summarized, not all 
of the comments are addressed explicitly in this preamble. HUD fully 
considered all of the comments and HUD's response is either explicit in 
this final rule or implicit in the general discussion of the rule or 
other comments. HUD is appreciative of the full range of public 
comments received and acknowledges the value of all of the comments

[[Page 65048]]

submitted in response to the proposed rule.
2. Other Public Input
    As part of the public comment process, the Department conducted 
extensive outreach to educate and inform interested parties of the 
nature and extent of the GSEs' affordable housing activities. The 
outreach was undertaken in order to encourage comments on the proposed 
rule from a wide range of individuals, organizations and businesses 
that are interested in or are affected by Congress' charge to the GSEs 
to further the financing needs of underserved families and 
neighborhoods. The Department's outreach in this regard included two 
forums, three subject matter meetings, and meetings with various 
industry trade groups and non-profit organizations to discuss the 
provisions of the proposed rule. These sessions are described below. 
Further, additional information on these meetings is contained in the 
public docket file of this rule in Room 10276 at HUD Headquarters.
    a. Forums. The Department conducted two forums designed to give 
participants an in-depth look at how well the GSEs are supporting 
affordable housing activities in local communities. One forum was held 
in Hartford, Connecticut and the other in Durham, North Carolina. Each 
forum had approximately 125 participants. In addition to sessions held 
at both forums that reviewed the GSEs' progress in meeting the 
affordable housing needs in the respective region, each forum had a 
session that addressed issues and needs specific to the region. In 
Hartford, a session was held on the role of multifamily housing in 
meeting affordable housing needs. Research was presented on how small 
multifamily properties disproportionately serve low- income families 
and data was provided on the extent of the GSEs' purchases of mortgages 
on small multifamily properties. Panel members discussed the unique 
problems of financing small multifamily properties and how Fannie Mae 
and Freddie Mac can better serve these markets. In Durham, a session 
was held on predatory lending. Panel members identified abusive 
practices and discussed the impacts that predatory lenders were having 
particularly on the elderly and in minority neighborhoods. Serious 
questions were raised as to whether Fannie Mae and Freddie Mac should 
be involved in this market.
    b. Subject Matter Meetings. HUD also held three smaller discussion 
group sessions designed to address specific subject matters included in 
the proposed rule. Subject matter meetings were held on the 
availability of data on the public use data base, issues related to 
identifying and meeting the credit needs of non-metropolitan areas, and 
the role of credit enhancements in affordable housing lending.
    c. Other Meetings. In addition to the meetings described above, the 
Department met with various industry trade groups and non-profit 
organizations to present the changes suggested in the proposed rule and 
the rationale for the changes. HUD also met with Fannie Mae and Freddie 
Mac to discuss their concerns regarding the proposed rule.

B. Subpart A--General

    HUD proposed to revise the definitions of ``median income,'' 
``metropolitan area,'' and ``underserved area'' in order to provide 
greater clarity, consistency and technical guidance. The few comments 
received on these definitions were supportive of the proposed technical 
changes. HUD also proposed certain changes to several aspects of the 
definition of underserved area to solicit public input on how best to 
identify the areas that are underserved by the mortgage credit markets.
1. Median Income
    HUD proposed to change the definition of ``median income'' to 
require the GSEs to use HUD estimates of median family income to 
further clarify the appropriate process for the GSEs' determination of 
area incomes. HUD has implemented this change in this final rule. As 
part of this change to the definition of ``median income,'' HUD will 
provide the GSEs, on an annual basis, information specifying how HUD's 
published median family income estimates are to be applied. This change 
is needed because, in some cases, HUD publishes area median family 
income estimates for portions of areas rather than whole metropolitan 
statistical areas (MSAs) or primary metropolitan statistical areas 
(PMSAs).
2. Metropolitan Area
    HUD proposed to clarify the definition of ``metropolitan area'' by 
revising the description of the relevant area for determining median 
incomes to eliminate the reference in Sec. 81.2 to consolidated 
metropolitan statistical areas (CMSAs). HUD has implemented this change 
in the final rule. ``Metropolitan area'' was defined in Sec. 81.2 under 
the 1995 final rule as an MSA, a PMSA, or a CMSA, designated by the 
Office of Management and Budget of the Executive Office of the 
President. This definition raised questions as to the definition of 
``underserved area'' and the denominator of the affordability ratio 
used to compute the Low- and Moderate-Income Housing Goal and the 
Special Affordable Housing Goal regarding whether to use the median 
income of the CMSA or the PMSA. HUD has consistently relied upon median 
incomes of PMSAs in defining underserved areas and determining 
denominators for the other goals and this final rule clarifies this 
point.
3. Underserved Area
    a. Technical Definition. HUD proposed to revise the definition of 
``underserved area'' to clarify the parameters of rural underserved 
areas. The definition under HUD's 1995 final rule omitted the 
requirement for a comparison between the ``greater of the State non-
metropolitan median income or nationwide non-metropolitan median 
income'' from the ``income/minority'' provision even though it had 
provided for this comparison when qualifying mortgage purchases under 
the ``income-only'' provision. HUD proposed to add the comparative 
language to the ``income/minority'' provision for rural underserved 
areas. The revision applies the same median income standard to both the 
``income-only'' and the ``income/minority'' definitions. HUD has 
implemented this change in Sec. 81.2 of this final rule. (HUD also 
proposed other changes to the definition of ``underserved areas.'' 
These are discussed in Subpart B--Housing Goals.)
    b. Other Changes Proposed and/or Comments Requested. The proposed 
rule described additional changes to the definition of underserved area 
relating to tribal lands and requested comments on possible changes to 
the income and minority requirements of the definition.
    (1) Tribal Lands. HUD proposed to revise the definition of 
``underserved areas'' in Sec. 81.2 to designate all qualifying Indian 
reservations and trust lands as underserved areas.
    c. Summary of Comments. Fannie Mae stated that it is ``particularly 
appropriate'' to include these lands in the definition of underserved 
areas. Fannie Mae added that it ``does not think it is feasible, 
practical, or appropriate to split trust lands between served and 
underserved designations, depending on the designation of the 
surrounding tracts or counties.'' Fannie Mae further commented that 
HUD's proposal could lead to ``split or proportional treatment of any 
one trust land,'' and that such areas should be

[[Page 65049]]

included as underserved areas ``without regard to income or minority 
status.'' Fannie Mae added that HUD should consider postponing this 
change until ``the new boundary files and data files'' become available 
from the 2000 Census. Fannie Mae further stated that HUD's proposal to 
define some underserved areas in terms of income and minority 
composition for the balance of a county or census tract excluding the 
area within any Federal or State American Indian reservation or tribal 
or individual trust land ``raises operational issues that will be 
difficult to overcome.''
    Freddie Mac stated that ``In principal [sic], Freddie Mac has no 
objection to treating an American Indian Reservation or tribal land as 
a geographic whole'' for determining underserved areas. It added, 
however, that ``adoption of a definition that would involve geocoding 
rural loans at the subcounty level could present formidable practical 
problems.'' Freddie Mac recommended that HUD ``designate entire tracts 
in metropolitan areas and entire counties in nonmetropolitan areas that 
contain qualifying reservations and trust lands as underserved.''
    Other commenters were generally supportive of the Department's 
proposal. One commenter called for an expansion of the proposal to 
include tribal service areas and urban living Native Americans.
    d. HUD's Determination. HUD believes that treating tribal lands as 
separate geographic entities implies that the balance of counties or 
tracts excluding such areas would logically be treated as separate 
entities, but it recognizes Fannie Mae's argument that this could raise 
``operational issues.'' HUD will issue operational guidance on this 
matter prior to the effective date of this Final Rule.
    HUD evaluated Fannie Mae's recommendation to classify all American 
Indian and Alaskan Native (AIAN) areas as underserved areas, without 
regard to income or minority status, in light of the problems involved 
in obtaining a mortgage on even the very few higher-income (or low 
minority) tribal lands. HUD analyzed data on 1989 median incomes and 
minority concentrations for AIAN areas provided by the U.S. Bureau of 
the Census. HUD's analysis showed that, out of 248 AIAN areas with 
sufficient population to determine an area median family income, 19 
areas, or 6.7 percent, would be classified as served and 265 areas, or 
93.3 percent, as underserved. The 19 areas include some with very low 
minority concentrations and some with very high median incomes. HUD 
concludes that implementation of Fannie Mae's recommendation would, in 
a small but significant number of instances, substantially breach the 
principle that underserved areas are areas with low median incomes and/
or high minority concentrations, as established in the 1995 Final Rule. 
Accordingly, HUD has not implemented Fannie Mae's recommendation.
    HUD believes that designating entire tracts or counties that 
contain qualifying tribal lands as underserved areas is not 
appropriate. The purpose of the definitional change in underserved 
areas to include all tribal lands is to focus attention on the mortgage 
financing needs of Native American communities. By designating the 
entire county or census tract as underserved by virtue of the presence 
of tribal lands in a portion of it, this focus is lost. HUD believes 
that any geocoding problems arising from this proposal can be resolved. 
HUD will issue operational guidance on this matter prior to the 
effective date of this final rule.
    HUD believes that underserved areas must have relatively fixed 
definitions--tribal service areas are evolving over time. The 
underserved areas goal is defined broadly by both geographic and area 
wide demographic features so that borrowers living in underserved areas 
benefit from the increased attention paid to lending in such areas as a 
result of HUD's geographic goal.
    (2) Enhanced Tract Definition. In the proposed rule, comments were 
sought on possible changes to the current metropolitan underserved 
areas definition to better target underserved areas with higher 
mortgage denial rates and thereby promote better access to mortgage 
credit for these areas. Specifically, HUD proposed changing the current 
tract income ratio to an ``enhanced'' tract income ratio requiring that 
for tracts to qualify as underserved they must have a tract income 
ratio at or below the maximum of 80 percent of area median income or 80 
percent of U.S. median income in metropolitan areas. The proposed 
change would make the underserved areas definition used by the GSEs 
consistent with the requirements of Federally insured depository 
institutions under the Community Reinvestment Act (CRA). The Department 
believes the concept has substantial merit, and there was a sizeable 
group of commenters that supported the concept, at least in part. 
However, there were a number of commenters, including the GSEs, that 
said that since the redesignation of census tracts as underserved would 
be based on data from the 1990 Census, and since data from the 2000 
Census would not be available for a few years, it would not be 
appropriate to make such a change at this time. Rather, they suggested 
that the Department wait until updated information from the 2000 Census 
is available to analyze. The Department agrees that, with more current 
information to become available from the 2000 Census in the near 
future, the timing is not optimal to make a change in the underserved 
areas designation. Once information from the 2000 Census is available, 
the Department will determine whether this proposal merits 
consideration.
    (3) Minority Composition. Similarly, the proposed rule requested 
comment on another approach to target high mortgage denial rate areas. 
The alternative approach would be to increase the minority component 
required to identify an area as underserved by increasing the 
requirement from 30 percent to 50 percent minority. Several commenters 
noted that increasing the minority component of a census tract to 
qualify as underserved would have a disproportionately negative impact 
on the Hispanic population. Commenters observed that Hispanic 
residential living patterns are not as concentrated as those of other 
minority groups. In addition, comments were provided suggesting that 
any changes in this area be considered once data from the 2000 Census 
is available before making a final determination in this regard. The 
Department has determined that it will obtain and analyze 2000 Census 
data and consider various minority population patterns and their 
relationship to the availability of mortgage credit before deciding 
whether this proposal continues to merit consideration.
    (4) Rural Areas. The proposed rule requested comments on how best 
to define underserved rural areas, posing questions on whether the 
underserved rural areas should be identified by census tract or by 
county. HUD received comments that supported both approaches. Again, 
the commenters raised the issue of the 2000 Census. Consistent with the 
Department's other determinations regarding significant changes to the 
definition of underserved areas, HUD will not make any changes at this 
time in defining underserved rural areas and will wait for the 
opportunity to analyze the data from the 2000 Census.

C. Subpart B--Housing Goals

1. Overview
    Comments received overwhelmingly supported the Department's 
proposal to increase the level of the affordable

[[Page 65050]]

housing goals. Both GSEs commented that, while meeting these goals will 
be a challenge (particularly the Underserved Areas Goal), they are 
committed to doing so. While some commenters, including the GSEs, 
expressed concern that the market scenarios used by HUD did not 
adequately consider an economic downturn, those commenters still felt 
that higher goals levels were appropriate. This section of the final 
rule reviews the statutory factors the Department must consider in 
setting the level of the housing goals, specific comments on the 
housing goals including the market methodology, and the determination 
made with regard to the level for each of the housing goals.
2. Statutory Considerations in Setting the Level of the Housing Goals
    In establishing the housing goals, FHEFSSA requires the Department 
to consider six factors--national housing needs; economic, housing and 
demographic conditions; performance and effort of the GSEs toward 
achieving the goal in previous years; size of the conventional mortgage 
market serving the targeted population or areas, relative to the size 
of the overall conventional mortgage market; ability of the GSEs to 
lead the industry in making mortgage credit available for the targeted 
population or areas; and the need to maintain the sound financial 
condition of the GSEs. These factors are discussed in more detail in 
the following sections of this preamble and in the Appendices to this 
rule. A summary of HUD's findings relative to each factor follows:
    a. National Housing Needs. Analysis and research by HUD and others 
in the housing industry indicate that there are, and will continue to 
be in the foreseeable future, substantial unmet housing needs among 
lower-income and minority families. Data from the American Housing 
Surveys demonstrate that there are substantial unmet housing needs 
among lower-income families. Many households are burdened by high 
homeownership costs or rent payments and will likely continue to face 
serious housing problems, given the dim prospects for earnings growth 
in entry-level occupations. According to HUD's ``Worst Case Housing 
Needs'' report, 21 percent of owner households faced a moderate or 
severe cost burden in 1997. Affordability problems were even more 
common among renters, with 40 percent paying more than 30 percent of 
their income for rent in 1997.\16\
    Despite the growth during the 1990s in affordable housing lending, 
disparities in the mortgage market remain, with certain minorities, 
particularly African-American and Hispanic families, lagging the 
overall market in rate of homeownership. In addition, there is evidence 
that the aging stocks of single family rental properties and small 
multifamily properties with 5-50 units, which play a key role in lower-
income housing, have experienced difficulties in obtaining financing. 
The ability of the nation to maintain the quality and availability of 
the existing affordable housing stock and to stabilize neighborhoods 
depends on an adequate supply of affordable credit to rehabilitate and 
repair older units.
    (1) Single Family Mortgage Market. 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 several years, economic expansion, 
accompanied by low interest rates and increased outreach on the part of 
the mortgage industry, has improved affordability conditions for lower-
income families. Between 1994 and 1999, record numbers of lower-income 
and minority families purchased homes. First time homeowners have 
become a major driving force in the home purchase market over the past 
five years. Thus, the 1990s have seen the development of a strong 
affordable lending market. Despite the growth of lending to minorities, 
disparities in the mortgage market remain. For example, African-
American applicants are still twice as likely to be denied a loan as 
white applicants, even after controlling for income.
    (2) Multifamily Mortgage Market. Since the early 1990s, the 
multifamily mortgage market has become more closely integrated 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 mortgages on single family properties. 
Property values, vacancy rates, and market rents of multifamily 
properties appear to be highly correlated with local job market 
conditions, creating greater sensitivity of loan performance to 
economic conditions than may be experienced for single family 
mortgages.
    There is a need for an on-going GSE presence in the multifamily 
secondary market both to increase liquidity and to further 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.
    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. Increased GSE presence would provide 
greater liquidity to lenders, i.e., a viable ``exit strategy,'' that in 
turn would serve to increase their lending. It appears that the 
financing of small multifamily rental properties with 5-50 units, where 
a substantial portion of the nation's affordable housing stock is 
concentrated, have been adversely affected by excessive borrowing 
costs. Multifamily properties with significant rehabilitation needs 
also appear to have experienced difficulty gaining access to mortgage 
financing. Moreover, the flow of capital into multifamily housing for 
seniors has been historically characterized by a great deal of 
volatility.
    b. Economic, Housing, and Demographic Conditions. Studies indicate 
that changing population demographics will result in a need for the 
mortgage market to meet nontraditional credit needs and to respond to 
diverse housing preferences. The U.S. population is expected to grow by 
an average of 2.4 million persons per year over the next 20 years, 
resulting in 1.1 to 1.2 million new households per year. In particular, 
the continued influx of immigrants will increase the demand for rental 
housing while those who immigrated during the 1980s will be in the 
market to purchase owner-occupied housing. The aging of the baby-boom 
generation and the entry of the small baby-bust generation into prime 
home buying age is expected, however, to result in a lessening of 
housing demand. Non-traditional households have, and will, become more 
important as overall household formation rates slow down. With later 
marriages, divorce, and non-traditional living arrangements, the 
fastest growing household groups have been single parent and single 
person households. With continued house price appreciation and 
favorable mortgage terms, ``trade-up buyers'' will also increase their 
role in the housing market. There will also be increased credit needs 
from new and expanding market sectors, such as manufactured housing and 
housing for senior citizens. These demographic trends will lead to 
greater diversity in the homebuying market, which, in turn, will 
require greater adaptation by the primary and secondary mortgage 
markets.
    As a result of the above demographic forces, housing starts are 
expected to average 1.5 million units annually between 2000 and 2003, 
essentially the same as in 1996-99.17 Refinancing of

[[Page 65051]]

existing mortgages, which accounted for 50 percent of originations in 
1998 and 34 percent in 1999, is expected to return to lower levels 
during 2000. The mortgage market remained strong with $1.3 trillion 
dollars in originations during 1999. A lower number of originations is 
expected in 2000 with approximately $962 billion in originations being 
projected by the Mortgage Bankers Association of America.
    c. Performance and Effort of the GSEs Toward Achieving the Goal in 
Previous Years. Both Fannie Mae and Freddie Mac have improved their 
affordable housing loan performance since the enactment of FHEFSSA in 
1992 and HUD's establishment of housing goals under the law. However, 
the GSEs' mortgage purchases continue to lag the overall market in 
providing financing for affordable housing to low- and moderate-income 
families, underserved borrowers and their neighborhoods, indicating 
that there is more that the GSEs can do to improve their performance. 
In addition, a large percentage of the lower-income loans purchased by 
the GSEs have relatively high down payments, which raises questions 
about whether the GSEs are adequately meeting the needs of those lower-
income families who have little cash for making large down payments but 
can fully meet their monthly payment obligations. The discussion of the 
performance and effort of the GSEs toward achieving the housing goals 
in previous years is specific to each of the three housing goals. This 
topic is discussed below and further details are provided in the 
Appendices to this rule.
    d. Size of the Mortgage Market Serving the Targeted Population or 
Areas, Relative to the Size of the Overall Conventional, Conforming 
Mortgage Market. The Department's analyses indicate that the size of 
the conventional, conforming market relative to each housing goal is 
greater than earlier estimates (based mainly on HMDA data for 1992 
through 1994) used in establishing the 1996-1999 housing goals. The 
discussion of the size of the conventional mortgage market serving 
targeted populations or areas relative to the size of the overall 
conventional, conforming mortgage market is specific to each of the 
three housing goals. The Department's estimate of the size of the 
conventional mortgage market is discussed below and further details are 
provided in the Appendices to this rule.
    e. Ability of the GSEs To Lead the Industry in Making Mortgage 
Credit Available for the Targeted Population or Areas. Research 
concludes that the GSEs have generally not been leading the market, but 
have lagged behind the primary market in financing housing for lower-
income families and housing in underserved areas. However, the GSEs' 
state-of-the-art technology, staff resources, share of the total 
conventional, conforming market, and their financial strength suggest 
that the GSEs have the ability to lead the industry in making mortgage 
credit available for lower-income families and underserved 
neighborhoods.
    The legislative history of FHEFSSA indicates 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.18 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.'' 19 
FHEFSSA, therefore, specifically required 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 Community Reinvestment Act 
20 and fair lending laws 21 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 establishing 
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 housing needs, as well as for underserved 
urban and rural areas.
    While the GSEs cannot be expected to solve all of the nation's 
housing problems, the efforts of Fannie Mae and Freddie Mac have not 
matched the opportunities that are available in the primary mortgage 
market. Although the GSEs were directed by Congress to lead the 
mortgage finance industry in making mortgage credit available for low- 
and moderate-income families, depository and other lending institutions 
have been more successful than the GSEs in providing affordable loans 
to lower-income borrowers and in historically underserved 
neighborhoods. In 1998 for example, very low-income borrowers accounted 
for 9.9 percent of Freddie Mac's acquisitions of home purchase mortgage 
loans, 11.4 percent of Fannie Mae's acquisitions, 15.2 percent of such 
mortgage loans originated and retained by depository institutions, and 
13.3 percent of such mortgage loans originated in the overall 
conventional, conforming market. Similarly, mortgage purchases on 
properties located in underserved areas accounted for 20.0 percent and 
22.5 percent of Freddie Mac's and Fannie Mae's purchases of home 
purchase loans, respectively, 26.1 percent of home purchase mortgages 
originated and retained by depository institutions and 24.6 percent of 
home purchase mortgages originated in the overall conventional, 
conforming market.
    Between 1993 and 1998, Fannie Mae improved its affordable lending 
performance and made progress toward closing the gap between its 
performance and that of the overall mortgage market. During that period 
Freddie Mac showed less improvement and, as a result, did not make as 
much progress in closing the gap between its performance and that of 
the overall market for home loans. However, during 1999, Freddie Mac's 
purchases of goals qualifying home loans increased significantly 
relative to Fannie Mae's purchases and, as a result Freddie Mac now 
matches or out-performs Fannie Mae in several affordable lending 
categories. For example, during 1999, very low-income borrowers 
accounted for 11.0 percent of Freddie Mac's purchases of home loans in 
metropolitan areas, compared with 10.8 percent of Fannie Mae's. 
Similarly, mortgages on properties in underserved census tracts 
accounted for 21.2 percent of Freddie Mac's acquisitions of home 
purchase mortgage loans in metropolitan areas, compared with 20.6 
percent of Fannie Mae's. The extent to which Freddie Mac has closed its 
performance gap relative to depositories and the overall market will be 
clarified once HUD has the opportunity to analyze 1999 HMDA data for 
metropolitan areas.
    The Department estimates the GSEs provided financing for 55 percent 
of units financed by conventional, conforming mortgages in 
1998.22 However, the GSEs' mortgage market presence varies 
significantly by property type. While the GSEs accounted for about 68 
percent of the owner-occupied units financed in the primary market in 
that year, their role was much less in the market for mortgages on 
rental properties. Specifically, HUD estimates that Fannie Mae and 
Freddie Mac accounted for only about 24 percent of rental units 
financed in 1998. Thus, the GSEs' presence in the rental mortgage 
market was well under half their presence in the market for mortgages 
on

[[Page 65052]]

single family owner-occupied properties.
    Within the rental category, GSE purchases have accounted for 29 
percent of the multifamily dwelling units that were financed in 1998. 
The GSEs have yet to play a major role in financing mortgages for 
rental units in single family rental properties (those with at least 
one rental unit and no more than four units in total), where their 
market share was only 19 percent.
    As noted above, the GSEs continue to lag the overall conforming, 
conventional market in providing affordable home purchase loans to 
lower-income families and for properties in underserved neighborhoods. 
Additionally, a large percentage of the lower-income loans purchased by 
both GSEs have relatively high down payments, which raises questions 
about whether the GSEs are adequately meeting the needs of those lower-
income families who find it difficult to raise enough cash for a large 
down payment. Also, while rental properties are an important source of 
low- and moderate-income rental housing, they represent only a small 
portion of the GSEs' business.
    The appendices to this rule provide more information on HUD's 
analysis of the extent to which the GSEs have lagged the mortgage 
industry in funding loans to underserved borrowers and neighborhoods. 
From this analysis of the GSEs' performance in comparison with the 
primary mortgage market and with other participants in the mortgage 
markets, it is clear that the GSEs need to improve their performance 
relative to the primary market of conventional, conforming mortgage 
lending. The need for improvements in the GSEs' performance is 
especially apparent with respect to the single family and multifamily 
rental markets.
    f. Need To Maintain the Sound Financial Condition of the GSEs. 
Based on HUD's economic analysis and discussions with the Office of 
Federal Housing Enterprise Oversight, HUD has concluded that the level 
of the goals as proposed would not adversely affect the sound financial 
condition of the GSEs. Further discussion of this issue is found in 
Appendix A.
3. Determinations Regarding the Level of the Housing Goals
    There are several reasons the Department, having considered all the 
statutory factors, is increasing the level of the housing goals.
    a. Market Needs and Opportunities. First, the GSEs appear to have 
substantial room for growth in serving the affordable housing mortgage 
market. For example, as discussed above, the Department estimates that 
the two GSEs' mortgage purchases accounted for 55 percent of the total 
(single family and multifamily) conventional, conforming mortgage 
market during 1998. In contrast, GSE purchases comprised only 44 
percent of the low- and moderate-income mortgage market in 1998, 46 
percent of the underserved areas market, and, a still smaller, 33 
percent of the special affordable market. As discussed above, the GSE 
presence in mortgage markets for rental properties, where much of the 
nation's affordable housing is concentrated, is far below that in the 
single family owner-occupied market.
    The GSEs' role in the mortgage market varies somewhat from year to 
year in response to changes in interest rates, mortgage product types, 
and a variety of other factors. Underlying market trends, however, show 
a clear and significant increase in the GSEs' role. Specifically, OFHEO 
estimates that the share (in dollars) of single family mortgages 
outstanding accounted for by mortgage-backed securities issued by the 
GSEs and by mortgages held in the GSEs' portfolios has risen from 31 
percent in 1990 to 42 percent in 1999. In absolute terms, the GSEs' 
presence has grown even more sharply, as the total volume of single 
family mortgage debt outstanding has increased rapidly over this 
period.
    The GSEs have indicated that they expect their role in the mortgage 
market to continue to increase in the future, as they develop new 
products, refine existing products, and enter markets where they have 
not played a major role in the past. The Department's housing goals for 
the GSEs also anticipate that their involvement in the mortgage market 
will continue to increase.
    There are a number of segments of the multifamily, single family 
owner, and single family rental markets that the GSEs have not tapped 
in which the GSEs might play an enhanced role thereby increasing their 
shares of targeted loans and their performance under the housing goals. 
Six such areas are discussed below.
    (1) Small Multifamily Properties. One sector of the multifamily 
mortgage market where the GSEs could play an enhanced role involves 
loans on small multifamily properties--those containing 5-50 units. 
These loans account for 39 percent of the units in recently mortgaged 
multifamily properties, according to the 1991 Survey of Residential 
Finance. However, the GSEs typically purchase relatively few of these 
loans. HUD estimates that the GSEs acquired loans financing only three 
percent of units in small multifamily properties originated during 
1998. This is substantially less than the GSEs' presence in the overall 
multifamily mortgage market, which the Department estimates was 29 
percent in 1998.
    Increased purchases of small multifamily mortgages would make a 
significant contribution to performance under the goals, since the 
percentages of these units qualifying for the income-based housing 
goals are high--in 1999, 95 percent of units backing Fannie Mae's 
multifamily mortgage transactions qualified for the Low- and Moderate-
Income Housing Goal, with a corresponding figure of 90 percent for 
Freddie Mac. That year, 43 percent of units backing Freddie Mac's 
multifamily transactions qualified for the Special Affordable Housing 
Goal, with a corresponding figure of 56 percent for Fannie Mae.
    (2) Multifamily Rehabilitation Loans. Another multifamily market 
segment holding potential for expanded GSE presence involves properties 
with significant rehabilitation needs. Properties that are more than 10 
years old are typically classified as ``C'' or ``D'' properties, and 
are considered less attractive than newer properties by many lenders 
and investors. Multifamily rehabilitation loans accounted for only 0.5 
percent of units backing Fannie Mae's 1998 mortgage purchases and for 
1.6 percent in 1999. These loans accounted for 1.9 percent of Freddie 
Mac's 1998 multifamily mortgage purchase total (with none indicated in 
1999).
    (3) Single Family Rental Properties. Studies show that single 
family rental properties are a major source of affordable housing for 
lower-income families, yet these properties are only a small portion of 
the GSEs' overall business.
    HUD estimates that approximately 203,000 mortgages were originated 
on owner-occupied single family rental properties in 1998. These 
mortgages financed a total of 458,000 units--the owners' units plus an 
additional 254,000 rental units.23 Data submitted to HUD by 
the GSEs indicate that, in 1998, together the GSEs acquired mortgages 
backed by 188,000 such units, 41 percent of the number of units 
financed in the primary market, well below the GSEs' overall 1998 
market share of 55 percent.24
    There is ample room for an enhanced GSE role in this goal-rich 
market. For the GSEs combined, 65 percent of the units in these 
properties qualified for the Low- and Moderate-Income Housing Goal in 
1999, 32 percent qualified for the Special Affordable Housing Goal, and 
54 percent qualified for the

[[Page 65053]]

Geographically Targeted Goal. Thus, significant gains could be made in 
performance on all of the goals if Fannie Mae and Freddie Mac played a 
larger role in the market for mortgages on single family owner-occupied 
rental properties (two to four units).
    (4) Manufactured Homes. The Manufactured Housing Institute, in its 
Annual Survey of Manufactured Home Financing, reported that 116 
reporting institutions originated $15.6 billion in consumer loans on 
manufactured homes in 1998, and that, with an average loan amount of 
about $30,000, approximately 520,000 loans were originated.
    While the GSEs have traditionally played a minimal role in 
financing manufactured housing, they have recently stepped up their 
activity in this market. However, even with their increased level of 
activity, the GSEs' purchases probably accounted for less than 15 
percent of total loans on manufactured homes in 1998--a figure well 
below their overall market presence of 55 percent.
    There is ample room for an enhanced GSE role in this market, with 
its high concentration of goals qualifying mortgage loans. In 1998, for 
loans reported by 21 manufactured housing lenders (that are required by 
HMDA to report loan data), 76 percent qualified for the Low- and 
Moderate-Income Housing Goal in 1998, 42 percent qualified for the 
Special Affordable Housing Goal, and 47 percent qualified for the 
Geographically Targeted Goal. Thus, manufactured housing has 
significantly higher shares of goal qualifying loans than all single 
family owner-occupied properties, though purchases of these loans are 
not quite as goal-rich as loans on multifamily properties. In general, 
goal performance could be enhanced substantially if the GSEs were to 
play an increased role in the manufactured housing mortgage market.
    (5) A-minus Loans. Industry sources estimate that subprime mortgage 
originations amounted to about $160 billion in 1999, and that these 
loans are divided evenly between the more creditworthy (``A-minus'') 
borrowers and less creditworthy (``B,'' ``C,'' and ``D'') borrowers. 
Based on HMDA data for 200 subprime lenders, the Department estimates 
that 58 percent of the units financed by subprime loans qualified for 
the Low- and Moderate-Income Housing Goal in 1998, 29 percent qualified 
for the Special Affordable Housing Goal, and 45 percent qualified for 
the Geographically Targeted Goal.
    Freddie Mac has estimated that 10 to 30 percent of subprime 
borrowers would qualify for a prime conventional loan. Fannie Mae 
Chairman Franklin Raines has stated that half of all mortgages in the 
high cost subprime market are candidates for purchase by Fannie Mae. 
Both Fannie Mae and Freddie Mac recently introduced programs aimed at 
borrowers with past credit problems that would lower the interest rates 
for those borrowers that were timely on their mortgage payments. 
Freddie Mac has also purchased subprime loans through structured 
transactions that limit Freddie Mac's risk to the ``A'' piece of a 
senior-subordinated transaction.
    However, there may be ample room for further enhancement of both 
GSEs' roles in the A-minus market. A larger role by the GSEs might help 
standardize mortgage terms in this market, possibly leading to lower 
interest rates.
    (6) Seasoned Mortgages. Over the past five years, depository 
institutions (banks and thrifts) have been expanding their affordable 
loan programs and, as a result, have originated substantial numbers of 
loans to low-income and minority borrowers and to low-income and 
predominantly minority neighborhoods, under the incentive of the 
Community Reinvestment Act (CRA),\25\ which requires many depository 
institutions to help meet the credit needs of their communities. As the 
GSEs noted in their comments, some of these loans, when originated, may 
not have met the GSEs' underwriting guidelines. A large number of the 
``CRA-type'' loans that have been recently originated remain in thrift 
and bank portfolios; selling these loans on the secondary market would 
free up capital for depositories to originate new CRA loans. Given its 
enormous size, the CRA market segment provides an opportunity for 
Fannie Mae and Freddie Mac to expand their affordable housing financing 
programs. The Department recognizes that purchasing these loans may 
present some challenges for the GSEs. However, it appears these loans 
are beginning to be purchased by GSEs after the loans have seasoned and 
through various structured transactions. As explained in Appendix A, 
Fannie Mae's purchases of seasoned loans improved its performance on 
the housing goals in 1997 and 1998. Seasoned loan purchases did not 
have a similar impact in 1999. Freddie Mac, on the other hand, has not 
been as active as Fannie Mae in purchasing seasoned CRA type loans. 
With billions of dollars worth of CRA loans in bank portfolios, the 
early experience of Fannie Mae suggests that purchasing these loans 
could be an important strategy for reaching the housing goals and 
provide needed liquidity for a market that is serving the needs of low-
income and minority homeowners.
    (7) Lending to Minority Borrowers. The GSEs have an opportunity to 
play a leadership role in making mortgage credit more widely available 
to African American and other minority borrowers, who represent yet 
another underserved market. In 1998, for example, African American 
borrowers accounted for five percent of conventional, conforming single 
family mortgage loans originated in metropolitan areas, as shown in 
Appendix A.\26\ By contrast, African American borrowers accounted for 
only 3.1 percent of Fannie Mae's metropolitan area mortgage purchases 
and three percent of Freddie Mac's mortgage purchases. Hispanic 
borrowers accounted for 5.2 percent of the metropolitan area 
conventional, conforming mortgage market in 1998, 4.8 percent of Fannie 
Mae's mortgage purchases and 4.4 percent of Freddie Mac's mortgage 
purchases.\27\
    b. Market Share Higher than Goal Levels. The shares of the mortgage 
markets that would qualify for each of the housing goals are higher 
than the goal levels as they were set through 1999. Specifically, the 
Low- and Moderate-Income Housing Goal for 1997 through 1999 was 42 
percent, but the market share for low- and moderate-income mortgages 
has been estimated at 50-55 percent. The Geographically Targeted Goal 
for 1997 through 1999 was 24 percent, but the estimated market share of 
geographically targeted mortgages has been estimated at 29-32 percent. 
The Special Affordable Housing Goal for 1997 through 1999 was 14 
percent, but the estimated special affordable market share is 23-26 
percent.28 Thus, the increases in the housing goals 
implemented in this final rule and described below will significantly 
reduce the disparities that existed between the previous housing goals 
and HUD's market estimates. HUD's analysis indicates that the goal 
levels established in the final rule are reasonable and feasible and 
that its market estimates reflect significantly more adverse economic 
environments than have recently existed. Reasons for the remaining 
disparity between the GSE housing goals established in this final rule 
and the respective shares of the overall mortgage market qualifying for 
each of the housing goals are discussed below. See Appendix D for 
further discussion of these issues.
---------------------------------------------------------------------------

    \28\ 28. The low-and moderate-income market share is the 
estimated proportion of newly mortgaged units in the market serving 
low-and moderate-income families. The two other shares are similarly 
defined. HUD's conservative range of estimates (such as 50-55 
percent) reflects uncertainty about future market conditions.
---------------------------------------------------------------------------

    c. Need for Increased Affordable Single Family Mortgage Purchases. 
Higher housing goals are needed to assure that both Fannie Mae and 
Freddie Mac increase their purchases of

[[Page 65054]]

single family mortgages for lower-income families. The GSEs lag behind 
depository institutions and other lenders in the conventional, 
conforming market in providing mortgage funds for underserved families 
and their neighborhoods. Numerous studies have concluded that Fannie 
Mae and Freddie Mac have room to increase their purchases of affordable 
loans originated by primary lenders. The single family affordable 
market, which had only begun to grow when HUD set housing goals in 
1995, has now established itself with seven straight years (1993-1999) 
of solid performance. Current projections suggest that the demand for 
affordable housing by minorities, immigrants, and non-traditional 
households will be maintained in the post-1999 period, leading to 
additional opportunities for the GSEs to support mortgage lending 
benefiting families targeted by the housing goals.
    d. Market Disparities. Despite the recent growth in affordable 
lending, there are many groups who continue to face problems obtaining 
mortgage credit and who would benefit from a more active and targeted 
secondary market. Homeownership rates for lower-income families, 
certain minorities, and central city residents are substantially below 
those of other families, and the disparities cannot simply be 
attributed to differences in income. Immigrants represent a ready 
supply of potential first-time home buyers and need access to mortgage 
credit. Special needs in the market, such as rehabilitation of older 
two- to four-unit properties, could be helped by new mortgage products 
and more flexibility in underwriting and appraisal guidelines. The 
GSEs, along with primary lenders and private mortgage insurers, have 
been making efforts to reach out to these underserved portions of the 
markets. However, more needs to be done, and the proposed increases in 
the housing goals are intended to encourage additional efforts by 
Fannie Mae and Freddie Mac.
    e. Impact of Multifamily Mortgage Purchases. When the 1996-99 goals 
were established in December 1995, Freddie Mac had only recently 
reentered the multifamily mortgage market, after an absence from the 
market in the early 1990s. Freddie Mac has made progress in rebuilding 
its multifamily mortgage purchase program, with its purchases of these 
loans rising from $191 million in 1993 to $7.6 billion in 1999. Freddie 
Mac's limited role in the multifamily market was a significant 
constraint when HUD set the level of the housing goals for 1996 through 
1999. While Freddie Mac has made progress in recent years in 
significantly increasing its multifamily mortgage purchases, Freddie 
Mac's smaller multifamily portfolio relative to that of Fannie Mae has 
meant fewer refinance opportunities from within its portfolio. 
Accordingly, the Department is providing Freddie Mac with a temporary 
adjustment factor for purchases of mortgages in multifamily properties 
with more than 50 units under the 2001-2003 goals as it continues to 
increase its multifamily mortgage purchases, as discussed in more 
detail, below.
    f. Financial Capacity to Support Affordable Housing Lending. A wide 
variety of quantitative and qualitative indicators 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 decade, from $677 million in 
1987 to over six billion dollars in 1999. 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.
    g. Closing the Gap Between the GSEs and the Market. This section 
discusses the relationship between the housing goals, the GSEs' 
performance and HUD's market estimates; and identifies key segments of 
the affordable market in which the GSEs have had only a weak presence. 
To lay the groundwork for this discussion, the following table 
summarizes the Department's findings regarding GSE performance under 
the 1997-2000 goals and the new goal levels for 2001-2003 as compared 
to HUD's estimates for 1995-1998 markets as well as HUD's projected 
market estimates for 2001-2003:

[[Page 65055]]

[GRAPHIC] [TIFF OMITTED] TR31OC00.000

    It is evident from this table that the new goal levels for the Low- 
and Moderate-Income Housing Goal and Special Affordable Housing Goal 
are below HUD's projected market estimate for the years covered by the 
new housing goals. One reason for this disparity can be discerned by 
disaggregating GSE purchases by property type, which shows that the 
GSEs have little presence in some important segments of the affordable 
housing market. For example, as shown in Figure 1, in 1998, the GSEs 
purchased loans representing only 19 percent of rental units in single 
family rental properties, and only three percent of units in small 
multifamily properties mortgaged that year. Figure 2 provides 
additional detail providing unit data comparing the GSEs' with the 
conventional, conforming market. Typically, about 90 percent of rental 
units in single family rental and small multifamily properties qualify 
for the Low- and Moderate-Income Housing Goal. One reason that the 
GSEs' performance under the Low- and Moderate-Income Housing Goal falls 
short of HUD's market estimate is that the GSEs have had only a weak 
and inconsistent presence in financing these important sources of 
affordable housing, notwithstanding that these market segments are 
important components in the market estimate. In the overall 
conventional, conforming mortgage market, rental units in single family 
properties and in small multifamily properties are expected to 
represent approximately 21 percent of the overall mortgage market, and 
33 percent of units backing mortgages qualifying for the Low- and 
Moderate-Income Housing Goal. Yet in 1999, units in such properties 
accounted for 6.6 percent of the GSEs' overall purchases, and only 11.5 
percent of the GSEs' purchases meeting the Low- and Moderate-Income 
Housing Goal. The continuing weakness in GSE purchases of mortgages on 
single

[[Page 65056]]

family rental and small multifamily properties is a major factor 
explaining the shortfall between GSE performance and that of the 
primary mortgage market.
    For a variety of reasons, the GSEs have historically viewed the 
single family rental and small multifamily market segments as more 
difficult for them to penetrate than the single family owner-occupied 
mortgage market. In order to provide the GSEs with an incentive to 
enter these markets and to provide this housing the benefits of greater 
financing through the secondary market, HUD is proposing to award 
``bonus points'' for the GSEs' purchases of mortgages on owner-occupied 
single family rental properties and small multifamily properties in 
calculating credit toward the housing goals. The bonus points will make 
the Department's increased housing goals easier for the GSEs to attain 
if they devote resources to affordable market segments where their past 
role has been limited and there are significant needs for greater 
secondary market involvement.
BILLING CODE 4210-27-P

[[Page 65057]]

[GRAPHIC] [TIFF OMITTED] TR31OC00.001


[[Page 65058]]


[GRAPHIC] [TIFF OMITTED] TR31OC00.002

4. Summary of Comments on HUD's Analysis of Statutory Factors
    HUD received several comments on the factors for determining the 
goal levels. Fannie Mae and Freddie Mac provided numerous technical 
comments on HUD's analyses in the appendices to the proposed rule. Most 
of the comments focused on two related topics concerning HUD's market 
methodology: (a) HUD's model for the determining the market size for 
each of the three housing goals; and (b) HUD's analysis of the GSEs' 
performance in the single family owner-occupied portion of the 
conventional, conforming mortgage market. Section A of Appendices A, B 
and C and Section B of Appendix D provide a more extensive discussion 
of HUD's response to the various questions raised by the GSEs about the 
factors for determining the housing goals.
    a. Market Share Methodology. In Appendix D, HUD estimates the 
following market shares for the three housing goals during 2001-2003: 
50-55 percent for the Low-Mod Goal, 23-26 percent for the Special 
Affordable Goal, and 29-32 percent for the Geographically Targeted 
Goal. Neither GSE objected to HUD's basic approach to calculating these 
market shares, which involves estimating (1) the share of the market 
(in dwelling units) by type of property (single family owner-occupied, 
single family rental, and multifamily), (2) the proportion of dwelling 
units financed by mortgages for each type of property meeting each 
goal, and (3) projecting the size of the total market by weighting each 
such goal share by the corresponding market share. In fact, both Fannie 
Mae and Freddie Mac stated that HUD's market share model was a 
reasonable approach

[[Page 65059]]

for estimating the goals qualifying shares of the mortgage market. 
Freddie Mac stated that the Department took the correct approach in 
estimating the size of the conventional, conforming market by examining 
several different data sets, using alternative methodologies, and 
conducting sensitivity analyses. Fannie Mae expressed similar 
sentiments asserting that HUD's model for assessing the size of the 
affordable housing market is reasonable.
    Both GSEs were critical, however, of HUD's implementation of its 
market methodology. Their major comments on the market methodology fall 
into two general areas. First, the GSEs expressed concern about HUD's 
assumptions and use of specific data elements both in constructing the 
distribution of property shares among single family owner-occupied, 
single family rental, and multifamily properties and in estimating the 
goals qualifying shares for each property type. The GSEs contended that 
HUD chose assumptions and data sources that resulted in an 
overstatement of the market estimate for each of the housing goals. In 
particular, the GSEs claimed that HUD overstated the importance of 
rental properties (both single family and multifamily) in its market 
model and overstated the Low-and Moderate-Income, Special Affordable, 
and Geographically Targeted shares of the single family owner market. 
Second, both GSEs argued that HUD's market estimates depended heavily 
on a continuation of recent conditions of economic expansion and low 
interest rates. According to the GSEs, HUD's range of market estimates 
did not include periods of adverse economic and affordability 
conditions such as those which existed in the early 1990s.
    b. GSEs' Performance in Single Family Owner-Occupied Market. Both 
GSEs differed with HUD's conclusions that they lag the conventional, 
conforming market in funding mortgages for the goals qualifying 
segments of the single family owner-occupied market. Rather, the GSEs 
hold strongly that they have led the mortgage market, from both 
quantitative and qualitative perspectives. The GSEs expressed concern 
about HUD's assumptions and treatment of HMDA data in estimating the 
goals qualifying shares for single family owner-occupied mortgages. The 
GSEs assert that certain portions of the conforming mortgage market 
(such as manufactured housing loans and selected CRA loans)--those 
market segments where they have not been very active--should be 
excluded from HUD's definition of the owner market. From their own 
analysis that excludes these markets from HMDA data, the GSEs conclude 
that they match or exceed the market in funding affordable loans.
    It should be noted that the GSEs extend their criticism to other 
researchers that have examined this issue of their leading the market 
with HMDA and related data. Appendix A summarizes findings of several 
research studies that have reached the same conclusion as HUD--that the 
GSEs have lagged the market in affordable lending
    c. Volatility of the Mortgage Market. Both GSEs claimed that HUD 
had not adequately considered the impact that changes in the national 
economy could have on the size of the affordable lending market and 
that HUD should significantly lower its market estimates to reflect 
adverse economic conditions. The GSEs commented that HUD based its 
market estimates on the unusually favorable economic and housing market 
conditions that have existed since 1995. The GSEs relied on a Freddie 
Mac funded study by PriceWaterhouse-Coopers (PWC) which concluded that 
the low- and moderate-income share of the mortgage market was heavily 
influenced by interest rate movements and changes in the rate of 
economic growth.\30\ PWC claims that the low-mod share of the market 
ranged from 35 percent to 56 percent during the 1990s, with a mean of 
46 percent. HUD's analysis, on the other hand, finds that the low- and 
moderate-income share of the market averaged 53 percent during the 
1990s.
    In HUD's view, a major shortcoming of the PWC report is that it 
underestimates the size of the multifamily mortgage market by relying 
on multifamily originations reported in HMDA data. While HMDA is for 
many purposes a preeminent data source on single family lending, its 
usefulness as a multifamily data source is much more limited due to 
severe underreporting of loan originations. Indeed, HMDA is not widely 
used as a multifamily data source in published works by highly regarded 
independent researchers, nor by Fannie Mae in its comments submitted in 
response to HUD's proposed rule.
    The discussion of single family lending in the PWC document 
initially appears to contradict HUD's analysis in Appendix D of the 
proposed rule, but this is mainly because HUD's analysis is based upon 
the conforming, conventional mortgage market, whereas PWC includes FHA 
loans and loans above the conforming loan limit, at least in the same 
years.\31\ Because the GSEs are prohibited from purchasing loans above 
the conforming limit, and because HUD is directed by statute to focus 
on the conventional market in setting the housing goals, it is 
necessary to restrict analyses of the mortgage market to the 
conventional, conforming market for purposes of establishing the 
housing goals.
    As explained in Appendices A and D, HUD is aware that the mortgage 
market is dynamic in character and susceptible to significant changes 
in conditions that would affect the overall level of affordable lending 
to lower-income families. In response to concerns expressed about the 
volatility of the mortgage markets over time, HUD has estimated a range 
of market shares for each of the housing goals for the years 2001-2003 
of 50-55 percent for the Low- and Moderate-Income Housing Goal, 23-26 
percent for the Special Affordable Housing Goal, and 29-32 percent for 
the Geographically Targeted Goal--that reflect economic environments 
significantly more adverse than those which existed during the period 
between 1995 and 1998, when the units financed in the conventional, 
conforming market meeting the Low- and Moderate-Income Housing Goal 
averaged 56 percent, the Special Affordable Housing Goal, 28 percent, 
and the Geographically Targeted Goal, 33 percent.
    HUD conducted detailed sensitivity analyses for each of the housing 
goals to reflect affordability conditions that are less conducive to 
lower-income homeownership than those that existed during the mid- to 
late-1990s. For example, the low- and moderate-income percentage for 
single family home purchase loans can fall to as low as 34 percent--or 
four-fifths of its 1995-98 average of over 42 percent--before the 
projected low- and moderate-income share of the overall market would 
fall below 50 percent. Additional sensitivity analyses examining 
recession and proportionately higher refinance scenarios and varying 
other key assumptions, such as the size of the multifamily market, show 
that HUD's market estimates consider a range of mortgage market and 
affordability conditions and provide a sound basis for setting housing 
goals for the years 2001-03.
    HUD recognizes that under certain adverse circumstances, the goals 
qualifying market shares could fall below its estimates. However, as 
HUD stated in its 1995 GSE Rule, while the housing goals must be 
feasible, setting goals so that they can be met even under the very 
worst of circumstances is unreasonable. As HUD stated in its 1995 Final 
GSE Rule, policy should not be based on market estimates that include 
the worst possible economic scenarios.

[[Page 65060]]

HUD believes that the range for the market shares should be broad 
enough to reflect the likely scenarios including an expected range of 
volatility in the mortgage market over the period during which the new 
housing goals will be in effect.
    FHEFSSA and HUD recognize that conditions could change in ways that 
would require revised expectations. Thus, HUD is given the statutory 
discretion to revise the goals if the need arises. Further, current 
regulations require that, if a GSE fails or if there is a substantial 
probability that a GSE will fail one or more of the housing goals, 
notice be provided to the GSE and an opportunity provided for the GSE 
to explain the reason for the failure, or potential failure, and to 
provide information as to the feasibility of achieving the housing 
goal. The Department then makes a determination, taking into 
consideration market and economic conditions and the financial 
condition of the GSE, as to whether the goal was feasible. If the goal 
is determined not to be feasible, no further action is taken. If the 
goal is determined to be feasible, the GSE is given the opportunity to 
submit, for HUD's approval, a housing plan demonstrating how the goal 
will be achieved in the future. Thus, there are adequate protections 
for the GSEs if they are unable to achieve one or more of their housing 
goals due to a dramatic downturn in the market.
    d. Shortcomings of Mortgage Market Data Bases. Major mortgage 
market data bases such as HMDA and the American Housing Survey (AHS) 
are used to implement HUD's market share model. The GSEs made extensive 
criticisms of these data bases, concluding from their critiques that 
the ranges for the estimates of the goals-qualifying market shares 
should be wider to reflect uncertainty due to inadequate data. Examples 
of problems asserted by the GSEs include: overstating of low-income 
loans in HMDA data; inability of HMDA data to identify important 
segments of the market (such as subprime lenders); underreporting of 
multifamily mortgages in HMDA data and generally unreliable reporting 
of rental mortgages in other data bases; underreporting of income in 
the AHS; and the fact that some important mortgage market data bases 
such as the 1991 Residential Mortgage Finance Survey are dated.
    HUD agrees that a single comprehensive source of information on 
mortgage markets is not available. Nevertheless, HUD considered and 
analyzed a number of data sources for the purpose of estimating market 
size, since no single source could provide all the data elements needed 
for its market model. In the appendices, HUD carefully defines the 
range of uncertainty associated with each data source, pulls together 
estimates of important market parameters from independent sources, and 
conducts sensitivity analyses to show the effects of various 
assumptions. In fact, Freddie Mac noted that ``We support the 
Department's approach for addressing the empirical challenges of 
setting the goals by examining several different data sets, using 
alternative methodologies, and conducting sensitivity analysis.''
    While HUD recognizes the shortcomings of the various data and the 
inability to derive precise point estimates of various market 
parameters, HUD does not believe that these limitations call for 
expanding the range of the market estimates, as suggested by the GSEs. 
One purpose of the appendices is to demonstrate that careful 
consideration of independent data sources can lead to reliable ranges 
of estimates for the goals-qualifying shares of the mortgage market. 
HUD demonstrates the robustness of its market estimates by reporting 
the results of numerous sensitivity analyses that examine a range of 
assumptions about the existing data on the rental and owner markets. It 
should also be emphasized that while there are some problems with 
existing mortgage market data, there is a wealth of information on 
important components of the market. For example, HMDA data provide wide 
coverage of the single family owner market in metropolitan areas, 
yielding important information on the borrower income and census tract 
(underserved area) characteristics of that market, and thus providing 
useful information on the affordability characteristics of the single 
family rental and multifamily housing stock.
    HUD's specific responses to the GSEs' comments on data are included 
mainly in Section A of Appendices A, B and C and Section B of Appendix 
D. For example, as noted there, HUD disagrees with the GSEs' assertions 
regarding the seriousness of the bias problem (i.e., overstating low-
income loans) in HMDA data. HUD does not rely heavily on some of the 
data bases that the GSEs criticize (e.g., the borrower income data from 
the AHS and the 1991 Residential Finance Survey).
    e. Size of the Multifamily Market. Because a high proportion of 
multifamily units qualify for the housing goals (e.g., 90 percent 
typically qualify for the Low- and Moderate-Income Housing Goal and 
about 50 percent for the Special Affordable Goal), the size of the 
multifamily market is an important determinant of the overall market 
shares for the housing goals, as estimated by HUD's model. Both GSEs 
commented that HUD overstated the role of multifamily financing, which 
they asserted led to HUD's overstated estimated market shares. Freddie 
Mac and PriceWaterhouseCoopers, in particular, advocated the use of 
HMDA data for measuring the size of the multifamily market.
    As explained in Appendix D, HUD disagrees with Freddie Mac's and 
PWC's analysis of the multifamily market. That appendix contains a 
detailed discussion of the size of the multifamily mortgage market that 
considers a number of alternative data sources providing ample evidence 
on multifamily origination volume over the years 1990 to 1999. HUD 
finds that newly mortgaged multifamily units represent an average of 
16-17 percent of units financed during the 1990s. HUD's estimated 
multifamily market shares exceed estimates prepared by PWC (averaging 
8.7 percent for 1991-1998); Appendix D outlines what HUD regards as 
errors in the PWC study that led to its unrealistically low estimates 
of the multifamily origination market. The three multifamily market 
shares--13.5 percent, 15 percent, and 16.5 percent--that HUD emphasizes 
in its market share model accommodates the possibility of a recession 
or heavy refinance year.
    f. GSEs' Affordable Lending Performance--Defining the Relevant 
Market. As noted earlier, HUD uses HMDA data to show that even though 
the GSEs have improved their performance since 1993, they have lagged 
depositories and others in the conventional, conforming market in 
funding affordable loans, both since 1993 and particularly during the 
more recent 1996-98 period when the new housing goals were in effect. 
In their analyses, the GSEs reach the opposite conclusion--each 
concludes that they already match or even lead the market, depending on 
the affordable category being considered. The GSEs obtain this result 
by adjusting HMDA market data to exclude single family loans that they 
perceive as not being available for them to purchase.
    Both GSEs provided numerous comments concerning the types of 
mortgages that HUD should exclude from the definition of the single 
family owner market. Fannie Mae states that it ``can only purchase or 
securitize mortgages that primary market lenders are willing to sell'' 
and that ``HUD fails to adjust for those housing markets that are not 
fully available to Fannie Mae

[[Page 65061]]

and Freddie Mac.'' Freddie Mac states that it ``has not achieved, and 
is unlikely to achieve in the near term, the same penetration in the 
subprime and manufactured housing segments of the market as it has 
achieved in the conventional, conforming market'' and, therefore, HUD 
should not include these segments in its market definition. According 
to the GSEs, markets that are ``not available'' to them or where they 
are not a ``full participant'' should be excluded from HUD's market 
definition. In addition to the subprime and manufactured housing 
markets, examples of market segments mentioned by the GSEs for 
exclusion consisted of the following: low-down payment mortgages (those 
with loan-to-value ratios greater than 80 percent) without private 
mortgage insurance or some other credit enhancement; loans financed 
through state and local housing finance agencies; below-market-
interest-rate mortgages; specialized CRA mortgages; and portions of 
depository portfolios that are not available for purchase by the GSEs 
at the time of mortgage origination.
    HUD disagrees with the comments offered by the GSEs advocating 
exclusion of those market segments that they have not yet been able to 
penetrate. The conventional, conforming market represents the 
appropriate benchmark for evaluating GSE performance as discussed 
previously, even if this is not the market that the GSEs perceive as 
available for them to purchase. However, with respect to the subprime 
market, HUD believes that the risky, B&C portion of that market should 
be excluded from the market estimates for each of the housing goals. 
Thus, HUD includes only the A-minus portion of the subprime market in 
its overall estimates of the goals-qualifying market shares.
    Excluding other important segments of the mortgage market as the 
GSEs recommend would render the resulting market benchmark useless for 
evaluating the GSEs' performance. The loans that the GSEs would exclude 
are important sources of goals credit and, in fact, are the very loans 
the GSEs are supposed to be reaching out to finance. A recent report by 
the Department of Treasury demonstrated the targeting of CRA-type loans 
to lower-income and minority families. Numerous studies have shown that 
the manufactured home sector is an important source of low-income 
housing. In many of these markets, a more active secondary market could 
encourage lending to traditionally underserved borrowers. While HUD 
recognizes that some segments of the market may be more challenging for 
the GSEs to enter than others, the data reported in Figure 2 of this 
Appendix show that the GSEs have ample opportunities to purchase goals-
qualifying mortgages. Furthermore, HUD recognizes the challenge of 
reaching segments of these markets by not setting each goal at the very 
top of its market estimate range.
    Finally, it should also be noted that 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--after these loans have 
seasoned and the GSEs have had the opportunity to observe their payment 
performance.
    g. HUD's Determination. HUD carefully examined the comments on its 
analysis of the statutory factors used to determine the appropriate 
level of the housing goals, particularly the methodology used to 
establish the market share for each of the goals. Based on that 
evaluation, as well as HUD's additional analysis of its estimates, HUD 
determined that its basic methodology is a reasonable and valid 
approach to estimating market share and that the percentage ranges for 
each of the three market share estimates do not need to be adjusted 
from those provided in the proposed rule. While a number of technical 
changes have been made in this final rule in response to the comments, 
the approach for determining market size has not been modified 
substantially. The detailed evaluations show that the methodology, as 
modified, produces conservative estimates of the market share for each 
goal. 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.
5. Period Covered by the Housing Goals
    This final rule establishes housing goals for the years 2001 
through 2003. The proposed rule would have established housing goals 
for the GSEs for the year 2000 as well as 2001-2003, with higher 
housing goals than currently required for 2000, a transition year, and 
still higher goals for 2001-2003.
    The GSEs commented that since the proposed rule would have set 
transitional goals for 2000, if the goals are established later in 
2000, then 2001 should become the transition year.
    HUD has considered the issue and concluded that while it could 
establish higher ``transitional'' goals for 2000 as were proposed late 
in the year, and require that the GSEs perform at the new goal levels, 
given the publication date of this final rule, HUD will not require 
that the GSEs meet higher goals for 2000.
    At the same time, HUD has determined that establishing 2001 as a 
transition year is unnecessary and unwarranted. The goal levels for the 
years 2001-2003, and 2000, were announced in July 1999 and formally 
proposed earlier this year, providing the GSEs ample notice of the goal 
levels expected for these years. Indeed, data indicate that the GSEs 
have increased their efforts in 2000 in light of the proposed 2001-2003 
levels. Moreover, the Department's analysis of the statutory factors 
supports establishment of the goals for 2001-2003 at the levels 
proposed as both reasonable and feasible. Accordingly, the housing 
goals for 2000 shall remain at the levels previously established in 
accordance with Secs. 81.12(c)(3), 81.13(c)(3), and 81.14(c)(3) of the 
regulations as they existed prior to the effectiveness of this final 
rule. The housing goals for 2001-2003 are established at the levels HUD 
proposed.
    The Department believes the new goal levels established by this 
rule to be appropriate based upon consideration of the statutory 
factors and comments received. Setting the goal levels for years 2001-
2003 provides the GSEs with a level of predictability to enable them to 
develop and implement business strategies to achieve the goals.
6. 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 for each of the years 2001-
2003 that are affordable to low- and moderate-income families at 50 
percent. A short discussion of the statutory factors received follows. 
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.''

[[Page 65062]]

    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 50-55 percent of total units financed 
in the overall conventional, conforming mortgage market during the 
period 2001 through 2003. HUD has developed a reasonable range, rather 
than a point estimate, that accounts for significantly more adverse 
economic conditions than have existed recently.
    b. Past Performance of the GSEs under the Low- and Moderate-Income 
Housing Goal. During the transition period from 1993 through 1995, 
Fannie Mae's performance under the Low- and Moderate-Income Housing 
Goal jumped sharply in one year, from 34.2 percent in 1993 to 44.8 
percent in 1994, before declining to 42.3 percent in 1995. It then 
stabilized at just over 45 percent in 1996 and 1997. Fannie Mae's 
performance in 1998 declined to 44.1 percent due in large measure to 
the high volume of refinance loans that Fannie Mae funded in 1998, 
before rising to 45.9 percent in 1999.
    During the same period, Freddie Mac demonstrated more consistent 
gains in performance under the Low- and Moderate-Income Housing Goal, 
from 29.7 percent in 1993 to 37.4 percent in 1994 and 38.9 percent in 
1995. Freddie Mac then achieved 41.1 percent in 1996, and 42.6 percent 
and 42.9 percent in 1997 and 1998, respectively. In 1999, Freddie Mac's 
performance increased sharply to 46.1 percent.
    The housing goals that have been in effect prior to this final rule 
specified that in 1996 at least 40 percent of the number of units 
financed by mortgage purchases of the GSEs and eligible to count toward 
the Low- and Moderate-Income Goal should qualify as low- and moderate-
income, and at least 42 percent should qualify as such in each year 
from 1997 through 1999. Fannie Mae surpassed these goal levels by 5.6 
percentage points in 1996, 3.7 percentage points in 1997, 2.1 
percentage points in 1998, and 3.9 percentage points in 1999. Freddie 
Mac surpassed the goals by 1.1 percentage points, 0.6 percentage 
points, 0.9 percentage points and 4.1 percentage points in 1996, 1997, 
1998 and 1999, respectively.
    Fannie Mae's performance on the Low- and Moderate-Income Housing 
Goal has surpassed Freddie Mac's in every year but one, 1999, when 
Freddie Mac slightly outperformed Fannie Mae (46.1 percent versus 45.9 
percent). However, Freddie Mac's 1999 performance represented a 55 
percent increase over its 1993 level, exceeding the 34 percent increase 
by Fannie Mae over the same period, recognizing, however, that Fannie 
Mae's 1993 performance was significantly greater than Freddie Mac's.
    The GSEs' performance under the Low- and Moderate-Income Housing 
Goal for the 1996 through 1999 period is summarized below:

           Summary of GSEs' Performance Under the Low- and Moderate-Income Housing Goal 1996-1999 \32\
                                                [In percentages]
----------------------------------------------------------------------------------------------------------------
                                                                  1996         1997         1998         1999
----------------------------------------------------------------------------------------------------------------
Required Goal Level.........................................           40           42           42           42
Fannie Mae: Percent Low- and Moderate-Income................         45.6         45.7         44.1         45.9
Freddie Mac: Percent Low- and Moderate-Income...............         41.1         42.6         42.9         46.1
----------------------------------------------------------------------------------------------------------------

    Freddie Mac's improved performance since 1993 is due mainly to its 
increased purchases of multifamily loans as it has again become active 
in this market. Some housing industry observers believe that the 
establishment of the Low- and Moderate-Income Housing Goal has been an 
important factor in explaining Freddie Mac's re-entry into the 
multifamily market. In fact, as indicated above, multifamily mortgage 
purchases represent a significant component of both GSEs' activities in 
meeting the Low- and Moderate-Income Housing Goal, even though 
multifamily loans comprise a relatively small portion of the GSEs' 
business activities. In 1999, while Fannie Mae's multifamily purchases 
represented only nine percent of its total mortgage acquisition volume 
measured in terms of dwelling units, these purchases comprised 20 
percent of units qualifying for the Low- and Moderate-Income Housing 
Goal. Multifamily purchases were eight percent of the units financed by 
Freddie Mac's 1999 mortgage purchases but represented 17 percent of the 
units comprising Freddie Mac's low- and moderate-income mortgage 
purchases.
    c. Summary of Comments. A number of commenters recommended that the 
Low- and Moderate-Income Housing Goal include separate goals targeting 
a portion of the GSEs' business to multifamily housing and a portion to 
single family housing. While there are distinctly different issues 
relevant to the single family market and the multifamily market, the 
Department does not believe that it is necessary or appropriate to 
establish separate goals for those two markets. First, the increased 
level of the Low- and Moderate-Income Housing Goal in this final rule 
will require an increase in both single family and multifamily mortgage 
purchases. HUD's present analysis of these markets indicates that a 
unitary goal will best achieve increased performance in both markets. 
Second, this final rule adopts a number of incentives to encourage the 
GSEs to move into markets with unmet needs including the financing of 
smaller multifamily properties. HUD will, however, continue to examine 
market needs and evaluate the effects of the goal structure established 
in this final rule on the GSEs' single family and multifamily mortgage 
purchase performance. Based on this ongoing review, HUD may at a future 
date consider separate single family and multifamily goals or subgoals 
under the Low- and Moderate-Income Housing Goal, as warranted.
    Fannie Mae expressed no objection to the higher goal level, 
provided the Department retains the proposed housing goals framework, 
including the proposed changes to the counting rules, in the final 
rule. Freddie Mac supports the goal framework included in the proposed 
rule and is committed to meeting the new goal levels. The Department's 
response to the issues raised by Fannie Mae and Freddie Mac relative to 
HUD's market share methodologies and its analysis of the statutory 
factors are discussed above.
    Overall, other commenters were supportive of the proposed increase 
in the Low- and Moderate-Income Housing Goal. One group of commenters 
thought that, since the GSEs are mandated to lead the market, the level 
of the Low- and Moderate-Income Housing Goal should be increased 
further. Another group of commenters supported the increased level of 
the goal, but felt the Department needed to be prepared to

[[Page 65063]]

accommodate shifts in economic conditions that may have a negative 
impact on the GSEs' ability to meet the housing goals.
    d. 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. 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, 
demonstrates 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 2001 
to 2003, 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 50 percent of 
eligible units financed in each of the years 2001, 2002 and 2003. The 
new goal level will increase the GSEs' current level of performance to 
a level that is consistent with reasonable estimates of the low- and 
moderate-income housing market.
7. Central Cities, Rural Areas, and Other Underserved Areas Goal, 
Sec. 81.13
    This section discusses the Department's consideration of the 
statutory factors in arriving at and comments received on the proposed 
new housing goal level for the Central Cities, Rural Areas, and Other 
Underserved Areas Housing Goal (the Geographically Targeted Goal).
    The Geographically Targeted Goal focuses on areas currently 
underserved by the mortgage finance system. The 1995 Final Rule 
provided that mortgage purchases count toward the Geographically 
Targeted Goal if such purchases finance properties that are located in 
underserved census tracts. In Sec. 81.2, HUD defined ``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 
percent 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 count toward the Geographically Targeted Goal where such 
purchases finance properties that are located in underserved counties. 
These are defined as counties where either: (1) The median income in 
the county does not exceed 95 percent of the greater of the state or 
nationwide non-metropolitan median income; or (2) minorities comprise 
at least 30 percent of the residents and the median income in the 
county does not exceed 120 percent of the state non-metropolitan median 
income.
    After analyzing the statutory factors and considering the comments, 
this final rule establishes the goal for the percentage of dwelling 
units financed by each GSE's mortgage purchases on properties that are 
located in underserved areas for each of the years 2001-2003 be 31 
percent. A short discussion of the statutory factors follows. 
Additional information analyzing each of the statutory factors is 
provided in Appendix B, ``Departmental Considerations to Establish the 
Central Cities, Rural Areas, and Other Underserved Areas Goal,'' and 
Appendix D, ``Estimating the Size of the Conventional Conforming Market 
for Each Housing Goal.''
    a. Market Estimate for the Geographically Targeted Goal. The 
Department estimates that dwelling units in underserved areas will 
account for 29-32 percent of total units financed in the overall 
conventional, conforming mortgage market during the period 2001 through 
2003. HUD has developed a reasonable range, rather than a point 
estimate, that accounts for significantly more adverse economic 
conditions than have existed recently.
    b. Past Performance of the GSEs under the Geographically Targeted 
Goal. The housing goals that have been in effect prior to this final 
rule required that in 1996 at least 21 percent of the units financed by 
the GSEs' mortgage purchases should count toward the Geographically 
Targeted Goal, and at least 24 percent in 1997 through 1999. Fannie Mae 
surpassed the goal by 7.1 percentage points in 1996, 4.8 percentage 
points in 1997, 3.0 percentage points in 1998, and 2.8 percentage 
points in 1999. Freddie Mac surpassed the goal by 4.0, 2.3, 2.1 and 3.5 
percentage points in 1996, 1997, 1998, and 1999, respectively. The 
GSEs' performance for the 1996-99 period is summarized below:

                Summary of GSE Performance Under the Geographically Targeted Goal 1996-1999 \33\
                                                [In percentages]
----------------------------------------------------------------------------------------------------------------
                                                                  1996         1997         1998         1999
----------------------------------------------------------------------------------------------------------------
Required Goal Level.........................................           21           24           24           24
Fannie Mae: Percent Geographically Targeted.................         28.1         28.8         27.0         26.8
Freddie Mac: Percent Geographically Targeted................         25.0         26.3         26.1         27.5
----------------------------------------------------------------------------------------------------------------

    Although both GSEs have improved their performance in underserved 
areas, on average, their mortgage purchases continue to lag the primary 
market in providing financing for housing in these areas. On average, 
during the 1996-1998 period, mortgage purchases on properties in 
underserved areas accounted for 19.9 percent of Freddie Mac's purchases 
of single family home purchase mortgages, compared with 22.9 percent of 
Fannie Mae's purchases, 25.8 percent of mortgages retained by portfolio 
lenders, and 24.9 percent of all home purchase mortgages originated in 
the conventional, conforming market. These figures indicate that 
Freddie Mac has been less likely than Fannie Mae to purchase mortgages 
on properties in underserved neighborhoods. Through 1998, Freddie Mac 
had not made progress in reducing the gap between its performance and 
that of the overall market. In 1992, underserved areas accounted for 
18.6 percent of Freddie Mac's purchases of home purchase mortgages and 
for 22.2 percent of such mortgage loans originated in the conforming 
market, which yields a ``Freddie Mac-to-Market'' ratio \34\ of

[[Page 65064]]

0.84. By 1998, the ``Freddie Mac-to-Market'' ratio had actually fallen 
to 0.81. During the same period, the ``Fannie Mae-to-Market'' ratio 
increased from 0.82 to 0.93. However, in 1999, Freddie Mac's purchase 
share for underserved area loans increased while Fannie Mae's declined. 
In 1999, underserved areas accounted for 21.2 percent of Freddie Mac's 
home purchase mortgage loan acquisitions, compared with 20.6 percent 
for Fannie Mae.\35\
    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 performance in underserved areas must be derived from mortgages on 
housing for lower income families. In 1999, housing for above median-
income households accounted for about half of the single family owner-
occupied mortgages the GSEs purchased in underserved areas.
    c. Summary of Comments. Fannie Mae expressed no objection to the 
higher goal level provided the Department retains the proposed housing 
goals framework, including the proposed changes to the counting rules, 
in the final rule. Freddie Mac supported the overall goal framework 
included in the proposed rule but recommended that the Geographically 
Targeted Goal be set at 30 percent. Freddie Mac noted that it was 
committed to stretching to meet the proposed new goal levels, but 
believed that the level of the Geographically Targeted Goal was set too 
far toward the high end of the market estimate, making it more 
difficult to achieve. The Department's response to the issues raised by 
both Fannie Mae and Freddie Mac relative to HUD's estimates of the 
markets and its analysis of the statutory factors used to set the level 
of the goals was discussed above.
    Overall, other commenters were supportive of the proposed increase 
in the Geographically Targeted Goal. Certain commenters noted that by 
placing the level of the goal around the midpoint of the estimate of 
market size, the GSEs will be encouraged to move into a market 
leadership position. Another group of commenters supported the 
increased level of the goal, but felt the Department needed to be 
prepared to accommodate changes in economic circumstances that may have 
a negative impact on the GSEs' ability to meet the housing goals.
    d. HUD's Determination. The Geographically Targeted Goal 
established in this final rule is reasonable and appropriate, 
considering the factors set forth in FHEFSSA. The Department's market 
share estimates for the Geographically Targeted Goal accommodate a 
variety of economic scenarios. In addition, a current examination of 
the gaps in the mortgage markets, along with the estimated size of the 
market available to the GSEs, demonstrates the opportunities for the 
GSEs to purchase mortgages secured by housing in underserved areas of 
the nation.
    Therefore, having considered all statutory factors including 
housing needs, projected economic and demographic conditions for 2001 
to 2003, the GSEs' past performance, the size of the market for central 
cities, rural areas and other underserved areas, and the GSEs' ability 
to lead the market while maintaining a sound financial condition; HUD 
is establishing the annual goal for mortgage purchases qualifying under 
the Geographically Targeted Goal to be 31 percent of eligible units 
financed in each of the years 2001, 2002 and 2003. The new goal level 
will increase the GSEs' current level of performance to a level that is 
consistent with reasonable estimates of the housing market in 
underserved areas.
8. 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 
counts mortgages on housing for very low-income families and low-income 
families living in low-income areas. After consideration of these 
factors and the comments received, this final rule establishes the goal 
for the percentage of the total number of dwelling units financed by 
each GSE's mortgage purchases for housing affordable to very low-income 
families and low-income families living in low-income areas for each of 
the years 2001-2003 at 20 percent. A short discussion of the statutory 
factors 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 23-26 percent of total units financed in the overall 
conventional, conforming mortgage market during the period 2001 through 
2003. HUD has developed a reasonable range, rather than a point 
estimate, that accounts for significantly more adverse economic 
conditions than have existed recently.
    b. Past Performance of the GSEs under the Special Affordable 
Housing Goal. The Special Affordable Housing Goal is designed to ensure 
that the GSEs serve the very low- and low-income portion of the housing 
market. However, analysis of HMDA data shows that the shares of 
mortgage loans for very low-income homebuyers are smaller for the GSEs' 
mortgage purchases than for depository institutions and others 
originating mortgage loans in the conforming conventional market. HUD's 
analysis suggests that the GSEs should improve their performance in 
providing financing for the very low-income housing market.
    The housing goals that have been in effect prior to this final rule 
specified that in 1996 at least 12 percent of the number of units 
eligible to count toward the Special Affordable Housing Goal should 
qualify as special affordable, and at least 14 percent in 1997 through 
1999. As indicated below, Fannie Mae surpassed the goal by 3.4 
percentage points in 1996, 3.0 percentage points in 1997, 0.3 
percentage points in 1998 and 3.6 percentage points in 1999. Freddie 
Mac surpassed the goal by 2.0, 1.2, 1.9, and 3.2 percentage points in 
1996, 1997, 1998, and 1999, respectively. The GSEs' performance for the 
1996-99 period is summarized below:

                Summary of GSE Performance under the Special Affordable Housing Goal 1996-1999 36
----------------------------------------------------------------------------------------------------------------
                                                               1996  (in    1997  (in    1998  (in    1999  (in
                                                                percent)     percent)     percent)     percent)
----------------------------------------------------------------------------------------------------------------
 Required Goal Level........................................           12           14           14           14
 Fannie Mae:
     Percent Low-and Moderate-Income........................         15.4         17.0         14.3         17.6
 Freddie Mac:

[[Page 65065]]

 
     Percent Low-and Moderate-Income........................         14.0         15.2         15.9         17.2
----------------------------------------------------------------------------------------------------------------

    As noted above, HMDA and GSE data for metropolitan areas show that 
both GSEs lag depository institutions and other lenders in providing 
financing for home loans that qualify for the Special Affordable 
Housing Goal. Special affordable loans, which include loans for very 
low-income borrowers and low-income borrowers living in low-income 
areas, accounted for 9.8 percent of Freddie Mac's purchases of home 
purchase mortgages during 1996-98, 11.9 percent of Fannie Mae's 
purchases, 16.7 percent of newly originated loans retained by 
depository institutions, and 15.3 percent of all new originations in 
the conventional, conforming market. While Freddie Mac has improved its 
special affordable lending since the housing goals were put in place in 
1993, up until 1999 it had not made as much progress as Fannie Mae in 
closing the gap with depository institutions and other lenders in the 
home loan market. In 1998, Freddie Mac's special affordable performance 
was 73 percent of the primary market proportion of home loans that 
would qualify under the Special Affordable Housing Goal, compared to 
Fannie Mae's performance of 85 percent during the same period. In 1999, 
Freddie Mac did match Fannie Mae, as special affordable loans accounted 
for 12.5 percent of its home loan purchases versus 12.3 percent of 
Fannie Mae's home loan purchases. Market data for 1999 are not yet 
available.
    The multifamily market 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 multifamily units meeting 
the Special Affordable Housing Goal. For example, in 1999, 56 percent 
of units financed by Fannie Mae's multifamily mortgage purchases met 
the Special Affordable Housing Goal, representing 31 percent of units 
counted toward the Special Affordable Housing Goal, at a time when 
multifamily units represented only nine percent of its total purchase 
volume.37
    c. Summary of Comments. Fannie Mae expressed no objection to the 
higher goal level, provided the Department retains the proposed housing 
goals framework, including the proposed changes to the counting rules, 
in the final rule. Freddie Mac supported the goal framework included in 
the proposed rule and is committed to stretching to meet the new goal 
levels. The Department's response to the issues raised by both Fannie 
Mae and Freddie Mac relative to HUD's market share methodologies and 
its analysis of the statutory factors used to set the level of the 
goals was discussed above.
    Overall, other commenters were supportive of the proposed increase 
in the Special Affordable Housing Goal. One group of commenters thought 
that, since the GSEs are mandated to lead the market, the level of the 
Special Affordable Housing Goal should be increased even more, at a 
minimum, to the lower range of the Department's market share, at 23-24 
percent. Another group of commenters supported the increased level of 
the goal but felt the Department needed to be prepared to accommodate 
changes in economic circumstances that may have a negative impact on 
the GSEs' ability to meet the housing goals.
    d. HUD Determination. The Special Affordable Housing Goal 
established in the final rule is reasonable and appropriate, 
considering the factors set forth in FHEFSSA. The market share 
estimates for this goal reflect a variety of economic scenarios 
significantly more adverse than have existed recently. 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 housing for special affordable 
families is more than sufficient for the GSEs to achieve the goal.
    Having considered all statutory factors including housing needs, 
projected economic and demographic conditions for 2001 to 2003, the 
GSEs' past performance, the size of the market serving very low-income 
families and low-income families living in low-income areas, and the 
GSEs' ability to lead the market while maintaining a sound financial 
condition; HUD is establishing the annual goal for mortgage purchases 
qualifying under the Special Affordable Housing Goal at 20 percent of 
eligible units financed by each GSE in each of the years 2001, 2002 and 
2003. This new goal level will increase the GSEs' current level of 
performance to a level that is consistent with reasonable estimates of 
the special affordable housing market.
    e. Special Affordable Housing Goal: Multifamily Subgoal. This final 
rule modifies the proposed rule by implementing a multifamily subgoal 
based upon each GSE's respective average mortgage purchase volume for 
the years 1997 through 1999. The proposed rule suggested that the 
subgoal be established at 0.9 percent of each GSE's dollar volume of 
combined 1998 mortgage purchases in 2000 and at 1.0 percent of combined 
1998 mortgage purchases from 2001 through 2003. In this final rule, the 
level of the subgoal is established at a fixed level of one percent of 
the average of each GSE's respective dollar volume of combined (single 
family and multifamily) mortgage purchases in the years 1997, 1998 and 
1999. This level is $2.85 billion for Fannie Mae and $2.11 billion for 
Freddie Mac, in each of the years 2001 through 2003.
    f. Summary of Comments. Both Fannie Mae and Freddie Mac opposed 
establishing the special affordable multifamily subgoal as a percentage 
of their 1998 transaction volumes, stating that 1998 was in some 
respects an unusual year in the mortgage markets. Instead, they both 
recommended that the special affordable multifamily subgoal be 
established as a percentage of a five year average of each GSE's 
transactions volume. Freddie Mac commented further that HUD's proposed 
subgoal was unreasonably high.
    Many other commenters supported the multifamily subgoal, although 
they questioned whether 1998 was the appropriate base year upon which 
to establish the subgoal. Some commenters asserted that the proposed 
subgoal was too high, in light of an expected decline in multifamily 
origination volume. Other commenters noted that the subgoal was too 
low, based on the needs of very low- and low-income families and those 
in rural areas. Yet, others agreed the subgoal should continue to be 
percentage based, but argued that the baseline year should move from 
year to year. Still other commenters felt that the multifamily subgoal 
should be eliminated, as it no longer appears to serve a purpose, 
particularly since Freddie Mac has re-entered the multifamily market.

[[Page 65066]]

    g. HUD's Determination. Both the multifamily mortgage market and 
Freddie Mac's multifamily transactions volume have grown significantly 
during the 1990's, indicating both increased opportunity and capacity 
to grow by Freddie Mac. While Freddie Mac continues to lag behind 
Fannie Mae somewhat in its multifamily volume, it appears to be within 
reach of catching up with its larger competitor with regard to the 
multifamily proportion of total purchases. In 1999, Fannie Mae's 
multifamily mortgage purchases were 9.5 percent of its total mortgage 
purchases and Freddie Mac's multifamily mortgage purchases were 8.3 
percent of its total mortgage purchases.
    Freddie Mac's multifamily special affordable transactions volume 
was $2.7 billion in 1998 and $2.3 billion in 1999, which demonstrates 
Freddie Mac's capacity to generate significant multifamily special 
affordable volume in a favorable market environment. However, the 
Department is mindful of the fact that the multifamily market 
conditions experienced during 1998 were very favorable and may not be 
fully representative of future years. HUD expects conventional 
multifamily volume in 2001 through 2003 to be somewhat lower than the 
level reached during 1998.
    The Special Affordable Housing Multifamily Subgoal established in 
this final rule is 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. Now that more recent data is available, it is apparent that 
taking 1999 mortgage volume into consideration, along with that of 1997 
and 1998, more accurately corresponds to the relative size and 
respective capabilities of the GSEs over the 2001-2003 goals period. 
Accordingly, as noted above, this final rule establishes each GSE's 
special affordable multifamily subgoal at the respective average of one 
percent of that GSEs' combined mortgage purchases over 1997 through 
1999.
    h. Multifamily Subgoal Alternatives. In the proposed rule, HUD 
identified three alternative approaches for specifying multifamily 
subgoals for the GSEs based on a (i) minimum number of units; (ii) 
minimum percentage of multifamily acquisition volume; and (iii) minimum 
number of mortgages acquired. While some of these proposals did receive 
support from commenters, HUD does not see any compelling reason to 
alter the dollar based structure of the multifamily subgoal as 
established in the regulations, which can be updated and adapted to the 
current market environment by basing it upon recent acquisition volume. 
It is noteworthy that the Special Affordable Housing Goal, as a 
percentage of business goal based on the number of units financed, 
combines elements of options (i) and (iii). HUD's decision to award 
bonus points toward the housing goals for GSE transactions involving 
small multifamily properties with 5-50 units will achieve some of the 
intended policy objectives associated with option (iii).
9. Bonuses and Subgoals
    a. Overview. The Department proposed to introduce a system of bonus 
points to encourage the GSEs to increase their activity in specified 
underserved markets that serve low- and moderate-income families and 
families in underserved areas. Bonus points were specifically proposed 
to encourage increased involvement by the GSEs under goals established 
for the years 2000-2003 for purchases of mortgages financing small 
multifamily properties (5-50 units) and two to four unit owner-occupied 
properties that contain rental units. The areas for which bonus points 
were suggested are areas in which the GSEs' mortgage purchases have 
traditionally played a minor role but which provide significant sources 
of affordable housing and for which the need for mortgage credit 
persists. As a regulatory incentive to encourage the GSEs to increase 
their mortgage purchase activity in underserved markets, the Department 
proposed the use of bonus points for mortgage purchases in these 
important segments of the housing market. HUD also sought comments on 
the utility of applying bonus points and other regulatory incentives 
such as subgoals to other underserved segments of the market including 
manufactured housing, multifamily properties in need of rehabilitation, 
and properties in tribal areas.
    This final rule incorporates the use of bonus points for small 
multifamily properties and owner-occupied single family rental 
properties as proposed for the years 2001 through 2003.
    b. Summary of Comments. Fannie Mae and Freddie Mac commented in 
detail on the use of bonus points and subgoals. Fannie Mae supported 
the use of bonus points to provide incentives to expand its presence in 
the markets for both the small multifamily and single family owner-
occupied, 2-4 unit property. Fannie Mae opposed the use of subgoals for 
that purpose, however, arguing that they would result in 
micromanagement of its business operation. Fannie Mae added that 
``these two property types pose great difficulties for the secondary 
market to serve and will require new channels, new products, new modes 
of operation, and significant investments to better understand the 
risks.'' Fannie Mae also recommended that if the Department adopts 
bonus points, the points should continue beyond 2003.
    Freddie Mac supported using bonus points and opposed using subgoals 
for small multifamily and single family owner-occupied, 2-4 unit 
property mortgage acquisitions. As with Fannie Mae, Freddie Mac 
commented that subgoals would result in micromanagement of its 
business. Freddie Mac also recommended calculating the threshold for 2-
4 unit properties based on the period from 1995-1999 instead of using a 
five-year rolling average. Overall, Freddie Mac commented that it would 
prefer bonus points to subgoals for any targeted market segments.
    Other commenters were generally supportive of the use of bonus 
points, with many noting that bonus points were preferable to 
additional subgoals. This group of commenters felt that additional 
subgoals would result in micromanagement of the GSEs' business 
operations but felt that bonus points provided an incentive rather than 
a mandate to move into markets that were underserved.
    One group of commenters was opposed to bonus points. Among many of 
these commenters, however, there was support for incentives for the 
GSEs to purchase mortgages on small rental properties, noting that the 
market is underserved and provides an excellent source of affordable 
rental housing. Specific comments regarding the use of bonus points 
concluded that bonus points would: (a) Allow the GSEs to meet the goals 
with less effort and that they might lead the GSEs to relax their 
single family efforts; and (b) inflate goal performance numbers. It was 
suggested by several commenters that subgoals would be a more 
appropriate vehicle to encourage the GSEs' involvement in those 
segments of the market as well as other segments, e.g., mortgages made 
to

[[Page 65067]]

minority borrowers and home purchase mortgages. Some commenters 
suggested that since there was evidence that the small multifamily 
mortgage market is well served by community banks, thrifts and small 
life insurance companies, there is no need for HUD to award bonus 
points as an incentive for the GSEs to enter that market.
    c. HUD's Determination. This final rule adopts the two categories 
for bonus points that were proposed by the Department. Bonus points are 
a temporary incentive for the GSEs to step up their efforts to serve 
this particular need. Availability of bonus points for this purpose 
beyond 2003, therefore, will require a determination by the Department 
that the bonus points continue to serve this need. HUD's research and 
analysis indicates that there is substantial unmet need in these two 
areas and believes that these are markets the GSEs should serve better. 
While HUD has determined to establish bonus points in the two market 
areas proposed, HUD does not believe that either the use of subgoals, 
that would be unenforceable under FHEFSSA (except for the Special 
Affordable Housing Goal), or bonus points amounts to micromanagement of 
the GSEs. By utilizing bonus points the GSEs can choose whether to 
increase their presence in these markets, and by evaluating the impact 
of these incentives on the GSEs' mortgage purchase patterns, the 
Department can evaluate the reasonableness and effectiveness of bonus 
points as a tool to increase activity in specific markets.
    d. Additional Bonus Points and Subgoals. Commenters suggested a 
wide variety of other areas to consider for either bonus points and/or 
subgoals including those for which views were invited. Suggestions by 
commenters for subgoals included home purchase mortgages and mortgages 
to minority borrowers. Commenters also suggested either bonus points 
and/or subgoals for reverse mortgages, groups with low homeownership 
rates, rural multifamily housing programs, manufactured housing, and 
expiring Section 8 assistance contracts, among other types of 
transactions. While there was some support for directing bonus points 
for encouraging GSE financing for minorities there was, however, no 
consensus among the commenters for this or other specific categories 
that bonus points and subgoals should address. Since HUD believes that 
the increased goals under this rule will result in increased financing 
of affordable housing and increased home ownership opportunities for 
minorities and other families in underserved areas, HUD has determined 
to establish bonus points only in the two categories proposed at this 
time. As indicated above, HUD will, however, monitor the effectiveness 
of these bonus points closely, based on these results and future 
housing needs, may establish bonus points for other mortgage purchases 
in the future.
10. Temporary Adjustment Factor for Freddie Mac
    a. Overview. To overcome any lingering effects of Freddie Mac's 
decision to dismantle and then cautiously reestablish a multifamily 
mortgage purchase program in the early 1990s, the Department proposed 
an incentive for Freddie Mac to further expand its scope of multifamily 
operations through the use of a temporary adjustment factor for its 
multifamily mortgage purchases in calculating its performance under the 
Low- and Moderate-Income Housing Goal and the Special Affordable 
Housing Goal. In determining Freddie Mac's performance for each of 
these two goals, the Department proposed that each unit in a property 
with more than 50 units meeting either of these two housing goals would 
be counted as 1.2 units in the numerator of the respective housing goal 
percentage. The temporary adjustment factor would be limited to 
properties with more than 50 units to avoid overlap with the proposal 
to award bonus points for multifamily properties with 5-50 units. 
Comments were requested on whether the proposed temporary adjustment 
factor for Freddie Mac was set at an appropriate level and whether such 
an adjustment factor should be phased out prior to 2003.
    This final rule incorporates the temporary adjustment factor for 
Freddie Mac for multifamily properties, other than those small 
multifamily units receiving bonus credit, as proposed for the years 
2001 through 2003.
    b. Summary of Comments. Fannie Mae and Freddie Mac commented in 
detail on the application of a temporary adjustment factor for Freddie 
Mac's multifamily business. Fannie Mae opposed the application of a 
temporary adjustment factor for Freddie Mac's multifamily business. 
Fannie Mae stated that Freddie Mac made a business decision to leave 
the multifamily market and HUD's action would effectively punish Fannie 
Mae for staying in the market. Fannie Mae recommended that instead of a 
temporary adjustment factor, HUD should lower Freddie Mac's goals to 
levels that would represent a similar ``stretch'' as the higher goal 
levels that would be established for Fannie Mae.
    Freddie Mac supported the idea of a temporary adjustment factor but 
recommended that it be set at a multiplier of 1.35 instead of 1.2. 
Noting that the difference in size and age between Freddie Mac's and 
Fannie Mae's multifamily portfolios makes goal achievement easier for 
Fannie Mae, Freddie Mac also recommended that the temporary adjustment 
factor apply to all three goals. Freddie Mac also opposed any phasing 
out or elimination of the adjustment factor.
    Other comments on the proposal were mixed. While there were many 
comments in support of the proposal, a number of commenters objected to 
the proposal, observing that by providing the temporary adjustment 
factor, HUD would be rewarding Freddie Mac for leaving the multifamily 
mortgage market in previous years. Commenters also suggested that the 
same objective could be achieved through the Special Affordable 
Multifamily Subgoal or by establishing separate housing goals for the 
single family and multifamily market. Many of these commenters said 
that, if the temporary adjustment factor were adopted for Freddie Mac, 
it should be phased out over a period of time.
    c. HUD's Determination. In the period since HUD's interim housing 
goals took effect in January 1993, the volume of Freddie Mac's 
multifamily mortgage purchase transactions has grown significantly, 
both in absolute terms and as a proportion of its total mortgage 
purchases. Freddie Mac's 1993 multifamily transactions volume was only 
$191 million, compared with $7.6 billion in 1999. In 1999, Freddie 
Mac's multifamily transactions volume represented 8.3 percent of units 
backing its total mortgage purchases, close to the Fannie Mae 
proportion of 9.5 percent. Thus, while Freddie Mac continues to lag 
behind Fannie Mae somewhat in its multifamily volume, it appears to be 
within reach of catching up with Fannie Mae with regard to the 
multifamily proportion of total purchases.
    In discussing the Department's appropriations for fiscal year 2000, 
the Conference Report stated in October, 1999 that ``* * * the stretch 
affordable housing efforts required of each of Freddie Mac and Fannie 
Mae should be equal, so that both enterprises are similarly challenged 
in attaining the goals. This will require the Secretary to recognize 
the present composition of each enterprise's overall portfolio in order 
to ensure regulatory parity in the application of regulatory guidelines 
measuring goal compliance.'' 38

[[Page 65068]]

    Consistent with Congress' October 1999 guidance, HUD's analysis 
indicates that a 1.2 adjustment factor applied to Freddie Mac's 
mortgage purchases for multifamily properties of more than 50 units for 
purposes of the Low- and Moderate-Income and Special Affordable Housing 
Goals, as proposed, is sufficient both to overcome any lingering 
effects of Freddie Mac's decision to leave the multifamily market in 
the early 1990s and to ``ensure regulatory parity,'' taking account of 
the recent magnitude of difference between the GSEs' respective 
multifamily shares of business and the multifamily market projections 
detailed in Appendix D. Therefore, while the goals are set at the same 
levels, the Department has decided to implement the temporary 
adjustment factor as proposed. The temporary adjustment factor of 1.2 
will be applied to the Low- and Moderate-Income Housing Goal and the 
Special Affordable Housing Goal. The temporary adjustment factor will 
terminate December 31, 2003. The temporary adjustment factor will not 
apply to Fannie Mae.
11. High Cost Mortgages
    a. Overview. The proposed rule requested comments on whether HUD 
should disallow goals credit for high cost mortgage loans, and if so, 
whether HUD should define high cost mortgage loans using the Home 
Ownership and Equity Protection Act (HOEPA) 39 or an 
alternative definition. HOEPA defines high cost mortgages as those that 
meet an annual percentage rate (APR) threshold (more than 10 percentage 
points above the yield on Treasury securities of comparable maturity; 
the Federal Reserve Board can adjust the threshold down to 8 percent or 
up to 12 percent), or a threshold for points and fees charged 
(exceeding the greater of 8 percent of the loan amount or $400--
adjusted for inflation to $451 for the year 2000). HOEPA requires 
additional disclosures and restricts certain loan terms (e.g., 
prepayment penalties, balloon payments, and negative amortization) and 
practices (e.g. failing to consider a borrower's ability to repay) for 
those mortgages.40
    The proposed rule also requested comments on the potential 
benefits, if any, associated with the GSEs' presence in the various 
higher cost mortgage markets, such as the standardization of 
underwriting guidelines or reductions in interest rates, as well as the 
potential dangers, if any, associated with the GSEs' presence in those 
markets. Finally, the proposed rule requested comments on what 
additional data would be useful for the purposes of monitoring the 
GSEs' activities in this area and on whether certain of these data 
elements should be included in the public use data base. The proposed 
rule noted that possible data elements that could be collected from the 
GSEs for monitoring include loan level data on the annual percentage 
rate, debt-to-income ratio, points and fees, and prepayment penalties.
    b. HUD/Treasury Report. On June 20, 2000, HUD and the Department of 
Treasury jointly released a report entitled ``Curbing Predatory Home 
Mortgage Lending,'' which detailed predatory or abusive lending 
practices in connection with higher cost loans in the subprime mortgage 
market. These practices include charging excessive fees, lending to 
borrowers without regard to their ability to repay, establishing 
prepayment penalties that prevent high cost borrowers from refinancing 
into lower cost loans, abusive terms and conditions that include 
packing loans with products such as single premium credit insurance, 
and other practices, including failing to steer borrowers to the 
lowest-cost product for which they qualify and incomplete reporting of 
borrowers' payment history to credit bureaus. The report recommended 
legislative and regulatory action to combat predatory lending while 
maintaining access to credit for low- and moderate-income borrowers. 
Respecting the secondary mortgage market, the report recommended that 
HUD restrict the GSEs from funding loans with predatory features since 
such loans may undermine homeownership by low- and moderate-income 
families. HUD and Treasury noted ``while the GSEs currently play a 
relatively small role in the subprime market today, they are beginning 
to reach out with new products in this marketplace.''
    Recently the GSEs have each announced corporate policies against 
the purchase of loans with certain features. Fannie Mae has established 
greater limitations than Freddie Mac, although Fannie Mae has been less 
involved in the subprime market to date. Fannie Mae announced that 
``[f]or loans delivered to Fannie Mae, the points and fees charged to a 
borrower should not exceed 5 percent, except where this would result in 
an unprofitable origination,'' and that Fannie Mae will not purchase 
high cost mortgages as defined under HOEPA. Fannie Mae announced 
further that it ``will not purchase or securitize any mortgage for 
which a prepaid single-premium credit life insurance policy was sold to 
the borrower,'' and that it will generally only allow prepayment 
penalties under the terms of a negotiated contract and where the lender 
adheres to the following criteria: A mortgage that has a prepayment 
penalty should provide some benefit to the borrower (such as a rate or 
fee reduction for accepting the prepayment premium); the borrower also 
should be offered the choice of another mortgage product that does not 
require payment of such premium; the terms of the mortgage provision 
that requires a prepayment penalty should be adequately disclosed to 
the borrower, and the prepayment penalty should not be charged when the 
mortgage debt is accelerated as a result of the borrower's default in 
making his or her mortgage payments.
    Fannie Mae also announced that it will not purchase loans from 
lenders who steer borrowers to higher cost products if those borrowers 
qualify for lower cost products. Freddie Mac announced that it will not 
purchase HOEPA loans, nor will it purchase mortgage loans with single-
premium credit life insurance. Both GSEs have announced that they will 
require lenders who sell them loans to file monthly full-file credit 
reports on every borrower. While the GSEs' policies differ somewhat in 
their scope and specificity, both have publicly expressed strong 
concern about predatory lending practices and have adopted policies 
requiring them to look harder at particular loan terms and their 
seller/servicers' business practices, and restricting their purchases 
of loans originated with such terms and practices. However, the GSEs' 
broad guidelines describing the characteristics of loans that they 
intend to make ineligible for purchase lack important details and are 
subject to changes in corporate direction, or other changes. Therefore, 
HUD and Treasury recognized in the report that such corporate policies 
may not be sufficient and that regulations would be needed to address 
this issue.
    c. Summary of Comments. Many commenters on the proposed rule 
supported the disallowance of credit under the GSE housing goals for 
high cost mortgages. Some of these commenters commended the GSEs for 
beginning to offer quality loan products to credit-impaired borrowers. 
Those commenters argued, however, that restrictions on goals credit for 
certain loans would not prohibit the GSEs from purchasing all subprime 
loans but merely those that are likely to be predatory and wealth-
stripping. Other commenters argued that without adequate controls, the 
GSEs' forays into the subprime market will not translate

[[Page 65069]]

into lower costs for borrowers, but will only lower the cost of capital 
for subprime lenders.
    Some commenters wrote that the GSEs should not receive credit under 
the housing goals for high cost mortgages that are subject to HOEPA. 
Many other commenters felt that such a standard would not go far 
enough, and that the GSEs should not receive goals credit for 
purchasing loans with certain features. Such features would include 
fees greater than 3 percent of the loan amount, prepayment penalties on 
high cost loans, and prepaid single premium credit life insurance that 
is to be financed in the loan. Commenters also provided additional 
features for which the GSEs should not receive goals credit, including 
negative amortization and accelerating indebtedness, fees to renew or 
modify, balloon payments, yield spread premiums, mandatory arbitration, 
or high cost loans for which the borrower did not receive homeownership 
counseling.
    One commenter suggested that the Department should treat loans 
purchased from an institution that engages in predatory lending the 
same as loans that actually have predatory features in order to send a 
message that such lenders are not responsible business partners and to 
restrict further the availability of mortgage credit for such loans. 
Other commenters suggested that the GSEs should not be allowed to 
purchase subprime loans at all, so that they will have an incentive to 
develop conventional mortgage products to reach out to those borrowers. 
Another suggestion was that the GSEs should be affirmatively penalized 
for purchasing certain abusive mortgages (i.e., by subtracting points 
from the numerator but fully counting such loans in the denominator).
    A number of commenters suggested that GSEs should be required to 
conduct fair lending reviews of subprime loans before they purchase 
them in order to receive credit. Such reviews would include determining 
whether the lending institution is reporting borrowers' full payment 
histories to credit bureaus.
    Many of the commenters that supported the disallowance of goals 
credit for high cost loans and loans with certain harmful features 
asserted that the GSEs' support of such lending poses great risks. 
These commenters argued that the types of mortgage products that strip 
equity out of homes and lead to higher foreclosures are not consistent 
with the GSEs' public mission. Further, to the extent that defaults on 
these loans lead to losses, these commenters asserted that the GSEs' 
financial condition will likely be affected.
    With regard to data collection and reporting, several commenters 
suggested that the GSEs should be required to provide full information 
on their subprime loans, including the APR, total closing costs, 
points, and fees (including financed credit insurance premiums), 
delinquency and foreclosure rates, and the length of time between 
purchase and refinance on an aggregate basis.
    Both GSEs and a large group of commenters objected to the 
Department's proposal regarding the disallowance of goals credit for 
purchases of high cost mortgages. Many of those commenting in this 
regard provided substantially similar responses to those submitted by 
Fannie Mae. These commenters emphasized the difference between 
legitimate subprime lending and lending through the use of abusive and 
predatory practices such as those outlined in the HUD/Treasury report. 
Several of these commenters expressed concern that the Department 
should not take any action that would discourage the GSEs from serving 
the subprime market. The GSEs both remarked that they are using 
enhanced technology (e.g., their respective automated underwriting 
systems) to allow them to offer products targeted toward borrowers with 
impaired credit, and that they are, therefore, able to move into the 
legitimate subprime market in a responsible and prudent manner, 
bringing liquidity, standardization, and efficiency to that market. The 
GSEs argue that disallowing goals credit for high cost mortgages will 
provide a disincentive for them to reach out to those borrowers and 
will do nothing to combat the predatory lending practices about which 
the Department is concerned. Indeed, Fannie Mae argued that disallowing 
goals credit for high cost mortgages would simply drive predatory 
lending ``into the government market or to secondary market sources who 
are less responsible than Fannie Mae on this issue.''
    Fannie Mae argued that disallowing goals credit for high cost 
mortgages is inconsistent with the Department's inclusion of A-minus 
mortgages in the market estimates to which the Department compares the 
GSEs' performance. Fannie Mae further argued that the Department would 
need to ``recalibrate the goals'' in order to implement a system of 
disallowing goals credit for high cost mortgages, which would be 
``extremely difficult, if not impossible'' due to ``the lack of 
reliable market data on loan costs.''
    Nonetheless, Fannie Mae urged the Department to work with other 
regulatory agencies to collect more data on the problem. Freddie Mac 
urged the Department to await the outcome of any Federal legislative or 
regulatory initiatives that may arise as a result of the widespread 
concern and focus on these issues among members of Congress and 
regulatory agencies.
    The GSEs also both objected to any additional reporting 
requirements related to monitoring their purchases of high cost 
mortgages. Fannie Mae argued that the relevant information is not now 
captured in the primary market, and that collecting and reporting this 
information would force a ``tremendous change to the way the market 
operates.'' Freddie Mac similarly argued that the required data 
elements are not stored uniformly across lenders, and collecting and 
reporting such data elements would require ``substantial investments,'' 
the economic impacts of which would likely be considerable.
    d. HUD's Determination. After considering the issues raised by the 
commenters, the Department has determined that, in accordance with the 
Secretary's authority under section 1336(a)(2) of FHEFSSA, the GSEs 
should not be assigned credit toward the Affordable Housing Goals for 
purchasing certain high cost mortgages including mortgages with certain 
unacceptable features. The GSEs have a statutory responsibility to lead 
the industry in making mortgage credit available to low and moderate 
income families and underserved areas. In carrying out this 
responsibility, the GSEs should seek to make the lowest cost credit 
available while ensuring that they do not purchase loans that actually 
harm borrowers and support unfair lending practices. The HUD/Treasury 
report recommended regulatory and/or legislative restrictions that 
would go beyond the matter of goals credit and would prohibit the GSEs 
from purchasing certain types of loans with high costs and/or predatory 
features altogether. These proposals stem from the concern that 
mortgages with predatory features undermine homeownership by low-and 
moderate-income families in derogation of the GSEs' Charter missions. 
As pointed out in the HUD/Treasury Report, ``While the secondary market 
could be viewed as part of the problem of abusive practices in the 
subprime mortgage market, it may also represent a large part of the 
solution to the problem. If the secondary market refuses to purchase 
loans that carry abusive terms, or loans originated by lenders engaging 
in abusive practices, the primary market might

[[Page 65070]]

react to the resulting loss of liquidity by ceasing to make these 
loans.''
    Accordingly, consistent with and combining restrictions already 
voluntarily undertaken by both GSEs, this final rule restricts credit 
under the goals for purchases of high cost loans including mortgages 
with certain unacceptable terms and resulting from unacceptable 
practices. Specifically, the GSEs will not receive credit toward any of 
the Affordable Housing Goals for dwelling units financed by mortgages 
that come within HOEPA's thresholds for high cost mortgages, nor will 
they receive credit for mortgages with certain unacceptable features or 
resulting from unacceptable practices. The housing goals provide 
incentives to encourage GSE efforts to finance housing for low and 
moderate income families, housing in underserved areas, and special 
affordable housing. Therefore, HUD has determined that the GSEs should 
not receive the incentive of goals credit for purchasing high cost 
mortgages including mortgages with unacceptable features.
    (1) Mortgages that Come Within HOEPA's Thresholds. The final rule 
disallows goals credit for dwelling units financed by mortgages that 
come within HOEPA's thresholds, i.e., with an APR of 10 percentage 
points or higher above the yield on Treasury securities of comparable 
maturity, or with points and fees that are above the greater of 8 
percent of the loan amount or $451. HOEPA's thresholds provide a 
discernible and standard industry measure of a class of loans that are 
very high cost, that present a very high risk that their borrowers will 
lose their homes, and that the GSEs themselves have determined not to 
purchase. While originating such loans is not illegal, but rather made 
subject to additional disclosures and protections under HOEPA, loans at 
these levels should not be encouraged by receiving credit under the 
goals. In incorporating the HOEPA high cost loan standards in this 
rule, the thresholds are subject to adjustment by the Federal Reserve 
Board 41 or Congress. This rule is established to encompass 
such adjustments unless the GSEs are otherwise notified in writing by 
HUD. While HOEPA itself only covers closed end loans made to refinance 
existing mortgages and closed end home equity loans, this final rule 
also applies the HOEPA thresholds to home purchase mortgages.
    (2) Mortgages with Unacceptable Terms or Conditions or Resulting 
from Unacceptable Practices. This final rule also disallows goals 
credit for dwelling units financed by mortgages with features that the 
GSEs themselves, either through announced policies or practices, have 
identified as unfair to borrowers and unacceptable. Specifically, these 
include mortgages with:
    (a) Excessive fees, where the total points and fees charged to a 
borrower exceed 5 percent of the loan amount, except where this 
restriction would result in an unprofitable origination. For such 
cases, involving small loans, this rule provides a maximum dollar 
amount of $1000, or such other amount as may be requested by a GSE and 
determined appropriate by the Secretary, as an alternative to the 5 
percent limit. For purposes of this provision, points and fees include: 
(i) Origination fees, (ii) underwriting fees, (iii) broker fees, (iv) 
finder's fees, and (v) charges that the lender imposes as a condition 
of making the loan--whether they are paid to the lender or a third 
party. For purposes of this provision, points and fees would not 
include: (i) Bona fide discount points; (ii) fees paid for actual 
services rendered in connection with the origination of the mortgage, 
such as attorneys' fees, notary's fees, and fees paid for property 
appraisals, credit reports, surveys, title examinations and extracts, 
flood and tax certifications, and home inspections; (iii) the cost of 
mortgage insurance or credit-risk price adjustments; (iv) the costs of 
title, hazard, and flood insurance policies; (v) state and local 
transfer taxes or fees; (vi) escrow deposits for the future payment of 
taxes and insurance premiums; and (vii) other miscellaneous fees and 
charges that, in total, do not exceed 0.25 percent of the loan amount.
    This restriction on goals credit for mortgages with excessive fees 
does not, of course, supplant the restriction on goals credit for HOEPA 
loans. If a mortgage has fees that exceed 5 percent of the loan amount 
as described in the immediately preceding paragraph, but do not exceed 
the 8 percent/$451 threshold under HOEPA, the mortgage would not 
receive credit toward the goals. HUD, Treasury, the GSEs, and many 
others have recognized that mortgages with excessive fees are a 
particularly onerous problem and disproportionately affect the low- and 
moderate-income borrowers that the GSEs are to serve. Therefore, this 
final rule will remove any incentive under the goals for the GSEs to 
purchase loans with excessive fees as described above. Having said 
that, the HUD/Treasury report called upon the Federal Reserve Board to 
expand the HOEPA ``points and fees'' threshold to include certain 
additional types of fees, including (i) fees and amounts imposed by 
third party closing agents (except payments for escrow and primary 
mortgage insurance), (ii) prepayment penalties that are levied on a 
refinancing, and (iii) all compensation received by a mortgage broker 
in connection with the mortgage transaction. As mentioned above, if the 
Federal Reserve changes the HOEPA thresholds, such changes will be 
encompassed within HUD's housing goals, unless HUD notifies the GSEs 
otherwise.
    (b) Prepayment penalties, except where: (i) the mortgage provides 
some benefits to the borrower (e.g., such as rate or fee reduction for 
accepting the prepayment premium); (ii) the borrower is offered the 
choice of a mortgage that does not contain such a penalty; (iii) the 
terms of the mortgage provision containing the prepayment penalty are 
adequately disclosed to the borrower; and (iv) the prepayment penalty 
is not charged when the mortgage debt is accelerated as the result of 
the borrower's default in making his or her mortgage payments.
    (c) Single premium credit life insurance products sold in 
connection with the origination of the mortgage.
    (d) Evidence that the lender did not adequately consider the 
borrower's ability to make payments, i.e., mortgages that are 
originated with underwriting techniques that focus on the borrower's 
equity in the home, and do not give full consideration to the 
borrower's income and other obligations. Ability to repay must be based 
upon relating the borrower's income, assets, and liabilities to the 
mortgage payments.
    (3) Mortgages Contrary to Good Lending Practices. As the GSEs have 
recognized in their own policies and many of the commenters pointed out 
as well, while good mortgage lending practices can reduce costs to 
borrowers, contrary practices can result in loans that are higher cost 
to borrowers in ways that are not directly reflected in the interest 
rate, points, or fees. Therefore, to remove any goals incentive for the 
GSEs to purchase mortgages or categories of mortgages regarding which 
there is evidence that lenders engaged in specific practices contrary 
to good lending practices identified in the rule, this rule provides 
that the GSEs may not receive goals credit for such loans or categories 
of loans. These specific practices identified in this rule that lenders 
employ to avoid abusive lending include regularly reporting complete 
borrower information to credit agencies, avoiding steering borrowers to 
higher cost products, and complying with fair lending requirements.
    FHEFSSA and HUD's GSE regulations at 24 CFR 81.41, prohibit the 
GSEs from discriminating in any manner in making

[[Page 65071]]

any mortgage purchases because of race, color, religion, sex, handicap, 
familial status, age or national origin. Since abusive lenders often 
specifically target and aggressively solicit homeowners in 
predominantly lower-income and minority communities who may lack 
sufficient access to mainstream sources of credit, it is essential that 
the GSEs scrutinize lender practices to protect against buying loans 
that are the result of unlawful discrimination. For example, good 
lending practices that help lenders avoid unlawful discrimination 
include employee training programs, periodic loan sampling, 
specifically tailored recordkeeping and reporting requirements, and 
other reviews. The GSEs have reported, consistent with their pledges 
not to buy certain harmful loans, that they will be looking closer at 
the lending practices of entities with which they do business, and HUD 
commends those efforts. HUD will review the processes the GSEs employ 
to ascertain positive practices to avoid unlawful discrimination and 
steering borrowers to higher cost products, as well as monthly credit 
reporting. This final rule provides that where HUD finds evidence that 
loans or categories of loans do not conform to such positive practices, 
HUD may deny goals credit for such loans in accordance with 
Sec. 81.16(d) of this rule.
    HUD recognizes that the particular loan terms and practices that 
are identified as abusive and unacceptable may change as some 
unscrupulous actors adjust to new restrictions and as the GSEs and HUD 
gain experience with abuses. Accordingly, to allow flexibility this 
rule allows the Department to modify the list of terms and practices 
that will not receive goals credit, by providing that the GSEs may 
request modifications to the list and that the Secretary will after 
reviewing such submissions determine whether or not to change the 
abuses for which goals credit will be restricted. HUD also will 
continue to monitor the mortgage industry with regard to abusive 
lending practices and may determine that future modifications are 
necessary and require further rulemaking.
    The restrictions and provisions in sections (1), (2), and (3), 
above, address terms and practices that are harmful to mortgage 
borrowers. Accordingly, these restrictions and provisions in this rule 
apply to mortgages purchased through the GSEs' ``flow'' business, as 
well as mortgages purchased or guaranteed through structured 
transactions. Since these restrictions and provisions are consistent 
with the GSEs' own measures, the Department does not believe that any 
of these restrictions will provide a disincentive for the GSEs to 
provide financing for borrowers with slightly impaired credit through 
innovative products that can bring competition and efficiencies to the 
legitimate subprime market.
    While the GSEs themselves will presumably be obtaining certain 
additional data and information to carry out their previously announced 
purchase restrictions and to monitor lending practices, HUD is not 
establishing any requirements for additional data to carry out these 
provisions under this rule. Subsequently, HUD plans to request only 
such additional data as is necessary. In this regard, HUD will consult 
with the GSEs, as practicable, to develop reasonable data reporting 
requirements that will not present an undue additional burden.
12. Data On Unit Affordability, Sec. 81.15
    The GSEs have reported that at times it can be difficult and costly 
for them to obtain the data on incomes and rents that is necessary to 
establish affordability for goals purposes, especially for seasoned 
loan transactions and some negotiated transactions. HUD proposed to 
allow (1) the use of estimation techniques to approximate unit rents in 
multifamily properties where current rental information is unavailable 
and (2) the exclusion of units, both single family and multifamily, 
from goal calculations where it is impossible to obtain full data or 
estimate values, subject to certain limits.
    As has been discussed, GSE purchases of mortgages on rental 
properties disproportionately serve the affordable housing market. 
Typically, around 90 percent of rental units backing GSE mortgage 
purchases would count towards the Low- and Moderate-Income Housing Goal 
and around 50 percent would meet the affordability requirements of the 
Special Affordable Housing Goal (excluding missing data). HUD did not 
want the lack of data on affordability to act as a disincentive for the 
GSEs to purchase mortgages in these important sectors, which have been 
identified by HUD as having substantial unmet credit needs in the 
mortgage market. While single family owner-occupied units are also 
affected by missing data, these units are typically not as affordable 
as the GSEs' rental purchases. Consequently, the provision in the 
proposed rule to exclude units from the numerator and denominator for 
single family owner-occupied properties is limited to properties 
located in lower income areas and is subject to a cap.
    a. Multifamily Rental Units.
    (1) Overview. The Department proposed allowing the use of estimated 
rents for multifamily units with missing data, subject to HUD review 
and approval of the data sources and methodologies used in computing 
them. The Department asked for comment on whether it should establish a 
percentage ceiling on the use of estimated rents.
    HUD further proposed that, in cases where multifamily rents are 
missing and where application of estimated rents is not possible, such 
units be excluded from both the denominator and numerator for purposes 
of calculating performance under the Low- and Moderate-Income Housing 
Goal and the Special Affordable Housing Goal. The Department requested 
comment on whether it should establish a percentage ceiling for the 
exclusion of multifamily units with missing data from the denominator 
for goal calculation purposes.
    (2) Summary of Comments. Several commenters endorsed the concept of 
using estimated data to calculate performance toward the Low- and 
Moderate-Income Housing Goal and the Special Affordable Housing Goal 
when multifamily rent data are missing. No commenters indicated 
opposition to allowing the use of estimated rents.
    In its comments, Fannie Mae stated that HUD should, in order to 
provide operational certainty, incorporate an approved methodology into 
the regulations for estimating rents on multifamily properties where 
actual rent data are missing. Freddie Mac commented that the GSEs 
should be given the choice of whether to provide estimated rents or to 
exclude units from the denominator for purposes of calculating goals 
performance in instances of missing multifamily rent data.
    In cases where calculation of estimated rents is not feasible, a 
number of commenters wrote in support of excluding the units in 
question from the denominator as well as the numerator for purposes of 
calculating performance toward the Low- and Moderate-Income Housing 
Goal and the Special Affordable Housing Goal. One commenter opposed 
such exclusion, noting that by including all multifamily units in the 
denominator whether or not the GSEs have the required income and rent 
data places a more serious burden on the GSEs to obtain the data and 
focus on affordable lending in the multifamily area.
    With regard to the issue of percentage ceilings, Freddie Mac 
suggested a two-percent (2%) ceiling on the exclusion of multifamily 
units from the denominator

[[Page 65072]]

because of missing rents. Other commenters suggested alternative 
limits, e.g., a half-of-one percent (0.5%) ceiling or a one-percent 
(1%) ceiling for the combined total of multifamily units with estimated 
rent and units excluded from the denominator. Only Fannie Mae indicated 
opposition to such a ceiling, writing that ``Enforcement of percentage 
ceilings will perpetuate penalties against and create a disincentive 
for Fannie Mae to engage in the very business that HUD has identified 
for expanded penetration--single family, owner-occupied, 2-4 unit 
housing and small multifamily rental properties.''
    (3) HUD's Determination. In order to promote liquidity in the 
multifamily mortgage market, including mortgages on properties which 
may not have current data on the affordability of such units the 
Department believes that it is reasonable for the GSEs to provide 
estimated affordability data for such properties, which would be 
utilized for purposes of calculating performance toward the Low- and 
Moderate-Income Goal and the Special Affordable Housing Goal as long as 
the data sources and methodology are reliable. The data sources and 
methodology used by a GSE to estimate affordability data are, 
therefore, subject to HUD review and approval. Estimated affordability 
data may be used up to a maximum of five (5) percent of units backing 
GSE multifamily purchases in any given year.
    In its evaluation of whether to accept a proposed methodology for 
estimating affordability data, the Department will seek to determine: 
(a) The reliability of the data source(s) used including the size of 
the sample used; (b) the accuracy of the calculations; and (c) the 
reasonableness of the proposed methodology with regard to providing an 
unbiased measure of GSE performance toward the Low- and Moderate-Income 
Housing Goal and the Special Affordable Housing Goal, including the 
degree to which the methodology accurately predicts affordability 
information and goals performance on units backing GSE acquisitions in 
cases where current affordability data are known. The GSEs will be 
required to certify that any proposed estimated affordability 
methodology meets these standards. Methodologies that tend to 
understate actual rents, or which otherwise tend to overstate the 
affordability of GSE multifamily mortgage purchases or exaggerate GSE 
goals performance relative to actual performance, will not be 
considered acceptable by HUD.
    Once a methodology is approved, the Department will closely monitor 
its implementation and its effects on calculated goals performance. 
Withdrawal of Departmental approval of an estimated affordability 
methodology could be warranted if evidence becomes available indicating 
that use of estimated affordability methodologies is unreliable or has 
undermined GSE incentives to collect and maintain rent data.
    HUD does not believe it is necessary to codify in the regulations 
the specific methodology for estimating affordability data. The concept 
of estimating affordability data is new relative to the affordable 
housing goals. Both HUD and the GSEs need to evaluate the implications 
of the methodology proposed, monitor performance over time using such 
data, evaluate new data sources that may become available and become 
more predictive. HUD needs the flexibility to make changes and 
refinements to the approved methodology based on experience, without 
unnecessary limitations. In approving any methodology and data sources, 
HUD will, of course, be mindful of the GSEs' needs for operational 
certainty in making determinations.
    With regard to circumstances where estimation of affordability on 
multifamily properties with missing data is not feasible, HUD believes 
it is reasonable to exclude such units from the denominator as well as 
the numerator for purposes of calculating performance toward the Low- 
and Moderate-Income Goal and the Special Affordable Housing Goal. The 
Department does not believe that a percentage ceiling on the exclusion 
of multifamily units with missing data from the denominator is needed 
in order to preserve incentives for data collection, and could actually 
be harmful from the standpoint of the reliability of the housing goals 
as a measure of actual GSE performance. Because the percent of 
multifamily units qualifying for the Low- and-Moderate Income Goal is 
so much higher than the average across all property types (over 90 
percent for multifamily, compared with approximately 45 percent 
overall), an incentive will remain in place for the GSEs to collect 
rent data or obtain reliable estimated rents wherever it is feasible to 
do so. For the same reason, the Department believes that applying a 
ceiling on exclusion of units from the denominator as well as the 
numerator for goal calculation purposes would undermine the reliability 
of the Low- and Moderate Income Goal as a measure of actual GSE 
performance, since multifamily units above the ceiling would be counted 
as not being affordable when, in fact, there is approximately a 90 
percent probability that such units do meet the requirements of the 
Low- and Moderate-Income Housing Goal. Similar arguments could be made 
with regard to the Special Affordable Housing Goal. Therefore, a 
percentage ceiling on removal of units from the denominator as well as 
the numerator is not necessary or warranted at this time.
    b. Single Family Rental Units.
    (1) Overview. The Department further proposed to exclude rental 
units in 1-4 unit properties with missing rent data from the 
denominator as well as the numerator in calculating performance under 
the Low- and Moderate-Income Housing Goal and the Special Affordable 
Housing Goal. HUD asked for comment on whether it should establish a 
percentage ceiling for such exclusions.
    This final rule retains the provision excluding rental units in 1-4 
unit properties with missing rent data from the numerator and the 
denominator in calculating performance under the two goals. These 
properties disproportionately serve affordable housing markets and the 
GSEs should be active in this segment of the market. As the Department 
is awarding bonus points for the units in owner-occupied single family 
rental properties, the GSEs have a large incentive to obtain the 
required affordability data. When the data is not available, however, 
the Department does not wish to create a disincentive to purchase 
mortgages on these properties simply because affordability data is not 
available.
    (2) Summary of Comments. A number of commenters wrote in favor of 
excluding rental units in 1-4 unit properties from the denominator as 
well as the numerator for purposes of calculating performance toward 
the Low- and Moderate-Income Housing Goal and the Special Affordable 
Housing Goal when rent data are missing. No commenters indicated 
opposition to such exclusion.
    Writing in support of the ceiling concept, Freddie Mac suggested a 
two-percent (2%) ceiling on the exclusion of single family rental units 
from the denominator. Fannie Mae objected to such a ceiling, commenting 
that a ceiling was unnecessary given that it is in Fannie Mae's 
interest to obtain rent data on single family rental properties when it 
is cost effective to do so. Other commenters endorsed a percentage 
ceiling on the number of single family rental units that would be 
excluded from the denominator as well as the numerator for purposes of 
calculating performance toward the Low- and Moderate-Income Housing 
Goal and the

[[Page 65073]]

Special Affordable Housing Goal when rent data are missing.
    Fannie Mae and Freddie Mac both suggested that the use of estimated 
rents should be permitted for single family rental properties with 
missing data.
    (3) HUD's Determination. With regard to single family rental units 
with missing rent data, HUD believes it is reasonable to remove such 
units from the denominator as well as the numerator for purposes of 
calculating performance toward the Low- and Moderate-Income Goal and 
the Special Affordable Housing Goal. Because of the high degree of 
affordability of single family rental units, the Department does not 
believe that a percentage ceiling on exclusion of single family rental 
units with missing data from the denominator is needed in order to 
preserve incentives for data collection, and could actually be harmful 
from the standpoint of the reliability of the housing goals as a 
measure of actual GSE performance. HUD will monitor the GSEs' use of 
missing data provisions to ensure that they are being used in a 
reasonable way.
    The Department has determined not to permit the use of estimated 
affordability data where it is missing for single family rental units. 
There are several reasons why HUD believes this a reasonable and 
prudent decision.
    A decision to exclude units with missing affordability data from 
the numerator as well as the denominator for certain goals calculation 
purposes on single family rental properties removes a potential 
disincentive to an expanded GSE presence in the markets for mortgages 
on single family rental properties at the same time. The Department 
believes this segment of the market has unmet credit needs. To 
encourage the GSEs to move into this market, it is awarding bonus 
points for the rental and owner-occupied units in owner-occupied single 
family rental properties. The use of bonus points will serve as an 
additional incentive to the GSEs to obtain the necessary affordability 
data in order to obtain bonus credit.
    Furthermore, HUD calculates affordability of single family rental 
units for purposes of the housing goals using origination-year rents, 
in contrast to multifamily, where acquisition year rents are used. 
While acquisition year rents on multifamily properties may sometimes be 
difficult to provide on seasoned and negotiated transactions where 
lenders have not continued to collect annual rent data following loan 
origination, this situation does not apply to single family rental 
properties, since information on rent at the time of loan origination 
is ordinarily required by lenders and secondary market institutions as 
part of the loan underwriting process.
    The Department's decision to allow the estimation of affordability 
data with the limitations provided in this rule for multifamily rental 
units affords an opportunity to pilot the estimated rent methodology in 
an appropriately controlled environment.
    c. Single Family Owner-Occupied Units.
    (1) Overview. The Department also proposed to exclude single family 
owner-occupied units from the denominator as well as the numerator for 
purposes of calculating performance toward the Low- and Moderate-Income 
Housing Goal and the Special Affordable Housing Goal when data on 
borrower income are missing, provided the unit is located in a census 
tract with median income less than or equal to area median. HUD 
proposed to restrict this exclusion up to a ceiling of one percent (1%) 
of the total number of single family, owner-occupied dwelling units 
eligible to be counted toward the respective housing goal.
    This final rule retains the provision to exclude single family 
owner-occupied mortgages from both the numerator and the denominator 
when borrower income is missing for properties located in lower income 
areas subject to a one percent maximum.
    (2) Summary of Comments. A number of commenters wrote in favor of 
excluding at least some single family owner-occupied units from the 
denominator as well as the numerator for purposes of calculating 
performance toward the Low- and Moderate-Income Housing Goal and the 
Special Affordable Housing Goal when income data are missing. One 
commenter indicated opposition to such exclusion.
    Both Fannie Mae and Freddie Mac expressed opposition to restricting 
the exclusion of single family owner-occupied units with missing income 
data from the denominator only in lower-income areas. They recommended 
a two percent ceiling without these geographic restrictions.
    In its comments, Fannie Mae stated that ``the place-based 
restriction that HUD proposes implies an unreasonable assumption that 
all the units that are missing data outside of the low-income census 
tracts are not affordable. The effect of the cap is to deny credit for 
units that are missing data and even when those units have some 
statistical likelihood of serving loans to low- and moderate-income 
borrowers. HUD's proposed methodology treats loans to low- and 
moderate-income borrowers differently simply because the borrower chose 
to purchase a property in a higher-income area.'' While opposed, in 
principle, to the concept of a ceiling on the exclusion of missing 
single family owner-occupied units from the denominator for goals 
calculation purposes, Fannie Mae stated that any ceiling established by 
the Department should be set at ``not less than two percent.''
    Similarly, Freddie Mac wrote that ``A substantial fraction of 
mortgages in above-average income tracts are made to low- and moderate-
income families' citing 1998 HMDA data in support of this contention. 
Consequently, ``geographic restrictions would erroneously exclude many 
low- and moderate-income loans from performance measures.''
    Several commenters endorsed HUD's proposed one percent ceiling on 
exclusion of single family owner-occupied units with missing data from 
the denominator although some commenters thought the ceiling should be 
lower than one percent. A number of other commenters expressed 
opposition to this ceiling. No comments were received on the geographic 
restrictions aside from those from the GSEs.
    (3) HUD's Determination.
    With regard to single-family owner-occupied units with missing 
income data, HUD believes it is reasonable to remove such units from 
the denominator as well as the numerator up to one percent of the 
eligible total for purposes of calculating performance toward the Low- 
and Moderate-Income Goal and the Special Affordable Housing Goal 
provided such units are located in tracts where median income is less 
than or equal to area median income.
    The percentage ceiling and the restriction to tracts where median 
income is less than or equal to area median income are both necessary 
in order to ensure that the exclusion does not result in undue 
exaggeration of GSE performance as calculated in achieving the housing 
goals as compared to actual performance. Because single family owner-
occupied units are significantly less affordable than all other 
property types in the conventional, conforming mortgage market 
according to HUD's estimates (approximately 36 percent single family 
owner-occupied units meet the Low-and Moderate-Income Housing Goal, 
compared with 45 percent overall), excluding single family owner-
occupied units with missing data from the denominator as well as the 
numerator could significantly raise the proportion of GSE acquisitions 
counting toward the Low-and Moderate-Income and Special Affordable 
Housing Goals

[[Page 65074]]

above actual performance. The one-percent ceiling on exclusion of 
single family owner-occupied units from the denominator places a limit 
on the degree to which such exclusions bias or affect the data, and the 
restriction to tracts with income less than area median serves to 
increase the likelihood that the affordability characteristics of the 
excluded units resembles that of the ``typical'' GSE purchase, further 
limiting the bias that would otherwise be introduced.
    In HUD's view, the proposed geographic restriction on the exclusion 
of missing single family owner-occupied units from the denominator as 
well as the numerator for certain goals calculation purposes is, 
therefore, reasonable and necessary to correct for the bias that would 
otherwise be introduced even with a one-percent ceiling. Fannie Mae's 
contention that ``the place-based restriction that HUD proposes implies 
an unreasonable assumption that all the units that are missing data 
outside of the low-income census tracts are not affordable'' is not 
pertinent to HUD's determination. The Department made no such 
assumption. HUD is well aware that many low-income borrowers choose to 
live in tracts with median income above the area median, as pointed out 
by Fannie Mae. Conversely, however, a significant number of above 
median-income borrowers choose to live in tracts with median income 
below the area median. HMDA data does, however, show a strong 
correlation between borrower income as a percent of area median and 
tract income as a percent of area median, suggesting that tract income 
serves as a useful predictor of borrower of income. For example, in 
1998, 55 percent of conforming, conventional owner-occupied loans in 
tracts where median income was less than area median were to low-and 
moderate-income borrowers. In contrast, only 33 percent of loans in 
high-income tracts were to low-and moderate-income borrowers. (Overall, 
42 percent of single family owner-occupied loans in HMDA data were to 
low-and moderate-income borrowers.) HUD's analysis of GSE loan-level 
data reveal a similar correlation between borrower income as a percent 
of area median and tract income as a percent of area median, although 
the low-mod percentage of GSE acquisitions is lower than in HMDA data.
    Accordingly, HMDA findings support the conclusions that HUD's 
proposed geographic restrictions on the exclusion of missing single 
family owner-occupied data will (i) result in goals calculations that 
more accurately track actual performance than would otherwise be the 
case and (ii) respond appropriately to any perceived weakening of 
incentives for the GSEs to collect affordability data to the extent 
feasible.
    d. Other Matters. Freddie Mac argued that units with missing census 
tract data should be excluded from the denominator as well as the 
numerator for purposes of calculating performance toward the 
Underserved Areas Goal up to a maximum of 0.5 percent of the total.
    The Department has not determined, however, that it is reasonable 
to remove units with missing geographic information from the 
denominator as well as the numerator for purposes of calculating 
performance toward the Underserved Areas Goal. In those limited 
instances where census tract (for metropolitan areas) or county (for 
nonmetropolitan areas) cannot be determined using automated methods, 
manual methods can be used.
13. Seasoned Mortgage Loan Purchases ``Recycling'' Requirement
    a. Overview. Under section 1333(b)(1)(B) of FHEFSSA, 42 
special rules apply for counting purchases of portfolios of seasoned 
mortgages under the Special Affordable Housing Goal. Specifically, the 
statute requires that purchases of seasoned mortgage portfolios receive 
full credit toward the achievement of the Special Affordable Housing 
Goal if ``(i) the seller is engaged in a specific program to use the 
proceeds of such sales to originate additional loans that meet such 
goal; and (ii) such purchases or refinancings support additional 
lending for housing that otherwise qualifies under such goal to be 
considered for purposes of such goal.'' 43 HUD refers to 
this provision as the ``recycling requirement.''
    The proposed rule suggested changes to Sec. 81.14(e)(4) of the 
current regulations. The proposed language was intended to provide 
guidance to the GSEs with regard to the recycling requirements 
described above and to provide new, simpler rules when it is evident 
based on the characteristics of a mortgage seller that the recycling 
requirements would likely be met.
    The rule proposed that certain categories of lenders could be 
presumed to conduct a lending program meeting the recycling 
requirements of the statute and regulations. These categories include 
federally regulated financial institutions with satisfactory ratings on 
recent Community Reinvestment Act examinations and specific categories 
of lenders with affordable housing missions.
    b. Guidance Provided on Recycling Requirements. Commenters were 
generally supportive of the overall guidance proposed by the Department 
with regard to determining when recycling requirements were met in 
order to count purchases of seasoned mortgage loans toward the Special 
Affordable Housing Goal, assuming they otherwise qualified for the 
goal. These provisions are included in the final rule with three 
specific changes based on the comments received. The changes made in 
the proposed language relate to the satisfactory CRA requirement for 
Federally insured financial institutions, identification of other 
institutions and/or organizations presumed to meet the recycling 
requirements, and the treatment of third party originations under the 
recycling provision. Changes made in the final rule on these three 
aspects are discussed in more detail below.
    c. CRA Requirement.
    (1) Summary of Comments. Overall commenters supported the proposed 
changes identifying specific criteria and standards for the recycling 
requirements. However, many commenters disagreed with HUD's requirement 
that a financial institution subject to CRA examinations must have 
received ``at least a satisfactory performance evaluation rating for at 
least the two most recent examinations under the Community Reinvestment 
Act'' to be presumed to meet the recycling requirements.
    Fannie Mae, Freddie Mac and several other commenters suggested that 
a satisfactory performance evaluation rating on the most recent 
examination is sufficient, as opposed to the two most recent 
examinations, since the period between examinations can be as long as 
60 months. A number of commenters noted that this could be a 
particularly difficult requirement for small institutions, who are 
examined much less frequently.
    Other commenters suggested that two consecutive outstandings is a 
more suitable standard, as 78 percent of banks received satisfactory 
ratings in their 1999 CRA exams and about 75 percent received these 
ratings in previous years.
    Still other commenters were supportive of HUD's proposal of at 
least a satisfactory performance evaluation rating for at least the two 
most recent examinations under the Community Reinvestment Act because 
it would reduce the compliance burden of both the GSEs and depository 
institutions, allowing them to spend more time on the business of 
financing housing loans.
    (2) HUD's Determination. HUD has reviewed these comments and noted 
that the proposed rule, in establishing the CRA examinations and 
ratings of financial depository institutions as a

[[Page 65075]]

basis for determining that a financial institution met the recycling 
requirements for seasoned loan purchases under the Special Affordable 
Housing Goal, did not make a distinction between small and large 
depository institutions as intended and reflected in the CRA regulation 
44 and the Gramm-Leach-Bliley Act of 1999. 45 The 
1995 CRA regulation distinguishes, for examination purposes, four 
different types of financial institutions based on their size, 
structures, and operations: Small banks, large banks, wholesale banks, 
and limited purpose banks. Accordingly, the 1995 regulation provides 
different performance procedures, standards, ratings, and cycles for 
small banks, large banks, wholesale banks, and limited purpose banks. 
All of the procedures reflect the intent of the regulation to establish 
performance-based CRA examinations that are complete and accurate but, 
to the maximum extent possible, mitigate the compliance burden for 
institutions.
    Under section 712 of the Gramm-Leach-Bliley Act, small banks with 
aggregate assets of not more than $250 million will be subject to 
routine examination:
     Not more than once every 60 months for an institution that 
has achieved a rating of ``outstanding record of meeting community 
credit needs'' at its most recent examination;
     Not more than once every 48 months for an institution that 
has received a rating of ``satisfactory record of meeting community 
credit needs'' at its most recent examination.
     As deemed necessary by the appropriate federal financial 
supervisory agency for an institution that has received a rating of 
``less than satisfactory record of meeting community credit needs'' at 
its most recent examination.
    In view of the comments received and based on its analysis of the 
1995 CRA regulations and the Gramm-Leach-Bliley Act of 1999, this rule 
includes the recycling requirement that a financial institution have 
``at least a satisfactory performance evaluation rating for at least 
the two most recent examinations under the Community Reinvestment Act'' 
for large banks and wholesale banks that are subject to CRA 
examinations. Limited purpose banks are not making home mortgage loans 
and therefore are not relevant for this analysis. This final rule adds 
a provision for small institutions with assets of no more than $250 
million that such institutions must have received ``a satisfactory 
performance evaluation rating for the most recent examination under the 
Community Reinvestment Act to be presumed to meet the requirements in 
paragraphs (e)(4)(i) through (e)(4)(iv) of this section for seasoned 
loans.'' This safe harbor provision will also apply to the affiliates 
of depository institutions, provided that these affiliates are subject 
to the CRA examinations.
    With regard to the suggestion that the standard for CRA 
examinations be two consecutive outstanding ratings, the Department 
believes that such a standard would be counterproductive. The purpose 
of the standard is to identify those financial institutions that are in 
the business of serving affordable housing markets. Using a 
satisfactory CRA examination rating achieves that purpose and is 
retained in the final rule.
    d. Classes or Categories of Organizations Presumed to Meet 
Recycling Requirement.
    (1) Summary of Comments. With regard to other additional classes of 
institutions or organizations that should be recognized as meeting the 
recycling requirements, most commenters, including the GSEs, agreed 
with HUD's proposal that State Housing Finance Agencies or Special 
Affordable Housing Loan Consortia should be presumed to meet the 
recycling requirements. However, both GSEs urged that HUD provide them 
with ``as much flexibility as possible on this provision.'' Fannie Mae 
opposed HUD approval of additional lending institutions or 
organizations and, instead recommended that HUD provide a list of HUD-
approved institutions, and criteria for the GSEs to qualify lenders or 
certain kinds of lending or transactions. Freddie Mac suggested HUD 
``broaden the regulatory presumption of recycling to all sellers of 
mortgages so long as they originate or purchase qualifying special 
affordable housing goal mortgages in the ordinary course of business.''
    A great number of commenters suggested that HUD's list also include 
other ``non-traditional lenders'' who serve targeted communities and 
who could potentially benefit from the liquidity that the change could 
provide. These commenters mentioned the following institutions: 
Community development financial institutions, minority owned lenders, 
women owned lenders, non-profit lenders, and public revolving loan 
funds.
    Other commenters urged HUD to include all credit unions in HUD's 
list because credit unions originate low-cost residential loans that 
make housing affordable to millions of credit union members even though 
they are exempt from CRA requirements. At a minimum, it was suggested 
that ``seasoned loans purchased from community development credit 
unions, which are chartered to serve low-income communities, should 
qualify for goal credit.
    (2) HUD's Determination. HUD has reviewed the above comments and 
agreed to expand the safe harbor provision to include the following 
institutions or classes of institutions that the GSEs may presume meet 
the recycling requirements as long as these institutions have an 
affordable housing mission: State housing finance agencies; affordable 
housing loan consortia; Federally insured credit unions that are either 
(a) community development credit unions, or (b) credit unions that are 
members of the Federal Home Loan Bank System and meet the first-time 
homebuyer standard of the Community Support Program; community 
development financial institutions; public loan funds; and non-profit 
lenders. The final rule retains the requirement that any additional 
classes of institutions or organizations must be approved by the 
Department. The final rule establishes a reasonable set of lender 
characteristics that are presumed to meet the recycling provisions that 
cover a large portion of the affordable lending market. For those 
lenders falling outside of these parameters, the final rule provides 
the GSEs with broad guidance as to what a recycling program should 
include if a lender does not fall into an accepted category. The GSEs 
have broad latitude to evaluate the circumstances of a particular 
lender in counting seasoned loan purchases toward the Special 
Affordable Housing Goal. A GSE does not have to get prior approval to 
do business with a lender that does not fall into the presumptive 
category as long as the GSE verifies and monitors that the lender is 
conducting an affordable lending program consistent with the guidelines 
provided. Prior approval is only required if a seller of loans falls 
outside the boundaries established in the final rule and the GSE wants 
them designated among the category of institutions already identified 
and presumed to meet the requirements. The Department does not 
anticipate that such action will limit the GSEs ability to conduct 
business in any material way, but rather will relieve the burden of 
having to verify and monitor the lending programs of those entities 
presumed to meet the recycling requirements.
    e. Third Party Transactions.
    (1) Overview. In the proposed rule, HUD solicited comments on the 
treatment under the recycling provisions of structured transactions 
where the mortgage loans included in the transaction were originated by 
a

[[Page 65076]]

depository institution or mortgage banker engaged in mortgage lending 
on special affordable housing but acquired, packaged and re-sold by a 
third-party, e.g., an investment banking firm that is not in the 
business of affordable housing lending.
    (2) Summary of Comments. Fannie Mae believes that ``the appropriate 
approach is to extend the streamlined application to third party 
deliveries.'' Fannie Mae argues that when it purchases loans delivered 
by third parties, it ``is supporting the marketplace dynamic that 
provides liquidity,'' and therefore ``the intermediate step in no way 
degrades the liquidity support provided to the institutions or the 
mortgage products.''
    Freddie Mac did not address this issue directly but pointed out 
that Congressional intent underlying the seasoned, recycling 
requirement was ``to ensure that the proceeds will be used in a manner 
that increases the availability of mortgage credit for the benefit of 
low-income families.'' According to Freddie Mac, Congress' interest was 
to ensure that ``mortgage proceeds were funneled back into the mortgage 
market, not that specific types of lending programs should be used to 
recycle these proceeds.'' Thus, Freddie Mac recommends that HUD include 
all mortgage sellers that regularly engage in originating or purchasing 
mortgages that meet the special affordable housing goal criteria. The 
alternative, according to Freddie Mac, would be ``adoption of the BIF/
SAIF regulatory presumption while maintaining the current regulatory 
scheme.''
    (3) HUD's Determination. HUD recognizes that Congress intended that 
the housing goals generally and the recycling provisions specifically 
were to expand the availability of affordable housing with particular 
emphasis on the purchase of loans that are originated in conjunction 
with affordable housing programs, the creation of innovative product 
lines, or the building of institutional capacity and infrastructure 
among others in the industry.46 If the mortgages were, in 
fact, originated by an entity that meets the new recycling 
presumptions, i.e., is regularly in the business of mortgage lending; 
is a BIF-insured or SAIF-insured depository institution; and is subject 
to, and has received at least a satisfactory performance evaluation 
rating under the Community Reinvestment Act, or is among the enumerated 
class or classes of organizations whose primary business is financing 
affordable housing mortgages; but the mortgages were delivered to the 
GSEs by a third party seller after a relatively short holding period, 
the purchase of such mortgages would meet the intent of Congress and 
fulfill the spirit of the recycling requirement. Therefore, in this 
final rule, HUD will allow mortgages delivered by such third party 
sellers to meet the recycling presumptions in Sec. 81.14(e)(4)(vi) and 
(vii) of this final rule if the mortgages were originated by an entity 
that comes within the recycling presumptions; and the seller acted for, 
or in conjunction with, such entity in the transaction with the GSE. A 
seller that holds loans itself for more than six months is not presumed 
to be acting for, or in conjunction with, such an entity. Accordingly, 
the final rule excepts such sellers from the benefit of the 
presumption. Notwithstanding, a seller that otherwise meets the tests 
of the recycling provisions may qualify under the rules on its own 
behalf. Moreover, in any case, if the mortgages were originated by an 
entity that does not meet the recycling presumptions, the GSEs can 
still get goals credit under the Special Affordable Housing Goal if 
they verify and monitor that the originator, acting in conjunction with 
a seller, meets the recycling requirements in Sec. 81.14(e)(4)(i) 
through (iv).
14. Counting Federally Insured Mortgages Including HECMs, Mortgages on 
Housing in Tribal Areas and Mortgages Guaranteed by the Rural Housing 
Service Under the Housing Goals
    a. Overview. Under Sec. 81.16(b)(3) of HUD's regulations prior to 
this final rule, non-conventional mortgages--mortgages that are 
guaranteed, insured or otherwise obligations of the United States--did 
not generally count under the three housing goals. However, mortgage 
loans under the Home Equity Conversion Mortgage (HECM) Program and the 
RHS's Guaranteed Rural Housing Loan Program have received credit under 
the Special Affordable Housing Goal. FHEFSSA specifically provides that 
mortgages that cannot be readily securitized through the Government 
National Mortgage Association (GNMA) or another Federal agency and for 
which a GSE's participation substantially enhances the affordability 
should receive full credit under the Special Affordable Housing Goal. 
On this basis, those two categories of mortgages would count under that 
goal if they finance housing for very low-income families or low-income 
families in low-income areas and meet recycling requirements if 
seasoned.
    In the proposed rule, HUD proposed to amend Sec. 81.16(b)(3) to 
count and give full credit for the following types of mortgage loans 
toward all three housing goals: mortgage loans under the HECM Program, 
mortgages guaranteed by RHS, and mortgage loans made under FHA's 
Section 248 program and HUD's Section 184 program for properties in 
tribal lands. (This section has also been amended as described herein 
at paragraph 14, Expiring Assistance Contracts.) HUD also proposed that 
other types of mortgages involving Federal guarantees, insurance or 
other Federal obligation may be eligible for credit under the goals if 
a GSE submits documentation to HUD that supports eligibility for HUD's 
approval and the Department determines, in writing, that the financing 
needs addressed by such programs are not well served and that the 
mortgage purchases under such program should count under the housing 
goals.
    b. Summary of Comments. Commenters other than the GSEs generally 
supported the proposed change allowing goals credit for the GSEs' 
purchases of HECMs and rural and tribal mortgages. They stressed the 
need for liquidity for such programs and for encouraging the GSEs to 
better serve these markets. They pointed out that these markets are 
still undeveloped and underserved.
    Fannie Mae supported the proposed changes with regard to government 
loans, but Freddie Mac made no comment.
    A few commenters recommended that HUD count all reverse mortgages, 
not just HECMs, toward the three goals. Other commenters suggested that 
loans guaranteed by the RHS' Sections 538 and 515 programs should also 
receive goals credit as they provide high quality affordable 
multifamily housing for lower-income families in rural areas.
    Some commenters suggested that HUD also should include all 
mortgages that are supported in some way by state and local 
governments. Others recommended that predevelopment grants or loans, 
interim development or bridge financing, and permanent financing be 
considered.
    Fannie Mae objected to the proposal for HUD's review and approval 
of goals credit for other types of government loan programs and 
requested that HUD provide a set of criteria for the GSEs to apply and 
make their own determinations. According to Fannie Mae, the GSEs should 
receive goal credit for the purchase of specialized government program 
loans if two conditions are met: (1) Loans are made under any 
federally-insured programs (except for FHA loans insured under section 
203(b) or VA loans insured under the VA single family insurance 
program); and (2) the GSEs add valuable

[[Page 65077]]

liquidity, lower costs, additional credit enhancements, or some other 
value to the financing of these loans.
    c. HUD's Determination. In view of this general support for the 
proposed changes and based upon its review of data on the GSEs' 
mortgage purchases of HECMs, RHS mortgages and loans made to Native 
Americans under FHA's Section 248 program and HUD's Section 184 
program, this final rule amends Sec. 81.16(b)(3) to except mortgages 
under the HECM program, single-family mortgages guaranteed by RHS under 
the Section 502 program, and loans made under FHA's Section 248 program 
and HUD's Section 184 program on properties in tribal lands from the 
general exclusion from goals credit for non-conventional loans. This 
final rule allows goal credit for those specific Federally insured or 
guaranteed mortgage loans.
    As proposed, the final rule provides that HUD will review other 
types of mortgages involving Federal guarantees, insurance or other 
Federal obligation for goals credit. HUD's review of the GSEs' non-
conventional mortgage purchases is needed, among other reasons, to 
ensure compliance with FHEFSSA, which permits mortgages that cannot be 
readily securitized through GNMA or another Federal agency and for 
which a GSE's participation substantially enhances liquidity, to 
receive full credit under the Special Affordable Housing Goal. In view 
of the ample liquidity among the great majority of FHA loans, HUD must 
exercise ongoing responsibility to evaluate whether the GSEs' mortgage 
purchases under non-conventional mortgage programs (other than HECM 
program, specified RHS mortgage programs, and FHA's Section 248 program 
and HUD's Section 184 program on properties in tribal lands) should 
count under the Special Affordable Housing Goal. Beyond its 
responsibility under the Special Affordable Housing Goal, HUD must 
continually determine whether goals credit should be provided for 
particular GSE purchases. HUD has evaluated and considered the specific 
programs enumerated above and, at this time, is able to determine that 
goals credit should be given for the GSEs purchases of mortgages under 
these programs because these purchases will address credit needs that 
are not well served. For other programs, HUD must make the same careful 
and complete evaluation before it can decide in accordance with FHEFSSA 
whether goals credit is warranted.
    This final rule retains a provision that to the extent categories 
of non-conventional mortgage purchases that now count toward the goals, 
they no longer will be excluded from the denominator of the GSEs' 
mortgage purchases as are other non-conventional loans that do not 
receive credit under the goals.
15. Expiring Section 8 Assistance Contracts
    a. Overview. Over 900,000 housing units in approximately 10,000 
multifamily projects have been financed with FHA-insured mortgages and 
supported by project based Section 8 housing assistance 
contracts.47 Many of these contracts will expire over the 
next five years. A significant portion of these contracts currently 
provide for rents for assisted units that substantially exceed the 
rents for comparable unassisted units in the local market. Simply 
reducing rents to a level which may not support the project's debt 
service would risk likely defaults on the FHA-insured mortgage payments 
resulting in substantial claims to FHA's insurance funds.
    In October 1997, Congress enacted the Multifamily Assisted Housing 
Reform and Affordability Act of 1997 (MAHRA; 42 U.S.C. 1737f) 
specifically to address the problem of expiring contract for project-
based Section 8 rent subsidies for certain multifamily rental projects, 
most of which are insured by FHA. MAHRA authorized a new Mark-to-Market 
Program designed to preserve low-income rental housing affordability 
while reducing the long-term costs of Federal rental assistance for 
these projects.48 MAHRA establishes processes and standards 
for debt restructuring under the program where it is determined that 
such restructuring is appropriate and necessary.
    MAHRA also amended section 1335(a) of FHEFSSA (12. U.S.C. 
4565(a)(5)) to require Fannie Mae and Freddie Mac to ``assist in 
maintaining the affordability of assisted units in eligible multifamily 
housing projects with expiring contracts.'' MAHRA amendments further 
stipulate that such actions shall constitute part of the contribution 
of each GSE toward meeting its housing goals as determined by the 
Secretary. In the proposed rule, HUD proposed to provide partial to 
full credit under the housing goals as determined by HUD for actions 
that maintain the affordability of assisted units in eligible 
multifamily housing projects with expiring contracts include the 
restructuring or refinancing of mortgages, and credit enhancements or 
risk-sharing arrangements to modified or refinanced mortgages. HUD 
solicited comments on how and to what extent the GSEs should receive 
credit for such actions.
    b. Summary of Comments. Commenters who addressed this issue were 
generally supportive of HUD's proposal to award credit for these 
activities. Although Freddie Mac did not express an opinion in its 
comments, Fannie Mae expressed some support for HUD's approach. 
However, Fannie Mae requested that HUD consider some revisions to its 
proposal. Specifically, Fannie Mae suggested that HUD broaden its 
definition of actions which would receive credit to include the 
purchase of FHA-insured mortgages, mortgage revenue bonds and equity 
investments, including Low Income Housing Tax Credits. Fannie Mae 
suggested that HUD strike the language ``* * * as determined by HUD'' 
from the final rule to avoid a regulatory process that requires prior 
HUD approval for determining goals credit. Fannie Mae also suggested 
that actions qualifying for credit under this section should always 
receive full, rather than partial, credit.
    c. HUD's Determination. HUD has determined that it is both 
appropriate and consistent with the statutory mandates of FHEFSSA and 
MAHRA that actions taken by the GSEs to assist in maintaining the 
affordability of assisted multifamily units with expiring contracts 
receive goals credit as part of the GSEs' contributions in meeting 
their housing goals as determined by the Secretary. HUD's current 
counting rules permit the GSEs to receive full credit for purchases of 
mortgages or interests in mortgages as set forth in 24 CFR 81.16. Those 
rules address goals eligibility standards for credit enhancements, the 
purchase of refinanced mortgages, mortgage revenue bonds and risk-
sharing. Because HUD intends that goals credit for actions in 
conjunction with expiring assistance contracts should conform to 
actions that are already awarded credit in other transactions, HUD has 
determined that it is not necessary to restate these rules with respect 
to eligibility of actions for goals credit that assist the Mark-to-
Market program. Accordingly, this final rule revises the language to 
eliminate redundancies by referencing current regulations.
    HUD agrees with Fannie Mae that the purchase of FHA-insured 
mortgages resulting from restructured financings of projects with 
expiring assistance contracts is an appropriate activity to include in 
actions eligible for goals credit. Accordingly, HUD has amended 
Sec. 81.14(e)(3) to specify that purchases of mortgages on projects 
with expiring assistance contracts that meet the

[[Page 65078]]

requirements of 12 U.S.C. 4563(b)(1)(A)(i) and (ii) will receive full 
credit toward achievement of the special affordable housing goal.
    This final rule also clarifies the counting treatment for actions a 
GSE takes to modify or restructure the terms of mortgages with expiring 
assistance contracts which it may hold in portfolio, provided such 
restructuring results in lower debt service costs to the project's 
owner. HUD has added Sec. 81.16(c)(9)(ii) to provide full credit under 
any housing goal for these activities.
    HUD has reviewed comments from Fannie Mae, Freddie Mac, and others 
regarding awarding goals credit for equity investments, particularly 
Low Income Housing Tax Credits (LIHTCs). These comments, while not 
necessarily offered in response to this section of the proposed rule, 
indicate a continuing interest in counting these transactions under the 
goals. The Department agrees that the GSEs' participation in LIHTCs 
plays a vital role in the development of affordable housing. By 
excluding these investments from goals credit HUD does not intend to 
convey any lack of appreciation for their importance. However, FHEFSSA 
imposes certain standards on what can and cannot be counted towards the 
housing goals.49
    Specifically, only mortgage purchases as defined in FHEFSSA and the 
implementing regulation meet the standard for eligibility. As described 
in the preamble to HUD's 1995 regulation, the purchase of LIHTCs is not 
a mortgage purchase or the equivalent of a mortgage purchase and, 
therefore, is not eligible for goals credit under HUD's general 
counting requirements as set forth in the implementing regulation.
    While MAHRA does provide that actions to maintain the affordability 
of assisted units under MAHRA will count under the goals, MAHRA does 
not specifically impose standards for counting actions with respect to 
expiring assistance contracts under the goals but leaves this matter to 
HUD's determination. In determining whether actions count under the 
goals, HUD will generally be guided by definitions and counting 
conventions set forth in the implementing regulation. In instances 
where a GSE engages in actions not specified in the implementing 
regulation but which it believes warrant goals credit, or where a GSE 
provides more than one form of assistance for a single project, the GSE 
must submit the transaction to HUD for a determination on the 
appropriate level of credit to be awarded if the goals credit is 
sought. In making a determination, HUD will award counting treatment 
for those actions that are required under MAHRA and that may count 
under FHEFSSA.
    A few commenters expressed concern about the counting treatment for 
mortgage purchases on projects with expiring contracts that ``opt out'' 
of the assisted program. One commenter suggested that HUD impose 
additional affordability requirements as a condition of awarding goals 
credit for such transactions. However, HUD finds that the issue of 
affordability relative to goals credit is already well established. 
HUD's current regulations address the income requirements for 
determining how mortgage purchases are counted under any of the housing 
goals. There are other statutory provisions that also address long-term 
affordability. Projects that rely upon or intend to rely upon equity 
investments from the LIHTC program must meet tax code requirements for 
affordability for a 15-year period.50 Mortgages secured by 
projects subject to restructuring plans must provide for a Use 
Agreement that includes affordability restrictions and remains in 
effect for at least 30 years.51 HUD believes that the 
current counting rules and statutory definitions under FHEFSSA and 
MAHRA are sufficient to ensure that goals credit is awarded 
appropriately for mortgage purchases that meet prescribed housing 
affordability standards.
16. Provision for HUD to Review New Activities To Determine Appropriate 
Counting Under the Housing Goals
    a. Overview. In order to address confusion about whether a given 
transaction will receive credit under the housing goals, HUD proposed 
adding a provision at Sec. 81.16(d) to further clarify its position 
regarding HUD's authority review new activities, or classes of 
transactions, to determine appropriate counting treatment under the 
housing goals.
    While the GSEs participate in transactions and activities that 
support community and housing development in general, FHEFSSA is clear 
that only ``mortgage purchases'' count toward performance on the 
housing goals. Section 81.16(a) of the regulations stipulates that the 
Secretary shall consider whether a transaction or activity of the GSE 
is substantially equivalent to a mortgage purchase and either creates a 
new market or adds liquidity to an existing market. As provided in 
Sec. 81.16(b), HUD has determined that certain transactions do not meet 
those criteria and, therefore, will not count toward a GSE's housing 
goals performance. Examples include equity investments in housing 
development projects; commitments, options or rights of first refusal 
to acquire mortgages; mortgage purchases financing secondary 
residences; purchases of non-conventional mortgages and government 
housing bonds except under certain circumstances. As provided in 
Sec. 81.16(c), HUD has determined that certain other transactions, 
including credit enhancements in certain situations, REMIC purchases 
and guarantees in certain circumstances, and others, do count as 
mortgage purchases.
    HUD believes that, in order to meet higher goal levels, the GSEs 
will need to continue to develop new products and approaches while also 
remaining mindful of FHEFSSA's requirements. HUD invited comment on 
this proposal.
    b. Summary of Comments. Commenters who addressed this issue 
generally offered support for the proposal. Some commenters, however, 
confused HUD's proposal to review classes of transactions for goals 
counting treatment with the Department's New Programs Approval 
authority as set forth in Sec. 81.51 which relates to HUD's review of a 
new GSE activity to determine whether it is a new program and whether 
it is authorized under the GSE's charter and in the public interest. 
The provision in Sec. 81.16(d) of the proposed rule concerns instead 
whether a class of transactions counts as mortgage purchases that will 
receive credit under the housing goals. In HUD's proposed rule, no 
regulatory changes to the New Programs Approval authority were 
proposed.
    Of the comments received, Fannie Mae addressed the issue of 
counting classes of transactions under the goals in some detail. 
Generally, Fannie Mae expressed an overall objection to any regulatory 
provisions that would require prior HUD approval for goals counting 
purposes, believing instead that HUD should codify clear but flexible 
rules that remove all uncertainty regarding goals counting treatment. 
Fannie Mae further stated that prior HUD review could ``put in place a 
disincentive to the development of new and innovative products.'' 
Fannie Mae did not suggest any specific examples of classes of 
transactions or characteristics that HUD should exclude from a prior 
review process nor did it specify how regulatory guidance could be 
constructed to address future events. However, Fannie Mae did suggest 
that HUD impose a 30-day time frame for review after which the 
transaction(s) would be approved for goals credit unless HUD had 
notified the GSE otherwise during the review period.
    Another commenter expressed concern that HUD intends to count

[[Page 65079]]

transactions that are not formally mortgages if HUD believes they serve 
a new market or add liquidity to an existing market, thereby 
potentially allowing the GSEs to expand their activities into areas now 
served by others.
    c. HUD's Determination. In assessing these concerns, HUD believes 
that Fannie Mae's suggestions for additional codified regulatory 
guidance in lieu of any HUD review are impractical and unnecessary. The 
regulation already includes numerous provisions that address eligible 
transactions and their counting treatment. In fact, virtually all 
transactions in current use which could be substantially equivalent to 
a mortgage purchase have been addressed elsewhere in the counting 
rules. Nevertheless, given the pace of innovation in the mortgage and 
investment markets and the likelihood that the GSEs will devise new 
lending and marketing approaches in the future, providing a prior-
review requirement to address goals counting treatment for these future 
transactions is both an efficient and practical solution while a more 
prescriptive approach may not be sufficiently foresighted or 
encompassing thereby disadvantaging both the public's and the GSEs' 
interests.
    HUD regards concerns that by adding Sec. 81.16(d) to the 
regulation, HUD is opening the door to counting non-mortgage 
transactions towards the goals as unwarranted. The regulatory language 
is explicit in stating that, in order to count towards goals 
performance, transactions must be ``mortgage purchases'' in accordance 
with FHEFSSA. The regulatory language does not use ``liquidity'' as a 
criteria for review and approval to count transactions for goals 
credit, and ``liquidity'' is not a defining element of ``mortgage 
purchase'' under this regulation. Further, the regulation explicitly 
states which classes of transactions are currently ineligible, and it 
provides guidance on criteria necessary for qualifying other classes of 
transactions. Thus the plain meaning of the regulations including the 
counting rule conventions set forth in the regulation would preclude a 
broader interpretation of Sec. 81.16(d).
    HUD has further determined that establishment of a time limit for 
HUD review of GSE requests to count transactions is unnecessary. While 
HUD is aware of the need for responsive action to a GSE's request for 
guidance and will respond to such requests reasonably, rigid time 
frames may not provide sufficient review of complex transactions to 
best serve the public interest. Accordingly, HUD has implemented 
Sec. 81.16(d) as originally proposed.
17. Counting Rules--Clarifying Technical Provisions
    a. Especially Low Income. Section 81.14(d)(1)(i) of the regulations 
provides that dwelling units in a multifamily property will count 
toward the Special Affordable Housing Goal if 20 percent of the units 
are affordable to families whose incomes do not exceed 50 percent of 
the area median income. HUD's regulations at Secs. 81.17 through 81.19 
stipulate that the income requirements are to be adjusted based on 
family size and provide adjustment tables for qualifying family income 
where incomes do not exceed from 60 percent to 100 percent of area 
median income. However, there has been no similar adjustment table 
provided for families whose incomes do not exceed 50 percent of area 
median income. HUD proposed to amend those sections to provide 
additional adjustment tables for such families. To be consistent, HUD 
also proposed to designate such families as ``especially low-income 
families'' for purposes of the Department's GSE regulations and to 
reflect this change in Sec. 81.14. HUD received no comments on these 
proposals. Therefore, this final rule implements the changes as 
proposed in Sec. 81.14 and Secs. 81.17 through 81.19.
    b. Defining the ``Denominator''. HUD proposed amending the 
calculation of ``Denominator'' to clarify that the denominator does not 
include GSE transactions or activities that are not mortgages or 
transactions that are specifically excluded. HUD received no comments 
on this proposed change, and this final rule implements the change as 
proposed in 81.14(a)(2).
    c. Balloon Note Conversions. HUD proposed to amend the definition 
of ``Refinancing'' at Sec. 81.2 to exclude a conversion of a balloon 
mortgage note on a single family property to a fully amortizing 
mortgage note provided the GSE already owns or has an interest in the 
balloon note at the time of the conversion. HUD also proposed amending 
the counting rules at Sec. 81.16(b)(9) to exclude these transactions 
from the denominator. Fannie Mae suggested deleting other proposed 
language which sought to clarify that single family loans with 
conversion features which had already been exercised prior to purchase 
by the GSE would count as new purchases. Fannie Mae believed this 
additional language created confusion and was unnecessary stating that 
the revised definition of ``Refinancing'' at Sec. 81.2 already provided 
sufficient clarification. HUD agrees with this comment. Accordingly, 
this final rule implements the proposed changes to Sec. 81.2 and to 
Sec. 81.16(b)(9), with slight revisions to Sec. 81.16(b)(9) to avoid 
any potential confusion.
    d. Title I. HUD proposed awarding the GSEs half credit for 
purchases of mortgage loans insured under HUD's Title I property 
improvement and manufactured homes program. Fannie Mae and one other 
commenter asked that the Department award full credit for Title I 
mortgages saying that these mortgages support affordable housing needs. 
Fannie Mae noted that purchases of these loans were difficult 
transactions to undertake and for this reason should receive more than 
half credit. One other commenter recommended that no goals credit be 
given for Title I loans, asserting that such loans do not directly 
support affordable housing needs.
    Given the limited number of comments and their conflicting nature, 
the Department decided to retain the provision in the final rule that 
purchases of Title I loans will receive half credit under the housing 
goals. As explained in more detail in the appendices to this final 
rule, HUD has determined that such loans finance an important source of 
affordable housing and an enhanced GSEs role could improve the 
affordability of such loans for lower-income families.
18. Credit Enhancements
    a. Overview. The GSEs utilize a large variety of credit 
enhancements, for both single family and multifamily mortgage 
purchases, to reduce the credit risk to which they might otherwise be 
exposed. For example, the GSEs generally require the use of mortgage 
insurance on single family loans with loan-to-value ratios exceeding 80 
percent. While more common in the multifamily mortgage market, seller-
provided credit enhancements may also be required for GSE purchases of 
single family mortgage loans. Other types of credit enhancements 
include arrangements such as credit enhancements in structured 
transactions where a GSE may acquire a pool of loans, mortgage-backed 
securities (MBS), or real estate mortgage investment conduits (REMICs), 
and then create separate senior and subordinated securities, structured 
so that the subordinated securities absorb credit losses; spread 
accounts, in which a GSE may create a special class of unguaranteed 
securities where pass-through payments will cease in the event of 
default of the underlying mortgage collateral; acquisition of senior 
tranches of REMIC securities by the GSEs which are enhanced by the

[[Page 65080]]

presence of subordinate tranches and where the collateral is already 
credit enhanced prior to purchase; and agency pool insurance coverage 
provided by a mortgage seller.
    Since enactment of FHEFSSA in 1992, HUD's regulations have awarded 
full goals credit for the purchase of most mortgages or interests in 
mortgages that otherwise qualify under the definition for each goal 
regardless of the level of credit risk a GSE might bear in the 
transaction. However, the increasing complexity of, and prevalence in, 
the use of credit enhancements have raised questions about whether the 
GSEs should receive full credit towards the goals for transactions 
where their credit risk exposure is minimal. In the proposed rule, HUD 
sought comments on various questions regarding the appropriate goals 
treatment for transactions with credit enhancements. For example, 
assuming credit risk can be measured, HUD asked commenters to consider 
whether HUD should establish a sliding scale from 0 to 100 percent for 
awarding goals credit depending on the GSE's risk exposure in a 
transaction. HUD also asked for comments on other issues including 
whether a minimum risk threshold should be established in order for a 
transaction to receive any goals credit as well as comments on whether 
HUD should measure counterparty risk on seller-provided credit 
enhancements.
    b. Summary of Comments. The overwhelming majority of commenters, 
including Fannie Mae and Freddie Mac, responded with strong opposition 
to the concept of basing goals credit on the level of credit risk borne 
by a GSE in the transaction. Freddie Mac expressed concern that, in 
addition to being inconsistent with the Freddie Mac Act and FHEFSSA, 
discounting goals credit for protections against default cost would 
lead to a host of unintended consequences and practical problems, 
including measurement problems. For example, with regard to multifamily 
mortgages especially, Freddie Mac stated that ``when cross-default or 
cross-collateralization techniques are used to price credit 
enhancements, there is no ready and straightforward method of 
allocating default cost protection to the risks presented by the 
individual mortgages, let alone to the housing units that are financed 
by each of those mortgages.''
    Fannie Mae also strongly opposed any goals scoring approach based 
on the level of credit enhancement. Fannie Mae stated that credit 
enhancements are essential to its safe and sound operation and, in 
fact, are explicitly recognized under OFHEO's risk-based capital 
standard as an important risk management tool. Fannie Mae further 
stated that reducing goals credit based on the level of credit 
enhancement ``is contrary to our charter, misconstrues the purpose of 
Fannie Mae, distorts the efficient functioning of the capital markets, 
increases the cost of homeownership, restricts the availability of 
capital, and weakens the financial soundness of Fannie Mae.''
    Commenters representing state and local housing finance agencies, 
for-profit and non-profit advocacy and consumer groups, trade 
associations, and the mortgage lending and investment industry were 
nearly unanimous in voicing objections to any regulatory approach that 
considered levels of credit enhancements in assigning goals credit. The 
recurring objection held that such an approach would undermine the 
purpose of the housing goals regulation by disrupting the risk-sharing 
partnerships that are critical to making affordable housing lending a 
reality, thereby resulting in a negative consequence to homeownership. 
For example, some commenters expressed concern that such an approach 
could interfere with the GSEs' incentive to develop new affordable 
mortgage products using risk-sharing arrangements while others felt 
that reducing goals credit based on the level of risk would have the 
effect of reducing the amount and liquidity of funds available for 
affordable housing lending rather than force the GSEs to take on more 
risk than they felt they could effectively manage. These commenters 
remarked that since risk sharing arrangements allow more industry 
partners to bring more capital to the mortgage market, they were 
concerned that the affordable housing market would be adversely 
impacted if HUD adopted a regulatory counting scheme that penalized the 
GSEs for sharing risk.
    Two commenters, however, suggested there may be instances in which 
goals credit should be limited and suggested further review and study 
of the issue. One commenter stated that the financial benefits of GSE 
status can and should function as an offset for the assumption of some 
amount of credit risk but also cautioned that HUD must carefully 
consider the effects of any regulatory change in this area, especially 
how OFHEO and the financial markets would view encouraging the GSEs to 
assume certain credit risks and what effect this approach could have on 
mortgage rates. Another commenter suggested that HUD establish an 
industry working group to examine these issues in greater detail. This 
commenter also supported limiting goals credit on the GSEs' purchase of 
seasoned mortgages when the selling institution provides a credit 
enhancement beyond customary representations and warranties, and also 
supported some limitation on goals credit for loans securitized in 
commercial mortgage-backed securities (CMBS) and REMIC structures to 
the risk level of the tranches purchased by the GSEs.
    One commenter suggested that, in assigning goals credit based on 
the GSEs' actual involvement in facilitating the flow of private 
capital into low/mod communities, there may be a useful prototype in 
the CRA provisions for allotting goals credit based upon the type of 
mortgage purchase transaction, i.e., the purchase of newly originated 
loan versus other mortgage investments. HUD appreciates this suggestion 
and plans to consider it further.
    c. HUD's Determination. HUD has taken the position that GSE credit 
enhancement transactions provide needed liquidity to the mortgage 
markets and play a key role in affordable housing lending. As explained 
in a study HUD has undertaken with the Urban Institute to assess recent 
innovations in the secondary market for low- and moderate-income 
lending, the GSEs' purchase of interests in CRA loans is identified as 
one approach to how the enterprises facilitate liquidity for loans that 
do not conform to standard guidelines.52 Investment analysts 
also report that the GSEs' credit enhancement of CRA REMIC securities 
results in a more attractive debt instrument for investors and a higher 
return for issuers which benefits lenders seeking to liquidate their 
CRA portfolios and ultimately borrowers.
    HUD recognizes there also are other valid reasons to grant the GSEs 
full credit under the housing goals for mortgage purchase transactions 
involving credit enhancements even where the enterprises bear 
relatively minimal credit risk. For example, in the absence of private 
mortgage insurance for multifamily mortgages, seller provided credit 
enhancements apparently are a viable means by which secondary market 
purchasers may delegate certain of their underwriting responsibilities 
and share risks. When a GSE purchases a mortgage subject to a recourse 
agreement or similar arrangement with the lender, the GSE still retains 
credit risk with respect to holders of the GSEs' mortgage-backed 
security or, where the mortgage is held in portfolio, for its own 
account. Of course, even if the GSE is not bearing

[[Page 65081]]

substantial credit risk, the GSE may still be bearing other types of 
risk. For example, the protection afforded to the GSE under recourse 
agreements is dependent on the soundness of the party to whom the GSE 
has recourse. In addition, the GSE assumes interest rate risk for 
mortgages that are retained in portfolio.
    In analyzing credit enhancement issues, thus far, there has emerged 
no clear approach to establishing an appropriate ``risk threshold'' 
associated with mortgages purchased by a GSE, below which credit toward 
the goals should not be granted. Under typical recourse agreements or 
similar arrangements, GSEs rarely divest themselves of credit risk 
associated with mortgage purchases in clear-cut percentages of risk. 
Some arrangements have time or dollar limits. The relative risk assumed 
by the GSE on one loan compared to another relates not only to the 
relative risk management characteristics (including mortgage insurance 
and recourse arrangements), but also to loan-to-value ratios, 
multifamily debt coverage ratios, interest rate risk, and many other 
parameters. Moreover, whether there is subsequent securitization or 
resecuritization of a GSE interest also bears upon the degree of credit 
risk retained by the GSE in a transaction.
    Any determination about discounting goals credit based on the level 
of risk borne by a GSE in the transaction also must take into account 
consistency with the GSEs' Charter Acts which require the GSEs to 
obtain mortgage insurance or its equivalent for certain single family 
mortgages, and must consider the financial safety and soundness 
requirements under FHEFSSA as well as its housing goals provisions.
    Accordingly, HUD has determined, based on its analysis of available 
information on the GSEs' credit enhanced transactions, comments and 
other input received on the proposed rule, as well as its analysis of 
the law, the complexity of these issues requires additional evaluations 
before changes are made to these rules. These evaluations will further 
assess the extent to which the GSEs' use of credit enhancements add 
value and liquidity to the marketplace, especially for affordable 
housing lending, as well as the impact their use has on the GSEs' 
mandate to play a leadership role in the mortgage markets. To assist 
its evaluations, HUD is undertaking further review and analysis on 
credit enhancements. Topics being covered in this review include the 
GSEs' use of credit enhancements provided by seller-servicers, third 
party vendors, and buyers of subordinated debt in the GSEs' single 
family and multifamily mortgage transactions. In addition, HUD will 
continue its assessments of credit enhancement structures including 
newly introduced structures to determine how and to what extent, if 
any, HUD's goal counting rules should be modified in the future.
19. Public Use Data Base and Public Information
    Section 1323 of FHEFSSA requires that HUD make available to the 
public data relating to the GSEs' mortgage purchases. In the 
legislative history of FHEFSSA, Congress indicated its intent that the 
GSE public use data base is to supplement HMDA data.53 The 
purpose of the GSE data base is to assist the public, including 
mortgage lenders, planners, researchers, and housing industry groups, 
as well as HUD and other government agencies, in studying the GSEs' 
mortgage activities and the flow of mortgage credit and capital into 
the nation's communities. At the same time, section 1326 of FHEFSSA 
protects from public access and disclosure, proprietary data and 
information that the GSEs submit to the Department and requires HUD to 
protect such data or information by order or regulation.
    To comply with FHEFSSA, HUD established a public use data base to 
collect and make available to the public, loan-level data on the GSEs' 
single family and multifamily mortgage purchases. In Appendix F to the 
December 1, 1995 final rule, the Department specified the structure of 
the GSE public use data base and identified the data to be withheld 
from public use.
    The single family data was to be disclosed in three separate 
files--a Census Tract File (with geographic identifiers down to the 
census tract level), a National File A (with mortgage-level data on 
owner-occupied 1-unit properties), and a National File B (with unit-
level data on all single family properties). The national files do not 
have geographic indicators. The multifamily data was to be disclosed in 
two separate files ``a Census Tract File and a National File. Each file 
consists of two parts, one part containing mortgage loan level data and 
the other containing unit level data for all multifamily properties. 
For each file, Appendix F identified data elements that were considered 
proprietary and those that were not proprietary and available to the 
public, and specified further that certain proprietary elements would 
be recoded or categorized into ranges to protect the proprietary 
information and to permit the release of non-proprietary information to 
the public. This multi-file structure was designed to allow the 
greatest dissemination of loan-level data, without disclosing 
proprietary data of the GSEs and causing competitive harm by, for 
example, allowing competitors to determine the GSEs' marketing and 
pricing strategies at the local level.
    On October 17, 1996, a Final Order describing each data element 
submitted by the GSEs and the proprietary or nonproprietary nature of 
each element was published in the Federal Register. The Final Order 
also recoded, adjusted, and categorized in ranges certain proprietary 
loan-level data elements to protect proprietary GSE information. HUD 
released the recoded data elements and the data elements that were 
identified as non-proprietary information to the public.
    In the fall of 1996, the Department released the first publicly 
available GSE loan level data base, containing non-proprietary 
information on every mortgage purchased by the GSEs from 1993 to 1995. 
Subsequently, HUD has made the 1996, 1997, 1998, and 1999 databases 
available to the public. In addition, HUD issued an order determining 
that certain aggregations of data that may otherwise be proprietary at 
the loan level is not proprietary at an aggregated level. Through that 
order, it is possible for HUD to make available to the public specific 
tables of nonproprietary information about the GSEs' activities and 
housing goal performance.
    After consideration of the current structure of the GSE public use 
data base, the Department proposed several changes to its 
classifications of the GSEs' mortgage data. Those proposed changes were 
either technical in nature or would, by reclassifying certain data from 
proprietary to non-proprietary, make available to the public the same 
data from the GSEs that is made available by primary lenders under the 
Home Mortgage Disclosure Act (HMDA).
    HUD received comments from both GSEs as well as trade 
organizations, advocacy groups, researchers, and lenders on this issue. 
Comments were almost evenly divided between those groups approving of 
increased data disclosure at the loan-level and those that opposed the 
proposals, mostly out of concern for protecting the privacy of 
borrowers' and lenders' business strategies. Both GSEs were strongly 
opposed to increased disclosure, citing competitive issues resulting 
from the release of what each GSE considered to be proprietary, 
confidential business information. Fannie Mae and Freddie Mac expressed 
general concern that

[[Page 65082]]

recoding certain loan-level data as non-proprietary at either the 
census tract or national file level would reveal information about 
lender relationships, pricing arrangements, and management of credit 
and interest rate risks. Fannie Mae also took issue with HUD's efforts 
to conform data available in the GSE public use data base to HMDA data 
for research purposes, contending that both databases are fundamentally 
different and cannot be readily reconciled. Lenders expressed a similar 
concern about the potential for additional public data to reveal 
business strategies, commenting that the more data HUD makes available 
through the public use data base, the more likely that other lenders 
would be able to discern the competition's lending strategies.
    Some trade organizations viewed the proposed changes as potentially 
harmful to consumers. Their viewpoints were representative of similar 
concerns expressed by lenders and the GSEs. One organization wrote that 
exposing more detailed information about the consumer to the general 
public will only enhance the ability of sellers of credit to take 
unfair advantage of the consumer, particularly the urban and minority 
consumer.'' Another urged that HUD be ``sensitive to emerging 
technology when deciding what data elements to make public on the 
[public use data base] files. Consumer financial and credit information 
privacy must be a paramount concern to the Department.'' A third 
organization strongly opposed releasing additional data out of concern 
for borrowers' privacy and ``potential exposure of association members' 
confidential business information.'' Another commenter, however, 
supported increased disclosure of data, contending that access to more 
data should lead to a better understanding of the affordable housing 
market and to reduced costs for those operating in the market.
    Housing and community organizations generally viewed HUD's proposed 
changes as a series of improvements that would make the public use data 
base more compatible with HMDA data and, therefore, more valuable as a 
research tool. One commenter also supported bringing the public use 
data base into conformity with HMDA stating that comparisons between 
the two databases are ``extremely important'' in evaluating the GSEs'' 
mandate to lead the primary market.
    HUD recognizes the potential harm that the release of truly 
proprietary data could have on the GSEs as well as their lending 
partners and is cognizant of its responsibilities under FHEFSSA to 
preserve and protect such data from public disclosure. Also, any 
implication that additional disclosure of GSE data might in fact 
facilitate a further loss of borrower privacy or encourage predatory 
lending practices are issues that HUD believes warrant especially close 
scrutiny.
    In recognition of its responsibilities to proceed with the utmost 
caution in releasing data, HUD follows a rigorous six-factor 
determination process in considering whether to accord proprietary 
treatment to mortgage data. For every data element under consideration 
for non-proprietary treatment, HUD evaluates:
    (1) The type of data or information involved and the nature of the 
adverse consequences to the GSE, financial or otherwise, that could 
result from disclosure;
    (2) The existence and applicability of any prior determinations by 
HUD, any other Federal agency, or a court, concerning similar data or 
information;
    (3) The measures taken by the GSE to protect the confidentiality of 
the mortgage data and similar data before and after its submission to 
the Secretary;
    (4) The extent to which the mortgage data is publicly available 
including whether the data or information is available from other 
entities, from local government offices or records, including deeds, 
recorded mortgages, and similar documents, or from publicly available 
data bases;
    (5) The difficulty that a competitor, including a seller/servicer, 
would face in obtaining or compiling the mortgage data; and
    (6) Such additional facts and legal and other authorities as the 
Secretary may consider appropriate, including the extent to which 
particular mortgage data, when considered together with other 
information, could reveal proprietary information.
    Section 1326 of FHEFSSA and Sec. 81.75 of the regulations provide 
that the Department may, by regulation or order, issue a list of 
information that shall be accorded proprietary treatment. HUD utilized 
the proposed rule to suggest changes to the proprietary treatment of 
certain GSE data. The comments received in response offered useful 
insights into concerns of many different organizations including the 
GSEs' respecting the proposed changes.
    Based on the comments received, HUD is not making a determination 
on this matter as part of this rulemaking. HUD will issue a decision on 
which data elements will be accorded proprietary and non-proprietary 
treatment by separate order following publication of this final rule in 
accordance with the Department's regulations at Secs. 81.72 through 
81.74.
20. Other Considerations
    a. Data Reporting. Many of the changes included in the final rule 
involve changes in data reporting requirements. The Department will not 
establish those requirements in this final rule, but rather will 
establish them in accordance with FHEFSSA and 24 CFR part 81, 
considering the proprietary concerns of the GSEs and other 
considerations in the public interest.
    Specific areas where additional data will need to be collected 
include but are not limited to indicators for mortgages located in 
tribal lands, identification of units with estimated affordability data 
mortgage loans receiving bonus points and the temporary adjustment 
factor, and mortgages relating to Section 8 assistance contracts.
    One area in particular that will require additional data elements 
is high cost mortgage loans. In order to monitor and enforce the 
restrictions included in this final rule, new data and reporting 
requirements may be required, as appropriate. The Department notes that 
the HUD/Treasury report recommended that the Federal Reserve amend its 
regulations to require the collection of similar data items under the 
Home Mortgage Disclosure Act (HMDA), including information on loan 
price (APR and cost of credit) and borrower debt-to-income ratio for 
HOEPA loans. If such recommendations are implemented, it may affect the 
data reporting required under this rule.
    b. Comments Regarding Regional Issues. Several commenters offered 
comments on the need to inform various communities and regions around 
the country of the GSEs' affordable housing goal performance in those 
areas. Separate from this rulemaking, as described above, HUD has 
recently taken steps to make more MSA level information, on an 
aggregated basis, about the GSEs mortgage purchases available to the 
public. HUD encourages the residents of local communities and regions 
of the country to increase their knowledge of the roles the GSEs' play 
in their areas and, toward that end, HUD will make available 
information to build understanding of the GSEs' activities.
    c. Technical Correction. Section 81.76(d) describes the protection 
of GSE information by HUD officers and employees. That section has 
cited HUD's Standards of Conduct regulations in 24 CFR part 0. HUD's 
Standards of Conduct regulations in part 0 were, however, largely 
superseded by new financial disclosure regulations codified in 5 CFR 
part 2634, new executive

[[Page 65083]]

branch-wide Standards of Conduct codified in 5 CFR part 2635, and 
supplemental HUD-specific Standards of Conduct codified in 5 CFR part 
7501. Consequently, in 1996, HUD removed the current text of 24 CFR 
part 0 and replaced it with a single section (Sec. 0.1) that provides 
cross-references to those provisions. (See final rules published in the 
Federal Register on April 5, 1996 (61 Fed. Reg. 15,350), and on July 9, 
1996 (61 Fed. Reg. 36,246).) In order to correct Sec. 81.76(d), this 
final rule will revise the references to those provisions accordingly.

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 
economically significant under E.O. 12866. Any changes made to this 
final rule subsequent to its submission to OMB are identified in the 
docket file, which is available for public inspection between 7:30 a.m. 
and 5:30 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.

Congressional Review of Major Final Rules

    This rule is a ``major rule'' as defined in Chapter 8 of 5 U.S.C. 
The rule has been 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 the Office of Management and Budget (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

    In accordance with 24 CFR 50.19(c)(1) of HUD's regulations, this 
final rule would not direct, provide for assistance or loan and 
mortgage insurance for, or otherwise govern or regulate real property 
acquisition, disposition, lease, rehabilitation, alteration, 
demolition, or new construction; nor would it establish, revise, or 
provide for standards for construction or construction materials, 
manufactured housing, or occupancy. Therefore, this final rule is 
categorically excluded from the requirements of the National 
Environmental Policy Act.

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 final 
regulation is applicable only to the GSEs, which are not small entities 
for purposes of the Regulatory Flexibility Act, and, thus, does not 
have a significant economic impact on a substantial number of small 
entities.

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 final 
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 (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 final rule would not impose any Federal 
mandates on any State, local, or tribal governments, or on the private 
sector, within the meaning of the UMRA.

Endnotes to Preamble

    1. See sec. 301 of the Federal National Mortgage Association 
Charter Act (Fannie Mae Charter Act) (12 U.S.C. 1716); sec. 301(b) 
of the Federal Home Loan Mortgage Corporation Act (Freddie Mac Act) 
(12 U.S.C. 1451 note).
    2. Secs. 306(c)(2) of the Freddie Mac Act and 304(c) of the 
Fannie Mae Charter Act.
    3. Secs. 306(g) of the Freddie Mac Act and 304(d) of the Fannie 
Mae Charter Act.
    4. Secs. 303(e) of the Freddie Mac Act and 309(c)(2) of the 
Fannie Mae Charter Act.
    5. U.S. Department of Treasury, Government Sponsorship of the 
Federal National Mortgage Association and the Federal Home Loan 
Mortgage Corporation (1996), page 3.
    6. S. Rep. No. 282, 102d Cong., 2d Sess. 34 (1992).
    7. FFIEC Press Release, July 29, 1999.
    8. Section 802(ee) of the Housing and Urban Development Act of 
1968 (Pub. L. 90-448, approved August 1, 1968; 82 Stat. 476, 541).
    9. See sec. 731 of the Financial Institutions Reform, Recovery, 
and Enforcement Act of 1989 (FIRREA) (Pub. L. 101-73, approved 
August 9, 1989), which amended the Freddie Mac Act.
    10. See 24 CFR 81.16(d) and 81.17 (1992 codification).
    11. Sec. 1321.
    12. See generally secs. 1331-34.
    13. Secs. 1332(b), 1333(a)(2), 1334(b).
    14. 65 FR 12632-12816
    15. S. Rep. No. 282, 102d Cong., 2d Sess. 34 (1992) at 35.
    16. Rental Housing Assistance--The Worsening Crisis: A Report to 
Congress on Worst Case Housing Needs, Department of Housing and 
Urban Development, Office of Policy Development and Research, (March 
2000).
    17. Standard & Poor's DRI Review of the U.S. Economy. (June 
2000), p. 57.
    18. See, e.g., S. Rep. at 34.
    19. S. Rep. at 34.
    20. 12 U.S.C. 2901 et seq.
    21. See section 1335(3)(B).
    22. The following discussion is based on analysis of 
conventional, conforming mortgage loans which were originated in 
1998, and which may have been acquired by the GSEs in 1998 or 1999. 
Appendix A contains further details regarding GSE acquisitions of 
1997 originations as well. HUD will analyze GSE purchases in 
relation to the 1999 mortgage market once HUD has the opportunity to 
analyze 1999 HMDA data for metropolitan areas.
    23. Totals do not add due to rounding.
    24. This percentage differs from the GSEs' 19 percent market 
share for rental units in single family rental properties financed 
in 1998 chiefly because the 41 percent figure reported here includes 
owner-occupied units in 2-4 unit properties which also have rental 
units.
    25. A recent Treasury-sponsored report on CRA found that banks 
and thrifts increased the share of their mortgage originations to 
low-income borrowers and communities from 25 percent in 1993 to 28 
percent in 1998. See Robert E. Litan, Nicolas P. Retsinas, Eric S. 
Belsky, and Susan White Haag, The Community Reinvestment Act After 
Financial Modernization: A Baseline Project, U.S. Department of 
Treasury, April 25, 2000.
    26. African American borrowers accounted for 6.5 percent of all 
conforming home loans, including FHA and VA loans, in metropolitan 
areas in 1998. Further information on the GSEs' purchases of 
mortgage loans to minority borrowers may be found in Appendix A.
    27. Hispanic borrowers were 6.7 percent of all conforming 
metropolitan area home loans, including FHA and VA loans, in 1998. 
Further information on the GSEs' purchases of mortgage loans to 
minority borrowers may be found in Appendix A.

[[Page 65084]]

    28. The low- and moderate-income market share is the estimated 
proportion of newly mortgaged units in the market serving low-and 
moderate-income families. The two other shares are similarly 
defined. HUD's conservative range of estimates (such as 50-55 
percent) reflects uncertainty about future market conditions.
    29. Appendix D explains the specific reasons for the 1995-98 
market estimates for the low-mode and special affordable housing 
goals are higher than the upper end of HUD's market projections for 
the years 2001-2003. Based on average 1993-1998 experience, HUD's 
projection model assumes that refinance borrowers have higher 
incomes than home purchase borrowers; however, between 1995 and 
1997, refinance borrowers had lower incomes. On average, the 1995-98 
period also exhibited a slightly higher percentage of rental units 
financed than assumed in HUD's projection model. See Appendix D for 
other reasons the 1995-1998 average market estimates are higher than 
those projected for the years 2001-2003.
    30. PriceWaterhouse-Coopers, ``The Impact of Economic Conditions 
on the Size and the Composition of the Affordable Housing Market'' 
(April 5, 2000).
    31. In 1998, PWC estimates the size of the single family 
mortgage market at $1.5 trillion. This estimate is identical to the 
widely used estimate by the Mortgage Bankers Association for the 
entire single family mortgage market, including FHA and jumbo loans.
    32. The figures presented for goal performance are based on HUD 
analysis of the GSEs' loan level data. Some results differ 
marginally from the corresponding figures presented by Fannie Mae 
and Freddie Mac in their respective Annual Housing Activities 
Reports (AHARs) to HUD, reflecting differences in application of 
counting rules.
    33. The figures presented for goal performance are based on 
HUD's analysis of the GSEs' loan level data. Some results differ 
marginally from the corresponding figures presented by the GSEs in 
their AHARs, reflecting differences in application of counting 
rules.
    34. GSE to market ratio is calculated by dividing the 
performance of the respective GSE by the performance of the market.
    35. Freddie Mac-to-Market and Fannie Mae-to-Market ratios cannot 
be calculated until 1999 HMDA data is available.
    36. The figures presented for goal performance are based on 
HUD's analysis of the GSEs' loan level data. Some results differ 
from the corresponding figures presented by Fannie Mae in its AHARs 
by one to two percentage points. The difference largely reflects 
differences between HUD and Fannie Mae in application of counting 
rules relating to counting of seasoned mortgage loans for purposes 
of this goal. Freddie Mac's AHAR figures for this goal differ 
marginally from the official figures presented above, also 
reflecting differences in application of counting rates.
    37. The percentage of Freddie Mac's multifamily transactions 
counting toward the Special Affordable Goal was unusually low in 
1999 relative to previous years, but the multifamily sector still 
contributed significantly to Freddie Mac's performance on the 
Special Affordable Goal. In 1999, 43 percent of units backing 
Freddie Mac's multifamily transactions met the Special Affordable 
Goal, representing 22% of units counted toward the Goal. Multifamily 
units were eight per cent of Freddie Mac's total purchase volume in 
1999.
    38. U.S. House of Representatives, Congressional Record. 
(October 13, 1999), p. H10014.
    39. 15 U.S.C. 1601 note; Title I, Subtitle B of the Riegle 
Community Development and Regulatory Improvement Act of 1994, Pub. 
L. 103-325 (Sept. 23, 1994); 108 Stat. 2190-98.
    40. Currently, HOEPA covers refinancings of mortgages. 15 U.S.C. 
1601(aa)(1).
    41. As mentioned above, HOEPA grants the Federal Reserve Board 
authority to lower the APR trigger to 8 percentage points over 
comparable treasuries (or to raise it to 12 percentage points 
above), 15 U.S.C. 1602(aa)(2), and to broaden the class of costs 
counted toward the fees trigger, 15 U.S.C. 1602(aa)(4)(D).
    42. 12 U.S.C. 4563(b)(1)(B).
    43. Id.
    44. CRA regulations were published as a joint final rule on May 
4, 1995. The regulation is codified at 12 CFR Part 25, CFR Parts 228 
and 203, 12 CFR Part 345, and 12 CFR Part 563e for the Office of the 
Comptroller of the Currency, the Federal Reserve Board, the Federal 
Deposit Insurance Corporation, and the Office of Thrift Supervision, 
respectively.
    45. Pub. L. 106-102; approved November 12, 1999.
    46. See S. Rep. No. 282, 102nd Cong., 2nd Sess. 39 (1992); H.R. 
Rept. 206, 102nd Cong., 1st Sess. 59 (1991)
    47. Ibid.
    48. 24 CFR parts 401 and 402, Multifamily Housing Mortgage and 
Housing Assistance Restructuring Program (Mark-to-Market): Final 
Rule, March 22, 2000.
    49. The 1992 House committee report on the bill that later 
became FHEFSSA emphasizes that ``the goals included in this 
legislation are specifically not to include purchases of equity for 
low-income housing tax credits.'' (House of Representatives Report 
102-206, 102d Congress, 1st Session, p. 60.)
    50. Handbook of Housing and Development Law, 1996, p. 10-8 and 
IRC Sec. 42 (i)(1).
    51. 42 U.S.C. 1437f, sec. 514(e)(6)
    52. Kenneth Temkin, Jennifer E. H. Johnston, and Charles 
Calhoun, An Assessment of Recent Innovations in the Secondary Market 
for Low- and Moderate-Income Lending, report submitted to the U.S. 
Department of Housing and Urban Development (March 2000).
    53. See S. Rep. No. 282, 102d Cong., 2d Sess. 39 (1992).

List of Subjects in 24 CFR Part 81

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

    Accordingly, 24 CFR part 81 is amended 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)

    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; 42 
U.S.C. 3535(d) and 3601-3619.

    2. Section 81.2, is amended by revising the definitions of ``Median 
income'' ``Metropolitan area,'' and ``Underserved area,'' by adding a 
new paragraph (7) to the definition of ``Refinancing,'' and by adding 
new definitions for ``HOEPA mortgage,'' ``Mortgages contrary to good 
lending practices,'' and ``Mortgages with unacceptable terms or 
conditions or resulting from unacceptable practices,'' to read as 
follows:


Sec. 81.2  Definitions.

* * * * *
    ``HOEPA mortgage'' means a mortgage for which the annual percentage 
rate (as calculated in accordance with the relevant provisions of 
section 107 of the Home Ownership Equity Protection Act (HOEPA) (15 
U.S.C. 1606)) exceeds the threshold described in section 103(aa)(1)(A) 
of HOEPA (15 U.S.C. 1602(aa)(1)(A)), or for which the total points and 
fees payable by the borrower exceed the threshold described in section 
103(aa)(1)(B) of HOEPA (15 U.S.C. 1602(aa)(1)(B)), as those thresholds 
may be increased or decreased by the Federal Reserve Board or by 
Congress, unless the GSEs are otherwise notified in writing by HUD. 
Notwithstanding the exclusions in section 103(aa)(1) of HOEPA, for 
purposes of this part, the term ``HOEPA mortgage'' includes all types 
of mortgages as defined in this section, including residential mortgage 
transactions as that term is defined in section 103(w) of HOEPA (15 
U.S.C. 1602(w)), but does not include reverse mortgages.
* * * * *
    Median income means, with respect to an area, the unadjusted median 
family income for the area as most recently determined and published by 
HUD. HUD will provide the GSEs annually with information specifying how 
HUD's published median family income estimates for metropolitan areas 
are to be applied for the purposes of determining median family income.
    Metropolitan area means a metropolitan statistical area (``MSA''), 
or primary metropolitan statistical area (``PMSA''), or a portion of 
such an area

[[Page 65085]]

for which median family income estimates are published annually by HUD.
* * * * *
    ``Mortgages contrary to good lending practices'' means a mortgage 
or a group or category of mortgages entered into by a lender and 
purchased by a GSE where it can be shown that a lender engaged in a 
practice of failing to:
    (1) Report monthly on borrowers' repayment history to credit 
repositories on the status of each GSE loan that a lender is servicing;
    (2) Offer mortgage applicants products for which they qualify, but 
rather steer applicants to high cost products that are designed for 
less credit worthy borrowers. Similarly, for consumers who seek 
financing through a lender's higher-priced subprime lending channel, 
lenders should not fail to offer or direct such consumers toward the 
lender's standard mortgage line if they are able to qualify for one of 
the standard products;
    (3) Comply with fair lending requirements; or
    (4) Engage in other good lending practices that are:
    (i) Identified in writing by a GSE as good lending practices for 
inclusion in this definition; and
    (ii) Determined by the Secretary to constitute good lending 
practices.
    ``Mortgages with unacceptable terms or conditions or resulting from 
unacceptable practices'' means a mortgage or a group or category of 
mortgages with one or more of the following terms or conditions:
    (1) Excessive fees, where the total points and fees charged to a 
borrower exceed the greater of 5 percent of the loan amount or a 
maximum dollar amount of $1000, or an alternative amount requested by a 
GSE and determined by the Secretary as appropriate for small mortgages.
    (i) For purposes of this definition, points and fees include:
    (A) Origination fees;
    (B) Underwriting fees;
    (C) Broker fees;
    (D) Finder's fees; and
    (E) Charges that the lender imposes as a condition of making the 
loan, whether they are paid to the lender or a third party.
    (ii) For purposes of this definition, points and fees do not 
include:
    (A) Bona fide discount points;
    (B) Fees paid for actual services rendered in connection with the 
origination of the mortgage, such as attorneys' fees, notary's fees, 
and fees paid for property appraisals, credit reports, surveys, title 
examinations and extracts, flood and tax certifications, and home 
inspections;
    (C) The cost of mortgage insurance or credit-risk price 
adjustments;
    (D) The costs of title, hazard, and flood insurance policies;
    (E) State and local transfer taxes or fees;
    (F) Escrow deposits for the future payment of taxes and insurance 
premiums; and
    (G) Other miscellaneous fees and charges that, in total, do not 
exceed 0.25 percent of the loan amount.
    (2) Prepayment penalties, except where:
    (i) The mortgage provides some benefits to the borrower (e.g., such 
as rate or fee reduction for accepting the prepayment premium);
    (ii) The borrower is offered the choice of another mortgage that 
does not contain payment of such a premium;
    (iii) The terms of the mortgage provision containing the prepayment 
penalty are adequately disclosed to the borrower; and
    (iv) The prepayment penalty is not charged when the mortgage debit 
is accelerated as the result of the borrower's default in making his or 
her mortgage payments.
    (3) The sale or financing of prepaid single-premium credit life 
insurance products in connection with the origination of the mortgage;
    (4) Evidence that the lender did not adequately consider the 
borrower's ability to make payments, i.e., mortgages that are 
originated with underwriting techniques that focus on the borrower's 
equity in the home, and do not give full consideration of the 
borrower's income and other obligations. Ability to repay must be 
determined and must be based upon relating the borrower's income, 
assets, and liabilities to the mortgage payments; or
    (5) Other terms or conditions that are:
    (i) Identified in writing by a GSE as unacceptable terms or 
conditions or resulting from unacceptable practices for inclusion in 
this definition; and
    (ii) Determined by the Secretary as an unacceptable term or 
condition of a mortgage for which goals credit should not be received.
* * * * *
    Refinancing means * * *
* * * * *
    (7) A conversion of a balloon mortgage note on a single family 
property to a fully amortizing mortgage note where the GSE already owns 
or has an interest in the balloon note at the time of the conversion.
* * * * *
    Underserved area means:
    (1) For purposes of the definitions of ``Central city'' and ``Other 
underserved area,'' a 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 median income of 
the metropolitan area and a minority population of 30 percent or 
greater; or
    (ii) A median income at or below 90 percent of median income of the 
metropolitan area.
    (2) For purposes of the definition of ``Rural area'':
    (i) In areas other than New England, a whole county, a Federal or 
State American Indian reservation or tribal or individual trust land, 
or the balance of a county excluding the area within any Federal or 
State American Indian reservation or tribal or individual trust land, 
having:
    (A) 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
    (B) A median income at or below 95 percent of the greater of the 
State non-metropolitan median income or nationwide non-metropolitan 
median income.
    (ii) In New England, a whole county having the characteristics in 
paragraphs (2)(i)(A) or (2)(i)(B) of this definition; a Federal or 
State American Indian reservation or tribal or individual trust land, 
having the characteristics in paragraphs (2)(i)(A) or (2)(i)(B) of this 
definition; or the balance of a county, excluding any portion that is 
within any Federal or State American Indian reservation or tribal or 
individual trust land, or metropolitan area where the remainder has the 
characteristics in paragraphs (2)(i)(A) or (2)(i)(B) of this 
definition.
    (3) Any Federal or State American Indian reservation or tribal or 
individual trust land that includes land that is both within and 
outside of a metropolitan area and that is designated as an underserved 
area by HUD. In such cases, HUD will notify the GSEs as to 
applicability of other definitions and counting conventions.
* * * * *

    3. Section 81.12 is amended as follows:
    a. Paragraph (b) is amended by revising the last sentence; and
    b. Paragraph (c) is revised, to read as follows:

[[Page 65086]]

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 October 31, 2000.
    (c) Goals. The annual goals for each GSE's purchases of mortgages 
on housing for low-and moderate-income families are:
    (1) For each of the years 2001-2003, 50 percent of the total number 
of dwelling units financed by that GSE's mortgage purchases in each of 
those years unless otherwise adjusted by HUD in accordance with 
FHEFSSA; and
    (2) For the year 2004 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2004 and thereafter, 
the annual goal for each of those years shall be 50 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years.

    4. Section 81.13 is amended as follows:
    a. Paragraph (b) is amended by revising the last sentence; and
    b. Paragraph (c) is revised, 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 October 31, 2000.
    (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 each of the years 2001-2003, 31 percent of the total number 
of dwelling units financed by that GSE's mortgage purchases in each of 
those years unless otherwise adjusted by HUD in accordance with 
FHEFSSA; and
    (2) For the year 2004 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2004 and thereafter, 
the annual goal for each of those years shall be 31 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years.
* * * * *

    5. Section 81.14 is amended as follows:
    a. Paragraph (b) is amended by revising the last sentence;
    b. Paragraph (c) is revised;
    c. Paragraph (d) is amended by revising paragraph (d)(1)(i);
    d. Paragraph (e) is amended by revising paragraphs (e)(2), (e)(3), 
and (e)(4);
    e. Paragraph (f) is redesignated as paragraph (g) and the last 
sentence of the newly redesignated paragraph (g) is revised; and
    f. A new paragraph (f) is added; 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 October 31, 2000.
    (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 each of the years 2001, 2002, and 2003, 20 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years unless otherwise adjusted by HUD in 
accordance with FHEFSSA. The goal for each year 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 1997, 1998 and 1999, unless otherwise adjusted by HUD in 
accordance with FHEFSSA; and
    (2) For the year 2004 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2004 and thereafter, 
the annual goal for each of those years shall be 20 percent of the 
total number of dwelling units financed by that 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 1997, 1998 and 1999.
    (d) * * *
    (1) * * *
    (i) 20 percent of the dwelling units in the particular multifamily 
property are affordable to especially low-income families; or
* * * * *
    (e) * * *
    (2) Mortgages insured under HUD's Home Equity Conversion Mortgage 
(``HECM'') Insurance Program, 12 U.S.C. 1715 z-20; mortgages guaranteed 
under the Rural Housing Service's Single Family Housing Guaranteed Loan 
Program, 42 U.S.C. 1472; mortgages on properties on tribal lands 
insured under FHA's Section 248 program, 12 U.S.C. 1715 z-13, HUD's 
Section 184 program, 12 U.S.C. 1515 z-13a, or Title VI of the Native 
American Housing Assistance and Self-Determination Act of 1996, 25 
U.S.C. 4191-4195; meet the requirements of 12 U.S.C. 4563(b)(1)(A)(i) 
and (ii).
    (3) HUD will give full credit toward achievement of the Special 
Affordable Housing Goal for the activities in 12 U.S.C. 4563(b)(1)(A), 
provided the GSE submits documentation to HUD that supports eligibility 
under 12 U.S.C. 4563(b)(1)(A) for HUD's approval.
    (4)(i) For purposes of determining whether a seller meets the 
requirement in 12 U.S.C. 4563(b)(1)(B), a seller must currently operate 
on its own or actively participate in an on-going, discernible, active, 
and verifiable program directly targeted at the origination of new 
mortgage loans that qualify under the Special Affordable Housing Goal.
    (ii) A seller's activities must evidence a current intention or 
plan to reinvest the proceeds of the sale into mortgages qualifying 
under the Special Affordable Housing Goal, with a current commitment of 
resources on the part of the seller for this purpose.
    (iii) A seller's actions must evidence willingness to buy 
qualifying loans when these loans become available in the market as 
part of active, on-going, sustainable efforts to ensure that additional 
loans that meet the goal are originated.
    (iv) Actively participating in such a program includes purchasing 
qualifying loans from a correspondent originator, including a lender or 
qualified housing group, that operates an on-going program resulting in 
the origination of loans that meet the requirements of the goal, has a 
history of delivering, and currently delivers qualifying loans to the 
seller.
    (v) The GSE must verify and monitor that the seller meets the 
requirements in paragraphs (e)(4)(i) through (e)(4)(iv) of this section 
and develop any necessary mechanisms to ensure compliance with the 
requirements, except as provided in paragraph (e)(4)(vi) and (vii) of 
this section.

[[Page 65087]]

    (vi) Where a seller's primary business is originating mortgages on 
housing that qualifies under this Special Affordable Housing Goal such 
seller is presumed to meet the requirements in paragraphs (e)(4)(i) 
through (e)(4)(iv) of this section. Sellers that are institutions that 
are:
    (A) Regularly in the business of mortgage lending;
    (B) A BIF-insured or SAIF-insured depository institution; and
    (C) Subject to, and has received at least a satisfactory 
performance evaluation rating for
    (1) At least the two most recent consecutive examinations under, 
the Community Reinvestment Act, if the lending institution has total 
assets in excess of $250 million; or
    (2) The most recent examination under the Community Reinvestment 
Act if the lending institutions which have total assets no more than 
$250 million are identified as sellers that are presumed to have a 
primary business of originating mortgages on housing that qualifies 
under this Special Affordable Housing Goal and, therefore, are presumed 
to meet the requirements in paragraphs (e)(4)(i) through (e)(4)(iv) of 
this section.
    (vii) Classes of institutions or organizations that are presumed 
have as their primary business originating mortgages on housing that 
qualifies under this Special Affordable Housing Goal and, therefore. 
are presumed in paragraphs (e)(4)(i) through (e)(4)(iv) of this section 
to meet the requirements are as follows: State housing finance 
agencies; affordable housing loan consortia; Federally insured credit 
unions that are:
    (A) Members of the Federal Home Loan Bank System and meet the 
first-time homebuyer standard of the Community Support Program; or
    (B) Community development credit unions; community development 
financial institutions; public loan funds; or non-profit mortgage 
lenders. HUD may determine that additional classes of institutions or 
organizations are primarily engaged in the business of financing 
affordable housing mortgages for purposes of this presumption, and if, 
so will notify the GSEs in writing.
    (viii) For purposes of paragraph (e)(4) of this section, if the 
seller did not originate the mortgage loans, but the originator of the 
mortgage loans fulfills the requirements of either paragraphs (e)(4)(i) 
through (e)(4)(iv), paragraph (e)(4)(vi) or paragraph (e)(4)(vii) of 
this section; and the seller has held the loans for six months or less 
prior to selling the loans to the GSE, HUD will consider that the 
seller has met the requirements of this paragraph (e)(4) and of 12 
U.S.C. 4563(b)(1)(B).
* * * * *
    (f) Partial credit activities. Mortgages insured under HUD's Title 
I program, which includes property improvement and manufactured home 
loans, shall receive one-half credit toward the Special Affordable 
Housing Goal until such time as the Government National Mortgage 
Association fully implements a program to purchase and securitize Title 
I loans.
    (g) No credit activities. * * * For purposes of this paragraph (g), 
``mortgages or mortgage-backed securities portfolios'' includes 
mortgages retained by Fannie Mae or Freddie Mac and mortgages utilized 
to back mortgage-backed securities.

    6. In Sec. 81.15, paragraph (a) is revised, paragraph (d) is 
amended by revising the second sentence and by adding two new sentences 
at the end, and paragraph (e) is amended by re-designating paragraph 
(e)(6) as (e)(7), and by adding a new paragraph (e)(6), to read as 
follows:


Sec. 81.15  General requirements.

    (a) Calculating the numerator and denominator. Performance under 
each of the housing goals shall be measured using a fraction that is 
converted into a percentage.
    (1) The numerator. The numerator of each fraction is the number of 
dwelling units financed by a GSE's mortgage purchases in a particular 
year that count toward achievement of the housing goal.
    (2) The denominator. The denominator of each fraction is, for all 
mortgages purchased, the number of dwelling units that could count 
toward achievement of the goal under appropriate circumstances. The 
denominator shall not include GSE transactions or activities that are 
not mortgages or mortgage purchases as defined by HUD or transactions 
that are specifically excluded as ineligible under Sec. 81.16(b).
    (3) Missing data or information. When a GSE lacks sufficient data 
or information to determine whether the purchase of a mortgage 
originated after 1992 counts toward achievement of a particular housing 
goal, that mortgage purchase shall be included in the denominator for 
that housing goal, except under the circumstances described in 
paragraphs (d) and (e)(6) of this section.
* * * * *
    (d) Counting owner-occupied units. * * * To determine whether 
mortgagors 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. When the income of the mortgagors is not 
available to determine whether the purchase of a mortgage originated 
after 1992 counts toward achievement of the Low- and Moderate-Income 
Housing Goal or the Special Affordable Housing Goal, a GSE may exclude 
single family owner-occupied units located in census tracts with median 
income less than or equal to area median income according to the most 
recent census from the denominator as well as the numerator, up to a 
ceiling 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 in excess of the 
ceiling will be included in the denominator and excluded from the 
numerator if they are missing data.
    (e) * * *
    (6) Affordability data unavailable. (i) Multifamily. When 
information regarding the affordability of a rental unit is not 
available, a GSE's performance with respect to such a unit may be 
evaluated with estimated affordability information, so long as the 
Department has reviewed and approved the data source and methodology 
for such estimated data. The use of estimated information to determine 
affordability may be used up to a maximum of five percent of the total 
number of units backing the GSEs' multifamily mortgage purchases in the 
current year, adjusted for REMIC percentage and participation percent. 
When the application of affordability data based on an approved market 
rental data source and methodology is not possible, and therefore the 
GSE lacks sufficient information to determine whether the purchase of a 
mortgage originated after 1992 counts toward the achievement of the 
Low- and Moderate-Income Housing Goal or the Special Affordable Housing 
Goal, HUD will exclude units in multifamily properties from the 
denominator as well as the numerator in calculating performance under 
those goals.
    (ii) Rental units in 1-4 unit single family properties. When 
neither the income of prospective or actual tenants of a rental unit in 
a 1-4 unit single family property nor actual or average rent data is 
available, and, therefore, the GSE lacks sufficient information to 
determine whether the purchase of a mortgage originated after 1992 
counts toward achievement of the Low- and Moderate-Income Housing Goal 
or the

[[Page 65088]]

Special Affordable Housing Goal, a GSE may exclude rental units in 1-4 
unit single family properties from the denominator as well as the 
numerator in calculating performance under those goals.
* * * * *

    7. Section 81.16 is amended as follows:
    a. Paragraph (a) is revised;
    b. Paragraph (b) is amended by revising paragraphs (b)(3) and 
(b)(9) and by adding a new paragraph (b)(10);
    c. Paragraph (c) is amended by adding introductory text, by 
revising paragraph (c)(6), and by adding new paragraphs (c)(9), 
(c)(10), (c)(11), (c)(12), and (c)(13); and
    d. A new paragraph (d) is added; to read as follows:


Sec. 81.16  Special counting requirements.

    (a) General. HUD shall determine whether a GSE shall receive full, 
partial, or no credit for a transaction toward achievement of any of 
the housing goals. In this determination, HUD will consider whether a 
transaction or activity of the GSE is substantially equivalent to a 
mortgage purchase and either creates a new market or adds liquidity to 
an existing market, provided however that such mortgage purchase 
actually fulfills the GSE's purposes and is in accordance with its 
Charter Act.
    (b) * * *
    (3) Purchases of non-conventional mortgages except:
    (i) Where such mortgages are acquired under a risk-sharing 
arrangement with a Federal agency;
    (ii) Mortgages insured under HUD's Home Equity Conversion Mortgage 
(``HECM'') insurance program, 12 U.S.C. 1715z-20; mortgages guaranteed 
under the Rural Housing Service's Single Family Housing Guaranteed Loan 
Program, 42 U.S.C. 1472; mortgages on properties on lands insured under 
FHA's Section 248 program, 12 U.S.C. 1715z-13, or HUD's Section 184 
program, 12 U.S.C. 1515z-13a, or Title VI of the Native American 
Housing Assistance and Self-Determination Act of 1996, 25 U.S.C. 4191-
4195; and mortgages with expiring assistance contracts as defined at 42 
U.S.C. 1737f;
    (iii) Mortgages under other mortgage programs involving Federal 
guarantees, insurance or other Federal obligation where the Department 
determines in writing that the financing needs addressed by the 
particular mortgage program are not well served and that the mortgage 
purchases under such program should count under the housing goals, 
provided the GSE submits documentation to HUD that supports eligibility 
and that HUD makes such a determination, or
    (iv) As provided in Sec. 81.14(e)(3)
* * * * *
    (9) Single family mortgage refinancings that result from conversion 
of balloon notes to fully amortizing notes, if the GSE already owns or 
has an interest in the balloon note at the time conversion occurs.
    (10) Any combination of factors in paragraphs (b)(1) through (9) of 
this section.
    (c) Other special rules. Subject to HUD's primary determination of 
whether a GSE shall receive full, partial, or no credit for a 
transaction toward achievement of any of the housing goals as provided 
in paragraph (a) of this section, the following supplemental rules 
apply:
* * * * *
    (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 the GSE has already counted the mortgage under a housing goal 
applicable to 1993 or any subsequent year, or where the Department 
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.
* * * * *
    (9) Expiring assistance contracts. In accordance with 12 U.S.C. 
4565(a)(5), actions that assist in maintaining the affordability of 
assisted units in eligible multifamily housing projects with expiring 
contracts shall receive credit under the housing goals as provided in 
paragraph (b)(3)(ii) and in accordance with paragraphs (b) and (c)(1) 
through (c)(9) of this section.
    (i) For restructured (modified) multifamily mortgage loans with an 
expiring assistance contract where a GSE holds the loan in portfolio 
and facilitates modification of loan terms that results in lower debt 
service to the project's owner, the GSE shall receive full credit under 
any of the housing goals for which the units covered by the mortgage 
otherwise qualify.
    (ii) Where a GSE undertakes more than one action to assist a single 
project or where a GSE engages in an activity that it believes assists 
in maintaining the affordability of assisted units in eligible 
multifamily housing projects but which is not otherwise covered in 
paragraph (c)(9)(i) of this section, the GSE must submit the 
transaction to HUD for a determination on appropriate goals counting 
treatment.
    (10) Bonus points. The following transactions or activities, to the 
extent the units otherwise qualify for one or more of the housing 
goals, will receive bonus points toward the particular goal or goals, 
by receiving double weight in the numerator under a housing goal or 
goals and receiving single weight in the denominator for the housing 
goal or goals. Bonus points will not be awarded for the purposes of 
calculating performance under the special affordable housing 
multifamily subgoal described in Sec. 81.14(c). All transactions or 
activities meeting the following criteria will qualify for bonus points 
even if a unit is missing affordability data and the missing 
affordability data is treated consistent with Sec. 81.15(e)(6)(i). 
Bonus points are available to the GSEs for purposes of determining 
housing goal performance for each year 2001 through 2003. Beginning in 
the year 2004, bonus points are not available for goal performance 
counting purposes unless the Department extends their availability 
beyond December 31, 2003 for one or more types of activities and 
notifies the GSEs by letter of that determination.
    (i) Small multifamily properties. HUD will assign double weight in 
the numerator under a housing goal or goals for each unit financed by 
GSE mortgage purchases in small multifamily properties (5 to 50 
physical units), provided, however, that bonus points will not be 
awarded for properties that are aggregated or disaggregated into 5-50 
unit financing packages for the purpose of earning bonus points.
    (ii) Units in 2-4 unit owner-occupied properties. HUD will assign 
double weight in the numerator under the housing goals for each unit 
financed by GSE mortgage purchases in 2- to 4-unit owner-occupied 
properties, to the extent that the number of such units financed by 
mortgage purchases are in excess of 60 percent of the yearly average 
number of units qualifying for the respective housing goal during the 
five years immediately preceding the year of mortgage purchase.
    (11) Temporary adjustment factor for Freddie Mac. In determining 
Freddie Mac's performance on the Low- and Moderate-Income Housing Goal 
and the Special Affordable Housing Goal, HUD will count each qualifying 
unit in a property with more than 50 units as 1.2 units in calculating 
the numerator and as one unit in calculating the

[[Page 65089]]

denominator, for the respective housing goal. HUD will apply this 
temporary adjustment factor for each year from 2001 through 2003; for 
the year 2004 and thereafter, this temporary adjustment factor will no 
longer apply.
    (12) HOEPA mortgages and mortgages with unacceptable terms and 
conditions. HOEPA mortgages and mortgages with unacceptable terms or 
conditions as defined in Sec. 81.2 will not receive credit toward any 
of the three housing goals.
    (13) Mortgages contrary to good lending practices. The Secretary 
will monitor the practices and processes of the GSEs to ensure that 
they are not purchasing loans that are contrary to good lending 
practices as defined in Sec. 81.2. Based on the results of such 
monitoring, the Secretary may determine in accordance with paragraph 
(d) of this section that mortgages or categories of mortgages where a 
lender has not engaged in good lending practices will not receive 
credit toward the three housing goals.
    (d) HUD review of transactions. HUD will determine whether a class 
of transactions counts as a mortgage purchase under the housing goals. 
If a GSE seeks to have a class of transactions counted under the 
housing goals that does not otherwise count under the rules in this 
part, the GSE may provide HUD detailed information regarding the 
transactions for evaluation and determination by HUD in accordance with 
this section. In making its determination, HUD may also request and 
evaluate additional information from a GSE with regard to how the GSE 
believes the transactions should be counted. HUD will notify the GSE of 
its determination regarding the extent to which the class of 
transactions may count under the goals.

    8. Section 81.17 is amended by adding a new paragraph (d), to read 
as follows:


Sec. 81.17  Affordability--Income level definitions--family size and 
income known (owner-occupied units, actual tenants, and prospective 
tenants).

* * * * *
    (d) Especially-low-income means, in the case of rental units, where 
the income of actual or prospective tenants is available, income not in 
excess of the following percentages of area median income corresponding 
to the following family sizes:

------------------------------------------------------------------------
                                                           Percentage of
               Number of persons in family                  area median
                                                              income
------------------------------------------------------------------------
1.......................................................              35
2.......................................................              40
3.......................................................              45
4.......................................................              50
5 or more...............................................            (*)
------------------------------------------------------------------------
* 50% plus (4.0% multiplied by the number of persons in excess of 4).


    9. Section 81.18 is amended by adding a new paragraph (d), to read 
as follows:


Sec. 81.18  Affordability--Income level definitions--family size not 
known (actual or prospective tenants).

* * * * *
    (d) For especially-low-income, income of prospective tenants shall 
not exceed the following percentages of area median income with 
adjustments, depending on unit size:

------------------------------------------------------------------------
                                                           Percentage of
                        Unit size                           area median
                                                              income
------------------------------------------------------------------------
Efficiency..............................................              35
1 bedroom...............................................            37.5
2 bedrooms..............................................              45
3 bedrooms or more......................................            (*)
------------------------------------------------------------------------
* 52% plus (6.0% multiplied by the number of bedrooms in excess of 3).


    10. In Sec. 81.19, paragraph (d) is re-designated as paragraph (e), 
a new paragraph (d) is added and the second sentence of the newly re-
designated paragraph (e) is revised, to read as follows:


Sec. 81.19  Affordability--Rent level definitions--tenant income is not 
known.

* * * * *
    (d) For especially-low-income, maximum affordable rents to count as 
housing for especially-low-income families shall not exceed the 
following percentages of area median income with adjustments, depending 
on unit size:

------------------------------------------------------------------------
                                                           Percentage of
                        Unit size                           area median
                                                              income
------------------------------------------------------------------------
Efficiency..............................................            10.5
1 bedroom...............................................           11.25
2 bedrooms..............................................            13.5
3 bedrooms or more......................................            (*)
------------------------------------------------------------------------
* 15.6% plus (1.8% multiplied by the number of bedrooms in excess of 3).

* * * * *
    (e) Missing Information. * * * If a GSE makes such efforts but 
cannot obtain data on the number of bedrooms in particular units, in 
making the calculations on such units, the units shall be assumed to be 
efficiencies except as provided in Sec. 81.15(e)(6)(i)

    11. In Sec. 81.76, paragraph (d) is revised to read as follows:


Sec. 81.76  FOIA requests and protection of GSE information.

* * * * *
    (d) Protection of information by HUD officers and employees. The 
Secretary will institute all reasonable safeguards to protect data or 
information submitted by or relating to either GSE, including, but not 
limited to, advising all HUD officers and employees having access to 
data or information submitted by or relating to either GSE of the legal 
restrictions against unauthorized disclosure of such data or 
information under the executive branch-wide standards of ethical 
conduct, 5 CFR part 2635, and the Trade Secrets Act, 18 U.S.C. 1905. 
Officers and employees shall be advised of the penalties for 
unauthorized disclosure, ranging from disciplinary action under 5 CFR 
part 2635 to criminal prosecution.
* * * * *

    Dated: October 16, 2000.
William C. Apgar,
Assistant Secretary for Housing--Federal Housing Commissioner.

    Note: The Following 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 and Response to Comments

    Sections 1 and 2 provide a basic description of the rule 
process. Section 3 discusses comments on the proposed rule and the 
Department's responses. Section 4 discusses conclusions based on 
consideration of the factors.

1. Establishment of 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.

[[Page 65090]]

2. Underlying Data

    In considering the statutory factors in establishing these 
goals, HUD relied on data from the 1995 American Housing Survey 
(AHS), the 1990 Census of Population and Housing, the 1991 
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 1993-99 
in accordance with the goal counting provisions established by the 
Department in the December 1995 rule (24 CFR part 81).

3. Response to Comments

a. Introduction

    Fannie Mae and Freddie Mac provided detailed comments on HUD's 
discussion of the factors for determining the goal levels in 
Appendix A of the proposed rule. A major portion of their 
substantive comments concerned HUD's analysis of the GSEs' 
performance relative to the market. Both GSEs disagreed with HUD's 
conclusions that they lag the conventional conforming market in 
funding mortgages for the goals-qualifying segments (low-mod 
borrowers, special affordable borrowers, and underserved 
neighborhoods) of the single-family owner market. The GSEs argued 
strongly that they have led the mortgage market, from both 
quantitative and qualitative perspectives (explained below). The 
GSEs expressed concern about HUD's assumptions and treatment of 
specific data in estimating the goals-qualifying shares for single-
family owner mortgages. The GSEs concluded that HUD chose 
assumptions and data sources that result in an overstatement of the 
low-mod, special affordable, and underserved areas shares of owner 
mortgages.
    It should be noted that the GSEs extended their criticisms to 
other researchers who have examined this issue of their targeted 
lending performance relative to the overall mortgage market. Section 
E.3 of this appendix summarizes findings of several independent 
studies that have also concluded that the GSEs have lagged the 
market in affordable lending. For the most part, these studies have 
used the same HMDA-based methodology described in Section E.2 of 
this appendix.
    The GSEs focused many of their comments on the adequacy of HMDA 
data, the main source for the goals-qualifying shares of the 
conventional conforming market, against which the GSEs are compared. 
The GSEs argued that HMDA data are biased (i.e., overstate the 
goals-qualifying shares of the market) and that significant portions 
of HMDA data are not relevant for calculating the market standard 
for evaluating GSE performance in the conventional conforming 
market. These and related comments of the GSEs are discussed below 
in subsections b-f.
    Both GSEs also argued that HUD's analysis and conclusions 
depended on a continuation of recent conditions of economic 
expansion and low interest rates. According to the GSEs, HUD's range 
of market estimates did not include periods of adverse economic and 
affordability conditions, such as existed in the early 1990s. HUD 
discusses the GSEs' comments on economic volatility in Section B of 
Appendix D. As explained there, HUD's ranges of market estimates for 
each of the housing goals are conservative, because they allow for 
economic and interest rate conditions much more adverse than existed 
during the mid- to late-1990s.
    The discussion that follows summarizes HUD's responses to the 
GSEs' comments on the ``leading the market'' analysis that HUD has 
conducted in Section E.2 of this appendix--that section fully 
develops the various concepts referenced here. The final two 
subsections, g and h, discuss additional issues that the GSEs raised 
about HUD's analysis of the factors in Appendix A.

b. Overview of Leading the Owner Market--Quantitative Analysis

    The analysis of HMDA data in Section E.2 of this appendix 
indicates demonstrates that even though the GSEs have improved their 
performance since 1993, they have lagged depositories and others in 
the conventional conforming market in funding affordable loans, both 
since 1993 and during the more recent 1996-98 period when the new 
housing goals have been in effect. For example, underserved areas 
accounted for 22.9 (19.9) percent of Fannie Mae's (Freddie Mac's) 
purchases of home loans between 1996 and 1998, compared with 24.4 
percent for the entire conforming market (excluding B&C loans). 
Based on comparisons such as these, HUD concludes that the GSEs need 
to continue improving their performance so that they can match or 
exceed the overall market in affordable lending.
    In their comments, the GSEs reached the opposite conclusion--
each stated that they already match or even lead the market, 
depending on the affordable category being considered. The GSEs also 
assert that HUD's analysis does not accurately reflect their 
performance relative to the overall market. Freddie Mac stated that 
``the shares of Freddie Mac's loan purchases serving low- and 
moderate-income families, families in underserved areas and minority 
families mirror those of the primary market''. Freddie Mac said that 
its market calculations ``account for the limitations on loans we 
[Freddie Mac] can purchase'' (see below). Similarly, Fannie Mae 
stated that ``an appropriate comparison between Fannie Mae and the 
primary single-family market shows that we [Fannie Mae] serve a 
higher percentage of low- and moderate-income borrowers, a higher 
percentage of minority borrowers, and a higher percentage of 
borrowers in underserved areas than does the primary market''.
    Both the GSEs and HUD rely on HMDA data for the market 
estimates. However, as suggested by the GSEs' comments, they 
frequently adjust HMDA data to exclude loans in the market that they 
perceive as not being available for them to purchase. The types of 
adjustments made by the GSEs, and HUD's response to those 
adjustments, are discussed in the next subsection. HUD's conclusions 
about the appropriate definition of the conventional conforming 
market are also discussed in Section E of this appendix, which 
provides a detailed analysis of the GSEs' goals-qualifying purchases 
in the single-family-owner market, and in Appendix D, which provides 
overall (both single-family and multifamily) estimates of the goals-
qualifying shares of the market. In Appendix D, HUD excludes B&C 
loans from its overall estimates of the market. In this appendix, 
HUD illustrates (to the extent HMDA data allow) the effects of 
excluding B&C loans on the GSE-market comparisons, as well as the 
effects of excluding other loan categories such as manufactured 
housing loans. However, as explained below, HUD does not believe 
that HMDA data for the conventional conforming market should be 
adjusted to reflect the GSEs' perceptions about the characteristics 
of loans that are available for them to purchase.

c. Relevant Market for Single-Family Owner Properties

    Both GSEs provided numerous comments concerning the types of 
mortgages that HUD should exclude from the definition of the single-
family owner market, both when HUD is evaluating the GSEs' 
performance relative to the conventional conforming owner market 
(i.e., determining whether the GSEs' lead or lag the market for 
single-family-owner mortgages) and when HUD is calculating the 
overall market shares for each housing goal (as described in 
Appendix D). Fannie Mae stated that it ``can only purchase or 
securitize mortgages that primary market lenders are willing to 
sell'' and that certain types of products (such as ARMs) ``are 
particularly difficult to structure for sale to the secondary 
market''. Fannie Mae added that ``HUD fails to adjust for those 
housing markets that are not fully available to Fannie Mae and 
Freddie Mac''. Freddie Mac stated that it ``has not achieved, and is 
unlikely to achieve in the near term, the same penetration in the 
subprime and manufactured housing segments of the market as it has 
achieved in the conventional, conforming market'' and therefore HUD 
should not include these segments in its market definition. 
According to the GSEs, markets that are ``not available'' to them or 
where they are not a ``full participant'' should be excluded from 
HUD's market definition. In addition to the subprime and 
manufactured housing markets, examples of market segments mentioned 
by the GSEs for exclusion included: low-down payment mortgages 
(those with loan-to-value ratios greater than 80 percent) without 
private mortgage insurance or some other credit enhancement; loans 
financed through state and local housing finance agencies; below-
market-interest-rate mortgages; specialized CRA mortgages; and 
portions of depository portfolios that are not available at mortgage 
origination for purchase by the GSEs.
    To analyze the availability of loans originated by depositories 
to the GSEs, Fannie Mae funded a study by KPMG Barefoot-Marrinan 
(KPMG). According to Fannie Mae, KPMG found that the advent of the 
Community Reinvestment Act (CRA) had encouraged depositories to hold 
lower-income loans in portfolio. Depositories may not offer their 
products for sale on the secondary market not only because they are

[[Page 65091]]

outside of the GSEs' guidelines, but also because of business and 
portfolio strategy reasons (such as the interest-rate-duration 
advantage of holding ARMs in portfolio).
    Freddie Mac estimated the impacts on HUD's market estimates of 
excluding from the market definition both specialized community 
development (CRA-type) loans and portions of depository portfolios. 
Based on Freddie Mac's analysis, the low-mod (underserved areas) 
share of the owner market would fall by four (three) percentage 
points and HUD's overall low-mod and underserved areas market 
estimates would each fall by about two percentage points. In 
commenting on whether Freddie Mac leads or lags depositories in 
affordable lending, Freddie Mac said that the HMDA data for 
depositories should be adjusted downward to exclude depositories' 
high-LTV loans without private mortgage insurance, their below-
market rate loans, their subprime loans, and coverage bias in HMDA 
(see the next subsection). Based on these adjustments, Freddie Mac 
reduced the 1998 HMDA-reported underserved areas percentage for 
depositories from 26.1 percent to 20.0, which led Freddie Mac to 
conclude that its performance equals or exceeds the performance of 
depositories on loans that are likely to be sold to Freddie Mac.
    HUD's Response. In general, HUD disagrees with the comments 
offered by the GSEs about excluding those market segments that they 
haven't yet been able to penetrate fully. Congress stated that HUD 
was to estimate the size of the conventional conforming mortgage 
market, not the market that the GSEs perceive as available for them 
to purchase. However, with respect to the subprime market, HUD 
believes that the risky, B&C portion of that market should be 
excluded from the market definition for each of the housing goals. 
Thus, HUD includes only the A-minus portion of the subprime market 
in its overall estimates of the goals-qualifying market shares. In 
Appendix D, HUD explains its methodology for adjusting the overall 
market estimates to exclude B&C loans. Section E.2 of this appendix 
uses HMDA data and the GSEs' loan-level data to examine the GSEs' 
performance in the single-family owner portion of the conventional 
conforming mortgage market in metropolitan areas. B&C loans are not 
identified in HMDA data; however, HUD shows the effects of adjusting 
the owner market definition for subprime and B&C loans by using a 
list of lenders that specialize in subprime loans (see Table A.4b).
    Excluding other important segments of the lower-income mortgage 
market, as the GSEs recommend, would render the resulting market 
benchmark useless for evaluating the GSEs' performance. The loans 
that the GSEs would exclude are important sources of lower-income 
credit and, in fact, are among the very loans the GSEs are supposed 
to be funding. A recent report by the Department of Treasury 
demonstrated the targeting of CRA-type loans to lower-income and 
minority families. Numerous studies have shown that the manufactured 
home sector is an important source of low-income housing. In many of 
these markets, a more active secondary market would encourage 
lending to traditionally underserved borrowers. While HUD recognizes 
that some segments of the market may be more challenging for the 
GSEs than others, the data reported in Tables A.7a and A.7b of this 
Appendix show that the GSEs have ample opportunities to purchase 
goals-qualifying mortgages. As market leaders, the GSEs should be 
looking for innovative ways to pursue this business, rather than 
suggesting that it is not available to the secondary market. 
Furthermore, there is evidence that the GSEs can earn reasonable 
returns on their goals business. The Economic Analysis that 
accompanies this final rule provides evidence that the GSEs have 
been earning financial returns on their purchases of goals-
qualifying loans that are only slightly below their 20-25 percent 
return on equity from their normal business.
    HUD also disagrees with other specific comments offered by the 
GSEs. For example, HUD does not think that the data for depositories 
should be adjusted downward as proposed by Freddie Mac and Fannie 
Mae. Both types of institutions receive government benefits and both 
operate in the conventional conforming market. 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. With respect to loans that are originated 
without private mortgage insurance, the GSEs have been quite 
innovative in structuring transactions to provide alternative credit 
enhancements. Between 1997 and 1999, Freddie Mac was involved in 16 
structured transactions totaling $8.1 billion, with Freddie Mac's 
1999 business accounting for over $5 billion of this total.\1\ HUD 
gives full goals credit for such credit-enhanced transactions.
    Finally, it should be noted that 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 experience in 1997-98, the purchase of seasoned 
loans appears to be one useful strategy for purchasing goals-
qualifying loans. In Section E.2, HUD's comparisons of the GSEs' 
single-family performance with those of depositories and the overall 
single-family market include the GSEs' purchases of prior-year as 
well newly-originated loans.

d. Bias in HMDA Data

    Both GSEs refer to findings from a study by Peter Zorn and Jim 
Berkovec concerning potential bias in HMDA data.\2\ 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, Zorn and 
Berkovec conclude that HMDA data overstates the percentage of 
conventional, conforming loans originated for lower-income borrowers 
and for properties located in underserved census tracts. The data 
reported in Table A.4a of this appendix, which are based on more 
recent data than the Zorn and Berkovec paper, do not appear to 
support their findings. With respect to the goals-qualifying 
percentages for GSE purchases, comparing columns 2 and 4 for Fannie 
Mae, and columns 6 and 8 for Freddie Mac, show that the HMDA-
reported goals-qualifying percentages for loans sold to the GSEs are 
not always larger than the corresponding percentages for loans the 
GSEs report as purchased. In fact, the HMDA-reported percentages are 
more likely to be smaller than the GSE-reported percentages for the 
Special Affordable and Underserved Areas Goals, yielding conclusions 
different from those drawn by Zorn and Berkovec with regard to bias 
in the HMDA data. In addition, as noted in Appendix D, other 
research has concluded that a portion of lower-income loan 
originations are not even reported to HMDA. Thus it is not clear 
that more recent and complete data would support the Zorn and 
Berkovec findings.

e. Other Technical Comments Related to GSE Performance in Single-Family 
Owner Market

    MSA-Level Analysis. In its comments, Fannie Mae raised several 
concerns about HUD's comparisons between Fannie Mae and the primary 
market at the metropolitan statistical area (MSA) level (see Table 
A.5 in this appendix). Essentially, Fannie Mae questioned the 
relevance of any analysis at the local level, given that the housing 
goals are national-level goals. HUD believes that its metropolitan-
area analyses support and clarify the national analyses on GSE 
performance. While official goal performance is measured only at the 
national level, HUD believes that analyses of, for example, the 
numbers of MSAs where Fannie Mae and Freddie Mac lead or lag the 
local market increases public understanding of the GSEs' 
performance. For example, if the national aggregate data showed that 
one GSE lagged the market in funding loans in underserved areas, it 
would be of interest to the public to determine if this reflected 
particularly poor performance in a few large MSAs or if it reflected 
shortfalls in many MSAs. In this case, an analysis of individual MSA 
data would increase public understanding of that GSE's performance.
    Missing Data. Both GSEs mentioned the increasing problem of 
missing information in HMDA data and in their own data bases--
particularly with regard to borrower race/ethnicity. HUD agrees that 
treatment of missing data is an important issue when measuring GSE 
performance and developing estimates of the size of the affordable 
market. Both Appendices A and D use several techniques for 
situations where data are limited or missing. HUD's treatment of 
missing data reflects a consistent commitment to fair and reasonable 
analyses, and is designed to permit ``apples-to-apples'' comparisons 
between the GSEs and the market to the extent possible. When 
calculating portfolio percentages for different sectors of the 
mortgage market, HUD followed its usual procedure of excluding loans 
with missing data. In certain analyses involving market shares, HUD 
used a variety of techniques such as reallocating missing data, 
making adjustments for undercoverage by HMDA data, or using data 
from other

[[Page 65092]]

sources to estimate the absolute number of mortgage originations. In 
general, HUD believes that methods for addressing missing data are 
reasonable and appropriate.
    Lender-Purchased Loans. When analyzing HMDA data, Fannie Mae 
included loans purchased by lenders, as well as loans originated by 
lenders, in its market definition. HUD included only HMDA-reported 
mortgage originations in its market definition--mortgages purchased 
by lenders were not included in HUD's market data. To do so would 
involve double counting loan originations in the HMDA data.
    Prior-Year/Current-Year Analysis. Fannie Mae raised a number of 
concerns about HUD's separation of its purchases into ``prior-year'' 
loans and ``current-year'' loans. Section E.2 of this appendix 
discusses this issue in some detail. Much of HUD's analysis is 
conducted along the lines that Fannie Mae recommends--considering 
each GSE's total purchases (of both prior-year mortgages and 
current-year mortgages) in a single calendar year. For example, see 
the discussion of the GSEs' past performance in Section E of this 
appendix and the data in Tables A.3 and A.4. But HUD believes the 
GSEs' performance should also be analyzed by focusing on the total 
number of mortgages from a particular origination year that the GSEs 
have purchased to date. Comparing the GSEs' current-year purchases, 
including prior-year originations, with newly-originated mortgages 
would result in somewhat of an ``apples-to-oranges'' comparison. 
Hence, to conduct more of an ``apples-to-apples'' comparison between 
the GSEs and the market, it is necessary to restrict the analysis to 
GSE loan acquisitions originated in a particular year (see Tables 
A.7a and A.7b). HUD recognizes some of the problems that result from 
analyses that focus on a single origination year. However, as 
indicated by the variety of analyses provided in Appendix A, HUD 
believes that both frameworks are useful for understanding the GSEs' 
role in the affordable lending market.

f. Leading the Market--The Qualitative Dimension

    The GSEs commented that they make a sizable contribution toward 
serving the housing needs of a wide range of American families 
through their innovative outreach and the overall leadership they 
provide to the affordable lending market. This ``qualitative'' 
dimension of market leadership comes from their normal operations in 
the market. Each GSE gave numerous examples of their market 
leadership, similar to the discussion that HUD provides in Section G 
of this appendix. Fannie Mae noted its Trillion Dollar Commitment, 
its programs with minority-and women-owned lenders, its initiative 
with Community Development Financial Institutions, and its numerous 
initiatives in the technology area. Freddie Mac noted similar 
program initiatives and outreach efforts, and stated that it has 
been a ``leader in removing historical barriers to mortgage credit'' 
and that a recent HUD-commission study commended both Freddie Mac 
and Fannie Mae for their leadership in the liberalization of 
mortgage underwriting standards.
    HUD understands the important role that the GSEs play in the 
market and applauds their efforts to re-examine their underwriting 
standards and to reach out to traditionally underserved borrowers 
and neighborhoods. This perspective is reflected in Section G of 
this appendix, which discusses qualitative dimensions of the GSEs' 
ability to lead the industry. HUD concludes that due to their 
dominant role in the market, their ability to influence the types of 
loans that lenders will originate, their utilization of state-of-
the-art technology, and their financial strength, the GSEs have the 
ability to lead the market in affordable lending and to reach out to 
those markets that have traditionally not received the benefits of 
an active secondary market.

g. Linking Housing Needs to GSEs

    Fannie Mae commented that HUD's analysis of housing needs in 
Appendix A needed to more carefully identify the appropriate roles 
for the public sector and the GSEs. Similar to its comments on HUD's 
1995 rule, Fannie Mae expressed concern that HUD did not distinguish 
between general housing needs of low- and moderate-income households 
and those needs that the GSEs can reasonably be expected to address. 
In this appendix, HUD presents an analysis of general housing needs 
to comply with FHEFSSA, which requires the Secretary to consider 
such needs when establishing the housing goals. HUD's examination of 
national housing needs does not suggest that the GSEs can or should 
meet all of those needs. Rather, the analysis is intended to provide 
background on the evolution and current state of the housing markets 
for low- and moderate-income households. HUD recognizes that the 
GSEs alone can not mitigate some of the more extreme problems 
identified in this analysis.
    However, with more focused effort, the GSEs can assist in 
addressing several problems discussed in this appendix with regard 
to single-family and multifamily housing. On the single-family side, 
the GSEs can develop secondary market programs for ``untapped'' 
markets such as 2-4 unit rental properties and properties needing 
rehabilitation in the nation's inner cities. The GSEs can increase 
their support of more customized mortgage products and underwriting, 
with greater outreach to those families who have not been served 
with traditional products, underwriting, and marketing. Particularly 
important in this regard, the GSEs can ensure that their automated 
underwriting systems recognize the special circumstances of lower-
income and minority borrowers. As discussed in Section 3.d of this 
appendix, HUD and others are concerned about potential negative 
effects of mortgage scoring on industry efforts to reach out to 
lower-income and minority families.
    On the multifamily side, with new product development and 
partnerships, the GSEs can more fully address the credit needs of 
the current market for affordable rental housing. This appendix 
cities several areas where the GSEs can help. One segment that would 
benefit from a more active secondary market is small multifamily 
properties--an important part of the rental housing market that is 
currently not being adequately served by the GSEs. The GSEs can work 
to improve overall efficiency and stability in this market by 
developing new products and promoting increased standardization and 
streamlined procedures.
    The GSEs have been immensely successful in the financing of 
traditional single-family housing. HUD recognizes that ``untapped'' 
markets will present some difficulties and challenges for the GSEs. 
But by helping develop a secondary market in these areas, the GSEs 
will bring increased liquidity, added stability, and ultimately 
lower interest rates and rents for lower-income families in these 
segments of the market.

h. Barriers to Higher GSE Performance on the Housing Goals

    Fannie Mae raised concerns with respect to the interplay of the 
housing goals and the risk-based capital standard proposed by OFHEO. 
Fannie Mae stated that ``the risk-based capital proposal represents 
another potentially significant barrier to meeting the goals that 
was not analyzed by the Department.'' OFHEO previously addressed 
this question in their notice of proposed rulemaking, dated April 
13, 1999, concluding that ``the risk-based capital standard will not 
affect the Enterprises' ability to purchase affordable housing 
loans.'' 3 In part, this conclusion was based on the 
finding that in 1996 and 1997, Freddie Mac would have enjoyed 
capital surpluses under OFHEO's proposed rule, despite increased 
purchases of loans meeting the housing goals. OFHEO concluded that 
even in more adverse economic environments, ``the capital cost of 
single family loans meeting the Enterprises' affordable housing 
goals should not be materially different, on average, from the cost 
of other loans.''
    Of the various issues mentioned by Fannie Mae in relation to 
OFHEO's proposed regulation, implications of the rule for high-LTV 
and multifamily lending are of the greatest relevance with regard to 
affordable lending and the GSEs' housing goals.
    High-LTV Lending. Fannie Mae stated concerns regarding the 
impacts of the proposed OFHEO regulation on high-LTV lending:

  The risk-based capital regulation as proposed imposes 
disproportionately high capital requirements on high-LTV loans. 
These requirements will impair our ability to serve those borrowers 
with limited resources. High-LTV lending is critically important to 
our affordable housing initiatives and outreach to first-time 
homebuyers.4

    It is not apparent that OFHEO's proposed rulemaking would impose 
``disproportionate'' capital requirements on high-LTV loans. Because 
high-LTV loans typically have higher default rates, it is reasonable 
to require the GSEs to hold more capital against high-LTV loans than 
against low-LTV loans, other things being equal.
    If Fannie Mae's view is that the proposed OFHEO regulation 
requires the GSEs to hold more capital against high-LTV loans than 
is the case for other financial institutions, their comments 
submitted in response to HUD's proposed housing goals rule do not 
contain any material documenting such a claim.

[[Page 65093]]

However, it is noteworthy that the GSEs enjoy benefits not conferred 
on other financial institutions (e.g., exemption from state and 
local taxes and exemption from securities registration). There is no 
evidence that Congress intended for the GSE risk-based capital 
requirements to be strictly comparable to capital standards for 
other regulated financial institutions.
    OFHEO's proposed rule would require the GSEs to hold more 
capital against high-LTV loans, assuming the GSEs charge the same 
guarantee against such loans as they do against low-LTV loans. In 
practice, however, the GSEs implicitly charge higher guarantee fees 
on high-LTV loans, mitigating the need for additional capital beyond 
what is added through the guarantee fee. In its discussion of this 
issue, OFHEO concluded that ``Both Enterprises use internal capital 
models that reflect the higher risk of high LTV loans and already 
may incorporate higher capital costs into the implicit fees charged 
for these loans.'' 5
    In addition, OFHEO observed that multifamily loans, which 
predominantly benefit low-and moderate-income households, act as a 
hedge against high-LTV loans in a down-rate environment ``so that 
higher costs on high LTV single family loans are substantially 
offset by lower costs on multifamily loans,'' reducing the amount of 
capital that the GSEs would otherwise be required to hold against 
high-LTV loans.
    Multifamily Risk-Sharing. Fannie Mae contends that, under the 
provisions of OFHEO's proposed rule, its Delegated Underwriting and 
Servicing (DUS) multifamily program ``will be impaired because of 
the onerous ``haircuts'' specified in the proposed capital 
regulation.'' The ``haircuts'' mentioned by Fannie Mae refer to 
adjustments for counterparty risk proposed by OFHEO under risk-
sharing provisions such as those governing the DUS program.
    Because of the importance of counterparty risk to GSE safety and 
soundness, it is certainly reasonable and necessary for OFHEO to 
take such risk into consideration in formulating its risk-based 
capital regulation for the GSEs. HUD notes that OFHEO received 
extensive comments from the GSEs and others on this issue in 
response to its proposed rule. Because the OFHEO capital standard is 
presently at the proposed rule stage, and not a final rule, it would 
be premature and inappropriate for HUD to speculate at this time on 
the possible implications of OFHEO's capital standards on GSE 
multifamily performance. The multifamily market and the GSEs' 
capabilities within it will continue to evolve during and after the 
time period when OFHEO revises and finalizes its proposed capital 
regulation in response to comments. Any implications of the OFHEO 
capital standards for GSE activities related to multifamily 
mortgages or affordable housing will merit consideration in future 
rounds of HUD's GSE rulemaking.

4. 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) and is 
useful for gauging the reasonableness of specific levels of the Low- 
and Moderate-Income Housing Goal. In addition, the severe housing 
problems faced by lower-income families are discussed.
    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. 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. The consideration of the factors in this appendix has 
led the Secretary to the following conclusions:
     Despite the record national homeownership rate of 66.8 
percent in 1999, much lower rates prevailed for minorities, 
especially for African-American households (46.7 percent) and 
Hispanics (45.5 percent), and these lower rates are only partly 
accounted for by differences in income, age, and other socioeconomic 
factors.
     Pervasive and widespread disparities in mortgage 
lending continued across the nation in 1998, when the loan denial 
rate was 10.2 percent for white mortgage applicants, but 23.9 
percent for African Americans and 18.9 percent for 
Hispanics.6
     Despite strong economic growth, low unemployment, the 
lowest mortgage rates in 1998-99 in 25 years, and relatively stable 
home prices, there is clear and compelling evidence of deep and 
persistent housing problems for Americans with the lowest incomes. 
The number of very-low-income American households with ``worst 
case'' housing needs is at an all-time high--5.4 
million.7
     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 barriers that many immigrants and 
minorities face. In addition, market segments such as single-family 
rental properties, small multifamily properties, manufactured 
housing, and older inner city properties would benefit from the 
additional financing and pricing efficiencies of a more active 
secondary mortgage market.
     The Low- and Moderate-Income Housing Goals for both 
GSEs were 40 percent in 1996 and 42 percent in 1997-1999. Fannie Mae 
surpassed these goals, with a performance of 45.6 percent in 1996, 
45.7 percent in 1997, 44.1 percent in 1998, and 45.9 percent in 
1999. Freddie Mac's performance of 41.1 percent in 1996, 42.6 
percent in 1997 and 42.9 percent in 1998 narrowly exceeded these 
goals, but Freddie Mac's performance jumped sharply in 1999 to 46.1 
percent, exceeding Fannie Mae's performance for the first time, by a 
narrow margin.
     Several studies have shown that both Fannie Mae and 
Freddie Mac lag behind depository institutions and the overall 
conventional conforming market in providing affordable home loans to 
lower-income borrowers and underserved neighborhoods. Though 1998 
Fannie Mae made efforts to improve its performance, while Freddie 
Mac made less improvement, and therefore fell behind Fannie Mae, 
depositories, and the overall market in serving lower-income and 
minority families and their neighborhoods. This indicated that there 
was room for both GSEs (but particularly Freddie Mac) to improve 
their funding of single-family home mortgages for lower-income 
families and underserved communities. Data on the performance of 
depositories and the primary market is not yet available for 1999, 
thus it is not possible to determine if the GSEs continued to lag 
these sectors of the market last year. But, based on the data 
provided by the GSEs to the Department, Freddie Mac's single-family 
low- and moderate-income performance in 1999 exceeded Fannie Mae's 
performance. It remains to be seen whether this represents a new 
trend, or a temporary reversal of the pattern for the 1996-98 
period.
     The GSEs' presence in the goal-qualifying market is 
significantly less than their presence in the overall mortgage 
market. Specifically, HUD estimates that they accounted for 40 
percent of all owner-occupied and rental units financed in the 
primary market in 1997, but only 32 percent of low- and moderate-
income units financed. Their role was even lower for low-and 
moderate-income rental properties, where they accounted for 26 
percent of low- and moderate-income multifamily units financed and 
only 14 percent of low- and moderate-income single-family rental 
units financed. These general patterns were also evident in 1998, a 
heavy refinance year, except that the GSEs had a higher share of the 
single-family owner market.
     Other issues have also been raised about the GSEs' 
affordable lending performance. A large percentage of the lower-
income loans purchased by the enterprises have relatively high down 
payments, which raises questions about whether the GSEs are 
adequately meeting the mortgage credit needs of lower-income 
families who do not have sufficient cash to make a high down 
payment. Also, while single-family rental properties are an 
important source of low- and moderate-income rental housing, they 
represent only a small portion of the GSEs' business.
     Freddie Mac has re-entered the multifamily market, 
after withdrawing for a time in the early 1990s. Thus, concerns 
regarding Freddie Mac's multifamily capabilities no longer constrain 
their performance with regard to the Low- and Moderate-Income 
Housing Goal and the Special Affordable Housing Goal to the same 
degree that prevailed at the time the Department issued its 1995 GSE 
regulations. However, Freddie Mac's multifamily presence remains 
proportionately lower than that of Fannie Mae. For example, units in

[[Page 65094]]

multifamily properties accounted for 7.3 percent of Freddie Mac's 
mortgage purchases during 1994-99, compared with 11.8 percent for 
Fannie Mae. Because a relatively large proportion of multifamily 
units qualify for the Low- and Moderate-Income Housing Goal and the 
Special Affordable Housing Goal, through 1998 Freddie Mac's lower 
multifamily presence was a major factor contributing to its weaker 
overall performance on these two housing goals relative to Fannie 
Mae. But in 1999, multifamily units accounted for 8.2 percent of 
total units financed by Freddie Mac and 9.5 percent of total units 
financed by Fannie Mae, the narrowest gap of the 1994-99 period.
     The overall presence of both GSEs in the multifamily 
mortgage market falls short of their involvement in the single-
family market. Specifically, the GSEs' purchases of 1997 
originations accounted for 50 percent of the owner market, but only 
24 percent of the multifamily market. Further expansion of the 
presence of both GSEs in the multifamily market is needed in order 
for them to make significant progress in closing the gaps between 
the affordability of their mortgage purchases and that of the 
overall conventional market.
     The GSEs have proceeded cautiously in expanding their 
multifamily purchases during the 1990s. Fannie Mae's multifamily 
lending has been described by Standard & Poor's as ``extremely 
conservative,'' and Freddie Mac has not experienced a single default 
on the multifamily mortgages it has purchased since 
1993.8 By the end of 1999, both GSEs' multifamily 
performance had improved to the point where multifamily delinquency 
rates were lower than those for single-family loans.9
     Because of the advantages conferred by Government 
sponsorship, the GSEs are in a unique position to provide leadership 
in addressing the excessive cost and difficulty in obtaining 
mortgage financing for underserved segments of the multifamily 
market, including small properties with 5-50 units and properties in 
need of rehabilitation.

B. Factor 1: National Housing Needs

    This section reviews the general housing needs of low- and 
moderate-income families that exist today and are expected to 
continue in the near future. In so doing, the section focuses on the 
affordability problems of lower- income families and on racial 
disparities in homeownership and mortgage lending. It also notes 
some special problems, such as the need to rehabilitate our older 
urban housing stock.

1. Homeownership Gaps

    Despite a record national homeownership rate, 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 at an all-time high of 67.1 
percent in the first quarter of 2000, the rate for minority 
households was lower. The homeownership rate for African-American 
households was 47.4 percent. Similarly, just 45.7 percent of 
Hispanic households owned a home.
    Importance of Homeownership. Homeownership is one of the most 
common forms of property ownership as well as savings.10 
Historically, home equity has been the largest source of wealth for 
most Americans. Only recently has stock equity exceeded home equity 
as a share of total household wealth. Even with stocks appreciating 
faster than home prices over the past decade, still 59 percent of 
all homeowners in 1998 held more than half of their net wealth in 
the form of home equity. Among low-income homeowners (household 
income less than $20,000), half held more than 70 percent of their 
wealth in home equity in 1995.11 Median net wealth for 
renters was less than four percent of the median net wealth for 
homeowners in 1998. For low-income households, renter median net 
wealth is less than two percent of homeowner median net 
wealth.12 Thus a homeownership gap translates directly 
into a wealth gap.
    Homeownership promotes social and community stability by 
increasing the number of stakeholders and reducing disparities in 
the distributions of wealth and income. There is growing evidence 
that planning for and meeting the demands of homeownership may 
reinforce the qualities of responsibility and self-reliance. White 
and Green 13 provide empirical support for the 
association of homeownership with a more responsible, self-reliant 
citizenry. Both private and public benefits are increased to the 
extent that developing and reinforcing these qualities improve 
prospects for individual economic opportunities.
    Barriers to Homeownership. 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, 
lower-income, and minority families who were closed out of the 
housing market during the 1980s re-entered the housing market during 
the last decade. However, many households still lack the financial 
resources and earning power to take advantage of today's homebuying 
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. Fully 45 percent of the nation's 
population between the ages of 25 and 34 have no advanced education 
and are therefore at risk of being unable to afford 
homeownership.14 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.
    In addition to low income, high debts are a primary reason 
households cannot afford to purchase a home. According to a 1993 
Census Bureau report, nearly 53 percent of renter families have both 
insufficient income and excessive debt problems that may cause 
difficulty in financing a home purchase.15 High debt-to-
income ratios frequently make potential borrowers ineligible for 
mortgages based on the underwriting criteria established in the 
conventional mortgage market.
    An additional barrier to homeownership is the fear and 
uncertainty about the buying process and the risks of ownership. 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.16 Also, many feared the obligations of ownership, 
because of concerns about the risk of future deterioration of the 
house or the neighborhood.
    Finally, discrimination in mortgage lending continues to be a 
barrier to homeownership. Disparities in treatment between borrowers 
of different races and neighborhoods of different racial makeup have 
been well documented. These disparities are discussed in the next 
section.

2. Disparities in Mortgage Financing

    Disparities Between Borrowers of Different Races. Research based 
on Home Mortgage Disclosure Act (HMDA) data suggests pervasive and 
widespread disparities in mortgage lending across the Nation. For 
1998, the denial rate for white mortgage applicants was 10.2 
percent, while 23.9 percent of African-American and 18.9 percent of 
Hispanic applicants were denied. Even after controlling for income, 
the African-American denial rate was approximately twice that of 
white applicants. A major study by researchers at the Federal 
Reserve Bank of Boston found that mortgage denial rates remained 
substantially higher for minorities in 1991-93, even after 
controlling for indicators of credit risk.17 African-
American and Hispanic applicants in Boston with the same borrower 
and property characteristics as white applicants had a 17 percent 
denial rate, compared with the 11 percent denial rate experienced by 
whites. A subsequent study conducted at the Federal Reserve Bank of 
Chicago reported similar findings.18
    Several possible explanations for these lending disparities have 
been suggested. The studies by the Boston and Chicago Federal 
Reserve Banks found that racial disparities cannot be explained by 
reported differences in creditworthiness. 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

[[Page 65095]]

than devote effort to distinguishing the creditworthiness of the 
individual applicant.19 This violates the Fair Housing 
Act.
    Underwriting Rigidities. 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. Over the past few 
years, lenders, private mortgage insurers, and the GSEs have 
adjusted their underwriting guidelines to take into account these 
special circumstances of lower-income families. Many of the changes 
recently undertaken by the industry to expand homeownership have 
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 degree the reduced rigidity in industry standards 
will benefit borrowers who have been adversely impacted by the 
traditional guidelines. 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. Thus 
lower-income and minority loan applicants, who often have lower 
credit scores than other applicants, may be dependent on the 
willingness of lenders to take the time to look beyond such credit 
scores and consider any appropriate ``mitigating factors,'' such as 
the timely payment of their bills, in the underwriting process. For 
example, there is a concern in the industry that a ``FICO'' score 
less than 620 means an automatic rejection of a loan application 
without further consideration of any such factors.20 This 
could disproportionately affect minority applicants. More 
information on the distribution of credit scores and on the effects 
of implementing automated underwriting systems is 
needed.21
    Disparities Between Neighborhoods. Mortgage credit also appears 
to be less accessible in low-income and high-minority neighborhoods. 
As discussed in Appendix B, 1998 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 (19.4 percent 
versus 10.3 percent). Numerous studies have found that mortgage 
denial rates are higher in low-income census tracts, even accounting 
for other loan and borrower characteristics.22 These 
geographic 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. Geographic 
disparities in mortgage lending and the issue of mortgage redlining 
are discussed further in Appendix B.

3. Affordability Problems and Worst Case Housing Needs

    The severe 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 report analyzes data from the 1997 
AHS and focuses on the housing problems faced by low-income renters, 
but some data is also presented on families living in owner-occupied 
housing. In introducing the most recent study, Secretary Cuomo noted 
that it found that ``despite the booming economy, worst case housing 
needs continue to increase'' and such needs ``have now reached an 
all-time high of million households.'' 23
    The ``Worst Cases'' report measures three types of problems 
faced by homeowners and renters:
     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'');
     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
     Crowded housing, where there is more than one person 
per room in a residence.
    The study reveals that in 1997, 5.4 million households had 
``worst case'' housing needs, defined as housing costs greater than 
50 percent of household income or severely inadequate housing among 
unassisted households.

a. Problems Faced by Owners

    Of the 65.5 million owner households in 1997, 5.5 million (8.5 
percent) confronted a severe cost burden and another 8.3 million 
(12.7 percent) faced a moderate cost burden. There were 725,000 
households with severe physical problems and 916,000 which were 
overcrowded. The report found that 25.4 percent of American 
homeowners faced at least one severe or moderate problem.
    Not surprisingly, problems were most common among very low-
income owners.24 More than a third of these households 
faced a severe cost burden, and an additional 23 percent faced a 
moderate cost burden. And 7 percent of these families lived in 
severely or moderately inadequate housing, while 2 percent faced 
overcrowding. Only 38 percent of very low-income owners reported no 
problems.
    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 grown--
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 1997. 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 1995.25 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.26 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 1997.

b. Problems Faced by Renters

    Problems of all three types listed above are more common among 
renters than among homeowners. In 1997 there were 6.7 million renter 
households (20 percent of all renters) who paid more than 50 percent 
of their income for rent.27 Another 6.8 million faced a 
moderate rent burden, thus in total 40 percent of renters paid more 
than 30 percent of their income for rent.
    Among very low-income renters, 72 percent faced an affordability 
problem, including 44 percent who paid more than half of their 
income in rent. More than one-third 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 42 percent in 1997.
    The share of families living in inadequate housing in 1997 was 
higher for renters (12 percent) than for owners (4 percent), as was 
the share living in overcrowded housing (6 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. But in 1997 there were also 
sharp increases in the inadequate and crowded shares of rental 
housing.
    Other problems faced by renters discussed in the ``Worst Cases'' 
report include the loss between 1991 and 1997 of 370,000 rental 
units affordable to very low-income families, the increase in 
``worst case needs'' among working families between 1991 and 1997, 
and the shortage of units affordable to very low-income households 
(especially in the West).

4. 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. This section presents a brief discussion of three 
such areas and the roles that the GSEs play or might play in 
addressing the needs in these areas. Other needs are discussed 
throughout these appendices.

a. Single-family Rental Housing

    The 1996 Property Owners and Managers Survey reported that 51 
percent of all rental

[[Page 65096]]

housing units are located in ``multifamily'' properties--i.e, 
properties that contain 5 or more rental units. The remaining 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, 
such as the duplexes in Baltimore and the triple-deckers in Boston. 
A number of these single-family rental properties are in need of 
financing for rehabilitation, discussed in the next subsection.
    Single-family rental units play an especially important role in 
lower-income housing. The 1997 AHS found that 59 percent of such 
units were affordable to very low-income families--exceeding the 
corresponding share of 53 percent for multifamily units. These units 
also play a significant role in the GSEs' performance on the housing 
goals, since 30 percent of the single-family rental units financed 
by the GSEs in 1999 were 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. In 
1999 the GSEs purchased $26 billion in mortgages for such 
properties, but this represented 5 percent of the total dollar 
volume of each enterprise's 1999 business and 8 percent of total 
single-family units financed by each GSE. With regard to their 
market share, HUD estimates that the GSEs have financed only about 
19 percent of all single-family rental units that received mortgages 
in 1998, well below the GSEs' estimated market share of 68 percent 
for single-family owner properties.
    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.28

b. Rehabilitation Problems of Older Areas

    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.
    The ability of the nation to maintain the quality and 
availability of the existing affordable housing stock and to 
stabilize the neighborhoods where it is found depends on an adequate 
supply of credit to rehabilitate and repair older units. 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.29 However, extra effort is 
required, due to the complexities of rehabilitation financing, as 
there is still a need to do more.

c. Small Multifamily Properties

    There is evidence that small multifamily properties with 5-50 
units have been adversely affected by differentials in the cost of 
mortgage financing relative to larger properties.30 While 
mortgage loans can generally be obtained for most properties, the 
financing that is available is relatively expensive, with interest 
rates as much as 150 basis points higher than those on standard 
multifamily loans. Loan products are characterized by shorter terms 
and adjustable interest rates. Borrowers typically incur costs for 
origination and placement fees, environmental reviews, architectural 
certifications (on new construction or substantial rehabilitation 
projects), inspections, attorney opinions and certifications, credit 
reviews, appraisals, and market surveys.31 Because of a 
large fixed element, these costs are usually not scaled according to 
the mortgage loan amount or number of dwelling units in a property 
and consequently are often prohibitively high on smaller projects.

d. Other Needs

    Further discussions of other housing needs and mortgage market 
problems are provided in the following sections on economic, 
housing, and demographic conditions. In the single-family area, for 
example, an important trend has been the growth of the subprime 
market and the GSEs' participation in the A-minus portion of that 
market. Manufactured housing finance and rural housing finance are 
areas that could be served more efficiently with an enhanced 
secondary market presence. In the multifamily area, properties in 
need of rehabilitation represent a market segment where financing 
has sometimes been difficult. Other housing needs and mortgage 
market problems are also discussed.

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, 
homebuyer characteristics, and the state of affordable lending. 
Section D follows with a discussion of the economic, housing, and 
demographic conditions affecting the multifamily mortgage market.

1. Recent Trends in the Housing Market

    Solid economic growth, low interest rates, price stability, and 
an unemployment rate of 4.2 percent, the lowest rate since 1969, 
combined to make 1999 a very strong year for the housing market. The 
employment-population ratio reached a record 64.3 percent last year, 
and a broad measure of labor market distress, combining the number 
of unemployed and the duration of unemployment, was down by 54 
percent from its 1992 peak.32 Rising real wages, a strong 
stock market, and higher home prices all contributed to a 
continuation of the rise in net household worth, contributing to the 
strong demand for 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. Major gains in 
ownership have occurred over the last few years, with the 
homeownership rate reaching a record level of 66.8 percent in 1999, 
when the number of households owning their own home was 7 million 
greater than in 1994, an unprecedented five-year increase.
    Gains in homeownership have been widespread in over the last six 
years.33 As a result, the homeownership rate rose from:
     42.0 percent in 1993 to 46.7 percent in 1999 for 
African American households,
     39.4 percent in 1993 to 45.5 percent in 1999 for 
Hispanic households,
     73.7 percent in 1993 to 77.6 percent in 1999 for 
married couples with children,
     65.1 percent in 1993 to 67.2 percent in 1999 for 
household heads aged 35-44, and
     48.9 percent in 1993 to 50.4 percent in 1999 for 
central city residents.
    However, as these figures demonstrate, sizable gaps in 
homeownership remain.
    Sales of New and Existing Homes.34 New home sales 
rose at a rate of 7.5 percent per year between 1991 and 1999, and 
exceeded the previous record level (set in 1998) by 2 percent in 
1999. The market for new homes has been strong throughout the 
nation, with record sales in the South and Midwest during 1999. New 
home sales in the Northeast and West, while strong, are running 
below the peak levels attained during their strong job markets of 
the mid-1980s and late-1970s, respectively.
    The National Association of Realtors reported that 5.2 million 
existing homes were sold in 1999, overturning the old record set in 
1998 by 5 percent. Combined new and existing home sales also set a 
record of 6.2 million last year. Since existing homes account for 
more than 80 percent of the total market and sales of existing homes 
are strong throughout the country, combined sales reach record 
levels in three of the four major regions of the nation and came 
within 97 percent of the record in the Northeast.
    One of the strongest sectors of the housing market in recent 
years has been shipments of manufactured homes, which more than 
doubled between 1991 and 1996, and essentially leveled off at the 
1996 record during 1997-99. Two-thirds of manufactured home 
placements were in the South, where they comprised more than one-
third of total new homes sold in 1999.
    Economy/Housing Market Prospects. As noted above, the U.S. 
economy is coming off

[[Page 65097]]

several years of economic expansion, accompanied by low interest 
rates and high housing affordability. In fact, 1999 was a record 
year for housing sales. The remainder of this subsection discusses 
the future prospects for the housing market.
    According to Standard & Poor's DRI, the housing market is 
slowing down from the record breaking pace of over five million 
single-family existing homes sold during 1999.35 Sales of 
existing single-family homes are on a pace of 4.5 million units for 
2000. Between 2001 and 2004, existing single-family home sales are 
expected to average 4.2 million units. Housing starts are expected 
to average 1.5 million units over the same period. Housing should 
remain affordable, as indicated by out-of-pocket costs as a share of 
disposable income, which are expected to continue their downward 
trend through 2004, dipping below 24 percent by 2003. According to 
Standard & Poor's DRI, the 30-year fixed rate mortgage rate is 
expected to average 8.4 percent in 2000, and then trend down to 7.7 
percent by 2004.
    The Congressional Budget Office (CBO) 36 projects 
that real Gross Domestic Product will grow at an average rate of 2.7 
percent from 2001 through 2005, down from the expected 4.9 percent 
growth rate during 2000. The ten-year Treasury rate is projected to 
average 6.0 percent between 2001 and 2005. Inflation, as measured by 
the Consumer Price Index (CPI) is projected to remain modest during 
the same period, averaging 2.7 percent. The unemployment rate is 
expected to remain low over the next four years, averaging 4.3 
percent.
    Certain risks exist, however, which could undermine the 
wellbeing of the economy. The probability of a recession still 
exists for the next couple of years. Under a pessimistic scenario 
(10 percent probability), Standard & Poor's DRI predicts that if a 
stock-market correction were to occur toward the end of 2000, 
housing starts could fall to 1.2 million units. With relatively low 
inflation, DRI anticipates that the Federal Reserve would respond 
quickly by lower interest rates. This would revive the housing 
market, although the recovery would be slow, with starts not 
returning to pre-recession levels until late 2004.37 An 
alternative scenario has a recession arriving in 2002, resulting 
from a Federal Reserve overreaction to higher inflation and a stock 
market correction in late 2001 or early 2002 (which DRI predicts 
with a probability of 35 percent). Under this scenario, housing 
starts would fall to almost one million units. As a result of lower 
interest rates, the housing market would rebound strongly, with 
starts reaching near-record levels by the end of 2004.38
    In addition to DRI and CBO, the Mortgage Bankers Association 
predicts that for 2000/2001 housing starts will reach 1.6/1.5 
million units for 2000 and 2001 and the 30-year fixed rate mortgage 
rate will average 8.5/9.0 percent.39 Fannie Mae predicts 
that the Federal Reserve will successfully engineer a soft landing, 
with real growth of the economy slowing to a two to three percent 
pace in 2001. As a result, mortgage originations should decline to 
$967 billion, 27 percent less than the 1998 record 
level.40

2. Underlying Demographic Conditions

    Over the next 20 years, the U.S. population is expected to grow 
by an average of 2.4 million per year. This will likely result in 
1.1 to 1.2 million new households per year, creating a continuing 
need for additional housing.41 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; ``trade-up buyers;'' non-
traditional and single households; and the growing income inequality 
between people with different levels of education.
    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 next decade due to the aging of the baby-boom 
population.42 However, growing demand from immigrants and 
non-traditional homebuyers will likely fill in the void. The Joint 
Center for Housing Studies recently projected that the share of the 
U.S. population accounted for by racial and ethnic minorities would 
increase from 25 percent to 30 percent by the year 
2010.43 The echo baby-boom (that is, children of the 
baby-boomers) will also add to housing demand later in the next 
decade. Finally, the growing income inequality between people with 
and without a post-secondary education will continue to affect the 
housing market.
    The Baby-Boom Effect. The demand for housing during the 1980s 
and 1990s was driven, in large part, by the coming of homebuying 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 homebuying 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.44
    As the youngest of the baby-boomers, those born in the 1960s, 
reached their peak homebuying 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.45
    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 is expected to 
lead to reduced housing demand during the next decade, though, as 
discussed below, other factors have 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 homebuying 
age later in the first decade of the new millennium, softening the 
blow somewhat.46
    Immigrant Homebuyers. Past, present, and future immigration will 
also help keep homeownership growth at a respectable level. During 
the 1980s, 6 million legal immigrants entered the United States, 
compared with 4.2 million during the 1970s and 3.2 million during 
the 1960s.47 As a result, the foreign-born population of 
the United States doubled from 9.6 million in 1970 to 19.8 million 
in 1990, and is expected to reach 31 million by 2010.48 
While immigrants tend to rent their first homes upon arriving in the 
United States, homeownership rates are substantially higher among 
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 67.4 percent for native-born households. For foreign-born 
naturalized citizens, the homeownership rate after six years was a 
remarkable 66.9 percent.49
    Immigration is projected to add even more new Americans in the 
1990s, which will help offset declines in the demand for housing 
caused by the aging of the baby-boom generation. While it is 
projected that immigrants will account for less than four percent of 
all households in 2010, without the increase in the number of 
immigrants, household growth would be 25 percent lower over the next 
15 years. As a result of the continued influx of immigrants and the 
aging of the domestic population, household growth over the next 
decade should remain at or near its current pace of 1.1-1.2 million 
new households per year, even though population growth is slowing. 
If this high rate of foreign immigration continues, it is possible 
that first-time homebuyers will make up as much as half of the home 
purchase market over the next several years.50
    Past and future immigration will lead to increasing racial and 
ethnic diversity, especially among the young adult 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.
    Trade-up Buyers. The fastest growing demographic group in the 
early part of the next millennium will be 45-to 65-year olds. This 
will translate into a strong demand for upscale housing and second 
homes. The greater equity resulting from recent increases in home 
prices should also lead to a larger role for ``trade-up buyers'' in 
the housing market during the next 10 to 15 years.
    Nontraditional and Single Homebuyers. While overall growth in 
new households has slowed down, nontraditional households have 
become more important in the homebuyer market. With later marriages 
and more divorces, single-person and single-parent households have 
increased rapidly. First-time buyers include a record number of 
never-married single households, although

[[Page 65098]]

their ownership rates still lag those of married couple households. 
According to the Chicago Title and Trust's Home Buyers Surveys, the 
share of first-time homebuyers who were never-married singles rose 
from 21 percent in 1991 to 37 percent in 1996, and to a record 43 
percent in 1997. However, in 1999 never-married singles fell to 30 
percent of first-time homebuyers.51 The shares for 
divorced/separated and widowed first-time homebuyers have stayed 
constant over the period, at eight percent and one percent, 
respectively.52 The National Association of Realtors 
reports that ``single individuals, unmarried couples and minorities 
are entering the market as first-time buyers in record numbers.'' 
53 With the increase in single person households, it is 
expected that there will be a greater need for apartments, 
condominiums and townhomes.
    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 20 percent. Single-parent households are 
also expected to decline as the baby-boom generation ages out of the 
childbearing years. For these reasons, nontraditional homebuyers may 
account for a smaller share of the housing market in the future.
    Growing Income Inequality. The Census Bureau recently reported 
that the top 5 percent of American households received 21.4 percent 
of aggregate household income in 1998, up sharply from 16.1 percent 
in 1977. The share accruing to the lowest 80 percent of households 
fell accordingly, from 56.5 percent in 1977 to 50.8 percent in 1998. 
The share of aggregate income accruing to households between the 
80th and 95th percentiles of the income distribution was virtually 
unchanged over this period.54
    The increase in income inequality over the past two decades has 
been especially significant between those with and those without 
post-secondary education. The Census Bureau reports that by 1997, 
the mean income of householders with a high school education (or 
less) was less than half that for householders with a bachelor's 
degree (or more). According to the Joint Center for Housing Studies, 
inflation-adjusted median earnings of men aged 25 to 34 with only a 
high-school education decreased by 14 percent between 1989 and 
1995.55 So, while homeownership is highly affordable, 
this cohort lacks 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.

3. Single-Family Owner Mortgage Market

    The mortgage market has undergone a great deal of growth and 
change over the past few years. Low interest rates, modest increases 
in home prices, and growth in real household income have increased 
the affordability of housing and resulted in a mortgage market boom. 
Total originations of single-family loans increased from $458 
billion in 1990 to $859 billion in 1997 and then jumped to a record 
$1.507 trillion during the heavy refinancing year of 1998, before 
declining to $1.287 billion in 1999, the second highest level 
recorded.56 There have also been many changes in the 
structure and operation of the mortgage market. Innovations in 
lending products, added flexibility in underwriting guidelines, the 
development of automated underwriting systems and the rise of the 
subprime market, have had impacts on both the overall market and 
affordable lending during the 1990s.
    The section starts with a review of trends in the market for 
mortgages on single-family owner-occupied housing. Next, trends in 
affordable lending, including new initiatives and changes to 
underwriting guidelines and the prospects for potential homebuyers 
are discussed. The section concludes with a summary of the activity 
of the GSEs relative to originations in the primary mortgage market.

a. Basic Trends in the Mortgage Market

    Interest Rate Trends. The high and volatile mortgage rates of 
the 1980s and early 1990s have given way to a period with much lower 
and more stable rates in the last six years. Interest rates on 
mortgages for new homes were above 12 percent as the 1980s began and 
quickly rose to more than 15 percent.57 After 1982, they 
drifted downward slowly to the 9 percent range in 1987-88, before 
rising back into double-digits in 1989-90. Rates then dropped by 
about one percentage point a year for three years, reaching a low of 
6.8 percent in October-November 1993 and averaging 7.2 percent for 
the year as a whole.
    Mortgage rates turned upward in 1994, peaking at 8.3 percent in 
early 1995, but fell to the 7.5 percent-7.9 percent range for most 
of 1996 and 1997. However, rates began another descent in late-1997 
and averaged 6.95 percent for 30-year fixed rate conventional 
mortgages during 1998, the lowest level since 1968, before rising to 
an average of 7.44 percent in 1999.58
    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 rates are high, because 
they carry lower rates than FRMs and because buyers may hope to 
refinance to a FRM when mortgage rates decline. Thus the Federal 
Housing Finance Board (FHFB) reports that the ARM share of the 
market jumped from 20 percent in the low-rate market of 1993 to 39 
percent when rates rose in 1994.59 The ARM share has 
since trended downward, falling to 22 percent in 1997 and a record 
low of 12 percent in 1998, before rising back to 22 percent in 1999.
    In 1997 the term-to-maturity was 30 years for 83 percent of 
conventional home purchase mortgages. Other maturities included 15 
years (11 percent of mortgages), 20 years (2 percent), and 25 years 
(1 percent). The average term was 27.5 years, up slightly from 26.9 
years in 1996, but within the narrow range of 25-28 years which has 
prevailed since 1975.
    One dimension of the mortgage market which has changed in recent 
years is the increased popularity of low- or no-point mortgages. 
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 1.0 percent in 1995-97. In 1998, 21 percent of all loans were 
no-point mortgages. These lower transactions costs have increased 
the propensity of homeowners to refinance their 
mortgages.60
    Another recent major change in the conventional mortgage market 
has been the proliferation of high loan-to-value ratio (LTV) 
mortgages. 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. 
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 
mortgages originated in 1994-97. As a result, the average LTV rose 
from 75 percent in 1989-91 to nearly 80 percent in 1994-
97.61
    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.
    Mortgage Originations: Refinance Mortgages. Mortgage rates 
affect the volume of both home purchase mortgages and mortgages used 
to refinance an existing mortgage. The effects of mortgage rates on 
the volume of home purchase mortgages are felt through their role in 
determining housing affordability, discussed in the next subsection. 
However, the largest impact of rate swings on single-family mortgage 
originations is reflected in the volume of refinancings.
    During 1992-93, homeowners responded to the lowest rates in 25 
years by refinancing existing mortgages. In 1989-90 interest rates 
exceeded 10 percent, and refinancings accounted for less than 25 
percent of total mortgage originations.62 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.
    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.63 Total single-family 
mortgage originations bottomed out at $639 billion in 1995, when the 
refinance share was only 15 percent. This meant that refinance 
volume declined by more than 80 percent in just two years.
    A second surge in refinancings began in late-1997, abated 
somewhat in early 1998, but regained momentum in June 1998. The 
refinance share rose above 30 percent in mid-1997, exceeded 40 
percent in late-1997, and peaked at 64 percent in January, before 
falling to 40 percent by May 1998. This share increased steadily 
over the June-September 1998 period, and averaged 50 percent for

[[Page 65099]]

1998. The refi boom ended abruptly in early 1999, as the share of 
loans for refinancings fell from 60 percent in the first quarter to 
27 percent in the second quarter and 22 percent in the third and 
fourth quarters. Total originations, driven by the volume of 
refinancings, amounted to $859 billion in 1997 and were $1.507 
trillion in 1998, nearly 50 percent higher than the previous record 
level of $1.02 trillion attained in 1993, before falling to $1.287 
trillion last year. Total refinance mortgage volume in 1998 was 
estimated to be nearly 10 times the level attained in 1995. The 
refinance wave from 1997 through early 1999 reflects 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 (including the GSEs), 
utilizing automated underwriting and mortgage origination systems, 
to handle this unprecedented volume expeditiously.
    Mortgage Originations: Home Purchase Mortgages. In 1972 the 
median price of existing homes in the United States was $27,000 and 
mortgage rates averaged 7.52 percent; thus with a 20 percent down 
payment, a family needed an income of $7,200 to qualify for a loan 
on a median-priced home. Actual median family income was $11,100, 
exceeding qualifying income by 55 percent. The National Association 
of Realtors (NAR) has developed a housing affordability index, 
calculated as the ratio of median income to qualifying income, which 
was 155 in 1972.
    By 1982 NAR's affordability index had plummeted to 70, 
reflecting a 154 percent increase in home prices and a doubling of 
mortgage rates over the decade. That is, qualifying income rose by 
nearly 400 percent, to $33,700, while median family income barely 
doubled, to $23,400. With so many families priced out of the market, 
single-family mortgage originations amounted to only $97 billion in 
1982.
    Declining interest rates and the moderation of inflation in home 
prices have led to a dramatic turnaround in housing affordability in 
the last decade and a half. Remarkably, qualifying income was 
$27,700 in 1993--$6,000 less than it had been in 1982. Median family 
income reached $37,000 in 1993, thus the NAR's housing affordability 
index reached 133. 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.64 
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.
    The high affordability of housing, low unemployment, and high 
consumer confidence meant that home purchase mortgages reached a 
record level in 1997. However, this record was surpassed in 1998, as 
a July 1998 survey by Fannie Mae found that ``every single 
previously cited barrier to homeownership--from not having enough 
money for a down payment, to not having sufficient information about 
how to buy a home, to the confidence one has in his job, to 
discrimination or social barriers--has collapsed to the lowest level 
recorded in the seven years Fannie Mae has sponsored its annual 
National Housing Survey.'' 65 Specifically, the Mortgage 
Bankers Association estimates that home purchase mortgages rose to 
about $754 billion in 1998, well above the previous record of $574 
billion established in 1997. The boom continued in 1999, with home 
purchase mortgage volume increasing further, to $824 billion.
    First-time Homebuyers. First-time homebuyers have been the 
driving force in the recovery of the nation's housing market over 
the past several years. First-time homebuyers 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 1992.66 Even though 
this cohort is smaller, first-time homebuyers increased their share 
of home sales. First-time buyers accounted for about 45 percent of 
home sales in 1999. Participation rates for first-time homebuyers so 
far this decade are all greater than or equal to 45 percent. This 
follows participation rates that averaged 40 percent in the 1980s, 
including a low of 36 percent in 1985. The highest first-time 
homebuyer participation rate was achieved in 1977, when it was 48 
percent.67
    The Chicago Title and Trust Company reports that the average 
first-time buyer in 1999 was 32 years old and spent 5 months looking 
at 12 homes before making a purchase decision. Most such buyers are 
married couples, but in 1999 29 percent had never been married, 9 
percent were divorced or separated, and 1 percent were widowed.
    First-time buyers paid an average of 34 percent of after-tax 
income, or $1,090 per month, on their mortgage payments in 1999, and 
saved for 2.2 years to accumulate a down payment. The National 
Association of Realtors reports that the median mortgage amount for 
first-time buyers was $104,000 in 1999, corresponding to an LTV of 
97 percent, compared with a median mortgage amount of $150,000 and 
an average LTV of 81 percent for repeat buyers.
    GSEs' Acquisitions as a Share of the Primary Single-Family 
Mortgage Market. The GSEs' single-family mortgage acquisitions have 
generally followed the volume of originations in the primary market 
for conventional mortgages, falling from 5.3 million mortgages in 
the record year of 1993 to 2.2 million mortgages in 1995, but 
rebounding to 2.9 million mortgages in 1996. In 1997, however, 
single-family originations were essentially unchanged, but the GSEs' 
acquisitions declined to 2.7 million mortgages.68 This 
pattern was reversed in 1998, when originations rose by 73 percent, 
but the GSEs' purchases jumped to 5.8 million mortgages. In 1999 the 
GSEs' acquired 4.8 million single-family mortgages, a decline of 17 
percent, which approximated the 15 percent decline in single-family 
originations.
    Reflecting these trends, the Office of Federal Housing 
Enterprise Oversight (OFHEO) estimates that the GSEs' share of total 
originations in the 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 market 
rebounded sharply in 1998-99, to 43-42 percent.
    Mortgage Market Prospects. The Mortgage Bankers Association 
(MBA) reports that mortgage originations in 1999 were $1.3 trillion. 
This followed the record-breaking year of 1998, with $1.5 trillion 
in mortgage originations. Refinancing of existing mortgages was down 
from 1998's 50 percent share of total mortgage originations to 34 
percent in 1999, still higher than an average year. Meanwhile, the 
ARM share in 1999 increased from 12 percent in 1998 to 22 percent of 
originations, reflecting the rise in overall interest rates. The MBA 
predicts that mortgage originations will amount to $962 billion and 
$912 billion, with refinancings representing 16 and 12 percent of 
originations, during 2000 and 2001, which is more in line with a 
normal pace. ARMs are expected to account for a larger share, 32 
percent in 2000 and 34 percent in 2001, of total mortgage 
originations.69 Fannie Mae projects that mortgage 
originations will fall to $967 billion for 2000, with 19 percent 
coming from refinancings, while 30 percent of originations will be 
in the form of ARMs.70

b. Affordable Lending in the Mortgage Market

    In the past few years, conventional lenders, private mortgage 
insurers and the GSEs have begun implementing changes to extend 
homeownership opportunities to lower-income and historically 
underserved households. The industry has started offering more 
customized 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. This section summarizes 
recent initiatives undertaken by the industry to expand affordable 
housing. The section also discusses the significant role FHA plays 
in making affordable housing available to historically underserved 
groups.
    Down Payments. GE Capital's 1989 Community Homebuyer Program 
first allowed homebuyers who completed a program of homeownership 
counseling to have higher than normal payment-to-income qualifying 
ratios, while providing less than the full 5-percent down payment 
from their own funds. Thus the program allowed borrowers to qualify 
for larger loans than would have been permitted under standard 
underwriting rules. Fannie Mae made this Community Homebuyer Program 
a part of its own offerings in 1990. Affordable Gold is a similar 
program introduced by Freddie Mac in 1992. Many of these programs 
allowed 2 percentage points of the 5-percent down payment to come 
from gifts from relatives or grants and unsecured loans from local 
governments or nonprofit organizations.

[[Page 65100]]

    In 1994, the industry (including lenders, private mortgage 
insurers and the GSEs) began offering mortgage products that 
required down payments of only 3 percent, plus points and closing 
costs. Other industry efforts to reduce borrowers' up front costs 
have 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.
    During 1998, Fannie Mae introduced its ``Flexible 97'' and 
Freddie Mac introduced its ``Alt 97'' low down payment lending 
programs. Under these programs borrowers are required to put down 
only 3 percent of the purchase price. The down payment, as well as 
closing costs, can 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. While these programs started 
out slowly, by November 1998 both GSEs' programs reached volumes of 
$200 million per month.
    In early 1999, Fannie Mae announced that it would introduce 
several changes to its mortgage insurance requirements. The planned 
result is to provide options for low downpayment borrowers to reduce 
their mortgage insurance costs. Franklin D. Raines, Fannie Mae 
chairman and chief executive officer stated, ``Now, thanks to our 
underwriting technology, our success in reducing credit losses, and 
innovative new arrangements with mortgage insurance companies, we 
can increase mortgage insurance options and pass the savings 
directly on to consumers.'' \71\
    Partnerships. 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's partnership offices in more 
than 40 central cities, serving to coordinate Fannie Mae's programs 
with local lenders and affordable housing groups, are an example of 
this initiative. Another example is the partnership Fannie Mae and 
the National Association for the Advancement of Colored People 
(NAACP) announced in January 1999.\72\ Under this partnership, 
Fannie Mae will provide funding for technical assistance to expand 
the NAACP's capacity to provide homeownership information and 
counseling. It will also invest in NAACP-affiliated affordable 
housing development efforts and explore structures to assist the 
organization in leveraging its assets to secure downpayment funds 
for eligible borrowers. Furthermore, Fannie Mae will provide up to 
$110 million in special financing products, including a new $50 
million underwriting experiment specifically tailored to NAACP 
clientele.
    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. Freddie Mac also announced on January 
15, 1999 that it entered into a broad initiative with the NAACP to 
increase minority homeownership. Through this alliance, Freddie Mac 
and the NAACP seek to expand community-based outreach, credit 
counseling and marketing efforts, and the availability of low-
downpayment mortgage products with flexible underwriting guidelines. 
As part of the initiative, Freddie Mac has committed to purchase 
$500 million in mortgage loans.\73\
    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.
    Underwriting Flexibility. Lenders, mortgage insurers, and the 
GSEs have also been modifying their underwriting standards to 
attempt 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 measure the circumstances of lower-income households. 
The changes to underwriting standards include, for example:
     Using a stable income standard rather than a stable job 
standard. 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.
     Making exceptions to the ``declining market'' rule and 
clarifying the treatment of mixed-use properties.74 These 
changes benefit applicants from inner-city underserved 
neighborhoods.
    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.
    Increase in Affordable Lending During the 1990s.75 
Home Mortgage Disclosure Act (HMDA) data suggest that the new 
industry initiatives may be increasing the flow of credit to 
underserved borrowers. Between 1993 and 1997 (prior to the heavy 
refinancing during 1998), 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, over this 
period home purchase originations to African Americans and Hispanics 
grew by almost 60 percent, and purchase loans to low-income 
borrowers (those with incomes less than 80 percent of area median 
income) increased by 45 percent.

------------------------------------------------------------------------
                                           1993-97  (in    1995-97  (in
                                             percent)        percent)
------------------------------------------------------------------------
All Borrowers...........................            28.1            11.1
African Americans/Hispanics.............            57.7            -0.2
Whites..................................            21.9             8.9
Income Less Than 80% AMI................            45.1            15.4
Income Greater Than 120% AMI............            31.5            24.5
------------------------------------------------------------------------

    However, as also shown, in the latter part of this period 
conventional lending for some groups slowed significantly. Between 
1995 and 1997, the slowing of the growth of home purchase 
originations was much greater for low-income borrowers than for 
higher-income borrowers. Moreover, even though remaining at near-
peak levels in 1997, conventional home purchase originations to 
African Americans and Hispanics actually decreased by two-tenths of 
a percent over the past three years. It should be noted, however, 
that total loans (conventional plus government) originated to 
African-American and Hispanic borrowers increased between 1995 and 
1997, but this was mainly the result of a 40.0 percent increase in 
FHA-insured loans originated for African-American and Hispanic 
borrowers.
    Affordable Lending Shares by Major Market Sector. The focus of 
the different sectors of the mortgage market on affordable lending 
can be seen by examining Tables A.1a, A.1b, and A.1c. Tables A.1a 
and A.1b present affordable lending percentages for FHA, the GSEs, 
depositories (banks and thrift institutions), the conventional 
conforming sector, and the overall market.76 The 
discussion below will center on Table A.1a, which provides 
information on home purchase loans and thus, homeownership 
opportunities. Table A.1b, which provides information on total (both 
home purchase and refinance) loans, is included to give a complete 
picture of mortgage activity. Both 1997 and 1998 HMDA data are 
included in these tables; the year 1997 represents a more typical 
year of mortgage activity than 1998, which was characterized by 
heavy refinance activity. The tables also include GSE data for 1999; 
the 1999 HMDA data will be incorporated when it is made available.
    The affordable market shares reported in parentheses for the 
conventional conforming market in Tables A.1a and A.1b were derived 
by excluding the estimated number of B&C loans from the HMDA data. 
HUD's method for excluding B&C loans is explained in

[[Page 65101]]

Section F.3a of Appendix D. Because B&C lenders operate mainly in 
the refinance sector, excluding these loans from the market totals 
has little impact on the home purchase percentages reported in Table 
A.1a. The reductions in the market shares are more significant for 
total loans (reported in Table A.1b) which include refinance as well 
as home purchase loans.
    The interpretation of the ``distribution of business'' 
percentages, reported in Table A.1a for several borrower and 
neighborhood characteristics, can be illustrated using the FHA 
percentage for low-income borrowers: during 1997, 47.5 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. Table A.1c, on the other hand, presents 
``market share'' percentages that measure the portion of all home 
purchase loans for a specific affordable lending category (such as 
low-income borrowers) accounted for by a particular sector of the 
mortgage market (FHA or the GSEs). In this case, the FHA market 
share of 33 percent for low-income borrowers is interpreted as 
follows: of all home purchase loans originated in metropolitan areas 
during 1997, 33 percent were FHA-insured loans. Thus, this ``market 
share'' percentage measures the importance of FHA to the market's 
overall funding of loans for low-income borrowers.
BILLING CODE 4210-27-P
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[GRAPHIC] [TIFF OMITTED] TR31OC00.005

BILLING CODE 4210-27-C
    Four main conclusions may be drawn from the data presented in 
Tables A.1a and A.1c. First, FHA places much more emphasis on 
affordable lending than the other market sectors. Low-income 
borrowers accounted for 47.5 percent of FHA-insured loans during 
1997, compared with 21.2 percent of the home loans purchased by the 
GSEs, 29.4 percent of home loans retained by depositories, and 27.3 
percent of conventional conforming loans.77 Likewise, 
41.3 percent of FHA-insured loans were originated in underserved 
census tracts, while only 22.1 percent of the GSE-purchased loans 
and 25.2 percent of conventional conforming loans were originated in 
these tracts.78 As shown in Table A.1c, while FHA insured 
only 23 percent of all home purchase mortgages originated in 
metropolitan areas during 1997, it insured 33 percent of all 
mortgages originated in underserved areas.79
    Second, the affordable lending shares for the conventional 
conforming sector are low for minority borrowers, particularly 
African-American borrowers. For example, African-American borrowers 
accounted for only 5.0 percent of all conventional conforming home 
purchase loans originated during 1997 and 1998, compared with over 
14 percent of FHA-insured loans and over 7.5 percent of all home 
purchase loans originated in the market. The African-American share 
of the GSEs' purchases is even lower than the corresponding share 
for the conventional conforming market. In 1998, home purchase loans 
to African-Americans accounted for 3.2 percent of Freddie Mac's 
purchases, 3.8 percent of Fannie Mae's purchases, and 4.9 percent of 
loans originated in the conventional conforming market (or 4.7 
percent if B&C loans are excluded from the market 
definition).80 As shown in Table A.1a, the results change 
when other minority borrowers are considered. Fannie Mae purchased 
mortgages for minority borrowers and their neighborhoods at higher 
rates than these loans were originated by primary lenders in the 
conventional conforming market. During 1997, 17.7 percent of Fannie 
Mae's purchases were mortgages for minority borrowers, compared with 
16.5 percent of conventional conforming loans. During 1998, 14.0 
percent of Fannie Mae's purchases financed homes in high-minority 
census tracts, compared with 14.1 percent of conventional conforming 
loans (or 13.7 percent without B&C loans). However, as suggested by 
the data presented above, the minority lending performance of 
conventional lenders has been subject to much criticism in recent 
studies. These studies contend that primary lenders in the 
conventional market are not doing their fair

[[Page 65104]]

share of minority lending which forces minorities, particularly 
African-American and Hispanic borrowers, to the more costly FHA and 
subprime markets.81
    Third, the GSEs, but particularly Freddie Mac, lagged the 
conventional conforming market in funding affordable loans for low-
income families and their neighborhoods during 1997 and 1998--in 
1998, for example, low-income census tracts accounted for 7.9 
percent of Freddie Mac's purchases, 9.4 percent of Fannie Mae's 
purchases, 12.1 percent of loans retained by depositories, and 10.7 
percent of all home loans originated by conventional conforming 
lenders. This pattern of Freddie Mac lagging all market participants 
during 1997 and 1998 holds up for all of the borrower and 
neighborhood categories examined in Table A.1a. One encouraging 
trend for Freddie Mac is the significant increases in its purchases 
of affordable loans between 1997 and 1999--for example, from 19.2 
percent to 24.5 percent for low-income borrowers, resulting in 
Freddie Mac surpassing Fannie Mae in the funding of home loans for 
low-income families. With respect to the GSEs' total (combined home 
purchase and refinance) purchases, Freddie Mac matched or out-
performed Fannie Mae in 1999 on all categories in Table A.1b except 
minority borrowers. A more complete analysis of the GSEs' purchases 
of mortgages qualifying for the housing goals is provided below in 
Section E.
    Finally, within the conventional conforming market, depository 
institutions stand out as important providers of affordable lending 
for lower-income families and their neighborhoods (see Table 
A.1a).82 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. 
Another important factor influencing the types of loans held by 
depository lenders is the Community Reinvestment Act, which is 
discussed next.
    Seasoned CRA Loans. The Community Reinvestment Act (CRA) 
requires depository institutions to help meet the credit needs of 
their communities. CRA provides an incentive for lenders to initiate 
affordable lending programs with underwriting 
flexibility.83 CRA loans are typically made to low- and 
moderate-income borrowers earning less than 80 percent of median 
income for their area, and in moderate-income neighborhoods. They 
are usually smaller than typical conventional mortgages and also are 
likely to have a high LTV, high debt-to-income ratios, 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. On average, CRA loans in a pool have three to four 
years seasoning.84
    However, because of the size, LTV and PMI characteristics of CRA 
loans, they have slower prepayment rates than traditional mortgages, 
making them attractive for securitization. CRA loan delinquencies 
also have very high cure rates.85 For banks, selling CRA 
pools will free up capital to make new CRA loans. As a result, the 
CRA market segment may provide an opportunity for Fannie Mae and 
Freddie Mac to expand their affordable lending programs. In mid-
1997, Fannie Mae launched its Community Reinvestment Act Portfolio 
Initiative. Under this pilot program Fannie Mae purchases seasoned 
CRA loans in bulk transactions taking into account track record as 
opposed to relying just on underwriting guidelines. By the end of 
1997, Fannie Mae had financed $1 billion in CRA loans through this 
pilot.86 With billions of dollars worth of CRA loans in 
bank portfolios the market for securitization should improve. 
Section E, below, presents data showing that Fannie Mae's purchases 
of CRA-type seasoned mortgages have increased recently. Fannie Mae 
also started another pilot program in 1998 where they purchase CRA 
loans on a flow basis, as they are originated. Results from this 
four-year $2 billion nationwide pilot should begin to be reflected 
in the 1999 production data.87

c. Potential Homebuyers

    While the growth in affordable lending and homeownership has 
been strong in recent years, attaining this Nation's housing goals 
will not be possible without tapping into the vast pool of potential 
homebuyers. The National Homeownership Strategy has set a goal of 
achieving a homeownership rate of 67.5 percent by the end of the 
year 2000. Due to the aging of the baby boomers, this rate reached 
an annual record of 66.8 percent in 1999, and rose further to 67.1 
percent in the first quarter of 2000. This section discusses the 
potential for further increases beyond those resulting from current 
demographic trends.
    The Urban Institute estimated in 1995 that there was a large 
group of potential homebuyers among the renter population who were 
creditworthy enough to qualify for homeownership.88 Of 
20.3 million renter households having low- or moderate-incomes, 
roughly 16 percent were better qualified for homeownership than half 
of the renter households who actually did become homeowners over the 
sample period. When one also considered their likelihood of 
defaulting relative to the average expected for those who actually 
moved into homeownership, 10.6 percent, or 2.15 million, low- and 
moderate-income renters were better qualified for homeownership, 
assuming the purchase of a home priced at or below median area home 
price. These results indicate the existence of a significant lower-
income population of low-risk potential homebuyer households that 
might become homeowners with continuing outreach efforts by the 
mortgage industry.
    Other surveys conducted by Fannie Mae indicate that renters 
desire to become homeowners, with 60 percent of all renters 
indicating in the July 1998 National Housing Survey that buying a 
home ranks from being a ``very important priority'' to their 
``number-one priority,'' the highest level found in any of the seven 
National Housing Surveys dating back to 1992. Immigration is 
expected to be a major source of future homebuyers--Fannie Mae's 
1995 National Housing Survey reported that immigrant renter 
household were 3 times as likely as renter households in general to 
list home purchase as their ``number-one priority.''
    Further increases in the homeownership rate also depend on 
whether or not recent gains in the homeowning share of specific 
groups are maintained. Minorities accounted for 18 percent of 
homeowners in 1999, but the Joint Center for Housing Studies has 
pointed out that minorities account were responsible for nearly 40 
percent of the 6.9 million increase in the number of homeowners 
between 1994 and 1999. Minority demand for homeownership continues 
to be high, as reported by the Fannie Mae Foundation's April 1998 
Survey of African Americans and Hispanics. For example, 38 percent 
of African Americans surveyed said it is fairly to very likely that 
they will buy a home in the next 3 years, compared with 25 percent 
in 1997.89 The survey also reports that 67 percent of 
African Americans and 65 percent of Hispanics cite homeownership as 
being a ``very important priority'' or ``number-one priority.'' 
90
    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 homeownership rate could reach 70 
percent by 2010.

d. Automated Mortgage Scoring

    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 manufactured housing.
    Automated mortgage scoring was developed as a high-tech tool 
with the purpose of identifying credit risks in a more efficient 
manner. As time and cost are reduced by the automated system, more 
time can be devoted by underwriters to qualifying marginal loan 
applicants that are referred by the automated system for more 
intensive review. Fannie Mae and Freddie Mac are in the forefront of 
new developments in automated mortgage scoring technology. Both 
enterprises released automated underwriting systems in 1995--Freddie 
Mac's Loan Prospector and Fannie Mae's Desktop Underwriter. Each 
system uses numerical credit scores, such as those developed by 
Fair, Isaac, and Company, and additional data submitted by the 
borrower, such as loan-to-value ratios and available assets, to 
calculate a mortgage score that evaluates the likelihood of a 
borrower defaulting on the 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.
    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

[[Page 65105]]

and minority homebuyers will not score well enough to be accepted by 
the automated underwriting system resulting in fewer getting loans. 
The second concern relates to the ``black box'' nature of the 
scoring algorithm. The scoring algorithm is proprietary and 
therefore it is difficult, if not impossible, for applicants to know 
the reasons for their scores.
    Federal Reserve Study. Four economists at the Board of Governors 
of the Federal Reserve System conducted a conceptual and empirical 
study on the use of credit scoring systems in mortgage 
lending.91 Their broad assessment of the models was that:

  ``[C]redit scoring is a technological innovation which has 
increased the speed and consistency of risk assessment while 
reducing costs. Research has uniformly found that credit history 
scores are powerful predictors of future loan performance. All of 
these features suggest that credit scoring is likely to benefit both 
lenders and consumers.'' 92

    The authors evaluated the current state-of-the-art of 
development of credit scoring models, focusing particularly on the 
comprehensiveness of statistical information used to develop the 
scoring equations. They presented a conceptual framework in which 
statistical predictors of default include regional and local market 
conditions, individual credit history, and applicants' 
characteristics other than credit history. The authors observed that 
the developers of credit scoring models have tended to disregard 
regional and local market conditions in model construction, and such 
neglect may tend to reduce the predictive accuracy of scoring 
equations. To determine the extent of the problem, they analyzed 
Equifax credit scores together with mortgage payment history data 
for households living in each of 994 randomly selected counties from 
across the country. The authors used these data to assess the 
variability of credit scores relative to county demographic and 
economic characteristics.
    The authors found a variety of pieces of evidence which 
confirmed their suspicions: Credit scores tended to be relatively 
lower in counties with relatively high unemployment rates, areas 
that have experienced recent rises in unemployment rates, areas with 
high minority population, areas with lower median educational 
attainment, areas with high percentages of individuals living in 
poverty, areas with low median incomes and low house values, and 
areas with relatively high proportions of younger populations and 
lower proportions of older residents.
    This analysis suggests the need for a two-step process of 
improvement of the equations and their application, in which (a) new 
statistical analyses would be performed to incorporate the omitted 
environmental variables, and (b) additional variables bearing on 
individuals' prospective and prior circumstances will be taken into 
account in determining their credit scores.
    These authors also discussed the relationship between credit 
scoring and discrimination. They found a significant statistical 
relationship between credit history scores and minority composition 
of an area, after controlling for other locational characteristics. 
From this, they concluded that concerns about potential disparate 
impact merit future study. However, a disparate impact study must 
include a business justification analysis to demonstrate the ability 
of the score card to predict defaults and an analysis of whether any 
alternative, but equally-predictive, score card has a less 
disproportionate effect.
    Urban Institute Study. The Urban Institute submitted a report to 
HUD in 1999 on a four-city reconnaissance study of issues related to 
the single-family underwriting guidelines and practices of Fannie 
Mae and Freddie Mac.93 The study included interviews with 
informants knowledgeable about mortgage markets and GSE business 
practices on the national level and in the four cities.
    The study observed, as did the Fed study summarized above, that 
minorities are more likely than whites to fail underwriting 
guidelines. Therefore, as a general matter the GSEs' underwriting 
guidelines--as well as the underwriting guidelines of others in the 
industry--do have disproportionate adverse effects on minority loan 
applicants.94
    Based on the field reconnaissance in four metropolitan housing 
markets, the study made several observations about the operation of 
credit scoring systems in practice, as follows: 95
     Credit scores are used in mortgage underwriting to 
separate loans that must be referred to loan underwriters from loans 
that may be forwarded directly to loan officers; for example, a 620 
score was mentioned by some respondents as the line below which the 
loan officer must refer the loan for manual underwriting. It is very 
difficult for applicants with low credit scores to be approved for a 
mortgage, according to the lenders interviewed by the Urban 
Institute.
     Some respondents believe the GSEs are applying cutoffs 
inflexibly, while others believe that lenders are not taking 
advantage of flexibility allowed by the GSEs.
     Some respondents believe that credit scores may not be 
accurate predictors of loan performance, despite the claims of users 
of these scores. Respondents who voiced this opinion tended to base 
these observations on their personal knowledge of low-income 
borrowers who are able to keep current on payments, rather than on 
an understanding of statistical validation studies of the models.
     Respondents indicate that the ``black box'' nature of 
the credit scoring process creates uncertainty among loan applicants 
and enhances the intimidating nature of the process for them.
    Based on these findings, the authors concluded that ``the use of 
automated underwriting systems and credit scores may place lower-
income borrowers at a disadvantage when applying for a loan, even 
though they are acceptable credit risks.''
    The Urban Institute report included several recommendations for 
ongoing HUD monitoring of the GSEs' underwriting including their use 
of credit scoring models. One suggestion was to develop a data base 
on the GSEs' lending activities relevant for analysis of fair 
lending issues. The data would include credit scores to reveal the 
GSEs' patterns of loan purchase by credit score. A second suggestion 
was to conduct analyses of the effects of credit scoring systems 
using a set of ``fictitious borrower profiles'' that would reveal 
how the systems reflect borrower differences in income, work 
history, credit history, and other relevant factors. HUD has begun 
following up on the Urban Institute's recommendations. For instance, 
in February 1999, HUD requested the information and data needed to 
analyze the GSEs' automated underwriting systems.
    Concluding Observations. It is important to note that both of 
the studies reviewed above comment on the problem of correlation of 
valid predictors of default (income, etc.) with protected factors 
(race, etc.). Both studies suggest that, ultimately, the question 
whether mortgage credit scoring models raise any problems of legal 
discrimination based on disparate effects would hinge on a business 
necessity analysis and analysis of whether any alternative 
underwriting procedures with less adverse disproportionate effect 
exist.
    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. 
The three most predictive factors are down payment, credit 
performance or bureau score, and financial cushion.
    In response to criticisms aimed at using FICO scores in mortgage 
underwriting, Fannie Mae's new version of Desktop Underwriter (DU) 
5.0 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.

e. Subprime Loans

    Another major development in housing finance has been the recent 
growth in subprime loans. In the past borrowers traditionally 
obtained an ``A'' quality (or ``investment grade'') mortgage or no 
mortgage. However, an increasing share of recent borrowers have 
obtained ``subprime'' mortgages, with their quality denoted as ``A-
minus,'' ``B,'' ``C,'' or even ``D.'' The subprime borrower 
typically is someone who has experienced credit problems in the past 
or has a high debt-to-income ratio.96 Through the first 
nine months of 1998, ``A-minus'' loans accounted for 63 percent of 
the subprime market, with ``B'' loans representing 24 percent and 
``C'' and ``D'' loans making up the remaining 13 
percent.97
    Because of the perceived higher risk of default, subprime loans 
typically carry mortgage rates that in some cases are substantially 
higher than the rates on prime mortgages. While in many cases these 
perceptions about risk are accurate, some housing advocates have 
expressed concern that there are a number of cases in which the 
perceptions are actually not accurate. The Community Reinvestment 
Association of North Carolina (CRA-NC), conducted a study based on 
HMDA data, records of deeds, and personal contacts with affected 
borrowers in Durham County, NC. They found that

[[Page 65106]]

subprime lenders make proportionally more loans to minority 
borrowers and in minority neighborhoods than to whites and white 
neighborhoods at the same income level. African-American borrowers 
represented 20 percent of subprime mortgages in Durham County, but 
only 10 percent of the prime market.98 As a result, these 
borrowers can end up paying very high mortgage rates that more than 
compensate for the additional risks to lenders. High subprime 
mortgage rates make homeownership more expensive or force subprime 
borrowers to buy less desirable homes than they would be able to 
purchase if they paid lower prime rates on their mortgages.
    The HMDA database does not provide information on interest 
rates, points, or other loan terms that would enable researchers to 
separate more expensive subprime loans from other loans. However, 
the Department has identified 200 lenders that specialize in such 
loans, providing some information on the growth of this 
market.99 This data shows that mortgages originated by 
subprime lenders, and reported in the HMDA data, has increased from 
104,000 subprime loans in 1993 to 210,000 in 1995 and 997,000 in 
1998. Most of the subprime loans reported in the HMDA data are 
refinance loans; for example, refinance loans accounted for 80 
percent of the subprime loans reported by the specialized subprime 
lenders in 1997.
    An important question is 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. It 
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, its automated underwriting 
system.100
    Most of the subprime loans that were purchased by the GSEs in 
past years were purchased through structured transactions. Under 
this form of transaction, whole groups of loans are purchased, and 
not all loans necessarily meet the GSEs' traditional underwriting 
guidelines. The GSEs typically guarantee the so-called ``A'' 
tranche, which is supported by a ``B'' tranche that covers default 
costs.
    An expanded GSE presence in the subprime market could be of 
significant benefit to lower-income families, minorities, and 
families living in underserved areas. HUD's research shows that in 
1998: African-Americans comprised 5.0 percent of market borrowers, 
but 19.4 percent of subprime borrowers; Hispanics made up 5.2 
percent of market borrowers, but 7.8 percent of subprime borrowers; 
very low-income borrowers accounted for 12.1 percent of market 
borrowers, but 23.3 percent of subprime borrowers; and borrowers in 
underserved areas amounted to 24.8 percent of market borrowers, but 
44.7 percent of subprime borrowers.101
    The GSEs. Fannie Mae and Freddie Mac have shown increasing 
interest in the subprime market throughout the latter half of the 
1990s. Both GSEs now purchase A-minus and Alt-A mortgages on a flow 
basis.102 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.
    Freddie Mac has been the more aggressive GSE in the subprime 
market. In early 1996, Freddie Mac stated that its interest in 
subprime loans was for the development of a subprime module for Loan 
Prospector (Freddie Mac's automated underwriting system), a joint 
project with Standard & Poor's to score subprime 
mortgages.103 Freddie Mac increased its subprime business 
through structured transactions, with Freddie Mac guaranteeing the 
senior classes of senior/subordinated securities backed by home 
equity loans. Between 1997 and 1999, Freddie Mac was involved in 16 
transactions totaling $8.1 billion, with Freddie Mac's 1999 business 
accounting for over $5 billion of this total.104 During 
1999, Freddie Mac did four transactions with Option One Mortgage, 
including its largest subprime deal to date, $930.4 million, in 
November of that year.
    Freddie Mac also offers a product for A-minus borrowers through 
its Loan Prospector system and it recently announced a product 
similar to the ``Timely Payment Rewards'' mortgage offered by Fannie 
Mae. In total, Freddie Mac 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.105 Freddie Mac is projecting to 
increase its subprime purchases to $17.5 billion in the year 2000, 
consisting of $9.5 billion in subprime flow purchases and $8.0 
billion in security purchases.106
    Fannie Mae has not focused on structured transactions as Freddie 
Mac has. However, 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 A-minus 
loans.107
    Because the GSEs have a funding advantage over other market 
participants, they have the ability to underprice their competitors 
and increase their market share.108 This advantage, as 
has been the case in the prime market, could allow the GSEs to 
eventually play a significant role in the subprime market. 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. Since, as explained earlier in this 
chapter, one could define a prime loan as one that the GSEs will 
purchase, the difference between the prime and subprime markets will 
become less clear. This melding of markets could occur even if many 
of the underlying characteristics of subprime borrowers and the 
market's (i.e., non-GSE participants) evaluation of the risks posed 
by these borrowers remain unchanged.
    Increased involvement by the GSEs in the subprime market might 
result in more standardized underwriting guidelines. As the subprime 
market becomes more standardized, market efficiencies might possibly 
reduce borrowing costs. Lending to credit-impaired borrowers will, 
in turn, increasingly make good business sense for the mortgage 
market.

f. Loans on Manufactured Housing

    Manufactured housing provides low-cost, basic-quality housing 
for millions of American households, especially younger, lower-
income families in the South, West, and rural areas of the nation. 
Many households live in manufactured housing because they simply 
cannot afford site-built homes, for which the construction cost per 
square foot is much higher. Because of its affordability to lower-
income families, manufactured housing is one of the fastest-growing 
parts of the American housing market.109
    The American Housing Survey found that 16.3 million people lived 
in 6.5 million manufactured homes in the United States in 1997, and 
that such units accounted for 6.6 percent of the occupied housing 
stock, an increase from 5.4 percent in 1985. Shipments of 
manufactured homes rose steadily from 171,000 units in 1991 to 
373,000 units in 1998, before tailing off to 348,000 units in 1999. 
The industry grew much faster over this period in sales volume, from 
$4.7 billion in 1991 to $15.3 billion in 1999, reflecting both 
higher sales prices and a major shift from single-section homes to 
multisection homes, which contain two or three units which are 
joined together on site.110
    Despite their eligibility for mortgage financing, only about 10-
20 percent of manufactured homes 111 are financed with 
mortgages secured by the property, even though half of owners hold 
title to the land on which the home is sited. Most purchasers of 
manufactured homes take out a personal property loan on the home 
and, if they buy the land, a separate loan to finance the purchase 
of the land.
    In 1995, the average loan size for a manufactured home was 
$24,500, with a 15 percent down payment and term of 13 years. Rates 
averaged about 3 percentage points higher than those paid on 15-year 
fixed rate mortgages, but borrowers benefit from very rapid loan-
processing and underwriting standards that allow high debt payment-
to-income (``back-end'') ratios.
    Traditionally loans on manufactured homes have been held in 
portfolio, but a secondary market has emerged since trading of 
asset-backed securities collateralized by manufactured home loans 
was initiated in 1987. Investor interest has been reported as strong 
due to reduced loan losses, low prepayments, and eligibility for 
packaging of such loans into real estate mortgage investment 
conduits (REMICs). The GSEs'

[[Page 65107]]

underwriting standards allow them to buy loans on manufactured homes 
that meet the HUD construction code, if they are owned, titled, and 
taxed as real estate.
    The GSEs are beginning to expand their roles in the manufactured 
home loan market.112 A representative of the Manufactured 
Housing Institute has stated that ``Clearly, manufactured housing 
loans would fit nicely into Fannie Mae's and Freddie Mac's 
affordable housing goals.'' 113 Given that manufactured 
housing loans often carry relatively high interest rates, an 
enhanced GSE role could also improve the affordability of such loans 
to lower-income families.

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

    Since the early 1990s, the multifamily mortgage market has 
become more closely integrated with global capital markets, 
approaching the same degree as the single-family mortgage market by 
the end of the decade. In 1999, 58.8 percent of multifamily mortgage 
originations were securitized, compared with 60.8 percent of single-
family originations.114
    Loans on multifamily properties are typically viewed as riskier 
than their single-family counterparts. Property values, vacancy 
rates, and market rents in multifamily properties appear to be 
highly correlated with local job market conditions, creating greater 
sensitivity of loan performance to economic conditions than may be 
experienced in the single-family market.
    Within much of the single-family mortgage market, the GSEs 
occupy an undisputed position of industrywide dominance, holding 
loans or guarantees with an unpaid principal comprising 39.0 percent 
of outstanding single-family mortgage debt and guarantees as of the 
end of 1999. In multifamily, the overall market presence of the GSEs 
is more modest. At the end of 1999, the GSEs' direct holdings and 
guarantees represented 17.3 percent of outstanding multifamily 
mortgage debt.115 It is estimated that GSE acquisitions 
of multifamily loans originated during 1997 represented 24 percent 
of the conventional multifamily origination market.116

1. Special Issues and Unmet Needs

    Recent studies have documented a pressing unmet need for 
affordable housing. For example, the Harvard University Joint Center 
for Housing Studies, in its report State of the Nation's Housing 
2000, points out that:
     Despite recent job and income growth, renters in the 
bottom quarter of the income distribution experienced a decline in 
real income from 1996-1998, at a time when real rents increased by 
2.3 percent.
     Between 1993 and 1995, the number of unsubsidized units 
affordable to very low-income households decreased by nearly 900,000 
units, or 8.6 percent.
     One-quarter of very low-income working households paid 
30 percent or more of their incomes for housing.
     Rising home prices and interest rates are raising the 
cost of homeownership.
     Reductions in federal subsidies may contribute to 
further losses in the affordable stock.
    The affordable housing issues go beyond the need for greater 
efficiency in delivering capital to the rental housing market. In 
many cases, subsidies are needed in order for low-income families to 
afford housing that meets adequate occupancy and quality standards. 
Nevertheless, greater access to reasonably priced capital can reduce 
the rate of losses to the stock, and can help finance the 
development of new or rehabilitated affordable housing when combined 
with locally funded subsidies. Development of a secondary market for 
affordable housing is one of many tools needed to address these 
issues.
    Recent scholarly research suggests that more needs to be done to 
develop the secondary market for affordable multifamily 
housing.117 Cummings and DiPasquale (1998) point to the 
numerous underwriting, pricing, and capacity building issues that 
impede the development of this market. They suggest the impediments 
can be addressed through the establishment of affordable lending 
standards, better information, and industry leadership.
     More consistent standards are especially needed for 
properties with multiple layers of subordinated financing (as is 
often the case with affordable properties allocated Low Income 
Housing Tax Credits and/or local subsidies).
     More comprehensive and accurate information, 
particularly with regard to the determinants of default, can help in 
setting standards for affordable lending.
     Leadership from the government or from a GSE is needed 
to develop consensus standards; it would be unprofitable for any 
single purely private lender to provide because costs would be borne 
privately but competitors would benefit.

2. Underserved Market Segments

    There is evidence that segments of the multifamily housing stock 
have been affected by costly, difficult, or inconsistent 
availability of mortgage financing. Small properties with 5-50 units 
represent an example. The fixed-rate financing that is available is 
typically structured with a 5-10 year term, with interest rates as 
much as 150 basis points higher than those on standard multifamily 
loans, which may have adverse implications for 
affordability.118 This market segment appears to be 
dominated by thrifts and other depositories who keep these loans in 
portfolio. In part to hedge interest rate risk, loans on small 
properties are often structured as adjustable-rate mortgages.
    Multifamily properties with significant rehabilitation needs 
have experienced difficulty in obtaining mortgage financing. 
Properties that are more than 10 years old are typically classified 
as ``C'' or ``D'' properties, and are considered less attractive 
than newer properties by many lenders and investors.119 
Multifamily rehabilitation loans accounted for only 0.5 percent of 
units backing Fannie Mae's 1998 purchases and for 1.6 percent in 
1999. These loans accounted for 1.9 percent of Freddie Mac's 1998 
multifamily total (with none indicated in 1999).
    Historically, the flow of capital into housing for seniors has 
been characterized by a great deal of volatility. A continuing lack 
of long-term, fixed-rate financing jeopardizes the viability of a 
number of some properties. There is evidence that financing for new 
construction remains scarce.120 Both Fannie Mae and 
Freddie Mac offer Senior Housing pilot programs.
    Under circumstances where mortgage financing is difficult, 
costly, or inconsistent, GSE intervention may be desirable. Follain 
and Szymanoski (1995) say that ``a [market] failure occurs when the 
market does not provide the quantity of a particular good or service 
at which the marginal social benefits of another unit equal the 
marginal social costs of producing that unit. In such a situation, 
the benefits to society of having one more unit exceeds the costs of 
producing one more unit; thus, a rationale exists for some level of 
government to intervene in the market and expand the output of this 
good.''121 It can be argued that the GSEs have the 
potential to contribute to the mitigation of difficult, costly, or 
inconsistent availability of mortgage financing to segments of the 
multifamily market because of their funding cost advantage, and even 
a responsibility to do so as a consequence of their public missions, 
especially in light of the limitations on direct government 
resources available to multifamily housing in today's budgetary 
environment.

3. Recent History and Future Prospects in Multifamily

    The expansion phase of the real estate cycle been well underway 
for several years now, at least insofar as it pertains to 
multifamily. Rental rates have been rising, and vacancy rates have 
been relatively stable, contributing to a favorable environment for 
multifamily construction and lending activity.122 
Delinquencies on commercial mortgages reached an 18-year low in 
1997.123 Some analysts have warned that recent prosperity 
may have contributed to overbuilding in some markets and 
deterioration in underwriting standards.124 A September 
1998, report by the Office of the Comptroller of the Currency 
anticipates continued decline in credit standards at the 77 largest 
national banks as a consequence of heightened competition between 
lenders, and the Federal Deposit Insurance Corporation has expressed 
similar concerns regarding 1,212 banks it examined.125
    Growth in the multifamily mortgage market has been fueled by 
investor appetites for Commercial Mortgage Backed Securities (CMBS). 
Nonagency securitization of multifamily and commercial mortgages 
received an initial impetus from the sale of nearly $20 billion in 
mortgages acquired by the Resolution Trust Corporation (RTC) from 
insolvent depositories in 1992-1993. Nonagency issuers typically 
enhance the credit-worthiness of their offerings through the use of 
senior-subordinated structures, combining investment-grade senior 
tranches with high-yield, below investment-grade junior tranches 
designed to absorb any credit losses.126
    Because of their relatively low default risk in comparison with 
loans on other types of income property, multifamily mortgages are 
often included in mixed-collateral financing structures including 
other commercial

[[Page 65108]]

property such as office buildings, shopping centers, and storage 
warehouses. CMBS volume reached $30 billion in 1996; $44 billion in 
1997; $78 billion in 1998; and $67 billion in 1999. Approximately 25 
percent of each year's total is comprised of multifamily 
loans.127
    During the financial markets turmoil in the fall of 1998, 
investors expressed reluctance to purchase the subordinated tranches 
in CMBS transactions, jeopardizing the ability of issuers to provide 
a cost-effective means of credit-enhancing the senior tranches as 
well.128 When investor perceptions regarding credit risk 
on subordinated debt escalated rapidly in August and September, the 
GSEs, which do not typically use subordination as a credit 
enhancement, benefited from a ``flight to quality.'' 129
    Depository institutions and life insurance companies, formerly 
among the largest holders of multifamily debt, have experienced a 
decline in their share of the market at the expense of CMBS 
conduits.130 Increasingly, depositories and life 
insurance companies are participating in multifamily markets by 
holding CMBS rather than whole loans, which are often less liquid, 
more expensive, and subject to more stringent risk-based capital 
standards.131 In recent years a rising proportion of 
multifamily mortgages have been originated to secondary market 
standards, a consequence of a combination of factors including the 
establishment of a smoothly functioning securitization 
``infrastructure;'' the greater liquidity of mortgage-related 
securities as compared with whole loans; and the desire for an 
``exit strategy'' on the part of investors.132
    Because of their limited use of mortgage debt, increased equity 
ownership of multifamily properties by REITs may have contributed to 
increased competition among mortgage originators, servicers and 
investors for a smaller mortgage market than would otherwise exist. 
During the first quarter of 1997, REITs accounted for 45 percent of 
all commercial real estate transactions, and the market 
capitalization of REITs at the end of January 1998 exceeded that of 
outstanding CMBS.133
    Demographic factors will contribute to continued steady growth 
in the new construction segment of the multifamily mortgage market. 
The number of apartment households is expected to grow approximately 
1.1 percent per year over 2000-2005. Taking into consideration 
losses from the housing stock, it has been projected that 
approximately 250,000-275,000 additional multifamily units will be 
needed in order to meet anticipated demand.134 This flow 
is approximately half that of the mid-1980s, but twice that of the 
depressed early 1990s. In 1999, 291,800 apartment units were 
completed. 135
    The high degree of volatility of multifamily new construction 
experienced historically is consistent with a view that this sector 
of the housing market is driven more by fluctuations in the 
availability of financing than by demographic fundamentals. The 
stability and liquidity of the housing finance system is therefore a 
significant determinant of whether the volume of new construction 
remains consistent with demand.
    Past experience suggests that the availability of financing for 
all forms of commercial real estate is highly sensitive to the state 
of the economy. In periods of economic uncertainty, lenders and 
investors sometimes raise underwriting and credit standards to a 
degree that properties that would be deemed creditworthy under 
normal circumstances are suddenly unable to obtain financing. 
Ironically, difficulty in obtaining financing may contribute to a 
fall in property values that can exacerbate a credit 
crunch.136 The sensitivity of commercial real estate 
markets to investor perceptions regarding global volatility was 
demonstrated by the rise in CMBS spreads in September, 
1998.137 Thus, market disruptions could have adverse 
implications on U.S. commercial and residential mortgage markets.

4. Recent Performance and Effort of the GSEs Toward Achieving the 
Low- and Moderate-Income Housing Goal: Role of Multifamily 
Mortgages

    The GSEs have rapidly expanded their presence in the multifamily 
mortgage market in the period since the housing goals were 
established in 1993. Fannie Mae has played a larger role in the 
multifamily market, with a portfolio of $47.4 billion in retained 
loans and outstanding guarantees, compared with $16.8 billion for 
Freddie Mac.138 Freddie Mac has successfully rebuilt its 
multifamily program after a three-year hiatus during 1991-1993 
precipitated by widespread defaults.
    Multifamily loans represent a relatively small portion of the 
GSEs' business activities. For example, multifamily loans held in 
portfolio or guaranteed by the GSEs at the end of 1999 represented 
less than three percent of their combined single- and multi-family 
holdings and guarantees. In comparison, multifamily mortgages not 
held or guaranteed by the GSEs represent approximately ten percent 
of the overall non-GSE stock of mortgage debt.
    However, the multifamily market contributes disproportionately 
to GSE purchases meeting both the Low- and Moderate-Income and 
Special Affordable Housing goals. In 1999, Fannie Mae's multifamily 
purchases represented 9.5 percent of their total acquisition volume, 
measured in terms of dwelling units. Yet these multifamily purchases 
comprised 20.4 percent of units qualifying for the Low- and 
Moderate-Income Housing Goal, and 31.3 percent of units meeting the 
Special Affordable goal. Multifamily purchases were 8.2 percent of 
units backing Freddie Mac's 1999 acquisitions, 16.8 percent of units 
meeting the Low- and Moderate-Income Housing Goal, and 21.6 percent 
of units qualifying for the Special Affordable Housing 
Goal.139 The multifamily market therefore comprises a 
significant share of units meeting the Low- and Moderate-Income and 
Special Affordable Housing Goals for both GSEs, and the goals may 
have contributed to increased emphasis by both GSEs on multifamily 
in the period since the previous final rule took effect in 
1996.140
    The majority of units backing GSE multifamily transactions meet 
the Low- and Moderate-Income Housing Goal because the great majority 
of rental units are affordable to families at 100 percent of median 
income, the standard upon which the Low- and Moderate-Income Housing 
Goal is defined. For example, 38.5 percent of units securing Freddie 
Mac's 1999 single-family, one-unit owner-occupied mortgage purchases 
met the Low- and Moderate-Income Housing Goal, compared with 90.0 
percent of its multifamily transactions. Corresponding figures for 
Fannie Mae were 37.9 percent and 94.8 percent. 141 For 
this reason, multifamily purchases represent a crucial component of 
the GSEs' efforts in meeting the Low- and Moderate-Income Housing 
Goal.
    Because such a large proportion of multifamily units qualify for 
the Low- and Moderate-Income Housing Goal and for the Special 
Affordable Housing Goal, Freddie Mac's weaker multifamily 
performance adversely affects its overall performance on these two 
housing goals relative to Fannie Mae. Units in multifamily 
properties accounted for 7.2 percent of Freddie Mac's mortgage 
purchases during 1994-1999, compared with 11.8 percent for Fannie 
Mae. Fannie Mae's greater emphasis on multifamily is a major factor 
contributing to the strength of its housing goals performance 
relative to Freddie Mac.

5. A Role for the GSEs in Multifamily Housing

    By sustaining a secondary market for multifamily mortgages, the 
GSEs can extend the benefits that come from increased mortgage 
liquidity to many more lower-income families while helping private 
owners to maintain the quality of the existing affordable housing 
stock. In addition, standardization of underwriting terms and loan 
documents by the GSEs has the potential to reduce transactions 
costs. As the GSEs gain experience in areas of the multifamily 
mortgage market affected by costly, difficult, or inconsistent 
access to secondary markets, they gain experience that enables them 
to better measure and price default risk, yielding greater 
efficiency and further cost savings.
    Ultimately, greater liquidity, stability, and efficiency in the 
secondary market due to a significant presence by the GSEs will 
benefit lower-income renters by enhancing the availability of 
mortgage financing for affordable rental units--in a manner 
analogous to the benefits the GSEs provide homebuyers. Providing 
liquidity and stability is the main role for the GSEs in the 
multifamily market, just as in the single-family market.
    Recent volatility in the CMBS market underlines the need for an 
ongoing GSE presence in the multifamily secondary market. The 
potential for an increased GSE presence is enhanced by virtue of the 
fact that an increasing proportion of multifamily mortgages are 
originated to secondary market standards, as noted previously. While 
the GSEs have also been affected by the widening of yield spreads 
affecting CMBS, historical experience suggests that agency spreads 
will converge to historical magnitudes as a consequence of the 
perceived benefits of federal sponsorship.\142\ When this occurs, 
the capability of the GSEs to serve and compete

[[Page 65109]]

in the multifamily secondary market will be enhanced.\143\

6. Multifamily Mortgage Market: GSEs' Ability To Lead the Industry

    Holding 12.8 percent of the outstanding stock of multifamily 
mortgage debt and guarantees as of the end of 1999, Fannie Mae is 
regarded as an influential force within the multifamily market. Its 
Delegated Underwriting and Servicing (DUS) program, in which Fannie 
Mae delegates underwriting responsibilities to originators in return 
for a commitment to share in any default risk, now accounts for more 
than half its multifamily acquisitions, and has been regarded as 
highly successful.
    Freddie Mac's presence in the multifamily market is not as large 
as that of Fannie Mae. Freddie Mac's direct holdings of multifamily 
mortgages and guarantees outstanding as of the end of 1999, $16.8 
billion, are much smaller than that Fannie Mae's $47.4 billion, not 
only in absolute terms, but also a percentage of all mortgage 
holdings and guarantees. Freddie Mac's multifamily holdings and 
guarantees are 2.1 percent of its total, compared with 4.3 percent 
for Fannie Mae.\144\ However, Freddie Mac is credited with rapidly 
rebuilding its multifamily operations since 1993. The GSEs' ability 
to lead the multifamily industry is discussed further below.

7. GSEs' Performance in the Multifamily Mortgage Market

    GSE activity in the multifamily mortgage market has expanded 
rapidly since 1993, as noted previously. However, it is not clear 
that the potential of the GSEs to lead the multifamily mortgage 
industry has been fully exploited. In particular, the GSEs' 
multifamily purchases do not appear to be consistently contributing 
to mitigation of excessive cost of mortgage financing facing small 
properties with 5-50 units. Based on data from the Survey of 
Residential Finance showing that 39.4 percent of units in recently 
mortgaged multifamily properties were in properties with 5-49 units, 
it appears reasonable to assume that loans backed by small 
properties account for 39.4 percent of multifamily units financed 
each year. As a share of units backing their multifamily 
transactions, however, GSE purchases of loans on small multifamily 
properties are typically less than 5 percent, and have never 
approached the estimated 39.4 percent market share, as shown in 
Table A.2.

            Table A.2.--GSE Multifamily Transactions by Size of Property, 1994-1999 Acquisition Year
----------------------------------------------------------------------------------------------------------------
                                        1994         1995         1996         1997         1998         1999
----------------------------------------------------------------------------------------------------------------
Fannie Mae:
    Small (5-50 units)............        8,717       45,488        5,838        8,111       64,753       12,351
    As % Fannie Mae Multifamily             3.9         19.3          2.1          3.2         16.5          4.2
     Total........................
Freddie Mac:
    Small (5-50 units)............        1,165        5,461        4,100        3,963       10,244        4,068
    As % Freddie Mac Multifamily            2.6          3.6          4.2          4.0          4.6         2.1
     Total........................
----------------------------------------------------------------------------------------------------------------
 Source: GSE loan-level data.

    In order to more usefully compare the GSEs with the market, it 
is desirable to supplement the data presented in Table A.2 by 
acquisition year with findings organized by year of origination. 
Based on HUD's analysis of loans originated in 1997 and acquired by 
the GSEs in 1997, 1998, and 1999, the GSEs have purchased loans 
backed by 24 percent of units financed in the overall conventional 
multifamily mortgage market in 1997, but their acquisitions of loans 
on small multifamily properties have been only 2.3 percent of such 
properties financed that year.\145\
    GSE multifamily acquisitions tend to involve larger properties 
than are typical for the market as a whole.\146\ For example, the 
average number of units in Fannie Mae's 1997 multifamily 
transactions was 163, with a corresponding figure of 158 for Freddie 
Mac. Both of these averages are significantly higher than the 
overall market average of 33.4 units per property on 1995 
originations estimated from the HUD Property Owners and Managers 
(POMS) survey.\147\ A factor possibly contributing to the GSEs' 
emphasis on larger properties is the relatively high fixed 
multifamily origination costs, including appraisal, environmental 
review, and legal fees typically required under GSE underwriting 
guidelines.\148\
    A recent noteworthy development is Fannie Mae's announcement of 
a new product through its Delegated Underwriting and Servicing (DUS) 
program for multifamily properties with 5-50 units. Features include 
a streamlined underwriting process designed, in part, to reduce 
borrower costs for third-party reports; use of FICO scores to 
evaluate borrower creditworthiness; and recourse to the borrower in 
the event of default.\149\
    Another area underserved by mortgage markets, in which the GSEs 
have not demonstrated market leadership is rehabilitation loans. 
Both GSEs' relatively weak performance in the multifamily 
rehabilitation market segment is related to the fact that, since the 
inception of the interim housing goals in 1993, the great majority 
of units backing GSE multifamily mortgage purchases have been in 
properties securing refinance loans with an established payment 
history, in a proportion exceeding 80 percent in some years.\150\
    The GSEs have been conservative in their approach to multifamily 
credit risk.\151\ HUD's analysis of prospectus data indicates that 
the average loan-to-value (LTV) ratio on pools of seasoned 
multifamily mortgages securitized by Freddie Mac during 1995 through 
1996 was 55 percent. In comparison, the average LTV on private-label 
multifamily conduit transactions over 1995-1996 was 73 percent based 
on HUD's analysis of Commercial Mortgage Backed Security data. 
Fannie Mae utilizes a variety of credit enhancements to further 
mitigate default risk on multifamily acquisitions, including loss 
sharing, recourse agreements, and the use of senior/subordinated 
debt structures.\152\ Freddie Mac is less reliant on credit 
enhancements than is Fannie Mae, possibly because of a more 
conservative underwriting approach.\153\
    The GSEs' ambivalence historically regarding the perception of 
credit risk in lending on affordable multifamily properties is 
evident with regard to pilot programs established in 1991 between 
Freddie Mac and the Local Initiatives Managed Assets Corporation 
(LIMAC), a subsidiary of the Local Initiatives Support Corporation 
(LISC), and in 1994 between Fannie Mae and Enterprise Mortgage 
Investments (EMI), a subsidiary of the Enterprise Foundation. 
Cummings and DiPasquale (1998) conclude that both initiatives had 
mixed results, although the Fannie Mae/EMI pilot was more successful 
in a number of regards. The Freddie Mac/LIMAC initiative was 
suspended after two years with only one completed transaction, 
involving eight loans with an aggregate loan amount of $4.6 million. 
As of June, 1997, 15 transactions comprising $20.5 million had been 
completed under the Fannie Mae/EMI pilot, which is ongoing.
    Both programs suffered initially from documentation requirements 
that borrowers perceived as burdensome. Cummings and DiPasquale 
observe that ``The smaller, nonprofit, and CDC developers that these 
programs intended to bring to the market were unprepared, and 
perhaps unwilling or unable, to meet the high costs of Freddie Mac's 
and Fannie Mae's due diligence requirements.''

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 1993-99 period. The 
data presented are ``official results''--i.e., they are based on 
HUD's in-depth analysis of the loan-level data submitted to the 
Department 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 to the Department by the GSEs in their Annual Housing 
Activities Reports.

[[Page 65110]]

    Following this analysis, the GSEs' past performance in funding 
low- and moderate-income borrowers in the single-family mortgage 
market is provided. Performance indicators for the Geographically-
Targeted and Special Affordable Housing Goals are also included in 
order to present a complete picture in Appendix A of the GSEs' 
funding of single-family mortgages that qualify for the three 
housing goals. In addition, the findings from a wide range of 
studies--employing both quantitative and qualitative techniques to 
analyze several performance indicators and conducted by HUD, 
academics, and major research organizations--are summarized below.
    Organization and Main Findings. Section E.1 reports the 
performance of Fannie Mae and Freddie Mac on the Low- and Moderate-
Income Housing Goal. Section E.2 uses HMDA data and the loan-level 
data that the GSEs provide to HUD on their mortgage purchases to 
compare the characteristics of GSE purchases of single-family loans 
with the characteristics of all loans in the primary mortgage market 
and of newly-originated loans held in portfolio by depositories. 
Section E.3 summarizes the findings from several studies that have 
examined the role of the GSEs in supporting affordable lending. 
Section E.4 discusses the findings from a recent HUD-sponsored study 
of the GSEs' underwriting guidelines.\154\ Finally, Section E.5 
reviews the GSEs' support of the single-family rental market.
    The Section's main findings with respect to the GSEs' single-
family mortgage purchases are as follows:
     Both Fannie Mae and Freddie Mac surpassed the Low- and 
Moderate-Income Housing Goals of 40 percent in 1996 and 42 percent 
in 1997-99.
     Both Fannie Mae and Freddie Mac have improved their 
affordable lending \155\ performance over the past seven years but, 
on average, they have lagged the primary market in providing 
mortgage funds for lower-income borrowers and underserved 
neighborhoods. This finding is based both on HUD's analysis of GSE 
and HMDA data as well as on numerous studies by academics and 
research organizations.
     The GSEs show very different patterns of home loan 
lending.\156\ Through 1998, Freddie Mac was less likely than Fannie 
Mae to fund single-family home mortgages for low-income families and 
their communities. However, this pattern did not continue in 1999. 
The percentages of Freddie Mac's purchases through 1998 benefiting 
historically underserved families and their neighborhoods were also 
substantially less than the corresponding shares of total market 
originations. Through 1998 Freddie Mac had not made much progress 
closing the gap between its performance and that of the overall home 
loan market. HMDA data to analyze the affordable lending shares of 
the primary market in 1999 were not available at the time this 
appendix was prepared. But since the GSEs are such major 
participants in the mortgage market, the fact that Freddie Mac 
surpassed Fannie Mae last year in many dimensions of affordable 
lending suggests that they may well have narrowed the gap between 
their performance and that of the primary market.
     Through 1998 Fannie Mae's purchases more nearly matched 
the patterns of originations in the primary market than did Freddie 
Mac's. However, during the 1993-98 period as a whole and the 1996-98 
period during which the new goals were in effect, Fannie Mae lagged 
depositories and others in the conforming market in providing 
funding for the lower-income borrowers and neighborhoods covered by 
the three housing goals. HMDA data are not currently available to 
compare Fannie Mae's performance relative to the primary market for 
1999.
     A large percentage of the lower-income loans purchased 
by the GSEs have relatively high down payments, which raises 
questions about whether the GSEs are adequately meeting the needs of 
lower-income families who have little cash for making large down 
payments.
     A study by The Urban Institute of lender experience 
with the GSEs' underwriting standards finds that the enterprises 
have stepped up their outreach efforts and have increased the 
flexibility in their underwriting standards, to better accommodate 
the special circumstances of lower-income borrowers. However, this 
study concludes that the GSEs' guidelines remain somewhat inflexible 
and that they are often hesitant to purchase affordable loans. 
Lenders also told the Urban Institute that Fannie Mae has been more 
aggressive than Freddie Mac in market outreach to underserved 
groups, in offering new affordable products, and in adjusting their 
underwriting standards.
     While single-family rental properties are an important 
source of low-income rental housing, they represent only a small 
portion of the GSEs' business. In addition, many of the single-
family rental properties funded by the GSEs are one-unit detached 
units in suburban areas rather than the older, 2-4 units commonly 
located in urban areas.

1. Past Performance on the Low- and Moderate-Income Housing Goal

    HUD's goals specified that in 1996 at least 40 percent of the 
number of units eligible to count toward the Low- and Moderate-
Income Goal should qualify as low-or moderate-income, and at least 
42 percent should qualify in 1997-99. Actual performance, based on 
HUD's analysis, was as follows:

----------------------------------------------------------------------------------------------------------------
                                                                  1996         1997         1998         1999
----------------------------------------------------------------------------------------------------------------
Fannie Mae:
    Units Eligible to Count Toward Goal.....................    1,831,690    1,710,530    3,468,428    2,925,347
    Low- and Moderate-Income Units..........................      834,393      782,265    1,530,308    1,530,308
    Percent Low- and Moderate-Income........................         45.6         45.7         44.1         45.9
Freddie Mac:
    Units Eligible to Count Toward Goal.....................    1,293,424    1,173,915    2,654,850    2,224,849
    Low- and Moderate-Income Units..........................      532,219      499,590    1,137,660    1,024,660
    Percent Low- and Moderate-Income........................         41.1         42.6         42.9         46.1
----------------------------------------------------------------------------------------------------------------

    Thus, Fannie Mae surpassed the goals by 5.6 percentage points 
and 3.7 percentage points in 1996 in 1997, respectively, while 
Freddie Mac surpassed the goals by 1.1 and 0.6 percentage points. In 
1998 Fannie Mae's performance fell by 1.6 percentage points, while 
Freddie Mac's reported performance continued to rise, by 0.3 
percentage point. Freddie Mac showed a sharp gain in performance to 
46.1 percent in 1999, exceeding its previous high by 3.2 percentage 
points. Fannie Mae's performance was also at a record level of 45.9 
percent, which, for the first time, slightly lagged Freddie Mac's 
performance.
    The figures for 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 
points in both 1996 and 1997, reflecting minor differences in 
application of counting rules. These differences also persisted for 
Freddie Mac for 1998-99, but the goal percentages shown above for 
Fannie Mae for these two years are the same as the results reported 
by Fannie Mae to the Department.
    Fannie Mae's performance on the Low- and Moderate-Income Goal 
jumped sharply in just one year, from 34.1 percent in 1993 to 45.1 
percent in 1994, before tailing off to 42.8 percent in 1995. As 
indicated, it then stabilized at the 1994 level, just over 45 
percent, in 1996 and 1997, before tailing off to 44.1 percent in 
1998, but rose to 45.9 percent last year. Freddie Mac has shown more 
steady gains in performance on the Low- and Moderate-Income Goal, 
from 30.0 percent in 1993 to 38.0 percent in 1994 and 39.6 percent 
in 1995, before surpassing 41 percent in 1996 and 42 percent 1997, 
and rising to nearly 43 percent in 1998 and to 46 percent last year.
    Fannie Mae's performance on the Low- and Moderate-Income Goal 
surpassed Freddie Mac's in every year through 1998. This pattern was 
reversed last year, 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 is due to its 
increased purchases of multifamily loans, as it re-entered that 
market, and to increases in

[[Page 65111]]

the goal-qualifying shares of its single-family mortgage purchases.

2. Comparisons With the Primary Mortgage Market

    This section summarizes several analyses conducted by HUD on the 
extent to which the GSEs' loan purchases through 1998 mirror or 
depart from the patterns found in the primary mortgage market. The 
GSEs' affordable lending performance is also compared with the 
performance of major portfolio lenders such as commercial banks and 
thrift institutions. Dimensions of lending considered include the 
borrower income and underserved area dimensions covered by the three 
housing goals. In addition, this section also analyzes Fannie Mae 
and Freddie Mac purchases during 1999; however, market data from 
HMDA were not available for 1999 at the time this analysis was 
prepared. Subsection a defines the primary mortgage market, 
subsection b addresses some questions that have recently arisen 
about HMDA's measurement of GSE activity, and subsections c-e 
present the findings.157
    The market analysis in this section is based mainly on HMDA data 
for home purchase loans originated in metropolitan areas during the 
years 1992 to 1998. The discussion below will often focus on the 
year 1997, as that year represents more typical mortgage market 
activity than the heavy refinancing year of 1998. Still, important 
shifts in mortgage funding that occurred during 1998 will be 
highlighted in order to offer a complete analysis.

a. Definition of Primary Market

    First it is necessary to define what is meant by ``primary 
market'' in making these comparisons. In this section this term 
includes all mortgages on single-family owner-occupied properties 
that are originated in the conventional conforming 
market.158 The source of this market information is the 
data provided by loan originators to the Federal Financial 
Institutions Examination Council (FFIEC) in accordance with the Home 
Mortgage Disclosure Act (HMDA).
    There is a consensus that the following loans should be excluded 
from the HMDA data in defining the ``primary market'' for the sake 
of comparison with the GSEs' purchases of goal-qualifying mortgages:
     Loans with a principal balance in excess of the loan 
limit for purchases by the GSEs--$240,000 for a 1-unit property in 
most parts of the United States in 1999.159 Loans not in 
excess of this limit are referred to as ``conforming mortgages'' and 
larger loans are referred to as ``jumbo mortgages.'' 160
     Loans which are backed by the Federal government, 
including those insured by the Federal Housing Administration and 
those guaranteed by the Department of Veterans Affairs, which are 
generally securitized by the Government National Mortgage 
Association (``Ginnie Mae''), as well as Rural Housing Loans, 
guaranteed by the Farmers Home Administration.161 
Generally, the GSEs do not receive credit on the housing goals for 
purchasing loans with Federal government backing. Loans without 
Federal government backing are referred to as ``conventional 
mortgages.''
    Questions have arisen about whether loans on manufactured 
housing should be excluded when comparing the primary market with 
the GSEs. As discussed elsewhere in this Appendix, the GSEs have not 
played a significant role in the manufactured housing mortgage 
market in the past. However, the manufactured home mortgage market 
is changing in ways that make a higher percentage of such loans 
eligible for purchase by the GSEs, and the GSEs are looking for ways 
to increase their purchases of these loans. But more importantly, 
the manufactured housing sector is one of the most important 
providers of affordable housing, which makes it appropriate to 
include this sector in the market definition. As discussed earlier 
in Section A.3c, HUD believes that excluding important low-income 
sectors such as manufactured housing from the market definition 
would render the resulting market benchmark useless for evaluating 
the GSEs' performance. For comparison purposes, data are presented 
for the primary market defined both to include and exclude mortgages 
originated by manufactured housing lenders. This issue of the market 
definition is discussed further in Appendix D, which calculates the 
market shares for each housing goal.
    Questions have also arisen about whether subprime loans should 
be excluded when comparing the primary market with the GSEs. 
Appendix D, which examines this issue in some detail, reports the 
effects of excluding the B&C portion of the subprime market from 
HUD's estimates of the goal-qualifying shares of the overall 
(combined owner and rental) mortgage market. As explained Section 
C.3.e of this appendix, the low-income and minority 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 Freddie Mac has been purchasing A-
minus loans, both on a flow basis and through negotiated 
transactions. Fannie Mae recently introduced a new program targeted 
at A-minus borrowers. Thus, HUD does not believe that A-minus loans 
should be excluded from the market definition.
    Unfortunately, HMDA does not identify subprime loans, much less 
separating them into their A-minus and B&C components. There is some 
evidence that many subprime loans are not reported to HMDA but there 
is nothing conclusive on this issue.162 Thus, it is not 
possible to exclude B&C loans from the comparisons reported below. 
However, HUD staff has identified HMDA reporters that primarily 
originate subprime loans.163 The text below will report 
the effects of excluding data for these lenders from the primary 
market. The effects are minor mostly because the analysis below 
focuses on home purchase loans, which accounted for only twenty 
percent of the mortgages originated by the subprime lenders. During 
1997 and 1998, the subprime market was primarily a refinance market.

b. Methods and Data for Measuring GSE Performance

    Several issues have arisen about the methods and the data used 
to measure the GSEs' performance relative to the characteristics of 
the mortgages being originated in the primary market. While most of 
these issues will be discussed throughout the appendices, one issue, 
the reliability of HMDA data in measuring GSE performance, needs to 
be addressed before presenting the market comparisons, which utilize 
the HMDA data. Fannie Mae, in particular, has raised questions about 
HUD's reliance on HMDA data for measuring its performance.
    There are two sources of loan-level information on 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 purchased loans 
are sold to Fannie Mae, Freddie Mac or some other entity. As 
discussed later, there have been numerous studies by HUD staff and 
other researchers that use the 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 the HMDA data, which is widely available to the public, 
provides an accurate measure of GSE performance, as compared with 
the GSEs' own data.164 Fannie Mae has argued that HMDA 
data have understated 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 such as 
underserved areas. As explained below, HMDA provided reliable 
national-level information through 1997 on the goals-qualifying 
percentages for the GSEs' purchases of newly-originated loans but 
not for their purchases of prior-year loans. In 1998, HMDA data 
differed from data that the GSEs reported to HUD on their purchases 
of newly-originated loans.
    In any given calendar year, the GSEs can purchase mortgages 
originated in that calendar year or mortgages originated in a prior 
calendar year. In 1997, purchases of prior-year mortgages accounted 
for 30 percent of the single-family units financed by Fannie Mae's 
mortgage purchases and 20 percent of the single-family units 
financed by Freddie Mac's mortgage purchases.165 HMDA 
data provides 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.166 The implications of this for measuring GSE 
performance can be seen in Tables A.3 and A.4a.167
    Table A.3 summarizes affordable lending by the GSEs, 
depositories and the conforming market for the six-year period 
between 1993 and 1998 and for the borrower and census tract 
characteristics covered by the housing goals. The GSE percentages 
presented in Table A.3 are derived from the GSEs' own data that they 
provide to HUD, while the depository and market percentages are 
taken

[[Page 65112]]

from HMDA data. Annual data on the borrower and census tract 
characteristics of GSE purchases are provided in Table A.4a. 
According to Fannie Mae's own data, 9.9 percent of its purchases 
during 1997 were loans for very low-income borrowers (see Table 
A.4a). According to HMDA data (also reported in Table A.4a), only 
8.8 percent of Fannie Mae's purchases were loans for very low-income 
borrowers.168 Thus, in this case the HMDA data 
underestimate the share of Fannie Mae's mortgage purchases for very 
low-income borrowers. Similarly, Fannie Mae reports a very low-
income percentage of 11.4 percent for its 1998 purchases while HMDA 
reports only 9.2 percent.
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    The reason that HMDA data underestimate those purchases can be 
seen by disaggregating Fannie Mae's purchases during 1997 into their 
``Prior Year'' and ``Current Year'' components. Table A.4a shows 
that the overall figure of 9.9 percent for very low-income borrowers 
is a weighted average of 13.4 percent for Fannie Mae's purchases 
during 1997 of ``Prior Year'' mortgages and 8.7 percent for its 
purchases of ``Current Year'' purchases. HMDA data report that 8.8 
percent of Fannie Mae's 1997 purchases consisted of loans to very 
low-income borrowers is based mainly on newly-mortgaged (current-
year originations) loans that lenders report they sold to Fannie 
Mae. Therefore, the HMDA data figure is similar in concept to the 
``Current Year'' percentage from the GSEs'' own data. As Table A.4a 
shows, HMDA data and ``Current Year'' figures are practically the 
same in this case (about nine percent). Thus, the relatively large 
share of very low-income mortgages in Fannie Mae's 1997 purchases of 
``Prior Year'' mortgages is the primary reason why Fannie Mae's own 
data show an overall (both prior-year and current-year) percentage 
of very low-income loans that is higher than that reported in HMDA 
data.
    A review of the data in Table A.4a yields the following insights 
about the reliability of HMDA data at the national level for 
metropolitan areas. First, comparing the HMDA data on GSE purchases 
with the GSE ``Current Year'' data suggests that HMDA data provided 
reasonable estimates of the GSEs' current year purchases through 
1997.\169\ Second, the HMDA data percentages through 1997 are 
actually rather close to Freddie Mac's overall percentages because 
Freddie Mac's prior-year purchases often resembled their current-
year originations. Fannie Mae, on the other hand, was more apt to 
purchase seasoned loans with a relatively high percentage of low-
income loans, which means that HMDA data was more likely to 
underestimate its overall performance. However, this underestimation 
of the share of Fannie Mae's goal-qualifying loans in the HMDA data 
first arose in 1997, when Fannie Mae's purchases of prior-year loans 
were particularly targeted to affordable lending groups. For the 
years 1993 to 1996, Fannie Mae's prior-year loan purchases more 
closely resembled their current-year originations.\170\
    Third, the 1998 data show that even the GSEs' ``Current Year'' 
data differ from the HMDA-reported data on GSE purchases. For 
example, special affordable loans accounted for 12.1 percent of 
Fannie Mae's current-year purchases in 1998 compared with only 10.7 
percent of Fannie Mae's special affordable purchases as reported by 
HMDA. Similarly, underserved areas accounted for 21.0 percent of 
Fannie Mae's current-year purchases compared with only 19.6 percent 
of Fannie Mae's underserved area purchases as reported by HMDA. The 
same patterns exist for Freddie Mac's 1998 data for the special 
affordable and underserved area categories. Thus, 1998 HMDA data do 
not provide a reliable estimate at the national level of the goals-
qualifying percentages for the GSEs' purchases of current-year 
(newly-mortgaged) loans. More research on this issue is 
needed.171
    The next section compares the GSE performance with that of the 
overall market. The fact that the GSE data includes prior-year as 
well as current-year loans, while the market data includes only 
current-year originations, means that the GSE-versus-market 
comparisons are defined somewhat inconsistently for any particular 
calendar year. Each year, the GSEs have newly-originated affordable 
loans available for purchase, but they can also purchase loans from 
a large stock of seasoned loans currently being held in the 
portfolios of depository lenders. Depository lenders have originated 
a large number of CRA-type loans over the past six years and many of 
them remain on their books. In fact, HUD has encouraged the GSEs to 
purchase seasoned, CRA-type loans that have demonstrated their 
creditworthiness. One method for making the 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 Table A.3.

c. Affordable Lending by the GSEs and the Primary Market

    Table A.3 summarizes goal-qualifying lending by the GSEs, 
depositories and the conforming market for the six-year period 
between 1993 and 1998 and for the more recent 1996-98 period, which 
covers the period since the most recent housing goals have been in 
effect. As noted above, the data are aggregated over time to provide 
a clearer picture of how the GSEs' purchases of both current-year 
and prior-year loans compare with the types of mortgages that have 
been originated during the past few years. All of the data are for 
home purchase mortgages in metropolitan areas. Several points stand 
out concerning the affordable lending performance of Freddie Mac and 
Fannie Mae through 1998.
    Freddie Mac--1993-98 Performance Relative to Market. The data in 
Table A.3 show that Freddie Mac substantially lagged both Fannie Mae 
and the primary market in funding affordable home loans between 1993 
and 1998. During that period, 7.6 percent of Freddie Mac's mortgage 
purchases were for very low-income borrowers, compared with 9.2 
percent of Fannie Mae's purchases, 14.5 percent of loans originated 
and retained by depositories, and 12.4 percent of loans originated 
in the conforming market (or 10.7 percent if manufactured home loans 
are excluded from the conforming market definition).172 
As shown by the annual data reported in Table A.4a, Freddie Mac did 
improve its funding of very low-income borrowers during this period, 
from 6.0 percent in 1993 to 7.6 percent in 1997, and then to 9.9 
percent in 1998. However, Freddie Mac did not make as much progress 
as Fannie Mae (discussed below) in closing the gap between its 
performance and that of the overall market. During the 1996-98 
period in which the new goals have been in effect, the ratio of 
Freddie Mac's average performance (8.4 percent) to that of the 
overall market (13.0 percent) was only 0.65; this ``Freddie-Mac-to-
market'' ratio remained at only 0.76 even when manufactured homes 
are excluded from the market definition.
    A similar conclusion about Freddie Mac's performance can be 
drawn for the other goal-qualifying categories presented in Tables 
A.3 and A.4a: Freddie Mac's performance was well below the market 
between 1993 and 1998. For example, during the recent 1996-98 
period, mortgages financing properties in underserved areas 
accounted for only 19.9 percent of Freddie Mac's purchases, compared 
with 22.9 percent of the loans purchased by Fannie Mae and 24.9 
percent of the mortgages originated in the conforming market. 
Similarly, mortgages originated for low- and moderate-income 
borrowers represented 34.9 percent of Freddie Mac's purchases during 
that period, compared with 42.6 percent of all mortgages originated 
in the conforming market.
    One encouraging sign for Freddie Mac is that the borrower-income 
categories showed a rather large increase between 1997 and 1998, 
followed by another significant increase between 1998 and 1999. 
Special affordable (low-mod) loans increased from 9.0 (34.1) percent 
in 1997 to 11.3 (36.9) percent in 1998 to 12.3 (40.0) percent in 
1999. The reasons for this increase require further study, but 
certainly, an interesting question going forward is whether Freddie 
Mac can continue this 1997-99 pattern and thus further close its 
performance gap relative to the overall market. It is somewhat 
surprising that Freddie Mac's purchases of home loans in underserved 
areas did not increase (in percentage terms) between 1997 and 1998; 
as shown in Table A.4a, the underserved areas share of Freddie Mac's 
home loan purchases remained constant at approximately 20 percent 
between 1994 and 1998 before rising to 21.2 percent in 1999.
    Fannie Mae--1993-98 Performance Relative to the Market. The data 
in Table A.3 show that Fannie Mae has also lagged depositories and 
the primary market in the funding of homes for lower-income 
borrowers and underserved neighborhoods. Between 1993 and 1998, 37.4 
percent of Fannie Mae's purchases were for low- and moderate-income 
borrowers, compared with 43.6 percent of loans originated and 
retained by depositories and with 41.8 percent of loans originated 
in the primary market. Over the more recent 1996-98 period, 22.9 
percent of Fannie Mae's purchases financed properties in underserved 
neighborhoods, compared with 25.8 percent of loans originated by 
depositories and 24.9 percent of loans originated in the 
conventional conforming market.
    However, Fannie Mae's affordable lending performance between 
1993 and 1998 can be distinguished from Freddie Mac's. First, Fannie 
Mae performed much better than Freddie Mac on every goal-category 
examined here. For example, home loans for special affordable loans 
accounted for 13.2 percent of Fannie Mae's purchases in 1998, 
compared with only 11.3 percent of Freddie Mac's purchases (see 
Table A.4a). In that same year, 22.9 percent of Fannie Mae's 
purchases were in underserved census tracts, compared with only 20.0 
percent of Freddie Mac's purchases.
    Second, Fannie Mae improved its performance between 1993 and 
1998 and made more progress than Freddie Mac in

[[Page 65117]]

closing the gap between its performance and the market's performance 
on the goal-qualifying categories examined here. In fact, by 1998, 
Fannie Mae's performance was close to that of the primary market for 
some important components of affordable lending. For example, in 
1992, very low-income loans accounted for 5.2 percent of Fannie 
Mae's purchases and 8.7 percent of all loans originated in the 
conforming market, giving a ``Fannie Mae-to-market'' ratio of 0.60. 
By 1998, this ratio had risen to 0.86, as very low-income loans had 
increased to 11.4 percent of Fannie Mae's purchases and to 13.3 
percent of market originations.
    A similar trend in market ratios can be observed for Fannie Mae 
on the underserved areas category. Fannie Mae improved its 
performance relative to the market; for example, the ``Fannie-Mae-
to-market'' ratio for underserved areas increased from 0.82 in 1992 
to 0.93 in 1998. This improved performance relative to the overall 
market by Fannie Mae is in sharp contrast to Freddie Mac's record 
during the same 1992 to 1998 period--the ``Freddie-Mac-to-market'' 
ratio for underserved areas actually declined, from 0.84 in 1992 to 
0.81 in 1998. As a result, Fannie Mae approached the home loan 
market in underserved areas while Freddie Mac lost ground relative 
to overall primary market.
    B&C Home Purchase Loan. As explained earlier, HMDA does not 
identify subprime loans, much less separate them into their A-minus 
and B&C components. Randall Scheessele at HUD has identified 200 
HMDA reporters that primarily originate subprime loans and probably 
accounted for at least half of the subprime market during 
1998.173 As shown in Table A.4b, excluding the home 
purchase loans originated by these lenders from the primary market 
data has only minor effects on the goal-qualifying shares of the 
market. The average market percentages for 1998 are reduced as 
follows: low- and moderate-income (43.0 to 42.6 percent); special 
affordable (15.5 to 15.2 percent); and underserved areas (24.6 to 
23.7 percent). As explained earlier, the effects are minor mostly 
because this analysis focuses on home purchase loans, which 
accounted for only 20 percent of the mortgages originated by these 
200 subprime lenders--the subprime market has been mainly a 
refinance market.
    GSEs' Purchases of Home Loans in 1999. Although market data are 
not yet available for 1999, the GSEs have reported their purchase 
data to HUD for that year. As shown in Table A.4a, the 1993-98 
pattern discussed above of Freddie Mac lagging behind Fannie Mae in 
funding affordable loans changed in 1999, as Freddie Mac matched or 
slightly out-performed Fannie Mae on all three goals-qualifying 
categories. For example, special affordable loans accounted for 
similar percentages of Freddie Mac's (12.5 percent) and Fannie Mae's 
(12.3 percent) purchases of home loans during 1999. Low-mod 
(underserved areas) loans accounted for 40.0 (21.2) percent of 
Freddie Mac's 1999 purchases, compared with 39.3 (20.6) percent of 
Fannie Mae's 1999 purchases. Between 1998 and 1999, Fannie Mae's 
shares of goals-qualifying home loans declined in every case while 
Freddie Mac's goals-qualifying shares increased. For example, the 
low-mod share of Freddie Mac's purchases of home loans increased by 
3.1 percentage points from 36.9 percent to 40.0 percent between 1998 
and 1999; this compares to a decrease of 1.1 percentage point for 
Fannie Mae, from 40.4 percent to 39.3 percent. Data from 1999 HMDA 
will enable HUD to examine the extent to which Freddie Mac has 
closed its performance gap relative to the overall conventional 
conforming market.

d. Prior-Year Loans

    An important source of the past differential in affordable 
lending between Fannie Mae and Freddie Mac concerns the purchase of 
prior-year loans. As shown in Table A.4a, the prior-year mortgages 
that Fannie Mae was purchasing through 1998 were much more likely to 
be loans for lower-income families and underserved areas than the 
newly-originated mortgages that they were purchasing. For example, 
30.1 percent of Fannie Mae's 1997 purchases of prior-year mortgages 
were loans financing properties in underserved areas, compared with 
20.8 percent of its purchases of newly-originated mortgages. These 
purchases of prior-year mortgages were one reason Fannie Mae 
improved its performance relative to the primary market, which 
includes only newly-originated mortgages, in 1997. Sixteen percent 
of its prior-year mortgages qualified for the Special Affordable 
Goal, compared with only 10.2 percent of its purchases of newly-
originated loans. The same patterns are exhibited by the 1998 data. 
For example, 17.9 percent of Fannie Mae's prior-year purchases 
during 1998 qualified for the Special Affordable Goal, compared with 
only 12.1 percent of its 1998 purchases of newly-originated loans. 
Through 1998, Fannie Mae seem to be purchasing affordable loans that 
were originated by portfolio lenders in previous years.
    Freddie Mac, on the other hand, does not seem to be pursuing 
such a strategy, or at least not to the same degree as Fannie Mae. 
In 1997, 1998, and 1999, Freddie Mac's purchases of prior-year 
mortgages and its purchases of newly-originated mortgages had 
similar percentages of special affordable and low-and moderate-
income borrowers. As Table A.4a shows, there is a small differential 
between Freddie Mac's prior-year and newly-originated mortgages for 
the underserved areas category but it is much smaller than the 
differential for Fannie Mae. Thus, during 1997 and 1998, Freddie 
Mac's purchases of prior-year mortgages were less likely to qualify 
for the housing goals, and this was one reason Freddie Mac's overall 
affordable lending performance was below Fannie Mae's during those 
years. In 1999, on the other hand, there was surprisingly little 
difference between the goals-qualifying percentages for Fannie Mae's 
prior-year and its current-year purchases.

e. GSE Purchases of Total (Home Purchase and Refinance) Loans

    The above sections have 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, this section briefly considers the GSEs' purchases of all 
single-family-owner mortgages, including both home purchase loans 
and refinance loans.174 As shown in Table A.4c, shifting 
the analysis to consider all (home purchase and refinance) mortgages 
does not change the basic finding that both GSEs lag the primary 
market in serving low-income borrowers and underserved 
neighborhoods. For example, in 1998 underserved areas accounted for 
21.2 (20.9) percent of Fannie Mae's (Freddie Mac's) purchases, 
compared to approximately 25 percent for both depository 
institutions and the overall primary market. Similarly, special 
affordable loans accounted for 11.1 (10.9) percent of Fannie Mae's 
(Freddie Mac's) purchases of single-family-owner loans, compared to 
14.9 percent for depository institutions and 14.2 percent for the 
overall primary market.
    There are two changes when one shifts the analysis from only 
home purchase loans to include all mortgages--one concerning the 
relative performance of Fannie Mae and Freddie Mac and one 
concerning the impact of subprime mortgages on the goals-qualifying 
percentages. These are discussed next.
    Fannie Mae versus Freddie Mac Performance--1997 to 1998. As 
indicated by the above percentages for 1998, the borrower-income and 
underserved area comparisons between Fannie Mae and Freddie Mac 
change when the analysis switches from their acquisitions of only 
home purchase loans to their acquisitions of total (both home 
purchase and refinance) loans--in the case of total loans, Freddie 
Mac's performance resembles Fannie Mae's performance in 1998 and 
surpasses Fannie Mae's performance in 1999 (see Table A.4c). These 
important shifts in the relative performance of Fannie Mae and 
Freddie Mac are best described by analyzing the 1997 to 1998 changes 
that led to Freddie Mac catching up with Fannie Mae in overall 
affordable lending, and then examining the 1998 to 1999 changes that 
led to Freddie Mac surpassing Fannie Mae in overall affordable 
lending.
    Consider the special affordable income category for 1997 and 
1998. As shown earlier in Table A.4a, special affordable loans 
accounted for a much higher percentage of Fannie Mae's acquisitions 
of home purchase loans than of Freddie Mac's in each of these two 
years. Similarly, in 1997, special affordable loans accounted for 
11.5 percent of Fannie Mae's total (both home purchase and 
refinance) purchases, compared with 9.9 percent of Freddie Mac's 
total purchases. However, between 1997 and 1998, the special 
affordable percentage of Freddie Mac's total purchases increased 
from 9.9 percent to 10.9 percent, while the corresponding percentage 
for Fannie Mae actually declined from 11.5 percent to 11.1 percent. 
Thus, in 1998, Freddie Mac's overall special affordable percentage 
(10.9 percent) was approximately the same as Fannie Mae's (11.1 
percent). This is reflected in Table A.4c by the ``Fannie-Mae-to-
Freddie-Mac'' ratio of 1.02 for the special affordable category.
    Further analysis shows that this improvement of Freddie Mac 
relative to

[[Page 65118]]

Fannie Mae was due to Freddie Mac's better performance on refinance 
loans during 1998. The special affordable percentage of Fannie Mae's 
refinance loans fell from 11.1 percent in 1997 to 9.7 percent in 
1998, which is not surprising given that middle-and upper-income 
borrowers typically dominate heavy refinance markets such as 1998. 
But the special affordable percentage of Freddie Mac's refinance 
loans did not drop very much, falling from 11.3 percent in 1997 to 
10.7 percent in 1998.175 Thus, Freddie Mac's higher 
special affordable percentage (10.7 percent versus 9.7 percent for 
Fannie Mae) on refinance loans in 1998 enabled Freddie Mac to close 
the gap between its overall single-family performance and that of 
Fannie Mae.
    The GSEs' low-mod and underserved areas percentages followed a 
somewhat similar pattern as their special affordable percentages 
between 1997 and 1998. In 1997, Freddie Mac's underserved area 
percentage (21.6 percent) for total purchases was significantly less 
than Fannie Mae's (23.6), but in 1998, Freddie Mac's underserved 
areas percentage (20.9) was about the same as Fannie Mae's (21.2 
percent), as indicated by a ``Fannie Mae to Freddie Mac'' ratio of 
1.01. This convergence was mainly due to a sharper decline in Fannie 
Mae's underserved area percentage for refinance loans between 1997 
and 1998.
    Fannie Mae versus Freddie Mac Performance--1998 to 1999. In 
1998, the ``Fannie-Mae-to-Freddie-Mac'' ratios for all three goals-
qualifying categories were approximately one, indicating similar 
performance for the two GSEs. As shown in Table A.4c, the 1999 
ratios were 0.93 for special affordable loans, 0.95 for low-mod 
loans, and 0.93 for underserved areas loans--indicating that Freddie 
Mac, for the first time, had significantly surpassed Fannie Mae in 
overall performance. For instance, in 1999, underserved areas 
accounted for 21.8 percent of Fannie Mae's purchases, compared with 
23.5 percent of Freddie Mac's purchases. For each of the three 
housing goal categories, Fannie Mae's performance increased between 
1998 and 1999, but Freddie Mac's increased even more. For example, 
Fannie Mae's special affordable performance increased by 1.2 
percentage points (from 11.1 percent to 12.3 percent) between 1998 
and 1999 while Freddie Mac's performance increased 2.4 percentage 
points (from 10.9 percent to 13.3 percent).
    B&C Loans. Table A.4b shows that the estimates for the home 
purchase market do not change much when loans for subprime lenders 
were excluded from the HMDA analysis; the reason was that these 
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. As indicated in Table 
A.4c, excluding 200 subprime lenders reduced the goal-qualifying 
shares of the total market in 1998 as follows: special affordable 
(from 14.2 to 12.7 percent); low-mod (from 40.9 to 39.0 percent); 
and underserved areas (from 24.8 to 22.6 percent). As discussed 
earlier, the GSEs have been entering the subprime market over the 
past two years, particularly the A-minus portion of that market. 
Industry observers estimate that A-minus loans account for 50-70 
percent of all subprime loans while the more risky B&C loans account 
for the remaining 30-50 percent. Thus, one proxy for excluding B&C 
loans originated by the 200 specialized lenders from the overall 
market benchmark might be to reduce the goal-qualifying percentages 
from the HMDA data by half the above differentials; accounting for 
B&C loans in this manner would reduce the 1998 HMDA-reported goal-
qualifying shares of the total conforming market as follows: special 
affordable (from 14.2 to 13.5 percent); low-mod (from 40.9 to 40.0 
percent); and underserved areas (from 24.8 to 23.7 percent). 
However, as discussed in Appendix D, much uncertainty exists about 
the size of the subprime market and its different components. More 
data and research are obviously needed on this growing sector of the 
mortgage market. 176

f. GSE Mortgage Purchases in Individual Metropolitan Areas

    While the above analyses, as well as earlier studies, 
177 concentrate on national-level data, it is also 
instructive to compare the GSEs' purchases of mortgages in 
individual metropolitan areas (e.g. MSAs). In this section, the 
GSEs' purchases of single-family owner-occupied home purchase loans 
are compared to the market in individual MSAs. 178 To do 
so, total primary market mortgage originations from three years, 
1995, 1996 and 1997, are summed up by year, by MSA, and for GSE 
purchases of these loans. The GSEs' purchases of 1995 originations 
include all 1995 originations purchased by each GSE between 1995 and 
1998 from 324 MSAs. For their purchases of 1996 originations, all 
1996 originations purchased between 1996 and 1999 from 326 MSAs are 
included. All 1997 originations purchased between 1997 and 1999 from 
328 MSAs are included for 1997 originations. This should cover 90 to 
95 percent of the 1995 through 1997 originated loans that will be 
purchased by the GSEs, thus making the GSE data comparable to HMDA 
market data. The loans are then grouped by the GSE housing goal 
categories for which they qualify and the ratio of the housing goal 
category originations to total originations in each MSA is 
calculated for each GSE and the market. The GSE-to-market ratio is 
then calculated by dividing each GSE ratio by the corresponding 
market ratio. For example, if it is calculated that one of the GSEs' 
purchases of Low- and Moderate-Income loans in a particular MSA is 
47 percent of their overall purchases in that MSA, while 49 percent 
of all originations in that MSA are Low-Mod, then that GSE-to-market 
ratio is 47/49 (or 0.96).
    Table A.5 shows the performance of the GSEs by MSA for 1995, 
1996 and 1997 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. 
179 For the above example, that GSE is considered to be 
lagging the market. These results are then summarized in Table A.5, 
which reports the number of MSAs in which each GSE under-performs 
the market with respect to the housing goal categories.
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    For 1996 originations, Fannie Mae:
     Lagged the market in 268 (83 percent) of the MSAs in 
the purchase of Underserved Area loans,
     Lagged the market in 288 (88 percent) of the MSAs in 
the purchase of Low- and Moderate-Income loans, and
     Lagged the market in 295 (90 percent) of the MSAs in 
the purchase of Special Affordable loans.
    Freddie Mac lagged the market to an even greater extent in 1996. 
Specifically, the market outperformed Freddie Mac in:
     296 (91 percent) of the MSAs in the purchase of 
Underserved Area loans,
     322 (99 percent) of the MSAs in the purchase of Low- 
and Moderate-Income loans, and
     323 (99 percent) of the MSAs in the purchase of Special 
Affordable loans.
    Thus Freddie Mac was behind Fannie Mae in at least three-
quarters of the MSAs for all three goal categories. As shown in 
Table A.5, the results for loans originated in 1995 and 1997 are 
similar.

g. High Down Payments on GSEs' Lower-Income Loans

    Recent studies have raised questions about whether the lower-
income loans purchased by the GSEs are adequately meeting the needs 
of some lower-income families. In particular, the lack of funds for 
down payments is one of the main impediments to homeownership, 
particularly for many lower-income families who find it difficult to 
accumulate enough cash for a down payment. As this section explains, 
a noticeable pattern among lower-income loans purchased by the GSEs 
is the predominance of loans with high down payments.
    HUD's 1996 report to Congress on the possible privatization of 
Fannie Mae and Freddie Mac \180\ found, rather surprisingly, that 
the mortgages taken out by lower-income borrowers and purchased by 
the GSEs were as likely to have high down payments as the mortgages 
taken out by higher-income borrowers and purchased by the GSEs. For 
example, considering the GSEs' purchases of home purchase loans in 
1995, 58 percent of very low-income borrowers made a down payment of 
at least 20 percent, compared with less than 50 percent of borrowers 
from other groups. In addition, a surprisingly large percentage of 
the GSEs' first-time homebuyer loans had high down payments. In 
1995, 35 percent of Fannie Mae's and 41 percent of Freddie Mac's 
first-time homebuyer loans had down payments of 20 percent or more.
    Table A.6 presents similar data for the GSEs' purchases of total 
loans during 1999. Over three-fourths (75.1 percent) of the GSEs' 
very low-income loans had a down payment more than 20 percent, 
compared with 72.1 percent of their remaining purchases. 
Essentially, the GSEs have been purchasing lower-income loans with 
large down payments. \181\
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    These results are consistent with previous studies that show 
that the proportion of large down payment loans purchased by the 
GSEs from lower-income borrowers is greater than that for all loan 
purchases.182
    As discussed in Section C, both Fannie Mae and Freddie Mac have 
introduced high-LTV products: ``Flexible 97'' and ``Alt 97'' 
respectively. By lowering the required down payment to three percent 
and adding flexibility to the source of the down payment, these 
loans should be more affordable. The down payment, as well as 
closing costs, can come from, 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.

[[Page 65122]]

However, in order to control default risk, these loans also have 
stricter credit history requirements.
    Fed Study. An important study by three economists--Glenn Canner, 
Wayne Passmore and Brian Surette 183--at the Federal 
Reserve Board showed the implications of the GSEs' focus on high 
down payment loans. Canner, Passmore, and Surette examined the 
degree to which different mortgage market institutions--the GSEs, 
FHA, depositories and private mortgage insurers--are taking on the 
credit risk associated with funding affordable mortgages. The 
authors combined market share and down payment data with data on 
projected foreclosure losses to arrive at an estimate of the credit 
risk assumed by each institution for each borrower group. This study 
found that Fannie Mae and Freddie Mac together provided only 4 to 5 
percent of the credit support for lower-income and minority 
borrowers and their neighborhoods. The relatively small role of the 
GSEs providing credit support is due to their low level of funding 
for these groups and to the fact that they purchase mainly high down 
payment loans. FHA, on the other hand, provided about two-thirds of 
the credit support for lower-income and minority borrowers, 
reflecting FHA's large market shares for these groups and the fact 
that most FHA-insured loans have less-than-five-percent down 
payments.

3. 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.

a. Studies by Bunce and Scheessele

    Harold Bunce and Randall Scheessele of the Department have 
published two studies of affordable lending. In December 1996, they 
published a study titled The GSEs' Funding of Affordable 
Loans.184 This report analyzed HMDA data for 1992-95, 
including a detailed comparison of the GSEs' purchases with 
originations in the primary market. In July 1998, they updated their 
earlier study to analyze the mortgage market and the GSEs' 
activities in 1996.185 The findings were largely similar 
in both studies: 186
     Both GSEs lagged the primary conventional market, 
depositories, and (particularly) FHA in funding mortgages for lower-
income and historically underserved borrowers. FHA stands out as the 
major funder of affordable loans. In 1996, approximately 30 percent 
of FHA-insured loans were for African-American and Hispanic 
borrowers, compared with only 10 percent of the loans purchased by 
the GSEs or originated in the conventional market.
     The two GSEs show very different patterns of lending--
Fannie Mae is much more likely than Freddie Mac to serve underserved 
borrowers and their neighborhoods. Since 1992, Fannie Mae has 
narrowed the gap between its affordable lending performance and that 
of the other lenders in the conforming market. Freddie Mac's 
improvement has been more mixed--in some cases it has improved 
slightly relative to the market but in other cases it has actually 
declined relative to the market. The findings with respect to 
Freddie Mac are similar to those discussed earlier in Section E.2.c.

b. Studies by Freddie Mac

    In 1995 Freddie Mac published Financing Homes for A Diverse 
America, which contained a wide variety of statistics and charts on 
the mortgage market. Several of the exhibits contained comparisons 
between the primary mortgage market and Freddie Mac's purchases in 
1993 and 1994:
     While not asserting strict parity, this report 
presented comparable frequency distributions of primary market 
originations and Freddie Mac's purchases by borrower and census 
tract income, concluding that Freddie Mac ``finances housing for 
Americans of all incomes'' and it ``buys mortgages from 
neighborhoods of all incomes.''
     With regard to minority share of census tracts, the 
report stated that Freddie Mac's ``share of minority neighborhoods 
matches the primary market.''
     The report acknowledged that Freddie Mac's purchases 
did not match the primary market in terms of borrower race. It found 
that in 1994 African-Americans and Hispanics each accounted for 4.9 
percent of the primary market but only 2.7 percent and 4.0 percent 
respectively of Freddie Mac's purchases. On the other hand, Whites 
and Asian Americans accounted for 83.7 percent and 3.2 percent of 
the primary market, but 86.3 percent and 3.9 percent respectively of 
Freddie Mac's acquisitions.
    In its March 1998 Annual Housing Activities Report (AHAR) 
submitted to the Department and Congress, Freddie Mac presented data 
on this issue for 1996 and 1997. This report stated that its 
purchases ``essentially mirror[ed] the overall distribution of 
mortgage originations in terms of borrower income.'' However, the 
data underlying Exhibit 4 of the AHAR indicated that the share of 
Freddie Mac's 1997 purchases for borrowers with income (in 1996 
dollars) less than $40,000 was more than 4 percentage points below 
the corresponding share for the primary market in 1996. A similar 
pattern prevailed in terms of census tract income--the data 
underlying Exhibit 5 of the AHAR indicated that the share of Freddie 
Mac's 1997 purchases in tracts with income in excess of 120 percent 
of area median income exceeded the corresponding share for the 
primary market in 1996 by about 4 percentage points.
    In its March 1998 AHAR, Freddie Mac found a much closer match 
between the distributions of home purchase mortgages by down payment 
for Freddie Mac's 1997 acquisitions and the primary market in 1997, 
as the latter was reported by the Federal Housing Finance Board. 
Specifically, Exhibit 6 of the AHAR reported that 42 percent of 
borrowers in each category made down payments of less than 20 
percent.187

c. Studies by Fannie Mae

    Fannie Mae has not published any studies on the comparability of 
its mortgage purchases with the primary market. However, in an 
October 1998 briefing for HUD staff, Fannie Mae presented the 
results of several comparisons of its purchases, based on the data 
supplied to the Department by Fannie Mae, with loans originated in 
the conventional conforming market, based on the HMDA data. In these 
analyses, Fannie Mae stated that:
     The percentage of Fannie Mae's home purchase loans 
serving minorities exceeded the corresponding percentage in the 
conventional conforming market by 2.6 percentage points in 1995, 2.0 
percentage points in 1996, and 2.7 percentage points (18.6 percent 
vs. 15.9 percent) in 1997;
     The percentage of Fannie Mae's home purchase loans for 
low-and moderate-income households exceeded the corresponding 
percentage in the conventional conforming market by 0.2 percentage 
point in 1995, fell 0.1 percentage point short of the market in 
1996, but exceeded it again, by 1.2 percentage points (38.5 percent 
vs. 37.3 percent), in 1997;
     The percentage of Fannie Mae's home purchase loans for 
households in underserved areas fell 0.04 percentage point short of 
the conventional conforming market in 1996, but exceeded the 
corresponding percentage in the conventional conforming market by 
1.4 percentage points (25.5 percent vs. 24.1 percent) in 1997;
     The percentage of Fannie Mae's home purchase loans for 
very low-income households and low-income households in low-income 
areas fell 1.0 percentage point short of the conventional conforming 
market in 1995 and 0.9 percentage point short in 1996, but exceeded 
the corresponding percentage in the conventional conforming market 
by 2.2 percentage points (12.7 percent vs. 10.5 percent) in 1997.
    Some of these findings by Fannie Mae differ from those of other 
researchers. This is due in part to the fact that most other studies 
have utilized HMDA data for both the primary market and sales to the 
GSEs, but Fannie Mae compared the primary market, based on HMDA 
data, with the patterns in the GSE loan-level data submitted to the 
Department.188 189

d. Other Studies

    Lind. John Lind examines HMDA data in order to compare the GSEs' 
loan purchase activity to mortgage originations in the primary 
conventional conforming market.190 Like other studies, 
Lind presents an aggregate comparison of GSE/primary market 
correspondence for Black, Hispanic, low-income borrowers, and low- 
and moderate-income Census tracts. Unlike other studies, however, 
Lind also examines market correspondence at the individual 
metropolitan area and regional levels.
    Lind finds that the GSEs are not leading the market, but that 
Fannie Mae, in particular, improved its performance between 1993 and 
1994. In 1994, Lind finds that the shares of Fannie Mae's home 
purchase loans to minority and low-income borrowers were comparable 
to the industry's shares. But the share of its home purchase loans 
for low- and moderate-income census tracts and the shares of Freddie 
Mac's home purchase loans for all categories examined trailed those 
for the industry as a whole. For refinance mortgages, on the other 
hand, both

[[Page 65123]]

GSEs trailed the industry in terms of the shares of their loans for 
the groups analyzed. In a subsequent study, Lind found that the 
difference between the affordable lending performance of Fannie Mae 
and Freddie Mac was caused by differences in policy and operating 
procedures of the GSEs, and not differences in the make-up of their 
suppliers of loans.191
    Ambrose and Pennington-Cross. There exists a wide variation in 
the market shares of the GSEs, FHA and portfolio lenders across 
geographic mortgage markets. Brent Ambrose and Anthony Pennington-
Cross analyze FHA, GSE and portfolio lender market shares to find 
insights into what factors affect the market shares for FHA eligible 
(under the FHA loan limit) loans.192 They hypothesize 
that the GSEs try to mitigate higher perceived risks at the MSA 
level by tightening lending standards, generating a prediction of 
higher FHA market share in locations with characteristically higher 
or dynamically worsening risk. A second hypothesis is that market 
share of portfolio lenders increases in areas with higher risk due 
to ``reputation effects'' and GSE repurchase requirements. In their 
model, they account for cyclical risk, permanent risk, demographic, 
lender and regional differences.
    Ambrose and Pennington-Cross found that the GSEs exhibit risk 
averse behavior as evidenced by lower GSE market presence in MSAs 
experiencing increasing risk and in MSAs that historically exhibit 
high-risk tendencies. FHA market shares, in contrast, are associated 
with high or deteriorating risk conditions. Portfolio lenders 
increase their mortgage portfolios during periods of economic 
distress, but increase the sale of originations out of portfolio 
during periods of increasing house prices. Lenders in MSAs with 
historically high delinquency hold more loans in portfolio. MSA risk 
is therefore concentrated among portfolio lenders and in FHA, with 
the GSEs bearing relatively little credit risk of this kind. The 
study does find that, other things being equal, the GSEs do have a 
higher presence in underserved areas and in areas where the minority 
population is highly segregated.
    MacDonald (1998). Heather MacDonald 193 examined the 
impact of the central city housing goal from HUD's 1993-1995 interim 
housing goals. Census tracts were clustered according to five 
variables (median house value, median house age, proportion of 
renters, percent minority and proportion of 2 to 4 units) argued to 
impede secondary market purchases of homes in some neighborhoods. 
Borrower characteristics and lending patterns were compared across 
the clusters of tracts, and across central city and suburban tracts. 
Clustered tracts were found to be more strongly related to a set of 
key lending variables than are tracts divided according to central 
city/suburban boundaries. MacDonald concludes that targeting 
affirmative lending requirements on the basis of neighborhood 
characteristics rather than political or statistical divisions may 
provide a more appropriate framework for efforts to expand access to 
credit.
    MacDonald (1999). In a 1999 study, Heather MacDonald 
investigated variations in GSE market share among a sample of 426 
nonmetropolitan counties in eight census divisions.194 
Conventional conforming mortgage originations were estimated using 
residential sales data, adjusted to exclude government-insured and 
nonconforming loans. Multivariate analysis was used to investigate 
whether GSE market shares differed significantly by location, after 
controlling for the economic, demographic, housing stock and credit 
market differences among counties that could affect use of the 
secondary markets. The study also investigated whether there were 
significant differences between the nonmetropolitan borrowers served 
by Fannie Mae and those served by Freddie Mac.
    MacDonald found that space contributes significantly to 
explaining variations in GSE market shares among nonmetropolitan 
counties, but its effects are quite specific. One region--non-
adjacent West North Central counties--had significantly lower GSE 
market shares than all others. The disparity persisted when analysis 
was restricted to underserved counties only. The study also 
suggested significant disparities between the income levels of the 
borrowers served by each agency, with Freddie Mac buying loans from 
borrowers with higher incomes than the incomes of borrowers served 
by Fannie Mae. An important limitation on any study of 
nonmetropolitan mortgages was found to be the lack of Home Mortgage 
Disclosure Act data. This meant that more precise conclusions about 
the extent to which the GSEs mirror primary mortgage originations in 
nometropolitan areas could not be reached.
    McClure. Kirk McClure examined the twin mandates of FHEFSSA: to 
direct mortgage credit to neighborhoods that have been underserved 
by mortgage lenders; and to direct mortgage credit to low-income and 
minority households.195 Using the Kansas City 
metropolitan area as a case study, mortgages purchased by the GSEs 
in 1993-96 were compared with mortgages held by portfolio lenders in 
order to determine the performance of the GSEs in serving these two 
objectives. Kansas City provides a useful case study area for this 
analysis, because it includes a range of weak and strong housing 
market areas where homebuyers have been able to move easily to serve 
their housing, employment, and neighborhood needs.
    McClure found that borrowers are better served if credit is 
directed to them independent of location. Very low-income and 
minority borrowers fared better, in terms of the demographic, 
housing, and employment opportunities of the neighborhoods into 
which they located, than borrowers in underserved neighborhoods, 
suggesting that directing credit to low-income and minority 
households has had the desired effect of helping these households 
purchase homes in areas where they would find good homes and good 
employment prospects. According to McClure, HUD's 1996-99 housing 
goals defined underserved tracts very broadly, such that nearly one-
half of the tracts in the Kansas City area are categorized as 
underserved. Because the definition of underserved is so broad, 
directing credit to these tracts means only increasing the flow of 
mortgage credit to the lesser one-half of all tracts, which includes 
many areas with stable housing stocks and viable job markets.
    The alternative approach of directing credit to underserved 
areas was found to be helpful only insofar as it has helped direct 
credit to neighborhoods with slightly lower household income levels 
and higher incidence of minorities than found elsewhere in the 
metropolitan area. McClure concluded that neighborhoods that receive 
very low levels of mortgage credit seemed to provide insufficient 
housing or employment opportunities to justify the effort that would 
be required to direct additional mortgage credit to them.
    McClure concluded that whatever the approach, the GSEs have not 
been performing as well as the primary credit lenders in the Kansas 
City metropolitan area. In terms of helping underserved areas, the 
GSEs lagged behind the industry in the proportion of loans found in 
these areas. In terms of helping low-income and minority borrowers, 
the GSEs also lagged behind the industry. However, to the extent 
that the GSEs served these targeted populations, these households 
used this credit to move to neighborhoods with better housing and 
employment opportunities than were generally present in the 
underserved areas.
    Williams.196 This study looks at mortgage lending in 
underserved markets in the primary and secondary mortgage markets 
for the MSAs in Indiana. A more extensive analysis is provided for 
South Bend/St. Joseph County, Indiana that looks at the GSE 
purchases in underserved markets by type of primary market lender in 
both 1992 and 1996. It shows the percentage of loans bought by the 
GSEs and the loan they did not buy. This study found that the GSEs 
were more aggressive in closing the gap in St. Joseph County than in 
other MSAs in Indiana. It also found that Fannie Mae's underserved 
market performance was slightly better than Freddie Mac's 
performance.
    Williams compared the GSEs performance in underserved markets 
and CRA institutions between 1992 and 1995. It shows that the GSEs 
have narrowed the gap between themselves and lenders while CRA 
institutions have lost ground relative to non-CRA lenders. A pattern 
observed across all Indiana MSAs is that the GSEs do not appear to 
lead the market but rather almost perfectly mirrored the performance 
of mortgage companies.
    Williams looked at the impact of size and location of lenders on 
the home mortgage market. Large lenders were more likely to finance 
mortgages for very low-income and African American borrowers than 
smaller lenders. Lenders headquartered in Indiana were more likely 
to purchase mortgages in underserved areas than lenders who only had 
branches or no apparent physical presence in Indiana. This suggest 
that served markets might benefit more than underserved areas from 
increased competition from non-local lenders.
    Gyourko and Hu. This study focuses on the GSEs' housing goals 
looking at the intra-metropolitan distribution of mortgage 
acquisitions by Fannie Mae and Freddie Mac

[[Page 65124]]

and the spatial distribution of households within 22 
MSAs.197 The data on the GSEs' mortgage purchases is 
provided by the Census Tract File of Public Use Data Base and data 
on households is provided by the 1990 census. The study found that 
the distribution of goal-qualifying loan purchases by the GSEs does 
not match the distribution of goal-qualifying households. On average 
44 percent of Low- and Moderate-Income Goal and 46 percent of 
Special Affordable Goal qualifying households are located in central 
cities. This compares to the GSEs' mortgage purchases where 26 
percent of Low- and Moderate-Income Goal and 36 percent of Special 
Affordable Goal were located in central cities.
    This study develops criteria for evaluating the GSEs' mortgage 
purchasing performance in census tracts. The first measure is a 
ratio. The numerator of the ratio is the share of the GSEs' mortgage 
purchases that qualify for the Special Affordable Housing Goal in 
the census tract. The denominator is the share of households that 
are targeted by the Special Affordable Housing Goal in the census 
tract. A ratio is also computed for the Low- and Moderate-Income 
Housing Goal. If the ratio is less than 0.80 then the census tract 
is called under-represented, meaning that the share of the GSEs' 
mortgage purchases which qualify for the housing goal is less than 
80 percent of the share of the households that the goal targets. The 
analysis of these ratios shows that: (1) Central cities are more 
likely to be under-represented in terms of the share of affordable 
loans purchased by the GSEs, (2) in suburbs, the larger the census 
tracts' percent minority the greater the probability that affordable 
loan purchases are under-represented, and (3) the higher the tract's 
median income, the greater the likelihood that census tract is over-
represented.
    Gyourko and Hu's results are broadly consistent across the 22 
MSAs analyzed; however, some noteworthy exceptions are made. In a 
few MSAs, particularly Miami and New York, the mismatch of 
affordable GSE purchases to affordable households is much less 
severe. In Boston, Los Angeles and New York, census tracts with 
higher relative median incomes are more likely to be under-
represented.
    Case and Gillen. This study provides a descriptive analysis of 
market share and logistic regression analysis of the GSEs' mortgage 
purchase patterns in 44 metropolitan areas over the period from 1993 
to 1996.198 The study compares the GSEs and the market 
along several borrower and neighborhood characteristics.
    This descriptive analysis of market shares finds that, compared 
with mortgages originated in the market, the GSEs' are less likely 
to purchase loans made to lower-income borrowers, minority 
borrowers, borrowers in lower-income neighborhoods, and borrowers in 
central city neighborhoods. The GSEs are more likely to purchase 
loans made to higher income borrowers, white borrowers, borrowers in 
higher income neighborhoods, and suburban borrowers than the non-
GSEs. Case and Gillen find that Fannie Mae provides a higher 
proportion of total GSE funding for mortgage lending to lower-income 
and minority borrowers and to borrowers living in lower income, 
predominantly minority, central city, and geographically targeted 
areas than Freddie Mac.
    A logistic regression analysis was conducted to look at the 
influence of specific borrower and neighborhood characteristics on 
the probability that a loan is purchased by one the GSEs. The 
results support the findings of the descriptive analysis with some 
exceptions. In contrast to the descriptive analysis, the impact of 
geographically targeted census tracts and neighborhood minority 
composition on the GSEs' purchasing behavior was inconsistent over 
the 44 areas. 199, 200
    The logistic regression analysis was extended to test for 
changes in the GSEs' purchasing behavior over time (1993-1996). 
Changes in the GSEs' purchasing activity are observed, but no 
systematic time trend was found. One explanation that was given for 
this result was that changes in the GSEs' purchases over time might 
be related to changes in overall market activity rather than changes 
in purchasing behavior by either of the GSEs.
    Myers. Earlier studies have shown that racial minority groups--
particularly African Americans and Latinos--are less likely to be 
approved for home mortgage loans than members of majority 
populations. It has been suggested that primary lenders may use the 
difficulty of selling loans to the GSEs on the secondary market as a 
pretext for not approving loans to racial minority group members. 
This study uses the residual difference approach to measure racial 
discrimination in mortgage lending and estimates differential 
treatment by the GSEs of minority and nonminority first-time 
homeowner loans in the 23 largest metropolitan statistical areas 
(MSAs).201
    The residual difference approach decomposes racial gaps in HMDA-
reported loan-rejection rates between the component that can be 
explained and that which cannot be explained by racial differences 
in characteristics. Characteristics Myers uses to explain poor 
credit history and denial rates include borrower, neighborhood, and 
loan variables from HMDA, the GSE Public Use Data Base, and Census 
1990.202 Myers interprets the unexplained gap as being 
``discrimination''. The residual difference method permits the 
estimation of minority loan rejection rates when minorities are 
treated like equally qualified white borrowers (i.e. equal treatment 
values).
    There are three main findings of this study. First, there are 
unexplained disparities in loan-rejection rates between black and 
white applicants for home mortgage loans in HMDA data; that is, 
blacks have higher denial rates than whites even after controlling 
for variables such as income. Second, the probability that a loan 
won't sell on the secondary market systematically increases the 
probability that a loan will be rejected by the 
lender.203 Third, African American and Hispanic loans are 
often less likely to sell on the secondary market than white loans.
    The study also looks at whether the GSEs' purchasing behavior 
explains racial gaps in loan rejection rates. It compares the 
residual difference on racial disparities in loan rejection rates 
with and without controlling for GSE decisions. If the equal-
treatment rejection rate is higher than the equal-treatment 
rejection rate that accounts for the GSE effect, then the purchase 
policies of the GSEs ``explains part of the lending gap''. If the 
equal-treatment value without accounting for racial difference in 
GSE effects is equal to or lower than the corresponding value than 
accounts for racial difference in GSE effect, then GSEs effect does 
not explain racial lending gaps.
    Myers concludes that there are no consistent patterns for the 
GSE effect, either across racial groups or across MSAs--that is, the 
GSE discussions do not systematically explain the observed racial 
disparities in loan rejection rates. In many MSAs, the GSE effect 
can account for some of the high rejection rates of blacks and 
``others''. Among other racial groups, however, there are as many 
MSAs where there is no such finding as there are ones where the 
effect seems to hold. But even in those cases where the effect seems 
to hold the amount explained is small. Myers finds that the impact 
is so small that even large differences in actual probabilities that 
loans are not sold to GSEs cannot explain the substantial racial 
difference in loan-rejection rates.
    Bradford. In a case study comparison of the Chicago and 
Washington D.C. mortgage markets, Bradford found that minority areas 
received considerably lower levels of GSE purchases than white areas 
in the Chicago market, but about equal and sometimes higher levels 
of GSE purchases in the D.C. study area.204 Bradford's 
interprets this finding as partially the result of the exceptionally 
large minority population in the D.C. area living in new development 
and suburban areas when compared to the minority population 
distribution in the Chicago market. In his view, the fact that many 
minority homeowners in the D.C. area reside in suburban and new 
growth areas provides for increasing housing values and high levels 
of demand that help mitigate the effects of mortgage default by 
providing borrowers with more options to refinance or sell their 
homes to escape from foreclosure. This makes the minority market in 
the D.C. area generally more attractive to lenders and secondary 
market investors.
    Bradford argues that the role of individual lenders is an 
important factor in explaining the disparate racial patterns between 
the Chicago and D.C. study areas. The large GSE lenders and the 
large lenders serving minority markets tend to be the same lenders 
in the D.C. market. He contends that the parity in the racial 
markets in the D.C. area would disappear and would be replaced by 
levels of disparity comparable to those in the Chicago market if 
just a handful of large GSE lenders in the minority areas reduced 
their GSE levels to the norm for the entire market.
    Bradford also examines differences between Fannie Mae and 
Freddie Mac in the two study areas. Both Fannie Mae and Freddie Mac 
showed lower levels of purchases in minority areas than in white 
areas in the Chicago market, based on his research. While there were 
some instances where Freddie Mac made improvements

[[Page 65125]]

relative to Fannie Mae (notably in the Chicago market in 1996), 
Fannie Mae's relative performance in different racial markets was 
better than that of Freddie Mac. In the Chicago market, for example, 
Fannie Mae had higher levels of market shares in the racially 
changing areas than in the white areas while Freddie Mac always had 
lower market shares in the racially changing areas compared to the 
white areas. In the D.C. market, Bradford found that while the GSEs 
as a whole showed relative parity in the different racial markets, 
this was largely due to Fannie Mae's performance that countered the 
systematic disparities in the Freddie Mac purchases.
    Harrison, et. al. Theories of ``information externalities,'' 
supported by recent empirical evidence, suggest that property 
transactions in a particular market area generate information making 
similar future transactions in that same market area less risky for 
prospective lenders. Specifically, home sales generate information 
useful to independent appraisers in generating more precise value 
estimates. This increased precision, in turn, reduces the 
uncertainty (risk) faced by lenders, and hence, may increase 
acceptance rates and the flow of funds to the given market area.
    Using a sample of GSE purchasing activities across twelve 
Florida counties, Harrison et al. find some evidence that both 
Fannie Mae and Freddie Mac are more active in neighborhoods with 
historically low transaction volume than they are in other 
neighborhoods.205 In addition, the results of their 
investigation are generally consistent with the previous literature 
suggesting Fannie Mae outperformed Freddie Mac in historically 
underserved market segments in 1993-95.

4. GSEs' Underwriting Guidelines

    Most studies on affordability of mortgage loans are quantitative 
using HMDA data, HUD's GSE Public Use Database or some other related 
database. To complement these studies, HUD commissioned a study by 
the Urban Institute (UI) to examine recent trends in the GSEs' 
underwriting criteria and to seek attitudes and opinions of informed 
players in four local mortgage market markets (Boston, Detroit, 
Miami and Seattle).206 Interviews were conducted with 
mortgage lenders, community advocates and local government 
officials--all local actors who would be knowledgeable about the 
impact of the GSEs' underwriting policies on their ability to fund 
affordable loans for lower-income borrowers.207
    The UI report reveals three major trends in the GSEs' 
underwriting that affects affordable lending. These include 
increased flexibility in standard 208 underwriting and 
appraisal guidelines, the introduction of affordable lending 
products, and the introduction of automated underwriting and credit 
scores in the loan application process. Through these trends, Fannie 
Mae and Freddie Mac have attempted to increase their capacity to 
serve low- and moderate-income homebuyers. They are also eliminating 
practices that could potentially have had disparate impacts on 
minority homebuyers. While both GSEs have made progress, ``most [of 
those interviewed] thought Fannie Mae has been more aggressive than 
Freddie Mac in outreach efforts, implementing underwriting changes 
and developing new products.'' 209
    While the GSEs improved their ability to serve low- and 
moderate-income borrowers, it does not appear that they have gone as 
far as some primary lenders to serve these borrowers and to minimize 
the disproportionate effects on minority borrowers. From previous 
published analyses of the GSEs' mortgage purchases, differences 
between the income characteristics and racial composition of 
borrowers served by the primary mortgage market and the purchase 
activity of the GSEs were found. ``This means that the GSEs are not 
serving lower-income and minority borrowers to the extent these 
families receive mortgages from primary lenders.'' 210 
From UI's discussions with lenders, it was revealed that primary 
lenders are 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. These mortgages are originated to a greater extent 
to minority borrowers who have lower incomes and wealth. From this 
evidence, UI concludes that the GSEs appear to be lagging the market 
in servicing low- and moderate-income and minority borrowers.
    Furthermore, UI 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. Moreover, the use of automated underwriting systems and 
credit scores may place lower-income borrowers at a disadvantage 
when applying for a loan, even though they are acceptable credit 
risks.'' 211

5. The GSEs' Support of the Mortgage Market for Single-family 
Rental Properties

    Single-family rental housing is an important part of the housing 
stock because it is an important source of housing for lower-income 
households. Based on the 1996 Property Owners and Managers Survey, 
49 percent of all rental units are in properties with fewer than 
five units and the 1997 American Housing Survey found that 
approximately 59 percent of the stock of single-family rental units 
are affordable to very-low income families (i.e., families earning 
60 percent or less of the area median income). Of the GSEs' mortgage 
purchases in 1999, around 30 percent of the single-family rental 
units financed were affordable to very-low income households.
    While single-family rental properties are a large segment of the 
rental stock for low-income families, they make up a small portion 
of the GSEs' overall business. In 1999, Fannie Mae and Freddie Mac 
purchased more than $26 billion in mortgages for these properties. 
These purchases represented less than 5 percent of the total dollar 
amount of their overall 1999 business.
    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.7b in Section G shows that in 
1998 the GSEs financed 68 percent of owner-occupied dwelling units 
but only 19 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 are important for the GSEs 
housing goals, especially for meeting the needs of lower-income 
families. In 1999 around 73 percent of single-family rental units 
qualified for the Low- and Moderate-Income Goals, compared with 38 
percent of one-family owner-occupied properties. This heavy focus on 
lower-income families meant that single-family rental properties 
accounted for 15 percent of the units qualifying for the Low- and 
Moderate-Income Goal, even though they accounted for 8 percent of 
the total units (single-family and multifamily) financed by the 
GSEs. Single-family rental properties account for 16 percent of the 
geographically-targeted and 23 percent of the special affordable 
housing goals.
    A comparison of the GSEs' single-family rental and one-family 
owner-occupied mortgage purchases reveals the following broad 
patterns of borrower and neighborhood characteristics. Borrowers for 
single-family rental properties are more likely to be minorities 
than borrowers for one-family owner-occupied properties. Mortgages 
purchased by the GSEs for single-family rental properties compared 
with one-family owner-occupied properties are more likely to be 
located in lower-income and higher minority neighborhoods. More 
single-family rental than one-family owner-occupied mortgages were 
refinance or prior-year loans.
    A closer look at borrower characteristics for single-family 
rental properties shows the following. First, based on ethnic/racial 
characteristics, borrowers for investor-owned properties are similar 
to borrowers for one-family owner-occupied properties. Second, 
borrowers for single-family rental properties, especially owner-
occupied 2- to 4-unit properties, are more likely to be nonwhite 
than are borrowers for one-family owner-occupied and investor-owned 
properties. About 35 percent of the borrowers for owner-occupied 2- 
to 4-unit properties are non-white compared with around 17 percent 
for both one-family and investor-owned properties. For one-family 
owner-occupied and investor-owned properties about 5 percent of 
borrowers are African American, compared with 9 percent for owner-
occupied 2- to 4-unit properties. A similar comparison applies for 
Hispanic borrowers, 6 percent and 15 percent respectively.
    With regard to neighborhood characteristics, a comparison of 
different

[[Page 65126]]

types of rental properties purchased by the GSEs shows that investor 
1-unit properties were more likely to be located in higher-income 
neighborhoods than were units in 2- to 4-unit rental properties. For 
units in investor 1-unit properties, about 18 percent were in low-
income neighborhoods, compared with 31 percent from units in 2- to 
4-unit rental properties. About 40 percent of the units in investor 
properties were in high-minority neighborhoods, compared to only a 
slightly lower 37 percent for owner-occupied 2- to 4-unit 
properties.
    The GSEs can mitigate risk by purchasing mortgages which are 
seasoned or refinanced. The data show that mortgages on properties 
with additional risk components such as being investor-owned, in 
low- income neighborhoods, and/or in high-minority neighborhoods are 
more likely to be seasoned or refinanced. For the GSEs' mortgage 
purchases, in general, mortgages on investor-owned properties are 
more likely to be prior-year than mortgages on owner-occupied 2- to 
4-unit properties (based on unit counts). These patterns are 
consistent with the notion that investor properties are more risky 
than owner-occupied 2- to 4-unit properties.

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 50-55 percent of total 
units financed in the overall conventional conforming mortgage 
market during 2001-2003, the period for which the Low- and Moderate-
Income Housing Goal is established. The market estimates exclude B&C 
loans and allow for much more adverse economic 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].'' \212\
    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 other lenders 
in funding lower-income borrowers and their communities. 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 50-55 percent, which is substantially 
higher than the GSEs' performance on that goal.
    This section provides another perspective on the GSEs' 
performance by examining the share of the total 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

    Table A.7 compares GSE mortgage purchases with HUD's estimates 
of the numbers of units financed in the conventional conforming 
market during 1997(A.7a) and 1998 (A.76).\213\ Because 1997 was a 
more typical year then the heavy refinance year of 1998, the 
following discussion will focus on 1997. HUD estimates that there 
were 7,306,950 owner and rental units financed by new mortgages in 
1997. Fannie Mae's and Freddie Mac's mortgage purchases financed 
2,948,112 dwelling units, or 40 percent of all dwelling units 
financed. As shown in Table A.7a, the GSEs play a much smaller role 
in the goals-qualifying markets than they do in the overall market. 
During 1997, new mortgages were originated for 4,201,287 dwelling 
units that qualified for the Low- and Moderate-Income Goal; the GSEs 
low-mod purchases financed 1,330,516 dwelling units, or only 32 
percent of the low-mod market. Similarly, the GSEs' purchases 
accounted for only 25 percent of the special affordable market and 
34 percent of the underserved areas market.\214\ Obviously, the GSEs 
are not leading the industry in financing units that qualify for the 
three housing goals.
BILLING CODE 4210-27-P

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BILLING CODE 4210-27-C
    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. As shown in 
Table A.7a, the GSEs accounted for 50 percent of the single-family 
owner market in 1997 but only 24 percent of the multifamily market 
and 14 percent of the single-family rental market (or a combined 
share of 20 percent of the rental market).
    Single-family Owner Market. This market is the bread-and-butter 
of the GSEs' business, and based on the financial and other factors 
discussed below, they 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 been lagging behind 
the market in their funding of single-family owner loans that 
qualify for the housing goals, as discussed in Section E.2.c. 
Between 1996 and 1998, low- and moderate-income borrowers accounted 
for 34.9 percent of Freddie Mac's mortgage purchases and 38.4 
percent of Fannie Mae's mortgage purchases, but 42.6 percent of 
primary market originations in metropolitan areas. The market share 
data reported in Table A.7. for the single-family owner market tell 
the same story. The GSEs' purchases of single-family owner loans 
represented 50 percent of all newly-originated owner loans in 1997, 
but only 43 percent of the low-mod loans that were originated, 35 
percent of the special affordable loans, and 48 percent of the 
underserved area loans. Thus, the GSEs 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 are not involved in almost two-thirds of special 
affordable owner market.
    Single-family Rental Market. Single-family rental housing is a 
major source of low- and moderate-income housing. As discussed in 
Appendix D, data on the size of the primary market for mortgages on 
these properties is limited, but information from the American 
Housing Survey on the stock of such units

[[Page 65129]]

and plausible rates of refinancing indicate that the GSEs are much 
less active in this market than in the single-family owner market. 
As shown in Table A.7a, HUD estimates that the GSEs' purchases have 
totaled only 14 percent of newly-mortgaged single-family rental 
units that were affordable to low- and moderate-income families.
    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 Department believes that there is room for such an enhanced 
role.
    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 five 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 17 percent all 
(single-family and multifamily) dwelling units financed during 
1997.215 By comparison, multifamily acquisitions 
represented 13.5 percent all units backing Fannie Mae's purchases of 
mortgages originated in 1997, with a corresponding figure of only 
8.8 percent for Freddie Mac.216 In other words, the GSEs 
place more emphasis on single-family mortgages than they do on 
multifamily mortgages.
    The GSEs role in the multifamily market is significantly smaller 
than in single-family. As shown in Table A.7a, the GSEs' purchases 
have accounted for only 24 percent of newly financed multifamily 
units during 1997--a market share much lower than their 50 percent 
share of the single-family owner market. Thus, these data suggest 
that a further enlargement of the GSEs' role in the multifamily 
market seems feasible and appropriate in the future.
    There are a number of submarkets, such as the market for 
mortgages on 5-50 unit multifamily properties, where the GSEs have 
particularly lagged the market. As mentioned above, the GSEs 
acquired loans representing 24 percent units multifamily units 
receiving conventional financing in 1997, but their acquisitions of 
loans on small multifamily properties represented only about 2 
percent of such properties financed that year. Certainly the GSEs 
face a number of challenges in better meeting the needs of the 
multifamily secondary 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. 
217 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.

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

    As discussed in Section C of this Appendix, the GSEs' single-
family mortgage acquisitions have generally followed the volume of 
originations in the primary market for conventional mortgages. 
However, in 1997, single-family originations rose by nearly 10 
percent, while the GSEs' acquisitions declined by 7 percent. As a 
result, the Office of Federal Housing Enterprise Oversight (OFHEO) 
estimates that the GSEs' share of single-family mortgage 
originations declined from 37 percent in 1996 to 32 percent in 1997. 
The GSEs' single-family mortgage share jumped to an estimated 43 
percent in 1998 and 42 percent in 1999, but that is still well below 
the peak of 51 percent attained in 1993.
    The GSEs' high shares of originations during the 1990s led to a 
rise in their share of total conventional single-family mortgages 
outstanding, including both conforming mortgages and jumbo 
mortgages.218 OFHEO estimates that the GSEs' share of 
such mortgages outstanding jumped from 34 percent at the end of 1991 
to 40 percent at the end of 1994 and an estimated 45 percent at the 
end of 1998.219 All of the increase in the GSEs' relative 
role between 1991 and 1998 was due to the growth in their portfolio 
holdings as a share of mortgages outstanding, from 5 percent at the 
end of 1991 to 17 percent at the end of 1998; relative holdings of 
the GSEs' mortgage-backed securities by others actually declined as 
a share of mortgages outstanding, from 29 percent at the end of 1991 
to 28 percent at the end of 1998.
    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, who accounted for 58 percent of all 
single-family loans in 1997, sell virtually all of their 
conventional conforming loans to the GSEs.220 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.221 
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. 
The GSEs, through their automated underwriting systems, have started 
adapting their underwriting for subprime loans and other loans that 
have not met their traditional underwriting standards.
    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. Congress realized the crucial role played 
by the GSEs' underwriting guidelines when it required each 
enterprise to submit a study on its guidelines to the Secretary and 
to Congress in 1993, and when it called for the Secretary to 
``periodically review and comment on the underwriting and appraisal 
guidelines of each enterprise.'' Some of the conclusions from a 
study of the GSEs' single-family underwriting guidelines prepared 
for the Department by the Urban Institute have been discussed in 
Section E.

c. State-of-the-Art Technology

    Both GSEs are in the forefront of new developments in mortgage 
industry technology. Each enterprise released an automated 
underwriting system in 1995--Freddie Mac's ``Loan Prospector'' and 
Fannie Mae's ``Desktop Underwriter.'' Both systems rely on numerical 
credit scores, such as those developed by Fair, Isaac, and Company, 
and additional data submitted by the borrower, to obtain a mortgage 
score. The mortgage score indicates to the lender either that the 
GSE will accept the mortgage, based on the application submitted, or 
that more detailed manual underwriting is required to make the loan 
eligible for GSE purchase.
    It is estimated that 25-40 percent of the GSEs' purchases were 
based on automated underwriting in 1999. These systems have also 
been adapted for FHA and jumbo loans. They have the potential to 
reduce the cost of loan origination, particularly for low-risk 
loans, but the systems are so new that no comprehensive studies of 
their effects have been conducted. As discussed earlier, concerns 
about the use of automated underwriting include the impact on 
minorities and the ``black box'' nature of the score algorithm.
    The GSEs are using their state-of -the-art technology in certain 
ways to help expand homeownership opportunities. For example, Fannie 
Mae has developed FannieMaps, a computerized mapping service offered 
to lenders, nonprofit organizations, and state and local governments 
to help them implement community lending programs.

[[Page 65130]]

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. 
They also contract with outside leaders in the finance industry for 
technical expertise not available in-house and for advice on a wide 
variety of issues.

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 has increased from $376 million in 1987 to $1.6 billion in 
1992, $3.1 billion in 1997, $3.4 billion in 1998 and $3.9 billion in 
1999--an average annual rate of increase of 22 percent. Through the 
fourth quarter of 1998, Fannie Mae has recorded 48 consecutive 
quarters of increased net income per share of common equity. Fannie 
Mae's return on equity averaged 24.0 percent over the 1995-99 
period--far above the rates achieved by most financial corporations.
    Investors in Fannie Mae's common stock have seen their annual 
dividends per share more than double since 1993, rising from $1.84 
to $4.32 in 1999. If dividends were fully reinvested, an investment 
of $1000 in Fannie Mae common stock on December 31, 1987 would have 
appreciated to $27,983.98 by December 31, 1997. This annualized 
total rate of return of 39.5 percent over the decade exceeded that 
of many leading U. S. corporations, including Intel (35.9 percent), 
Coca-Cola (32.4 percent), and General Electric (24.3 percent).
    Freddie Mac. Freddie Mac has shown similar trends. Freddie Mac's 
net income has increased from $301 million in 1987 to $622 million 
in 1992, $1.4 billion in 1997, $1.7 billion in 1998 and $2.2 billion 
in 1999--an average annual rate of increase of 18 percent. Freddie 
Mac's return on equity averaged 23.4 percent over the 1995-99 
period--also well above the rates achieved by most financial 
corporations.
    Investors in Freddie Mac's common stock have also seen their 
annual dividends per share more than double since 1993, rising from 
$0.88 to $2.40 in 1999. If dividends were fully reinvested, an 
investment of $1000 in Freddie Mac common stock on December 29, 1989 
would have appreciated to $8,670.20 by December 31, 1997, for an 
annualized total rate of return of 31.0 percent over this period. 
This was slightly higher than the annual return on Fannie Mae common 
stock (29.9 percent) and substantially higher than the average gain 
in the S&P Financial-Miscellaneous index (24.1 percent) over the 
1990-97 period.222
    Other indicators. Additional indicators of the strength of the 
GSEs are provided by various rankings of American corporations. One 
survey found that at the end of 1999 Fannie Mae was third of all 
companies in total assets and Freddie Mac ranked 14th.223 
Business Week has reported that among Standard & Poor's 500 
companies in 1999, Fannie Mae and Freddie Mac respectively ranked 
49th and 88th in market value, and 24th and 43rd in total 
profits.224

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 discussions with the 
Office of Federal Housing Enterprise Oversight, 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 established at 50 
percent of eligible units financed in each of calendar years 2001, 
2002 and 2003. This goal will remain in effect for 2004 and 
thereafter, unless changed by the Secretary prior to that time. The 
goal represents an increase over the 1996 goal of 40 percent and the 
1997-99 goal of 42 percent. These goals are in the lower portion of 
the range of market share estimates of 50-55 percent, presented in 
Appendix D. 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

    Data from the 1990 Census and the American Housing Surveys 
demonstrate that there are substantial housing needs among low- and 
moderate-income families, especially among lower-income and minority 
families in this group. Many of these households are burdened by 
high homeownership costs or rent payments and will likely continue 
to face serious housing problems, given the dim prospects for 
earnings growth in entry-level occupations. According to HUD's 
``Worst Case Housing Needs'' report, 21 percent of owner households 
faced a moderate or severe cost burden in 1997. Affordability 
problems were even more common among renters, with 40 percent paying 
more than 30 percent of their income for rent in 1997.225
    Single-family Mortgage Market. 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 seven 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. Between 1993 and 1999, record numbers 
of lower-income and minority families purchased homes. First-time 
homeowners have become a major driving force in the home purchase 
market over the past five years. Thus, the 1990s have seen the 
development of a strong affordable lending market. Despite this 
growth in affordable lending to minorities, disparities in the 
mortgage market remain. For example, African-American applicants are 
still twice as likely to be denied a loan as white applicants, even 
after controlling for income.
    Several demographic changes will affect the housing finance 
system over the next few years. First, the U.S. population is 
expected to grow by an average of 2.4 million per year over the next 
20 years, resulting in 1.1 to 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. However, the continued influx of immigrants will 
increase the demand for rental housing, while those who immigrated 
during the 1980's will be in the market for owner-occupied housing. 
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. With continued house price appreciation and favorable 
mortgage terms, ``trade-up buyers'' will increase their role in the 
housing market. These demographic trends will lead to greater 
diversity in the homebuying market, which will require adaptation by 
the primary and secondary mortgage markets.
    As a result of the above demographic forces, housing starts are 
expected to average 1.5 million units between 2000 and 2004, 
essentially the same as in 1996-99.226 Refinancing of 
existing mortgages, which accounted for 50 percent of originations 
in 1998 and 34 percent in 1999 are returning to lower levels during 
2000 and 2001 (16 and 12 percent respectively).
    Multifamily Mortgage Market. Since the early 1990s, the 
multifamily mortgage market has become more closely integrated with 
global capital markets, although not to the same degree as the 
single-family mortgage market. Loans on multifamily properties 
remain viewed as riskier than their single-family counterparts. 
Property values, vacancy rates, and market rents in multifamily 
properties appear to be highly correlated with local job market 
conditions, creating greater sensitivity of loan performance to 
economic conditions than may be experienced for single-family 
mortgages.
    Volatility during 1998 in the market for Commercial Mortgage 
Backed Securities (CMBS), an important source of financing for 
multifamily properties, underlines the need for an ongoing GSE 
presence in the multifamily secondary market. The potential for an 
increased GSE presence is enhanced

[[Page 65131]]

by virtue of the fact that an increasing proportion of multifamily 
mortgages is now originated in accordance with secondary market 
standards.
    The GSEs have the capability to increase the availability of 
long-term, fixed rate financing, thereby contributing greater 
liquidity in market segments where increased GSE presence can 
provide lenders with a more viable ``exit strategy'' than what is 
presently available. It appears that the cost of mortgage financing 
on properties with 5-50 units, where much of the nation's affordable 
housing stock is concentrated, may be higher than warranted by the 
degree of inherent credit risk.227 Presently, however, 
the GSEs purchase only about 5 percent of units in 5-50 unit 
properties financed annually. Borrowers have also experienced 
difficulty obtaining mortgage financing for multifamily properties 
with significant rehabilitation needs. Historically the flow of 
capital into multifamily housing for seniors has, moreover, been 
characterized by a great deal of volatility.

2. Past Performance and Ability To Lead the Industry

    The GSEs have played a major role in the conventional single-
family mortgage market in the 1990s. The GSEs' purchases of single-
family-owner mortgages accounted for 42 percent of mortgages 
originated in the single-family market during 1999. Many industry 
observers believe that the role of the GSEs in the late-1980s and 
1990s is a major reason why the decline of the thrift industry had 
only minor effects on the nation's housing finance system. 
Additionally, the American mortgage market was not impacted 
adversely in any way by the volatility in world financial markets in 
late 1998.
    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, including activities involving subprime mortgages and 
mortgages on manufactured housing.
    The GSEs' performance on the Low- and Moderate-Income Housing 
Goal has also improved significantly in recent years, as shown in 
Figure A.1. Fannie Mae's performance increased from 34.2 percent in 
1993 to 42.3 percent in 1995, 45.6 percent in 1996, and 45.7 percent 
in 1997, then falling slightly to 44.1 percent in 1998, but rising 
to 45.9 percent in 1999. Freddie Mac's performance also increased, 
from 29.7 percent in 1993 to 38.9 percent in 1995, 41.1 percent in 
1996, 42.6 percent in 1997, 42.9 percent in 1998, and 46.1 percent 
in 1999. Freddie Mac's low- and moderate-income shares were below 
Fannie Mae's shares in every year through 1998, but its goal 
performance slightly exceeded Fannie Mae's performance in 1999. This 
increase in Freddie Mac's relative performance on the Low- and 
Moderate-Income Housing Goal resulted from its increased role in the 
multifamily mortgage market and the increase in the goal-qualifying 
share of its single-family mortgages.
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    Single-family Affordable Lending Market. Despite these gains in 
goal performance, the Department remains concerned about the GSEs' 
support of lending for the lower-income end of the market. As shown 
in Figures A.2 and A.3, the lower-income shares of the GSEs' 
purchases are too low, particularly when compared with the 
corresponding shares for portfolio lenders and the primary market.

[[Page 65135]]

    This appendix has reached the following findings with respect to 
the GSEs' purchases of affordable loans for low- and moderate-income 
families and their communities.
     While Fannie Mae and Freddie Mac have both improved 
their support for the single-family affordable lending market over 
the past seven years, they have generally lagged the overall single-
family market in providing affordable loans to lower-income 
borrowers. This finding is based on HUD's analysis of GSE and HMDA 
data and on numerous studies by academics and research 
organizations.
     The GSEs show somewhat different patterns of mortgage 
purchases--through 1998, Freddie Mac was less likely than Fannie Mae 
to fund mortgages for lower-income families. As a result, the 
percentage of Freddie Mac's purchases benefiting historically 
underserved families and their neighborhoods was less than the 
corresponding shares of total market originations, while Fannie 
Mae's purchases were closer to the patterns of originations in the 
primary market (see Figure A.3). However, in 1999, Freddie Mac's 
purchases of home loans included a higher percentage of low-mod 
loans than Fannie Mae's purchases (40.0 percent and 39.3 percent, 
respectively). It remains to be seen whether this represents a new 
trend for Freddie Mac, or a temporary reversal of the pattern for 
the 1996-98 period.
     A study by The Urban Institute of lender experience 
with the GSEs' underwriting guidelines finds that the enterprises 
had stepped up their outreach efforts and increased the flexibility 
in their standards to better accommodate the special circumstances 
of lower-income borrowers. However, this study concluded that the 
GSEs' guidelines remain somewhat inflexible and that the enterprises 
are often hesitant to purchase affordable loans. Lenders also told 
The Urban Institute that Fannie Mae has been more aggressive than 
Freddie Mac in market outreach to underserved groups, in offering 
new affordable products, and in adjusting its underwriting 
standards.
     A large percentage of the lower-income loans purchased 
by the enterprises have relatively high down payments, which raises 
questions about whether the GSEs are adequately meeting the needs of 
lower-income families have difficulty raising enough cash for a 
large down payment.
     There are important parts of the single-family market 
where the GSEs have played a minimal role. For example, single-
family rental properties are an important source of low-income 
housing, but they represent only a small portion of the GSEs' 
business. GSE purchases have accounted for only 14 percent of the 
single-family rental units that received financing in 1997. An 
increased presence by Fannie Mae and Freddie Mac would bring lower 
interest rates and liquidity to this market, as well as improve 
their goals performance.
     The above points can be summarized by examining the 
GSEs' share of the single-family mortgage market. The GSEs' total 
purchases have accounted for 44 percent of all single-family (both 
owner and rental) units financed during 1997; however, their low-mod 
purchases have accounted for only 34 percent of the low- and 
moderate-income single-family units that were financed during that 
year.
    In conclusion, the Department's analysis suggests that the GSEs 
are not leading the single-family market in purchasing loans that 
qualify for the Low- and Moderate-Income Goal. There is room for 
Fannie Mae and Freddie Mac to improve their performance in 
purchasing affordable loans at the lower-income end of the market. 
Moreover, evidence suggests that there is a significant population 
of potential homebuyers who might respond well to aggressive 
outreach by the GSEs. Specifically, both Fannie Mae and the Joint 
Center for Housing Studies expect immigration 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.
    Multifamily Market. 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.228
    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 $7.6 billion in 1999. As a 
result, concerns regarding Freddie Mac's multifamily capabilities no 
longer constrain their performance with regard to low- and moderate-
income families in the manner that prevailed at the time of the 
December 1995 rule.
    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. Holding 12.8 percent of the outstanding stock of 
multifamily mortgage debt and guarantees as of the end of 1999, 
Fannie Mae is regarded as an influential force within the 
multifamily market. Fannie Mae's multifamily underwriting standards 
have been widely emulated throughout the multifamily mortgage 
market.
    The increased role of Fannie Mae and Freddie Mac in the 
multifamily market has 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 Table A.7a, the GSEs' purchases (through 1999) have accounted for 
only 24 percent of the multifamily units that received financing 
during 1997. Standard & Poor's recently described both GSEs' 
multifamily lending as ``extremely conservative.'' 229 In 
particular, their multifamily purchases to date do not appear to be 
contributing to mitigation of the excessive cost of mortgage 
financing for small multifamily properties, nor have the GSEs 
demonstrated market leadership with regard to rehabilitation loans, 
a segment where financing has sometimes been difficult to obtain. In 
conclusion, it appears that both GSEs can make improvements in their 
underwriting policies and procedures and introduce new products that 
will enable them to more effectively serve segments of the 
multifamily market that can benefit from greater liquidity.

3. 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 50 to 55 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 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.

4. The Low- and Moderate-Income Housing Goals for 2001-03

    There are several reasons why the Secretary is increasing the 
Low- and Moderate-Income Housing Goal from 42 percent in 1997-99 to 
50 percent of eligible units financed in each of calendar years 
2001, 2002 and 2003.
    First, when the 1996-99 goals were established in December 1995, 
Freddie Mac had only recently reentered the multifamily mortgage 
market, after its absence in the early 1990s. Freddie Mac has 
rebuilt its multifamily acquisition program over the past several 
years, with its 1999 purchases at a level more than eight times what 
they were in 1994 (in dollar terms). The limited role of Freddie Mac 
in the multifamily market was a significant constraint in setting 
the Low- and Moderate-Income Housing Goals for 1996-99. Freddie 
Mac's return as a major participant in the multifamily market was an 
important factor in the improvement in its performance on the Low- 
and Moderate-Income Housing Goal, as shown in Figure A.1, and it 
removes an impediment to higher goals for both GSEs. These goals 
will create new opportunities for the GSEs to further step up their 
support of mortgages on properties with rents affordable to low- and 
moderate-income families. However, as discussed in the Preamble, to 
encourage Freddie Mac to further step up its role in the multifamily 
market, the Secretary is proposing a ``temporary adjustment factor'' 
for its purchases of loans on properties with more than 50 units. 
Specifically, each unit in such properties would be weighted as 1.2 
units in the numerator of the housing goal percentage for both the 
Low and Moderate Income Goal and the Special Affordable Housing Goal 
for the years 2001-2003.

[[Page 65136]]

    Second, the single-family affordable market had only recently 
begun to grow in 1993 and 1994, the latest period for which data was 
available when the 1996-99 goals were established in December 1995. 
But the historically high low-and moderate-income share of the 
primary mortgage market attained in 1994 has been maintained over 
the 1995-98 period. The three-year average estimate of the low- and 
moderate-income share of the single-family owner mortgage market was 
38 percent for 1992-94, but 42 percent for 1995-98 and 41 percent 
for the 1992-98 period as a whole. The continued high affordability 
of housing suggests that a strong low-income market continued for a 
sixth straight year in 1999. Current economic forecasts suggest that 
housing affordability could be maintained in the post-2000 period, 
leading to additional opportunities for the GSEs to support mortgage 
lending benefiting low- and moderate-income families.\230\ And 
various surveys indicate that the demand for homeownership by 
minorities, immigrants, and younger households will remain strong 
for the foreseeable future.
    Although single-family owner 1-unit properties comprise the 
``bread-and-butter'' of the GSEs' business, evidence presented above 
demonstrates that the shares of their loans for low- and moderate-
income families taking out loans on such properties lag the 
corresponding shares for the primary market. For example, in 1997 
the Department finds that these shares amounted to 34.1 percent for 
Freddie Mac, 37.6 percent for Fannie Mae, and 42.5 percent for the 
primary market; as shown in Figure A.3, a similar pattern holds for 
1998. Thus 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 
outreach efforts, (2) their incorporation of greater flexibility 
into their underwriting guidelines, (3) their purchases of seasoned 
CRA loans, (4) their entry into new single-family mortgage markets 
such as loans on manufactured housing, (5) their increased purchases 
of loans on small multifamily properties, and (6) their increased 
presence in other rental markets where they have had only a limited 
presence in the past.
    Third, one particular area where the GSEs could play a greater 
role is in the mortgage market for single-family rental dwellings. 
These properties, containing 1-4 rental units, are an important 
source of housing for low- and moderate-income families, but the 
GSEs have not played a major role in this mortgage market--they 
accounted for only 6.5 percent of units financed by Fannie Mae and 
6.4 percent of units financed by Freddie Mac in 1997. The Department 
believes that the GSEs' role in financing loans on such properties, 
which are generally owned by ``mom and pop'' businesses, can and 
should be enhanced, though it recognizes that single-family rental 
properties are very heterogeneous, making it more difficult to 
develop standardized underwriting standards for the secondary 
market. But the Secretary believes that the GSEs can do more to play 
a leadership role in providing financing for such properties.\231\
    Finally, a wide variety of quantitative and qualitative 
indicators indicate that the GSEs' have the financial strength to 
improve their affordable lending performance. For example, combined 
net income has risen steadily over the last decade, from $1.244 
billion in 1989 to $6.135 billion in 1999, an average annual growth 
rate of 17 percent per year. This financial strength provides the 
GSEs with the resources to lead the industry in supporting mortgage 
lending for units affordable to low- and moderate-income families.
    Summary. Figure A.7a 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 have provided financing for 2,948,712 (or 
40 percent) of the 7,306,950 single-family and multifamily units 
that were financed in the conventional conforming market during 
1997. However, in the low- and moderate-income part of the market, 
the 1,330,516 units that were financed by GSE purchases represented 
only 32 percent of the 4,201,287 dwelling units that were financed 
in the market. Thus, there appears to 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.
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5. Conclusions

    Having considered the projected mortgage market serving low- and 
moderate-income families, economic, housing and demographic 
conditions for 2001-03, and the GSEs' recent performance in 
purchasing mortgages for low- and moderate-income families, the 
Secretary has determined that the annual goal of 50 percent of 
eligible units financed in each of calendar years 2001, 2002 and 
2003 is feasible. Moreover, the Secretary has considered the GSEs' 
ability to lead the industry as well as the GSEs' financial 
condition. The Secretary has determined that the goal is necessary 
and appropriate.

Endnotes to Appendix A

    \1\ See ``Freddie's Subprime Wrap Business Blooms in 1999'', 
Inside B&C Lending, December 27, 1999, pages 8-9.
    \2\ 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.
    \3\ U.S. Department of Housing and Urban Development, Office of 
Federal Housing Enterprise Oversight, ``Risk-Based Capital'' (Notice 
of Proposed Rulemaking), Federal Register, April 13, 1999, p. 18116.
    \4\ Fannie Mae (2000), p. 102.
    \5\ OFHEO NPR, Ibid. 
    \6\ Mortgage denial rates are based on 1998 HMDA data; 
manufactured housing lenders are excluded from these comparisons.
    \7\ U.S. Department of Housing and Urban Development. Rental 
Housing Assistance--The Worsening Crisis: A Report to Congress on 
Worst Case Housing Needs. (March 2000).
    \8\ ``Final Report of Standard & Poor's to the Office of Federal 
Housing Enterprise Oversight,'' February 3, 1997; Freddie Mac, 1998 
Annual Report to Shareholders, p. 6.
    \9\ Freddie Mac reported delinquency rates of 0.14% for 
multifamily and 0.39% for single-family in 1999 (1999 Annual Report 
to Shareholders, p. 23.) Fannie Mae reported ``serious delinquency 
rates'' of 0.12% for multifamily and 0.48% for single-family in 1999 
(1999 Annual Report to Shareholders, p. 27).
    \10\ According to the National Association of Realtors, Housing 
Market Will Change in New Millennium as Population Shifts, (November 
7, 1998), 45 percent of U.S. household wealth is in the form of home 
equity in 1998. Since 1968, home prices have increased each year, on 
average, at the rate of inflation plus up to two percentage points.
    \11\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 2000. (2000), p. 9.
    \12\ Joint Center for Housing Studies of Harvard University. 
(2000), p. 33.
    \13\ Michelle J. White, and Richard K. Green. ``Measuring the 
Benefits of Homeowning: Effects on Children,'' Journal of Urban 
Economics. 41 (May 1997), pp. 441-61. Also see ``The Social Benefits 
and Costs of Homeownership: A Critical Assessment of the Research,'' 
Working Paper No. 00-01, Research Institute for Housing America, May 
2000.
    \14\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 1998 (1998).
    \15\ Howard Savage and Peter Fronczek, Who Can Afford to Buy A 
House in 1991?, U.S. Bureau of the Census, Current Housing Reports 
H121/93-3, (July 1993), p. ix.
    \16\ Donald S. Bradley and Peter Zorn. ``Fear of Homebuying: Why 
Financially Able Households May Avoid Ownership,'' Secondary 
Mortgage Markets (1996).
    \17\ Munnell, Alicia H., Geoffrey M. B. Tootell, Lynn E. Browne, 
and James McEneaney, ``Mortgage Lending in Boston: Interpreting HMDA 
Data,'' American Economic Review. 86 (March 1996).
    \18\ William C. Hunter. ``The Cultural Affinity Hypothesis and 
Mortgage Lending Decisions,'' WP-95-8, Federal Reserve Bank of 
Chicago, (1995). In addition, a study undertaken for HUD also found 
higher denial rates among FHA borrowers for minorities after 
controlling for credit risk. See Ann B. Schnare and Stuart A. 
Gabriel. ``The Role of FHA in the Provision of Credit to 
Minorities,'' ICF Incorporated, Prepared for the U.S. Department of 
Housing and Urban Development, (April 25, 1994).
    \19\ See Charles W. Calomiris, 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.''
    \20\ The FICO score, developed by Fair, Isaac and Company, is 
summary index of an individual's credit history. The FICO score is 
based on elements from the applicant's credit report, such as number 
of delinquencies in the past year, number of trade lines, and the 
amount owed on trade lines as compared to the available maximum 
credit limits. The FICO score is said to reflect the credit risk of 
the applicant and a score of 620 is often cited as a threshold 
between being an acceptable and an unacceptable credit risk.
    \21\ Section 3.b of this appendix provides a further discussion 
of automated underwriting.
    \22\ 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).
    \23\ Rental Housing Assistance--The Worsening Crisis: A Report 
to Congress on Worst Case Housing Needs, Department of Housing and 
Urban Development, (March 2000), p. i. All statistics in this 
subsection are taken from this report, except as noted.
    \24\ Very low-income households are defined in the report as 
those whose income, adjusted for family size, is less than 50 
percent of 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.
    \25\ Edward N. Wolff, ``Recent Trends in the Size Distribution 
of Household Wealth,'' The Journal of Economic Perspectives, 12( 3), 
(Summer 1998), p. 137.
    \26\ Joint Center for Housing Studies, The State of the Nation's 
Housing: 2000, June 2000, p. 24.
    \27\ Rent is measured in this report as gross rent, defined as 
contract rent plus the cost of any utilities which are not included 
in contract rent.
    \28\ 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).
    \29\ One program that shows promise is Fannie Mae's HomeStyle 
Home Improvement Mortgage Loan Product. Under this program, Fannie 
Mae will purchase mortgages that finance the purchase and 
rehabilitation of 1- to 4-unit properties in ``as-is'' condition. 
The mortgage amount is limited to 90 percent of the appraised ``as-
completed'' value, with the rehab amount not to exceed 50 percent of 
this value.
    \30\ See Drew Schneider and James Follain, ``A New Initiative in 
the Federal Housing Administration's Office of Multifamily Housing 
Programs: An Assessment of Small Projects Processing,'' Cityscape: A 
Journal of Policy Development and Research 4 (1), (1998), pp. 43-58; 
and William Segal and Christopher Herbert, Segmentation of the 
Multifamily Mortgage Market: The Case of Small Properties, paper 
presented to annual meetings of the American Real Estate and Urban 
Economics Association, (January 2000).
    \31\ These costs have been estimated at $30,000 for a typical 
transaction. Presentation by Jeff Stern, Vice President, Enterprise 
Mortgage Investments, HUD GSE Working Group, July 23, 1998. The most 
comprehensive account of the multifamily housing finance system as 
it relates to small properties is contained in Schneider and Follain 
(see above reference).
    \32\ This measure is discussed in Paul B. Manchester, ``A New 
Measure of Labor Market Distress,'' Challenge, (November/December 
1982).
    \33\ 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.
    \34\ All of the home sales data in this section are obtained 
from U.S. Housing Market Conditions, 1st Quarter 2000, U.S. 
Department of Housing and Urban Development, (May 2000).
    \35\ Existing home sales, housing starts, housing affordability 
and 30-year fixed rate mortgage rate forecasts are obtained from 
Standard & Poor's DRI, The U.S. Economy. (June 2000), pp. 55-7. 
While DRI provides forecasts through 2004, one should obviously 
interpret them with care.
    \36\ Real GDP, unemployment, inflation, and treasury note 
interest rate projections are obtained for fiscal years 2000-2009 
from The Economic and Budget Outlook: An Update, Washington DC: 
Congressional Budget Office, (July 2000).
    \37\ Standard & Poor's DRI, The U.S. Economy. (June 2000), pp. 
31 and 56.
    \38\ Standard & Poor's DRI, The U.S. Economy. (June 2000), p. 
56.
    \39\ Mortgage Bankers Association of America. MBA Mortgage 
Finance Forecast, (July 14, 2000).
    \40\ Fannie Mae. Berson's Housing and Economic Report, (June 
2000).
    \41\ National Association of Realtors. Housing Market Will 
Change in New

[[Page 65139]]

Millennium as Population Shifts. (November 7, 1998).
    \42\ Homeownership rates do not peek until population groups 
reach 65 to 74 years of age. Since the baby-boom population is such 
a large cohort, even though they will be past their homebuying peak, 
it is possible they will still have an impact.
    \43\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 2000. (2000), p. 11.
    \44\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 1998. (1998), p. 14.
    \45\ Joint Center for Housing Studies of Harvard University. 
(1998), p. 15.
    \46\ National Association of Realtors. Housing Market Will 
Change in New Millennium As population Shifts. (November 7, 1998).
    \47\ Joint Center for Housing Studies of Harvard University. 
(1998).
    \48\ John R. Pitkin and Patrick A. Simmons. ``The Foreign-Born 
Population to 2010: A Prospective Analysis by Country of Birth, Age, 
and Duration of U.S. Residence,'' Journal of Housing Research. 7(1) 
(1996), pp. 1-31.
    \49\ Fred Flick and Kate Anderson. ``Future of Housing Demand: 
Special Markets,'' Real Estate Outlook. (1998), p. 6.
    \50\ Mark A. Calabria. ``The Changing Picture of Homebuyers,'' 
Real Estate Outlook. (May 1999), p. 10.
    \51\ Chicago Title and Trust Family of Insurers, Who's Buying 
Homes in America. (2000).
    \52\ Chicago Title and Trust Family of Insurers, Who's Buying 
Homes in America. (1998 and 2000).
    \53\ Calabria. (May 1999), p. 11.
    \54\ U.S. Census Bureau, Current Population Reports, P60-206, 
Money Income in the United States: 1998, U.S. Government Printing 
Office, Washington, DC, (1999).
    \55\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 1998. (1998).
    \56\ Data for 1990-97 from U.S. Housing Market Conditions, 1st 
Quarter 1999, U.S. Department of Housing and Urban Development, (May 
1999), Table 17; data for 1998-99 from the Mortgage Bankers 
Association.
    \57\ 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.
    \58\ U.S. Housing Market Conditions, 1st Quarter 2000, (May 
2000), Table 14.
    \59\ All statistics in this section are taken from the Federal 
Housing Finance Board's MIRS.
    \60\ 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).
    \61\ 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.
    \62\ Refinancing data is taken from Freddie Mac's monthly 
Primary Mortgage Market Survey.
    \63\ 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.
    \64\ Housing affordability varies markedly between regions, 
ranging in May 2000 from 147 in the Midwest to 93 in the West, with 
the South and Northeast falling in between.
    \65\ Fannie Mae, http://www.fanniemae.com/news/housingsurvey/1998, (July 16, 1998).
    \66\ 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).
    \67\ Chicago Title and Trust Family of Insurers, Who's Buying 
Homes in America, (1998).
    \68\ Single-family originations rose by 10 percent in dollar 
terms in 1997, but the Mortgage Bankers Association estimates that 
they fell by 0.6 percent in terms of the number of loans.
    \69\ Mortgage market projections obtained from the MBA's MBA 
Mortgage Finance Forecast, (July 14, 2000).
    \70\ Fannie Mae. Berson's Housing and Economic Report, (June 
2000).
    \71\ Speech before the annual convention of the National 
Association of Home Builders in Dallas TX, (January 1999).
    \72\ Fannie Mae News Release (January 1999).
    \73\ Freddie Mac News Release (January 15, 1999).
    \74\ Standard underwriting procedures characterize a property in 
a declining neighborhood as one at high risk of losing value. 
Implicitly, these underwriting standards presume that the real 
estate market is inefficient in economic terms, that is, prices do 
not reflect all available information.
    \75\ For an update of this analysis to include 1998, see Randall 
M. Scheessele, 1998 HMDA Highlights, Housing Finance Working Paper 
HF-009, Office of Policy Development and Research, U.S. Department 
of Housing and Urban Development, (October 1999).
    \76\ The ``overall'' market is defined as all loans (including 
both government and conventional) below the 1997 conforming loan 
limit of $214,600 and the 1998 conforming loan limit of $227,150.
    \77\ The percentages reported in Table A.1a for the year 1998 
are similar; in that year, low-income borrowers accounted for 49.1 
percent of FHA-insured loans, 23.9 percent of GSE purchases, and 
27.8 percent of home purchase mortgages originated in the 
conventional conforming market.
    \78\ FHA, which focuses on first-time homebuyers and low down 
payment loans, 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.
    \79\ FHA's role in the market is particularly important for 
African-American and Hispanic borrowers. As shown in Table A.1c, FHA 
insured 44 percent of all 1997 home loan originations for these 
borrowers.
    \80\ It should be noted that Tables A.1a and A.1b include only 
the GSEs' purchases of conventional loans; the same tables in the 
proposed rule also included the GSEs' purchases of government 
(particularly FHA-insured) loans.
    \81\ 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).
    \82\ However, as shown in Table A.1a, depository institutions 
resemble other conventional lenders in their relatively low level of 
originating loans for African-American, Hispanic and minority 
borrowers.
    \83\ For an analysis of the impact of CRA agreements signed by 
lending institutions, see Alex Schwartz, ``From Confrontation to 
Collaboration? Banks, Community Groups, and the Implementation of 
Community Reinvestment Agreements'', Housing Policy Debate, 9(3), 
(1998), pp. 631-662. Also see the Department of Treasury CRA study 
by Litan et al., op cit.
    \84\ ``With Securities Market Back on Track, Analysts Expect 
Surge in CRA Loan Securitization in 1999,'' Inside MBS & ABS. 
(February 19, 1999), pp. 11-12.
    \85\ Inside MBS & ABS. (February 19, 1999), p. 12.
    \86\ Fannie Mae. 1997 Annual Housing Activities Report, (1998), 
p. 28.
    \87\ For an analysis of the GSEs' CRA purchases, see the HUD-
sponsored study by the Urban Institute, An Assessment of Recent 
Innovations in the Secondary Market for Low- and Moderate-Income 
Lending, by Kenneth Temkin, Jennifer E.H. Johnson, and Charles 
Calhoun, March 2000.
    \88\ George Galster, Laudan Y. Aron, Peter Tatain and Keith 
Watson. Estimating the Size, Characteristics, and Risk Profile of 
Potential Homebuyers. Washington: The Urban Institute, (1995). 
Report Prepared for the Department of Housing and Urban Development.
    \89\ Fannie Mae Foundation. African American and Hispanic 
Attitudes on Homeownership: A Guide for Mortgage Industry Leaders, 
(1998), p. 3.
    \90\ Fannie Mae Foundation. (1998), p. 14.
    \91\ Robert B. Avery, Raphael W. Bostic, Paul S. Calem, and 
Glenn B. Canner, Credit Scoring: Issues and Evidence from Credit 
Bureau Files, mimeo., (1998).
    \92\ Avery et al. (1998), p. 24.
    \93\ Kenneth Temkin, Roberto Quercia, George Galster, and Sheila 
O'Leary, A Study of the GSEs' Single Family Underwriting Guidelines: 
Final Report. Washington DC:

[[Page 65140]]

U.S. Department of Housing and Urban Development, (April 1999). This 
study involves an analysis of the GSEs' underwriting guidelines in 
general. This section reviews only the aspects of the study related 
to mortgage scoring. A broader review of this paper is provided 
below in section E.4.
    \94\ Temkin, et al. (1999), p. 2.
    \95\ Temkin, et al. (1999), p. 5; pp. 26-27.
    \96\ Standard & Poor's B and C mortgage guidelines can be used 
to illustrate that underwriting criteria in the subprime market 
becomes more flexible as the grade of borrower moves from the most 
creditworthy A-borrowers to the riskier D borrowers. For Example, 
the A-grade borrower is allowed to be delinquent 30 days on his 
mortgage twice in the last year whereas the D grade borrower is 
allowed to be delinquent 30 days on his mortgage credit five times 
in the last year. Moreover, the A-borrower is permitted to have a 45 
percent debt-to-income ratio compared to the D grade borrower's 60 
percent.
    \97\ ``Subprime Product Mix, Strategies Changed During a 
Turbulent 1998,'' Inside B&C Lending. (December 21, 1998), p. 2.
    \98\ ``Renewed Attack on `Predatory' Subprime Lenders.'' Fair 
Lending/CRA Compass, (June 1999) and http://cra-cn.home.mindspring.com. 
    \99\ See Randall M. Scheessele. 1998 HMDA Highlights, Housing 
Finance Working Paper HF-009, Office of Policy Development and 
Research, U.S. Department of Housing and Urban Development, (October 
1999). Nonspecialized lenders such as banks and thrifts also make 
subprime loans, but no data is available to estimate the number of 
these loans.
    \100\ Freddie Mac, We Open Doors for America's Families, Freddie 
Mac's Annual Housing Activities Report for 1997, (March 16, 1998), 
p. 23.
    \101\ The statistics cited for the ``market'' refer to all 
conforming conventional mortgages (both home purchase and 
refinance). The data for the subprime market are for 200 lenders 
that specialize in such loans; see Scheessele, op. cit. 
    \102\ Alternative--A (or Alt--A) mortgages are made to prime 
borrowers who desire low down payments or do not want to provide 
full documentation for loans.
    \103\ Freddie Mac and Standard & Poor's tested the new module in 
a pilot during early 1996 and marketed it to lenders at the end of 
that year.
    \104\ See ``Freddie's Subprime Wrap Business Blooms in 1999'', 
Inside B&C Lending, December 27, 1999, pages 8-9.
    \105\ David A. Andrukonis, ``Entering the Subprime Arena,'' 
Mortgage Banking, May 2000, pages 57-60.
    \106\ The figures include their purchases of Alt A mortgages. 
Inside B&C Lending, May 22, 2000, page 12.
    \107\ See Lederman, et al., op cit.
    \108\ For an explanation of the GSEs funding advantage see 
``Government Sponsorship of FNMA and FHLMC,'' United States 
Department of the Treasury, July 11, 1996.
    \109\ A detailed discussion of manufactured housing is contained 
in Kimberly Vermeer and Josephine Louie, The Future of Manufactured 
Housing, Joint Center for Housing Studies, Harvard University, 
(January 1997).
    \110\ Data on industry shipments and sales has been obtained 
from ``U.S. Housing Market Conditions,'' U.S. Department of Housing 
and Urban Development (May, 2000), p. 49.
    \111\ Although the terms are sometimes used interchangeably, 
manufactured housing and mobile homes differ in significant ways 
relative to construction standards, mobility, permanence, and 
financing (These distinctions are spelled out in detail in Donald S. 
Bradley, ``Will Manufactured Housing Become Home of First Choice?'' 
Secondary Mortgage Markets, (July 1997)). Mobile homes are not 
covered by national construction standards, though they may be 
subject to State or local siting requirements. Manufactured homes 
must be built according to the National Manufactured Housing 
Construction Safety and Standards Act of 1974. In accordance with 
this act, HUD developed minimum building standards in 1976 and 
upgraded them in 1994. Manufactured homes, like mobile homes, are 
constructed on a permanent chassis and include both axles and 
wheels. However, with manufactured housing, the axles and wheels are 
intended to be removed at the time the unit is permanently affixed 
to a foundation. Manufactured homes, unlike mobile homes, are 
seldom, if ever, moved. Mobile homes are financed with personal 
property loans, but manufactured homes are eligible for 
conventional-mortgage financing if they are located on land owned by 
or under long-term lease to the borrower. Other types of factory-
built housing, such as modular and panelized homes, are not included 
in this definition of ``manufactured housing.'' These housing types 
are often treated as ``site built'' for purposes of eligibility for 
mortgage financing.
    \112\ Freddie Mac, the Manufactured Housing Institute and the 
Low Income Housing Fund have formed an alliance to utilize 
manufactured housing along with permanent financing and secondary 
market involvement to bring affordable, attractive housing to 
underserved, low- and moderate-income urban neighborhoods. 
Origination News. (December 1998), p. 18.
    \113\ Mortgage-Backed Securities Letter. (September 7, 1998), p. 
3.
    \114\ The Mortgage Market Statistical Annual for 2000 
(Washington, DC: Inside Mortgage Finance Publications), 1, 286. A 
conventional multifamily mortgage market of $46 billion is assumed 
in this calculation. B and C mortgages are excluded from the 
calculation.
    \115\ The Mortgage Market Statistical Annual for 2000 
(Washington, DC: Inside Mortgage Finance Publications), 1, 286. A 
conventional multifamily mortgage market of $46 billion is assumed 
in this calculation. B and C mortgages are excluded from the 
calculation.
    \116\ This calculation incorporates GSE multifamily transactions 
involving loans originated during 1997 and acquired during 1997-
1999. A multifamily conventional origination market of $38 billion 
and a per-unit loan amount of $27,266 is assumed per Appendix D.
    \117\ Jean L. Cummings and Denise DiPasquale, ``Developing a 
Secondary Market for Affordable Rental Housing: Lessons From the 
LIMAC/Freddie Mac and EMI/Fannie Mae Programs,'' Cityscape: A 
Journal of Policy Development and Research, 4(1), (1998), pp. 19-41.
    \118\ Drew Schneider and James Follain assert that interest 
rates on small property mortgages are as high as 300 basis points 
over comparable maturity Treasuries in ``A New Initiative in the 
Federal Housing Administration's Office of Multifamily Housing 
Programs: An Assessment of Small Projects Processing,'' Cityscape: A 
Journal of Policy Development and Research 4(1): 43-58, 1998. 
Berkshire Realty, a Fannie Mae Delegated Underwriting and Servicing 
(DUS) lender based in Boston, was quoting spreads of 135 to 150 
basis points in ``Loans Smorgasbord,'' Multi-Housing News, August-
September 1996. Additional information on the interest rate 
differential between large and small multifamily properties is 
contained in William Segal and Christopher Herbert, Segmentation of 
the Multifamily Mortgage Market: The Case of Small Properties, paper 
presented to annual meetings of the American Real Estate and Urban 
Economics Association, (January 2000).
    \119\ On the relation between age of property and quality 
classification see Jack Goodman and Brook Scott, ``Rating the 
Quality of Multifamily Housing,'' Real Estate Finance, (Summer, 
1997).
    \120\ W. Donald Campbell. Seniors Housing Finance, prepared for 
American Association of Retired Persons White House Conference on 
Aging Mini-Conference on Expanding Housing Choices for Older People, 
(January 26-27, 1995).
    \121\ 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), p. 154.
    \122\ Despite sustained economic expansion, however, the rise in 
homeownership, has not fallen below 9 percent in recent years. 
(Regis J. Sheehan, ``Steady Growth,'' Units, (November/December 
1998), pp. 40-43). Regarding rents and vacancy rates see also Ted 
Cornwell. ``Multifamily Lending Approaches Record Level,'' National 
Mortgage News, (September 23, 1996); and David Berson, Monthly 
Economic and Mortgage Market Report, Fannie Mae, (November 1998).
    \123\ American Council of Life Insurance data reported in Inside 
MBS & ABS, (March 20, 1998).
    \124\ A November, 1998 ``Review of the Short-Term Supply/Demand 
Conditions for Apartments'' by Peter P. Kozel of Standard and Poor's 
concludes that ``in some markets, the supply of units exceeds the 
likely level of demand, and in only a few MSAs should the pace of 
development accelerate.'' See also ``Apartment Projects Find Lenders 
Are Ready with Financing,'' Lew Sichelman, National Mortgage News, 
(April 14, 1997); Commercial Lenders Warned That They Could Spur 
Overbuilding, National Mortgage News, (March 30, 1998); 
``Multifamily, Commercial Markets Grow Up,'' Neil Morse, Secondary 
Marketing Executive, (February 1998);''

[[Page 65141]]

``Recipe for Disaster,'' National Mortgage News editorial, (July 6, 
1998).
    \125\ 1998 Survey of Credit Underwriting Practices, Comptroller 
of the Currency, National Credit Committee. ``For the fourth 
consecutive year, underwriting standards for commercial loans have 
eased,'' states the OCC report. ``Examiners again cite competitive 
pressure as the primary reason for easing underwriting standards.'' 
The weakening of underwriting practices is especially concentrated 
in commercial real estate lending according to a the Federal Deposit 
Insurance Corporation's Report on Underwriting Practices, (October 
1997-March 1998). See also Donna Tanoue, ``Underwriting Concerns 
Grow,'' National Mortgage News, (September 21, 1998), and ``Making 
the Risk-Takers Pay,'' National Mortgage News, (October 12, 1998).
    \126\ On the effects of multifamily mortgage securitization see 
``Financing Multifamily Properties: A Play With new Actors and New 
Lines,'' Donald S. Bradley, Frank E. Nothaft, and James L. Freund, 
Cityscape, A Journal of Policy Development and Research, vol. 4, No. 
1 (1998); and ``Financing Multifamily Properties,'' Donald S. 
Bradley, Frank E. Nothaft, and James L. Freund, Urban Land (November 
1998).
    \127\ CMBS Database, Commercial Mortgage Alert, Harrison-Scott 
Publications, Hoboken, NJ.
    \128\ ``New CMBS Headache: B-Piece Market Softens,'' Commercial 
Mortgage Alert, (September 21, 1998); ``Criimi Bankruptcy 
Accelerates CMBS Freefall,'' Commercial Mortgage Alert, (October 12, 
1998); ``Capital America Halts Lending Amid Woes,'' Commercial 
Mortgage Alert, (October 12, 1998).
    \129\ On CMBS spreads see ``Turmoil Hikes Loan Rates'' in Wall 
Street Mortgage Report, (September 14, 1998). Regarding implications 
for the GSEs of the conduit pullback see ``No Credit Crunch for 
First Mortgages'' in Commercial Mortgage Alert, (October 12, 1998).
    \130\ ``Financing Multifamily Properties: A Play With New Actors 
and New Lines,'' Donald S. Bradley, Frank E. Nothaft, and James L. 
Freund, Cityscape: A Journal of Policy Development and Research, 
4(1), (1998).
    \131\ The Impact of Public Capital Markets on Urban Real Estate, 
Clement Dinsmore, discussion paper, Brookings Institution Center on 
Urban and Metropolitan Policy, July 1998; ``Capital Availability 
Fuels Commercial Market Growth,'' Marshall Taylor, Real Estate 
Finance Today, (February 17, 1997).
    \132\ Board of Governors of the Federal Reserve System and U.S. 
Securities and Exchange Commission, Report to the Congress on 
Markets for Small-Business-and Commercial-Mortgage-Backed 
Securities, (September 1998).
    \133\ ``REITs Tally Nearly Half of All Big CRE Deals in First 
Quarter,'' National Mortgage News, (July 7, 1997); ``Will REITs, 
Mortgage-Backeds Make Difference in Downturn,'' Jennifer Goldblatt, 
American Banker, (February 18, 1998).
    \134\ ``Apartment Demographics: Good for the Long Haul?'' Jack 
Goodman, Real Estate Finance, (Winter 1997); ``The Multifamily 
Outlook,'' Jack Goodman, Urban Land, (November 1998).
    \135\ U.S. Housing Market Conditions, U.S. Department of Housing 
and Urban Development (May 2000), Table 4.
    \136\ Howard Esaki, a principal in CMBS Research at Morgan 
Stanley Dean Witter stated at a recent conference that volatility in 
global markets contributed to a 10-20 percent decline in commercial 
real estate values in late 1998. John Hackett, ``CRE Seen Down 10% 
to 20%,'' National Mortgage News, (November 23, 1998), p. 1.
    \137\ John Holusha, ``As Financing Pool Dries Up, Some See 
Opportunity,'' New York Times, November 1, 1998.
    \138\ Federal Reserve Bulletin, June 2000, A 35.
    \139\ 1997 Annual Housing Activity Reports, Table 1.
    \140\ William Segal and Edward J. Szymanoski. The Multifamily 
Secondary Mortgage Market: The Role of Government-Sponsored 
Enterprises. Housing Finance Working Paper No. HF-002, Office of 
Policy Development and Research, Department of Housing and Urban 
Development, (March 1997).
    \141\ HUD analysis of GSE loan-level data.
    \142\ Fundingnotes, Vol. 3, Issue 9; (September 1998), Eric 
Avidon, ``PaineWebber Lauds Fannie DUS Paper,'' National Mortgage 
News, (September 14, 1998),p. 21.
    \143\ There is evidence that the GSEs have benefited from recent 
widening in CMBS spreads because of their funding cost advantage. 
See ``No Credit Crunch for First Mortgages,'' Commercial Mortgage 
Alert, (October 12, 1998); and ``Turmoil a Bonanza for Freddie,'' 
Commercial Mortgage Alert, (November 2, 1998).
    \144\ Federal Reserve Bulletin, June 2000, A 35.
    \145\ See Table A.7a for details. It is assumed that units in 
small multifamily properties represented approximately 39.4 percent 
of multifamily units financed in 1997, per the 1991 Residential 
Finance Survey, as discussed above. Additionally, it is assumed that 
1997 multifamily conventional origination volume was $38 billion, as 
discussed in Appendix D. An average loan amount per unit of $27,266 
is used, the GSE average for 1997 acquisitions.
    \146\ Larger properties may be perceived as less subject to 
income volatility caused by vacancy losses. Scale economies in 
securitization may also favor purchase of larger multifamily 
mortgages by the GSEs. Scale economies refer to the fixed costs in 
creating a mortgage backed security, and the smaller reduction in 
yield (higher security price) if these costs can be spread over 
larger unpaid principal balances.
    \147\ 1995 POMS data are used because 1995 represents the year 
with the most complete mortgage origination information in the 
Survey. 1996 GSE data are used because of number of units of 
property exhibited atypical behavior during 1995.
    \148\ These costs have been estimated at $30,000 for a typical 
transaction. Presentation by Jeff Stern, Vice President, Enterprise 
Mortgage Investments, HUD GSE Working Group, (July 23, 1998).
    \149\ ``Fannie Mae Announces New 5-50(SM) Streamlined Mortgage 
for Small Multifamily Properties is Now Available Through DUS 
Lenders; 10-Year Volume Goal is $18 Billion,'' Fannie Mae press 
release, May 10, 2000.
    \150\ Data from the HUD Property Owners and Managers Survey 
(POMS) suggests that, in and of itself, the GSEs' emphasis on 
refinance loans may roughly track that of the overall market.
    \151\ Standard & Poor's described Fannie Mae's multifamily 
lending as ``extremely conservative'' in ``Final Report of Standard 
& Poor's to the Office of Federal Housing Enterprise Oversight 
(OFHEO),'' (February 3, 1997), p. 10.
    \152\ See William Segal and Edward J. Szymanoski. ``Fannie Mae, 
Freddie Mac, and the Multifamily Mortgage Market,'' Cityscape: A 
Journal of Policy Development and Research, vol. 4, no. 1 (1998), 
pp. 59-91.
    \153\ Freddie Mac's policy of re-underwriting each multifamily 
acquisition is a response to widespread defaults affecting its 
multifamily portfolio during the late 1980s according to Follain and 
Szymanoski (1995).
    \154\ A more detailed discussion of underwriting guidelines is 
contained in the analysis below regarding Factor 5, ``The GSEs'' 
Ability to Lead the Industry.''
    \155\ The term ``affordable lending'' is used generically here 
to refer to lending for lower-income families and neighborhoods that 
have historically been underserved by the mortgage market.
    \156\ Throughout these appendices, the terms ``home loan'' or 
``home mortgage'' will refer to a ``home purchase loan,'' as opposed 
to a ``refinance loan.''
    \157\ Subsections b-d of this section focus on the single-family 
mortgage market for home purchase loans, which is the relevant 
market for analysis of homeownership opportunities. Subsection e 
extends the analysis to include single-family refinance loans. For a 
discussion of past performance in the multifamily mortgage market, 
see Section D of this Appendix.
    \158\ Thus, the market definition in this section is narrower 
than the data presented earlier in Section C and Tables A.1a and 
A.1b, which covered all loans (both government and conventional) 
less than or equal to the conforming loan limit. As in that section, 
only the GSEs' purchases of conventional conforming loans are 
considered; their purchases of FHA-insured, VA-guaranteed, and Rural 
Housing Service loans are excluded from this analysis.
    \159\ Higher limits apply for loans on 2-, 
3-, and 4-unit properties and for properties in Alaska, Hawaii, 
Guam, and the Virgin Islands.
    \160\ ``Jumbo mortgages'' in any given year might become 
eligible for purchase by the GSEs in later years as the loan limits 
rise and the outstanding principal balance is reduced.
    \161\ However, in analyzing the provision of mortgage finance 
more generally, it is often appropriate to include government loans; 
see Tables A.1a, A.1b and A.2 in Section C.3.b.
    \162\ Fair Lending/CRA Compass, (June 1999), p. 3.
    \163\ Randall M. Scheessele developed a list of 42 subprime 
lenders that was used by

[[Page 65142]]

HUD and others in analyzing HMDA data through 1997. In 1998, 
Scheessele updated the list to 200 subprime lenders. For analysis 
comparing various lists of subprime lenders, see Appendix D of 
Scheessele (1999), op. cit. That paper also discusses Scheessele's 
lists of manufactured housing lenders.
    \164\ 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. Section 
A.4 of this appendix also discusses several issues regarding HMDA 
data that were raised by the GSEs in their comments on the proposed 
rule.
    \165\ Since 1993, the GSEs have increased their purchases of 
seasoned loans. See Paul B. Manchester, Characteristics of Mortgages 
Purchased by Fannie Mae and Freddie Mac: 1996-1997 Update, Housing 
Finance Working Paper HF-006, Office of Policy Development and 
Research, Department of Housing and Urban Development, (August 
1998), p.17.
    \166\ For a discussion of the impact of the GSEs' seasoned 
mortgage purchases on HMDA data coverage, see Scheessele (1998), op. 
cit. 
    \167\ Table A.4b, which reports similar GSE information as Table 
A.4a, provides several alternative estimates of the conventional 
conforming market depending on the treatment of small loans, 
manufactured housing loans, and subprime loans. The data in Table 
A.4b will be referenced throughout the discussion.
    \168\ Any HMDA data reported in the appendices on borrower 
incomes excludes loans where the loan-to-borrower-income ratio is 
greater than six.
    \169\ For example, in 1997 Fannie Mae reported that 20.8 percent 
of the loans they purchased, that were originated during 1997, were 
for properties in underserved areas. HMDA reports that 21.0 percent 
of the loans sold to Fannie Mae during 1997 were for properties in 
underserved areas. The corresponding numbers for Freddie Mac, in 
1997, are 19.3 percent reported by them and 18.6 percent reported by 
HMDA. During 1997, both Fannie Mae and HMDA reported that 
approximately 37 percent of the ``current year'' loans purchased by 
Fannie Mae were for low- and moderate-income borrowers. Freddie Mac 
reported that 34.2 percent of the current year loans they purchased 
were for low-mod borrowers, compared to the 35.4 low-mod percent 
that HMDA reported as sold to Freddie Mac.
    \170\ Notice that while Fannie Mae's 1998 purchases resembled 
their 1997 purchases with prior-year loans having higher goals-
qualifying percentages than current-year loans, the pattern for 1999 
was similar to that for 1993 to 1996 when there were smaller 
differentials between the goals-qualifying percentages of prior-year 
and current-year mortgages.
    \171\ Referencing the study by Peter Zorn and Jim Berkovec, op 
cit., the GSEs argued in their comments on the proposed rule that 
HMDA overstates goals-qualifying loans. See Section A.3d for HUD's 
response which questions the findings of the Zorn-Berkovec study.
    \172\ The borrower income distributions in Tables A.3 and A.4a 
for the ``market without manufactured housing'' exclude loans less 
than $15,000 as well as all loans originated by lenders that 
primarily originate manufactured housing loans. See Table A.4b for 
market definitions that show the separate effects of excluding small 
loans and manufactured housing loans. Also, Table A.4b shows that 
excluding subprime loans has only a minor effect on the goals-
qualifying percentages in the mortgage market.
    \173\ See Scheessele (1999), op. cit. As explained in Appendix D 
of Scheessele's paper, the number of subprime lenders varies by 
year; the 200 figure cited in the text applies to 1998. The number 
of loans identified as subprime in these appendices is the same as 
reported by Scheessele in Table D.2b of his paper.
    \174\ Table A.1b in Section C.3.b provides several comparisons 
of the GSEs' total purchases with primary market originations. As 
shown there, many of the same patterns described above for home 
purchase loans can be seen in the data for the GSEs' total 
purchases.
    \175\ In general, the HMDA-reported affordability percentages 
for GSE purchases of refinance loans have matched the corresponding 
GSE-reported percentages. For example, in 1997, both GSEs reported 
to HUD that special affordable loans accounted for about 11 percent 
of their purchases of refinance loans in metropolitan areas; HMDA 
reported the same percentage for each GSE. Similarly, in 1998, both 
HMDA and Fannie Mae reported that special affordable loans accounted 
for 9.7 percent of Fannie Mae's refinance purchases. However, in 
1998, the Freddie-Mac-reported special affordable percentage (10.7 
percent) for its refinance loans was significantly higher than the 
corresponding percentage (9.5 percent) reported in the HMDA data. 
The reasons for this discrepancy require further study.
    \176\ The Mortgage Information Corporation (MIC) has recently 
started publishing origination and default performance data for the 
subprime market. For an explanation of their data and some early 
findings, see Dan Feshbach and Michael Simpson, ``Tools for Boosting 
Portfolio Performance'', Mortgage Banking: The Magazine of Real 
Estate Finance, (October 1999), pp. 137-150.
    \177\ For example, see Bunce and Scheessele (1996 and 1998), op. 
cit. 
    \178\ This analysis is limited to the conventional conforming 
market.
    \179\ To test the robustness of these statistics, this analysis 
was conducted where the ``lag'' determination is made at 95 percent 
instead of 99 percent. The results are consistent with those shown 
in Table A.5. For example, at the 95 percent cutoff, Fannie Mae 
lagged the market in 286 MSAs (88 percent) in the purchase of 1996 
originated Special Affordable category loans. Likewise, Freddie Mac 
lagged the market in 322 MSAs (99 percent).
    \180\ Privatization of Fannie Mae and Freddie Mac: Desirability 
and Feasibility. Office of Policy Development and Research, 
Department of Housing and Urban Development, (July 1996).
    \181\ The Treasury Department reached similar conclusions in its 
1996 report on the privatization of the GSEs, Government Sponsorship 
of the Federal National Mortgage Association and the Federal Home 
Loan Mortgage Corporation, U.S. Department of the Treasury (July 11, 
1996). Based on data such as the above, the Treasury Department 
questioned whether the GSEs were influencing the availability of 
affordable mortgages and suggested that the lower-income loans 
purchased by the GSEs would have been funded by private market 
entities if the GSEs had not purchased them.
    \182\ See Glenn B. Canner, and Wayne Passmore. ``Credit Risk and 
the Provision of Mortgages to Lower-Income and Minority 
Homebuyers,'' Federal Reserve Bulletin. 81 (November 1995), pp. 989-
1016; Glenn B. Canner, Wayne Passmore and Brian J. Surette. 
``Distribution of Credit Risk among Providers of Mortgages to Lower-
Income and Minority Homebuyers.'' Federal Reserve Bulletin. 82 
(December 1996), pp. 1077-1102; Harold L. Bunce, and Randall M. 
Scheessele, The GSEs' Funding of Affordable Loans: A 1996 Update, 
Housing Finance Working Paper HF-005, Office of Policy Development 
and Research, Department of Housing and Urban Development, (July 
1998); and Manchester, (1998), p. 24.
    \183\ Canner, et al. (1996).
    \184\ Harold L. Bunce and Randall M. Scheessele, The GSEs' 
Funding of Affordable Loans, Housing Finance Working Paper HF-001, 
Office of Policy Development and Research, U.S. Department of 
Housing and Urban Development, (December 1996).
    \185\ Harold L. Bunce and Randall M. Scheessele, The GSEs' 
Funding of Affordable Loans: A 1996 Update, Housing Finance Working 
Paper HF-005, Office of Policy Development and Research, U.S. 
Department of Housing and Urban Development, (July 1998), pp. 15-16.
    \186\ Statistics cited are from Table B.1 of Bunce and 
Scheessele, (1998) and are based on sales to the GSEs as reported by 
lenders in accordance with the HMDA. ``Lagging the market'' means, 
for example, that the percentage of the GSEs' loans for very low- 
and low-income borrowers is less than the corresponding percentage 
for the primary market, depositories, and the FHA.
    \187\ Under their charter acts, loans purchased by the GSEs with 
down payments of less than 20 percent must carry private mortgage 
insurance or a comparable form of credit enhancement.
    \188\ It is generally agreed that HMDA does not capture all 
loans originated in the primary market--for example, small lenders 
need not report under HMDA. But Fannie Mae believes that the 
undercount is not

[[Page 65143]]

spread uniformly across all borrower classes--in particular, it 
argues that the HMDA data exclude relatively more loans made to 
minorities and lower-income families.
    \189\ Bunce and Scheessele (1998) contained a comparison (Table 
A.1) of HMDA-reported and GSE-reported data on the characteristics 
of GSE mortgage purchases in 1996. In most cases the differences 
between the results utilizing the two different data sources were 
minimal, but in some cases (such as lending in underserved areas) 
the evidence lent some support to Fannie Mae's assertion that the 
HMDA data underreports their level of activity. The discrepancies 
between HMDA data and GSE data at the national level are also due to 
the seasoned loan effect (see Section E.2.e above and Table A.4a).
    \190\ John E. Lind. Community Reinvestment and Equal Credit 
Opportunity Performance of Fannie Mae and Freddie Mac from the 1994 
HMDA Data. San Francisco: Caniccor. Report, (February 1996).
    \191\ John E. Lind. A Comparison of the Community Reinvestment 
and Equal Credit Opportunity Performance of Fannie Mae and Freddie 
Mac Portfolios by Supplier from the 1994 HMDA Data. San Francisco: 
Cannicor. Report, (April 1996).
    \192\ Brent W. Ambrose and Anthony Pennington-Cross, Spatial 
Variation in Lender Market Shares, Research Study submitted to the 
Office of Policy Development and Research, Department of Housing and 
Urban Development, (1999).
    \193\ Heather MacDonald. ``Expanding Access to the Secondary 
Mortgage Markets: The Role of Central City Lending Goals,'' Growth 
and Change. (27), (1998), pp. 298-312.
    \194\ Heather MacDonald, Fannie Mae and Freddie Mac in Non-
metropolitan Housing Markets: Does Space Matter, Research Study 
submitted to the Office of Policy Development and Research, 
Department of Housing and Urban Development, (1999).
    \195\ Kirk McClure, The Twin Mandates Given to the GSEs: Which 
Works Best, Helping Low-Income Homebuyers or Helping Underserved 
Areas in the Kansas City Metropolitan Area? Research Study submitted 
to the Office of Policy Development and Research, Department of 
Housing and Urban Development, (1999).
    \196\ Richard Williams, The Effect of GSEs, CRA, and 
Institutional Characteristics on Home Mortgage Lending to 
Underserved Markets,'' Research Study submitted to the Office of 
Policy Development and Research, Department of Housing and Urban 
Development, (1999).
    \197\ Joseph Gyourko and Dapeng Hu. The Spatial Distribution of 
Secondary Market Purchases in Support of Affordable Lending, 
Research Study submitted to the Office of Policy Development and 
Research, Department of Housing and Urban Development, (1999).
    \198\ Bradford Case and Kevin Gillen. Studies of Mortgage 
Purchases by Fannie Mae and Freddie Mac: Spatial Variation in GSE 
Mortgage Purchase Activity. Research Study submitted to the Office 
of Policy Development and Research, Department of Housing and Urban 
Development, (1999).
    \199\ The coefficient for geographic targeting was significant 
and negative in 19 MSAs, significant and positive in another eight, 
and not significant in the remaining 17 MSAs.
    \200\ The coefficient for the highest minority-concentration 
category (census tracts with greater than 50% minority population) 
was significantly negative in 21 MSAs, but significantly positive in 
10 MSAs and not significantly different from zero in the remaining 
13.
    \201\ Samuel L. Myers, Jr. The Effects of Government-Sponsored 
Enterprise Secondary Market Decisions on Racial Disparities in Loan 
Rejection Rates. Research Study submitted to the Office of Policy 
Development and Research, Department of Housing and Urban 
Development, (1999).
    \202\ Variables from the GSE Public Use Data Base include the 
income and gender of the borrower, the gender and race of the 
coborrower, first-time homebuyer, and loan amount. Variables from 
Census 1990 include the following information for the census tract 
in which the property is located: percent of owner-occupied houses, 
average size of household, average number of persons per owner-
occupied house, average number of persons per renter-occupied unit, 
percentage of white, black, Asian, American Indian, and other 
minority households, average poverty rate, median monthly rent, 
median house value, percent of persons 65 or older, percent of 
persons under 18, and percent of female-headed households. Variables 
from HMDA include reason for denial, whether or not loan is sold to 
GSE, type of loan (conventional), type of agency, and origination 
year.
    \203\ The unconditional probability that a loan will not be 
sold, P(NS), to a GSE is computed using Bayes' rule. It is based on 
the conditional probability that a loan is sold to GSEs given that 
it was originated, P(SO), and the probability that a loan is 
originated which are obtained using HMDA data. The unconditional 
probability that a loan will be sold to a GSE can not be obtained 
from either the HMDA data which does not include details of which 
loans were sent for review and which were declined by the secondary 
purchaser--or from the HUD-GSE data, which only includes approved 
loans. However, we know from Bayes' rule that
[GRAPHIC] [TIFF OMITTED] TR31OC00.018

    where S mean that the loan was sold and O means that the loan 
was originated and where all loan sold by the lender must have been 
originated such that P(OS)=1. We can obtain a measure of the 
unconditional probability that a loan will not be sold from
[GRAPHIC] [TIFF OMITTED] TR31OC00.019

    \204\ Calvin Bradford, The Patterns of GSE Participation in 
Minority and Racially Changing Markets Reviewed from the Context of 
the Levels of distress Associated with High Levels of FHA Lending, 
Research Study submitted to the Office of Policy Development and 
Research, Department of Housing and Urban Development (2000).
    \205\ David M. Harrison, Wayne R. Archer, David C. Ling, and 
Marc T. Smith, Mitigating Information Externalities in Mortgage 
Markets: The Role of Government Sponsored Enterprises, Research 
Study submitted to the Office of Policy Development and Research, 
Department of Housing and Urban Development (2000).
    \206\ 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).
    \207\ In following up on the Urban Institute study, HUD began in 
February 2000 a review of Fannie Mae's and Freddie Mac's automated 
underwriting systems.
    \208\ Standard guidelines refer to guidelines not associated 
with affordable lending programs.
    \209\ Temkin, et al. (1999), p. 4.
    \210\ Temkin, et al. (1999), p. 5.
    \211\ Temkin, et al. (1999), p. 28.
    \212\ Senate Report 102-282, (May 15, 1992), p. 35.
    \213\ Table A.7a(A.7b) considers GSE purchases during 1997, 
1998, and 1999 (1998 and 1999) of conventional mortgages that were 
originated during 1997 (1998). HUD's methodology for deriving the 
market estimates is explained in Appendix D. B&C loans have been 
excluded from the market estimates in Table A.7.
    \214\ Two caveats about the data in Table A.7 should be 
mentioned here. First, the various market totals for underserved 
areas are probably understated due to the model's underestimation of 
mortgage activity in non-metropolitan underserved counties and of 
manufactured housing originations in non-metropolitan areas. Second, 
as discussed in Appendix D, some uncertainty exists around the 
adjustment for B&C single-family owner loans.
    \215\ Table A.7a shows that multifamily represented 19 percent 
of total units financed during 1997 (obtained by dividing 1,393,677 
multifamily units by 7,306,950 ``Total Market'' units). Increasing 
the single-family-owner number in Table A.7 by 732,182 to account 
for excluded B&C mortgages increases the ``Total Market'' number to 
8,039,132 which is consistent with the percent multifamily share 
reported in the text. See Appendix D for discussion of the B&C 
market.
    \216\ A similar imbalance is evident with regard to figures on 
the stock of mortgage debt published by the Federal Reserve Board. 
Within the single-family mortgage market the GSEs held loans or 
guarantees with an unpaid principal balance (UPB) of $1.5 trillion, 
comprising 36 percent of $4.0 trillion in outstanding single-family 
mortgage debt as of the end of 1997. At the end of 1997, the GSEs 
direct holdings and guarantees of $41.4 billion represented 13.7 
percent of $301 billion in multifamily mortgage debt outstanding. 
(Federal Reserve Bulletin, June 1998, A 35.)
    \217\ 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).

[[Page 65144]]

    \218\ A jumbo mortgage is one for which the loan amount exceeds 
the maximum principal amount for mortgages purchased by the 
enterprises--$240,000 for mortgages on 1-unit properties in 1999, 
with limits that are 50 percent higher in Alaska, Hawaii, Guam, and 
the Virgin Islands.
    \219\ Office of Federal Housing Enterprise Oversight, 1998 
Report to Congress, (June 15, 1998), Figure 9, p. 32; and 
unpublished OFHEO estimates for 1998.
    \220\ Mortgage originations for 1997 were reported in the 
Department of Housing and Urban Development, HUD Survey of Mortgage 
Lending Activity: Fourth Quarter/Annual 1997, (September 24, 1998).
    \221\ The underwriting guidelines published by the two GSEs are 
similar in most aspects. And since November 30, 1992, Fannie Mae and 
Freddie Mac have provided lenders the same Uniform Underwriting and 
Transmittal Summary (Fannie Mae Form 1008/Freddie Mac Form 1077), 
which is used by originators to collect certain mortgage information 
that they need for data entry when mortgages are sold to either GSE.
    \222\ Freddie Mac stock was not publicly traded until after the 
passage of the Financial Institutions Reform, Recovery and 
Enforcement Act of 1989 (FIRREA), thus it is not possible to 
calculate a 10-year annualized rate of return.
    \223\ Fortune, (April 17, 2000), pp. F-1, F-2.
    \224\ Business Week, (March 27, 2000), p. 197.
    \225\ U.S. Department of Housing and Urban Development. Rental 
Housing Assistance--The Worsening Crisis: A Report to Congress on 
Worst Case Housing Needs. (March 2000).
    \226\ Standard & Poor's DRI, The U.S. Economy. (June 2000), p. 
56.
    \227\ See Drew Schneider and James Follain, ``A New Initiative 
in the Federal Housing Administration's Office of Multifamily 
Housing Programs: An Assessment of Small Projects Processing,'' 
Cityscape: A Journal of Policy Development and Research 4(1), 
(1998), pp. 43-58.
    \228\ Senate Report 102-282, (May 15, 1992), p. 36.
    \229\ ``Final Report of Standard & Poor's to the Office of 
Federal Housing Enterprise Oversight (OFHEO),'' (February 3, 1997), 
p. 10.
    \230\ However, the Department's goals for the GSEs have been set 
so that they will be feasible even under less favorable conditions 
in the housing market.
    \231\ Another area where stepped-up GSE involvement could 
benefit low- and moderate-income families is lending for the 
rehabilitation of properties, which is especially needed in our 
urban areas. The GSEs have made some efforts in this complex area, 
but the benefits of stepped-up roles by the GSE could be sizable.

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

A. Introduction and Response to Comments

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 
``Geographically Targeted 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 Geographically Targeted 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 Geographically Targeted Goal for both metropolitan areas 
and nonmetropolitan areas and then discusses HUD's response to the 
public comments raised in this appendix. 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 Geographically Targeted Goal (the 
third factor) and Sections E-G report the Secretary's findings for 
the remaining factors. Section H summarizes the Secretary's 
rationale for setting the level for the Geographically Targeted 
Goal.

2. HUD's Geographically Targeted Goal

    HUD's definition of the geographic areas targeted by this goal 
is basically the same as that used during 1996-99. It is divided 
into a metropolitan component and a nonmetropolitan component.
    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.
    The definition includes 20,326 of the 43,232 census tracts (47 
percent) in metropolitan areas, which include 44 percent of the 
metropolitan population.1 The tracts included in this 
definition suffer from poor mortgage access and distressed 
socioeconomic conditions. The average mortgage denial rate in these 
tracts is 19.4 percent, almost twice the denial rate in excluded 
tracts. The tracts include 73 percent of the number of poor persons 
in metropolitan areas.
    This definition is based on studies of mortgage lending and 
mortgage credit flows conducted by academic researchers, community 
groups, the GSEs, HUD and other government agencies. While more 
research must be done before mortgage access for different types of 
people and neighborhoods is fully understood, one finding from the 
existing research literature stands out--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 measuring access to mortgage credit.
    Nonmetropolitan Areas. This rule provides that in 
nonmetropolitan areas mortgage purchases that finance properties 
that are located in counties will count toward the Geographically 
Targeted Goal 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. The nonmetropolitan 
definition has been expanded slightly by adding criterion (b) under 
part (2) of this definition--as a result, 14 counties in Texas, 
Mississippi, Arizona, Arkansas, Georgia, and Louisiana that were 
previously classified as served areas have now been reclassified as 
underserved counties.
    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, this rule uses a more 
inclusive, county-based definition of underservedness in rural 
areas. HUD's definition includes 1,511 of the 2,305 counties (66 
percent) in nonmetropolitan areas and accounts for 54 percent of the 
nonmetropolitan population and 67 percent of the nonmetropolitan 
poverty population.
    Goal Levels. The Geographically Targeted Goal is 31 percent of 
eligible units financed for calendar years 2001-03. HUD estimates 
that the mortgage market in areas included in the Geographically 
Targeted Goal accounts for 29-32 percent of the total number of 
newly-mortgaged dwelling units. HUD's analysis indicates that 27.0 
percent of Fannie Mae's 1998 purchases and 26.8 percent of its 1999 
purchases financed dwelling units located in these areas. The 
corresponding performance for Freddie Mac was 26.1 percent in 1998 
and 27.5 percent in 1999.

3. Response to Comments

    This section briefly reviews the main comments on the analyses 
reported in this appendix. First, both GSEs, but particularly 
Freddie Mac, were concerned that the Underserved Areas Goal was set 
too high.

[[Page 65145]]

Second, HUD received varying responses on changing the underserved 
areas definition to adopt an ``enhanced'' definition that would 
lower the income threshold for the census tract definition to 80 
percent and raise the minority threshold to 50 percent. Finally, HUD 
received a range of comments on switching the non-metropolitan 
underserved areas definition from a county-based to a tract-based 
approach. With respect to the latter two issues, HUD has decided to 
wait until year 2000 Census data are available, which will allow for 
an up-to-date comprehensive analysis of these issues.

a. The Level of the Underserved Areas Goal

    Fannie Mae supported the increase in affordable housing goals, 
which includes raising the underserved areas goal from its current 
level of 24 percent to 31 percent. Freddie Mac stated that ``the 
Underserved Areas Goal proposed by the Department is unreasonably 
high'' and recommended that the goal level be reduced from 31 
percent to 30 percent. Freddie Mac stated further that ``setting the 
Underserved Areas Goal at 31 percent for those three years [2001-03] 
amounts to a significantly larger stretch than for the other two 
goals and makes it significantly less feasible under a variety of 
economic conditions''. Freddie Mac based its conclusion on a number 
of factors, such as the fact that this goal is set closer to the 
upper end of HUD's market range (29-32 percent), as compared with 
the Low-Mod and Special Affordable Goals; Freddie Mac concluded that 
consistency with the other two goals would call for a 30 percent 
Underserved Areas Goal. In addition, Freddie Mac stated that HUD's 
market range is overestimated and does not fully account for adverse 
economic changes. According to Freddie Mac, HUD's overestimation of 
the underserved areas market is due to HUD's overestimation of the 
rental property share of the mortgage market; to a bias in HMDA data 
that leads to the underserved areas portion of the owner market 
being overstated; and to HUD's underestimation of the subprime 
portion of the single-family market.
    HUD's Response. HUD does not agree with Freddie Mac's 
recommendation that the Underserved Areas Goal should be lowered 
below the proposed level. Several factors must be considered when 
evaluating Freddie Mac's analysis and recommendations. First, HUD 
disagrees with Freddie Mac's conclusion that the Department's 
methodology overstates the rental portion of the market. HUD's 
analysis of this issue is discussed in Sections B and C of Appendix 
D. By relying on HMDA data, Freddie Mac (as well as the Freddie Mac-
funded study by PriceWaterhouseCoopers) significantly underestimates 
the multifamily share of the mortgage market, which leads to its 
erroneous conclusions about the size of the underserved areas 
market.
    Second, HUD has set its range of market estimates for this goal 
at a rather conservative level. As discussed in Section G of 
Appendix D, the underserved areas portion of the market (without B&C 
loans) averaged 33 percent between 1995 and 1998--somewhat higher 
than the top end of HUD's 29-32 percent market range. As shown in 
Table D.19 of Appendix D, the underserved areas share of the owner 
market could fall from its 1995-98 average of 33 percent to 24 
percent before the overall market estimate would fall to 30 percent, 
and to below 22 percent before the overall market estimate would 
fall below 29 percent. As mentioned in HUD's response to the 
``volatility'' issue (see Section B of Appendix D), the Secretary 
can re-examine the feasibility of the housing goals if a recession 
or other economic conditions cause a substantial decline in the 
mortgage market in underserved areas.
    Third, HUD excluded the B&C portion of the subprime market when 
determining its market range (29-32 percent) for underserved areas. 
As explained in Section G of Appendix D, the estimated increase in 
the market share due to the county-based definition in non-
metropolitan areas more than offsets the estimated reduction in 
market share due to the exclusion of B&C loans. (This offsetting 
pattern can be seen in Table D.15 of Appendix D for the years 1995-
98.) But due to inadequate mortgage market data for non-metropolitan 
areas, HUD was unable to fully include the effects of underserved 
counties in its market range for the Underserved Areas Goal. Thus, 
the 29-32 percent range is a conservative market estimate. HUD 
continues to explore other data bases to improve its estimates of 
the mortgage market in rural underserved counties.
    Finally, it should be noted that the rental sectors that the 
GSEs have traditionally experienced the most difficulty penetrating 
are less important for the Underserved Areas Goal than for the Low-
Mod and Special Affordable Goals. The latter two goals rely more 
heavily on the GSEs' single-family rental and multifamily purchases 
than the Underserved Areas Goal. For example, special affordable 
loans amounted to one half of the rental units financed by the GSEs 
during 1998, versus only 10.6 percent of the owner units, yielding a 
rental-to-owner ratio of 4.7. On the other hand, units in 
underserved areas amounted to 43.1 percent of the rental units 
financed, versus 23.4 percent of the owner units, yielding a much 
lower rental-to-owner ratio of 1.8.

b. Changes in the Underserved Areas Definition for Metropolitan Areas

    Neither Fannie Mae nor Freddie Mac supported changing the 
underserved areas definition in metropolitan areas. With regard to 
the enhanced option, the GSEs advocated against reducing the number 
of census tracts that qualified for goal based on 1990 Census data, 
since these tracts might qualify under the updated 2000 Census data. 
Both GSEs believe that HUD should not change the current definition 
until the updated information for demographics and housing stock 
composition of census tracts is available from the 2000 census data.
    In addition to the GSEs' views, a number of comments both 
supporting and opposing the enhanced definition were received. 
Advocates for the enhanced definition supported changing the tract 
income ratio from 90 percent to 80 percent to coincide with the 
definition under the Community Reinvestment Act (CRA). This change 
would make the GSEs' housing goals and CRA mutually supportive and 
would use a standard already employed by banks. Comments against the 
enhanced definition fell into two categories: some commenters did 
not support decreasing the number of census tracts that qualify as 
underserved areas, while others did not support using the greater of 
local or national median income in computing the tract income ratio.
    No general support from the GSEs or other commenters was found 
for increasing the minimum minority composition of underserved 
census tracts from 30 percent to 50 percent. One commenter indicated 
that this change would disproportionately impact the Hispanic 
population, though no data was presented to support this claim.
    HUD's Response. HUD is not changing the definition of 
underserved metropolitan areas in this final rule, but the 
Department reserves the right to reexamine this definition following 
the release of the 2000 Census data. The Department acknowledges 
that the 2000 Census will impact the designation of census tracts 
that are currently targeted as underserved areas. Many changes have 
occurred in the last decade that impact the various factors which 
make up the underserved areas definition. Any changes in the 
underserved area definition based on the 1990 Census data would not 
provide a complete assessment of outcomes.

c. Changes to the Underserved Areas Definition for Non-metropolitan 
Areas

    Fannie Mae and Freddie Mac agreed that the current county-based 
definition for non-metropolitan areas should be retained. Both GSEs 
believe, as also indicated in their comments on the 1995 rule, that 
rural lenders' business is centered around counties, rather than 
census tracts. They cite the lack of data for rural areas as 
sufficient cause to maintain the status quo, since the information 
void makes it difficult to judge the impact of any change in the 
definition.
    Some commenters agreed with the GSEs, while others did not. One 
set of commenters including America's Community Bankers and the 
Independent Community Bankers of America agreed with the GSEs 
regarding retention of the county-based definition. The Housing 
Assistance Council supported changing the underserved areas 
definition to a more targeted, census tract-based definition.
    Other recommendations for defining rural underserved areas were 
received. The Wisconsin Rural Development Center and the Fair 
Lending Coalition of Milwaukee proposed looking at the minimum 
income ratio based on county, tract, or block group. A few 
commenters proposed using poverty levels as a criteria for targeting 
underserved counties.
    HUD's Response. HUD recognizes the broad nature of the current 
definition of rural underserved areas. As explained in the proposed 
rule, one shortcoming of this goal in non metropolitan counties is 
that it does not target the GSEs' purchases very well--for example, 
the GSEs' mortgage purchases in rural underserved areas have a 
higher share of borrowers with income above county median income 
than their purchases in urban underserved areas. However, due to the 
lack of data on mortgage originations in non-metropolitan areas, it 
is difficult to precisely identify rural underserved areas. The

[[Page 65146]]

Department acknowledges that the 2000 Census will impact the 
designation of counties that are currently targeted as underserved. 
Before changing the definition for underserved non-metropolitan 
areas, it would be prudent to wait for new data on area 
demographics. HUD will re-examine this issue when data from the 2000 
Census are available.

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 mortgage funding. Section B.1 provides an overview 
of the problem of unequal access to mortgage funding in the nation's 
housing finance system, 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 Geographically 
Targeted Goal in metropolitan areas. The most thorough studies 
available provide strong evidence that in metropolitan areas low 
income and high minority census tracts are underserved by the 
mortgage market.
    Three main points are made in this section:
     There is evidence of racial disparities in both the 
housing and mortgage markets. 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 definition. Studies 
conclude that characteristics of the applicant and the neighborhood 
where the property is located are the major determinants of mortgage 
denials and origination rates. Once these characteristics are 
accounted for, other influences, such as location in an OMB-
designated central city, play only a minor role in explaining 
disparities in mortgage lending.\2\

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. 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. A quick look at mortgage 
denial rates reported by the 1998 HMDA data reveals that minority 
denial rates were higher than those for white loan applicants. For 
lower-income borrowers, the conventional denial rate for African 
Americans was 1.9 times the denial rate for white borrowers, while 
for higher-income borrowers, the denial rate for African Americans 
was 2.5 times the rate for white borrowers. Similarly, the FHA 
denial rate for lower-income African Americans was 1.7 times the 
denial rates for lower-income white borrowers and twice as high for 
higher-income African Americans as for whites with similar incomes.
    Several analytical studies, some of which are reviewed later in 
this section, show that these differentials in denial rates are not 
fully accounted for by differences in credit risk. Perhaps the most 
publicized example is a study by the Federal Reserve Bank of Boston, 
described in more detail below, which found that differential denial 
rates were most prevalent among marginal applicants.\3\ 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.
    The Urban Institute conducted a case study of lenders' 
origination processes.\4\ The research team and lenders believed 
origination processes to be race-blind. A review of the HMDA data 
revealed that origination outcomes were different for whites, black, 
and Hispanics--where lenders denied a small proportion of minority 
applicants, they denied an even smaller proportion of white 
applications. This may result from the lender's staff making greater 
efforts to qualify marginal white applicants compared with marginal 
black and Hispanic applicants.
    In addition to discrimination in the lending market, substantial 
evidence exists of discrimination in the housing market. The 1991 
Housing Discrimination Study sponsored by HUD found that minority 
home buyers encounter some form of discrimination about half the 
time when they visit a rental or sales agent to ask about advertised 
housing.\5\ The incidence of discrimination was higher for African 
Americans than for Hispanics and for homebuyers than for renters. 
For renters, the incidence of discrimination was 46 percent for 
Hispanics and 53 percent for African Americans. The incidence among 
buyers was 56 percent for Hispanics and 59 percent for African 
Americans.
    While discrimination is rarely overt, minorities are more often 
told the unit of interest is unavailable, shown fewer properties, 
offered less attractive terms, offered less financing assistance, or 
provided less information than similarly situated non-minority 
homeseekers. Some evidence indicates that properties in minority and 
racially-diverse neighborhoods are marketed differently from those 
in White neighborhoods. Houses for sale in non-White neighborhoods 
are rarely advertised in metropolitan newspapers, open houses are 
rarely held, and listing real estate agents are less often 
associated with a multiple listing service.\6\
    Discrimination, while not the only cause, contributes to the 
pervasive level of segregation that persists between African 
Americans and Whites in our urban areas. Because minorities tend to 
live in segregated neighborhoods, their difficulty in obtaining 
mortgage credit has a concentrated effect on the viability of their 
neighborhoods. 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.

2. Evidence About Access to Credit in Urban Neighborhoods

    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 
from existing data. To provide the reasoning behind the Department's 
definition of underserved areas, this section first uses 1998 HMDA 
data to examine geographic variation in mortgage denial rates, and 
then it reviews three sets of studies that support HUD's definition. 
These include (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 review of the economics literature 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.

[[Page 65147]]

a. HMDA Data on Mortgage Originations and Denial Rates

    Home Mortgage Disclosure Act (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, it is a rich data base for 
analyzing mortgage activity in urban neighborhoods. HUD's analysis 
using HMDA data for 1998 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.1 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 1998 the denial rate for census tracts that are over 90 
percent minority (26.6 percent) was 2.5 times that for census tracts 
with less than 10 percent minority (10.4 percent).
     Census tracts with lower incomes have higher denial 
rates and lower origination rates than higher income tracts. For 
example, in 1998 mortgage denial rates declined from 26.8 percent to 
7.4 percent as tract income increased from less than 20 percent of 
area median income to more than 150 percent of area median 
income.7 Similar patterns arose in HUD's analysis of 1993 
and 1994 HMDA data (see Appendix B of the 1995 rule).
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    Table B.2 illustrates the interaction between tract minority 
composition and tract income by aggregating the data in Table B.1 
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 7.9 percent and an origination 
rate of 19.6 loans per 100 owner occupants in 1998. The high-
minority (over 50 percent), low-income (under 90 percent of area 
median) group had a denial rate of 24.0 percent and an origination 
rate of only 8.5 loans per 100 owner occupants. The other groupings 
fall between these two extremes.
    The advantages of HUD's underserved area definition can be seen 
by examining the minority-income combinations highlighted in Table 
B.2. 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 1998 underserved areas had 
almost twice the average denial rate of served areas (19.4 percent 
versus 10.3 percent) and less than two-thirds the average 
origination rate per 100 owner occupants (10.8 versus 17.5). HUD's 
definition does not include high-income (over 120 percent of area 
median) census tracts even if they meet the minority threshold. The 
mortgage denial rate (13.3 percent) for high-income tracts with a 
minority share of population over 30 percent is much less than the 
denial rate (19.4 percent) in underserved areas as defined by HUD, 
and only slightly above the average (10.3 percent) for all served 
areas.

b. Federal Reserve Bank Studies

    The analysis of denial rates in the above section suggests that 
HUD's definition is a good proxy for identifying areas experiencing 
credit problems. However, an important question is the degree to 
which variations in denial rates reflect lender bias against certain 
kinds of neighborhoods and borrowers versus the degree to which they 
reflect the credit quality of potential borrowers (as indicated by 
applicants' available assets, credit rating, employment history, 
etc.). Some studies of credit disparities have attempted to control 
for credit risk factors that might influence a lender's decision to 
approve a loan. Without fully accounting for the creditworthiness of 
the borrower, racial differences in denial rates cannot be 
attributed to lender bias.
    The best example of accounting for credit risk is the study by 
researchers at the Federal Reserve Bank of Boston, which analyzed 
mortgage denial rates.\8\ 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. 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 of all races were approved, 
differential treatment was observed among borrowers with more 
marginal qualifications.\9\
    A subsequent reassessment and refinement of the data used by the 
Federal Reserve Bank of Boston confirmed the findings of that 
study.\10\ William C. Hunter of the Federal Reserve Bank of Chicago 
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 two Fed studies concluded that the effect of borrower race 
on mortgage rejections persists even after controlling for 
legitimate determinants of lenders' credit decisions. Thus, they 
imply that variations in mortgage denial rates, such as those given 
in Table B.2, 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 
\11\ and by underwriting standards that have disparate effects on 
minority and lower-income borrowers and their neighborhoods.\12\

c. 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 1980's and early 1990's, a number 
of studies using HMDA data (such as that reported in Tables B.1 and 
B.2) 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.\13\ However, such analyses were criticized because 
they did not distinguish between demand, risk, and supply effects 
\14\--that is, they did not determine whether loan volume was low 
because families in high-minority and low-income areas were unable 
to afford home ownership 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.\15\ \16\
    Recent statistical studies have sought to test the redlining 
hypothesis by more completely controlling for differences in 
neighborhood risk and demand. The first two studies reviewed below 
are good examples of the more recent literature. 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. However, as explained below, these studies cannot reach 
definitive conclusions about redlining because segregation in our 
inner cities makes it difficult to distinguish the impacts of 
geographic redlining from the effects of individual discrimination.
    Additional studies related to redlining and the credit problems 
facing low- income and minority neighborhoods are also summarized. 
Particularly important are studies that 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.
    Holmes and Horvitz Study. Andrew Holmes and Paul Horvitz used 
1988-1991 HMDA data to examine variations in conventional mortgage 
originations across census tracts in Houston. Their single-equation 
regression model included as explanatory variables the economic 
viability of the loan, characteristics of properties in and 
residents of the tract (e.g., house value, income, age distribution 
and education level), measures of demand (e.g., recent movers into 
the tract and change in owner-occupied units between 1980 and 1990), 
and measures of credit risk (defaults on government-insured loans 
and change in tract house values between 1980 and 1990). To test the 
existence of racial redlining, the model also included as 
explanatory variables the percentages of African American and 
Hispanic residents in the tract and the increase in the tract's 
minority percentage between 1980 and 1990. 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.
    Schill and Wachter Study. Michael Schill and Susan Wachter 
posited that the probability that a lender will accept a specific 
mortgage application depends on characteristics of the individual 
loan application \17\ and characteristics of the neighborhood where 
the property collateralizing the loan is located. Schill and Wachter 
included neighborhood risk proxies that are likely to affect the 
future value of the properties,\18\ and they included the percentage 
of the tract population comprised of African Americans and Hispanics 
in order to test for the existence of racial discrepancies in 
lending patterns across census tracts.
    Testing their model for conventional mortgages in Philadelphia 
and Boston, Schill and Wachter found that the applicant race 
variables--whether the applicant was African

[[Page 65150]]

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). In an initial analysis 
that excluded the neighborhood risk variables from the model, the 
percentage of the census tract that was African American also showed 
a significant and negative coefficient, a result that is consistent 
with redlining. However, when the neighborhood risk proxies were 
included in the model along with the individual loan variables, the 
percentage of the census tract that was African American became 
insignificant. Thus, similar 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.'' \19\
    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.\20\ 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.
    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.\21\ 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.\22\
    Geoffrey Tootell has authored two papers on neighborhood 
redlining based on the mortgage rejection data from the Boston Fed 
study.\23\ 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.\24\ 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.
    In a 1999 paper, Stephen Ross and Geoffrey Tootell used the 
Boston Fed data base to take a closer at both lender redlining and 
the role of private mortgage insurance (PMI) in neighborhood 
lending.\25\ 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.
    Studies of Information Externalities. A 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.\26\ 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.''
    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.27 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.28
    Robert Avery, Patricia Beeson, and Mark Sniderman found 
significant evidence of economies associated with the scale of 
operation of individual lenders in a neighborhood.29 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.

d. 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. This section reports findings from 
several analyses by HUD and 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.
    Socioeconomic Characteristics. The targeted nature of HUD's 
definition can be seen from the data presented in Table B.3,

[[Page 65151]]

which show that families living in underserved areas experience much 
more economic and social distress than families living in served 
areas. For example, the poverty rate in underserved census tracts is 
20.1 percent, or almost four times the poverty rate (5.8 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 in 
underserved areas (11.5 percent) than in served areas (4.3 percent).
    The majority of units in served areas are owner-occupied, while 
the majority of units in underserved areas are renter-occupied.
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    Credit Characteristics. Tables B.1 and B.2 documented the 
relatively high denial rates and low mortgage origination rates in 
underserved areas as defined by HUD. This section extends that 
analysis by comparing underserved and served areas within central 
cities and suburbs. Figure B.1 shows that HUD's definition targets 
central city neighborhoods that are experiencing problems obtaining 
mortgage credit. The 19.6 percent denial rate in these neighborhoods 
in 1998 was nearly twice the 10.6 percent denial rate in the 
remaining areas of central cities. A broad, inclusive definition of 
``central city'' that includes all areas of all OMB-designated 
central cities would include these ``remaining'' portions of cities. 
Figure B.1 shows that these areas, which account for approximately 
43 percent of the population in OMB-designated central cities, 
appear to be well served by the mortgage market. As a whole, they 
are not experiencing problems obtaining mortgage credit.\30\
    HUD's definition also targets underserved census tracts in the 
suburbs as well as in central cities--for example, the average 
denial rate in underserved suburban areas (19.2 percent) is more 
than twice that in the remaining served areas of the suburbs (10.1 
percent). Low-income and high-minority suburban tracts appear to 
have credit problems similar to their central city counterparts. 
These suburban tracts, which account for 40 percent of the suburban 
population, are encompassed by the definition of other underserved 
areas.
    As explained in the Preamble, HUD asked for public comment on 
two options that would tighten the targeting of the underserved 
areas definition and reduce the number of qualifying census tracts. 
After examining the comments the Department has decided to wait 
until the release of the 2000 Census Bureau data. In addition to 
providing updated information on neighborhoods, the 2000 Census 
Bureau will incorporate changes adopted by the Metropolitan Area 
Standards Review Committee that will impact the boundaries of 
current metropolitan areas.\31\
    Shear, Berkovec, Dougherty, and Nothaft Study. William Shear, 
James Berkovec, Ann Dougherty, and Frank Nothaft conducted an 
analysis of mortgage flows and application acceptance rates in 32 
metropolitan areas that supports a targeted definition of 
underserved areas.\32\ They 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; \33\ and (b) once census tract influences were 
accounted for, central city location had only a minimal effect on 
credit flows. Shear, Berkovec, Dougherty, and Nothaft 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. They explain the 
implications of their results for measuring underserved areas as 
follows:
    While it is not at all clear how we might rigorously define, let 
alone measure, what it means to be underserved, it is clear that 
there are important housing-related problems associated with certain 
location characteristics, and it is possible that, in the second or 
third best world in which we live, mortgage markets might be useful 
in helping to solve some of these problems. We then might use these 
data to help single out important areas or at least eliminate some 
bad choices. * * * The regression results indicate that income and 
minority status are better indicators of areas with special needs 
than central city location.\34\
    Avery, Beeson, and Sniderman Study. Robert Avery, Patricia 
Beeson, and Mark Sniderman of the Federal Reserve Bank of Cleveland 
presented a paper specifically addressing the issue of underserved 
areas in the context of the GSE legislation.35 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. They sought to isolate the differences that stem from the 
characteristics of the neighborhood itself rather than the 
characteristics of the individuals that apply for loans in the 
neighborhood or lenders that happen to serve them. Similar to the 
studies of redlining reviewed in the previous section, Avery, Beeson 
and Sniderman hypothesized that variations in mortgage application 
and denial rates would be a function of several risk variables such 
as the income of the applicant and changes in neighborhood house 
values; they tested for independent racial effects by adding to 
their model the applicant's race and the racial composition of the 
census tract. Econometric techniques were used to separate 
individual applicant effects from neighborhood effects.
    Based on their empirical work, Avery, Beeson and Sniderman 
reached the following conclusions:
     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.\36\ For white 
applicants, on the other hand, denial rates were significantly 
higher in minority tracts.\37\ 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, Avery et al. noted that since minorities tend to live in 
segregated communities, a policy of targeting minority neighborhoods 
may be warranted.
    Other findings were:
     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.
     There was little difference in overall denial rates 
between central cities and suburbs, once individual applicant and 
census tract characteristics were controlled 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.

e. Conclusions from HUD's Analysis and 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. 
HUD's analysis of HMDA data shows that 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 our 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, thus, the need continues for further 
research on the underlying determinants of geographic disparities in 
mortgage lending.\38\
    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's analysis shows that both credit and 
socioeconomic problems are highly concentrated in underserved areas 
within central cities and suburbs. The remaining, high-income 
portions of central cities and suburbs appear to be well served by 
the mortgage market.
    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. HUD 
believes, however, that the economics literature is consistent with 
a targeted rather than a broad approach for defining underserved 
areas.

[[Page 65154]]

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

    Because of the absence of HMDA data for rural areas, the 
analysis for metropolitan underserved areas cannot be carried over 
to non-metropolitan 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. But this definition parallels 
that used in metropolitan areas--specifically, a nonmetro 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 
nonmetro or national nonmetro 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 nonmetro or national nonmetro median income. For nonmetro 
areas the median income component of the underserved areas 
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 ``enhanced income''--the 
greater of state nonmetro income and national nonmetro income. This 
is based on HUD's analysis of 1990 census data, which indicated that 
comparing county nonmetro income only to state nonmetro income would 
lead to the exclusion of many lower-income low-minority counties 
from the definition, especially in Appalachia. 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 county-wide definition of rural underserved areas 
could give the GSEs an incentive to purchase mortgages in the 
``better served'' portions of underserved counties which may face 
few, if any, barriers to accessing mortgage credit in rural areas. 
This issue is discussed in more detail in the proposed Rule.
    The demographic characteristics of served and underserved 
counties are first presented in this section. Next, a literature 
review of recent studies provides an overview of rural mortgage 
markets, GSE activity, and the growing demand for manufactured 
housing in rural housing markets. It also discusses characteristics 
of rural housing markets that lead to higher interest rates and 
mortgage access problems and makes some policy recommendations for 
addressing market inefficiencies.

1. Demographics

    As discussed, majorities of rural households and rural counties 
fall under the definition of underserved areas. As shown in Table 
B.4, rural underserved counties have higher unemployment, poverty 
rates, minority shares of households, and homeownership rates than 
rural served counties. The poverty rate in underserved rural 
counties (21.2 percent) is nearly twice that in served rural 
counties (12.2 percent). Joblessness is more common, with average 
unemployment rates of 8.3 percent in underserved counties and 5.9 
percent in served counties. Minorities make up 20.8 percent of the 
residents in underserved counties and 7.4 percent in served 
counties. Homeownership is slightly higher in underserved counties 
(72.4 percent) than in served counties (70.8 percent).
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[[Page 65156]]

    Some differences exist between metro and nonmetro underserved 
areas. The definition is somewhat more inclusive in nonmetro areas--
the majority of the nonmetro population lives in underserved 
counties, while the majority of the metropolitan population lives in 
served areas. The majority of units in underserved metropolitan 
areas are occupied by renters, while the majority of units in 
underserved rural counties are occupied by owners. But poverty and 
unemployment rates are higher in underserved areas than in served 
areas in both nonmetropolitan and metropolitan areas.

2. Literature Review

    Research related to housing and mortgage finance issues in rural 
areas is reviewed in this section. It finds that lack of competition 
between rural lenders and lack of participation in secondary 
mortgage markets may contribute to higher interest rates and lower 
mortgage availability in rural areas. The mortgages purchased by the 
GSEs on properties in underserved counties are not particularly 
focused on lower-income borrowers and first-time homebuyers, which 
suggests that additional research needs to be conducted to target 
areas in nonmetropolitan areas which experience difficulty accessing 
mortgage credit. The role of manufactured housing in providing 
affordable housing in rural areas is also discussed.
    Mikesell Study (1998).\39\ A study by Jim Mikesell provides an 
overview of mortgage lending in rural areas. It finds that home 
loans in rural areas have higher costs, which can be attributed to 
at least three factors that characterize rural mortgage markets. 
First, the fixed cost associated with rural lending may be higher as 
a result of the smaller loan size and remoteness of many rural 
areas. Second, there are fewer mortgage lenders in rural areas 
competing for business, which may account for higher interest rates. 
Third, the secondary mortgage market is not as well developed as in 
metropolitan areas.
    Higher interest rates for rural mortgages are documented by the 
Federal Housing Finance Board's monthly survey of conventional home 
purchase mortgages. On average, relative to rates on mortgages in 
urban areas, rates on mortgages in rural areas in 1997 were 8 basis 
points (bp) higher on 30-year fixed rate mortgages (FRMs), 18 bp 
higher for 15-year FRMs, 38 bp higher for adjustable-rate mortgages 
(ARMs), and 52 bp higher for nonstandard loans.\40\ The higher rates 
in rural areas translate into differences in monthly payments of $3 
to $16 for a $100,000 mortgage.
    Mikesell finds that property location and small loan size are 
two factors that make lending more costly in rural areas. Borrower 
characteristics, such as income, assets, and credit history, and 
lender characteristics, such as ownership, size, and location, might 
influence loan pricing, but the influence of these factors could not 
be tested due to lack of data.
    Rural-based lenders are fewer and originate a smaller volume of 
loans than their urban counterparts. These factors contribute to 
less competition between rural lenders and a less efficient housing 
finance market, which result in higher costs for rural borrowers.
    Rural lenders are less likely than urban lenders to participate 
in the secondary mortgage market. As a result, rural borrowers do 
not receive the benefits associated with the secondary market--the 
increased competition between lenders, the greater potential supply 
of mortgage financing, and the alignment of financing costs more 
closely with those in urban markets.
    Some obstacles for rural lenders participating in the secondary 
market are that borrower characteristics and remote properties may 
not conform to the secondary market's underwriting standards. Rural 
households may have their borrowing capacity reduced by loan 
qualification standards which discount income that varies widely 
from year to year and income from self-employment held for less than 
several years. Rural properties may have one or more of the 
following characteristics which preclude a mortgage from being 
purchased by the GSEs: excessive distance to a firehouse, 
unacceptable water or sewer facilities, location on a less-than-all-
weather road, and dated plumbing or electrical systems.
    Mikesell concludes that increased participation by rural lenders 
in the secondary mortgage market would bring down lending costs and 
offset some of the higher costs characteristic of rural lending, and 
that HUD's goals for the GSEs could encourage such increased 
participation.
    MacDonald Study.\41\ This study investigates variations in GSE 
market shares among a sample of 426 non-metropolitan counties in 
eight census divisions. Conventional conforming mortgage 
originations are estimated using residential sales data, adjusted to 
exclude non-conforming mortgages. Multivariate analysis is used to 
investigate whether the GSE market share differs significantly by 
location, after controlling for the economic, demographic, housing 
stock, and credit market differences among counties that could 
affect use of the secondary markets by lenders.\42\
    MacDonald has four main findings regarding mortgage financing 
and the GSEs' purchases in rural mortgage markets. First, smaller, 
poorer and less rapidly growing non-metro areas have less access to 
mortgage credit than larger, wealthier and more rapidly growing 
areas. Second, the mortgages that are originated in the former areas 
are seldom purchased by the GSEs. Third, higher-income borrowers are 
more likely, and first-time homebuyers are less likely, to be served 
by the GSEs in underserved areas than in served areas. This suggests 
that the GSEs are not reaching out to marginal borrowers in 
underserved nonmetropolitan areas. Finally, the GSEs serve a smaller 
proportion of the low-income market in rural areas than do 
depository institutions. This finding is consistent with studies of 
the GSEs' affordable lending performance in metropolitan areas.
    With regard to the GSEs' underwriting guidelines MacDonald makes 
two points. First, the GSEs' purchase guidelines may adversely 
affect non-metro areas where many borrowers are seasonally-or self-
employed and where houses pose appraisal problems. Second, MacDonald 
speculates that mortgage originators in nonmetropolitan areas may 
interpret guidelines too conservatively, or may not try to qualify 
non-traditional borrowers for mortgages.
    MacDonald also echoes the findings of Mikesell that the 
existence and extent of mortgage lending problems are difficult to 
identify in many rural areas because of the lack of comprehensive 
mortgage lending data. Problems that have been identified include 
the lack of market competition among small, conservative lending 
institutions typical in rural and non-metropolitan areas; 
consolidation and other changes in the financial services industry, 
which may have different consequences in rural areas than in urban 
areas; lack of access to government housing finance programs in more 
rural locations; and weak development of secondary market sources of 
funds in rural areas, exacerbating liquidity problems.
    MacDonald discusses briefly the importance of low-cost 
homeownership alternatives in rural areas. One alternative is 
manufactured (mobile) housing. In general, manufactured housing is 
less costly to construct than site-built housing. Manufactured 
housing makes up more than 25 percent of the housing stock in rural 
counties in the South and Mountain states.
    MacDonald concludes that the lower participation of the GSEs in 
underserved areas compared with served areas may result from 
additional risk components for some borrowers and from lack of 
sophistication by the lenders that serve small non-metro markets. In 
smaller and poorer counties, low volumes of loan sales to the GSEs 
may be a result of lower incomes and smaller populations. These 
counties may not have sufficient loan-generating activity to justify 
mortgage originators pursuing secondary market outlets.
    The Role of Manufactured Housing.\43\ The Joint Center for 
Housing Studies at Harvard University conducted a comprehensive 
study of the importance of manufactured housing as an affordable 
housing choice in rural communities. In all segments of the housing 
market, but especially in rural areas and among low-income 
households, manufactured housing is growing. Based on the American 
Housing Survey, in 1985, 61 percent of the manufactured housing 
stock was located in rural areas, compared with 70 percent in 1993. 
Between 1985 and 1993, manufactured housing increased over 2.2 
percent annually while all other housing increased 0.7 percent per 
year. In 1993, 6.0 percent (or 6 million) of households lived in 
manufactured housing.
    Since the 1970's, the face of manufactured housing has changed. 
Once a highly mobile form of recreational housing in this country, 
today manufactured housing provides basic quality, year-round 
housing for millions of American households. Most earlier units were 
placed in mobile home parks or on leased parcels of land. Today an 
increasing number of units are owned by households that also own the 
land on which the manufactured home is located.
    Manufactured housing's appeal lies in its affordability. The low 
purchase price, downpayments, and monthly cash costs of manufactured 
housing provide households

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who are priced out of the conventional housing market a means of 
becoming homeowners. The occupants of manufactured housing on 
average are younger, have less income, have less education and are 
more often white than occupants of single-family detached homes. 
This type of housing is often found in areas with persistent 
poverty, retirement destinations, areas for recreation and 
vacations, and commuting counties.
    The manufactured housing industry is well positioned for 
continued growth. The affordability of manufacturing housing is 
increasingly attractive to the growing ranks of low-income 
households. Manufactured housing is becoming more popular among 
first-time homebuyers and the elderly, both of which are growing 
segments of the housing market. The migration of people to the 
South, where manufactured housing is already highly accepted, and to 
metropolitan fringes will further increase the demand for this type 
of housing.\44\

D. Factor 3: Previous Performance and Effort of the GSEs in Connection 
With the Central Cities, Rural Areas and Other Underserved Areas Goal

    As discussed in Sections B and C, HUD has structured the 
Geographically Targeted Goal to increase mortgage credit to areas 
underserved by the mortgage markets. This section looks at the GSEs' 
past performance to determine the impact the Geographically Targeted 
Goal is having on borrowers and neighborhoods, with particular 
emphasis on underserved areas. Section D.1 reports the past 
performance of each GSE with regard to the Geographically Targeted 
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. Section 
D.3 concludes this section with an analysis of the GSEs' purchases 
in rural (nonmetropolitan) areas.

1. GSE Performance on the Geographically Targeted Goal

    This section discusses each GSE's performance under the 
Geographically Targeted Goal over the 1993-99 period. The data 
presented here are ``official results'' i.e., they are based on 
HUD's in-depth analysis of the loan-level data submitted annually to 
the Department, subject and the counting provisions contained in 
Subpart B of HUD's December 1, 1995 Regulation of Fannie Mae and 
Freddie Mac. As explained below, in some cases these ``official 
results'' differ to some degree from goal performance reported by 
the GSEs in their Annual Housing Activities Reports to the 
Department.
    HUD's goals specified that in 1996 at least 21 percent of the 
number of each GSE's units eligible to count toward the 
Geographically Targeted Goal should qualify as geographically 
targeted, and at least 24 percent should qualify in 1997 and 1998. 
Actual performance, based on HUD analysis of GSE loan-level data, 
was as follows:

----------------------------------------------------------------------------------------------------------------
                                                       1996            1997            1998            1999
----------------------------------------------------------------------------------------------------------------
Fannie Mae:
    Units Eligible to Count Toward Goal.........       1,891,896       1,765,347       3,546,302       2,956,155
    Geographically Targeted Units...............         532,434         508,746         958,233         791,593
    Percent Geographically Targeted.............            28.1            28.8            27.0            26.8
Freddie Mac:
    Units Eligible to Count Toward Goal.........       1,325,900       1,180,517       2,658,556       2,245,087
    Geographically Targeted Units...............         331,495         310,572         693,748         618,385
    Percent Geographically Targeted.............            25.0            26.3            26.1            27.5
----------------------------------------------------------------------------------------------------------------

Thus, Fannie Mae and Freddie Mac surpassed the goals in 1996 by 7.1 
percentage points and 4.0 percentage points, respectively. And both 
GSEs surpassed the 1997-99 goals by at least 2 percentage points in 
each of these three years.
    Fannie Mae's performance on the Geographically Targeted Goal 
jumped sharply in just two years, from 23.6 percent in 1993 to 31.9 
percent in 1995, before tailing off to 28.1 percent in 1996. As 
indicated, it then rose slightly to 28.8 percent in 1997, before 
tailing off to 27.0 percent in 1998 and 26.8 percent in 
1999.45 Freddie Mac has shown more steady gains in 
performance on the Geographically Targeted Goal, from 21.3 percent 
in 1993 to 24.2 percent in 1994, 25.0 percent in 1995-96, just over 
26 percent in 1997-98, and 27.5 percent in 1999.46
    Fannie Mae's performance on the Geographically Targeted Goal has 
surpassed Freddie Mac's in every year from 1993 through 1998. 
However, Freddie Mac's 1999 performance represented a 26 percent 
increase over the 1993 level, exceeding the 14 percent increase for 
Fannie Mae. As a result, Freddie Mac's performance in 1999 (27.5 
percent) was 103 percent of Fannie Mae's geographically targeted 
share last year (26.8 percent)--the only year in which Freddie Mac's 
performance on this goal has exceeded Fannie Mae's performance. The 
main reason why Freddie Mac moved past Fannie Mae in performance on 
the Geographically Targeted Goal last year is that the 
geographically-targeted share of Freddie Mac's total single-family 
mortgage purchases rose from 24.5 percent in 1998 to 26.7 percent in 
1999, exceeding the corresponding increase for Fannie Mae, from 24.8 
percent in 1998 to 25.5 percent in 1999. A second reason why Freddie 
Mac surpassed Fannie Mae in performance on this goal last year is 
that multifamily properties are ``goal-rich''-that is, they are more 
likely to be in underserved areas than single-family units, and the 
multifamily share of purchases eligible for this goal rose slightly 
for Freddie Mac, from 8.3 percent in 1998 to 8.5 percent in 1999, 
but fell somewhat for Fannie Mae, from 10.4 percent in 1998 to 9.8 
percent in 1999.

2. GSEs' Mortgage Purchases in Metropolitan Neighborhoods

    As shown in Table B.5, metropolitan areas accounted for about 85 
percent of total GSE purchases under the Geographically Targeted 
Goal in 1998 and 1999. 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 that of 
portfolio lenders and 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. In subsection 2.b., the characteristics of the GSEs' 
purchases within underserved areas are compared with those for their 
purchases in served areas.
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a. Comparisons With the Primary Market

    Overview and Main Conclusions. Tables A.3 and A.4a in Appendix A 
provided information on the GSEs' funding of home purchase loans for 
properties located in underserved neighborhoods for the years 1993 
to 1998. 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. While 
both GSEs improved their performance over the 1993-1998 period, they 
lagged the conventional conforming market in providing affordable 
loans to underserved neighborhoods. As discussed in Appendix A, the 
two GSEs showed very different patterns of lending--Freddie Mac was 
much less likely than Fannie Mae to fund home loans in underserved 
neighborhoods through 1998. The percentage of Freddie Mac's 
purchases financing properties in underserved census tracts was 
substantially less than the percentage of total market originations 
in these tracts; furthermore, by 1998 Freddie Mac had not made 
progress closing the gap with the primary market. Fannie Mae, on the 
other hand, was much closer to 1998 market levels in its funding of 
underserved areas. The GSE data for 1999 show a shift in these 
patterns--during 1999, Freddie Mac surpassed Fannie Mae in funding 
mortgages in underserved neighborhoods.
    Freddie Mac--1993-1998. While Freddie Mac lagged Fannie Mae, 
portfolio lenders, and the overall conforming market in providing 
home loans to underserved neighborhoods during the 1993-1998 period, 
it pulled ahead of Fannie Mae during 1999 in purchasing mortgages 
for properties located in urban underserved areas (discussed below). 
Over the 1993-1998 period, underserved census tracts accounted for 
19.7 percent of Freddie Mac's single-family home mortgages, compared 
with 22.9 percent of Fannie Mae's purchases, 26.3 percent of loans 
originated and held in portfolio by depository lenders, and 24.5 
percent of the overall conforming primary market. If the analysis is 
restricted to the 1996-98 period during which the current housing 
goals have been in effect, the data continue to show that Freddie 
Mac lagged the market in funding underserved neighborhoods (see 
Table A.3 in Appendix A). In 1998, underserved census tracts 
accounted for 20.0 percent of Freddie Mac's purchases and 24.6 
percent of loans originated in the conforming home purchase market, 
yielding a ``Freddie Mac-to-market'' ratio of only 0.81 (i.e. 20.0 
divided by 24.6).
    Fannie Mae--1993-1998. Over the longer 1993-98 period and the 
more recent 1996-98 period, Fannie Mae has lagged the market and 
portfolio lenders in funding properties in underserved areas, but to 
a much smaller degree than Freddie Mac. During the 1996-98 period, 
underserved tracts accounted for 22.9 percent of Fannie Mae's 
purchases, compared with 25.8 percent of loans retained in portfolio 
by depositories and with 24.9 percent of home loans originated in 
the conventional conforming market. Fannie Mae's performance is much 
closer to the market than Freddie Mac's performance, as can be seen 
by the ``Fannie Mae-to-market'' ratio of 0.92 for the 1996-98 period 
(i.e. 22.9 divided by 24.9).Fannie Mae's performance improved during 
1997, due mainly to Fannie Mae's increased purchases during 1997 of 
prior-year mortgages in underserved neighborhoods. Overall, Fannie 
Mae's purchases of home loans in underserved areas increased from 
22.3 percent in 1996 to 23.5 percent in 1997. The underserved area 
percentage for Fannie Mae's purchases of newly-originated mortgages 
was actually lower in 1997 (20.8 percent) than in 1996 (21.9 
percent). This decline was offset by the fact that a particularly 
high percentage (30.1 percent) of Fannie Mae's 1997 purchases of 
prior-year mortgages was for properties in underserved areas. Thus, 
Fannie Mae improved its overall performance in 1997 by supplementing 
its purchases of newly-originated mortgages with purchases of prior-
year mortgages targeted to underserved neighborhoods. As shown in 
Table A.4a in Appendix A, Fannie Mae continued this strategy in 
1998, but not in 1999. The annual data in Table A.4a show the 
progress that Fannie Mae has made in closing the gap between its 
performance and that of the overall market. 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 22.9 percent of 
Fannie Mae's purchases and 24.6 percent of market originations, for 
a higher ``Fannie Mae-to-market'' ratio of 0.93. Freddie Mac, on the 
other hand, fell further behind the market during this period. In 
1992, Freddie Mac had a slightly higher underserved area percentage 
(18.6 percent) than Fannie Mae (18.3 percent). However, Freddie 
Mac's underserved area percentage had only increased to 20.0 percent 
by 1998 (versus 22.9 percent for Fannie Mae). Thus, the ``Freddie 
Mac-to-market'' ratio fell from 0.84 in 1992 to 0.81 in 1998.
    1999 GSE Purchases. In 1999, Freddie Mac's funding of both home 
purchase loans and total (combined home purchase and refinance) 
loans in underserved neighborhoods improved to the point that it 
surpassed Fannie Mae's performance. In 1999, underserved areas 
accounted for 21.2 percent of Freddie Mac's purchases of home 
purchase loans in metropolitan areas--a figure slightly higher than 
the 20.6 percent for Fannie Mae. With respect to combined home 
purchase and refinance loans, Freddie Mac's underserved areas 
percentage in metropolitan areas jumped by 2.6 percentage points, 
from 20.9 percent in 1998 to 23.5 percent in 1999, while the 
corresponding percentage for Fannie Mae increased by only 0.6 
percentage point, from 21.2 percent in 1998 to 21.8 percent in 1999.
    Down Payment Characteristics. Table B.6 reports the down payment 
and borrower income characteristics of mortgages that the GSEs 
purchased in underserved areas during 1999. Two points stand out. 
First, loans on properties in underserved areas were more likely to 
have a high loan-to-value ratio than loans on properties in served 
areas. Specifically, about 15.4 percent of loans in underserved 
areas had a down payment less than ten percent, compared with 13.4 
percent of all loans purchased by the GSEs. Second, loans to low-
income borrowers in underserved areas were typically high down 
payment loans. Approximately 70 percent of the GSE-purchased loans 
to very low-income borrowers living in underserved areas had a down 
payment more than 20 percent.
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b. Characteristics of GSEs' Purchases of Mortgages on Properties in 
Metropolitan Underserved Areas

    Several characteristics of loans purchased by the GSEs in 
metropolitan underserved areas are presented in Table B.7. As shown, 
borrowers in underserved areas are more likely than borrowers in 
served areas to be first-time homebuyers, females, and older than 40 
or younger than 30. And, as expected, they are more likely to have 
below-median income and to be members of minority groups. For 
example, first-time homebuyers make up 12.0 percent of the GSEs' 
mortgage purchases in underserved areas and 10.4 percent of their 
business in served areas. In underserved areas, 54.7 percent of 
borrowers had incomes below the area median, compared with 35.9 
percent of borrowers in served areas.
    Minorities' share of the GSEs' mortgage purchases in underserved 
areas (30.1 percent) was nearly three times their share in served 
areas (11.4 percent). And the pattern was even more pronounced for 
African Americans and Hispanics, who accounted for 20.9 percent of 
the GSEs' business in underserved areas, but only 5.5 percent of 
their purchases in served areas.

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3. GSE Mortgage Purchases in Nonmetropolitan Areas

    Nonmetropolitan mortgage purchases made up 13 percent of the 
GSEs' total mortgage purchases in 1999. Mortgages in underserved 
counties made up 39 percent of the GSEs' business in nonmetropolitan 
areas. \47\
    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 is provided by the Home 
Mortgage Disclosure Act (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.8 compares borrower and 
loan characteristics for the GSEs' mortgage purchases in served and 
underserved areas.
    The GSEs are slightly less likely to purchase loans for first-
time homebuyers and more likely to purchases mortgages for high-
income borrowers in underserved than in served counties. Mortgages 
to first-time homebuyers accounted for 8.4 percent of the GSEs' 1999 
mortgage purchases in served counties, compared with 7.3 percent of 
their purchases in underserved counties. Surprisingly, borrowers in 
served counties were more likely to have incomes below the median 
than in underserved counties (37.9 percent, compared to 33.6 
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.
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    There are similarities and differences between the types of 
loans that Fannie Mae and Freddie Mac purchase in served and 
underserved counties. The GSEs are similar in that they are more 
likely to purchase refinance loans in underserved counties than in 
served counties and that, in general, mortgage purchases with loan-
to-value ratios above 80 percent are more likely to be in 
underserved counties than in served counties. The GSEs differ in 
that Freddie Mac is more likely to purchase seasoned mortgages in 
served than in underserved counties, while the reverse is true for 
Fannie Mae.

E. Factor 4: Size of the Conventional Conforming Mortgage Market for 
Underserved Areas

    HUD estimates that underserved areas account for 29-32 percent 
of the conventional conforming mortgage market. The analysis 
underlying this estimate is detailed in Appendix D.

[[Page 65164]]

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.

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 discussions with the Office of 
Federal Housing Enterprise Oversight, HUD concludes that the goals 
raise minimal, if any, safety and soundness concerns.

H. Determination of the Geographically-Targeted Areas Housing Goals

    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 
established at 31 percent of eligible units financed in each of 
calendar years 2001-03. The 2001-03 goal will remain in effect in 
subsequent years, unless changed by the Secretary prior to that 
time. The goal represents an increase over the 1996 goal of 21 
percent and the 1997-2000 goal of 24 percent. However, it is 
commensurate with the market share estimates of 29-32 percent, 
presented in Appendix D.
    This section summarizes the Secretary's consideration of the six 
statutory factors that led to the choice of these goals. It 
discusses the Secretary's rationale for defining these 
geographically-targeted 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. Credit Needs in Metropolitan Areas

    HUD's analysis of HMDA data shows that mortgage credit flows in 
metropolitan areas are substantially lower in high-minority and low-
income neighborhoods and mortgage denial rates are much higher for 
residents of such neighborhoods. The economics literature discusses 
the underlying causes of these disparities in access to mortgage 
credit, particularly as related to the roles of discrimination, 
``redlining'' of specific neighborhoods, and the barriers posed by 
underwriting guidelines to potential minority and low-income 
borrowers. Studies reviewed in Section B of this Appendix found that 
the racial and income composition of neighborhoods influence 
mortgage access even after accounting for demand and risk factors 
that may influence borrowers' decisions to apply for loans and 
lenders' decisions to make those loans. Therefore, the Secretary 
concludes that high-minority and low-income neighborhoods in 
metropolitan areas are underserved by the mortgage system.

2. Identifying Underserved Portions of 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: \48\ application denial rates and mortgage 
origination rates per 100 owner-occupied units.\49\ Tables B.1 and 
B.2 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.\50\ Aggregating this data is 
useful in order to examine denial and origination rates for broader 
groupings of census tracts:

----------------------------------------------------------------------------------------------------------------
                                          Denial rate   Orig.                               Denial rate   Orig.
     Minority composition  (percent)        (percent)    rate     Tract income  (percent)     (percent)    rate
----------------------------------------------------------------------------------------------------------------
0-30....................................         11.4     16.4  Less than 90..............         19.8     10.7
30-50...................................         17.2     12.5  90-120....................         13.0     15.5
50-100..................................         21.9      9.4  Greater than 120..........          8.3     19.2
----------------------------------------------------------------------------------------------------------------

Two points stand out from these data. 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.\51\ 
Second, census tracts with lower incomes have higher denial rates 
and lower origination rates than higher income tracts. Tracts with 
income less than or equal to 90 percent of area median income have 
nearly 2.5 times the denial rate and three-fourths the origination 
rate for tracts with income over 120 percent of area median income.
    In 1995, HUD's research determined that ``underserved areas'' 
could best be characterized in metropolitan areas as census tracts 
with minority population of at least 30 percent in 1990 and/or 
census tract median income no greater than 90 percent of area median 
income in 1990, excluding high-minority high-income tracts. These 
cutoffs produced sharp differentials in denial and origination rates 
between underserved areas and adequately served areas. For example, 
the mortgage denial rate in underserved areas (19.4 percent) was 
nearly twice that in adequately served areas (10.3 percent) in 1999.
    These minority population and income thresholds apply in the 
suburbs as well as in OMB-defined central cities. HUD's research has 
found that the average denial rate in underserved suburban areas is 
almost twice that in adequately served areas in the suburbs. (See 
Figure B.1 in Section B of this Appendix.) 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. And HUD's definition, which covers 57 percent of the 
central city population and 33 percent of the suburban population, 
is clearly preferable to a definition which would count 100 percent 
of central city residents and zero percent of suburban residents as 
living in underserved areas.
    This definition of metropolitan underserved areas includes 
21,586 of the 46,904 census tracts in metropolitan areas, covering 
44 percent of the metropolitan population. It includes 73 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 rental units comprise 52.4 percent of total units 
in underserved tracts, versus 28.6 percent of total units in served 
tracts. As shown in Table B.9, this definition covers most of the 
population in the nation's most distressed central cities: Newark 
(99 percent), Detroit (96 percent), Hartford (97 percent), and 
Cleveland (90 percent). The nation's five largest cities also 
contain large concentrations of their population in underserved 
areas: New York (62 percent), Los Angeles (69 percent), Chicago (77 
percent), Houston (67 percent), and Philadelphia (80 percent).
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BILLING CODE 4210-27-C

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3. Identifying Underserved Portions of Nonmetropolitan Areas

    Recognizing the difficulty of defining rural underserved areas 
and the need to encourage GSE activity in such areas, HUD has chosen 
a rather broad, county-based definition of underservedness in rural 
areas. Specifically, a nonmetropolitan county is underserved if in 
1990 (1) county median family income was less than or equal to 95 
percent of the greater of state or national nonmetropolitan income 
or (2) county median family income was less than or equal to 120 
percent of the greater of state or national nonmetropolitan income 
and county minority population was at least 30 percent of total 
county population. This definition includes 1,511 of the 2,305 
counties in nonmetropolitan areas and covers 54 percent of the 
nonmetropolitan population. The definition does target the most 
disadvantaged rural counties--it includes as underserved areas 67 
percent of the nonmetropolitan poor and 75 percent of 
nonmetropolitan minorities. The average poverty rate in underserved 
counties in 1990 was 21 percent, significantly greater than the 12 
percent poverty rate in counties designated as adequately served. 
The definition also includes 84 percent of the population that 
resides in remote counties that are not adjacent to metropolitan 
areas and have fewer than 2,500 residents in towns.

4. Past Performance of the GSEs

    The GSEs' performance on the geographically-targeted goal has 
improved significantly in recent years, as shown in Figure B.2. 
Fannie Mae's performance, as measure by HUD, increased sharply from 
23.6 percent in 1993 to 31.9 percent in 1995, dropped to 28.1 
percent in 1996, rose to 28.8 percent in 1997, and then dropped to 
27.0 percent in 1998 and 26.8 percent in 1999. Freddie Mac's 
performance, as measured by HUD, rose from 21.8 percent in 1993 to 
26.4 percent in 1995, followed by 25.0 percent in 1996, 26.3 percent 
in 1997, 26.1 percent in 1998, and 27.5 percent in 1999. Last year 
was the only year in which Freddie Mac's performance on this goal 
has exceeded Fannie Mae's performance.
    While both GSEs improved their performance in underserved areas 
during the past six years, they lagged the conforming primary market 
in providing single-family home loans to distressed neighborhoods. 
As discussed in Section D, the GSEs show different patterns of 
lending--through 1998 Freddie Mac was less likely than Fannie Mae to 
purchase home loans on properties in low-income and high-minority 
neighborhoods. During the 1996-98 period, Freddie Mac lagged Fannie 
Mae, portfolio lenders, and the overall conforming market in 
providing funds to underserved neighborhoods. As shown in Figure 
B.3, underserved areas accounted for 20.0 percent of Freddie Mac's 
1998 purchases of home loans, compared with 22.9 percent of Fannie 
Mae's purchases, 26.1 percent of home loans retained in 
depositories' portfolios, and 24.6 percent of the overall conforming 
market. While Freddie Mac did not make any progress during the 1993-
98 period in reducing the gap between its performance and that of 
the conventional conforming home purchase market, Fannie Mae 
improved its funding in underserved areas and closed the gap between 
its performance and the single-family primary market in funding low-
income and high-minority neighborhoods.\52\ However, between 1998 
and 1999, Freddie Mac improved its purchases in underserved areas so 
much that its performance surpassed Fannie Mae's performance. In 
1999, underserved areas accounted for 21.2 (23.5) percent of Freddie 
Mac's purchases of home (total) loans, compared with 20.6 (21.8) 
percent of Fannie Mae's purchases of home (total) loans.
    HUD also conducted an analysis of the share of the overall 
(single-family and multifamily) conventional conforming mortgage 
market accounted for by the GSEs. As shown in Tables A.7a and A.7b 
of Appendix A, the GSEs' purchases represented 40/55 percent of 
total dwelling units financed during 1997/1998, but they represented 
only 33/46 percent of the dwelling units financed in underserved 
neighborhoods. In other words, the GSEs accounted for less than half 
of the single-family and multifamily units financed in underserved 
areas. This suggests that there is room for the GSEs to increase 
their purchases in underserved neighborhoods.

5. Size of the Mortgage Market for Geographically-Targeted Areas

    As detailed in Appendix D, the market for mortgages in 
geographically-targeted areas accounts for 29 to 32 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 Geographically-Targeted Areas Housing Goal for 2001-03

    There are several reasons that the Secretary is increasing the 
Geographically Targeted Areas Goal. First, the present 24 percent 
goal level for 1997-2000 and the GSEs' recent performance are below 
the estimated 29-32 percent of the primary mortgage market accounted 
for by units in properties located in geographically-targeted areas. 
Raising the goal reflects the Secretary's concern that the GSEs 
close the remaining gap between their performance and that of the 
primary mortgage market.
    Second, the single-family-owner mortgage market in underserved 
areas has demonstrated remarkable strength over the past few years 
relative to the preceding period. This market had only recently 
begun to grow in 1993 and 1994, the latest period for which data was 
available when the 1996-99 goals were established in December 1995. 
But the historically high underserved areas share of the primary 
single-family mortgage market attained in 1994 has been maintained 
over the 1995-99 period. The three-average of the underserved areas 
share of the single-family-owner mortgage market in metropolitan 
areas was 22.2 percent for 1992-94, but 25.1 percent for 1995-98 and 
24.1 percent for the 1992-98 period as a whole.
    Third, as discussed in detail in Appendix A, there are several 
market segments that would benefit from a greater secondary market 
role by the GSEs; many of these market segments are concentrated in 
underserved areas. For example, one such area is single-family 
rental dwellings. These properties, containing 1-4 rental units, are 
an important source of housing for families in low-income and high-
minority neighborhoods. However, the GSEs' purchases accounted for 
only 14/19 percent of the single-family rental units financed in 
underserved areas during 1997/1998. The Secretary believes that the 
GSEs can do more to play a leadership role in providing financing 
for such properties. Examples of other market segments in need of an 
enhanced GSE role include small multifamily properties, 
rehabilitation loans, seasoned CRA loans, and manufactured housing. 
Additional efforts by the GSEs in these markets would benefit 
families living in underserved areas.
    Finally, a wide variety of quantitative and qualitative 
indicators indicate that the GSEs' have the financial strength to 
improve their affordable lending performance. For example, combined 
net income has risen steadily over the last decade, from $677 
million in 1987 to $6.1 billion in 1999, an average growth rate of 
20 percent per year. This financial strength provides the GSEs with 
the resources to lead the industry in supporting mortgage lending 
for properties located in geographically-targeted areas.
    Summary. Figure A.4 of Appendix A summarizes many of the points 
made in this section regarding opportunities for Fannie Mae and 
Freddie Mac to improve their overall performance on the 
Geographically-Targeted Goal. The GSEs' purchases provided financing 
for 6,507,173 dwelling units, which represented 55 percent of the 
11,744,804 single-family and multifamily units that were financed in 
the conventional conforming market during 1998. However, in the 
underserved areas part of the market, the 1,679,464 units that were 
financed by GSE purchases represented only 46 percent of the 
3,629,144 dwelling units that were financed in the market in 1998. 
Thus, there appears to be ample room for the GSEs to increase their 
purchases in underserved areas. It is hoped that expression of 
concern in the current rulemaking will foster additional effort by 
both GSEs to increase their purchases in underserved areas.

7. Conclusions

    Having considered the projected mortgage market serving 
geographically-targeted areas, economic, housing and demographic 
conditions for 2001-03, and the GSEs' recent performance in 
purchasing mortgages on properties in geographically-targeted areas, 
the Secretary has determined that the annual goal of 31 percent in 
calendar year 2001 and the years following is feasible. Moreover, 
the Secretary has considered the GSEs' ability to

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lead the industry as well as the GSEs' financial condition. The 
Secretary has determined that these goal levels are necessary and 
appropriate.

Endnotes to Appendix B

    \1\ Tracts are excluded from the analysis if median income is 
suppressed or there are no owner-occupied 1-4 unit properties. There 
are 2,033 such tracts. When reporting denial, origination, and 
application rates, tracts are excluded from the analysis if there 
are no purchase or refinance applications. Tracts are also excluded 
from the analysis 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 
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.
    \2\ For the sake of brevity, in the remainder of this appendix, 
the term ``central city'' is used to mean ``OMB-designated central 
city.''
    \3\ Alicia H. Munnell, Lynn Browne, James McEneaney, and 
Geoffrey Tootell. 1996. ``Mortgage Lending in Boston: Interpreting 
HMDA Data,'' American Economic Review, 86(1) March:25-54.
    \4\ Mortgage Lending Discrimination: A Review of Existing 
Evidence edited by Margery A. Turner and Felicity Skidmore, The 
Urban Institute: Washington, D.C., June 1999.
    \5\ Margery A. Turner, Raymond J. Struyk, and John Yinger. 
Housing Discrimination Study: Synthesis, Washington, D.C., U.S. 
Department of Housing and Urban Development: 1991.
    \6\ Margery A. Turner, ``Discrimination in Urban Housing 
Markets: Lessons from Fair Housing Audits,'' Housing Policy Debate, 
Vol. 3, Issue 2, 1992, pp. 185-215.
    \7\ The denial rates in Table B.1 are for home purchase 
mortgages. Denial rates are several percentage points lower for 
refinance loans than for purchase loans, but denial rates follow the 
same pattern for both types of loans: rising with minority 
concentration and falling with increasing income.
    \8\ 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.
    \9\ A HUD study also found mortgage denial rates for minorities 
to be higher in ten metropolitan areas, even after controlling for 
credit risk. In addition, the higher denial rates observed in 
minority neighborhoods were not purely a reflection of the higher 
denial rates experienced by minorities. Whites experienced higher 
denial rates in some minority neighborhoods than in some 
predominantly white neighborhoods. Ann B. Schnare and Stuart A. 
Gabriel, ``The Role of FHA in the Provision of Credit to 
Minorities,'' ICF Incorporated, prepared for the U.S. Department of 
Housing and Urban Development, April 25, 1994.
    \10\ William C. Hunter, ``The Cultural Affinity Hypothesis and 
Mortgage Lending Decisions,'' WP-95-8, Federal Reserve Bank of 
Chicago, 1995.
    \11\ 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.
    \12\ 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.
    \13\ 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.
    \14\ 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.
    \15\ Like early HMDA studies, an analysis of deed transfer data 
in Boston found lower rates of mortgage activity in minority 
neighborhoods. The discrepancies held even after controlling for 
income, house values and other economic and non-racial factors that 
might explain 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.
    \16\ 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 Science 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 Affairs, Volume 
11, No. 3, 1989, pp. 201-223.
    \17\ Individual loan characteristics include loan size 
(economies of scale cause lenders to prefer large loans to small 
loans) and all individual borrower variables included in the HMDA 
data (the applicant's income, sex, and race).
    \18\ Their neighborhood risk proxies include median income and 
house value (inverse indicators of risk), percent of households 
receiving welfare, median age of houses, homeownership rate (an 
inverse indicator), vacancy rate, and the rent-to-value ratio (an 
inverse indicator). A high rent-to-value ratio suggests lower 
expectations of capital gains on properties in the neighborhood.
    \19\ 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.
    \20\ 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.
    \21\ 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.
    \22\ 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, 88(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.
    \23\ 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.
    \24\ 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.
    \25\ Stephen L. Ross and Geoffrey M. B. Tootell, ``Redlining, 
the Community Reinvestment Act, and Private Mortgage Insurance'', 
unpublished manuscript, March, 1999.
    \26\ Lang, William W. and Leonard I. Nakamura, ``A Model of 
Redlining,'' Journal

[[Page 65170]]

of Urban Economics, Volume 33, 1993, pp. 223-234.
    \27\ Calem, Paul S. ``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.
    \28\ Ling, David C. and Susan M. Wachter, ``Information 
Externalities and Home Mortgage Underwriting,'' Journal of Urban 
Economics, Volume 44, 1998, pp. 317-332.
    \29\ 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.
    \30\ The Preamble to the 1995 Rule provides additional reasons 
why central city location should not be used as a proxy for 
underserved areas.
    \31\ Federal Register, October 20, 1999, ``Office of Management 
and Budget: Recommendations from the Metropolitan Area Standards 
Review Committee to the Office of Management and Budget Concerning 
Changes to the Standards for Defining Metropolitan Areas.''
    \32\ 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. The tract's 
minority composition and central city location were included to test 
if these characteristics were associated with underserved 
neighborhoods after controlling for the demand and supply variables. 
Examples of the demand and supply variables at the census tract 
level include: tract income relative to the area median income, the 
increase in house values between 1980 and 1990, the percentage of 
units boarded up, and the age distributions of households and 
housing units. See also Susan Wharton Gates, ``Defining the 
Underserved,'' Secondary Mortgage Markets, 1994 Mortgage Market 
Review Issue, 1995, pp. 34-48.
    \33\ For example, census tracts at 80 percent of area median 
income were estimated to have 8.6 originations per 100 owners as 
compared with 10.8 originations for tracts over 120 percent of area 
median income.
    \34\ Shear et al., p. 18.
    \35\ See Avery, et al.
    \36\ Avery et al. find very large unadjusted differences in 
denial rates between white and minority neighborhoods, and although 
the gap is greatly reduced by controlling for applicant 
characteristics (such as race and income) and other census tract 
characteristics (such as house price and income level), a 
significant difference between white and minority tracts remains 
(for purchase loans, the denial rate difference falls from an 
unadjusted level of 16.7 percent to 4.4 percent after controlling 
for applicant and other census tract characteristics, and for 
refinance loans, the denial rate difference falls from 21.3 percent 
to 6.4 percent). However, when between-MSA differences are removed, 
the gap drops to 1.5 percent and 1.6 percent for purchase and 
refinance loans, respectively. See Avery, et al., p. 16.
    \37\ Avery, et al., page 19, note that, other things equal, a 
black applicant for a home purchase loan is 3.7 percent more likely 
to have his/her application denied in an all-minority tract than in 
an all-white tract, while a white applicant from an all-minority 
tract would be 11.5 percent more likely to be denied.
    \38\ 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.
    \39\ Mikesell, Jim. Can Federal Policy Changes Improve the 
Performance of Rural Mortgage Markets, Economic Research Service, 
U.S. Department of Agriculture, Issues in Agricultural and Rural 
Finance. Agriculture Information Bulletin No. 724-12, August 1998.
    \40\ Standard mortgage types are 30-year fixed-rate mortgages, 
15-year FRMs, and 30-year adjustable rate mortgages (ARMs). These 
are the ones most often traded in the secondary markets. Nonstandard 
mortgages generally have shorter terms than the standard mortgages.
    \41\ MacDonald, Heather. Fannie Mae and Freddie Mac in Rural 
Housing Markets: Does Space Matter? Study funded as part of the 1997 
GSE Small Grants by HUD's Office of Policy Development and Research.
    \42\ MacDonald constructs a county-level mortgage market data in 
rural areas using information collected by the Department of Revenue 
for counties and states. Annual Sales Ratio Studies conducted by 
many states' Department of Revenue provide the number of sales for 
different property types. This is done by using residential sales 
recorded for property tax purposes. Other county-level variables 
used to compare rural counties are obtained from the 1990 Census of 
Population and Housing and Bureaus of labor Statistics. Data 
obtained from Census included county populations, racial 
composition, a variety of housing stock characteristics like home 
ownership rates, vacancy rates, proportion of owner-occupied mobile 
homes, median housing value in 1990, median age of the housing 
stock, proportion of units with complete plumbing, and access to 
infrastructure, e.g., public roads and sewage systems. Data 
collected from the Bureau of Labor Statistics included unemployment 
rates and residential building permits.
    \43\ The Future of Manufactured Housing, Harvard University 
Joint Center for Housing Studies, February 1997.
    \44\ Though future demand for manufactured housing is promising, 
the Joint Center notes some continued obstacles to growth. 
Challenges for the industry to overcome include a lack of 
standardization of installation procedures and product guarantees, 
exclusionary zoning laws, and certain provisions of the national 
building code.
    \45\ The official figures on goal performance shown above for 
Fannie Mae are identical with the corresponding figures present by 
Fannie Mae in its Annual Housing Activity Report to HUD except for 
1997 (HUD-reported: 28.8 percent/Fannie Mae-reported: 30.0 percent) 
and 1999 (26.8 percent/26.7 percent), reflecting minor differences 
in the application of counting rules.
    \46\ The official figures on goal performance shown above for 
Freddie Mac are identical with the corresponding figures presented 
by Freddie Mac in its Annual Housing Activity Reports to HUD except 
for 1999 (HUD-reported: 27.5 percent/Freddie Mac-reported: 27.6 
percent), reflecting minor differences in the application of 
counting rules.
    \47\ 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 (38 percent) than in metropolitan areas (22 
percent).
    \48\ HMDA provides little useful information on rural areas. 
Therefore, the HMDA data reported here apply only to metropolitan 
areas.
    \49\ Analysis of application rates are not reported here. 
Although application rates are sometimes used as a measure of 
mortgage demand, they provide no additional information beyond that 
provided by looking at both denial and origination rates. The 
patterns observed for application rates are still very similar to 
those observed for origination rates.
    \50\ As shown in Table B.1, no sharp breaks occur in the denial 
and origination rates across the minority and income deciles--
mostly, the increments are somewhat similar as one moves across the 
various deciles that account for the major portions of mortgage 
activity.
    \51\ 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.
    \52\ Although this goal is targeted to lower-income and high-
minority areas, it does not mean that GSE purchase activity in 
underserved areas derives totally from lower income or minority 
families. In 1999, above-median income households accounted for 50 
percent of the mortgages that the GSEs purchased in underserved 
areas. This suggests that these areas are quite diverse.

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

[[Page 65171]]

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

    The final rule provides that the Special Affordable Housing Goal 
is 20 percent in 2001-2003. Of the total Special Affordable Housing 
Goal for each year, each GSE must purchase multifamily mortgages in 
an amount at least equal to one percent of the GSE's combined 
(single-family and multifamily) annual average mortgage purchases 
over 1997-1999.
    Approximately 23-26 percent of the conventional conforming 
mortgage market in 2001-03 would qualify under the Special 
Affordable Housing Goal as defined in the final rule, as projected 
by HUD.
    Units that count toward the goal: Subject to further provisions 
discussed in the Preamble to this final rule regarding seasoned 
loans, 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.

B. Summary and Response to Comments

1. Multifamily Subgoal Level

    HUD's proposed rule would have set the multifamily subgoal at 
0.9 percent of the dollar volume of combined (single-family and 
multifamily) 1998 mortgage purchases in calendar year 2000, and 1.0 
percent in each of calendar years 2001-2003. This would have implied 
the following thresholds for the two GSEs:

------------------------------------------------------------------------
                                             2000  (in    2001-2003  (in
                                             billions)       billions)
------------------------------------------------------------------------
Fannie Mae..............................           $3.31           $3.68
Freddie Mac.............................            2.46            2.73
------------------------------------------------------------------------

    Both GSEs opposed establishing the special affordable 
multifamily subgoal as a percentage of their 1998 transaction 
volume, stating that 1998 was in some respects an unusual year in 
the mortgage markets. Instead, they both recommended that the 
special affordable multifamily subgoal be established as a 
percentage of a five-year average of each GSEs' transactions volume. 
Freddie Mac commented further that HUD's proposed subgoal was 
``unreasonably high.''
    Many other commenters supported the multifamily subgoal, 
although they questioned whether 1998 was the appropriate base year 
upon which to establish the subgoal. Some commenters argued that the 
proposed subgoal was too high, in light of an expected decline in 
multifamily origination volume. Others argued that the subgoal was 
too low, based on the needs of very low- and low-income families and 
families in rural areas. Comments were received from some who felt 
the subgoal should be percentage-based and move from year to year. 
Still other commenters felt that the multifamily subgoal should be 
eliminated, as it no longer appeared to serve a purpose, 
particularly since Freddie Mac had re-entered the multifamily 
market.
    From its inception, the multifamily subgoal has been viewed as a 
means for expanding and maintaining Freddie Mac's presence in the 
multifamily mortgage market. Both the multifamily mortgage market and 
Freddie Mac's multifamily transactions volume have grown significantly 
during the 1990s, indicating both increased opportunity and capacity to 
grow by Freddie Mac. While Freddie Mac continues to lag behind Fannie 
Mae somewhat in its multifamily volume, it appears to be within reach 
of catching up with its larger competitor with regard to the 
multifamily proportion of total purchases. In 1999, Fannie Mae's 
multifamily mortgage purchases were 9.5 percent of its total mortgage 
purchases and Freddie Mac's multifamily mortgage purchases were 8.3 
percent of its total mortgage purchases.
    Freddie Mac's multifamily special affordable transactions volume 
was $2.7 billion in 1998 and $2.3 billion in 1999, showing that Freddie 
Mac does have the capacity to generate significant multifamily special 
affordable transactions volume in a favorable market environment. At 
the same time, however, the Department is mindful of the fact that 
multifamily market conditions experienced during 1998-1999 may not be 
representative of future years. Because of extensive multifamily 
refinancing during 1998-1999, in particular, in conjunction with the 
widespread use of ``lockout'' provisions which place significant 
limitations on borrower's right to refinance recently originated loans, 
HUD expects conventional multifamily origination volume in 2001-2003 to 
be somewhat lower than the levels reached during 1998-1999. Based on 
partial-year information collected by the Department on GSE and CMBS 
multifamily transactions volume during 2000, it appears that 
origination volume will be somewhat lower this year than in 1999. 
Taking into consideration new information and data not available at the 
time HUD published its proposed GSE rule in March of 2000, the 
Department has determined that a modest reduction in multifamily 
special affordable goal thresholds relative to those in the proposed 
rule is reasonable and appropriate.
    There is merit to the view that 1998 was an unusual year in the 
mortgage markets. HUD's motivation in setting the subgoal based on 1998 
transactions volume was to establish the subgoal in a fair and 
reasonable manner, given the difference between the two GSEs in size 
and capacity. HUD selected a subgoal of one percent of 1998 
transactions volume in recognition of the increased capacity of the 
GSEs to conduct multifamily special affordable lending, as well as the 
need to challenge the GSEs to maintain and expand their commitment to 
this segment of the market in a manner feasible and consistent with 
safety and soundness. Now that more recent data are available, it is 
apparent that establishing the subgoal in a manner taking 1999 mortgage 
volume into consideration, along with that of 1997 and 1998, more 
accurately corresponds to the relative size and respective capabilities 
of the GSEs over the 2001-2003 goals period than would a subgoal 
established on the basis of 1998 volume alone. Accordingly, the final 
rule establishes the special affordable multifamily subgoal at the 
respective average of one percent of each GSEs' combined (single-family 
and multifamily) mortgage purchases over 1997-1999, resulting in 
subgoals somewhat lower than those in the proposed rule, but with the 
advantages of (i) being based on more recent and complete information 
regarding the differential size and resource capabilities of each GSE, 
and (ii) taking into consideration new information regarding 
multifamily conventional origination volume. This implies the following 
thresholds for the two GSEs: \1\

------------------------------------------------------------------------
                                                          2001-2003  (in
                                                             billions)
------------------------------------------------------------------------
Fannie Mae..............................................           $2.85
Freddie Mac.............................................           $2.11
------------------------------------------------------------------------

2. Multifamily Subgoal Alternatives

    In the proposed rule, HUD identified three alternative approaches 
for specifying multifamily subgoals for the GSEs based on a (i) minimum 
number of units; (ii) minimum percentage of multifamily acquisition 
volume; and (iii) minimum number of mortgages acquired. While some of 
these proposals did receive support from commenters, HUD does not see 
any compelling reason to alter the dollar-based structure of the 
multifamily subgoal as established in the 1995 rule, which can be 
updated and adapted to the current market environment by basing it upon 
recent acquisition volume. It is noteworthy that the Special Affordable 
Housing Goal, as a percentage-of-business goal based on number of units 
financed, combines elements of options (i) and (iii). HUD's decision to 
award bonus points toward the housing goals for GSE transactions 
involving small multifamily properties with 5-50 units will achieve 
some of the intended policy objectives associated with option (iii).

3. Temporary Adjustment Factor

    In the proposed rule, HUD noted that Freddie Mac's presence in the 
multifamily market has lagged far behind that in single-

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family, in part because Freddie Mac ceased purchasing multifamily 
mortgages for a period of time in the early 1990s. Freddie Mac's direct 
holdings of multifamily mortgages and guarantees outstanding as of the 
end of 1999, $16.8 billion, are much smaller than that Fannie Mae's 
$47.4 billion, not only in absolute terms, but also a percentage of all 
mortgage holdings and guarantees. Freddie Mac's multifamily holdings 
and guarantees are 2.1 percent of its total, compared with 4.3 percent 
for Fannie Mae.\2\ Freddie Mac's smaller multifamily portfolio relative 
to that of Fannie Mae has meant fewer refinance opportunities from 
within its portfolio, reducing anticipated multifamily transactions 
volume.
    Because of the importance of multifamily mortgages to GSE 
performance on the Special Affordable Housing Goal, Fannie Mae's larger 
multifamily portfolio confers a significant advantage with regard to 
goals performance. For example, in 1999, 56.0 percent of units backing 
Fannie Mae's multifamily transactions met the special affordable goal, 
representing 31.3 percent of units meeting the special affordable goal, 
when multifamily units represented only 9.5 percent of total purchase 
volume. In contrast, only 13.4 percent of Fannie Mae's single-family 
owner-occupied units met the special affordable goal.\3\
    In recognition of the implications for housing goals performance of 
differences in the relative size of multifamily portfolios between the 
two GSEs, the Conference Report on HUD's appropriations for 2000 
provides the following guidance: ``* * * the stretch affordable housing 
efforts required of each of Freddie Mac and Fannie Mae should be equal, 
so that both enterprises are similarly challenged in attaining the 
goals. This will require the Secretary to recognize the present 
composition of each enterprise's overall portfolio in order to ensure 
regulatory parity in the application of regulatory guidelines measuring 
goal compliance.'' \4\
    In order to overcome any lingering effects of Freddie Mac's 
decision to leave the multifamily market in the early 1990s, and to 
provide an incentive to continue the rapid expansion of its multifamily 
presence since then, the Department proposed a ``Temporary Adjustment 
Factor'' for Freddie Mac's multifamily mortgage purchases for purposes 
of calculating performance on the Low- and Moderate-Income Housing Goal 
and the Special Affordable Housing Goal. In determining Freddie Mac's 
performance for each of these two goals, each unit in a property with 
more than 50 units meeting one or both of these two housing goals would 
be counted as 1.2 units in calculating the numerator of the respective 
housing goal percentage. The Temporary Adjustment Factor will be 
limited to properties with more than 50 units because of separate 
provisions regarding multifamily properties with 5-50 units.
    In its comments, Freddie Mac supported the idea of a temporary 
adjustment factor; however, Freddie Mac recommended that it be set at 
1.35 instead of the 1.2 level proposed by HUD. According to Freddie 
Mac, the difference in size and age between Freddie Mac's and Fannie 
Mae's multifamily portfolios makes goal achievement easier for Fannie 
Mae. Freddie Mac also recommended that the temporary adjustment factor 
apply to all three goals and opposed any phasing out of the factor over 
the three-year goals period.
    In the period since HUD's interim housing goals took effect in 
January 1993, Freddie Mac's multifamily transactions volume has 
expanded rapidly, as noted above. Freddie Mac's 1999 multifamily 
transactions volume was $7.6 billion, compared with only $191 million 
in 1993. HUD's analysis indicates that a Temporary Adjustment Factor of 
1.2 is sufficient to provide ``regulatory parity'' consistent with the 
direction provided by the Conference Report addressing this issue. The 
Department has, therefore, decided to implement the temporary 
adjustment factor as proposed in the proposed rule. The Adjustment 
Factor of 1.2 will be applied to the Low- and Moderate-Income and 
Special Affordable Goals. The Temporary Adjustment Factor would 
terminate December 31, 2003. The Temporary Adjustment Factor will not 
apply to Fannie Mae.

4. Seasoned Mortgage Loan Purchases ``Recycling'' Requirement

    Comments submitted in response to HUD's proposed rule regarding 
``recycling requirements'' pertaining to seasoned loans are discussed 
in the Preamble, as are the Department's determinations regarding this 
matter.

C. 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 1997, the Census Bureau's 1991 
Residential Finance Survey, the 1990 Census of Population and Housing, 
Home Mortgage Disclosure Act (HMDA) data for 1992 through 1998, and 
annual loan-level data from the GSEs on their mortgage purchases 
through 1999. 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 goal.

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.
a. GSE Performance Relative to the 1996-99 Goals
    This section discusses each GSE's performance under the Special 
Affordable Housing Goal over the 1993-99 period. The data presented 
here are ``official results''--i.e., they are based on HUD's in-depth 
analysis of the loan-level data submitted annually to the Department 
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 to the Department by 
the GSEs in their Annual Housing Activities Reports.
    HUD's goals specified that in 1996 at least 12 percent of the 
number of units eligible to count toward the Special Affordable goal 
should qualify as Special Affordable, and at least 14 percent annually 
beginning in 1997. The actual performance in 1996 through 1999, based 
on HUD's analysis of loan-level data submitted by the GSEs, is shown in 
Table C.1 and Figure C.1. Fannie Mae surpassed the goal by 3.4 
percentage points and 3.0 percentage points, respectively, in 1996 and 
1997, while Freddie Mac surpassed the goal by 2.0 and 1.2 percentage 
points. In 1998, Fannie Mae exceeded the goal by 0.3 percentage point, 
while Freddie Mac exceeded the goal by 1.9 percentage points.
    Both GSEs stepped up their performance and attained their highest 
performance to date in 1999, with Fannie Mae surpassing the 14 percent 
goal by 3.6 percentage points and Freddie Mac surpassing the goal by 
3.2 percentage points (Table C.1). After lagging Freddie Mac on special 
affordable performance in 1998, Fannie Mae surpassed Freddie Mac last 
year.\5\ A major reason for Fannie Mae's record special affordable goal 
performance in 1999 was the 15 percent increase in the dollar volume of 
its special affordable multifamily purchases; Freddie Mac, on the other 
hand, experienced a 16 percent decline in such purchases between 1998 
and 1999.\6\
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    Table C.1 also includes, for comparison purposes, comparable 
figures for 1993 through 1995, calculated according to the counting 
conventions of the 1995 rule that became applicable in 1996. Each GSE's 
performance in 1996 through 1999 exceeded its performance in each of 
the three preceding years.
    The Fannie Mae figures presented above are smaller than the 
corresponding figures presented by Fannie Mae in its Annual Housing 
Activity Reports to HUD by approximately 2 percentage points in both 
1996 and 1997, 1.3 percentage points in 1998, and 1.1 percentage points 
in 1999. The difference largely reflects HUD-Fannie Mae differences in 
application of counting rules relating to counting of seasoned loans 
for purposes of this goal. In particular, HUD's tabulations reflect 
inclusion of seasoned loan purchases in the denominator in calculating 
performance under the Special Affordable goal, as discussed in Preamble 
section II(B)(6)(c) on the Seasoned Mortgage Loan Purchases 
``Recycling'' Requirement. Freddie Mac's Annual Housing Activity Report 
figures for this goal differ from the figures presented above by 0.1 
percentage point, reflecting minor differences in application of 
counting rules.
    Since 1996 each GSE has been subject to an annual subgoal for 
multifamily Special Affordable mortgage purchases, as discussed above, 
established as 0.8 percent of the dollar volume of single-family and 
multifamily mortgages purchased by the respective GSE in 1994. Fannie 
Mae's subgoal was $1.29 billion and Freddie Mac's subgoal was $988 
million for each year. Fannie Mae surpassed the subgoal by $1.08 
billion, $1.90 billion, $2.24 billion, and $2.77 billion in 1996, 1997, 
1998, and 1999, respectively, while Freddie Mac exceeded the subgoal by 
$18 million, $220 million, $1.70 billion, and $1.27 billion. Table C.1 
includes figures on subgoal performance, and they are depicted 
graphically in Figure C.2.
b. Characteristics of 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).
    Increased reliance on multifamily housing to meet goal. Tables C.2 
and C.3 show that both GSEs have increasingly relied on multifamily 
housing units to meet the special affordable goal since 1993. Fannie 
Mae's multifamily purchases represented 31.3 percent of all purchases 
qualifying for the goal in 1999, compared with 28.1 percent in 1993. 
Freddie Mac's multifamily purchases represented 21.6 percent of all 
purchases qualifying for the goal in 1999, compared to 5.5 percent in 
1993. The trends for both GSEs were steadily upward throughout the 
1993-97 period, with some decrease in multifamily share of the special 
affordable purchases since 1997.
    The other two housing categories--single-family owner and single-
family rental--both exhibited downward trends for both GSEs. In 1999 
Fannie Mae's single-family owner units qualifying for the goal 
represented 54.8 percent of all qualifying units, and Fannie Mae's 
single-family rental units were 13.9 percent of all qualifying units. 
In 1999 Freddie Mac's single-family owner units qualifying for the goal 
represented 62.0 percent of all qualifying units, and Freddie Mac's 
single-family rental units were 16.3 percent of all qualifying units.
    Reliance on household income relative to area income 
characteristics to meet goal. Tables C.2 and C.3 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 85.2 percent of Fannie Mae's units qualifying under the 
goal in 1999, compared to 80.2 percent in 1993. For Freddie Mac, very-
low-income families accounted for 84.9 percent of units qualifying 
under the goal in 1999 and 80.3 percent in 1993. In contrast, mortgage 
purchases from low-income areas (shown in the first and third columns 
in the tables) accounted for 32.0 percent of Fannie Mae's units 
qualifying under the goal in 1999, compared to 36.8 percent in 1993. 
The corresponding percentages for Freddie Mac were 33.7 percent in 1999 
and 36.3 percent in 1993. 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.
c. GSEs' Performance Relative to Market
    Section E in Appendix A used 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 were three main findings. 
First, both GSEs lag depositories and the overall market in providing 
mortgage funds for very low-income and other special affordable 
borrowers. Second, the performance of Freddie Mac through 1998 was 
particularly weak compared to Fannie Mae, the depositories, and the 
overall market. For example, between 1996 and 1998, special affordable 
borrowers accounted for 9.8 percent of the home loans purchased by 
Freddie Mac, 11.9 percent of Fannie Mae's purchases, 16.7 percent of 
home loans originated and retained by depositories, and 15.3 percent of 
all home loans originated in the conventional conforming market (see 
Table A.3 in Appendix A). While Freddie Mac improved its performance, 
it had not closed the gap between its performance and that of the 
overall market. In 1992, special affordable loans accounted for 6.5 
percent of Freddie Mac's purchases and 10.4 percent of market 
originations, for a ``Freddie-Mac-to-market'' ratio of 0.63. By 1998, 
that ratio had increased only to 0.73 (11.3 percent versus 15.5 
percent). Third, in 1999, Freddie Mac matched Fannie Mae in purchasing 
special affordable home loans. Special affordable loans accounted for 
12.5 percent of Freddie Mac's 1999 home purchase mortgages, and for 
12.3 percent of Fannie Mae's purchases. With respect to the GSEs' total 
(combined home purchase and refinance) loans, Freddie Mac's performance 
in 1999 surpassed Fannie Mae's performance. The special affordable 
category accounted for 13.3 percent of Freddie Mac's 1999 purchases, 
compared with 12.3 percent of Fannie Mae's purchases.
    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 
have accounted for 25 percent of all special affordable owner and 
rental units that were financed in the conventional conforming market 
during 1997. The GSEs' 25-percent share of the special affordable 
market was three-fifths of their 40-percent share of the overall 
market. Even in the owner market, where the GSEs account for 50 percent 
of the market, their share of the special affordable market was only 36 
percent. Similar patterns prevailed in 1998. This analysis suggests 
that the GSEs are not leading the single-family market in purchasing 
loans that qualify for the Special Affordable Goal. There is room for 
the GSEs to improve their performance in purchasing affordable loans at 
the lower-income end of the market.
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 rule. Table C.4 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 1995 were much more frequent for the 
lowest-income groups.\7\ Incidence of problems is shown for households 
in the income range covered by the special affordable goal, as well as 
for higher income households.
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    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 (31.5 
percent of renter households and 23.8 percent of owner households). In 
contrast, 3.5 percent of renter households and 7.1 percent of owner 
households with incomes above 60 percent of area median income, up to 
80 percent of area median income, had priority problems. For more than 
two-thirds of the very low-income renter families with worst case 
problems, the only problem was affordability--they did not have 
problems with housing adequacy or crowding.

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.5 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.2 
generally, and in Section D.3 with respect to multifamily housing.

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 low- and moderate-income loans and (b) the 
financial safety and soundness implications of the housing goals. Based 
on this economic analysis and discussions with the Office of Federal 
Housing Enterprise Oversight, HUD concludes that the housing goals in 
this final rule raise minimal, if any, safety and soundness concerns.

D. Determination of the 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.

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.

2. GSE Performance and the Market

a. GSEs' Single-Family Performance
    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. 
The bulk of the GSEs' low- and moderate-income mortgage purchases are 
for the higher-income portion of this category. The lowest-income 
borrowers account for approximately one-fourth of each GSE's below-
median income purchases of owner-occupied mortgages.
b. Single-Family Market Comparisons in Metropolitan Areas
    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 both GSEs lag depositories and the overall market 
in providing mortgage funds for very low-income and other special 
affordable borrowers. Figure C.3 illustrates these findings. In 1998, 
special affordable borrowers accounted for 11.3 percent of the home 
loans purchased by Freddie Mac, 13.2 percent of Fannie Mae's purchases, 
17.7 percent of home loans originated and retained by depositories, and 
15.5 percent of all home loans originated in the conventional 
conforming market. Section C also noted that Freddie Mac improved its 
performance, but it had not made much progress in closing the gap 
between its performance and that of the overall market. In 1999, 
however, Freddie Mac's funding of special affordable loans improved to 
the point that it matched Fannie Mae's performance with respect to 
purchases of home loans (12.5 percent and 12.3 percent, respectively) 
and it surpassed Fannie Mae's performance with respect to purchases of 
total combined home purchases and refinance loans (13.3 percent and 
12.3 percent, respectively).
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c. Overall Market Comparisons
    Section C compared the GSEs' role in the overall market with their 
role in the special affordable market. The GSEs' purchases have 
provided financing for 2,948,112 dwelling units, which represented 40 
percent of the 7,306,950 single-family and multifamily units that were 
financed in the conventional conforming market during 1997. However, in 
the special affordable part of the market, the 519,371 units that were 
financed by GSE

[[Page 65182]]

purchases represented only 25 percent of the 2,105,508 dwelling units 
that were financed in the market. A similar pattern prevailed in 1998. 
Thus, there appears to ample room for the GSEs to improve their 
performance in the special affordable market.

3. Reasons for Increasing the Special Affordable Housing Goal

    The reasons the Secretary is increasing the Special Affordable Goal 
are essentially the same as those given in Section H.4 of Appendix A 
for the Low- and Moderate-Income Goal. Although that discussion will 
not be repeated here, the main considerations are the following: 
Freddie Mac's re-entry into the multifamily market; the underlying 
strength of the primary mortgage market for lower-income families; the 
need for the GSEs to improve their purchases of mortgages for lower-
income families and their communities; the existence of several low-
income market segments that would benefit from more active efforts by 
the GSEs; and the substantial profits and financial capacity of Fannie 
Mae and Freddie Mac. The Department's analysis shows that the GSEs are 
not leading the market in purchasing loans that qualify for the Special 
Affordable Goal. There are also plenty of opportunities for the GSEs to 
improve their performance in purchasing special affordable loans. The 
GSEs' accounted for only 25 percent of the special affordable market in 
1997--a figure substantially below their 40-percent share of the 
overall market. Similarly, the GSEs accounted for only 33 percent of 
the special affordable market in 1998, compared with their 55-percent 
share of the overall market during that heavy refinance year.

4. Multifamily Purchases--Further Analysis

    As noted previously, the multifamily sector is especially important 
in the establishment of the special affordable housing goals for Fannie 
Mae and Freddie Mac because of the relatively high percentage of 
multifamily units meeting the special affordable goal as compared with 
single-family. For example, in 1999, 56.0 percent of units backing 
Fannie Mae's multifamily transactions met the special affordable goal, 
representing 31.3 percent of units meeting the special affordable goal, 
when multifamily units represented only 9.5 percent of total purchase 
volume.\8\
    Significant new developments in the multifamily mortgage market 
have occurred since the publication of the December 1995 rule, most 
notably the increased rate of debt securitization via Commercial 
Mortgage Backed Securities (CMBS) and a higher level of equity 
securitization by Real Estate Investment Trusts (REITs). Fannie Mae has 
played a role in establishing underwriting standards that have been 
widely emulated in the growth of the CMBS market. Freddie Mac has 
contributed to the growth and stability of the CMBS sector by acting as 
an investor.
    Increased securitization of debt and equity interests in 
multifamily property present the GSEs with new challenges as well as 
new opportunities. The GSEs are currently experiencing a higher degree 
of secondary market competition than they did in 1995. At the same 
time, recent volatility in the CMBS market underlines the need for an 
ongoing GSE presence in the multifamily secondary market. The potential 
for an increased GSE presence is enhanced by virtue of the fact that an 
increasing proportion of multifamily mortgages are originated to 
secondary market standards.
    Despite the expanded presence of the GSEs in the multifamily 
mortgage market and the rapid growth in multifamily securitization by 
means of CMBS, increased secondary market liquidity does not appear to 
have benefited all segments of the market equally. Small properties 
with 5-50 units appear to have been adversely affected by excessive 
borrowing costs as described in Appendix A. Another market segment that 
appears experiencing difficulty in obtaining mortgage credit consists 
of multifamily properties with significant rehabilitation needs. 
Properties that are more than 10 years old are typically classified as 
``C'' or ``D'' properties, and are considered less attractive than 
newer properties by many lenders and investors.
    Context. As discussed above, in the 1995 Final Rule, the 
multifamily subgoal for the 1996-1999 period was set at 0.8 percent of 
the dollar value of each GSEs' respective 1994 origination volume, or 
$998 million for Freddie Mac and $1.29 billion for Fannie Mae. Freddie 
Mac exceeded the goal by a narrow margin in 1996 and more comfortably 
in 1997-1999. Fannie Mae has exceeded the goal by a wide margin in all 
four years.
    The experience of the 1996-1999 period suggests the following 
preliminary findings regarding the multifamily special affordable 
subgoal:
     The goal has contributed toward a significantly increased 
presence by Freddie Mac in the multifamily market.
     The current goal is out of date, as it is based on market 
conditions in 1993-94. The goal has remained at a fixed level, despite 
significant growth in the multifamily market and in the GSEs' 
administrative capabilities with regard to multifamily.
    As mentioned previously, HUD's final rule establishes the 
multifamily subgoal at the respective average of one percent of each 
GSEs' combined mortgage purchases over 1997-1999. This implies the 
following thresholds for the two GSEs:

------------------------------------------------------------------------
                                                         2001-2003  (in
                                                            billions)
------------------------------------------------------------------------
Fannie Mae............................................             $2.85
Freddie Mac...........................................              2.11
------------------------------------------------------------------------

    A multifamily subgoal for 2001-2003 set at one percent of each 
GSEs' combined mortgage purchases over 1997-1999 will sustain and 
likely increase the efforts of the GSEs in the multifamily mortgage 
market, with particular emphasis upon the special affordable segment.

5. Conclusion

    HUD has determined that the Special Affordable Housing Goal in this 
final 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 20 percent in 2001-2003 is both necessary 
and achievable. HUD has also determined that a multifamily special 
affordable subgoal for 2001-2003 set at one percent of the average of 
each GSE's respective dollar volume of combined (single-family and 
multifamily) 1997-1999 mortgage purchases in is both necessary and 
achievable.

Endnotes to Appendix C

    \1\ HUD has determined that the total dollar volume of the GSEs' 
combined (single and multifamily) mortgage purchases by Fannie Mae was 
$165.3 billion in 1997, $367.6 billion 1998, and $323.0 in 1999. 
Freddie Mac's corresponding acquisition volume was $117.7 billion in 
1997, $273.2 billion in 1998, and $240.7 billion in 1999.
    \2\ Federal Reserve Bulletin, June 2000, A 35.
    \3\ Source: HUD analysis of GSE loan-level data.
    \4\ U.S. House of Representatives, Congressional Record. (October 
13, 1999), p. H10014.
    \5\ It should be noted that in all years, Fannie Mae's performance 
on the special affordable goal under HUD scoring lags performance as 
reported by Fannie Mae, because of differences pertaining to the 
``recycling'' of proceeds from the sales of portfolios of special 
affordable loans.
    \6\ Total dollar volume of multifamily purchases moved in the 
opposite direction from special affordable multifamily volume last 
year--total volume fell by 25 percent for Fannie Mae (from $12.50 
billion in 1998 to $9.39 billion in 1999), but rose by 16 percent for 
Freddie Mac (from $6.58 billion in 1998 to $7.62 billion in 1999); 
special affordable multifamily volume rose by 15 percent for Fannie Mae 
(from $3.53 billion in 1998 to $4.06 billion in 1999), but fell by 16 
percent for Freddie Mac (from $2.69 billion in 1998 to $2.26 billion in 
1999).
    \7\ Tabulations of the 1995 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.
    \8\ Source: HUD analysis of GSE loan-level data.

Appendix D--Estimating the Size of the Conventional Conforming Market 
for Each Housing Goal

A. Introduction

1. Overview of Appendix D

    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, the 
remainder of Section A summarizes the main components

[[Page 65183]]

of HUD's market-share model and identifies those parameters that 
have a large effect on the relative market shares. With this 
material as background, Section B provides an overview of the GSEs' 
main comments on, and criticisms of, HUD's market share methodology, 
as well HUD's response to those comments and criticisms. More 
detailed analyses of selected comments by the GSEs are provided 
throughout this appendix. 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 Geographically-Targeted 
(Underserved Areas) Goal, and the Special Affordable Housing Goal, 
respectively.\1\
    In developing this 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. Data on the 
multifamily mortgage market from HUD's Property Owners and Managers' 
Survey (POMS), not available at the time 1995 GSE final rule was 
published, is utilized here. 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.
    In a 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.\2\ Blackley and 
Follain correctly note that the challenge lies in getting accurate 
estimates of the model's parameters. As noted later, both GSEs 
reached the same conclusion in their comments on the proposed rule.
    This appendix reviews in some detail HUD's efforts to combine 
information from several mortgage market data bases to obtain 
reasonable values for the model's parameters. Numerous sensitivity 
analyses are performed in order to arrive at a set of reasonable 
market estimates.
    The single-family market analysis in this appendix is based 
heavily on HMDA data for the years 1992 to 1998. The HMDA data for 
1999 were not released until August 2000, which did not give HUD 
enough time to incorporate that data into the analyses reported in 
the Appendices. It should also be noted that the discussion 
sometimes focuses on the year 1997, as 1997 represents a more 
typical mortgage market than the heavy refinancing year of 1998.

2. Overview of HUD's Market Share Methodology 3

a. 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. 4 Using the Low- and 
Moderate-Income Housing Goal as an example, the market share in a 
particular year is defined as follows:

    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 
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.5 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).

b. 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:
    (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); 6
    (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).7
    (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. 
8 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.
BILLING CODE 4210-27-P

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[GRAPHIC] [TIFF OMITTED] TR31OC00.039

BILLING CODE 4210-27-C
    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 Geographically-Targeted Goal 9 
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.

c. 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), Property Owners and Managers Survey (POMS) and the 
Census Bureau's 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 1995 rule-making process and as noted in Section B below, 
an issue that the GSEs focussed on in their comments on this year's 
proposed rule. In 1997, HMDA reported about $20.0 billion in 
multifamily originations while the SMLA reported more than double 
that amount ($47.9 billion). 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 
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 G-H do.
    Goal Percentages. To derive the goal percentages for each 
property type, HUD relied heavily on HMDA, AHS, and POMS data. For 
single-family owner originations,

[[Page 65185]]

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. The 
POMS data, which were not available during the 1995 rule-making 
process, are used below to examine the rents of newly-mortgaged 
rental properties; thus, the POMS data supplements the AHS data. 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.

d. Conclusions

    HUD is using the same basic methodology for estimating market 
shares that it used during 1995. 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 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.
    During the 1995 rule-making process, HUD contracted with the 
Urban Institute to comment on the reasonableness of its market share 
approach and to conduct analyses related to specific comments 
received from the public about its market share methodology. Several 
findings from the Urban Institute reports are discussed throughout 
this appendix. Since 1995, HUD has continued to examine the 
reliability of data sources about mortgage activity. HUD's Office of 
Policy Development and Research has published several studies 
concerning the reliability of HMDA data. 10 In addition, 
since 1995, HUD has gathered additional information regarding the 
mortgages for multifamily and single-family rental properties 
through the Property Owners and Managers Survey (POMS). 
11 Findings regarding the magnitude of multifamily 
originations, as well as the rent and affordability characteristics 
of mortgages backing both single-family and multifamily rental 
properties have been made by combining data from POMS with that from 
internal Census Bureau files from the 1995 American Housing Survey-
National Sample. The results of these more recent analyses will be 
presented in the following sections.

B. Comments on HUD's Market Share Methodology

1. Overall Issues

    Both Fannie Mae and Freddie Mac stated that HUD's market share 
model (outlined in Section A above) was a reasonable approach for 
estimating the goals-qualifying (low-mod, special affordable, and 
underserved areas) shares of the mortgage market. Freddie Mac 
stated:
    We believe the Department takes the correct approach in the 
Proposed 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.12

    Similarly, Fannie Mae stated that ``* * * HUD has developed a 
reasonable model for assessing the size of the affordable housing 
market''. 13
    However, both GSEs provided extensive criticisms of HUD's 
implementation of its market methodology. Their major comments fall 
into two general areas. First, the GSEs expressed concern about 
HUD's assumptions and use of specific data elements both in 
constructing the distribution of property shares among single-family 
owner, single-family rental, and multifamily properties and in 
estimating the goals-qualifying shares for each property type. The 
GSEs contended that HUD chose assumptions and data sources that 
result in an overstatement of the market estimate for each of the 
housing goals. In particular, the GSEs claimed that HUD overstated 
the importance of rental properties (both single-family and 
multifamily) in its market model and overstated the low-mod, special 
affordable, and underserved areas shares of the single-family owner 
market.
    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 A.2 above).
    While HUD recognizes that existing mortgage market data bases 
vary in terms of comprehensiveness and quality, HUD believes that 
the GSEs have exaggerated the inadequacies of available mortgage 
market data, such as HMDA-reported data on the borrower income and 
census tract characteristics of mortgages for single-family owner 
properties. In addition, as explained below and demonstrated 
throughout this appendix, 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.
    Second, both GSEs argued that HUD's market estimates depended 
heavily on a continuation of recent conditions of economic expansion 
and low interest rates. According to the GSEs, HUD's range of market 
estimates did not include periods of adverse economic and 
affordability conditions such as those which existed in the early 
1990s. HUD believes that the range for the market shares should be 
broad enough to reflect the likely volatility in the mortgage market 
over the three-year period (2001-03) in which the new housing goals 
will be in effect. As explained below and demonstrated throughout 
this appendix, HUD's range of market estimates for each of the 
housing goals is reasonable because it allows for economic and 
interest rate conditions significantly more adverse than have 
existed in the mid-to-late 1990s. As HUD stated in its 1995 final 
GSE rule, policy should not necessarily be based on market estimates 
that include the worst possible economic scenarios.
    To support their contentions, the GSEs made extensive criticisms 
of the inadequacies of the major mortgage market data bases (such as 
HMDA and the American Housing Survey), offering in their place 
findings from market share and simulation models they had developed. 
Fannie Mae focused many of its comments on the inadequacy of the 
single-family-owner data reported by HMDA, arguing that significant 
portions of HMDA data are not relevant for calculating the market 
standard for evaluating GSE performance in the conventional 
conforming market. Fannie Mae's comments on this topic are discussed 
and critiqued by HUD in Appendix A of this final rule. Freddie Mac 
focused many of its comments on the size of the rental portion of 
the mortgage market, concluding that HUD had overestimated that 
portion of the market. Both Fannie Mae and Freddie Mac commented 
extensively on the need for the market estimates to reflect the 
significant volatility that exists in the single-family and 
multifamily mortgage markets. In this regard, the GSEs relied 
heavily on a Freddie-Mac-funded study by PriceWaterhouseCoopers 
(PWC), entitled ``The Impact of Economic Conditions on the Size and 
the Composition of the Affordable Housing Market'' (dated April 5, 
2000). Because the GSEs' comments (especially those of Freddie Mac) 
draw heavily upon the PWC study, the next section reports and 
critiques its main findings. This analysis of the PWC report also 
incorporates related GSE comments where appropriate. Following that, 
other major issues raised by the GSEs about HUD's market estimates 
will be examined.
    The discussion in the remainder of this section assumes readers 
are familiar with the market methodology and related concepts 
developed in later sections of the appendix. There is no attempt in 
this section to fully develop the various concepts. Rather, the 
purpose of this section is to provide, in one place, HUD's insights 
and comments on the more important issues raised by the GSEs in 
their comments and by PriceWaterhouseCoopers in its report. It 
should be noted that the GSEs' comments are also discussed 
throughout the development of the market share methodology in this 
appendix.

[[Page 65186]]

2. PriceWaterhouseCoopers (PWC) Study

    The main purpose of the PWC study was to address how the 
business cycle affects the affordability of mortgages originated in 
the conventional conforming mortgage market. Based on its analysis 
of the 1990-98 mortgage market, PWC concluded that (a) changing 
economic conditions can quickly impact the low-and moderate-income 
portion of the mortgage market; (b) the highly affordable economic 
conditions that have existed since 1995 are not likely to persist in 
the future; and (c) it is difficult to project affordable lending 
levels accurately. PWC argues that HUD's basing its market shares on 
the recent past may lead to unrealistic housing goals.
    HUD's review of the PWC study found that it included several 
interesting analyses and insights about economic volatility. For 
example, its regression analyses of the multifamily and affordable 
lending shares of the market highlight the impacts that shifts in 
economic conditions can have on these sectors of the market, as well 
as the difficulty in modeling changes in market conditions. The PWC 
document also included a useful critique of existing mortgage market 
data bases. In the event of a severe economic downturn, the PWC 
study will serve as an interesting reference document for 
policymakers and mortgage market analysts concerned about the 
implications of the business cycle for affordable lending.
    In relation to the policy discussion surrounding the GSE housing 
goals, however, the PWC document contains significant shortcomings. 
A major shortcoming is that the PWC document underestimates the size 
of the multifamily mortgage market by relying heavily on multifamily 
originations reported in HMDA. While HMDA is for many purposes a 
preeminent data source on single-family lending, it has been widely 
discredited as a multifamily data source due to severe 
underreporting of loan originations. Indeed, HMDA has been rejected 
as inadequate in published work by highly regarded independent 
researchers, as well as by Fannie Mae in its comments submitted in 
response to HUD's proposed rule.
    Another major shortcoming of the PWC report is an error in 
calculating the size of the single-family conventional conforming 
market. The discussion of single-family lending in the PWC document 
initially appears to contradict HUD's analysis in Appendix D of the 
proposed rule, but this is mainly because HUD's analysis is based 
upon the conforming conventional mortgage market, whereas PWC 
effectively includes FHA loans and loans above the conforming loan 
limit in portions of their analysis of the 1980-98 mortgage market. 
For example, in 1998, PWC estimates the size of the single-family 
mortgage market at $1.5 trillion. This is identical to the widely 
used estimate by the Mortgage Bankers Association (MBA) for the 
entire single-family mortgage market that year, including jumbo and 
FHA loans.\14\ Because the GSEs are prohibited from purchasing loans 
above the conforming limit, and because HUD is directed by statute 
to focus on the conventional market in setting the housing goals, it 
is necessary to restrict analyses of the mortgage market to the 
conventional conforming market if they are to be used in connection 
with the housing goals. Because of these statutory considerations, 
PWC's calculations (which effectively include mortgages outside the 
conventional conforming market) cannot be relied upon for 
policymaking purposes. PWC's error (overstating single-family 
originations), combined with their underestimating multifamily 
originations (see above), leads PWC to substantially underestimate 
the multifamily share of the conventional conforming mortgage 
market, which further leads them to substantially underestimate the 
low- and moderate-income share of the market.
    The PWC study focuses on the low-mod share of the mortgage 
market during the 1990s. PWC claims that the low-mod share of the 
market ranged from 35 percent to 56 percent during the 1990s, with a 
mean of 46 percent. These figures are contrasted with HUD's 50-55 
percent projection of the low-mod market for the years 2001-03. The 
following are observations about this and other findings in the PWC 
report.
     PWC begins its analysis by estimating the low-mod share 
of the existing mortgage market and then applying its results to an 
analysis of the low-mod share of the market for newly-originated 
mortgages. In the top portion of its Table 2, PWC assumes the low-
mod share of the existing housing stock is 50 percent. In fact, it 
can be shown empirically that the actual proportion is 56.8 percent 
based on data from AHS and the Property Owners and Managers Survey 
(POMS).\15\ PWC then proceeds to compound this error. Based on the 
mistaken assumption that 50 percent of the housing stock is occupied 
by low- and moderate-income households, PWC infers that the low-mod 
share of the stock of mortgaged owner-occupied properties is 31 
percent. Empirically, however, the correct figure is 37 percent, 
based on AHS data.
     Based on HUD's best estimates of the multifamily 
market, the multifamily mix averaged 16-17 percent for 1991-1998, 
not 8.7 percent as estimated by PWC.\16\ PWC's multifamily mix is 
unrealistically low because of their reliance on a flawed, HMDA-
based methodology which underestimates the size of the conventional 
multifamily origination market, and because they used techniques for 
estimating the size of the single-family mortgage market equivalent 
in several years to including FHA and jumbo single-family loans. 
Inclusion of loans outside the conventional conforming market is 
inappropriate for purposes of setting the housing goals, as 
discussed above.
     Although Fannie Mae relies on the PWC study, Fannie 
Mae's multifamily market estimates are higher than PWC's--for 
example, Fannie Mae's $35-$40 billion multifamily origination 
estimate for 1997 leads to a multifamily mix of 16-18 percent 
(versus 11 percent for PWC) and its $40-$45 billion estimate for 
1998 leads to a 11-12 percent multifamily mix (versus 7.3 percent 
for PWC).
     In calculating the multifamily share of housing units 
financed each year (the ``multifamily mix'') PWC compounds the 
problems associated with its unrealistically low figure for 
multifamily originations by utilizing estimates for single-family 
origination volume far exceeding realistic figures for the 
conventional conforming segment of the single-family mortgage 
market. When HUD implemented PWC's HMDA-based procedure for 
calculating the size of the multifamily market, it derived an 
average multifamily mix of 11.6 percent for 1991-1998, well above 
the PWC figure of 8.7 percent.
     Results of PWC simulations are contradicted by 
historical evidence. For example, PWC simulates a refinance boom and 
under one scenario projects that the low-mod share of the market 
would fall to 40 percent. However, during the 1998 refinance wave, 
the low-mod share of the market was 54 percent, and even GSE 
performance exceeded 45 percent, suggesting that PWC overestimates 
the effect of a refinance boom on the low-mod share.
    Mainly for the above reasons, PWC substantially underestimates 
the size of the low-mod market during the 1990s. Using realistic 
estimates of the multifamily market outlined in Section C, HUD 
derives an average low-mod share of 52 percent during the 1990s, 
substantially higher than the 46 percent average advocated by PWC.
    The remainder of the section summarizes the main comments of 
Fannie Mae and Freddie Mac on HUD's market share methodology. 
Because the GSEs relied heavily on the PWC study or a similar 
analysis, the points in this section will apply to their comments as 
well.

3. Volatility of the Mortgage Market

    Based on the PWC study and their own analyses, both GSEs 
contended that HUD had not adequately considered the impact that 
changes in the national economy could have on the size of the 
conventional conforming mortgage market. The GSEs commented that HUD 
based its market estimates on the unusually favorable economic and 
housing market conditions that have existed since 1995. Fannie Mae 
stated that HUD's analysis overstates the size of the market because 
it ``does not reflect the potential effects of a broader range of 
plausible economic scenarios''. Freddie Mac recommended that ``the 
market estimates in the Final Rule be revised to reflect the large 
impact of economic conditions on the very-low, low- and moderate-
income, and underserved areas' shares of the market''. As noted 
earlier, both GSEs relied on the PWC study which concluded that 
``interest rate movements and changes in the rate of economic growth 
are statistically significant determinants of the low- and moderate-
income share of the conventional conforming mortgage market by 
affecting both the multifamily share of aggregate lending and the 
affordability composition of single-family lending''. (PWC, page 
iv).
    As explained in Appendix A and Section F of this appendix, HUD 
understands that the current levels of interest rates, home prices, 
borrower incomes, alternative rental costs, and consumer confidence, 
as well as expectations about their future levels, play a role in 
determining whether homeownership is feasible or desirable for any 
particular household. HUD is also aware that the

[[Page 65187]]

mortgage market is very dynamic and susceptible to significant 
changes in conditions that would affect the overall level of 
affordable lending to lower-income families. HUD agrees that 
forecasting all these factors for upcoming years to obtain a picture 
of the future climate for the mortgage market is difficult.
    In response to concerns expressed about the volatility of the 
mortgage markets over time, HUD has estimated a range of market 
shares for each of the housing goals--50-55 percent of the Low-Mod 
Goal, 23-26 percent for the Special Affordable Goal, and 29-32 
percent for the Underserved Areas Goal--that reflect economic 
environments significantly more adverse than those which existed 
during the period between 1995 and 1998, when the Low-Mod Goal 
averaged 56.5 percent, the Special Affordable Goal, 28.1 percent, 
and the Underserved Areas Goal, 33.0 percent.
    HUD conducted detailed sensitivity analyses for each of the 
housing goals to reflect affordability conditions that are less 
conducive to lower-income homeownership than those that existed 
during the mid- to late-1990s. The following examples drawn from 
Sections F and H of this appendix may be helpful in clarifying this 
issue:
     The low-mod percentage for single-family home purchase 
loans can fall to as low as 34 percent--or four-fifths of its 1995-
98 average of over 42 percent--before the projected low- and 
moderate-income share of the overall market would fall below 50 
percent.
     Similarly, the underserved areas percentage for owner 
loans can fall to as low as 22 percent--also about four-fifths of 
its 1995-98 average of almost 27 percent--before the projected 
underserved areas share of the overall market would fall below 29 
percent.
    HUD also conducted additional sensitivity analyses by examining 
recession and refinance scenarios and varying other key assumptions, 
such as the size of the multifamily market. These sensitivity 
analyses, presented in this appendix, show that HUD's market 
estimates cover a range of mortgage market and affordability 
conditions and provide a sound basis for setting housing goals for 
the years 2001-03.
    HUD recognizes that under certain extremely adverse 
circumstances, the goals-qualifying market shares could fall below 
its estimates. The PWC study and the GSEs presented estimates based 
on a hypothetical economic slowdown accompanied by low affordability 
conditions that fall below the range of HUD's estimates. Fannie Mae, 
for example, included mortgage originations falling to as low as 
$771 billion and as high as $1,706 billion in its ``likely single 
family mortgage market volume ranges'' for the year 2001. However, 
as HUD stated in its 1995 GSE rule, setting goals so that they can 
be met even under the worst of circumstances is unreasonable. If 
macroeconomic conditions change dramatically, then the levels of the 
goals can be revised to reflect the changed conditions. As discussed 
below in Section F, FHEFSSA and HUD recognize that conditions could 
change in ways that would require revised expectations. Thus, HUD is 
given the statutory discretion to revise the goals if the need 
arises. If a GSE fails to meet a housing goal, HUD has the authority 
to determine that the goal was not feasible, and not take further 
action.

4. Size of the Multifamily Market

    Section C contains a detailed discussion of the size of the 
conventional multifamily origination market, summarizing findings 
from a variety of sources regarding the size of the conventional 
multifamily mortgage market, measured in terms of dollars, units, 
and as a share of total conventional conforming annual mortgage 
origination volume, a key factor influencing the share of the 
overall market comprised of units meeting each of the housing goals. 
This section considers a number of alternative data sources 
providing evidence on conventional multifamily origination volume 
over a number of years, in some cases the entire 1990-1999 period. 
The approaches considered here include the HUD Survey of Mortgage 
Lending Activity (SMLA); Home Mortgage Disclosure Act data (HMDA); 
and a projection model developed by the Urban Institute based on 
data from the 1991 Residential Finance Survey (RFS). A new 
methodology, developed by HUD for purposes of this analysis, is 
discussed, as are estimates submitted by Fannie Mae and Freddie Mac 
on their comments on the proposed rule. Estimates for 1990 from the 
RFS and for 1995 from the Property Owners and Managers Survey (POMS) 
are also discussed.
    Based on the likely range of annual conventional multifamily 
origination volume, multifamily units represent an average of 16-17 
percent of units financed each year during the 1990s.\17\ HUD's 
estimated multifamily market shares exceed estimates prepared by PWC 
(averaging 8.7 percent for 1991-1998) for two reasons, as mentioned 
previously. One is that PWC's adjusted HMDA methodology does not 
adequately correct for underreporting in HMDA, resulting in 
unrealistically low estimates of the size of the conventional 
multifamily origination market. Another reason that PWC's estimated 
multifamily market shares are low is that a number of their 
calculations appear to include FHA and jumbo loans in estimating the 
number of single-family units financed each year, as discussed 
above. HUD's market share calculations, in contrast, are based on 
the multifamily share of conventional conforming mortgage loans 
originated each year.
    The multifamily share of the conforming conventional market (or 
``multifamily mix'') derived from this discussion of multifamily 
origination volume is utilized below as part of HUD's analysis of 
the share of units financed each year meeting each of the housing 
goals. For purposes of that analysis, a multifamily mix of 16.5 
percent is reasonable, based upon the analysis and discussion below. 
However, a 15 percent market share can be utilized as an alternative 
market share estimate corresponding to a somewhat less favorable 
environment for multifamily lending. While somewhat low from an 
historical standpoint, a 15 percent mix more readily accommodates 
the possibility of a recession or heavy refinance year than would 
baseline assumptions based more strictly on historical data. In 
order to more fully consider the effects of an even more adverse 
market environments, an alternative multifamily mix assumptions of 
13.5 is also considered, as well as a number of others.

5. Size of the Single-Family Rental Market

    Both GSEs argued that the single-family (1-4) investor portion 
of the single-family mortgage market should be eight percent or less 
of total single-family originations, based on HMDA data. In both 
1995 and in the proposed rule, HUD considered three scenarios for 
investor mortgages when estimating the housing goals--a baseline 
model that assumed 10 percent, a lower scenario that assumed 8 
percent, and a higher scenario that assumed 12 percent. HUD's base 
case of 10 percent is well below the 17.3 percent reported by the 
1991 Residential Finance Survey (which is considered accurate but 
unfortunately is out-of-date) and above the 7-8 percent estimates 
provided by HMDA over the past few years. In 1995, research by Urban 
Institute researchers concluded that the HMDA estimates were too low 
(although the GSEs raise concerns about this research in their 
comments). HUD has decided to stay with its baseline 10 percent 
estimate but it acknowledges that due to limited data there is some 
uncertainty about the investor share of the single-family market, 
which will be clarified when the next Residential Finance Survey is 
released in a couple of years. Sensitivity analyses indicate that 
reducing the investor share from 10 percent to 8 percent would 
reduce the low-mod market share by 1.05 percent, the special 
affordable share by 0.90 percent, and the underserved areas share by 
0.36 percent.

6. Relevant Market for Single-Family Owner Market

    Both GSEs provided numerous comments concerning the types of 
mortgages that HUD should exclude from the definition of the single-
family owner market when HUD is calculating the market shares for 
each housing goal. The GSEs comments and HUD's response to them are 
discussed in Section A of Appendix A. As noted there, HUD believes 
that the risky, B&C portion of the subprime market should be 
excluded from the market definition for each of the housing goals. 
HUD includes the A-minus portion of the subprime market in its 
market estimates. This appendix explains HUD's method for making 
this adjustment to the overall market estimates.
    As explained in Appendix A, HUD disagrees with most of the other 
adjustments proposed by the GSEs. Excluding important segments of 
the lower-income mortgage market as the GSEs recommend would distort 
HUD's estimates of the goals-qualifying shares of the conventional 
conforming market.

7. Shortcomings of Various Mortgage Market Data Bases

    Major mortgage market data bases such as HMDA and the American 
Housing Survey (AHS) are used to implement HUD's market

[[Page 65188]]

methodology. In their comments, Fannie Mae and Freddie Mac, as well 
as PWC, each provided a useful critique of the various mortgage data 
bases. Based on its analysis, Freddie Mac concluded that HUD should 
revise its market share estimates to reflect ``the lack of reliable 
data''. Similarly, Fannie Mae concluded that ``HUD analysis 
overstates the size of the market because it relies on unreliable 
data sources. * * *''. Fannie Mae further states that ``* * * HUD 
has chosen to extrapolate from several disparate data sources in 
ways that inflate the Department's estimate of the market size for 
each of the goals''. PWC, as well as the GSEs, expressed concern 
that mortgage market data bases had not improved since 1995, when 
HUD issued its last GSE rule on the housing goals.
    Examples of problems noted by the GSEs include: limited 
variables (such as LTV ratio) and bias in HMDA data; inability of 
HMDA to identify important segments of the market (such as subprime 
lenders); underreporting of multifamily mortgages in HMDA and 
general unreliable reporting of rental mortgages in other data 
bases; underreporting of income in the AHS; and the fact that some 
important mortgage market data bases such as the 1991 Residential 
Mortgage Finance Survey are simply out of date. Both GSEs expressed 
particularly strong criticism of HUD's use of data on the rental 
market, that is, estimates of the proportion of 1-to 4-unit rental 
properties and of annual multifamily origination volume.
    HUD agrees that a comprehensive source of information on 
mortgage markets is not available. However, HUD considered and 
analyzed a number of data sources for the purpose of estimating 
market size, because no single source could provide all the data 
elements needed. In these appendices, HUD has carefully defined the 
range of uncertainty associated with each of these data sources, has 
pulled together estimates of important market parameters from 
independent sources, and has conducted sensitivity analyses to show 
the effects of various assumptions. In fact, Freddie Mac noted that 
``We [Freddie Mac] support the Department's approach for addressing 
the empirical challenges of setting the goals by examining several 
different data sets, using alternative methodologies, and conducting 
sensitivity analysis.''
    While HUD recognizes the shortcomings of the various data and 
the inability to derive precise point estimates of various market 
parameters, HUD, however, does not believe that these limitations 
call for expanding the range of the market estimates, as suggested 
by the GSEs. One purpose of this appendix is to demonstrate that 
careful consideration of independent data sources can lead to 
reliable ranges of estimates for the goals-qualifying shares of the 
mortgage market. It should also be emphasized that while there are 
some problems with existing mortgage market data, there is a wealth 
of information on important components of the market. HMDA provides 
wide coverage of the single-family owner market in metropolitan 
areas, yielding important information on the borrower income and 
census tract (underserved area) characteristics of that market. The 
AHS provides excellent information on the affordability 
characteristics of the single-family rental and multifamily housing 
stock. As explained in Section F of this appendix, POMS data confirm 
that the rent affordability data based on the AHS stock provide 
reliable estimates of the rent characteristics of newly-mortgaged 
dwelling units in the rental stock.
    HUD's specific responses to the GSEs' comments on data are 
included throughout these appendices. For example, see subsection 
B.4 above and Section C of this appendix for a discussion of the 
multifamily data; as explained there, HUD concludes that Freddie Mac 
and PWC, in particular, underestimate the size of the multifamily 
market. Issues related to single-family rental data are discussed in 
B.5 above and in Section D to this appendix. Appendix A provides a 
complete discussion of the single-family owner data reported in 
HMDA. As noted in Section A of Appendix A, HUD disagrees with the 
GSEs in terms of the seriousness of the bias problem in HMDA data. 
It should also be mentioned that HUD does not rely heavily on some 
of the data bases that the GSEs criticize. For example, Freddie Mac 
argues that the AHS underreports borrower income; but HUD relies on 
HMDA data for the borrower income characteristics of home purchase 
and refinance markets. According to the out-of-date RFS data, 
investor mortgages account for 17 percent of the single-family 
mortgage market the RFS; as explained in above, HUD's baseline model 
uses 10 percent, with sensitivity analyses at 8 percent and 12 
percent.

8. Miscellaneous Comments

    There are several specific comments of the GSEs that should be 
mentioned and clarified. In many cases, these comments relate to the 
broad issues that have already been discussed in this section. 
However, because of their technical nature, it was decided to 
discuss them in this separate section rather than including them in 
the above discussion.
     On page 17 of its Appendix III, Freddie Mac states that 
HUD assumed the investor share of single-family mortgages was 10.7 
percent; in fact, HUD's baseline model assumed 10 percent.
     On page 22 of its Appendix III, Freddie Mac states that 
because HMDA does not identify subprime and manufactured housing 
loans, the proposed rule does not adjust for these loans originated 
by prime lenders. As this appendix explains, HUD's market estimates 
for the three housing goals are adjusted for all loans originated in 
the B&C portion of the subprime market.
     On page 23 of its Appendix III, Freddie Mac states that 
HUD does not compare HMDA and GSE data with the same precision as 
Berkovec and Zorn because HUD has included HMDA-reported non-
metropolitan loans, which are poorly reported by HMDA. Freddie Mac 
is incorrect. HUD's analysis in Table A.4a is based on HMDA and GSE 
data for only metropolitan areas. In addition, HUD does not include 
GSE purchases of FHA loans in Table A.4a, as suggested by Freddie 
Mac.
     On page 1 of its Appendix III, Freddie Mac states that 
HUD's market projections ``effectively are based on an analysis of 
mortgage lending patterns since 1995.'' Freddie Mac is incorrect, as 
explained in B.3 above and throughout this appendix. For example, as 
reported in Table D.15 below, the low-mod share of the conventional 
conforming market has averaged over 56 percent since 1995; this 
compares with HUD's projection of 50-55 percent for this market.
     On page 6 of its Appendix III, Freddie Mac states that 
HMDA accurately reports multifamily originations for commercial 
banks. HUD's analysis concurs with that of other researchers that 
HMDA significantly underreports multifamily originations by 
commercial banks. For example, Crews, Dunsky and Follain (1995) 
conclude that ``HMDA surely underestimates lending by both mortgage 
bankers and commercial banks.'' \18\
     On pages 20-21, Freddie Mac uses the AHS and POMS to 
estimate the distribution of newly-mortgaged units by property type. 
Based on this analysis, Freddie Mac estimates that multifamily units 
represented 10.6 percent of newly financed dwelling units over the 
1993-95 period. Based on HUD's calculations, however, multifamily 
units were 20.6 percent of conventional conforming units financed 
during 1993-1995. Freddie Mac may have underestimated the number of 
rental units by excluding observations with missing origination 
year, and may have overestimated the number of single-family units 
by including jumbo or FHA loans.
     In its comments (page 30) about the low-mod goal, 
Freddie Mac states that ``an analysis limited to the exceptional 
economic environment since 1995 would suggest a narrow range 
centered at 50 percent * * *''. As explained in Section F of this 
appendix, the low-mod goal averaged 56.5 percent between 1995 and 
1998.
     On pages 34 and 35 of its comments, Fannie Mae states 
that HUD's approach to housing and economic conditions involves 
``point estimates''. As this appendix makes clear, HUD's analysis is 
based on a range of market estimates--not point estimates as stated 
by Fannie Mae. Of course, the ``likely single-family mortgage market 
volume ranges'' chosen by Fannie Mae are not necessarily the ones 
HUD would choose for setting housing goals for the next three years. 
Fannie Mae offers wide ranges in mortgage market projections for the 
years 2001-03; for example, $771 billion to $1,706 billion is its 
projection for the year 2001.
     Fannie Mae states ``HUD should provide an explicit 
range of goals based upon differing economic outlooks with 
reasonable chances of occurring--ranging from modest recession to a 
continued boom economy''. As demonstrated in Sections F-H, HUD's 
market ranges are reasonably set to include much more adverse 
economic and affordability conditions than have existed during the 
past few years.
     On pages 66-67, Fannie Mae estimates a market range of 
48-51 percent for the Low-Mod Goal, 21-24 percent for the Special 
Affordable Goal, and 24-28 percent for the Underserved Areas Goals; 
the range covers a recession scenario and a growth scenario and

[[Page 65189]]

adjusts for B&C loans. Fannie Mae states that its market share 
analysis supports the proposed higher levels for the new housing 
goals but it also shows that the GSEs will experience greater 
difficulty achieving the new goals (and particularly the underserved 
areas goal) than suggested by HUD's market share estimates. Fannie 
Mae assumes a lower percentage of single-family and multifamily 
rental properties than HUD, which is one reason Fannie Mae obtains 
lower market estimates than HUD. Fannie Mae assumes that the goals-
qualifying shares for the single-family owner market can fall to 
their 1993 levels when, for example, the underserved areas share of 
the owner market equaled 20 percent. As explained in Section G, 
HUD's range of market estimates (29-32 percent) for the underserved 
areas goal is consistent with the underserved areas owner percentage 
for the single-family market falling from its average of 28 percent 
over the 1995-98 period to 22 percent. Fannie Mae's assumes an 
additional two percentage point decline in its sensitivity analysis. 
It should also be noted that while Fannie Mae adjusts for B&C loans, 
it does not make the 1-2 percentage point upward adjustment to 
incorporate the effects of underserved counties in non-metropolitan 
areas.

9. Conclusions

    In considering the levels of the goals, HUD carefully examined 
the comments 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, the basic methodology employed by HUD is 
a reasonable and valid approach to estimating market share and the 
percentage range for each of the three market share estimates do not 
need to be adjusted from those reported in the proposed rule. While 
a number of technical changes have been made in response to the 
comments, the approach for determining market size has not been 
modified substantially. The detailed evaluations show that the 
methodology, as modified, produces reasonable estimates of the 
market share for each goal. 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

    This section derives projections of conventional multifamily 
mortgage origination volume.\19\
    The multifamily sector is especially important in the 
establishment of housing goals for Fannie Mae and Freddie Mac 
because multifamily properties are overwhelmingly occupied by low- 
and moderate-income families. For example, in 1999, 9.5 percent of 
units financed by Fannie Mae were multifamily, but 95 percent of 
those units met the Low- and Moderate-Income Goal, accounting for 20 
percent of all of Fannie Mae's low- and moderate-income purchases 
for that year.\20\ Multifamily acquisitions are also of strategic 
significance with regard to the Special Affordable Goal. In 1999, 43 
percent of units backing Freddie Mac's multifamily acquisitions met 
the Special Affordable Goal, representing 22 percent of units 
counted toward its Special Affordable Goal, at a time when 
multifamily units represented only 8.3 percent of total annual 
purchase volume.\21\
    This discussion is organized as follows: Section 1 identifies 
and evaluates available data resources regarding the dollar value of 
conventional multifamily mortgage origination during 1990-1999. 
Section 2 discusses loan amount per unit, a key parameter in 
estimating the number of units backing multifamily originations. 
Section 3 summarizes findings from a variety of sources regarding 
the size of the conventional multifamily mortgage market, measured 
in terms of dollars, units, and as a share of total conventional 
conforming annual mortgage origination volume, a key factor 
influencing the share of the overall market comprised of units 
meeting each of the housing goals. Inferences regarding the likely 
range and ``baseline'' estimates of annual multifamily origination 
volume for 1990-1999 are drawn.

1. Multifamily Data Sources

    This section considers a number of alternative data sources 
providing evidence on conventional multifamily origination volume 
over a number of years, in some cases the entire 1990-1999 period. 
The approaches considered here include the HUD Survey of Mortgage 
Lending Activity (SMLA); Home Mortgage Disclosure Act data (HMDA); 
and a projection model developed by the Urban Institute based on 
data from the 1991 Residential Finance Survey (RFS). A new 
methodology, developed by HUD for purposes of this analysis, is 
discussed, as are estimates submitted by Fannie Mae and Freddie Mac 
in connection with the Department's GSE rulemaking efforts. 
Estimates for 1990 from the RFS and for 1995 from the Property 
Owners and Managers Survey (POMS) are also discussed.

a. Survey of Mortgage Lending Activity (SMLA)

    The data that enter into SMLA were compiled by HUD until 1998 
from source materials generated in various ways from the different 
institutional types of mortgage lenders. Data on lending by savings 
associations were collected for HUD by the Office of Thrift 
Supervision; these data cover all thrifts, not a sample. Mortgage 
company and life insurance company data were collected through 
sample surveys conducted by the Mortgage Bankers Association of 
America and the American Council of Life Insurance, respectively. 
Data on commercial banks and mutual savings banks were collected 
through sample surveys conducted by a number of different entities 
over the years. Federal credit agencies such as the U.S. Small 
Business Administration and HUD non-FHA programs as well as State 
credit agencies such as housing finance agencies reported their data 
directly to HUD. Local credit agency data are collected by HUD staff 
from a publication that lists their mortgage financing activities. 
The SMLA was discontinued by HUD in 1998, and data are available 
only through 1997.
    Commercial bank data in the SMLA have been questioned by a 
number of researchers. Part of the problem arises from the 
possibility of double-counting of originations by mortgage banks in 
the American Bankers Association (ABA) and Mortgage Bankers 
Association (MBA) surveys conducted as part of SMLA. Originations by 
mortgage banks which are affiliated with commercial banks may be 
counted in both surveys. A 1995 analysis prepared by Crews, Dunsky 
and Follain found that, in 1993, the SMLA conventional origination 
figure of $30 billion was calculated on the basis of overstated 
originations by commercial banks, but understated lending volume by 
mortgage banks, life insurance companies, and individuals. Taking 
all of these factors into consideration, as well as other evidence, 
they conclude that actual 1993 origination volume appears to be in 
the range of $25-$30 billion. 22
    One solution to the double-counting problem in SMLA is to remove 
the mortgage bank subtotal from total origination volume. The 
resulting figure may provide a more accurate representation of 
conventional multifamily lending volume. Table D.2 presents SMLA 
figures for 1990-1997, including and excluding mortgage banks.
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b. Home Mortgage Disclosure Act (HMDA)

    HMDA data are collected by lending institutions and reported to 
their respective regulators as required by law. HMDA was enacted as 
a mechanism to permit the public to determine locations of 
properties on which local depository institutions make mortgage 
loans, ``to enable them to determine whether depository institutions 
are filling their obligations to serve the housing needs of the 
communities and neighborhoods in which they are located * * *'' (12 
U.S.C. 2801). HMDA reporting requirements generally apply to all 
depository lenders with more than $29 million in total assets and 
which have offices in Metropolitan Statistical Areas. Reporting is 
generally required of other mortgage lending institutions (e.g. 
mortgage bankers) originating at least 100 home purchase loans 
annually provided that home purchase loan originations exceed 10 
percent of total loans. Reporting is required for all loans closed 
in the name of the lending institution and loans approved and later 
acquired by the lending institution, including multifamily loans. 
Thus, the HMDA data base concentrates on lending by depository 
institutions in metropolitan areas but, unlike SMLA and RFS, it is 
not a sample survey; it is intended to include loan-level data on 
all loans made by the institutions that are required to file 
reports.
    A deficiency of the HMDA database is that there is compelling 
evidence of significant underreporting of multifamily mortgages. In 
their 1995 analysis, Crews, Dunsky and Follain conclude ``We clearly 
demonstrate that HMDA alone is not an accurate measure of the total 
market. Our argument is based upon two facts. First, HMDA was not 
designed to cover multifamily lending by all lenders; it focuses on 
lending done primarily by commercial banks, thrifts, and large 
mortgage bankers in metropolitan areas. Second, HMDA surely 
underestimates lending by both mortgage bankers and commercial 
banks.'' \23\ In its comments submitted in response to HUD's 
proposed rule, Fannie Mae observes that ``HMDA is not considered a 
reliable source of multifamily mortgage originations because it 
provides an incomplete view of non-depository institution sources of 
loans.'' \24\
    It does not appear that HMDA has significantly improved its 
multifamily coverage since the time of the 1995 Crews, Dunsky and 
Follain analysis. For example, in 1998, HMDA reports approximately 
$1 billion in FHA multifamily origination volume, compared with $2.5 
billion reported by FHA. The underreporting appears to be even more 
serious with regard to GSE acquisitions. The 1998 HMDA file reports 
approximately $2 billion in Fannie Mae multifamily transactions, 
compared with an actual total of $12.5 billion. A sizeable shortfall 
is also evident with regard to Freddie Mac, with HMDA reporting 1998 
transactions volume of $295 million, compared with an actual figure 
of $6.6 billion.
    In addition, the HMDA data base does not cover a number of 
important categories of multifamily lenders such as life insurance 
companies and State housing finance agencies, providing another 
reason that the HMDA data understates the size of the multifamily 
market.
    One way to address the undercounting problem in HMDA is to 
incorporate an adjustment factor to correct for underreporting, for 
example by multiplying each year's annual total by 1.25, as 
suggested by PriceWaterhouseCoopers (PWC) in their report prepared 
for Freddie Mac in connection with HUD's proposed rule. However, 
this 1.25 correction factor is based upon an estimate of 
underreporting of single-family loans in HMDA, and may be too small 
to accurately capture the degree of multifamily underreporting in 
HMDA, judging from comparisons between actual and HMDA-reported 
volume by the GSEs and FHA cited above.
    To the adjusted HMDA figure, PWC then adds an estimate for 
originations by life insurance companies by utilizing figures on 
multifamily loan commitments published by the American Council on 
Life Insurance (ACLI), a trade group which conducts regular surveys. 
Table D.3 shows annual conventional multifamily origination volume 
as reported in HMDA, as well as an adjusted HMDA figure including a 
1.25 correction factor as well as the ACLI figure for loan 
commitments in the last quarter of the preceding year as well as the 
first three quarters of each origination year. In calculating annual 
totals, the absolute value is taken of loan amounts reporting as 
negative numbers. The table shows a sharp drop in origination volume 
between 1990 and 1991, possibly associated with the commercial real 
estate recession of the early 1990s. However, the implication that 
multifamily mortgage lending has remained 20 percent below the 1990 
level for the entire remainder of the decade is inconsistent with

[[Page 65191]]

other data sources, and raises further concerns regarding the 
accuracy and reliability of HMDA as a multifamily data source.
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BILLING CODE 4210-27-C
    A difficulty with the adjustment factor approach is that very 
little is known regarding the degree of underreporting of 
multifamily originations in HMDA. There is no reason that the 20 
percent underreporting figure sometimes used in single-family 
discussions of HMDA is applicable to multifamily. Indeed, if the 
degree of underreporting of FHA originations or GSE acquisitions 
noted above is representative, even the adjusted HMDA figures are 
likely to significantly underreport the actual totals.

c. Urban Institute Statistical Model

    In 1995, Urban Institute researchers developed a model to 
project multifamily origination volumes from 1992 forward, based on 
data from the 1991 Survey of Residential Finance.\25\ They applied a 
statistical model of mortgage terminations based on Freddie Mac's 
experience from the mid-1970s to around 1990. While mortgage 
characteristics in 1990 are not wholly similar to the 
characteristics of these historical mortgages financed by Freddie 
Mac, nevertheless the prepayment propensities of contemporary 
mortgages may at least be approximated by the prepayment experience 
of these historical mortgages. The research methodology took account 
of the influence of interest rate fluctuations on prepayments of the 
historical mortgages; the projections assumed that prepayments are 
motivated mainly by property sales.
    Table D.4 shows annual projected conventional multifamily 
origination volume as reported in the Urban Institute model, derived 
by subtracting actual FHA origination volume from the overall 
projected multifamily total each year, except in 2000, when 1999 FHA 
originations are used as a proxy for 2000 originations.
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BILLING CODE 4210-27-C

d. New Methodology for Recent Years

    In the context of (i) the discontinuation of SMLA; (ii) evidence 
of significant underreporting in HMDA; and (iii) increased 
availability of data regarding purely private, non-GSE 
securitization of commercial mortgage loans, HUD has developed a new 
methodology for the purpose of preparing a lower-bound estimate for 
the minimum size of the multifamily market. The following sources 
are combined to calculate the estimated size of the conventional 
multifamily market in a way that is relatively complete, but which 
avoids double-counting and excludes seasoned loans:
    (1) HMDA portfolio loans. This component comprises conventional 
loans originated by depositories and not sold, plus conventional 
loans acquired by depositories but not sold, less overlap between 
these two categories. In principle, if a loan originated during the 
current year is acquired by a depository, it should show up as an 
origination. However, due to underreporting, this is not always the 
case. The procedure utilized here is to sum conventional 
originations by depositories and conventional acquisitions by 
depositories, and then to utilize a matching procedure to identify 
loans falling into both categories, which are then subtracted.
    (2) GSE purchases of current-year acquisitions. A data series on 
GSE multifamily transactions covering 1995-1999 that excludes non-
GSE securities and repurchased GSE securities is published by OFHEO 
in their 2000 Report to Congress. These exclusions are needed in 
order to avoid double-counting. However, this figure must be further 
adjusted to take into consideration the fact that some of these 
transactions involved seasoned purchases, and a few involve 
government-insured mortgages. In order to adjust the data for this 
possibility, the OFHEO figures are reduced by 33 percent, the figure 
derived by calculating the proportion of seasoned and FHA mortgages 
among the GSEs' cash and swap transactions during 1995-1999, using 
GSE loan-level data provided to HUD. Any loans sold by depositories 
to the GSEs would be counted here, but not in the HMDA component, 
which is restricted to loans kept in portfolio by depositories.
    (3) Commercial Mortgage Backed Security multifamily loans. 
Commercial Mortgage Alert, Hoboken NJ, publishes detailed, 
transaction-level database that provides information on transaction 
size and the proportion of collateral comprised by multifamily 
collateral for the entire 1990-1999 period. Multifamily loan amounts 
at the transaction level are derived by applying the multifamily 
proportion to the transaction amount. These transaction-level loan 
amounts are then aggregated over all transactions conducted during a 
calendar year to derive an annual total. This data series identifies 
securitizations by depositories, government and insurance companies; 
seasoned loans; GSE transactions; and transactions involving foreign 
collateral, all of which are in order to avoid double-counting. 
Thus, loans included in this component consist of nongovernment, 
non-GSE securitizations of recently-originated mortgages by non-
depository, non-life insurance company institutions.
    (4) Conventional originations by life insurance companies. 
Source: American Council on Life Insurance (ACLI) quarterly data on 
multifamily loan commitments. Annual originations estimated by 
combining commitment in the last quarter of the preceding year and 
the first three quarters of the origination year.
    (5) Conventional originations by private pension funds; state 
and local retirement funds; federal credit agencies; state and local 
credit agencies. Source: SMLA (1990-1997). Data not available for 
1998 and subsequent years.
    This methodology is intended to generate a lower-bound estimate 
for the annual size of the conventional multifamily mortgage 
origination market. A more accurate and realistic estimate could be 
derived if corrections for the following could be generated:
    (1) HMDA under-reporting. To the extent that lenders do not 
report to HMDA, this data source leads to downward bias in 
origination

[[Page 65193]]

volume attributable to the depository sector. While the true extent 
of under-reporting is unknown, a correction factor of 1.25 could be 
employed.
    (2) State and local credit agencies, state and local retirement 
funds, noninsured pension funds are not counted following 1997 
because of the discontinuation of SMLA.
    (3) REITs, individuals. FRB data show significant growth in 
multifamily mortgage debt held by ``individuals and others'' 
including mortgage companies, real estate investment trusts, state 
and local credit agencies, state and local retirement funds, 
noninsured pension funds, credit unions, and finance companies. 
Estimates derived using the above procedure do not include any data 
on originations by individuals. Some REIT activity is included to 
the extent that REITs purchase CMBS included in the CMBS database. 
However, circumstances where REITs originate and hold mortgage loans 
without securitizing them would not be included.
    (4) Pipeline effects. Conduit loans originated during the 
current year but which remain in securitization pipelines as of the 
end of the year are not counted. However, this is mitigated by 
inclusion of CMBS transactions conducted during the calendar year, 
which may include a small number of loans originated late in the 
prior year.
    Table D.5 illustrates annual estimated conventional multifamily 
origination flow utilizing this methodology. A shortcoming of the 
methodology is that it shows a sharp, $10 billion increase in 
origination volume from 1995-1996 which does not appear on any of 
the other data sources discussed above. This discontinuity may, in 
part, reflect improved data quality during the latter part of the 
decade as increased CMBS transactions volume has promoted greater 
market transparency and more complete and accurate public reporting 
with regard to this market segment. It may therefore be concluded 
that this methodology appears to provide more reliable estimates for 
the latter part of the decade, from 1996 forward, than with regard 
to 1995 and earlier years.
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e. Fannie Mae

    Fannie Mae has developed a number of estimates of the size of 
the conventional multifamily mortgage market that it has shared with 
the Department. In discussions with HUD staff in connection with the 
Department's 1995 GSE final rule, Fannie Mae estimated the size of 
the market in 1994 at $32.2 billion, and in 1995 at $33.7 billion.
    In discussions with HUD staff in connection with the 2000 
proposed rule, Fannie Mae provided estimates for 1997-1999 based on 
a combination of data sources including SMLA, HMDA, ACLI, Commercial 
Mortgage Alert, and the Office of Thrift Supervision. Fannie Mae's 
estimates are summarized in Table D.6.

[[Page 65195]]

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f. Freddie Mac

    In its comments submitted in response to HUD's proposed rule, 
Freddie Mac provided estimates of the size of the conventional 
multifamily market for 1995-1997. Some of these estimates are 
derived from HMDA, incorporating a 25 percent expansion factor to 
adjust for underreporting, plus estimated originations by life 
insurance companies, pension funds, and government credit agencies. 
Other estimates are derived by combining HMDA with SMLA. Freddie Mac 
derives an alternative estimate for 1995 using the public-use 
version of the Property Owners and Managers Survey (POMS). In 
discussions with HUD staff in connection with the 2000 proposed 
rule, Freddie Mac staff provided an estimate of the 1998 
conventional multifamily market of $40-$50 billion. Freddie Mac's 
estimates are summarized in Table D.7.
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BILLING CODE 4210-27-C

g. Other Estimates

    1990 Residential Finance Survey (RFS). The 1990 Residential 
Finance Survey (RFS) can be utilized to derive an estimate of the 
size of the conventional multifamily market in 1990. Because loans 
originated during 1989-1991 are grouped together during in the 
public use version of the RFS, a combined figure for loans 
originated over this time period must be divided by 2\1/3\ to derive 
estimated 1990 conventional origination volume of $37.4 billion.
    HUD Property Owners and Managers Survey (POMS). HUD's analysis 
of data in the HUD Property Owners and Managers Survey (POMS) yields 
an estimated size of the 1995 multifamily origination market of 
approximately $37 billion. Analysis of this survey data is 
complicated by virtue of the

[[Page 65196]]

fact that data on mortgage loan amount are missing for a large 
number of properties, requiring the imputation of missing values, 
and also because the mortgage loan amount is ``topcoded'' on some 
observations in order to protect the privacy of respondents. Such 
topcoding complicates the use of multiple regression techniques for 
imputation of missing values. In order to more effectively utilize 
regression techniques, HUD staff and contractors were sworn in as 
special employees of the Census Bureau in order to gain access to 
the internal Census file. The regression specification with the 
greatest explanatory power imputed missing loan amounts on the basis 
of number of units, region of the country, and a dummy variable for 
large properties with more than 1,000 units. The use of this 
specification yielded an estimated total multifamily market size of 
$39.1 billion. After subtracting $2.3 billion in FHA-insured 
originations, this yields $36.7 billion as the estimated size of the 
conforming multifamily mortgage market in 1995. Details are provided 
in Table D.8.
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[[Page 65197]]



2. Loan Amount per Unit

    Another issue regarding the multifamily mortgage market concerns 
average loan amount per unit. This ratio is used in converting 
estimates of conventional multifamily lending volume as measured in 
dollars into a number of units financed. For this purpose, the ratio 
of total UPB to total units financed, rather than UPB on a 
``typical'' multifamily unit, is the appropriate measure, since the 
objective of this exercise is to convert total UPB to total units 
financed.
    For the purposes of estimating the number of units financed in 
the conventional multifamily market during 1993-1998, publicly 
available GSE loan-level data appear to generate reasonable loan 
amount per unit figures. The public use version of the GSE data do 
not provide a means for excluding seasoned loans, which limits the 
usefulness of the data for the purpose of analyzing current-year 
originations, but this does not appear to be a major shortcoming for 
the purposes of this analysis.
    The GSE loan-level data are not available for 1990-1992. For 
this time period, therefore, multifamily loan amount per unit must 
be estimated utilizing an alternative technique. The method utilized 
here is to calculate the ratio of the average conventional 
conforming single-family mortgage to the average per-unit 
multifamily mortgage loan amount over 1993-1998. 26 The 
resulting figure (3.57) is then applied to average single-family 
loan amounts over 1990-1992 to derive estimated multifamily per-unit 
loan amounts for this earlier time period. The resulting annual 
multifamily per-unit loan amount series for 1990-1998 is applied in 
the following section of this discussion to the estimated dollar 
volume of conventional multifamily originations to derive an 
estimate of annual origination volume measured in dwelling units.
    While HUD's market share analysis for purposes of this final 
rule does not rely on assumptions regarding per-unit loan amounts on 
a going-forward basis, further discussion of the issue is warranted 
in light of comments by Freddie Mac in response to the analysis 
supporting HUD's proposed rule. Freddie Mac forecasts that per-unit 
loan amounts will rise to $37,500 to $40,000 over 2000-2003. This 
forecast is based in part upon a sudden increase in GSE per-unit 
loan amounts from approximately $31,000 in 1998 to more than $35,000 
in 1999. In reality, however, this increase is almost entirely 
attributable to Freddie Mac, which experienced an increase in per-
unit loan amount of more than $10,000 over 1998-1999, in contrast to 
Fannie Mae, which experienced an increase of only about $200 over 
this time period. (See Table D.9 for details.)

[[Page 65198]]

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BILLING CODE 4210-27-C

[[Page 65199]]

    Additional information regarding multifamily loan amount per 
unit can be derived from loan-level data on multifamily mortgages 
contained in prospectus disclosures. This data source yields an 
average per-unit loan amount of approximately $31,000 in both 1998 
and 1999, based on $12.5 billion in 1998 non-GSE multifamily 
transactions and $9.2 billion the following year. Thus, the large 
increase in loan-amount per unit in the GSE data for 1999 does not 
appear to be representative of larger trends in the multifamily 
market. Rather, it appears to reflect changes in Freddie Mac's 
business practices which may or may not be evident in future 
years.27

3. Conventional Multifamily Origination Volume, 1990-1999

    Taken by itself, none of the data sources appears to 
definitively answer the question of the size of the market each year 
for the entire time period, but taken together, the various data 
sources can be compared and analyzed in relation to each other in 
order to determine a likely range of estimates. Table D.10 brings 
together the various estimates discussed here, and presents the 
results of calculations of the multifamily share of the conventional 
conforming mortgage market derived using per-unit loan amounts 
discussed above.28 As discussed below in Section E, the 
multifamily share of units financed in the conventional conforming 
market (or ``multifamily mix'') is a key determinant of the share of 
units meeting each of the HUD housing goals.
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[[Page 65200]]

[GRAPHIC] [TIFF OMITTED] TR31OC00.048

    In the 1991-1994 period, the SMLA can be utilized to derive 
annual estimates of multifamily origination volume after removing 
originations by mortgage banks in order to eliminate double-counting 
of lending in the commercial bank and mortgage bank surveys included 
in SMLA. The plausibility of the revised SMLA estimates during this 
time period is enhanced by their proximity to other, independently 
derived figures. For example, the 1992 revised SMLA estimate of 
$23.5 billion is relatively close to the Urban Institute (UI) 
estimate of $28.7 billion during the period of time when the UI 
projection model is presumably most reliable, since it was based on 
the 1991 RFS, a relatively recent data source during the early 
1990s. The 1994 revised SMLA estimate of $31.7 billion is relatively 
close to the Fannie Mae estimate of $32.2 billion. It is not clear 
that the ``augmented'' HMDA methodology introduced by PWC adequately 
corrects for undercounting. The likely range of estimates for the 
1991-1994 period therefore express a range of uncertainty around the 
revised SMLA figures.
    In 1995, it appears likely that actual origination volume lies 
somewhere between the revised SMLA ($32.4 billion) and POMS ($36.7 
billion) estimates. The Freddie Mac

[[Page 65201]]

POMS figure of $27 billion, based on the public-use version of the 
POMS file, may be affected adversely by topcoding, and for this 
reason the HUD POMS estimate, derived from internal Census data, may 
be considered more reliable. The Fannie Mae estimate of $33.7 
billion lies approximately in the middle of the reasonable range of 
$33-$35 billion for 1995. Freddie Mac's HMDA-based methodology, 
generating an estimate of $21 billion, appears to suffer from 
significant undercounting as discussed above. Overall, the Fannie 
Mae multifamily estimates summarized here appear to reflect more 
careful consideration of the various components of the multifamily 
market, in contrast to the mechanical application of a 25 percent 
correction factor to the HMDA data by Freddie Mac, based on 
estimated single-family underreporting.
    HUD's new methodology can be utilized for the years 1996 and 
later, in part because the accuracy and completeness of CMBS data 
expanded rapidly during this time period. The new methodology 
estimate of $34.5 billion for 1996 is close to the revised SMLA 
estimate of $33.3 billion. Based on these two independent estimates, 
a likely range of $33-37 billion is selected.
    In 1997, the new methodology ($38.2 billion ) and the revised 
SMLA figure ($35.5 billion) diverge slightly, but remain relatively 
close to each other, and to Fannie Mae's estimate of $35-40 billion, 
in comparison with other methodological choices. In light of these 
three, relatively consistent estimates, a likely range of $36-40 
billion is a reasonable choice for 1997.
    HUD's new methodology generates a 1998 estimate of $52.9 
billion, exceeding even Freddie Mac's estimate of $40-50 billion. 
However, because of the careful avoidance of double-counting in 
construction of this methodology, it is difficult to see how 
conventional multifamily volume could be less than $52.9 billion. 
Indeed, because of the discontinuation of the SMLA in 1998, the 
$52.9 billion new methodology estimate does not include originations 
by pension funds or government credit agencies. Therefore, a likely 
range of $52-55 billion appears reasonable.
    Table D.10 concludes with estimates for 1999 origination volume 
as well as projections for 2000. The Federal Reserve Board of 
Governors has published data indicating that net multifamily 
borrowing in 1999 was $42.4 billion.29 Because net 
multifamily borrowing includes only increases in the stock of 
indebtedness, it excludes refinance loans, which are a significant 
component of the multifamily origination market. Hence, the Federal 
Reserve figure can be used as a lower bound for 1999 origination 
volume. Consequently, it would appear reasonable to reject the 
Fannie Mae figure of $37-$41 billion for 1999 as unrealistically 
low. Because it is based on data regarding the multifamily mortgage 
market from 1991, the UI figure of $48.8 billion may not be valid. 
Of the four 1999 estimates reported in Table D.10, the $44.5 billion 
HUD figure appears to be the most reliable. Because this figure 
excludes several important conventional lending categories, such as 
pension and retirement funds and state and federal agencies, it 
would appear to be on the low side of the likely range. Based on 
information on origination volume represented by these omitted 
categories in the years prior to discontinuation of the SMLA, a 
likely range of $45-$48 billion for 1999 may be derived.
    Multifamily Mix During the 1990s. Based on the likely range of 
annual conventional multifamily origination volume, multifamily 
units represent an average of 16-17 percent of units financed each 
year during the 1990s.\30\ HUD's estimated multifamily market shares 
exceed estimates prepared by PWC (averaging 8.7 percent for 1991-
1998) for two reasons.\31\ One is that PWC's adjusted HMDA 
methodology does not adequately correct for underreporting in HMDA, 
resulting in unrealistically low estimates of the size of the 
conventional multifamily origination market. Another reason that 
PWC's estimated multifamily market shares are low is that a number 
of their calculations appear to include FHA and jumbo loans in 
estimating the number of single-family units financed each year. For 
example, in 1998, PWC estimates the size of the single-family 
mortgage market at $1.5 trillion. This is identical to the widely-
used estimate by the Mortgage Bankers Association (MBA) for the 
entire single-family mortgage market that year, including jumbo and 
FHA loans, as discussed previously. HUD's market share calculations, 
in contrast, are based on the multifamily share of conventional 
conforming mortgage loans originated each year.
    The multifamily share of the conforming conventional market (or 
``multifamily mix'') derived from this discussion of multifamily 
origination volume is utilized below as part of HUD's analysis of 
the share of units financed each year meeting each of the housing 
goals. For purposes of that analysis, a multifamily mix of 16.5 
percent is reasonable, since it corresponds most closely to the 
midpoint of the likely range of estimates in Table D.10. However, a 
15 percent market share can be utilized as an alternative market 
share estimate corresponding to a somewhat less favorable 
environment for multifamily lending. While somewhat low from an 
historical standpoint, a 15 percent mix more readily accommodates 
the possibility of a recession or heavy refinance year than would 
baseline assumptions based more strictly on historical data. In 
order to more fully consider the effects of an even more adverse 
market environments, an alternative multifamily mix assumption of 
13.5 is also considered, as well as a number of others.

D. Single-Family Owner and Rental Mortgage Market Shares

1. Available Data

    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 RFS and HMDA are the data sources for estimating the 
relative size of the single-family rental market. The RFS, provides 
mortgage origination estimates for each of the three single-family 
property types but it is quite dated, as it includes mortgages 
originated between 1987 and 1991. HMDA divides newly-originated 
single-family mortgages into two property types:\32\
    (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 mortgages from these data 
sources are provided in Table D.11a. (Table D.11b will be discussed 
below.) 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. According to 1997 (1998) HMDA data, 
investors account for 9.4 (9.0 percent) percent of home purchase 
loans and 7.4 percent (5.5 percent) of refinance loans.\33\ Assuming 
a 35 percent refinance rate per HUD's projection model, the 1997 
(1998) HMDA data are consistent with an investor share of 8.7 (7.8) 
percent. The RFS estimate of 17.3 percent is approximately twice the 
HMDA estimates. In their comments, the GSEs argued that the HMDA-
reported SF investor share of approximately 8 percent should be used 
by HUD. In its 1995 rule as well as in this year's proposed rule, 
HUD's baseline model assumed a 10 percent share for the SF investor 
group; alternative models assuming 8 percent and 12 percent were 
also considered. As discussed below, HUD's baseline projection of 10 
percent is probably quite conservative; however, given the 
uncertainty around the data, it is difficult to draw firm 
conclusions about the size of the single-family investor market, 
which necessitates the sensitivity analysis that HUD conducts.

2. Analysis of Investor Market Share

Blackley and Follain

    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. 34 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.

[[Page 65202]]

    Blackley and Follain also noted that the fact that investor 
loans prepay at a faster rate than other single-family loans 
suggests that the investor share of single-family mortgage 
originations should be higher not lower than the investor share of 
the single-family housing stock. In comments, Freddie Mac questions 
this part of Follain and Blackely's analysis.
    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 
17.3 percent to about 14-15 percent.
    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. 
35 In their 1996 paper, they conclude that 12 percent is 
a reasonable estimate of the investor share of single-family 
mortgage originations. 36 Blackley and Follain caution 
that uncertainty exists around this estimate because of inadequate 
data.

3. 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. Thus, it is necessary to compare unit-based distributions 
of the single-family mortgage market under the alternative estimates 
discussed so far. The mortgage-based distributions given in Table 
D.11a were adjusted in two ways. First, the owner-occupied HMDA data 
were disaggregated between SF-O and SF 2-4 mortgages by assuming 
that SF 2-4 mortgages account for 2.0 percent of all single-family 
mortgages; according to RFS data, SF 2-4 mortgages represent 2.3 
percent of all single-family mortgages so the 2.0 percent assumption 
may be slightly conservative. Second, the resulting mortgage-based 
distributions were shifted to unit-based distributions by applying 
the following unit-per-mortgage assumptions: 2.25 units per SF 2-4 
property and 1.35 units per SF investor property. Both figures were 
derived from the 1991 RFS.37
    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 (discussed earlier and reported in Table D.11a). The 
results are presented in Table D.11b. Three points should be made 
about these data. First, notice that the ``SF-Rental'' row 
highlights the share of the single-family mortgage market accounted 
for by all rental units.
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[[Page 65203]]

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BILLING CODE 4210-27-C
    Second, notice that the rental categories represent a larger 
share of the unit-based market than they did of the mortgage-based 
market reported earlier. This, of course, follows directly from 
applying the loan-per-unit expansion factors.
    Third, notice that the rental share under HMDA's unit-based 
distribution is again about one-half of the rental share under the 
RFS's distribution. The rental share in HUD's 1995 rule and this 
year's proposed rule is slightly larger than that reported by HMDA. 
The rental share in the ``Blackley-Follain'' alternative is slightly 
above that in HUD's 1995 rule. Rental units account for 15.1 percent 
of all newly financed single-family units under HUD's baseline 
model, compared with 13.5 (12.4) percent under a model based on 1997 
(1998) HMDA data.

4. Conclusions

    This section has reviewed data and analyses related to 
determining the rental share of the single-family mortgage market. 
There are two main conclusions:
    (1) While there is uncertainty concerning the relative size of 
this market, the projections made by HUD in 1995 appear reasonable 
and, therefore, will serve as the baseline assumption in the HUD's 
market share model for this year's final rule.
    (2) HMDA likely underestimates the single-family rental mortgage 
market. Thus, this part of the HMDA data are not considered reliable 
enough to use in computing the market shares for the housing goals. 
Various sensitivity analyses of the market shares for single-family 
rental properties are conducted in Sections F, G, and H. These 
sensitivity analyses will include the GSEs' recommended model that 
assumes investors

[[Page 65204]]

account for 8 percent of all single-family mortgages. These 
sensitivity analyses will show the effects on the overall market 
estimates of the different projections about the size of the single-
family rental market.
    The upcoming RFS based on the year 2000 Census will help clarify 
issues related to the investor share of the single-family mortgage 
market. At that time, HUD will reconsider its estimates of the 
investor share of the mortgage market.

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.\38\ 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.

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$=CONF%*CONV%*SFORIG$
 Where

CONV%=conforming mortgage originations (measured in dollars) as a 
percent of conventional single-family originations; estimated to be 
87%.\39\
    CONF%=conventional mortgage originations as a percent of total 
mortgage originations; forecasted to 78% by industry and GSEs.\40\
    SFORIG$=dollar volume of single-family one-to-four unit 
mortgages; $950 billion is used here as a starting assumption to 
reflect market conditions during the years 2001-2003.\41\ 
Alternative assumptions will be examined later.\42\

Substituting these values into (1) yields an estimate for the 
conventional conforming market (CCSFM$) of $645 billion.

    Second, the number of conventional conforming single-family 
mortgages (CCSFM#) is derived as follows:

(2) CCSFM#=CCSFM$/SFLOAN$

Where SFLOAN$=the average conventional conforming mortgage amount 
for single-family properties; estimated to be $110,000.\43\ 
Substituting this value into (2) yields an estimate of 5.9 million 
mortgages.

    Third, the total number of single-family mortgages is divided 
among the three single-family property types. Using the 88/2/10 
percentage distribution for single-family mortgages (see Section D), 
the following results are obtained:

(3a) SF-OM#=.88*CCSFM#
    =number of owner-occupied, one-unit mortgages
    =5.2 million.
(3b) SF-2-4M#=.02*CCSFM#
    =number of owner-occupied, two-to-four unit mortgages
    =.1 million.
(3c) SF-INVM# =.10*CCSFM#
    =number of one-to-four unit investor mortgages
    =.6 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
    =5.3 million.
(4b) SF 2-4=1.25*SF-2-4M#
    =number of rental units in 2-4 properties where a owner occupies 
one of the units
    =.1 million.\44\
(4c) SF-INVESTOR=1.35*SF-INVM#
    =number of single-family investor dwelling units financed
    =.8 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
= 6.2 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. Section C concludes that 15.0 percent and 
16.5 percent are reasonable projections for the year 2001-03. The 
baseline model assumes the more conservative of these two 
multifamily mixes--15 percent.

    Assuming a multifamily mix of 15 percent and solving (5b) yields 
the following:
(5c) MF-UNITS = [0.15/0.85] * SF-UNITS
    = 0.176 * SF-UNITS
    = 1.1 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 = 7,308,558
(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.\45\
    The projections used above in equations (1)-(6) produce the 
following distributions of financed units by property type:

----------------------------------------------------------------------------------------------------------------
                                                   % Share                                            % Share
----------------------------------------------------------------------------------------------------------------
SF-O.........................................            72.2   ................................  ..............
SF 2-4.......................................             2.0   SF-O............................         46 72.2
SFINVESTOR...................................            10.8   SF-RENTER.......................            12.8
MF-UNITs.....................................            15.0   MF-UNITS........................            15.0
    Total....................................           100.0    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 focus on three multifamily mixes (13.5 
percent, 15.0 percent, and 16.5 percent) but there will also be 
sensitivity analysis of other multifamily mix assumptions. Under a 
16.5 percent multifamily mix'the average mix during the 1990s--the 
newly-mortgaged unit distribution would be 70.9 percent for Single-
Family Owner, 12.6 percent for Single-Family Renter, and 16.5 
percent for Multifamily-Units. This distribution is similar to the 
baseline distribution in HUD's 1995 final rule and in this year's 
proposed rule. The analysis in sections F-H will focus on goals-
qualifying market shares for this property distribution as well as 
the one presented above for the more conservative multifamily mix of 
15 percent.

[[Page 65205]]

    The appendix will assume the following for the investor share of 
single-family mortgages--8 percent, 10 percent, and 12 percent. The 
middle value (10 percent investor share) is used in the above 
calculations and will be considered the ``baseline'' projection 
throughout the appendix. However, HUD recognizes the uncertainty of 
projecting origination volume in markets such as single-family 
investor properties; therefore, the analysis in Sections G-H will 
also consider market assumptions other than the baseline 
assumptions.
    Table D.12 reports the unit-based distributions produced by 
HUD's market share model for different combinations of these 
projections. The effects of the different projections can best be 
seen by examining the owner category which varies by 6.6 percentage 
points, from a low of 68.9 percent (multifamily mix of 16.5 percent 
coupled with an investor mortgage share of 12 percent) to a high of 
75.5 percent (multifamily mix of 13.5 percent coupled with an 
investor mortgage share of 8 percent). The owner share under the 
baseline projections (15 percent mix and 10 percent investor) is 
72.2 percent, which is slightly higher than the owner share (71.0 
percent) in the baseline projection of HUD's 1995 rule and this 
year's proposed rule.
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BILLING CODE 4210-27-C
    Comparison with the RFS. The Residential Finance Survey is the 
only mortgage data source that provides unit-based property 
distributions directly comparable to those reported in Table D.12. 
Based on RFS data for 1987 to 1991, HUD estimated that, of total 
dwelling units in properties financed by recently acquired 
conventional conforming mortgages, 56.5 percent were owner-occupied 
units, 17.9 percent were single-family rental units, and 25.6 
percent were

[[Page 65206]]

multifamily rental units.\47\ Thus, the RFS presents a much lower 
owner share than does HUD's model. This difference is due mainly to 
the relatively high level of multifamily originations (relative to 
single-family originations) during the mid-to late-1980s, which is 
the period covered by the RFS.\48\ As noted earlier, the RFS based 
on the year 2000 census should clarify issues related to the rental 
segment of the mortgage market.

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.12. This section essentially 
accomplishes Steps 2 and 3 of the three-step procedure discussed in 
Section A.2.b.
    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 
50-55 percent is a reasonable estimate of the mortgage market's low- 
and moderate-income share for the years (2001-2003) when the new 
goals will be in effect.
    This rule establishes that the Low- and Moderate-Income Goal at 
50 percent of eligible units financed in each of calendar years 
2001-2003.
    HMDA data for 1999 was not released until August 2000, thus it 
was not available at the time this rule was prepared.

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.\49\ Table D.13 gives the percentage of mortgages 
originated for low- and moderate-income families for the years 1992-
1998. Data for home purchase and refinance loans are presented 
separately; the discussion will focus on home purchase loans because 
they typically account for the majority of all single-family owner 
mortgages. For each year, a low- and moderate-income percentage is 
also reported for the conforming market without loans originated by 
lenders that primarily originate manufactured home loans (discussed 
below) in metropolitan areas.
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    Table D.13 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.
    Two trends in the income data should be mentioned--one related 
to the market's funding of low- and moderate-income families since 
the 1995 rule was written and the other related to the different 
borrower income distributions for refinance and home purchase 
mortgages.
    Low-Mod Market Share Since 1995. As discussed in the 1995 rule, 
the percentage of borrowers with less than area median income

[[Page 65207]]

increased significantly between 1992 and 1994. Mortgages to low-mod 
borrowers increased from 34.4 percent of the home purchase market in 
1992 to 41.8 percent of that market in 1994. Over the next four 
years (1995-98), the low-mod share of the home purchase market 
remained at a high level, averaging about 42 percent, or almost 40 
percent if manufactured loans are excluded from the market totals. 
The share of the market accounted for by very-low-income borrowers 
followed a similar trend, increasing from 8.7 percent in 1992 to 
11.9 percent in 1994 and then remaining at a high level through 
1998. As discussed in Appendix A, this jump in low-income lending 
has been attributed to several factors, including a favorable 
economy accompanied by historically low interest rates; the entry 
into the housing market of more diverse groups including non-
traditional households (e.g., singles), immigrants, and minority 
families seeking homeownership for the first time; and affordable 
lending initiatives and outreach efforts on the part of the mortgage 
industry. Essentially, the affordable lending market is much 
stronger than it appeared to be when HUD wrote the 1995 rule. At 
that time, there had been two years (1993 and 1994) of increasing 
affordable lending for lower-income borrowers. The four additional 
years of data for 1995-98 show more clearly the underlying strength 
of this market.
    It is recognized that lending patterns could change with sharp 
changes in the economy. However, the fact that there have been six 
years (1993-98) of strong affordable lending suggests the market may 
have 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 
non-traditional borrowers, minorities, and immigrants 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.
    Refinance Mortgages. HUD's model for determining the size of the 
low- and moderate-income market assumes that low-mod borrowers will 
represent a smaller share of refinance mortgages than they do of 
home purchase mortgages. However, as shown in Table D.4, 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. In 1998, another period of high refinance activity, low- 
and moderate-income borrowers accounted for 39.7 percent of 
refinance loans, versus 43.0 percent of home purchase loans. But 
during the years (1995-97) characterized by lower levels of 
refinancing activity, the low-mod share for refinance mortgages was 
about the same as that for home purchase mortgages. In 1997, the 
low-mod share of refinance mortgages (45.0) was even higher than the 
low-mod share of home loans (42.5 percent).
    The projection model assumes that refinancing will be 35 percent 
of the single-family mortgage market. However given the volatility 
of refinance rates from year to year, it is important to conduct 
sensitivity tests using different refinance rates.

b. Manufactured Housing Loans

    The mortgage market definition in this appendix includes 
manufactured housing loans,\50\ which have become an important 
source of affordable housing and which the GSEs have started to 
purchase. Because the market estimates in HUD's 1995 rule were 
adjusted to exclude manufactured housing loans, several tables in 
this appendix will show how the goals-qualifying shares of the 
single-family-owner market change depending on the treatment of 
manufactured housing loans. As explained later, the effect of 
manufactured housing on HUD's metropolitan area market estimate for 
each of the three housing goals is a modest one percentage point
    As discussed in Appendix A, the manufactured housing market has 
been increasing rapidly over the past few years, as sales volume has 
increased from $4.7 billion in 1991 to $15.3 billion in 1999. The 
affordability of manufactured homes for lower-income families is 
demonstrated by their average price of $44,000 in 1999, a fraction 
of the $196,000 for new homes and $168,000 for existing 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.
    Data on the incomes of purchasers of manufactured homes is not 
readily available, but HMDA data on home loans made by 22 lenders 
that primarily originate manufactured home loans, discussed below, 
indicate that: \51\
     A very high percentage of these loans--76 percent in 
1998--would qualify for the Low- and Moderate-Income Goal,
     A substantial percentage of these loans--42 percent in 
1998--would qualify for the Special Affordable Goal, and
     Almost half of these loans--47 percent in 1998--would 
qualify for the Underserved Areas Goal.
    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.
    To date the GSEs have played a minimal role in the manufactured 
home loan market, but both enterprises have expressed an interest in 
expanding their roles.52 Except in structured 
transactions, the GSEs do not purchase manufactured housing loans 
under their seller/servicer guidelines unless they are real estate 
loans. That is, such homes must have a permanent foundation and the 
site must be either purchased as part of the transaction or already 
owned by the borrower. Industry trends toward more homes on private 
lots and on concrete foundations suggest that the percentage of 
manufactured homes that would qualify as real estate loans under GSE 
guidelines has grown in the past few years. There has also been a 
major shift from single-section homes to multisection homes, which 
contain two or three units which are joined together on site.
    Although manufactured home loans cannot be identified in the 
HMDA data, HUD staff have identified 22 lenders that primarily 
originate manufactured home loans and likely account for most of 
these loans in the HMDA data for metropolitan areas. In Table D.13, 
the data presented under ``Conforming Market Without Manufactured 
Home Loans'' excludes loans originated by manufactured housing 
lenders, as well as loans less than $15,000. The lenders include 
companies such as Green Tree Financial; Vanderbilt Mortgage; 
Deutsche Financial Capital; Oakwood Acceptance Corporation; Allied 
Acceptance Corporation; Belgravia Financial Services; Ford Consumer 
Finance Company; and the CIT Group.53

c. American Housing Survey Data

    The American Housing Survey also reports borrower income data 
similar to that reported in Table D.3. The low- and moderate-income 
market shares from the AHS are as follows:
    1985  27.0%
    1987  32.0%
    1989  34.0%
    1991  36.0%
    1993  33.0% (38.7% home purchase and 28.6% refinance)
    1995  40.0% (38.5% home purchase and 43.2% refinance)
    According to the AHS, 38.5 percent of those families surveyed 
during 1995 who had recently purchased their homes, and who obtained 
conventional mortgages below the conforming loan limit, had incomes 
below the area median; this compares with 39.3 percent based on 1995 
HMDA data that excludes manufactured homes (as the AHS data do).
    A longer-term perspective of the mortgage market can be gained 
by examining income data from the last six American Housing Surveys. 
During the earlier period between 1987 and 1991, the low- and 
moderate-income share increased from 27 percent to 36 percent, and 
averaged 32.3 percent. After remaining at a relatively low 
percentage (33.0 percent) during the heavy refinance year of 1993, 
the low- and moderate-income share rebounded to 40.0 percent in 
1995. As noted earlier, this is about the same market share reported 
by HMDA data for 1995.
    The GSEs have raised issues concerning underreporting of income 
in the AHS.54 Since HMDA data cover over 80 percent of 
the single-family-owner mortgage market, and the American Housing 
Survey represents only a very small sample of this market, the HMDA 
data will be the source of information on the characteristics of 
single-family property owners receiving mortgage financing. As 
discussed next, the American Housing Survey and the Property Owners 
and Managers Survey will be relied on for information about the 
rents and affordability

[[Page 65208]]

of single-family and multifamily rental properties.

2. Low- and Moderate-Income Percentage for Renter Mortgages

    The 1995 rule relied on the American Housing Survey for a 
measure of the rent affordability of the single-family rental stock 
and the multifamily rental stock. As explained below, the AHS 
provides rent information for the stock of rental properties rather 
than for the flow of mortgages financing that stock. This section 
discusses a new survey, the Property Owners and Managers Survey 
(POMS), that provides information on the flow of mortgages financing 
rental properties. 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 presents AHS data on 
the affordability of the rental housing stock for the survey years 
between 1985 and 1997. The 1997 AHS shows 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 1989, 1991, 1993, and 1995 are similar to 
the 1997 data.
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[[Page 65210]]

b. Property Owners and Managers Survey (POMS)

    During the 1995 rule-making, concern was expressed about using 
data on rents from the outstanding rental stock to proxy rents for 
newly mortgaged rental units.55 At that time, HUD 
conducted an analysis of this issue using the Residential Finance 
Survey and concluded that the existing stock was an adequate proxy 
for the mortgage flow when rent affordability is defined in terms of 
less than 30 percent of area median income, which is the 
affordability definition for the Low- and Moderate-Income Goal. More 
specifically, that analysis suggested that 85 percent of single-
family rental units and 90 percent of multifamily units are 
reasonable estimates for projecting the percentage of financed units 
affordable at the low- and moderate-income level.56 HUD 
has investigated this 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 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 reported in Table D.5 on the 
affordability of the rental stock. Ninety-six (96) percent of 
single-family rental properties with new mortgages between 1993 and 
1995 were affordable to low- and moderate-income families, and 56 
percent were affordable to very-low-income families. The 
corresponding percentages for newly-mortgaged multifamily properties 
are 96 percent and 51 percent, respectively. Thus, these percentages 
for newly-mortgaged properties from the POMS are similar to those 
from the AHS for the rental stock. As discussed in the next section, 
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.

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 provides some 
necessary background by comparing HUD's estimate made during the 
1995 rule-making process with actual experience between 1995 and 
1998. Subsection 3.b presents new estimates of the low-mod market 
while Subsection 3.c reports the sensitivity of the new estimates to 
changes in assumptions about economic and mortgage market 
conditions.

a. Comparison of Market Estimates With Actual Performance

    The market share estimates that HUD made during 1995 can now be 
compared with actual market shares for 1995 to 1998. This discussion 
of the accuracy of HUD's past market estimates considers all three 
housing goals, since the explanations for the differences between 
the estimated and actual market shares are common across the three 
goals. HUD estimated the market for each housing goal for 1995-98, 
and obtained the results reported in Table D.15.57 B&C 
loans are not included in the market estimates reported in Table 
D.15. The discussion of Table D.15 will proceed as follows. It will 
first focus on the market estimates for 1995 to 1997 which are the 
most useful comparisons with HUD's market estimates from the 1995 
rule. The discussion will then examine the market estimates for the 
heavy refinance year of 1998. After that, HUD's method for adjusting 
the 1995-98 market data to exclude B&C loans as well as the non-
metropolitan area adjusted market for the Underserved Areas Goal 
will be explained. (See Table D.15)
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[[Page 65211]]

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    HUD's market estimates in 1995 were 48-52 percent for the Low- 
and Moderate-Income Goal, 20-23 percent for the Special Affordable 
Goal, and 25-28 percent for the Underserved Areas Goal. Thus, even 
the upper bound figures for the market share ranges in the 1995 rule 
proved to be low for the 1995-97 period--for the low-mod estimate, 
52 percent versus 57-58 percent; for the special affordable 
estimate, 23 versus 28-29 percent, and for the underserved areas 
estimate, 28 percent versus 33-34 percent.
    There are several factors explaining HUD's underestimate of the 
goals-qualifying market shares. The 1995-97 mortgage markets 
originated more affordable single-family mortgages than anticipated, 
mainly due to historically low interest rates and strong economic 
expansion. In 1997, for instance, almost 44 percent of all (home 
purchase and refinance) single-family-owner mortgages qualified for 
the Low- and Moderate-Income Goal, 16 percent qualified for the 
Special Affordable Goal, and 28 percent qualified for the 
Underserved Areas Goal.\58\ HUD's 1995 estimates anticipated smaller 
shares of new mortgages being originated for low-income families and 
in their neighborhoods.59 60

[[Page 65212]]

    The financing of multifamily properties during 1995-97 was 
larger than anticipated. HUD's earlier estimates assumed a 
multifamily share of 16 percent, which was lower than the 
approximately 19 percent multifamily share for the years 1995-97. 
The underestimate for the multifamily share was due both to a larger 
multifamily dollar volume ($34 billion for 1995, $37 billion for 
1996, and $38 billion for 1997) than anticipated in the 1995 GSE 
rule ($30 billion) and to lower per unit multifamily loan amounts 
than assumed in HUD's earlier model.\61\
    B&C Mortgages. As discussed in Appendix A, the market for 
subprime mortgages has experienced rapid growth over the past 2-3 
years. Table D.15 provides goals-qualifying market shares that 
exclude the B&C portion of the subprime market. This section 
explains how these ``adjusted'' market shares are calculated from 
``unadjusted'' market shares that include B&C loans, using the year 
1997 as an example. Comprehensive data for measuring the size of the 
subprime market are not available. However, estimates by various 
industry observers suggest that the subprime market could have 
accounted for as much as 15 percent of all mortgages originated 
during 1997, which would have amounted to approximately $125 
billion.\62\ In terms of credit risk, this $125 billion includes a 
wide range of mortgage types. ``A-minus'' loans, which represented 
at least half of the subprime market in 1997, make up the least 
risky category. 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). The B&C loans experience much higher delinquency rates than 
A-minus loans.\63\
    The procedure for excluding B&C mortgages from estimated 
``unadjusted'' market shares for goals-qualifying loans in 1997 
combined information from several sources. First, the $125 billion 
estimate for the subprime market was reduced by 20 percent to arrive 
at an estimate of $100 billion for subprime loans that were less 
than the conforming loan limit of $214,600 in 1997. This figure was 
reduced by one-half to arrive at an estimate of $50 billion for the 
conforming B&C market; with an average loan amount of $68,289 
(obtained from HMDA data, as discussed below), the $50 billion 
represented approximately 732,182 B&C loans originated during 1997 
under the conforming loan limit.
    HMDA data was used to provide an estimate of the portion of 
these 732,182 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 200 HMDA reporters that primarily originate 
subprime loans. The goals-qualifying percentages of the loans 
originated by these subprime lenders in 1997 were as follows: 57.3 
percent qualified for the Low- and Moderate-Income Goal, 28.1 
percent for the Special Affordable Goal, and 44.7 percent for the 
Underserved Areas Goal.\64\ Applying the goals-qualifying 
percentages to the estimated B&C market total of 732,182 gives the 
following estimates of B&C loans that qualified for each of the 
housing goals in 1997: Low- and Moderate Income (419,540), Special 
Affordable (205,743), and Underserved Areas (327,286).
    Adjusting HUD's model to exclude the B&C market involves 
subtracting the above four figures' one for the overall B&C market 
and three for B&C loans 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 loans. HUD's 
model estimates that 8,039,132 single-family and multifamily units 
were financed during 1997; of these, 4,620,828 (57.5 percent) 
qualified for the Low- and Moderate-Income Goal, 2,311,251 (28.8 
percent) for the Special Affordable Goal, and 2,694,351 (33.5 
percent) for the Underserved Areas Goal. Deducting the B&C market 
estimates produces the following adjusted market estimates: a total 
market of 7,306,950, of which 4,201,287 (57.5 percent) qualified for 
the Low- and Moderate-Income Goal, 2,105,508 (28.8 percent) for the 
Special Affordable Goal, and 2,367,066 (32.4 percent) for the 
Underserved Areas Goal.
    As seen, the low-mod market share estimate exclusive of B&C 
loans (57.5 percent) is the same as the original market estimate 
(57.5 percent) and the corresponding special affordable market 
estimate (28.8 percent) is also the same as the original estimate. 
This occurs because the B&C loans that were dropped from the 
analysis had 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 57.3 
percent and HUD's market model projected the overall low-mod share 
to be 57.5 percent. Thus, dropping B&C loans from the market totals 
does not change the overall low-mod share of the market.
    The situation is different for the Underserved Areas Goal. 
Underserved areas account for 44.7 percent of the B&C loans, which 
is a higher percentage than the underserved area share of the 
overall market (33.5 percent). Thus, dropping the B&C loans leads to 
a reduction in the underserved areas market share of 1.1 percentage 
points, from 33.5 percent to 32.4 percent.
    Dropping B&C loans from HUD's model changes the mix between 
rental and owner units in the final market estimate. Based on 
assumptions about the size of the owner and rental markets for 1997, 
HUD's model calculates that single-family-owner units accounted for 
70.2 percent of total units financed during 1997. Dropping the B&C 
owner loans, as described above, reduces the owner percentage of the 
market by three percentage points to 67.2 percent. Thus, another way 
of explaining why the goals-qualifying market shares are not 
affected so much by dropping B&C 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.
    There are caveats that should be mentioned concerning the above 
adjustments for the B&C market for 1997. The adjustment for B&C 
loans depends on several estimates relating to the 1997 mortgage 
market, derived from various sources. Different estimates of the 
size of the B&C market in 1997 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.\65\ Despite these caveats, it also 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 below, 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.
    Adjustment for Non-Metropolitan Areas. The first set of 1995-98 
market shares for underserved areas is based on single-family-owner 
parameters for metropolitan areas. It is necessary to adjust these 
market shares upward by about 1.5 percentage points to reflect the 
fact that underserved counties account for a much larger portion of 
non-metropolitan areas than underserved census tracts do 
metropolitan areas. The method for deriving the 1.5 percentage point 
adjustment is explained in Section G.3 below, which presents the 
projected 2001-03 market estimates for the Underserved Areas Goal.
    1998 Market Estimates. The high volume of single-family 
mortgages in the heavy refinance year of 1998 increased the share of 
single-family-owner units to 73.1 percent, compared with 68-70 
percent for 1995 to 1997. This shift toward single-family loans, 
combined with the higher level of single-family refinance activity 
in 1998, results in market shares that are slightly smaller than 
reported for 1995-97. The following estimates are obtained: low-mod, 
53.8 percent; special affordable, 25.8 percent; and underserved 
areas, 30.9 percent.\66\ While lower, these estimates remain higher 
than the market estimates that HUD made in 1995 (see earlier 
discussion for reasons).

b. Market Estimates

    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 (2001-2003) when the new housing goals will be 
in effect. Three alternative sets of projections about property 
shares and rental property low-and moderate-

[[Page 65213]]

income percentages are given in Table D.16. Case 1 projections 
represent the baseline and intermediate case; it assumes that 
investors account for 10 percent of the single-family mortgage 
market. Case 2 assumes a lower investor share (8 percent) based on 
HMDA data and slightly more conservative low-and moderate-income 
percentages for single-family rental and multifamily properties (85 
percent). Case 3 assumes a higher investor share (12 percent) 
consistent with Follain and Blackley's suggestions.
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BILLING CODE 4210-27-C
    Because single-family-owner units account for about 70 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.\67\ Thus, Table D.17 provides market estimates for 
different low-mod percentages for the owner market as well as for 
different multifamily mix percentages--the 15.0 percent projection 
bracketed by 13.5 percent and 16.5 percent. As discussed in Section 
C of this appendix, 16.5 percent represents the average multifamily 
share between 1991 and 1998, while 15 percent represents a slightly 
more conservative baseline.
    Several low-mod percentages of the owner market are given in 
Table D.17 to account for different perceptions about the low-mod 
share 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 on the goals-qualifying share of the 
overall mortgage 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.
    With respect to excluding B&C loans from the market estimates, 
Table D.17 can be interpreted in two ways. First, readers could 
choose a home purchase low-mod percentage (that is, one of the 
percentages in the first column) that they believe is adjusted for 
B&C loans and then obtain a rough estimate of the overall low-mod 
estimate from the second to fourth columns corresponding to 
different

[[Page 65215]]

multifamily mixes. For instance, if one believes the appropriate 
home purchase percentage adjusted for B&C loans (or adjusted for any 
other exclusions that the reader thinks are appropriate) is 39 
percent, then the low-mod market estimate is 52.4 percent assuming a 
multifamily mix of 15 percent. Second, readers could choose a home 
purchase percentage directly from HMDA data that is unadjusted for 
B&C loans and then rely on HUD's methodology (described below) for 
excluding B&C loans from the market estimates reported in Table 
D.17. 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) due to excluding B&C 
owner loans from the analysis. According to HUD's methodology, 
dropping B&C owner loans would reduce the various low-mod market 
estimates reported in Table D.17 by less than half of a 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 share when B&C 
owner loans are dropped from the market totals. For this reason, the 
low-mod market estimates reported in Table D.17 provide a reasonable 
proxy for low-mod market estimates without B&C loans. This issue is 
discussed in more detail below.
    As shown in Table D.17, the market estimate is 53-56 percent if 
the owner percentage is at or above 40 percent (slightly less than 
its 1994-98 levels), and it is 52-53 percent if the owner percentage 
is 39 percent (its 1993 level). If the low- and moderate-income 
percentage for owners fell from its 1997-98 level of 43 percent to 
35 percent, the overall market estimate would be approximately 50 
percent. Thus, 50 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 34 percent--about four-fifths of the 1997-98 
level--and the low- and moderate-income market share would still be 
49 percent.
    The volume of multifamily activity is 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. As discussed in Section 
E.2, the multifamily mix assumption of 15 percent produces an 
overall (both multifamily and single-family) rental mix of 27.8 
percent, which is about a percentage point less than the overall 
rental mix projection in HUD's 1995 rule. Lowering the multifamily 
mix to 13.5 produces the set of overall low-mod market estimates 
that are reported in the first column of Table D.17. Compared with 
15 percent, the 13.5 percent mix assumption reduces the overall low-
mod market estimates by slightly over a half percentage point. For 
example, when the low-mod share of the owner market is 42 percent, 
the low-mod share of the overall market is 54.6 percent assuming a 
15 percent multifamily mix but is 54.0 percent assuming a 13.5 
percent multifamily mix.\68\
    The market estimates for Case 2 and Case 3 bracket those for 
Case 1. The smaller single-family rental market and lower low- and 
moderate-income percentages for rental properties result in the Case 
2 estimates being almost two percentage points below the Case 1 
estimates. Conversely, the higher percentages under Case 3 result in 
estimates of the low-mod market approximately three percentage 
points higher than the baseline estimates.
    The various market estimates presented in Table D.17 are not all 
equally likely. Most of them equal or exceed 51 percent; in the 
baseline model, estimates below 51 percent would require the low-mod 
share of the single-family owner market for home purchase loans to 
drop to approximately 36 percent which would be over six percentage 
points lower than the 1993-98 average for the low-mod share of the 
home purchase market. With a multifamily mix at 13.5 percent, the 
low-mod share of the owner market can fall to 36 percent before the 
average market share falls below 50 percent.
    The upper bound (56 percent) of the low-mod estimates reported 
in Table D.17 for the baseline case is lower than the low-mod share 
of the market between 1995 and 1997. As reported above, HUD 
estimates that the low-mod market share during this period was about 
57 percent. There are two reasons the projected low-mod estimates 
are lower than the 1995-97 experience. First, the projected rental 
share of 28 percent is lower than the rental share of 31 percent for 
the 1995-97 period; a smaller market share for rental units lowers 
the low-mod market share. Second, HUD's projections assume that 
refinancing borrowers will have higher incomes than borrowers 
purchasing a home (explained below). As Table D.14 shows, this was 
the reverse of the situation between 1995 and 1997 when refinancing 
borrowers had higher incomes than borrowers purchasing a home. 
69 This fact, along with the larger single-family mix 
effect, resulted in the low-mod share of the market falling below 
the 1997 level of 57 percent.
    B&C Loans. As discussed above, if one assumes the home purchase 
percentages in the first column of Table D.17 are unadjusted for B&C 
loans, then the overall low-mod market estimates must be adjusted to 
exclude these loans. B&C loans can be deducted from HUD's low-mod 
market estimates using the same procedure described earlier. But 
before doing that, some additional comments about how HUD's 
projection model operates are in order. HUD's projection model 
assumes that the low-mod share of refinance loans will be three 
percentage points lower than the low-mod share of home purchase 
loans, even though there have been years recently (1995-97) when the 
low-mod share of refinance loans has been as high or higher than 
that for home purchase loans (see Table D.14).70 Since 
B&C loans are primarily refinance loans, this assumption of a lower 
low-mod share for refinance loans partially adjusts for the effects 
of B&C loans, based on 1995-97 market conditions. For example, in 
Table D.17, the low-mod home purchase percentage of 43 percent, 
which reflects 1997 conditions, is combined with a low-mod refinance 
percentage of 40 percentage when, in fact, the low-mod refinance 
percentage in 1997 was 45 percent. Thus, by taking the 1992-98 
average low-mod differential between home purchase and refinance 
loans, the projection model deviates from 1995-97 conditions in the 
single-family owner market.71
    The effects of deducting the B&C loans from the projection model 
can be illustrated using the above example of a low-mod home 
purchase percentage of 42 percent and a low-mod refinance percentage 
of 39 percent; as Table D.17 shows, this translates into an overall 
low-mod market share of 54.6 percent. It is assumed that the 
subprime market accounts for 12 percent of all mortgages originated, 
which would be $114 billion based on $827 billion for the 
conventional market. This $114 billion estimate for the subprime 
market is reduced by 20 percent to arrive at $91 billion for 
subprime loans that will be less than the conforming loan limit. 
This figure is reduced by one-half to arrive at approximately $46 
billion for the conforming B&C market; with an average loan amount 
of $82,022; the $46 billion represents 556,000 B&C loans projected 
to be originated under the conforming loan limit.72
    Following the procedure discussed in Section F.3.a, the low-mod 
share of the market exclusive of B&C loans is estimated to be 54.3 
percent, which is only slightly lower than the original estimate 
(54.6 percent).73 As noted earlier, this occurs because 
the B&C loans that were dropped from the analysis had similar low-
mod percentages as the overall (both single family and multifamily) 
market (59.3 percent and 55.7 percent, respectively). The impact of 
dropping B&C loans is larger when the overall market share for low-
mod loans is smaller. As shown in Table D.17, a 38 percent low-mod 
share for single-family owners is associated with an overall low-mod 
share of 51.7 percent. In this case, dropping B&C loans would reduce 
the low-mod market share by 0.5 percentage point to 51.2 percent. 
Still, dropping B&C loans from the market totals does not change the 
overall low-mod share of the market appreciably.
    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 30.1 percent of total units after dropping B&C 
loans compared with 27.8 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.
    Section F.3.a discussed several caveats concerning the analysis 
of B&C loans. It is not clear what types of loans (e.g., first 
versus second mortgages) are included in the B&C market estimates. 
There is only limited data on the borrower characteristics of B&C 
loans and the extent to which these loans are included in HMDA is 
not clear. Still, the analysis of Table D.17 and the above analysis 
of the effects of dropping B&C loans from the market suggest that 
50-55 percent is a reasonable range of estimates for the low- and 
moderate-income market for the years 2001-

[[Page 65216]]

2003. This range covers markets without B&C loans 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.

c. Economic Conditions, Market Estimates, and the Feasibility of the 
Low- and Moderate-Income Housing Goal

    During the 1995 rule-making, there was a 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. As discussed in Section B of this appendix, the GSEs 
expressed similar concerns in their comments on this year's proposed 
rule. This section discusses 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 existed during the 1993 to 1998 period.
    Volatility of Market. The starting point for HUD's estimates of 
market share is the projected $950 billion in single-family 
originations. Shifts in economic activity could obviously affect the 
degree to which this projection is borne out. As noted earlier, the 
Mortgage Bankers Association has recently revised its forecasts of 
mortgage originations numerous times in the face of projected 
changes in market conditions. Changing economic conditions can 
affect the validity of HUD's market estimates as well as the 
feasibility of the GSEs' accomplishing the housing goals.
    One only has to recall the volatile nature of the mortgage 
market in the past few years to appreciate the uncertainty around 
projections of that 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 1998 and early 1999. While 
interest rates have recently risen, they continue to be moderate by 
historical standards. A period of low-to-moderate interest rates 
would sustain affordability levels without causing the rush to 
refinance seen earlier in 1993 and more recently in 1998. A high 
percentage of potential refinancers have already done so, and are 
less likely to do so again.
    HUD conducted numerous sensitivity analyses of the market 
shares. In the projection model, increasing the single-family 
mortgage origination forecast while holding the multifamily 
origination forecast constant is equivalent to reducing the 
multifamily mix. Increasing the single-family projection by $100 
billion, from $950 billion to $1,050 billion, would reduce the 
market share for the Low-and Moderate-Income Goal by approximately 
0.5 percentage point, assuming the other baseline assumptions remain 
unchanged.74 A $200 billion increase would reduce the 
low-mod projected market share by 0.9 percentage point.
    HUD also examined potential changes in the market shares under 
very different macroeconomic environments, one assuming a recession 
and one assuming a period of low interest rates and heavy 
refinancing. The recessionary environment was simulated using Fannie 
Mae's minimum projections of single-family mortgage originations 
($880 billion). The low- and moderate-income share of the home 
purchase market was reduced to 34 percent, or 8.5 percentage points 
lower than its 1997 share.75 Under these rather severe 
conditions, the overall market share for the Low- and Moderate-
Income Goal would decline to 50.4 percent. If the low-mod share of 
the owner market were reduced to 32 percent (for both home purchase 
and refinance loans), the low-mod share for the overall market would 
fall to 49.0 percent.
    The heavy refinance environment was simulated assuming that the 
single-family origination market increased to $1,400 billion, which 
increases the owner share of newly-mortgaged dwelling units from 
72.2 percent under HUD's baseline model to 73.2 percent. Refinances 
were assumed to account for 60 percent of all single-family mortgage 
originations. If low- and moderate-income borrowers accounted for 40 
percent of borrowers purchasing a home but only 36 percent of 
refinancing borrowers, then the market share for the Low- and 
Moderate-Income Goal would be 51.6 percent. If the first two 
percentages were reduced to 39 percent and 32 percent, respectively, 
then the market share for the Low- and Moderate-Income Goal would 
fall to 49.6 percent. However, if the refinance market resembled 
1998 conditions, the low-mod share would be 54 percent, as reported 
earlier.
    Finally, HUD simulated the specific scenario based on the MBA's 
most recent market estimate of $912 billion and a refinance rate of 
22 percent. In this case, assuming a low-mod home purchase 
percentage of 40, the overall low-mod market share was 53.4 percent, 
assuming a multifamily mix of 15 percent; 52.8 percent, assuming a 
multifamily mix of 13.5 percent; and 54.1 percent, assuming a 
multifamily mix of 16.5 percent.
    Feasibility Determination. As stated in the 1995 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.76 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 the 1995 GSE rule, 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 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.
    Affordability Conditions and Market Estimates. The market share 
estimates rely on 1992-1998 HMDA data for the percentage of low- and 
moderate-income borrowers. 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 during the mid- and late-1990s. 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 
discussed above, the 50-55 percent range for the low-mod market 
share covers economic and housing market 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 34 percent, which is over nine percentage 
points lower than its 1998 level of about 43 percent, before the 
baseline market share for the Low- and Moderate-Income Goal would 
fall to 49 percent.

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 50-55 percent is a reasonable range of 
estimates of the mortgage market's low- and moderate-income share 
for each of years 2001-2003. This range covers much more adverse 
market conditions than have existed recently, allows for different 
assumptions about the multifamily market, and excludes the effects 
of B&C loans. HUD recognizes that shifts in economic conditions 
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 or the

[[Page 65217]]

Geographically-Targeted Goal. The first two sections focus on 
underserved census tracts in metropolitan areas. 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.
    This rule establishes that the Central Cities, Rural Areas, and 
other Underserved Areas Goal at 31 percent of eligible units 
financed in each of calendar years 2001-2003.

1. Geographically-Targeted Goal Shares by Property Type

    For purposes of the Geographically-Targeted 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.18 are the 
percentages of single-family-owner mortgages that financed 
properties located in underserved census tracts of metropolitan 
areas between 1992 and 1998. In 1997 and 1998, approximately 25 
percent of home purchase loans financed properties located in these 
areas; this represents an increase from 22 percent in 1992 and 1993. 
In some years, refinance loans are even more likely than home 
purchase loans to finance properties located in underserved census 
tracts. Between 1994 and 1997, 28.5 percent of refinance loans were 
for properties in underserved areas, compared to 25.1 percent of 
home purchase loans.\77\ In the heavy refinance year of 1998, 
underserved areas accounted for about 25 percent of both refinance 
and home purchase loans.
BILLING CODE 4210-27-P

[[Page 65218]]

[GRAPHIC] [TIFF OMITTED] TR31OC00.056

BILLING CODE 4120-27-C
    Since the 1995 rule was written, the single-family-owner market 
in underserved areas has remained strong, similar to the low- and 
moderate-income market discussed in Section F. Over the past five 
years, the underserved area share of the metropolitan mortgage 
market has leveled off at 25-28 percent, considering both home 
purchase and refinance loans. This is higher than the 23 percent 
average for the 1992-94 period, which was the period that HUD was

[[Page 65219]]

considering when writing the 1995 rule. As discussed earlier, 
economic conditions could change and reduce the size of the 
underserved areas market; however, that market appears to have 
shifted to a higher level over the past five years.
    Renter Mortgages. The second and third sets of numbers in Table 
D.18 are the underserved area percentages for single-family rental 
mortgages and multifamily mortgages, respectively. Based on HMDA 
data for single-family, non-owner-occupied (investor) loans, the 
underserved area share of newly-mortgaged single-family rental units 
has been in the 43-45 percent range over the past five years. HMDA 
data also show that about half of newly-mortgaged multifamily rental 
units are located in underserved areas.

2. Market Estimates for Underserved Areas in Metropolitan Areas

    In the 1995 GSE rule, HUD estimated that the market share for 
underserved areas would be between 25 and 28 percent. This estimate 
turned out to be below market experience, as underserved areas 
accounted for approximately 33-34 percent of all mortgages 
originated in metropolitan areas between 1995 and 1997 and for 31 
percent in 1998 (see Table D.15).\78\
    Table D.19 reports HUD's estimates of the market share for 
underserved areas based on the projection model discussed 
earlier.\79\ As indicated in Table D.18, these overall market 
estimates are based mainly on HMDA-reported underserved area shares 
of owner and rental properties in metropolitan areas. As explained 
in Section F.3 below, the estimated combined effect of dropping B&C 
loans and of including non-metropolitan areas is to increase the 
underserved area market shares reported in Table D.19 by 
approximately one-half percentage point.
BILLING CODE 4210-27-P

[[Page 65220]]

[GRAPHIC] [TIFF OMITTED] TR31OC00.057

BILLING CODE 4210-27-C
    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.19 
reports market shares for different single-family-owner percentages 
ranging from 28 percent (1997 HMDA) to 20 percent (1993 HMDA) to 18 
percent. If the single-family-owner percentage for underserved areas 
is at its 1994-98 HMDA average of 26 percent, the market share 
estimate is over 31 percent. The overall market share for 
underserved areas peaks at 33 percent when the single-family-owner 
percentage is at its 1997 figure of 28 percent. Most of the 
estimated market shares for the owner percentages that are slightly 
below recent experience are in the 30 percent range. In the baseline 
case, the single-family-owner percentage can go as low as 23 
percent, which is over 3 percentage points lower than the 1994-98 
HMDA average, and the estimated market share for underserved areas 
remains over 29 percent.
    Unlike the Low- and Moderate-Income Goal, the market estimates 
differ only slightly as one moves from Case 1 to Case 3 and from a 
13.5 percent mix to 16.5 percent mix. For example, reducing the 
assumed multifamily mix to 13.5 percent reduces the overall market 
projection for underserved areas by only about 0.3 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. Additional 
sensitivity analyses were conducted as described in Section F.3c.
    For example, adding $100 ($200) billion to the $950 billion 
single-family originations would reduce the underserved area market

[[Page 65221]]

share by about 0.3 (0.5) percent, assuming there were no other 
changes. The MBA scenario combined with a single-family owner 
underserved area percentage of 25 percent, would produce an overall 
market share for underserved areas of 30.7 percent. The recession 
scenario described in Section F.3.c assumed that the underserved 
area percentage for single-family-owner mortgages was 21 percent or 
almost seven percentage points lower than its 1997 value. In this 
case, the overall market share for underserved areas declines to 
28.4 percent. In the refinance scenarios, the underserved areas 
market share was approximately 31 percent.

3. Adjustments: B&C Loans and the Rural Underserved Area Market

    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 44.7 percent, which is much higher than the projected 
percentage for the overall market (30-33 percent as indicated in 
Table D.19). Thus, dropping B&C loans will reduce the overall market 
estimates. Consider in Table D.19, the case of a single-family-owner 
percentage of 26 percent, which yields an overall market estimate 
for underserved areas of 31.4 percent. Dropping B&C loans from the 
projection model reduces the underserved areas market share by 1.1 
percentage points to 30.3.
    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 the greater of 
statewide or national 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 1997-99, 36-38 percent of the GSE's total purchases in 
non-metropolitan areas were in underserved counties while 25-27 
percent of their purchases in metropolitan areas were in underserved 
census tracts. These figures suggest the market share for 
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. Over the past few years, the 
non-metropolitan portion of the Underserved Areas Goal has 
contributed approximately 1.3 percentage point to the GSEs 
performance, 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 42 
percent of all mortgages originated in non-metropolitan areas during 
1997 and 1998. By contrast, underserved census tracts accounted for 
approximately 25 percent of all mortgages in metropolitan 
area.80 If this 17 point differential reflected actual 
market conditions, then the underserved areas market share estimated 
using metropolitan area data should be increased by 1.9 percentage 
points to account for the effects of underserved counties in non-
metropolitan areas.81 To be conservative, HUD used a 1.5 
percentage adjustment in Table D.15 which reported market estimates 
for the 1995-98 period.
    The combined effects of the above analyses on the underserved 
area market shares presented in Table D.19 can now be considered. 
First, deducting B&C loans from the analysis reduces the market 
estimates presented in Table D.19 by almost one percentage point. 
Second, including non-metropolitan counties in data for estimating 
the underserved areas market share could increase the market share 
estimates up to 2 percentage points. Therefore, the combination of 
these two effects suggests that the market estimates in Table D.19 
should be increased by up to one percentage point, with one-half 
percentage point being a conservative upward adjustment. At a 
minimum, the various estimates presented in Table D.19 are 
conservative estimates of the underserved areas market excluding B&C 
loans but including non-metropolitan counties.82
    The estimates presented in Table D.19 and this section's 
analysis of dropping B&C loans and including non-metropolitan areas 
suggest that 29-32 percent is a conservative range for the market 
estimate for underserved areas based on the projection model 
described earlier. This range incorporates market conditions that 
are more adverse than have existed recently and it excludes B&C 
loans from the market estimates. The estimate is conservative 
because, due to lack of data, it does not fully reflect the size of 
the mortgage market in non-metropolitan underserved counties.

4. Conclusions

    Based on the above findings as well as numerous sensitivity 
analyses, HUD concludes that 29-32 percent is a conservative 
estimate of mortgage market originations that would qualify toward 
achievement of the Geographically Targeted Goal if purchased by a 
GSE. 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).\38\ HUD estimates that the special affordable market is 23-
26 percent of the conventional conforming market.
    HUD has determined that the annual goal for mortgage purchases 
qualifying under the Special Affordable Housing Goal shall be 20 
percent of eligible units financed in each of calendar years 2001-
2003. This final rule further provides that of the total mortgage 
purchases counted toward the Special Affordable Housing Goal, each 
GSE must annually purchase multifamily mortgages in an amount equal 
to at least 1.0 percent of the dollar volume of combined (single-
family and multifamily) mortgage purchases over 1997 through 1999. 
This implies the following thresholds for the two GSEs:

------------------------------------------------------------------------
                                                          (In billions)
------------------------------------------------------------------------
Fannie Mae.............................................            $2.85
Freddie Mac............................................             2.11
------------------------------------------------------------------------

    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 in a particular 
year that are occupied by very-low-income families or by low-income 
families living in low-income areas. HUD has combined mortgage 
information from HMDA, the American Housing Survey, and the Property 
Owners and Managers Survey in order to estimate these special 
affordable shares.

a. Special Affordable Owner Percentages

    The percentage of single-family-owners that qualify for the 
Special Affordable Goal is reported in Table D.20. That table also 
reports data for the two components of the Special Affordable Goal--
very-low-income

[[Page 65222]]

borrowers and low-income borrowers living in low-income census 
tracts. HMDA data show that special affordable borrowers accounted 
for 15.3 percent of all conforming home purchase loans between 1996 
and 1998. The special affordable share of the market has followed a 
pattern similar to that discussed earlier for the low-mod share of 
the market. The percentage of special affordable borrowers increased 
significantly between 1992 and 1994, from 10.4 percent of the 
conforming market to 12.6 percent in 1993, and then to 14.1 percent 
in 1994. The additional years since the 1995 rule was written have 
seen the special affordable market maintain itself at an even higher 
level. Over the past four years (1995-98), the special affordable 
share of the home loan market has averaged 15.1 percent, or almost 
13.0 percent if manufactured and small loans are excluded from the 
market totals. 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 market 
has changed in fundamental ways from the mortgage market of the 
early 1990s. The effect of one factor, the growth in the B&C loans, 
on the special affordable market is discussed below in Section H.2.
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b. Very-Low-Income Rental Percentages

    Table D.14 in Section F 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.

[[Page 65223]]

    Outstanding Housing Stock versus Mortgage Flow. As discussed 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.84 HUD's analysis of POMS 
data suggests that it can--estimates from POMS of the rent 
affordability of newly-mortgaged rental properties are quite 
consistent with the AHS data reported in Table D.14 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 was 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. The baseline projection 
from HUD's market share model assumes that 50 percent of newly-
mortgaged, single-family rental units, and 47 percent of multifamily 
units, are affordable to very-low-income families.

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. 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.85 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.86 The baseline 
analysis below assumes 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.87

2. Size of the Special Affordable Market

    During the 1995 rule making, HUD estimated a market share for 
the Special Affordable Goal of 20-23 percent. This estimate turned 
out to be below market experience, as the special affordable market 
accounted for almost 29 percent of all housing units financed in 
metropolitan areas between 1995 and 1997 (see Table D.15). As 
explained in Section F.3.a, there are several explanations for HUD's 
underestimate of the 1995-97 market. The financing of rental 
properties during 1995-97 was larger than anticipated. Another 
important reason for HUD's underestimate was not anticipating the 
high percentage of single-family-owner mortgages that would be 
originated for special affordable borrowers. During the 1995-97 
period, 15.4 percent of all (both home purchase and refinance) 
single-family-owner mortgages financed properties for special 
affordable borrowers; this compares with 9.5 percent for the 1992-94 
period which was the basis for HUD's earlier analysis. The 1995-97 
mortgage markets originated more affordable single-family mortgages 
than anticipated.88 Furthermore, the special affordable 
market remained strong during the heavy refinance year of 1998. 
Almost 26 percent of all dwelling units financed in 1998 qualified 
for the Special Affordable Goal.
    The size of the special affordable market depends in large part 
on the size of the multifamily market and on the special affordable 
percentages of both owners and renters. Table D.21 gives new market 
estimates for different combinations of these factors. As before, 
Case 2 is slightly more conservative than the baseline projections 
(Case 1) mentioned above. For instance, Case 2 assumes that only 6 
percent of rental units are affordable to low-income renters living 
in low-income areas.
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[[Page 65225]]

    When the special affordable share of the single-family market 
for home mortgages is at its 1994-98 level of 14-15 percent, the 
special affordable market estimate is 26-27 percent under HUD's 
projections. In fact, the market estimates remain above 23 percent 
even if the special affordable percentage for home loans falls from 
its 15-percent-plus level during 1996-1998 to as low as 10-11 
percent, which is similar to the 1992 level. Thus, a 23 percent 
market estimate allows for the possibility that adverse economic 
conditions could keep special affordable families out of the housing 
market. On the other hand, if the special affordable percentage 
stays at its recent levels, the market estimate is in the 26-27 
percent range.\89\
    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 special affordable percentage for B&C 
loans is 28.5 percent, which is not much higher than the projected 
percentages for the overall market given in Table D.21. Thus, 
dropping B&C loans will not appreciably reduce the overall market 
estimates. Consider in Table D.21, the case of a single-family-owner 
percentage of 14 percent, which yields an overall market estimate 
for Special Affordable Goal of 25.9 percent. Dropping B&C loans from 
the projection model reduces the special affordable market share by 
0.2 percentage points to 25.7. Thus, the market shares reported in 
Table D.21 are reasonable estimates of the size of the special 
affordable market excluding B&C loans.
    Based on the data presented in Table D.21 and the analysis of 
the effects of excluding B&C loans from the market, a range of 23-26 
percent is a reasonable estimate of the special affordable market. 
This range includes market conditions that are much more adverse 
than have recently existed. Additional sensitivity analyses are 
provided in the remainder of this section.
    Additional Sensitivity Analyses. Assuming that the special 
affordable share of the home loan market is 13 percent, reducing the 
multifamily mix from 15 percent to 12 (10) percent would reduce the 
overall special affordable market share from 25.2 percent to 24.0 
(23.3) percent. In this case, increasing the multifamily mix from 15 
percent to 18 percent would increase the special affordable market 
share from 25.2 percent to 26.4 percent.
    As shown in Table D.21, the market estimates under the more 
conservative Case 2 projections are approximately two percentage 
points below those under the Case 1 projections. This is due mainly 
to Case 2's lower share of single-family investor mortgages (8 
percent versus 10 percent in Case 1) and its lower affordability and 
low-income-area percentages for rental housing (e.g., 53 percent for 
single-family rental units in Case 2 versus 58 percent in Case 1).
    Increasing the single-family projection by $100 billion, from 
$950 billion to $1,050 billion, would reduce the market share for 
the Special Affordable Goal by approximately 0.4 percentage points, 
assuming the other baseline assumptions remain unchanged.\90\ A $200 
billion increase would reduce the special affordable market share by 
0.8 percentage point.
    A recession scenario and a heavy refinance scenario were 
described during the discussion of the Low- and Moderate-Income Goal 
in Section F. The recession scenario assumed that special affordable 
borrowers would account for only 10 (9) percent of newly-originated 
home loans. In this case, the market share for the Special 
Affordable Goal declines to 24.2 (23.5) percent. In the heavy 
refinance scenario, the special affordable percentage for 
refinancing borrowers was assumed to be four percentage points lower 
that the corresponding percentage for borrowers purchasing a home. 
In this case, the market share for the Special Affordable Goal was 
typically in the 24-25 percent range, depending on assumptions about 
the incomes of borrowers in the home purchase market. As noted 
earlier, the special affordable market share was approximately 26 
percent during 1998, a period of heavy refinance activity.
    Finally, HUD simulated the specific scenario based on the MBA's 
most recent market estimate of $912 billion and a refinance rate of 
22 percent. In this case, assuming a special affordable home 
purchase percentage of 14, the overall special affordable market 
share was varied from 25.5 percent to 26.6 percent as the 
multifamily mix of varied from 13.5 percent to 16.5 percent.
    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 increase Fannie 
Mae's performance as follows: 0.5 percentage point in 1997 (from 
16.5 to 12.0 percent); 0.29 percentage point in 1998 (from 14.05 to 
14.34 percent); and 0.42 percent point in 1999 (from 17.20 to 17.62 
percent). The increase for Freddie Mac has been lower (about 0.20 
percentage point in 1998 and 1999).

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 23-26 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 five years. In addition, the estimate covers 
a range of projections about the size of the multifamily market.

Endnotes to Appendix D

    \1\ Appendix D of the proposed rule also included a Section I 
that examined the likely impacts of the increase in FHA loans limits 
on market originations for lower-income families in the conventional 
market. That analysis--which concluded that the market impacts would 
likely be small given that FHA attracts a different group of 
borrowers than conventional lenders--is now included in the 
Department's Economic Analysis for this final GSE rule.
    \2\ 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.
    \3\ Readers not interested in this overview may want to proceed 
to Section B, which summarizes HUD's response to the GSEs' comments 
on HUD's market methodology.
    \4\ Sections 1332(b)(4), 1333(a)(2), and 1334(b)(4).
    \5\ So-called ``jumbo'' mortgages, greater than $227,150 in 1998 
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.
    \6\ The owner of the SF 2-4 property is counted in (a).
    \7\ 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).
    \8\ 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.
    \9\ This goal will be referred to as the ``Underserved Areas 
Goal''.
    \10\ See Randall M. Scheessele, HMDA Coverage of the Mortgage 
Market, Housing Finance Working Paper No. 7, Office of Policy 
Development and Research, Department of Housing and Urban 
Development, July 1998; and 1998 HMDA Highlights, Housing Finance 
Working Paper No. HF-009, Office of Policy Development and Research, 
Department of Housing and Urban Development, October 1999.
    \11\ See William Segal, The Property Owners and Managers Survey 
and the Multifamily Housing Finance System, Housing Finance Working 
Paper No. 10, Office of Policy Development and Research, Department 
of Housing and Urban Development, September 2000.
    \12\ 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.
    \13\ 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.
    \14\ PWC estimates of single-family mortgage lending volume 
exceed the MBA figure for

[[Page 65226]]

the entire single-family market (conventional, conforming, jumbo, 
and government-insured) in 1993. The PWC estimates exceed MBA 
figures on all conventional lending volume, including jumbo loans, 
in 1994, 1996 and 1997. In effect, therefore, the PWC estimates of 
the single-family market include the jumbo market in 1993, 1994, 
1996, 1997, and 1998. The PWC estimates are as large, or larger than 
the entire single-family market in 1993 and 1998. The MBA figures 
are found at www.mbaa.org/marketkdata.
    \15\ PWC does not offer any empirical evidence in support of 
their claim that 50 percent of households have below median family 
income. The main reason that more than half of all households have 
incomes below the median family income is that, empirically, 
household incomes are significantly lower than family incomes (which 
serve as the basis for the local area median income against which 
household incomes are compared to determine affordability status). 
Individuals are not included in family income calculations, but are 
included in household income calculations, thus causing a family-
based median income to be larger than a household-based median 
income.
    \16\ 1990 is excluded from this discussion because of the 
unusually high multifamily mix that year.
    \17\ These market share estimates are based on the annual 
averages of the likely range of multifamily origination volume 
expressed in the last column of Table D.10 over 1991-1998. 1990 is 
excluded from this calculation because of the unusually high 
multifamily mix that year.
    \18\ Amy D. Crews, Robert M. Dunsky, and James R. Follain, 
``What We Know about Multifamily Mortgage Originations,'' report for 
the U.S. Department of Housing and Urban Development, October 1995, 
20.
    \19\ Because they are not counted toward the GSE housing goals 
(with the exception of a relatively small risk-sharing program), FHA 
mortgages are excluded from this analysis. Other categories of 
mortgages, considering the type of insurer, servicer, or holder, do 
not tend to have mortgage characteristics that appear to differ 
substantially from the multifamily mortgages that are purchased by 
Fannie Mae and Freddie Mac. There is thus no particular basis for 
excluding them.
    \20\ Corresponding percentages for Freddie Mac were 8.3 percent, 
90 percent and 17 percent.
    \21\ Corresponding percentages for Fannie Mae were 56 percent 
and 31 percent.
    \22\ Amy D. Crews, Robert M. Dunsky, and James R. Follain, 
``What We Know about Multifamily Mortgage Originations,'' report for 
the U.S. Department of Housing and Urban Development, October 1995.
    \23\ Crews, Dunsky, and Follain, ibid., 20.
    \24\ Fannie Mae (2000), p. 58.
    \25\ Robert Dunsky, James R. Follain, and Jan Ondrich, ``An 
Alternative Methodology to Estimate the Volume of Multifamily 
Mortgage Originations,'' report for the U.S. Department of Housing 
and Urban Development, October 1995.
    \26\ Average single-family loan amounts are from HMDA. 
Multifamily per-unit loan amounts are from the loan-level GSE data, 
as discussed above.
    \27\ Increased per-unit loan amounts evident in the 1999 Freddie 
Mac data could be related to a higher level of activity in senior 
housing. Freddie Mac reported an increase in multifamily senior 
housing transactions from $84 million in 1998 to $383 million in 
1999. See ``Freddie Mac Posts Record Year in Multifamily Financing, 
Nearly $7 Billion in Originations, `` press release, February 8, 
1999; and ``Freddie Mac Posts Record Year in Multifamily Financing, 
Nearly $8 Billion in Total Funding In 1999,'' press release, 
February 14, 2000. Per-unit loan amounts on some Freddie Mac seniors 
transactions appear to exceed $100,000. See ``Freddie Mac Teams With 
Glaser Financial to Credit Enhance $65 Million in Seniors Housing 
Loans,'' press release, July 13, 1999; and ``Freddie Mac Closes Its 
Largest Seniors Housing Transaction With $88 Million Deal With GMAC 
and Sunrise Assisted Living,'' press release, June 1, 1999.
    \28\ Assumptions regarding the single-family mortgage market 
utilized in preparing the market share estimates presented in Table 
D.10 are discussed below in section F.
    \29\ Board of Governors of the Federal Reserve System, Flow of 
Funds Accounts of the United States, Federal Reserve Statistical 
Release Z.1, June 9, 2000, p. 49.
    \30\ These market share estimates are based on the annual 
averages of the likely range of multifamily origination volume 
expressed in the last column of Table 10 over 1991-1998. 1990 is 
excluded from this calculation because of the unusually high 
multifamily mix that year.
    \31\ Calculation based on PriceWaterhouseCoopers, Ibid., p. 15.
    \32\ The data in Table D.11a ignore HMDA loans with ``non-
applicable'' for owner type.
    \33\ Due to the higher share of refinance mortgages during 1998, 
the overall single-family owner percentage reported by HMDA for 1998 
(93.2 percent) is larger than that reported for 1997 (91.5 percent).
    \34\ 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.
    \35\ For example, they note that discussions with some lenders 
suggest that because of higher mortgage rates on investor 
properties, some HMDA-reported owner-occupants may in fact be 
``hidden'' investors; however, it would be difficult to quantify 
this effect. They also note that some properties may switch from 
owner to renter properties soon after the mortgage is originated. 
While such loans would be classified by HMDA as owner-occupied at 
the time of mortgage origination, they could be classified by the 
RFS as rental mortgages. Again, it would be difficult to quantify 
this effect given available data.
    \36\ Blackley and Follain (1996), p. 20.
    \37\ The unit-per-mortgage data from the 1991 RFS match closely 
the GSE purchase data for 1996 and 1997. Blackley and Follain show 
that an adjustment for vacant investor properties would raise the 
average units per mortgage to 1.4; however, this increase is so 
small that it has little effect on the overall market estimates.
    \38\ The property distribution reported in Table D.1 is an 
example of the market share model. Thus, this section completes Step 
1 of the three-step procedure outlined in Section A.2.b.
    \39\ From MBA volume estimates, 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-period low of 81 percent in 1994. 
Calculated from ``1-4 Family Mortgage Originations'' tables (Table 
1--Industry and Table 2--Conventional Loans) from ``MBA Mortgage and 
Market Data,'' at www.mbaa.org/marketdata/ as of July 13, 2000.
    \40\ Data provided by Fannie Mae show that conforming loans have 
been about 78 percent of total conventional loans over the past few 
years.
    \41\ Single-family mortgage originations of $950 billion were 
$266 billion higher than the $834 billion in 1997, $520 billion less 
than the record setting $1,470 billion in 1998 and $335 billion less 
than the $1,285 billion in 1999. As discussed later, single-family 
originations could differ from $950 billion during the 2001-2003 
period that the goals will be in effect. As recent experience shows, 
market projections often change. For example, $950 billion is 
similar to recent projections (made in June, 2000) by the Mortgage 
Bankers Association (MBA) of $955 billion in 2000 and $903 billion 
in 2001. (See http://www.mbaa.org/marketdata/forecasts June, 2000 
Mortgage Finance Forecasts.) However, MBA estimates for year 2000 
volume have changed substantially over the past year, dropping from 
$1,043 in June, 1999 to $955 billion more recently (see MBA Mortgage 
Finance Forecasts table in Mortgage Finance Review, Vol. 7, Issue 
No. 2, 1999 2nd quarter, p. 2). Section F will report the effects on 
the market estimates of alternative estimates of single-family 
mortgage originations. As also explained later, 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.
    \42\ The model also requires an estimated refinance rate because 
purchase and refinance loans have different shares of goals-
qualifying units. Over the past year, the MBA has estimated the year 
2000 refinance rate to be 16, 20, 30, and 38 percent for the total 
market (expressed in dollar terms), with 16 percent the latest 
estimate. The MBA's current estimate of the year 2001 refinance rate 
is very low 12 percent. The baseline model uses a refinance rate of 
35 percent for conforming conventional loans, which is consistent 
with an MBA-type estimate of 22 percent, since refinance rates are 
higher for the number of conventional conforming loans than for the 
total market expressed in dollar terms. The 35 percent refinance 
assumption (compared with the recent, lower MBA

[[Page 65227]]

projections) results in conservative estimates of goals-qualifying 
units in the market, since the low-mod share of refinance units in 
HUD's model is lower than the low-mod share of home purchase units. 
Sensitivity analyses for alternative refinance rates are presented 
in Sections F-H.
    \43\ The average 1998 loan amount is estimated at $104,656 for 
owner occupied units using 1998 HMDA metro average loan amounts for 
purchase and refinance loans, and then weighting by an assumed 35 
percent refinance rate. A small adjustment is made to this figure 
for a small number of two-to-four and investor properties (see 
Section D above). This produces an average loan size of $102,664 for 
1998, which is then inflated 3 percent a year for three years to 
arrive at an estimated $110,000 average loan size for 2001.
    \44\ Based on the RFS, there is an average of 2.25 housing units 
per mortgage for 2-4 properties. 1.25 is used here because one 
(i.e., the owner occupant) of the 2.25 units is allocated to the SF-
O category. The RFS is also the source of the 1.35 used in (4c).
    \45\ 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.
    \46\ Owners of 2-4 properties account for 1.6 percentage points 
of the 88 percent for SF-O.
    \47\ Restricting the RFS analysis to 1991 resulted in only minor 
changes to the market shares.
    \48\ 1990 conventional multifamily origination volume in RFS can 
be estimated at $37.4 billion, comparable to HUD's estimate of $36-
$40 billion in 1997. Conventional, conforming single-family 
origination volume grew from $285 billion to $581 billion over the 
same period. 1990 appears to have exhibited unusually high 
multifamily origination volume, as discussed earlier in Section C.
    \49\ As noted earlier, 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.
    \50\ Actually, the goals-qualifying percentages reported in this 
appendix include only the effects of manufactured houses in 
metropolitan areas, as HMDA does not adequately cover non-
metropolitan areas.
    \51\ 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.
    \52\ Freddie Mac, the Manufactured Housing Institute and the Low 
Income Housing Fund have formed an alliance to utilize manufactured 
housing along with permanent financing and secondary market 
involvement to bring affordable, attractive housing to underserved, 
low- and moderate-income urban neighborhoods. Origination News. 
(December 1998), p.18.
    \53\ Randall M. Scheessele had developed a list of nine 
manufactured home lenders that has been used by several researchers 
in analyses of HMDA data prior to 1997. Scheessele developed the 
expanded list of 21 manufactured home loan lenders in his analysis 
of 1998 HMDA data. (See Randall M. Scheessele, 1998 HMDA Highlights, 
op. cit.) In these appendices, the number of manufactured home loans 
deducted from the market totals for the years 1993 to 1997 are the 
same as reported by Scheessele (1999) in his Table D.2b.
    \54\ See Appendix D of the 1995 rule for a detailed discussion 
of the AHS data and improvements that have been made to the survey 
to better measure borrower incomes and rent affordability.
    \55\ Some even argued that data based on the recently completed 
stock would be a better proxy for mortgage flows. In the case of the 
Low- and Moderate-Income Goal, there is not a large difference 
between the affordability percentages for the recently constructed 
stock and those for the outstanding stock of rental properties. But 
this is not the case when affordability is defined at the very-low-
income level. As shown in Table D.5, the recently completed stock 
houses substantially fewer very-low-income renters than does the 
existing stock. Because this issue is important for the Special 
Affordable Goal, it will be further analyzed in Section H when that 
goal is considered.
    \56\ In 1999, 88.7 percent of GSE purchases of single-family 
rental units and 93.1 percent of their purchases of multifamily 
units qualified under the Low- and Moderate-Income Goal, excluding 
the effects of missing data.
    \57\ The goals-qualifying shares reported in Table D.15 for 
1995-98 are, of course, estimates themselves; even though 
information is available from HMDA and other data sources for most 
of the important model parameters, there are some areas where 
information is limited, as discussed throughout this appendix.
    \58\ The 1995-98 goals-qualifying percentages for single-family 
mortgages are based on HMDA data for all (both home purchase and 
refinance) mortgages. Thus, the implicit refinance rate is that 
reported by HMDA for conventional conforming mortgages.
    \59\ HUD had based its earlier projections heavily on market 
trends between 1992 and 1994. During this period, low- and moderate-
income borrowers accounted for only 38 percent of home purchase 
loans, which is consistent with an overall market share for the Low- 
and Moderate-Income Goal of 52 percent (see Table D.17 below), which 
was HUD's upper bound in the 1995 rule. Based on the 1993 and 1994 
mortgage markets, HUD's earlier estimates also assumed that 
refinance mortgages would have smaller shares of lower-income 
borrowers than home purchase loans; the experience during the 1995-
1997 period was the reverse, with refinance loans having higher 
shares of lower-income borrowers than home purchase loans. For 
example, in 1997, 45 percent of refinancing borrowers had less-than-
area-median incomes, compared with 42.5 percent of borrowers 
purchasing a home.
    \60\ The 1995-97 estimates also include the effects of small 
loans (less than $15,000) and manufactured housing loans which 
increase the market shares for metropolitan areas by approximately 
one percentage point. For example, assuming a constant mix of owner 
and rental properties, excluding these loans would reduce the goals-
qualifying shares as follows: the Low- and Moderate-Income Goal by 
1.4 percentage points, and the Special Affordable Goal and 
Underserved Areas Goals by one percentage point. However, dropping 
manufactured housing from the market totals would increase the 
rental share of the market, which would tend to lower these impact 
estimates. 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 this segment of the market would tend to increase 
the goals-qualifying shares of the overall market. Thus, the 
analyses of manufactured housing reported above and throughout the 
text pertain only to manufactured housing loans in metropolitan 
areas, as measured by loans originated by the manufactured housing 
lenders identified by Scheessele, op. cit.
    \61\ The accuracy of the single-family portion of HUD's model 
can be tested using HMDA data. The number of single-family loans 
reported to HMDA for the years 1995 to 1997 can be compared with the 
corresponding number predicted by HUD's model. Single-family loans 
reported to HMDA during 1995 were 79 percent of the number of loans 
predicted by HUD's model; comparable percentages for 1996, 1997, and 
1998 were 83 percent , 82 percent, and 88 percent, respectively. 
Studies of the coverage of HMDA data through 1996 conclude that HMDA 
covers approximately 85 percent of the conventional conforming 
market. (See Randall M. Scheessele, HMDA Coverage of the Mortgage 
Market, op. cit.) The fact that the HMDA data account for lower 
percentages of the single-family loans predicted by HUD's model 
suggests that HUD's model may be slightly overestimating the number 
of single-family loans during the 1995-97 period. The only caveat to 
this concerns manufactured housing in non-metropolitan areas. The 
average loan amount that HUD used in calculating the number of units 
financed from mortgage origination dollars did not include the 
effects of manufactured housing in non-metropolitan areas; thus, 
HUD's average loan amount is too high, which suggests that single-
family-owner mortgages are underestimated. (Similarly, the goals-
qualifying percentages in HUD's model are based on metropolitan area 
data and therefore do not include the effects of manufactured 
housing in non-metropolitan areas.)
    \62\ A 15 percent estimate for 1997 is reported by Michelle C. 
Hamecs and Michael Benedict, ``Mortgage Market Developments'', in 
Housing Economics, National Association of Home Builders, April 
1998, pages 14-17. Hamecs and Benedict draw their estimate from a 
survey by Inside B&C Lending, an industry publication. A 12 percent 
estimate is reported in ``Subprime Products: Originators Still Say 
Subprime Is `Wanted Dead or Alive' '' in Secondary Marketing 
Executive, August 1998, 34-38. Forest Pafenberg reports that 
subprime mortgages

[[Page 65228]]

accounted for 10 percent of the conventional conforming market in 
1997; see his article, ``The Changing Face of Mortgage Lending: The 
Subprime Market'', Real Estate Outlook, National Association of 
Realtors, March 1999, pages 6-7. Pafenberg draws his estimate from 
Inside Mortgage Capital, which used data from the Mortgage 
Information Corporation. 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.
    \63\ Based on information from The Mortgage Information 
Corporation, Pafenberg reports the following serious delinquency 
rates (either 90 days past due or in foreclosure) for 1997 by type 
of subprime loan: 2.97 percent for A-minus; 6.31 percent for B; 9.10 
percent for C; and 17.69 percent for D. The D category accounted for 
only 5 percent of subprime loans and of course, is included in the 
``B&C'' category referred to in this appendix. Also see ``Subprime 
Mortgage Delinquencies Inch Higher, Prepayments Slow During Final 
Months of 1998'', Inside MBS & ABS: Inside MBS & ABS, March 12, 
pages 8-11, where it is reported that fixed-rate A-minus loans have 
delinquency rates similar to high-LTV (over 95 percent) conventional 
conforming loans.
    \64\ Not surprisingly, the goals-qualifying percentages for 
subprime lenders are much higher than the percentages (43.6 percent, 
16.3 percent, and 27.8 percent, respectively) for the overall 
single-family conventional conforming market in 1997. For further 
analysis of subprime lenders, see Randall M. Scheessele, 1998 HMDA 
Highlights, op. cit.
    \65\ 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 Table D.13 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.
    \66\ In 1998, the ``unadjusted'' market shares (i.e., inclusive 
of B&C loans) were as follows: Low-Mod Goal (54.1 percent); Special 
Affordable Goal (26.0 percent); and Underserved Areas Goal (30.4 
percent). The 1998 conforming B&C market is estimated to be $61 
billion, with an average loan amount of $75,062 representing an 
estimated 812,662 B&C conforming loans. The 1998 goals-qualifying 
percentages (low-mod, 58.0 percent; special affordable, 28.5 
percent; and underserved areas, 44.7 percent) used to ``proxy'' the 
B&C market are similar to those for 1995-97. As noted earlier, there 
is much uncertainty about the size of the B&C market.
    \67\ The percentages in Table D.17 refer to borrowers purchasing 
a home. In HUD's model, the low-mod share of refinancing borrowers 
is assumed to be three percentage points lower than the low-mod 
share of borrowers purchasing a home; three percentage points is the 
average differential between 1992 and 1999. Thus, the market share 
model with the 40 percent owner percentage in Table D.17 assumes 
that 40 percent of home purchase loans and 37 percent of refinance 
loans are originated for borrowers with low- and moderate-income. If 
the same low-mod percentage were used for both refinancing and home 
purchase borrowers, the overall market share for the Low- and 
Moderate-Income Goal would increase by 0.7 of a percentage point.
    \68\ Assuming a 42 (40) percent low-mod share of the owner 
market, the low-mod share of the overall market increased from 52.5 
(51.0) percent to 55.9 (54.5) percent as the multifamily mix 
increased from 10 percent to 18 percent.
    \69\ On the other hand, in the heavy refinance year of 1998, 
refinancing borrowers had higher incomes than borrowers purchasing a 
home.
    \70\ The three percentage point differential is the average for 
the years 1992 to 1998 (see Table D.14).
    \71\ Rather, this approach reflects 1998 market conditions when 
the low-mod differential between home purchase and refinance loans 
was approximately three percentage points.
    \72\ The $82,022 is derived by adjusting the 1997 figure of 
$68,289 upward based on recent growth in the average loan amount for 
all loans. Also, it should be mentioned that one recent industry 
report suggests that the B&C part of the subprime market has fallen 
to 37 percent. See ``Retail Channel Surges in the Troubled ``98 
Market'' in Inside B&C Lending, March 25, 1999, page 3.
    \73\ As before, 1998 HMDA data for 200 subprime lenders were 
used to provide an estimate of 58.0 percent for the portion of the 
B&C market that would qualify as low- and moderate-income. Applying 
the 58.0 percentage to the estimated B&C market total of 555,948 
gives an estimate of 322,450 B&C loans that would qualify for the 
Low- and Moderate-Income Goal. Adjusting HUD's model to exclude the 
B&C market involves subtracting the 555,948 B&C loans and the 
322,450 B&C low-mod loans from the corresponding figures estimated 
by HUD for the total single-family and multifamily market inclusive 
of B&C loans. HUD's projection model estimates that 7,308,558 
single-family and multifamily units will be financed and of these, 
3,990,525 (54.6 percent as in Table D.17) will qualify for the Low- 
and Moderate-Income Goal. Deducting the B&C market estimates 
produces the following adjusted market estimates: a total market of 
6,752,610 of which 3,668,074 (54.3 percent) will qualify for the 
Low- and Moderate-Income Goal.
    \74\ This reduction in the low-mod share of the mortgage market 
share occurs because the multifamily mix is reduced from 15 percent 
to 13.8 percent. (See Section F.3b for additional sensitivity 
analyses of the multifamily mix.)
    \75\ Refinance mortgages were assumed to account for 15 percent 
of all single-family originations; 31 percent of refinancing 
borrowers were assumed to have less-than-area-median incomes, which 
is 14 percentage points below the 1997 level. A multifamily mix of 
17.3 percent was assumed during the recession scenario. If the 
multifamily mix were reduced to 15.2 percent in this environment, 
the low-mod share would drop to 47.9 percent.
    \76\ Section 1336(b)(3)(A).
    \77\ As shown in Table D.18, excluding loans less than $15,000 
and manufactured home loans reduces the 1997 underserved area 
percentage by 1.2 percentage points for all single-family-owner 
loans from 27.8 to 26.6 percent. Dropping only small loans reduces 
the underserved areas share of the metropolitan market by 0.4 and 
dropping manufactured loans (above $15,0000) reduces the market by 
0.8.
    \78\ The main reason for HUD's underestimate in 1995 was not 
anticipating the high percentages of single-family-owner mortgages 
that would be originated in underserved areas. During the 1995-97 
period, about 27 percent of single-family-owner mortgages financed 
properties in underserved areas; this compares with 24 percent for 
the 1992-94 period which was the basis for HUD's earlier analysis. 
There are other reasons the underserved area market shares for 1995 
to 1997 were higher than HUD's 25-28 percent estimate. Single-family 
rental and multifamily mortgages originated during this period were 
also more likely to finance properties located in underserved areas 
than assumed in HUD's earlier model. In 1997, 45 percent of single-
family rental mortgages and 48 percent of multifamily mortgages 
financed properties in underserved areas, both figures larger than 
HUD's assumptions (37.5 percent and 42.5 percent, respectively) in 
its earlier model. Even in the heavy refinance year of 1998, the 
underserved areas market share (31 percent) was higher than 
projected by HUD during the 1995 rule-making process.
    \79\ Table D.19 presents estimates for the same combinations of 
projections used to analyze the Low- and Moderate-Income Goal. Table 
D.16 in Section F.3 defines Cases 1, 2, and 3; Case 1 (the baseline) 
projects a 42.5 percent share for single-family rentals and a 48 
percent share for multifamily properties while the more conservative 
Case 2 projects 40 percent and 46 percent, respectively.
    \80\ These data do not include loans originated by lenders that 
specialize in manufactured housing loans.
    \81\ Assuming that non-metropolitan areas account for 15 percent 
of all single-family-owner mortgages and recalling that the 
projected single-family-owner market for the year 2001 accounts for 
72.2 percent of newly-mortgaged dwelling units, then the non-
metropolitan underserved area differential of 17 percent would raise 
the overall market estimate by 1.9 percentage point--17 percentage 
points times 0.15 (non-metropolitan area mortgage market share) 
times 0.722 (single-family owner mortgage

[[Page 65229]]

market share). This calculation is the basis for the 1.5 percentage 
point adjustments to the 1995-98 underserved area market shares 
reported earlier in Table D.15.
    \82\ It is recognized that some may not view all of the 
assumptions made to generate the results in Table D.19 as 
conservative. The term ``conservative'' is being use here to reflect 
the fact that adjusting the data in Table D.19 to include 
underserved non-metropolitan counties would increase the underserved 
areas market share more than adjusting the same data to exclude B&C 
loans would reduce it.
    \83\ 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.
    \84\ Previous analysis of this issue has focused on the relative 
merits of data from the recently completed stock versus data from 
the outstanding stock. The very-low-income percentages are much 
lower for the recently completed stock--for instance, the averages 
across the five AHS surveys were 15 percent for recently completed 
multifamily properties versus 46 percent for the multifamily stock. 
But it seems obvious that data from the recently completed stock 
would underestimate the affordability of newly-mortgaged units 
because they exclude purchase and refinance transactions involving 
older buildings, which generally charge lower rents than newly 
constructed buildings. Blackley and Follain concluded that newly 
constructed properties did not provide a satisfactory basis for 
estimating the affordability of newly mortgaged properties. See ``A 
Critique of the Methodology Used to Determine Affordable Housing 
Goals for the Government Sponsored Enterprises.''
    \85\ 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.
    \86\ 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.
    \87\ Therefore, 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 is the baseline 
Case 1 in Table D.6.
    \88\ The 28.8 percent estimate for 1997 excludes B&C loans but 
includes manufactured housing and small loans while HUD's earlier 
20-23 percent estimate excluded the effects of these loans. 
Excluding manufacturing housing and small loans from the 1997 market 
would reduce the special affordable share of 28.8 percent by a 
percentage point. This can be approximated by multiplying the 
single-family-owner property share (0.702) for 1997 by the 1.4 
percentage point differential between the special affordable share 
of all (home purchase and refinance) single-family-owner mortgages 
in 1997 with manufactured and small loans included (16.3 percent) 
and the corresponding share with these loans excluded (14.9 
percent). This gives a reduction of 0.98 percentage point. These 
calculations overstate the actual reduction because they do not 
include the effect of the increase in the rental share of the market 
that accompanies dropping manufactured housing and small loans from 
the market totals.
    \89\ The upper bound of 27 percent from HUD's baseline special 
affordable model is obtained when the special affordable share of 
home purchase loans is 15 percent, which was the figure for 1997 
(see Table D.20). However, the upper bound of 27 percent is below 
the 1997 estimate of the special affordable market of almost 29 
percent (see Table D.15). There are several reasons for this 
discrepancy. As mentioned earlier, the rental share in HUD's 
baseline projection model is less than the rental share of the 1997 
market. In addition, HUD's projection model assumes that the special 
affordable share of refinance mortgages will be 1.4 percentage 
points less than the corresponding share for home purchase loans 
(1.4 percent is the average difference between 1992 and 1998). But 
in 1997, the special affordable share (17.6 percent) of refinance 
mortgages was larger than the corresponding share (15.3 percent) for 
home loans.
    \90\ This reduction in the special affordable share of the 
mortgage market share occurs because the multifamily mix is reduced 
from 15 percent to 13.8 percent. (See above for additional 
sensitivity analyses of the multifamily mix.)

[FR Doc. 00-27367 Filed 10-30-00; 8:45 am]
BILLING CODE 4210-27-P