[Federal Register Volume 69, Number 85 (Monday, May 3, 2004)]
[Proposed Rules]
[Pages 24229-24493]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 04-9352]



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Part II





Department of Housing and Urban Development





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24 CFR Part 81



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

[[Page 24228]]

nie Mae and Freddie Mac; Proposed Rule

  Federal Register / Vol. 69, No. 85 / Monday, May 3, 2004 / Proposed 
Rules  
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DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT

24 CFR Part 81

[Docket No. FR-4790-P-01]
RIN 2501-AC92


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

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

ACTION: Proposed rule.

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SUMMARY: Through this proposed rule, the Department of Housing and 
Urban Development is proposing new housing goal levels for the Federal 
National Mortgage Association (Fannie Mae) and the Federal Home Loan 
Mortgage Corporation (Freddie Mac) (collectively, the Government 
Sponsored Enterprises, or GSEs) for calendar years 2005 through 2008. 
The new housing goal levels are proposed 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.
    To increase homeownership opportunities for families targeted by 
the three housing goals, this rule also would establish new subgoals 
for the GSEs' acquisitions of home purchase loans that qualify for each 
of the housing goals. Under the proposed rule, performance under these 
subgoals would be calculated as percentages of the GSEs' total 
acquisitions of home purchase mortgages for single-family, owner-
occupied properties located in metropolitan areas meeting each of the 
three housing goals.
    The Department also proposes to revise the existing rule to provide 
enhanced requirements to ensure GSE data integrity by: codifying the 
existing authority that authorizes HUD to independently verify the 
accuracy and completeness of data, information and reports provided by 
the GSEs; establishing certification requirements for the submission of 
the GSEs' Annual Housing Activities Report (AHAR) and for such other 
report(s), data submission(s) or information for which certification is 
requested in writing by HUD; codifying a process for handling errors, 
omissions or discrepancies in a GSE's current year-end data 
submissions; clarifying that HUD may exercise its goal counting 
authority by adjusting a GSE's housing goals performance for a current 
year by deducting miscredits from a previous year caused by errors, 
omissions or discrepancies in a GSE's prior year data submissions 
(including the AHAR); and clarifying that HUD may take enforcement 
action against the GSEs, as authorized by FHEFSSA and as implemented by 
HUD's regulations at 24 CFR part 81, subpart G, for the submission of 
non-current, inaccurate or incomplete report(s), data or information.
    In addition, HUD is proposing in this rulemaking to amend the 
definitions of ``Underserved area'', ``Metropolitan area'' and 
``Minority'', and to add a new definition of the term ``Home Purchase 
Mortgage'.
    The rulemaking also invites comments on whether HUD should have a 
standard econometrically based method for imputing the distribution of 
GSE-purchased mortgages that lack income data, and whether HUD should 
revise its definitions or other rules (including the counting rules) to 
ensure that only those large scale GSE transactions that are consistent 
with the statute and its purposes qualify under the goals.

DATES: Comments must be submitted on or before: July 2, 2004.

ADDRESSES: Interested persons are invited to submit written comments 
regarding this proposed rule to the Regulations Division, Office of 
General Counsel, Room 10276, Department of Housing and Urban 
Development, 451 Seventh Street, SW., Washington, DC 20410. All 
communications should refer to the above docket number and title. 
Facsimile (FAX) comments and e-mail comments are not acceptable. A copy 
of each communication submitted will be available for public inspection 
and copying between 8 a.m. and 5 p.m. weekdays at the above address.

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

SUPPLEMENTARY INFORMATION:

I. General

A. Statutory and Regulatory Background

    In 1968, at the time Fannie Mae was chartered in its current form 
as a government sponsored enterprise (GSE), Congress assigned the 
Department of Housing and Urban Development (``HUD'' or ``the 
Department'') regulatory authority over Fannie Mae pursuant to section 
802(ee) of the Housing and Urban Development Act of 1968 (Pub. L. 90-
448, approved August 1, 1968, 82 Stat. 476, 541) (HUD Act of 1968). In 
1989, Congress granted the Department essentially identical authority 
over another GSE, Freddie Mac, pursuant to section 731 of the Financial 
Institutions Reform, Recovery, and Enforcement Act of 1989 (FIRREA) 
(Pub. L. 101-73, approved August 9, 1989), which amended the Federal 
Home Loan Mortgage Corporation Charter Act, Pub. L. 91-351, approved 
July 24, 1970 (the ``Freddie Mac Charter Act'').
    Under section 802(ee) of the HUD Act of 1968, HUD was authorized to 
require that a ``reasonable portion'' of Fannie Mae's mortgage 
purchases be related to the national goal of providing adequate housing 
for low- and moderate-income families. Accordingly, in 1978, the 
Department established by regulation two housing goals for Fannie Mae: 
a goal for mortgages on low- and moderate-income housing and a goal for 
mortgages on housing located in central cities (see 24 CFR 81.16(d) and 
81.17 of HUD's former rules at 43 FR 39203, published August 15, 1978). 
HUD established each goal at the level of 30 percent of Fannie Mae's 
conventional mortgage purchases.
    Similar housing goals for Freddie Mac were proposed by the 
Department in 1991 (at 56 FR 41022, published August 16, 1991) but were 
not finalized prior to October 1992, when Congress enacted FHEFSSA and 
revised the Department's GSE regulatory authorities, including 
establishing new requirements for the housing goals.
    Specifically, FHEFSSA established the Office of Federal Housing 
Enterprise

[[Page 24229]]

Oversight (OFHEO) as the GSEs' safety and soundness regulator and 
affirmed, clarified and expanded the Secretary of Housing and Urban 
Development's GSE regulatory authority. FHEFSSA also provided that, 
except for certain exclusive authorities of the Director of OFHEO, and 
all other matters relating to the GSEs' safety and soundness, the 
Secretary had general regulatory power over the GSEs. (See section 1321 
of FHEFSSA, 12 U.S.C. 4541.)
    Further, FHEFSSA detailed and expanded the Department's 
responsibilities to establish, monitor, and enforce housing goals for 
the GSEs' purchases of mortgages that finance housing for low- and 
moderate-income families (the ``Low- and Moderate-Income Housing 
Goal''), housing located in central cities, rural areas, and other 
underserved areas (the ``Underserved Areas Housing Goal''), and special 
affordable housing, affordable to very low-income families and low-
income families in low-income areas (the ``Special Affordable Housing 
Goal'') (collectively, the ``Housing Goals'' or, individually, the 
``Housing Goal''). (See, generally, sections 1331-1334 of FHEFSSA, 12 
U.S.C. 4561-4564.) There is also a subgoal under the Special Affordable 
Housing Goal for multifamily housing.
    Under FHEFSSA, the Department is required to establish each Housing 
Goal after consideration of certain factors that are relevant to the 
particular Housing Goal, including: (a) National housing needs; (b) 
economic, housing and demographic conditions; (c) the performance and 
efforts of the GSEs toward achieving the Housing Goal in previous 
years; (d) the size of the market for mortgages targeted by the Housing 
Goal relative to the overall conventional mortgage market; (e) the 
ability of the GSEs to lead the industry in making credit available for 
mortgages targeted by the Housing Goal; and (f) the need to maintain 
the sound financial condition of the GSEs. (See sections 1332(b), 
1333(a)(2), 1334(b) of FHEFSSA; 12 U.S.C. 4562(b); 12 U.S.C. 
4563(a)(2); and 12 U.S.C. 4564.) (There are slight differences among 
the three Housing Goals in the statutory specification of the factors. 
In particular, for the Special Affordable Housing Goal factors (b) and 
(d) are absent, and there is a factor for data submitted in previous 
years to the Secretary in connection with the Housing Goal.)
    For the transition period of 1993-1994, FHEFSSA required HUD to 
establish interim Housing Goals, which HUD did in 1993 (at 53 FR 
53048). In November 1994, HUD extended the 1994 interim Housing Goals 
for both GSEs through 1995 while the Department completed its 
development of post-transition Housing Goals (see 59 FR 61504).
    In 1995, the Department issued a proposed rule (60 FR 9154, 
published February 16, 1995) and, several months later, a final rule 
(60 FR 61846, published December 1, 1995) (the ``Housing Goals 1995 
final rule'') establishing the Housing Goals for the years 1996 through 
1999, along with regulations implementing FHEFSSA. The Housing Goals 
1995 final rule provided that the Housing Goals for 1999 would continue 
beyond 1999 if the Department elected not to change the Housing Goals, 
and that HUD could change the level of the Housing Goals for the years 
2000 and beyond based upon HUD's experience and in accordance with 
HUD's statutory authority and responsibility.
    The Housing Goals 1995 final rule established counting requirements 
to calculate performance under the Housing Goals. The Housing Goals 
1995 final rule also: (1) Prohibited the GSEs from discriminating in 
any manner, on any prohibited basis, in their mortgage purchases; (2) 
implemented procedures for the exercise of HUD's new program review 
authority; (3) established reporting requirements and a public use data 
base of the GSEs' mortgage purchase activities; (4) provided 
protections for GSE confidential and proprietary information; and (5) 
established enforcement procedures.
    On March 9, 2000, HUD published a proposed rule to establish new 
Housing Goal levels for Fannie Mae and Freddie Mac for calendar years 
2000 through 2003 (see 65 FR 12632-12816). On October 31, 2000, after 
analyzing over 250 comments, HUD issued a final rule establishing the 
new Housing Goals (the ``Housing Goals 2000 Final Rule,'' 65 FR 65044-
65229).
    The Housing Goals 2000 final rule increased the level of the 
Housing Goals for Fannie Mae and Freddie Mac. Specifically, this rule:
    (1) Increased the level of the Housing Goals for calendar years 
2001 through 2003 as follows:
     The Low- and Moderate-Income Housing Goal 
increased to 50 percent;
     The Underserved Areas Housing Goal increased to 
31 percent;
     The Special Affordable Housing Goal increased to 
20 percent;
     The Special Affordable Multifamily Subgoal 
increased to the respective average of one percent of each GSE's total 
mortgage purchases during the period of 1997 Through 1999; and
     Pending establishment of annual Housing Goals 
for the year 2004 and thereafter, the annual Housing Goals for each of 
those years were to be established at 50 percent, 31 percent, and 20 
percent, respectively;
    (2) Made temporary bonus points available for the GSEs' purchases 
of mortgages for small multifamily properties with 5 to 50 units, and, 
above a threshold, for single-family 2- to 4-unit owner-occupied rental 
properties, for calendar years 2001 through 2003 (but not for 
subsequent years, unless determined by HUD);
    (3) Established a temporary adjustment factor (``TAF'') for Freddie 
Mac's purchases of mortgages on large multifamily properties (over 50 
units) for calendar years 2001 through 2003;
    (4) Prohibited high-cost mortgage loans with predatory features 
from receiving Housing Goals credit;
    (5) Established and clarified counting rules under the Housing 
Goals 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) Established procedures for HUD's review of transactions to 
determine appropriate Housing Goal treatment; and
    (7) Made certain definitional and technical corrections to the 
Housing Goals 1995 final rule.
    The Housing Goals 2000 final rule provided for the award of 
temporary bonus points (double credit) toward the Housing Goals for 
both GSEs' mortgage purchases that financed single-family, owner-
occupied 2-4 unit properties and 5-50 unit multifamily properties. 
Under the TAF, the rule also awarded Freddie Mac 1.2 units credit for 
each multifamily unit in property over 50 units.\1\ The Housing Goals 
2000 final rule made clear, however, that both of these measures were 
temporary, intended to encourage the GSEs to ramp up their efforts to 
meet financing needs that had not been well served. During the three 
years for which the temporary bonus points and TAF were established, 
HUD expected the GSEs to develop new, sustainable business 
relationships and purchasing strategies for the targeted needs.
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    \1\ Congress increased the level of the TAF to 1.35 per unit, 
section 1002 of Pub. L. 106-554 (December 21, 2000).
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    At the end of the three years (2001-2003), the Department 
determined not to extend the bonus points or the TAF, after careful 
review of the facts and circumstances of performance under the Housing 
Goals. Data indicate that both GSEs increased their financing of units

[[Page 24230]]

targeted by the bonus points and the TAF.

B. Background: Fannie Mae and Freddie Mac

    Fannie Mae and Freddie Mac were chartered by the Congress as 
government sponsored enterprises. Pursuant to section 301 of the 
Federal National Mortgage Association Charter Act (the ``Fannie Mae 
Charter Act'', 12 U.S.C. 1716, et seq.) and section 301(b) of the 
Federal Home Loan Mortgage Corporation Act (the ``Freddie Mac Charter 
Act'', 12 U.S.C. 1451, et seq.), the GSEs were chartered expressly to:
    (1) Provide stability in the secondary market for residential 
mortgages;
    (2) Respond appropriately to the private capital market;
    (3) Provide ongoing assistance to the secondary market for 
residential mortgages (including activities relating to mortgages on 
housing for low- and moderate-income families involving a reasonable 
economic return that may be less than the return earned on other 
activities) by increasing the liquidity of mortgage investments and 
improving the distribution of investment capital available for 
residential mortgage financing; and
    (4) Promote access to mortgage credit throughout the nation 
(including central cities, rural areas, and other underserved areas) by 
increasing the liquidity of mortgage investments and improving the 
distribution of investment capital available for residential mortgage 
financing.
    As a result of their status as GSEs, Fannie Mae and Freddie Mac 
receive significant explicit benefits that are not enjoyed by fully 
private shareholder-owned corporations in the mortgage market. These 
benefits include:
     Conditional access to a $2.25 billion line of 
credit from the U.S. Treasury (see section 306(c)(2) of the Freddie Mac 
Charter Act and section 304(c) of the Fannie Mae Charter Act);
     Exemption from the securities registration 
requirements of the Securities and Exchange Commission and the States 
(see section 306(g) of the Freddie Mac Charter Act and section 304(d) 
of the Fannie Mae Charter Act); \2\ and
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    \2\ Fannie Mae and Freddie Mac have both announced their 
intention voluntarily to register their common stock with the 
Securities and Exchange Commission (SEC) under section 12(g) of the 
Securities Exchange Act of 1934. Fannie Mae's registration became 
effective March 31, 2003. Freddie Mac has stated that it will 
complete the process of voluntarily registering its common stock 
once it resumes timely reporting of its financial results.
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     Exemption from all State and local taxes except 
property taxes (see section 303(e) of the Freddie Mac Charter Act and 
section 309(c)(2) of the Fannie Mae Charter Act).
    Fannie Mae and Freddie Mac engage in two principal businesses: 
purchasing and otherwise investing in residential mortgages and 
guaranteeing securities backed by residential mortgages.
    While the securities that the GSEs guarantee, and the debt 
instruments they issue, are explicitly not backed by the full faith and 
credit of the United States, and nothing in this proposed rule should 
be construed otherwise, such securities and instruments trade at yields 
only a few basis points over those of U.S. Treasury securities with 
comparable terms. Moreover, these securities also offer yields lower 
than those for securities issued by fully private firms that are more 
highly capitalized but otherwise comparable.
    These factors, in addition to the fact that the market does not 
require that individual GSE securities be rated by a national rating 
agency, evidence that investors perceive that GSE-guaranteed securities 
have inherent advantages over other types of guaranteed securities in 
light of the GSEs' relationship to the Federal Government, including 
their public purposes, their Congressional charters, and the explicit 
benefits provided in their charters as described above.
    Consequently, the GSEs are able to fund their operations at lower 
cost than other private firms with similar financial characteristics. 
In a recent report, the Congressional Budget Office (CBO) estimated 
this funding advantage for the year 2003 to be a $19.6 billion annual 
combined subsidy for both GSEs. Of this amount, CBO estimated that the 
GSEs retained about $6.2 billion, or approximately one-third of the 
subsidy, for their officers and shareholders, while the remainder 
accrued to borrowers.\3\
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    \3\ ``Updated Estimates of the Subsidies to the Housing GSEs'', 
attachment to a letter from Douglas Holtz-Eakin, Director, 
Congressional Budget Office, to the Honorable Richard C. Shelby, 
Chairman, Committee on Banking, Housing, and Urban Affairs, United 
States Senate, April 8, 2004. A related recent study is Wayne 
Passmore, ``The GSE Implicit Subsidy and Value of Government 
Ambiguity,'' Board of Governors of the Federal Reserve System, 
Finance and Economics Discussion Series, FEDS Working Paper 2003-64, 
December 2003.
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C. Secretary's Approach To Regulating the GSEs

    In return for the public benefits they receive, Congress has 
mandated in the GSEs' Charter Acts that the GSEs carry out public 
purposes not required of other private sector entities in the housing 
finance industry.
    Specifically, as indicated, the GSEs' Charter Acts require them to 
continually assist in the efficient functioning of the secondary market 
for residential mortgages, including mortgages for low- and moderate-
income families that may involve a reasonable economic return that is 
less than the economic return on other mortgages. The GSEs also are 
required to promote access to mortgage credit throughout the nation, 
including central cities, rural areas, and other underserved areas. 
These statutory mandates obligate the GSEs to work to ensure that 
everyone in the nation has a reasonable opportunity to enjoy access to 
the mortgage financing benefits resulting from the activities of these 
enterprises.
    The GSEs have achieved an important part of their mission: 
providing stability and liquidity to large segments of the housing 
finance markets. They have also increased their purchases of loans 
affordable to low-income families over the past decade since the 
affordable housing goals were put in place under FHEFSSA. Through 
partnership efforts, new product offerings, and flexible underwriting 
and purchase standards, both enterprises have reached out to 
underserved borrowers, as discussed below in this preamble and in the 
appendices.
    The major premise of this proposed rule is that the GSEs must 
further utilize their entrepreneurial talents and power in the 
marketplace to genuinely ``lead the mortgage finance industry'' and to 
``ensure that citizens throughout the country enjoy access to the 
public benefits provided by these federally related entities.'' (See, 
S. Rep. No. 282, 102d Cong., 2d Sess. 34 (1992).)
    For example, despite the record national homeownership rate of 67.9 
percent in 2002, certain segments of the population clearly have not 
benefited to the same degree that others have from the advantages and 
efficiencies provided by Fannie Mae and Freddie Mac. Problems continue 
to persist for low-income families and certain minorities:
     Lower homeownership rates prevail for certain 
minorities, especially for African-American households (47.9 percent) 
and Hispanics (48.2 percent). These gaps are only partly explained by 
differences in income, age, and other socioeconomic factors. 
Disparities in mortgage lending are reflected in loan denial rates of 
minority groups when compared to white applicants. Denial rates for 
conventional home purchase mortgage loans (excluding manufactured 
housing loans) in 2002 were 19.9 percent for African Americans, 14.0 
percent for Native

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American applicants, 15.1 percent for Hispanic applicants, 8.9 percent 
for Asian applicants, and 7.9 percent for White applicants.
     While Fannie Mae and Freddie Mac cannot be 
expected to solve all these problems, they have both the resources and 
the expertise to improve credit access for low- and moderate-income 
families, minority families, and families in underserved areas. The 
GSEs also have the ability to increase the financing of affordable 
multifamily rental housing. Yet, studies by HUD and others show that 
the GSEs generally have been less active in historically underserved 
markets where there is a need for additional sources of financing to 
address persistent housing and credit needs, and fully private 
companies, operating without the benefits of GSE status, perform better 
in these markets.
     Between 1999 and 2002, special affordable 
housing borrowers accounted for 14.4 percent of Fannie Mae's 
acquisitions of home purchase mortgage loans and 14.5 percent of 
Freddie Mac's acquisitions, at the same time that such mortgages 
accounted for 16.4 percent of home purchase loans originated in the 
overall conventional, conforming market (excluding B&C loans) in 
metropolitan areas.
     During the same period, mortgage purchases on 
properties located in underserved areas accounted for 24.0 percent and 
22.9 percent of Fannie Mae's and Freddie Mac's acquisitions of home 
purchase loans, respectively, and 25.8 percent of home purchase 
mortgages originated in the primary market.
     Both Fannie Mae and Freddie Mac have lagged the 
market in funding first-time homebuyers. Between 1999 and 2002, first-
time homebuyers accounted for 27 percent of each GSE's purchases of 
home purchase loans, compared with 38 percent for home purchase loans 
originated in the conventional conforming market.
    Fannie Mae and Freddie Mac have increased their role in providing 
financing for the low-income end of the mortgage market, but the GSEs 
need to increase their efforts further and demonstrate their capacity 
to be industry leaders. There are ample market opportunities for them 
to do so, including:
     Continuing to introduce new products, and 
providing greater flexibility in their purchase and underwriting 
guidelines, to better address the unique circumstances of low-income 
families;
     Continuing to look for sound investment 
opportunities in those lower-income sectors that have not yet received 
the benefits of mainstream lenders supported by an active secondary 
market;
     Expanding their penetration in the following 
market segments: (1) Borrowers with credit blemishes, or with little 
traditional credit history; (2) first-time homebuyers; (3) Community 
Reinvestment Act (``CRA'')-related loans, which are loans to low- and 
moderate-income populations and neighborhoods in a financial 
institution's assessment area as established under the CRA; (4) the 
rental property market; and (5) the market for rehabilitation loans; 
and
     Increasing their outreach to, and achieving 
greater efficiency in, the above identified markets, as well as in 
other markets that serve low-income and moderate-income families and 
families living in underserved areas.
    Under the present rulemaking, the Department is proposing new, 
higher levels for the Housing Goals, accompanied by subgoals under each 
of the Housing Goals for purchases of home purchase mortgages on owner-
occupied properties in metropolitan areas. (The subgoals are hereafter 
referred to in this rule as ``Home Purchase Subgoal'' or ``Subgoal''.) 
The Department's purpose in proposing higher Housing Goals and in 
establishing new Home Purchase Subgoals in this rulemaking is to 
encourage the GSEs to facilitate greater financing and homeownership 
opportunities for families and neighborhoods targeted by the Housing 
Goals. In developing these regulations, the Department was guided by, 
and re-affirms, the following principles established in the Housing 
Goals 1995 final rule:
    (1) The GSEs should fulfill FHEFSSA's intent that they lead the 
industry in ensuring that access to mortgage credit is made available 
for very low-, low- and moderate-income families and residents of 
underserved areas. HUD recognizes that, to lead the mortgage industry 
over time, the GSEs will have to stretch to reach certain Housing Goals 
and to close gaps between the secondary mortgage market and the primary 
mortgage market for various categories of loans. This approach is 
consistent with the Congress' directive that ``the enterprises will 
need to stretch their efforts to achieve'' the goals (see S. Rep. No. 
282, 102d Cong., 2d Sess., 35 (1992)).
    (2) The Department's role as a regulator is to set broad 
performance standards for the GSEs through the Housing Goals, but not 
to dictate the specific products or delivery mechanisms the GSEs will 
use to achieve a Housing Goal. Regulating two exceedingly large 
financial enterprises in a dynamic market requires that HUD provide the 
GSEs with sufficient latitude to use their innovative capacities to 
determine how best to develop products to carry out their respective 
missions. HUD's regulations are intended to allow the GSEs the 
flexibility to respond quickly to market opportunities. At the same 
time, the Department must ensure that the GSEs' strategies address 
national credit needs, especially as they relate to housing for low- 
and moderate-income families and housing located in underserved 
geographical areas. The addition of Home Purchase Subgoals to the 
regulatory structure provides an additional means of encouraging the 
GSEs' affordable housing activities to address identified, persistent 
credit needs while leaving to the GSEs the specific approaches to 
meeting these needs.
    (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. As noted above, troublesome gaps in 
homeownership remain for minorities even after record growth in 
affordable lending and homeownership during the nineties. Studies 
indicate that, over the next few years, minorities will account for a 
growing share of the families seeking to buy their first home. HUD's 
analyses indicate, however, that Fannie Mae and Freddie Mac account for 
a relatively small share of the minority first-time homebuyer market. 
The GSEs have a responsibility to promote access to capital for 
minorities and others who are seeking their first homes, and to 
demonstrate the benefits of such lending to industry and borrowers 
alike. The GSEs also have an integral role in eliminating predatory 
mortgage lending practices.
    (4) In addition to the GSEs' purchases of single-family home 
mortgages, the GSEs also must continue to assist in the creation of an 
active secondary market for mortgages on multifamily rental housing. 
Affordable rental housing is essential for those families who cannot 
afford to become, or who choose not to become, homeowners. For this 
reason, the GSEs must assist in making capital available to assure the 
continued development of single-family and multifamily rental housing.
    With these principles in mind, the Department is proposing levels 
of the Housing Goals that will bring the GSEs to a position of market 
leadership in a range of foreseeable economic

[[Page 24232]]

circumstances related to the future course of interest rates and 
consequent fluctuations in origination rates on home purchase and 
refinance mortgages--both multifamily and single-family. For each Goal, 
HUD has projected Goal-qualifying percentages of mortgage originations 
in terms of ranges that cover a variety of economic scenarios. The 
objective of HUD's proposed Housing Goals is to bring the GSEs' 
performance to the upper end of HUD's market range estimate for each 
Goal, consistent with the statutory criterion that HUD should consider 
the GSEs' ability to lead the market for each Goal. To enable the GSEs 
to achieve this leadership, the Department is proposing modest 
increases in Housing Goal levels for 2005 which will increase further, 
year-by-year through 2008, to achieve the ultimate objective for the 
GSEs to lead the market under a range of foreseeable economic 
circumstances by 2008. Such a program of staged increases is consistent 
with the statutory requirement that HUD consider the past performance 
of the GSEs in setting the Goals. Staged annual increases in the Goals 
will provide the enterprises with opportunity to adjust their business 
models and prudently try out business strategies, so as to meet the 
required 2008 levels without compromising other business objectives and 
requirements.
    The Department believes that the Home Purchase Subgoals that it 
proposes to establish under this rulemaking are necessary and 
warranted. Increasing homeownership is a national priority. As detailed 
below, the GSEs must apply greater efforts to increasing homeownership 
for low- and moderate-income families, families living in underserved 
areas, and very-low income families and low-income families living in 
low-income areas. The addition of Home Purchase Subgoals to the 
regulatory structure will serve to better focus the GSEs' efforts in a 
clear and transparent manner and better allow the government and public 
alike to monitor the GSEs' efforts in meeting the nation's 
homeownership needs.
    Moreover, the Department reaffirms its view that neither the award 
of bonus points for particular mortgage purchases nor the temporary 
adjustment factor for Freddie Mac's multifamily purchases are 
necessary. At this point, their continued use would only result in 
misleading information about the extent to which the GSEs are, in fact, 
meeting the Housing Goals. The decision to increase the levels of the 
Housing Goals substantially in a staged manner under this proposal and, 
at the same time, not to renew the bonus points or TAF, will ensure 
that the GSEs continue to address the areas formerly targeted by these 
measures. The business relationships that the GSEs established when 
these provisions were in place will be necessary to meet the higher 
Housing Goals.
    The Department's proposals to increase the levels of the Housing 
Goals, and to establish new Home Purchase Subgoals, are predicated upon 
its recognition that the GSEs not only have the ability to achieve 
these Housing Goals but, also, that they are fully consistent with the 
statutory factors established under FHEFSSA. In addition, these 
proposals are supported by the Department's comprehensive analyses of 
the size of the mortgage market, the opportunities available to the 
GSEs, America's unmet housing needs, and identified credit gaps.
    The Department anticipates that, as the GSEs' businesses grow, the 
increased level of the Housing Goals, and the new Home Purchase 
Subgoals, will enable the GSEs to continue to address new markets and 
persistent, unmet housing finance needs.

II. Implementation

A. Affordable Housing Goals

1. Proposed Changes to Housing Goal Levels
    The current Housing Goal levels are 50 percent for the Low- and 
Moderate-Income Housing Goal, 31 percent for the Underserved Areas 
Housing Goal, and 20 percent for the Special Affordable Housing Goal. 
The Special Affordable Housing Goal includes a Subgoal for mortgage 
purchases financing dwelling units in multifamily housing which is 1.0 
percent of the average annual dollar volume of mortgages (both single-
family and multifamily) purchased by the respective GSE in 1997, 1998, 
and 1999$2.85 billion annually for Fannie Mae and $2.11 billion 
annually for Freddie Mac.
    The Department is proposing in this rulemaking to increase the 
Housing Goal levels as follows:
     The proposed level of the Low- and Moderate-
Income Housing Goal is 52 percent in 2005, 53 percent in 2006, 55 
percent in 2007, and 57 percent in 2008;
     The proposed level of the Underserved Areas 
Housing Goal is 38 percent in 2005, 39 percent in 2006, 39 percent in 
2007, and 40 percent in 2008; and
     The proposed level of the Special Affordable 
Housing Goal is 22 percent in 2005, 24 percent in 2006, 26 percent in 
2007, and 28 percent in 2008.
     In addition, HUD is proposing to retain the 
Special Affordable Multifamily Subgoal for calendar years 2005-2008, at 
1.0 percent of their respective average dollar volumes of mortgage 
purchases in calendar years 2000, 2001, and 2002. This would increase 
the dollar value to $5.49 billion annually for Fannie Mae and $3.92 
billion annually for Freddie Mac.
    The Housing Goal percentages that are proposed in this rule reflect 
the application of area median incomes and minority percentages based 
on 2000 Census data, the Census Bureau's specification of census tract 
boundaries for the 2000 Census, and the Office of Management and 
Budget's specification of metropolitan area boundaries based on the 
2000 Census.
2. HUD's Consideration of Statutory Factors in Setting the Housing 
Goals
    As discussed above, HUD considered six statutory factors before it 
decided upon the levels of the Housing Goals being proposed in this 
rulemaking, as described in Section III(B) of this preamble and 
proposed rule amendment numbers 3-5 of this proposed rule. A summary of 
HUD's findings relative to each factor follows. More detailed 
discussion of these points is included in Appendices A, B, and C.
a. Demographic, Economic, and Housing Conditions
    (i) Demographic Trends. Changing population demographics will 
result in a need for the primary and secondary mortgage markets to meet 
nontraditional credit needs, respond to diverse housing preferences and 
overcome information and other barriers that many immigrants and 
minorities face.
    The U.S. Census Bureau has projected that the U.S. population will 
grow by an average of 2.5 million persons per year between 2000 and 
2025, resulting in about 1.2 million new households per year. The aging 
of the baby-boom generation and the entry of the baby-bust generation 
into prime home-buying age will have a dampening effect on housing 
demand. Growing housing demand from minorities, immigrants and non-
traditional homebuyers will help offset declines in the demand for 
housing caused by the aging of the population.
    The continued influx of immigrants will increase the demand for 
rental housing, while those who immigrated during the 1980s and 1990s 
will be in the market for homeownership. Immigrants and minorities--who 
accounted for nearly 40 percent of the growth in the nation's 
homeownership rate over the past five years--will be responsible for 
almost two-thirds of the growth in the number of new households over 
the next ten years.

[[Page 24233]]

    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. By 2025, 
non-family households will make up a third of all households. The role 
of traditional 25-to-34 year-old married, first-time homebuyers in the 
housing market will be smaller in the current decade due to the aging 
of the population. Between 2000 and 2025, the Census Bureau projects 
that the largest growth in households will occur among householders 65 
and over.
    As these demographic factors play out, the overall effect on 
housing demand will likely be continued growth and an increasingly 
diverse household population from which to draw new renters and 
homeowners. A greater diversity in the housing market will, in turn, 
require greater adaptation by the primary and secondary mortgage 
markets.
    (ii) Economic and Housing Conditions. While most other sectors of 
the economy were weak or declining during 2001 and 2002, the housing 
sector showed remarkable strength. The housing market continued at a 
record pace during 2003.
    In 2002, the U.S. economy moved into recovery, with real Gross 
Domestic Product (GDP) growing 2.2 percent, although measures of 
unemployment continued to rise. In October 2002, the average 30-year 
home mortgage interest rate slipped below 6 percent for the first time 
since the mid-1960s. Favorable financing conditions and solid increases 
in house prices were the key supports to record housing markets during 
both 2002 and 2003. By the end of 2003, the industry had set new 
records in single-family permits, new home sales, existing home sales, 
interest rates, and homeownership. Other indicators--total permits, 
starts, completions, and affordability--reached levels that were among 
the highest in the past two decades.
    Over the near term, the Administration's forecast for real GDP 
growth is 4.0 percent for 2004, while the Congressional Budget Office 
(CBO) projects that real GDP will grow at an average rate of 3.2 
percent from 2005 through 2008. The ten-year Treasury rate is projected 
to average 5.5 percent between 2005 and 2008 compared to its average of 
4.6 percent in 2002 and 4.0 percent in 2003. Standard & Poor's expects 
housing starts to average 1.8 million units in 2004-05. Fannie Mae 
projects existing home sales at 6.1 million units for 2004 and 5.8 
million for 2005, compared to their record 6 million level in 2003.
    (iii) Mortgage Market Conditions. Low interest rates and record 
levels of refinancing caused mortgage originations to soar from $2.2 
trillion in 2001 to $2.9 trillion in 2002 and around $3.8 trillion in 
2003. Fannie Mae projects that mortgage originations will drop to $2.4 
trillion in 2004 and $1.7 trillion in 2005, as refinancing returns to 
more normal levels. The volume of home purchase mortgages was $910 
billion to $1.1 trillion between 1999 and 2001 before jumping to $1.2 
trillion in 2002 and $1.3 trillion in 2003. As with housing starts, the 
home purchase origination market is expected to exhibit sustained 
growth.
b. National Housing Needs
    (i) Affordability Problems. Data from the 2000 Census and the 
American Housing Surveys demonstrate that there are substantial housing 
needs among low- and moderate-income families. Many of these households 
are burdened by high homeownership costs or rent payments and, 
consequently, are facing serious housing affordability problems.
    There is evidence of persistent housing problems for Americans with 
the lowest incomes. HUD's analysis of American Housing Survey data 
reveals that, in 2001, 5.1 million households had ``worst case'' 
housing needs, defined as housing costs greater than 50 percent of 
household income or severely inadequate housing among unassisted very-
low-income renter households. Among these households, 90 percent had a 
severe rent burden, 6 percent lived in severely inadequate housing, and 
4 percent suffered from both problems. Among the 34 million renters in 
all income categories, 6.3 million (19 percent) had a severe rent 
burden and over one million renters (3 percent) lived in housing that 
was severely inadequate.
    (ii) Disparities in Housing and Mortgage Markets. Despite the 
strong growth in affordable lending over the past ten years, there are 
families who are not being adequately served by the nation's housing 
and mortgage markets.
    Serious racial and income disparities remain. The homeownership 
rate for minorities is 25 percentage points below that for whites. A 
major HUD-funded study of discrimination in the sales and rental 
markets found that while discrimination against minorities was 
generally down since 1989, it remained at unacceptable levels in 2000. 
The most prevalent form of discrimination against Hispanic and African-
American home seekers observed in the study was Hispanics and African 
Americans being told that housing units were unavailable when non-
Hispanic whites found them to be available. The study also found other 
worrisome trends of discrimination in metropolitan housing markets that 
persisted in 2000, for example, geographical steering experienced by 
African-American homebuyers, and real estate agents who provided less 
assistance in obtaining financing for Hispanic homebuyers than for non-
Hispanic whites.\4\ Racial disparities in mortgage lending are also 
well documented. HUD-sponsored studies of the pre-qualification process 
conclude that African Americans and Hispanics face a significant risk 
of unequal treatment when they visit mainstream mortgage lenders. 
Studies have shown that mortgage denial rates are substantially higher 
for African Americans and Hispanics, even after controlling for 
applicant income and a host of underwriting characteristics, such as 
the credit record of the applicant.\5\
---------------------------------------------------------------------------

    \4\ Margery Austin Turner, All Other Things Being Equal: A 
Paired Testing Study of Mortgage Lending Institutions, The Urban 
Institute Press, April 2002. Appendix A includes further discussion 
of this study.
    \5\ These studies are discussed in section B.1 of Appendix B.
---------------------------------------------------------------------------

    The existence of substantial neighborhood disparities in 
homeownership and mortgage credit is also well documented for 
metropolitan areas. HUD's analysis of 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 these neighborhoods. Studies have also 
documented that mainstream lenders often do not operate in inner-city 
minority neighborhoods, leaving their residents with only high-cost 
lenders as options. Too often, residents of these same neighborhoods 
have been subjected to the abusive practices of predatory lenders.
    These troublesome disparities mostly affect those families 
(minorities and immigrants) who are projected to account for almost 
two-thirds of the growth in the number of new households over the next 
ten years.
    (iii) Single-Family Market: Trends in Affordable Lending and 
Homeownership. Many younger, minority and lower-income families did not 
become homeowners during the 1980s due to the slow growth of earnings, 
high real interest rates, and continued house price increases. Over the 
past ten years, economic expansion, accompanied by low interest rates 
and

[[Page 24234]]

increased outreach on the part of the mortgage industry, has improved 
affordability conditions for these families.
    As this preamble and the appendices note, there has been a 
``revolution in affordable lending'' that has extended homeownership 
opportunities to historically underserved households. The mortgage 
industry, including the GSEs, has offered more customized mortgage 
products, more flexible underwriting, and expanded outreach to low-
income and minority borrowers.
    HMDA data suggest that the industry and GSE initiatives are 
increasing the flow of credit to underserved borrowers. Between 1993 
and 2002, conventional loans to low-income and minority families 
increased at much faster rates than loans to upper-income and non-
minority families. Conventional home purchase originations to African-
Americans more than doubled between 1993 and 2002 and those to Hispanic 
borrowers more than tripled during this period. Home loans to low-
income borrowers and to low-income and high-minority census tracts also 
more than doubled during this period.
    Thus, the 1990s and the early part of the current decade have seen 
the development of a strong affordable lending market. Homeownership 
statistics show similar trends. After declining during the 1980s, the 
homeownership rate has increased every year since 1994, reaching a 
record mark of 67.9 percent in 2002. The number of households owning 
their own home in 2002 was 10.6 million greater than in 1994. Gains in 
homeownership rates have been widespread over the last eight years, 
with the homeownership rate for African American households increasing 
from 42.5 percent to 47.9 percent, for Hispanic households from 41.2 
percent to 48.2 percent, for non-Hispanic white households from 50.8 
percent to 55.1 percent, and for central city residents from 48.5 
percent to 51.8 percent from 1994 to 2002.
    Despite the record gains in homeownership since 1994, a substantial 
gap in the homeownership rate of approximately 25 percentage points 
prevails for African-American and Hispanic households as compared to 
white non-Hispanic households. Studies show that these lower 
homeownership rates are only partly accounted for by differences in 
income, age, and other socioeconomic factors.
    In addition to low income, barriers to homeownership that 
disproportionately affect minorities and immigrants include: lack of 
capital for down payment and closing costs; poor credit history; lack 
of access to mainstream lenders; little understanding of the home 
buying process; a limited supply of modestly priced homes; and 
continued discrimination in housing markets and mortgage lending. These 
barriers are discussed in Appendix A.
    (iv) Single-Family Market: Potential Homeowners. As already noted, 
the potential homeowner population over the next decade will be highly 
diverse, as growing housing demand from immigrants (both those who are 
already in this country and those who are projected to arrive), 
minorities, and non-traditional homebuyers will help to offset declines 
in the demand for housing caused by the aging of the population.
    Fannie Mae reports that, between 1980 and 1995, the number of new 
immigrant owners increased by 1.4 million and, between 1995 and 2010, 
that figure is expected to rise by more than 50 percent to 2.2 million. 
These trends do not depend on the future inflow of new immigrants, as 
immigrants do not, on average, enter the home purchase market until 
they have been in this country for eleven years. Fannie Mae staff note 
that there are enough immigrants already in this country to keep 
housing demand strong for several years.
    Thus, the need for the GSEs and other industry participants to meet 
nontraditional credit needs, respond to diverse housing preferences, 
and to overcome the information barriers that many immigrants face will 
take on added importance. A new or recent immigrant may have no credit 
history or, at least, may not have a credit history that can be 
documented by traditional methods. In order to address these needs, the 
GSEs and the mortgage industry have been developing innovative products 
and seeking to extend their outreach efforts to attract these 
homebuyers, as discussed in Appendix A.
    In addition, the current low homeownership rates in inner cities 
(as compared with the suburbs) also suggest that urban areas may be a 
potential growth market for lenders. As explained in Appendix A, 
lenders are beginning to recognize that urban borrowers and properties 
have different needs than suburban borrowers and properties. CRA-type 
lending will continue to be important in our inner cities.
    Surveys indicate that these demographic trends will be reinforced 
by the fact that most Americans desire, and plan, to become homeowners. 
According to Fannie Mae's 2002 National Housing Survey, Americans rate 
homeownership as the best investment they can make, far ahead of 
401(k)s, other retirement accounts, and stocks. Forty-two percent of 
African-American families reported that they were ``very or fairly 
likely'' to buy a home in the next three years, up from 38 percent in 
1998 and 25 percent in 1997. Among Hispanics and Hispanic immigrants, 
the numbers reached 37 percent and 34 percent, respectively. The survey 
also reported that more than half of Hispanic renters cite 
homeownership as being ``one of their top priorities.''
    In spite of these trends, potential minority and immigrant 
homebuyers see more obstacles to buying a home than does the general 
public. Typically, the primary barriers to homeownership are credit 
issues and a lack of funds for a downpayment and closing costs. 
However, other barriers also exist, such as a lack of affordable 
housing, little understanding of the home buying process, and language 
barriers. Thus, the new group of potential homeowners will have unique 
needs.
    The GSEs can play an important role in tapping this potential 
homeowner population. Along with others in the industry, they can 
address these needs on several fronts, such as expanding education and 
outreach efforts, introducing new products, and adjusting current 
underwriting standards to better reflect the special circumstances of 
these new households. These efforts will be necessary if the 
Administration's goal of expanding minority homeownership by 5.5 
million families by the end of the decade is to be achieved. (In this 
regard, 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.)
    The single-family mortgage market has been very dynamic over the 
past few years, experiencing volatile swings in originations (with the 
1998 and 2001-2003 refinancing waves), witnessing the rapid growth in 
new types of lending (such as subprime lending), incorporating new 
technologies (such as automated underwriting systems), and facing 
serious challenges (such as abusive predatory lending). Fannie Mae and 
Freddie Mac have played a major role in the ongoing changes in the 
single-family market and in helping the industry address the problems 
and challenges that have arisen.
    The appendices to this proposed rule discuss the various roles that 
Fannie Mae and Freddie Mac have played in

[[Page 24235]]

the single-family market. A wide range of topics is examined, including 
the GSEs' automated underwriting technology used throughout the 
industry, their many affordable lending partnerships and underwriting 
initiatives aimed at extending credit to underserved borrowers, their 
development of new targeted low-downpayment products, their entry into 
new markets such as subprime lending, and their attempts to reduce 
predatory lending. As that discussion emphasizes, the GSEs have the 
ability to bring increased efficiencies to a market and to attract 
mainstream lenders into markets. (Readers are referred to Appendices A-
C for further discussion of the GSEs' role in different segments of the 
single-family mortgage market.)
    (v) Multifamily Mortgage Market. The market for financing of 
multifamily apartments has reached record volume. The favorable long-
term prospects for apartments, combined with record low interest rates, 
have kept investor demand for apartments strong and have also supported 
property prices.
    Fannie Mae and Freddie Mac have been among those boosting their 
volumes of multifamily financing and both have introduced new programs 
to serve the multifamily market. Fannie Mae and, especially 
(considering its early withdrawal from the market), Freddie Mac have 
rapidly expanded their presence in the multifamily mortgage market 
under the Housing Goals.
    Freddie Mac has successfully rebuilt its multifamily acquisition 
program, as shown by the increase in its purchases of multifamily 
mortgages: from $27 million in 1992 to $3 billion in 1997 and then to 
approximately $7 billion annually during the next three years (1998 to 
2000), before rising further to $11.9 billion in 2001 and $13.3 billion 
in 2002. Multifamily units accounted for 8.4 percent of all dwelling 
units (both owner and rental) financed by Freddie Mac between 1999 and 
2002.
    Concerns regarding multifamily capabilities no longer constrain 
Freddie Mac's performance with regard to the Housing Goals. Although 
Fannie Mae never withdrew from the multifamily market, it has stepped 
up its activities in this area substantially, with multifamily 
purchases rising from $3.0 billion in 1992 to $9.4 billion in 1999, and 
$18.7 billion in 2001, and then declining slightly to $18.3 billion in 
2002. Multifamily units accounted for 9.2 percent of all dwelling units 
(both owner and rental) financed by Fannie Mae between 1999 and 2002.
    The increased role of Fannie Mae and Freddie Mac in the multifamily 
market has major implications for the Low- and Moderate-Income Housing 
and Special Affordable Housing Goals, since high percentages of 
multifamily units have affordable-level rents and can count toward one 
or both of these Housing Goals. However, the potential of the GSEs to 
lead the multifamily mortgage industry has not been fully developed. 
The GSEs' purchases between 1999 and 2002 accounted for only 30 percent 
of the multifamily units that received financing during this period. 
Certainly there are ample opportunities and room for expansion of the 
GSEs' share of the multifamily mortgage market.
    The GSEs' size and market position between loan originators and 
mortgage investors make them the logical institutions to identify and 
promote needed innovations and to establish standards that will improve 
market efficiency. As their role in the multifamily market continues to 
grow, the GSEs will have the knowledge and market presence to push 
simultaneously for standardization and for programmatic flexibility to 
meet special needs and circumstances, with the ultimate goal of 
increasing the availability and reducing the cost of financing for 
affordable and other multifamily rental properties.
    The long-term outlook for the multifamily rental market is 
sustained, moderate growth, based on favorable demographics. The 
minority population, especially Hispanics, provides a growing source of 
demand for affordable rental housing. ``Lifestyle renters'' (older, 
middle-income households) are also a fast-growing segment of the rental 
population.
    At the same time, the provision of affordable housing units will 
continue to challenge suppliers of multifamily rental housing as well 
as policy makers at all levels of government. Low incomes, combined 
with high housing costs, define the difficult situation of millions of 
renter households. Housing cost reductions are constrained by high land 
prices and construction costs in many markets. Regulatory barriers at 
the state and local level have an enormous impact on the development of 
affordable rental housing. Government action--through land use 
regulation, building codes, and occupancy standards--is a major 
contributor to high housing costs.
    Since the early 1990s, the multifamily mortgage market has become 
more closely interconnected with global capital markets, although not 
to the same degree as the single-family mortgage market. Loans on 
multifamily properties are still viewed as riskier by some than 
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 in loan performance to economic conditions than may be 
experienced for single-family mortgages.
    There is a need for an ongoing 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. Small multifamily properties, and multifamily properties 
with significant rehabilitation needs, have historically experienced 
difficulty gaining access to mortgage financing, and the flow of 
capital into multifamily housing for seniors has been historically 
characterized by volatility. The GSEs can play a role in promoting 
liquidity for multifamily mortgages and increasing the availability of 
long-term, fixed rate financing for these properties.
c. GSEs' Past Performance and Effort Toward Achieving the Housing Goals
    Both Fannie Mae and Freddie Mac have improved their affordable 
housing loan performance over the past ten years, since the enactment 
of FHEFSSA and HUD's establishment in 1993 of the Housing Goals. 
However, the GSEs' mortgage purchases have generally lagged, and not 
led, the overall primary market in providing financing for affordable 
housing to low- and moderate-income families and underserved borrowers 
and their neighborhoods, indicating that there is more that the GSEs 
can do to improve their performance.
    (i) Performance on the Housing Goals. The year 2001 was the first 
year under the higher levels of the Housing Goals established in the 
Housing Goals 2000 final rule. Both GSEs met all three Housing Goals in 
2001 and 2002. Their performance is discussed further in a later 
section of this preamble.
    (ii) The GSEs' Efforts in the Home Purchase Mortgage Market. The 
Appendices include a comprehensive analysis of each GSE's performance 
in funding home purchase mortgages for borrowers and neighborhoods 
targeted by the three Housing Goals--special affordable and low- and 
moderate-income borrowers and underserved areas. The GSEs' role in the 
first-time homebuyer market is also analyzed. Because homeownership 
opportunities are integrally tied to the ready availability of 
affordable home purchase

[[Page 24236]]

loans, the main findings from that analysis are provided below:
     Both Fannie Mae and Freddie Mac have increased 
their purchases of affordable loans since the Housing Goals were put 
into effect, as indicated by the increasing share of their business 
going to the three Goals-qualifying categories. Between 1992 and 2002, 
the special affordable share of Fannie Mae's purchases of home purchase 
loans in metropolitan areas more than doubled, rising from 6.3 percent 
to 16.3 percent, while the underserved areas share increased more 
modestly, from 18.3 percent to 26.7 percent. The figures for Freddie 
Mac are similar. The special affordable share of Freddie Mac's business 
rose from 6.5 percent to 15.8 percent, while the underserved areas 
share increased more modestly, from 18.6 percent to 25.8 percent.
     While both GSEs improved their performance, they 
have lagged the primary market in providing affordable loans to low-
income borrowers and underserved neighborhoods. Freddie Mac's average 
performance, in particular, fell far short of market performance during 
the 1990s. Fannie Mae's performance was better than Freddie Mac's 
during 1993-2002, as well as during 1996-2002, which covers the period 
under HUD's currently-defined Housing Goals. For the 1996-2002 period, 
21.7 percent of Freddie Mac's purchases financed properties in 
underserved neighborhoods, compared with 23.5 percent of Fannie Mae's 
purchases, 24.9 percent of loans originated by depository institutions 
(i.e., banks and savings associations), and 25.4 percent of loans 
originated in the conventional conforming market (i.e., loans below the 
conforming loan limit that are not government insured or guaranteed).
     During the more recent 1999-to-2002 period, both 
Fannie Mae and Freddie Mac fell significantly below the market in 
funding special affordable loans. During that period, special 
affordable loans accounted for 14.4 percent of Fannie Mae's purchases, 
14.5 percent of Freddie Mac's purchases, and 16.4 percent of loans 
originated in the market. Thus, the ``Fannie Mae-to-market'' ratio was 
0.88 (14.4/16.4), as was the ``Freddie Mac-to-market'' ratio. Between 
1999 and 2002, underserved area loans accounted for 24.0 percent of 
Fannie Mae's purchases, 22.9 percent of Freddie Mac's purchases, and 
25.8 percent of loans originated in the market, resulting in a ``Fannie 
Mae-to-market'' ratio of 0.93 and a ``Freddie Mac-to-market'' ratio of 
0.89.
     Both GSEs, but particularly Fannie Mae, markedly 
improved their performance during 2001 and 2002, the first two years 
under HUD's higher Housing Goal targets. Evaluating their activity 
relative to the market depends, to some extent, on the way in which GSE 
activity is measured. Under the purchase-year approach for measuring 
GSE activity (in which characteristics of mortgages purchased by a GSE 
in a particular year, including mortgages originated in prior years, 
are compared with characteristics of mortgages originated just within 
the year), Fannie Mae's average performance during 2001 and 2002 
matched the market in the low- and moderate-income category and 
approached the market in the special affordable and underserved areas 
categories. For example, during 2001 and 2002, loans for special 
affordable borrowers accounted for 15.6 percent of Fannie Mae's 
purchases, compared with 16.0 percent of market originations. As 
explained in Appendix A, conclusions about Fannie Mae's recent 
performance relative to the market depend significantly on whether GSE 
activity is measured on a ``purchase year'' basis or on an 
``origination year'' basis (in which characteristics of mortgages 
originated in a particular year are compared with characteristics of 
mortgages that were originated in that year and purchased by a GSE in 
that year or a subsequent year). Fannie Mae matched the market in the 
low- and moderate-income category in 2002, using the more consistent 
``origination year'' approach. (See Appendix A for further discussion.)
     While Freddie Mac has consistently improved its 
performance relative to the market, it continued to lag the market in 
all three Housing Goal categories during 2001 and 2002. For example, 
during 2001 and 2002, loans financing properties in underserved areas 
accounted for 24.1 percent of Freddie Mac's purchases, compared with 
25.9 percent of market originations.
     Appendix A to this rule compares the GSEs' 
funding of first-time homebuyers with that of primary lenders in the 
conventional conforming market. Both Fannie Mae and Freddie Mac lag the 
market in funding first-time homebuyers, and by a rather wide margin. 
Between 1999 and 2002, first-time homebuyers accounted for 27 percent 
of each GSE's purchases of home loans, compared with 38 percent for 
home loans originated in the conventional conforming market.
     The GSEs account for a small share of the market 
for important groups such as minority first-time homebuyers. 
Considering all mortgage originations (both government and 
conventional) between 1999 and 2001, it is estimated that the GSEs 
purchased only 14 percent of all loans originated for African-American 
and Hispanic first-time homebuyers, or one-third of their share (42 
percent) of all home purchase loans originated during that period. 
Considering conventional conforming originations during the same time 
period, it is estimated that the GSEs purchased only 31 percent of 
loans for African-American and Hispanic first-time homebuyers, or about 
one-half of their share (57 percent) of all home purchase loans in that 
market. A large percentage of the lower-income loans purchased by the 
GSEs had relatively low loan-to-value ratios and consequently high down 
payments, which may explain the GSEs' limited role in the first-time 
homebuyer market.
d. Size of the Mortgage Market That Qualifies for the Housing Goals
    The Department estimates the size of the conventional, conforming 
market for loans that would qualify under each Housing Goal category. 
The market estimates (which reflect 2000 Census data and geography) are 
as follows:
     51-57 percent for the Low- and Moderate-Income 
Housing Goal
     24-28 percent for the Special Affordable Housing 
Goal
     35-40 percent for the Underserved Areas Housing 
Goal (based on 2000 Census geography).
    These market estimates exclude the B&C (subprime loans that are not 
A minus grade) portion of the subprime market. The estimates, expressed 
as ranges, allow for economic and market affordability conditions that 
are more adverse than recent conditions. The market estimates are based 
on several mortgage market databases such as Home Mortgage Disclosure 
Act (HMDA) and American Housing Survey data. The Department's estimates 
of the size of the conventional mortgage market for each Housing Goal 
are discussed in detail in Appendix D.
    The GSEs have substantial room for growth in serving the affordable 
housing mortgage market. The Department estimates that the two GSEs' 
mortgage purchases accounted for 49 percent of the total (single-family 
and multifamily) conventional, conforming mortgage market between 1999 
and 2002. In contrast, GSE purchases comprised 42 percent of the low- 
and moderate-income market, 41 percent of the underserved areas market, 
and a still smaller 35 percent of the special affordable market. Thus, 
58-65 percent of the Goals-qualifying markets have not yet been touched 
by the GSEs.
    The GSEs' presence in mortgage markets for rental properties, where 
much of the nation's affordable housing

[[Page 24237]]

is concentrated, is below that in the single-family-owner market. The 
GSEs' share of the rental market (including both single-family and 
multifamily) was only 30 percent during the 1999-to-2002 period. 
Obviously, there is room for the GSEs to increase their presence in the 
single-family rental and multifamily rental markets.
    Table 1 summarizes the Department's findings regarding GSE 
performance relative to HUD's market estimates for 1999-2002, market 
projections for 2005-2008, and the proposed Housing Goal levels for 
2005-2008.
BILLING CODE 4210-27-P

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    The analysis reflected in Table 1 is based on 2000 Census data on 
area median incomes and minority concentrations, with the metropolitan 
area boundaries specified in June 2003 by the Office of Management and 
Budget. This affects the market percentages for all three Housing 
Goals, as well as the figures on area median incomes and minority 
percentage figures that will be used to measure GSE performance on the 
Housing Goals beginning in 2005. For example, expressing the 
Underserved Areas Housing Goal in terms of 2000 Census data adds 
approximately 5 percentage points to the Housing Goal and market 
levels, compared with analysis using 1990 Census data with Metropolitan 
Statistical Areas as defined prior to 2000.
    The GSEs' baseline performance figures in Table 1 exclude the 
effects of the bonus points for small multifamily and single-family 2-4 
unit owner-occupied properties and the Temporary Adjustment Factor for 
Freddie Mac which were applied in official scoring toward the Housing 
Goals in 2001-2003. The Department did not extend these adjustments 
beyond 2003.
    Table 1 reveals several features of HUD's proposed Housing Goals. 
First, the high end of the range for HUD's 2005-2008 market projections 
is the same as or within one percentage point of the 1999-2002 average 
of the market levels for the Housing Goals.
    Second, it is evident from this table that the proposed initial new 
level for the Special Affordable Housing Goal (22 percent) is below the 
low end of HUD's projected market range for 2005-2008 (24 percent). The 
proposed initial level of the Low- and Moderate-Income Housing Goal (52 
percent) is at the low-end of HUD's market estimate range.
    Third, the proposed initial Underserved Areas Housing goal level is 
more consistent than the current Goal level with the market range now 
projected by HUD for the Housing Goals using 2000 Census data.
    Fourth, the GSEs' performance on all of the Housing Goals was 
significantly below the market average for 1999-2002. The higher 
Housing Goals are intended to move the GSEs closer to or within the 
market range for 2005 and to the upper end of the market range 
projection by 2008.
    An analysis of the GSEs' mortgage purchases by property type shows 
that they have had much less presence in the ``Goals-rich'' rental 
segments of the market, as compared with the ``less-Goals-rich'' owner 
segment of the market. As shown in Figure 1, GSE mortgage purchases 
represented only 27 percent of single-family rental units financed 
between 1999 and 2002, and only 30 percent of multifamily units 
financed during that time period--both figures are much lower than 
their 57 percent market share for single-family owner-occupied 
properties. (Figure 2 provides unit-level detail comparing the GSEs' 
purchases with originations in the conventional conforming market.) 
Typically, about 90 percent of rental units in single-family rental and 
multifamily properties qualify for the Low- and Moderate-Income Housing 
Goal, compared with about 44 percent of owner units. Corresponding 
figures for the Special Affordable Housing Goal are approximately 60 
percent of rental units and 16.4 percent of owner units. Thus, one 
reason that the GSEs' performance under the Low- and Moderate-Income 
Housing and Special Affordable Housing Goals has fallen short of HUD's 
market estimates is that the GSEs have had a relatively small presence 
in the two rental market segments, notwithstanding that these market 
segments are important sources of affordable housing and important 
components in HUD's market estimates.

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    In the overall conventional conforming mortgage market, rental 
units in single-family properties and in multifamily properties are 
expected to represent approximately 30 percent of the overall mortgage 
market, 45 percent of the units that collateralize mortgages qualifying 
for the Low- and Moderate-Income Housing Goal, and 60 percent of the 
units that collateralize mortgages qualifying for the Special 
Affordable Housing Goal. Yet between 1999 and 2002, units in such 
properties accounted for only 17 percent of the GSEs' overall 
purchases, 31 percent of the GSEs' purchases meeting the Low- and 
Moderate-Income Housing Goal, and 44 percent of the GSEs' purchases 
meeting the Special Affordable Housing Goal.\6\ The continuing weakness 
in GSE purchases of mortgages on single-family rental and multifamily 
properties is a significant factor explaining the shortfall between GSE 
performance and that of the primary mortgage market.
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    \6\ These percentage shares are computed from Table A.30 in 
Appendix A. Note that B&C loans are excluded from these data.
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e. Ability of the GSEs To Lead the Industry
    An important factor in determining the overall Housing Goal level 
is the ability of the GSEs to lead the industry in making mortgage 
credit available for Housing Goals-qualifying populations and areas.
    The legislative history of FHEFSSA reflects Congress's strong 
concern that the GSEs need to do more to benefit low- and moderate-
income families and residents of underserved areas that lack access to 
credit. (See, e.g., S. Rep. 102-282 at 34.) The Senate Report on 
FHEFSSA emphasized that the GSEs should ``lead the mortgage finance 
industry in making mortgage credit available for low- and moderate-
income families.'' (See S. Rep. 102-282 at 34.)
    Thus, FHEFSSA specifically requires that HUD consider the ability 
of the GSEs to lead the industry in establishing the level of the 
Housing Goals. FHEFSSA also clarified the GSEs' responsibility to 
complement the requirements of the CRA (see section 1335(a)(3)(B) of 
FHEFSSA, 12 U.S.C. 4565(a)(3)(B)), and fair lending laws (see section 
1325 of FHEFSSA, 12 U.S.C. 4545) in order to expand access to capital 
to those historically underserved by the housing finance market.
    While leadership may be exhibited through the GSEs' introduction of 
innovative products, technology, and processes, and through their 
establishment of partnerships and alliances with local communities and 
community groups, leadership must always involve increasing the 
availability of financing for homeownership and affordable rental 
housing. Thus, the GSEs' obligation to ``lead the industry'' entails 
leadership in facilitating access to affordable credit in the primary 
market for borrowers at different income levels, and with different 
housing needs, as well as in underserved urban and rural areas.
    Because the GSEs' market presence varies significantly by property 
type, the Department examined whether the GSEs have led the industry in 
three different market sectors served by the GSEs: single-family-owner, 
single-family rental (those with at least one rental unit and no more 
than four units in total), and multifamily rental.
    The GSEs' purchases between 1999 and 2002 financed almost 60 
percent of the approximately 35 million owner-occupied units financed 
in the conventional conforming market during that period. The GSEs' 
state-of-the-art technology, staff resources, share of the total 
conventional conforming market, and financial strength strongly suggest 
that they have the ability to lead the industry in making home purchase 
credit available for low-income families and underserved neighborhoods. 
From the analysis in Appendices A-D, it is clear that the GSEs are able 
to improve their performance and lead the primary market in financing 
Housing Goals-qualifying home purchase mortgages.
    As discussed in Appendix A, there are a wide variety of 
quantitative and qualitative indicators that demonstrate that the GSEs 
have ample, indeed robust, financial strength to improve their 
affordable lending performance. For example, the combined net income of 
the GSEs has risen steadily over the last 15 years, from $677 million 
in 1987 to $10.4 billion in 2002. 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.
    The GSEs have been much less active in providing financing for the 
multifamily rental housing market. Between 1999 and 2002, the GSEs 
financed 2.2 million multifamily dwelling units, which represented 
approximately 30 percent of the 7.0 million multifamily dwelling units 
that were financed in the conventional market during this period. Thus, 
the GSEs' share of the multifamily mortgage market was just slightly 
over one-half of their share of the market for mortgages on single-
family owner-occupied properties.
    Similarly, HUD estimates that Fannie Mae and Freddie Mac accounted 
for only 27 percent of single-family rental units financed between 1999 
and 2002. In this case, the GSEs' presence in the single-family rental 
mortgage market was less than one-half their presence in the market for 
mortgages on single-family owner-occupied properties.
    Clearly there is room for the GSEs to increase their presence in 
the single-family rental and multifamily rental markets. As explained 
above, these markets are an important source of low- and moderate-
income housing since these units qualify for the Housing Goals in a 
greater proportion than do single-family owner-occupied properties. 
Thus, Fannie Mae and Freddie Mac can improve their performance on each 
of the three Housing Goals if they increase their purchases of 
mortgages on rental properties.
    As discussed in Section B below with respect to the Home Purchase 
Subgoals, the GSEs should be able to lead the market for single-family 
owner-occupied properties. The GSEs are already dominant players in 
this market which, unlike the rental markets, is their main business 
activity. However, as already discussed, research studies conducted by 
HUD and academic researchers conclude that the GSEs have not been 
leading this market, but have historically lagged behind the primary 
market in financing owner-occupied housing for low-income families, 
first-time homebuyers, and housing in underserved areas.
f. Need To Maintain the Sound Financial Condition of the GSEs
    Based on HUD's economic analysis and review by the Office of 
Federal Housing Enterprise Oversight, the Department has concluded that 
the proposed levels of the Housing Goals will not adversely affect the 
sound financial condition of the GSEs. Further discussion of this issue 
is found in the economic analysis that accompanies this rule.
3. Other Factors Considered by HUD in Proposing the New Housing Goals
    HUD considered a number of additional factors in connection with 
its proposal to establish the new Housing Goals described in this rule. 
These additional factors also were relevant to HUD's proposal to 
establish the new Home Purchase Subgoals. The Department describes 
these additional factors in Section B of this preamble (see, ``Home 
Purchase Subgoals'' immediately below).

[[Page 24242]]

B. Home Purchase Subgoals

    Given the need for, and the Administration's emphasis on, 
increasing homeownership opportunities, including those for low- and 
moderate-income and minority borrowers, HUD is proposing also to set 
Subgoals for GSE mortgage purchase activities to increase financing 
opportunities for low- and moderate-income, underserved, and special 
affordable borrowers who are purchasing single-family homes.
    Specifically, the Department is proposing Subgoals for home 
purchase loans that qualify for the Housing Goals. The purpose of the 
Home Purchase Subgoals is to assure that the GSEs focus on financing 
home purchases for the homeowners targeted by the Housing Goals. The 
Department believes that the establishment of Home Purchase Subgoals 
will place the GSEs in an important leadership position in the Housing 
Goals categories, while also facilitating homeownership. The GSEs have 
years of experience in providing secondary market financing for single-
family properties and are fully capable of exerting such leadership.
    The focus of these Subgoals on home purchase loans meeting the 
Housing Goals will also help address the racial and income disparities 
in homeownership that exist today. Although minority homeownership has 
grown, the homeownership rate for African Americans and Hispanic 
families is still approximately 25 percentage points below that for 
non-Hispanic white families. The focus of the Subgoals on home purchase 
will also increase the GSEs' support of first-time homebuyers, a market 
segment where they have lagged primary lenders.
    The Department's analysis suggests that the GSEs have not been 
leading the market in purchasing single-family, owner-occupied loans 
that qualify for the Housing Goals. Although Fannie Mae's average 
performance during 2001 and 2002 matched the market in the low- and 
moderate-income category, and approached the market in the special 
affordable and underserved areas categories, the Department's analysis 
shows that there is ample room for both Fannie Mae and Freddie Mac to 
improve their performance in purchasing home loans that qualify for 
these Housing Goals, particularly in important market segments such as 
the minority, first-time homebuyer market.
    As detailed in Appendix A, evidence suggests that there is a 
significant population of potential homebuyers who are likely to 
respond well to increased homeownership opportunities produced by 
increased GSE purchases in this area. Immigrants and minorities, in 
particular, are expected to be a major source of future homebuyers. 
Furthermore, studies indicate the existence of a large untapped pool of 
potential homeowners among the rental population. Indeed, the GSEs' 
recent experience with new outreach and affordable housing initiatives 
confirms the existence of this potential.
    Thus, the Department is proposing to establish Subgoals for home 
purchase loans that qualify for the three Housing Goals to encourage 
the GSEs to take a leadership position in creating homeownership 
financing opportunities within the categories that Congress expressly 
targeted with the Housing Goals.
1. Proposed Home Purchase Subgoals
    Under this proposed rule, performance on the Home Purchase Subgoals 
would be calculated as Housing Goal-qualifying percentages of the GSEs' 
total purchases of mortgages that finance purchases of single-family, 
owner-occupied properties located in metropolitan areas, based on the 
owner's income and the location of the property. Specifically, for each 
GSE the following proposed Subgoals would apply. (A ``home purchase 
mortgage'' is defined as a residential mortgage for the purchase of an 
owner-occupied single-family property.)
     45 percent of home purchase mortgages purchased 
by the GSE in metropolitan areas must qualify under the Low- and 
Moderate-Income Housing Goal in 2005, with this share rising to 46 
percent in 2006 and 47 percent in both 2007 and 2008;
     33 percent of home purchase mortgages purchased 
by the GSE in metropolitan areas must qualify under the Underserved 
Areas Housing Goal in 2005, with this share rising to 34 percent in 
2006 and 35 percent in both 2007 and 2008; and
     17 percent of home purchase mortgages purchased 
by the GSE in metropolitan areas must qualify under the Special 
Affordable Housing Goal in 2005, with this share rising to 18 percent 
in 2006 and 19 percent in both 2007 and 2008.

Counting toward the Subgoals will be in terms of numbers of mortgages, 
not numbers of units. This is consistent with the basis of reporting in 
HMDA data, which were HUD's point of reference in establishing the 
Subgoal levels. HMDA data are reported in terms of numbers of 
mortgages.
    These proposed Subgoals are shown in Table 2, along with 
information on what the GSEs' performance on the Subgoals would have 
been if they had been in effect for 1999-2002 (under the proposed 
scoring rules for 2005-08). Table 2 also presents HUD's estimates of 
the average shares of mortgages on owner-occupied single-family 
properties in metropolitan areas that were originated in 1999-2002 that 
would have qualified for these Subgoals.
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2. HUD's Determinations Regarding the Home Purchase Subgoal Levels
    Current law does not require that HUD consider the statutory 
factors set forth in FHEFSSA prior to establishing or setting the level 
of Subgoals. FHEFSSA authorizes HUD to establish Subgoals within the 
Low- and Moderate-Income Housing Goal and the Underserved Areas Housing 
Goal. However, under current law, Subgoals under these two Goals are 
not enforceable. Also, FHEFFSA authorizes HUD to establish Subgoals 
within the Special Affordable Housing Goal and these Subgoals are 
enforceable. The Administration has proposed, as part of GSE regulatory 
reform, that Congress authorize HUD to establish a separate Home 
Purchase Goal that would include enforceable components. Pending the 
enactment of any such legislation, HUD is proposing the Subgoals 
described in this proposed rule under its current statutory authority.
    The following sections provide an overview of HUD's reasons for 
establishing the Subgoals, which are detailed in the Appendices.
    (a) The GSEs Have the Ability to Lead the Market. The GSEs have the 
ability to lead the primary market for mortgages on single-family 
owner-occupied properties, which are the ``bread-and-butter'' of their 
business. Both GSEs have long experience in the home purchase mortgage 
market, and therefore there is no issue of the degree to which they 
have penetrated the market, as there is with the single-family rental 
and multifamily mortgage markets. In addition, because the Subgoals 
focus on homeownership opportunities and, thus, do not include 
refinance loans, there is no issue regarding potentially large year-to-
year changes in refinance mortgage volumes, which affect the magnitude 
of the denominator in calculating performance percentages under the 
Housing Goals, as experienced in the heavy refinance years of 1998 and 
2001-2003.
    Both GSEs have not only been operating in the single-family owner 
mortgage market for years, they have been the dominant players in that 
market, funding 57 percent of mortgages on single-family owner-occupied 
residences financed between 1999 and 2002. As discussed in Section G of 
Appendix A, their underwriting guidelines are industry standards and 
their automated mortgage systems are widely used in the mortgage 
industry.
    Through their new low-downpayment products and various underwriting 
initiatives, and through their various partnership and outreach 
efforts, the GSEs have shown that they have the capacity to operate in 
underserved neighborhoods and to reach out to lower-income families 
seeking to buy a home. Both Fannie Mae and Freddie Mac have the staff 
expertise and financial resources to make the extra effort to lead the 
primary market in funding single-family-owner mortgages for low- and 
moderate-income, special affordable, and underserved area mortgages.
    (b) The GSEs Have Lagged the Market. Even though the GSEs have the 
ability to lead the market, they have not done so under the Housing 
Goals. As noted earlier, 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 funding loans that 
qualify for the three Housing Goals. While the GSEs have significantly 
improved their performance, they have lagged the primary market in 
funding Housing Goals-qualifying loans since FHEFSSA was enacted in 
1992.
    As also noted above, the type of improvement needed to meet the new 
Subgoals was demonstrated by Fannie Mae during 2001 and 2002, when its 
average performance matched the primary market in funding low- and 
moderate-income families and approached the market in funding special 
affordable families and properties in underserved areas.
    (c) Disparities in Homeownership and Credit Access Remain. There 
remain troublesome disparities in our housing and mortgage markets, 
even after the ``revolution in affordable lending'' and the growth in 
homeownership that has taken place since the mid-1990s. The 
homeownership rate for African-American and Hispanic households remains 
25 percentage points below that of white households. In 2002, the 
mortgage denial rate for African-American borrowers was over twice that 
for white borrowers, even after controlling for the income of the 
borrower.
    There is growing evidence that inner city neighborhoods are not 
always being adequately served by mainstream lenders. Some have 
concluded that a dual mortgage market has developed in our nation, with 
conventional mainstream lenders serving mainly white families living in 
the suburbs and FHA and subprime lenders serving minority families 
concentrated in inner city neighborhoods. In addition to the 
unavailability of mainstream lenders, families living in high-minority 
neighborhoods generally face many additional hurdles, such as lack of 
cash for a downpayment, credit problems, and discrimination.
    Immigrants and minorities are projected to account for almost two-
thirds of the growth in the number of new households over the next ten 
years. As emphasized throughout this preamble and the Appendices, 
changing population demographics will result in a need for the primary 
and secondary mortgage markets to meet nontraditional credit needs, 
respond to diverse housing preferences and overcome information and 
other barriers that many immigrants and minorities face. The GSEs must 
increase their efforts towards providing financing for these families.
    (d) There Are Ample Opportunities for the GSEs to Improve Their 
Performance in the Home Purchase Market. Home purchase loans that 
qualify for the Housing Goals are available for the GSEs to purchase, 
which means they can improve their performance and lead the primary 
market in purchasing loans for lower-income borrowers and properties in 
underserved areas. Three indicators of this have already been 
discussed.
    First, the affordable lending market has shown an underlying 
strength over the past few years that is unlikely to vanish (without a 
significant increase in interest rates or a decline in the economy). 
Since 1999, the shares of the home purchase market accounted for by the 
three Housing Goal categories are as follows: 16.4 percent for special 
affordable, 32.3 for underserved areas, and 44.2 percent for low- and 
moderate-income.
    Second, market share data reported in Section G of Appendix A show 
that over half of newly-originated loans that qualify for the Housing 
Goals are not purchased by the GSEs. As noted above, the situation is 
even more extreme for special sub-markets, such as the minority first-
time homebuyer market where the GSEs have only a minimal presence. In 
terms of the overall mortgage market (both conventional and 
government), the GSEs funded only 24 percent of all first-time 
homebuyers and 17 percent of minority first-time homebuyers between 
1999 and 2001. Similarly, during the same period, the GSEs funded only 
40 percent of first-time homebuyers in the conventional conforming 
market, and only 33 percent of minority first-time homebuyers in that 
market.
    Finally, the GSEs' purchases that can count toward the Subgoal are 
not limited to new mortgages that are originated in the current 
calendar year. The GSEs can purchase loans from the substantial, 
existing stock of affordable loans held in lenders' portfolios, after

[[Page 24245]]

these loans have seasoned and the GSEs have had the opportunity to 
observe their payment performance. In fact, based on Fannie Mae's 
recent experience, the purchase of seasoned loans appears to be one 
useful strategy for purchasing Housing Goals-qualifying loans.
    The current low homeownership rate of minorities and others living 
in inner cities suggests that there will be considerable growth in the 
origination of CRA loans in urban areas. For banks and thrifts, selling 
their CRA originations will free up capital to make new CRA loans. As a 
result, the CRA market segment provides an opportunity for the GSEs to 
expand their affordable lending programs. As explained in Appendix A, 
Fannie Mae and Freddie Mac have already started developing programs to 
purchase CRA-type loans on a flow basis as well as after they have 
seasoned.
    While the GSEs can choose any strategy for leading the market, this 
leadership role can likely be accomplished by building on the many 
initiatives and programs that the enterprises have already started, 
including: (1) Their outreach to underserved markets and their 
partnership efforts that encourage mainstream lenders to move into 
these markets; (2) their incorporation of greater flexibility into 
their purchase and underwriting guidelines, (3) their development of 
new products for borrowers with little cash for a downpayment and for 
borrowers with credit blemishes or non-traditional credit histories; 
(4) their targeting of important markets where they have had only a 
limited presence in the past, such as the markets for minority first-
time homebuyers; (5) their purchases of both newly-originated and 
seasoned CRA loans; and (6) their use of automated underwriting 
technology to qualify creditworthy borrowers that would have been 
deemed not creditworthy under traditional underwriting rules.
    The experience of Fannie Mae and Freddie Mac in the subprime market 
indicates that they have the expertise and experience to develop 
technologies and new products that allow them to enter new markets in a 
prudent manner. Given the innovativeness of Fannie Mae and Freddie Mac, 
other strategies will be available as well. In fact, a wide variety of 
quantitative and qualitative indicators suggest that the GSEs have the 
expertise, resources and financial strength to improve their affordable 
lending performance enough to lead the home purchase market for special 
affordable, low- and moderate-income, and underserved areas loans. The 
recent improvement in the affordable lending performance of the GSEs, 
and particularly Fannie Mae, further demonstrates the GSEs' capacity to 
lead the home purchase market.
3. Counting of Mortgages for the Home Purchase Subgoals
    The Department is proposing to amend Sec. 81.15 to add a new 
paragraph (i) that would clarify that the procedures in Sec. 81.15 
generally govern the counting of home purchase mortgages toward the 
Home Purchase Subgoals in Secs. 81.12, 81.13 and 81.14. The new 
paragraph provides, however, that the numerator and denominator for 
purposes of counting performance under the Subgoals are comprised of 
numbers of home purchase mortgages in metropolitan areas, rather than 
numbers of dwelling units. Paragraph (i) also provides that, for 
purposes of addressing missing data or information for each Subgoal, 
the procedures in Sec. 81.15(d) shall be implemented using numbers of 
home purchase mortgages in metropolitan areas and not single-family 
owner-occupied dwelling units. Finally, the new paragraph provides that 
where a single home purchase mortgage finances the purchase of two or 
more owner-occupied units, the mortgage shall count once toward each 
Subgoal that applies to the GSE's mortgage purchase.

C. Definition of Underserved Area for Rural Areas

    The rule proposes to change the definition of ``Underserved Area'' 
for purposes of determining whether a ``Rural Area'' is an 
``Underserved Area.'' The definition of a ``Rural Area'' that is an 
``Underserved Area'' would be a census tract, Federal or State American 
Indian Reservation or tribal or individual trust land, or the balance 
of a census tract excluding the area within any Federal or State 
American Indian reservation or tribal or individual trust land, having: 
(i) A median income at or below 120 percent of the greater of the State 
non-metropolitan median income or nationwide non-metropolitan median 
income and a minority population of 30 percent or greater, or (ii) a 
median income at or below 95 percent of the greater of the State non-
metropolitan median income or nationwide non-metropolitan income.
    This is essentially the same definition that was established in 
HUD's Housing Goals 2000 final rule, except that census tracts, rather 
than counties, are the basic spatial unit for determining whether an 
area is underserved. Because HUD's proposed amendment would establish 
uniform standards for determining whether a rural area qualifies as an 
underserved area, there is no longer any need to distinguish 
underserved areas located in New England from underserved areas in 
other areas of the country. For this reason, the Department is 
proposing to eliminate from the definition of ``Underserved area'' the 
current distinct regulatory treatment for New England.

D. Adequacy of Borrower Income Data

    Accurate measurement of the GSEs' performance under the three 
Housing Goals depends on the completeness of data on borrower income 
(or, in the case of non-owner-occupied units, the rent) and property 
location. As between these two, property location is reported by the 
GSEs on most of the mortgages they purchase--a less than one percent 
incidence of missing or incomplete geographical data between 2000 and 
2002 for each GSE. The incidence of missing borrower income data has 
been greater--on the order of several percentage points each year.
    One reason for the increase in missing income data is the recent 
increased use of mortgages for which the borrower is not required to 
provide income information. For some of these mortgages the borrower 
presents information on assets but not income because of circumstances 
that make assets easier to document. Other mortgages are originated 
entirely on the basis of a credit report, property appraisal, and cash 
for the downpayment. These mortgages typically require relatively large 
downpayments and often require a higher interest rate than fully 
documented mortgages.
    The Housing Goals 2000 Final Rule provided that the GSEs may 
exclude from the denominator owner-occupied units lacking mortgagor 
income data which are located in low-or moderate-income census tracts, 
i.e., tracts whose median income is no greater than the median income 
of the metropolitan area or, for properties located outside of 
metropolitan areas, the larger of the median incomes of the county or 
the statewide non-metropolitan area (see 24 CFR 81.15(d)).\7\
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    \7\ For rental units, the 2000 Housing Goals Final Rule also 
established counting rules which allow the GSEs to estimate rents or 
exclude units from the denominator when rent data are missing. See 
24 CFR 81.15(e)(6)(i) on the rules applicable to multifamily units 
and 24 CFR 81.15(e)(6)(ii) on the rules for single-familly rental 
units.
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    In view of the increasing use of loans made without obtaining 
income information from the borrower, there is a question whether HUD's 
existing counting rules for missing-data

[[Page 24246]]

situations are adequately reliable and create no more than a negligible 
statistical bias in the GSEs' Housing Goals performance figures 
relative to the values that they would have if complete income data 
could be obtained, and whether a more precise method for imputing 
incomes could be employed. In order to inform HUD's consideration of 
this issue, HUD requests comments from the public on the following 
question: Would it be desirable for HUD to have a standard, 
econometrically-based method for imputing the income distribution of 
mortgages purchased by each GSE that lack income data, based on known 
characteristics of the loan and the tract? Income distribution 
information would be needed that shows proportions of units that are in 
the very-low-income range (below 60 percent of area median), low- but 
not very-low income (60-80 percent) and moderate income (80-100 
percent), to support estimating proportions of missing-data loans for 
both the Low- and Moderate-Income Housing Goal and the Special 
Affordable Housing Goal. For example, the mortgage amount as a 
percentage of average loan amounts in the tract, or home prices in the 
local market, might be used in the estimation process. Depending on the 
type of methodology that is developed, such a procedure might be 
applied on a geographical level from census tracts up to the United 
States as a whole. In the latter case one national estimate would be 
created for the proportion of owner-occupied units lacking income data 
that qualify for each Goal, for each GSE.

E. Possible Changes to GSE Counting Rules

    FHEFSSA establishes housing goals for the GSEs' purchases of 
mortgages for low- and moderate-income families, special affordable 
housing (very-low income families and low-income families in low-income 
areas) and families with properties in underserved areas (see sections 
1332-1334) in order to ensure that the GSEs increase the availability 
to these borrowers of the lower cost financing available through the 
GSEs. With increasing frequency, the GSEs have entered into large-scale 
transactions with lenders involving seasoned mortgages to achieve the 
housing goals. It is possible that some of these transactions may 
include broad buyback arrangements with the seller for the transaction.
    HUD's rules at 24 CFR 81.2 define a ``mortgage purchase'' to mean a 
transaction in which a GSE bought or otherwise acquired with cash or 
other thing of value a mortgage for its portfolio or securitization. 
HUD counts the GSEs' performance under the Housing Goals pursuant to 
HUD's counting rules under 24 CFR 81.15 and 81.16. Both the counting 
rules and definitions are designed to ensure consistency with the 
statute and its purposes of increasing the availability of financing 
for homeowners targeted by the Goals.
    In light of HUD's interest in ensuring that transactions are 
appropriately counted under the law and in accordance with its 
purposes, HUD asks whether the definition of ``mortgage purchase'' in 
Sec. 81.2 should be revised in the final rule. Should HUD, for example, 
further define ``transactions in which a GSE bought or otherwise 
acquired with cash or other thing of value, a mortgage for its 
portfolio or for securitization'' for purposes of ensuring appropriate 
counting of large transactions and, if so, how? HUD also asks what 
changes, if any, to HUD's regulations (including, but not limited to, 
changes to the counting rules at Secs. 81.15 and 81.16) are warranted 
to ensure that the GSEs' large scale transactions further the 
requirements and purposes of the Housing Goals. Do commenters believe 
HUD's current rules are sufficiently specific to determine which 
seasoned mortgage transactions, including large-scale transactions, are 
substantially equivalent to mortgage purchases? If commenters believe 
the rules are not sufficiently specific, how should the rules be 
changed?

F. Verification and Enforcement of GSE Data Integrity--Revised 
Sec. 81.102

1. Summary
    The Department's ability to monitor effectively the GSEs' 
performance under the Housing Goals, and otherwise to carry out its 
regulatory functions, depends in large measure upon the submission of 
accurate, complete and current data, information and reports by Fannie 
Mae and Freddie Mac. The GSEs' Charter Acts require Fannie Mae and 
Freddie Mac to submit data, information and reports on Housing Goals 
performance under subsections 307(e) and (f) of the Freddie Mac Charter 
Act and subsections 309(m) and (n) of the Fannie Mae Charter Act. 
FHEFSSA also requires the GSEs to submit reports (see section 1327 of 
FHEFSSA, 12 U.S.C. 4547), and other authorities necessitate that the 
GSEs submit information for HUD's review (see, for example, section 
1325 of FHEFSSA, 12 U.S.C. 4545).
    HUD's current GSE regulations at 24 CFR 81.102 make clear that HUD 
may verify the accuracy and completeness of data, information and 
reports submitted by the GSEs, but as a practical matter most 
verification of data, information and reports occurs well after their 
submission to the Department, which renders this current verification 
provision a useful but not immediately effective regulatory control. 
Indeed, in the case of data and information needed to calculate Housing 
Goals performance, verification occurs only after such Housing Goals 
performance has been calculated. Likewise, the information provided in 
reports ordinarily would not be verified until well after the report is 
submitted.
    For these reasons, the Department has concluded that, to ensure the 
integrity of the report(s), data submission(s) and other information 
provided to the Department, additional measures are necessary. 
Accordingly, as described more fully below, the Department is proposing 
to revise Sec. 81.102 to: (1) Re-codify in paragraph (a) the existing 
authority under Sec. 81.102 which authorizes HUD to independently 
verify the accuracy and completeness of data, information and reports 
provided by the GSEs; (2) establish in paragraph (b) certification 
requirements for the submission of the GSEs' Annual Housing Activities 
Report (AHAR) and for such other report(s), data submission(s) or 
information for which certification is requested in writing by HUD; (3) 
codify in paragraph (c) HUD's process for handling errors, omissions or 
discrepancies in the GSEs' current year-end data submissions (including 
the AHAR); (4) clarify in paragraph (d) that HUD may exercise its 
Housing Goal counting authority by adjusting Goals performance for a 
current year by deducting miscredits from a previous year caused by 
errors, omissions or discrepancies in a GSE's prior year data 
submissions (including the AHAR); and (5) clarify in paragraph (e) that 
HUD may take enforcement action against the GSEs under section 1341 of 
FHEFSSA (12 U.S.C. 4581) and section 1345 of FHEFSSA (12 U.S.C. 4585), 
as implemented by subpart G (``Procedures for Actions and Review of 
Actions'') of HUD's regulations at 24 CFR part 81 for the submission of 
non-current, inaccurate or incomplete information or data.
2. Background
    Under section 1336 of FHEFSSA (12 U.S.C. 4566), HUD is required to 
monitor and enforce compliance with the Housing Goals. The GSEs each 
submit quarterly information and semi-annual loan-level data on their 
mortgage purchases pursuant to their Charters and the requirements of 
24 CFR part 81. To fulfill its monitoring responsibility,

[[Page 24247]]

HUD conducts two types of verification procedures for this data and 
information.
    The first procedure is a recalculation process whereby HUD, using 
the loan-level data provided by the GSEs, reconstructs each GSE's 
Housing Goals performance for the reporting period by applying current 
counting rules and Housing Goal eligibility criteria to the data 
provided. These recalculations are conducted immediately upon receipt 
of the GSEs' loan-level data. If adjustments in performance data are 
necessary because a GSE has improperly applied counting rules, or HUD 
discovers some other error during the recalculation process, the 
Department makes these adjustments at the time recalculation work is 
done and calculates the GSE's official Housing Goals performance based 
on the adjustment. HUD publishes the GSEs' official Housing Goal 
performance figures for the year on its Web site, usually within six 
months of the end of the reporting year, and includes these figures in 
other published HUD management and performance reports.
    The second type of verification procedure consists of performance 
reviews, including audit procedures, which occur after the reporting 
year is closed and Housing Goal results have been announced. 
Performance reviews evaluate the GSEs' internal controls and related 
business practices relative to the accuracy, completeness, and 
appropriateness of the information and data that were provided to HUD 
and upon which Housing Goals performance was based. These reviews also 
include sampling tests of source documents and data testing to 
determine the accuracy of reported data and to review the transactions 
a GSE relied upon to develop the data. Due to the timing of these 
reviews, which can begin no earlier than the close of a reporting year, 
and the extensive sampling work involved, it may take up to 24 months 
from the date of the report under review for HUD to develop its 
findings on a reporting year.
3. Independent Verification Authority--Sec. 81.102(a)
    As indicated, the Department is first proposing to recodify 
existing Sec. 81.102 as paragraph (a) in the revised Sec. 81.102. 
Paragraph (a) would retain HUD's current regulatory authority to 
independently verify the accuracy and completeness of data, information 
and reports submitted by a GSE, thereby retaining the Department's 
authority to conduct on-site verifications, and to carry out 
performance reviews.
    As the Department noted in the preamble to its Housing Goals 1995 
final rule, the authority to verify information is derived in part from 
section 1321 of FHEFSSA (12 U.S.C. 4541), which accords the Secretary 
``general regulatory power over each enterprise.'' The Secretary's 
general regulatory power is in addition to the enumerated powers 
conferred on the Secretary by FHEFSSA and the GSEs' Charter Acts. The 
Department also regards verification authority as necessary and 
incidental to its authority under section 1336 of FHEFSSA to monitor 
and enforce compliance with the Housing Goals.
    Accordingly, the rule would retain in paragraph (a) of Sec. 81.102 
its existing regulatory authority to independently verify the accuracy 
and completeness of data, information and reports submitted by a GSE.
4. Certification--Sec. 81.102(b)
    The Department is proposing in this rule to require the GSEs to 
provide a certification in connection with their AHARs submitted under 
sections 309 (m) and (n) of the Fannie Mae Charter Act or section 
307(e) and (f) of the Freddie Mac Charter Act, as applicable, that, 
among other things, the AHAR is current, complete and does not contain 
any untrue statement of a material fact as detailed below. The rule 
would also make clear that the Department could require such 
certification for such other report(s), data submission(s) or 
information for which certification is requested in writing by HUD.
    Because of the post facto nature of performance reviews, such 
reviews cannot be the sole means of preventing the submission of 
incorrect data. HUD believes that certification requirements better 
serve the end of assuring the integrity of data, information and 
report(s) (including the AHAR) submitted at the outset and such 
requirements are consistent with current practice.
    Pursuant to its regulatory authority, HUD has in the past, with 
regard to certain specific matters, required that Fannie Mae and 
Freddie Mac certify the accuracy, currency and completeness of 
information and data submitted to the Department. Other financial 
regulators, such as the Office of Federal Housing Enterprise Oversight 
(OFHEO), the Securities and Exchange Commission (SEC), and the Federal 
Deposit Insurance Corporation (FDIC) require similar certifications to 
ensure the accuracy of information submitted to them. Similarly as the 
GSEs register their stock with the SEC, they will be required to 
certify financial statements and other information submitted to the 
SEC. Moreover, the recently enacted Sarbanes-Oxley Act of 2002 (P.L. 
107-204, approved July 30, 2002) requires certification as a means of 
ensuring corporate accuracy in, and accountability for, the financial 
information provided by a corporation to its regulators and to the 
public (see 15 U.S.C. 7241).
    The Department's proposal requiring the GSEs to submit a 
certification in connection with their AHARs and such other report(s), 
data submission(s) or information for which certification is requested 
in writing by the Department, is reasonably related to the Department's 
performance of its statutory duties under FHEFSSA and is well supported 
by both statutory and regulatory authority.
    Specifically, as stated, section 1321 of FHEFSSA grants the 
Secretary ``general regulatory power'' over the GSEs and directs the 
Secretary to ``make such rules and regulations as shall be necessary 
and proper'' to carry out the purposes of FHEFSSA and the GSEs' Charter 
Acts. The Supreme Court has repeatedly held that a grant to an agency 
of ``general regulatory authority'' extends to the agency those 
unenumerated powers that are ``reasonably related to the purposes of 
the enabling legislation.'' (See Mourning v. Family Publications 
Service, Inc., 411 U.S. 356, 369 (1973) (quoting Thorpe v. Housing 
Authority of City of Durham, 393 U.S. 268, 280-281 (1969).) This 
standard has been accepted by every Federal Court of Appeals. (See, 
e.g., Action on Smoking and Health v. CAB, 699 F.2d 1209, 1212 (D.C. 
Cir. 1983).)
    Moreover, under section 1336 of FHEFSSA, the Secretary is expressly 
mandated by Congress to ``monitor and enforce [the GSEs'] compliance 
with the housing goals established under * * * [FHEFSSA]'' and the 
GSEs' Charter Acts require the GSEs to submit a report to designated 
Congressional committees and to the Secretary ``on [their] activities 
under subpart B of * * * [FHEFSSA].'' (See section 309(n) of the Fannie 
Mae Charter Act, 12 U.S.C. 1723a(n); section 307(f) of the Freddie Mac 
Charter Act, 12 U.S.C.1456(f).) Also, section 309(n)(2)(L) of the 
Fannie Mae Charter Act and section 307(f)(2)(L) of the Freddie Mac 
Charter Act expressly grant the Secretary the discretion to require the 
GSEs to submit in their AHARs ``any other information that the 
Secretary considers appropriate'' with respect to their activities 
under subpart B of FHEFSSA. (Emphasis added.)
    The Secretary also is accorded by statute a number of fact finding

[[Page 24248]]

functions. These include the authority to require reports (see section 
1327 of FHEFSSA), to gather data from the GSEs on their mortgage 
purchases (see sections 309(m) and (n) of the Fannie Mae Charter Act 
and sections 307(e) and (f) of the Freddie Mac Charter Act), to monitor 
and enforce compliance with the housing goals (see section 1336 of 
FHEFSSA), and to issue subpoenas (see section 1348 of FHEFSSA). These 
functions in turn permit the Secretary to make factual determinations, 
such as: (1) Whether a GSE is complying with the Housing Goals; (2) 
whether a GSE has made a good-faith effort to comply with a housing 
plan; and (3) whether a GSE has submitted the mortgage information and 
reports required under sections 309(m) and (n) of the Fannie Mae 
Charter Act, sections 307(e) and (f) of the Freddie Mac Charter Act and 
section 1327 of FHEFSSA. The Secretary also is charged with the 
authority to initiate enforcement actions upon determining that the law 
has been violated.
    Since all of these functions necessitate the submission of current, 
complete and accurate information, data and reports, a certification 
requirement is necessary to carrying out these functions.
    For these reasons, the Department is proposing to amend Sec. 81.102 
by adding a new paragraph (b) that requires the GSE senior officer 
responsible for submitting to HUD the AHAR and such other report(s), 
data submission(s) or information for which a certification is 
requested in writing by HUD (referred to in the rule as the ``GSE 
Certifying Official'') to submit a certification in connection with 
such documents.
    The rule would require that the GSE certification provide: (1) The 
GSE Certifying Official has reviewed the particular AHAR, other 
report(s), data submission(s) or information; (2) to the best of the 
GSE Certifying Official's knowledge and belief, the particular AHAR, 
other report(s), data submission(s) or information are current, 
complete and do not contain any untrue statement of a material fact; 
(3) to the best of the GSE Certifying Official's knowledge and belief, 
the AHAR or other report(s), data submission(s) and information fairly 
present in all material respects the GSE's performance, as required to 
be reported by section 309(m) or (n) of the Fannie Mae Act, section 
307(e) or (f) of the Freddie Mac Charter Act, or other applicable legal 
authority; and (4) to the best of the GSE Certifying Official's 
knowledge and belief, the GSE has identified in writing any areas in 
which the GSE's particular AHAR, other report(s), data submission(s) or 
information may differ from HUD's written articulations of its counting 
rules including, but not limited to, the regulations under 24 CFR part 
81, and any other areas of ambiguity.
5. Adjustment To Correct Current Year-End Errors, Omissions or 
Discrepancies--Sec. 81.102(c)
    The Department is proposing to add a new paragraph (c) to 
Sec. 81.102 that would largely codify its administrative practice 
regarding errors, omissions or discrepancies it discovers relative to 
HUD's regulations and/or other guidance concerning how current year 
data are reported by a GSE and provide the GSEs with a mechanism upon 
which to comment.
    Under this paragraph, the Department is proposing to notify the GSE 
initially by telephone or e-mail transmission of errors, omissions or 
discrepancies in current year-end data reporting relative to HUD's 
regulations and other guidance. The GSE has five business days to 
respond to such notification. If each error, omission or discrepancy is 
not resolved to the Department's satisfaction, HUD will then notify the 
GSE in writing and seek clarification or additional information to 
correct the error, omission or discrepancy. The GSE will have 10 
business days from the date of HUD's written notice to respond in 
writing to the request (or such longer time as HUD may establish, not 
to exceed 30 business days). If the GSE fails to submit a written 
response to HUD within the 10-day (or longer) time period, or if HUD 
determines that the GSE's written response fails to explain or correct 
the error, omission or discrepancy in its current year-end reported 
data submissions (including the AHAR) to HUD's satisfaction, the 
Department will determine the appropriate adjustments to the numerator 
and the denominator to calculate performance under the applicable 
Housing Goal(s) and/or Subgoal(s). The Department's determination may 
involve excluding the unit(s) or mortgage(s) from the numerator and 
including them in the denominator of the applicable Housing Goal(s) 
and/or Subgoal(s). The Department may also pursue additional 
enforcement actions against the GSE under Sec. 81.102(e), if it 
determines that such action is warranted.
    The Department's legal authority to implement this provision also 
is based upon its general regulatory power over each enterprise 
pursuant to section 1321 of FHEFSSA and its explicit statutory 
authority under section 1336 of FHEFSSA to monitor and enforce the 
GSE's compliance with the Housing Goals. In addition, this provision is 
predicated upon the Department's existing regulatory authority under 24 
CFR 81.102 to independently verify the accuracy and completeness of 
data, information and reports submitted by a GSE.
6. Adjustment To Correct Prior Year Reporting Errors--Sec. 81.102(d)
    The Department is proposing to add a new paragraph (d) to 
Sec. 81.102 that would provide for effective regulatory oversight and 
enforcement when it determines that a GSE has, in a prior year, 
improperly calculated its performance under one or more Housing Goals 
and/or Subgoals as a result of errors, omissions or discrepancies in 
its data submissions (including its AHAR).
    As background for this proposal, notably unlike financial reporting 
where results are cumulative from year to year and the results of 
adjustments in prior years carry forward to the current year, the GSEs' 
Housing Goal performance reports (the Annual Housing Activity Reports) 
impact only the current reporting year. This means that, unlike 
financial reporting, if corrections are not made prior to release of 
HUD's official performance data for the reporting year, any subsequent 
corrections to that data for that year are likely to go unnoticed by 
the public and policy makers.
    In addition, if a correction is such that it would have caused 
failure under a Housing Goal that was previously reported as having 
been achieved, HUD's enforcement remedies under section 1336 of FHEFSSA 
would have little relevance as they only require a GSE to submit a 
housing plan to ensure compliance with the Housing Goals in the current 
or subsequent calendar year.
    For these reasons, it is not practical to correct overstatements in 
performance data that were reported in previous years by adjusting 
performance for a prior year. On the other hand, adjustments to current 
year performance are an effective means of assuring accuracy in 
counting under the Housing Goals in a manner that makes the public 
aware of the adjustment. Accordingly, the Department is proposing to 
add a new paragraph (d) to Sec. 81.102 that would enable it to reduce a 
GSE's current year credit toward its Housing Goals performance based on 
errors, omissions or discrepancies that the Department discovers in a 
GSE's prior year's data submissions (including its AHAR).
    This procedure, to be known as an ``adjustment to correct prior 
year reporting errors, omissions or discrepancies,'' would provide the

[[Page 24249]]

Department with a mechanism for ensuring the continued accuracy, 
completeness and currency of each GSE's performance results. The 
Department anticipates that the procedure would be used infrequently. 
Even so, given the increasing complexity of each GSE's business as well 
as the complexity of many of the transactions that the GSEs use to meet 
their Housing Goals, the Department believes that the proposed 
procedure is both reasonable and necessary. Should its use become 
necessary, the proposed procedure will provide a means for HUD to 
effect corrections in a manner that is appropriate and obvious to those 
who track the GSEs' performance annually, and it will help to ensure 
that the GSEs continue to exercise appropriate diligence in their 
Housing Goals reporting.
    The Department's proposed procedure would provide that the 
Department may adjust a GSE's current year Housing Goal performance to 
correct for any overstatement in Housing Goals reporting discovered in 
the course of performance reviews or otherwise of any previous year's 
Annual Housing Activity Report that were the result of errors, 
omissions or discrepancies. Should the Department determine that an 
adjustment to current year data for a prior year error, omission or 
discrepancy in Housing Goal reporting is warranted, the Department 
would communicate its initial findings and determinations in writing to 
the GSE within 24 months of the end of the relevant reporting year. The 
GSE would have 30 days from the date of HUD's initial letter to respond 
in writing, with supporting documentation, to contest the 
determination. Within 60 days of the date of the GSE's written 
response, the Department would issue a final determination letter to 
the GSE (unless HUD determines that good cause exists to extend this 
period for an additional 30 days.)
    If the GSE fails to submit a written response to HUD within the 30-
day period, or if the Department otherwise determines that an 
adjustment is warranted, the GSE would be required to reflect an 
adjustment in its Annual Housing Activity Report for the current year, 
as directed by HUD. The adjustment would be reflected in the GSE's 
year-end performance under the applicable Housing Goal(s) or Subgoal(s) 
for the current reporting year by deducting the number of units or 
mortgages that HUD has determined were erroneously counted in a 
previous year from the numerator (but not the denominator) for the 
relevant Housing Goal or Subgoal.
    The Department proposes that this provision will become effective 
upon publication of the final rule for reporting periods occurring on 
or after the rule's effective date. It will not be retroactive to 
reporting periods that preceded publication of the final rule. Should 
any adjustment cause a failure under a Housing Goal in the current 
year, then current year Housing Goals performance would be subject to 
enforcement under sections 1336, 1341, and 1345 of FHEFSSA, and subpart 
G of part 81.
    As noted, section 1321 of FHEFSSA grants the Secretary ``general 
regulatory power over each enterprise'' which includes the authority to 
``make such rules and regulations as shall be necessary and proper to 
ensure that [Part 2, Subtitle A, of FHEFSSA] and the purposes of [the 
GSEs' Charter Acts] are accomplished.'' The Secretary's general 
regulatory power under section 1321 is in addition to the specific 
enumerated powers conferred on the Secretary by FHEFSSA and the GSEs' 
Charter Acts.
    Moreover, also as noted, section 1336 of FHEFSSA--under which the 
Secretary is mandated by Congress to ``monitor and enforce compliance 
with the housing goals established under sections 1332, 1333, and 1334, 
as provided in this section * * *''--expressly authorizes HUD to 
establish guidelines to measure the extent of compliance with the 
Housing Goals. Section 1336 further authorizes HUD to ``assign full 
credit, partial credit, or no credit toward achievement of the Housing 
Goals to different categories of mortgage purchase activities of the 
enterprises, based on such criteria as the Secretary deems 
appropriate.'' (Emphasis added.)
    The Department's proposal to grant only partial credit to a GSE in 
its current year performance report to correct for a prior year's error 
constitutes an appropriate counting criterion to assure the accuracy of 
data used to assess GSE performance under the Housing Goals.
7. Additional Enforcement Provisions--Sec. 81.102(e)
    Finally, the rule would make clear that a GSE's submission of data, 
information, or reports required by section 307(e) or (f) of the 
Freddie Mac Charter Act, section 309(m) or (n) of the Fannie Mae 
Charter Act or subpart E of part 81 that are incomplete, not current, 
or contain an untrue statement of material fact shall be regarded by 
the Department as equivalent to failing to submit such data, 
information or reports. For such a non-submission, the Department may 
bring under subpart G of part 81 an order to cease and desist and/or to 
levy civil money penalties in connection with a GSE's failure to comply 
with its statutory obligations under its Charter Act and FHEFSSA.

III. Discussion of Proposed Regulatory Changes

A. Subpart A--General

Section 81.2--Definitions
    The proposed regulation would change several current definitions in 
Sec. 81.2, and add a new definition to this section. First, to conform 
HUD's regulations to changes in data collection practices made by the 
Office of Management and Budget (OMB), HUD's proposed regulation would 
change the current definitions of ``Metropolitan area'' and 
``Minority.'' Second, the proposed regulation would modify the current 
definition of ``Underserved area.'' Finally, the proposed regulation 
would add a new definition for ``Home Purchase Mortgage'' consistent 
with this proposal.
    ``Metropolitan area''--The proposed regulation would change the 
current definition of ``metropolitan area'' to remove the term 
``primary metropolitan statistical area (``PMSA'')'' since this is a 
term that is no longer used by the Office of Management and Budget 
(OMB) in defining ``metropolitan area.'' See Office of Management and 
Budget, Standards for Defining Metropolitan and Micropolitan 
Statistical Areas, 65 FR 82228-82238 (December 27, 2000).
    ``Minority''--The proposed regulation would also change the 
definition of the term ``minority'' in light of significant changes in 
reporting conventions for race and ethnicity, in accordance with OMB 
guidance.
    Currently, ``minority'' is defined in HUD regulations as ``any 
individual who is included within any one'' of the following list of 
racial and ethnic categories (emphasis added). The proposed regulation 
would change the definition of minority to ``any individual who is 
included within any one or more'' of the following list of racial and 
ethnic categories (emphasis added). This change is consistent with a 
decision made by OMB in 1997, revising federal data classification 
standards on race and ethnicity, to allow individuals, in federal data 
collection, to identify themselves in more than one category. See 
Office of Management and Budget, Revisions to the Standards for the 
Classification of Federal Data on Race and Ethnicity, 62 FR 58781-58790 
(October 30, 1997).
    Also, consistent with OMB determinations, the proposed regulation 
would change the current definition of ``minority'' so that: (1) 
``American

[[Page 24250]]

Indian'' would be defined to include persons with origins in any of the 
original peoples of South and Central America; (2) ``Asian or Pacific 
Islander'' would be divided into separate categories--''Asian,'' which 
would include examples of countries of origin, and ``Pacific Islander'' 
which would be included in a new definition with ``Native Hawaiian'' 
(which would include ``peoples having origins in any of the original 
peoples of Hawaii, Guam, Samoa, or other Pacific Islands;'' (3) 
``African-American'' would be changed to ``Black or African American;'' 
and (4) ``Hispanic'' would be changed to ``Hispanic or Latino.''
    ``Underserved area''--As discussed more fully above (see section 
II.C), the proposed regulation would change the definition of 
``Underserved area'' for purposes of determining whether a ``Rural 
area'' is an underserved area.
    ``Home Purchase Mortgage''--Consistent with the proposed 
establishment of Home Purchase Subgoals, the proposed regulation would 
add a definition for ``Home Purchase Mortgage,'' which would be defined 
to mean a residential mortgage for the purchase of an owner-occupied 
single-family property.

B. Subpart B--Housing Goals

1. Background
    The Department is required to establish, by regulation, annual 
Housing Goals for each GSE. The Goals include a Low- and Moderate-
Income Housing Goal, a Special Affordable Housing Goal, and a Central 
Cities, Rural Areas, and Other Underserved Areas Housing Goal (the 
Underserved Areas Housing Goal). Section 1331(a) of FHEFSSA requires 
HUD to establish these Goals in a manner consistent with sections 
301(3) of the Fannie Mae Charter Act and 301(b)(3) of the Freddie Mac 
Charter Act, which require the GSEs ``to provide ongoing assistance to 
the secondary market for residential mortgages (including * * * 
mortgages on housing for low- and moderate-income families involving a 
reasonable economic return that may be less than the return earned on 
other activities).'' Under section 1331(c) of FHEFSSA, HUD may, by 
regulation, adjust any Housing Goal from year to year.
    In October 2000, HUD established Housing Goals for the GSEs for 
2001-2003, revising and restructuring the Goals that had been in effect 
for 1996-2000. The current Housing Goal levels, which were in place for 
2001-2003 and extended through 2004 without the bonus points and 
Temporary Adjustment Factor, are:
     A Low- and Moderate-Income Housing Goal, which 
focuses on mortgages on housing for families with incomes no greater 
than area median income (as defined by HUD),\8\ and which is set at 50 
percent of total units financed by each of the GSEs' mortgage 
purchases;
---------------------------------------------------------------------------

    \8\ 24 CFR 81.2.
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     An Underserved Areas Housing Goal, which focuses 
on mortgages on properties located in ``underserved areas,'' defined as 
low-income and/or high-minority census tracts and rural counties 
(excluding high-income, high-minority tracts), and which is set at 31 
percent of total units financed by each of the GSEs' mortgage purchases 
in 2001-2004;
     A Special Affordable Housing Goal, which focuses 
on mortgages on housing for very low-income families and low-income 
families living in low-income areas, and which is set at 20 percent of 
total units financed by each of the GSEs' mortgage purchases in 2001-
2004; and
     A Special Affordable Multifamily Subgoal, which 
focuses on mortgages on housing for very low-income families and low-
income families living in low-income areas, in multifamily properties 
(defined as properties with five or more units), and which is set at a 
fixed amount of 1.0 percent of the average total dollar volume of 
mortgages purchased by each GSE in the years 1997, 1998, and 1999. This 
formula results in a Subgoal of special affordable multifamily mortgage 
purchases totaling $2.85 billion per year for Fannie Mae and $2.11 
billion per year for Freddie Mac for each calendar year from 2001 
through 2004.
    These Housing Goals, excluding the Special Affordable Multifamily 
Subgoal, share common characteristics: (1) The Goal levels are the same 
for both GSEs; (2) they are percentage based Goals defined in terms of 
percentages of housing units financed; and (3) one unit may qualify for 
one or more Goals. In addition, under the current regulation, Goals 
were established based on consideration of the statutory factors and 
set for a three-year period from 2001 through 2003 to allow the GSEs 
time to develop long-range strategies.
    A key factor in determining the level of the Goals was and is the 
estimated size of the conventional market for each Goal. This 
determination is discussed above and in Appendix D. HUD estimates that 
the low- and moderate-income market accounted for 54-59 percent of all 
mortgages originated during the 1997 to 2002 period, and for 54-55 
percent in 2001 and 2002. The special affordable market accounted for 
26-30 percent for 1997-2002, and 26-27 percent for 2001-2002. The 
underserved areas market defined in terms of 1990 Census data and pre-
2003 metropolitan area boundaries accounted for 31-35 percent for 1997-
2002 and 32-33 percent for 2001-2002. With 2000 Census data and the 
metropolitan area boundaries established in June, 2003, these figures 
become 37-40 percent for 1999-2002 and 37-39 percent for 2001-2002.
    In accordance with FHEFSSA, HUD has re-estimated the market shares 
of the mortgages in the primary conventional market that would qualify 
for each of the GSEs' Housing Goals for the years 2005 through 2008.\9\ 
HUD estimates that for the years 2005 through 2008 the low- and 
moderate-income share of the conventional market will be 51-57 percent, 
the underserved areas share of the market will be 35-40 percent, and 
the special affordable share will be 24-28 percent. Appendix D, 
``Estimating the Size of the Conventional Conforming Market for Each 
Housing Goal,'' provides an extensive analysis of the Department's 
market share estimates.
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    \9\ The Goal-qualifying market shares are estimated for the 
years 2005-2008 under several projections about the relative sizes 
of the single-family and multifamily markets. Numerous sensitivity 
analyses that consider alternative market and economic conditions 
are examined in Appendix D.
---------------------------------------------------------------------------

    The gaps between the current Goal levels and HUD's latest market 
estimates indicate that the Goals should be higher and that there are 
ample opportunities available for the GSEs to meet the new initial 
Goals in 2005 as they institute measures to ensure that they will 
attain the increased goal levels in 2006-2008. Moreover, HUD's new 
market estimates allow for more adverse economic and affordability 
conditions than recently experienced. For example, the lower end--51 
percent--of the range for the low- and moderate-income market estimate 
is consistent with low- and moderate-income borrowers accounting for 38 
percent of home purchase loans in the single-family owner-occupied 
market. (The remainder of the low- and moderate-income market share 
estimate includes multifamily and single-family rental properties.) 
Since the 1995-2002 average for the low- and moderate-income share of 
the home purchase market was 43.5 percent, and the more recent 1999-
2002 average was 44.6 percent, the initial Goals for 2005 allow leeway 
for more adverse income and interest rate conditions.

[[Page 24251]]

2. Low- and Moderate-Income Housing Goal, Sec. 81.12
    This section discusses the Department's consideration of the 
statutory factors in arriving at 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 analyzing the statutory factors, this proposed rule would 
establish (a) a Goal of 52 percent for the percentage of the total 
number of dwelling units financed by each GSE's mortgage purchases for 
housing affordable to low- and moderate-income families for 2005, 
rising to 53 percent in 2006, 55 percent in 2007, and 57 percent in 
2008, and (b) a Subgoal of 45 percent of the total number of owner-
occupied dwelling units financed by each GSE's purchases of home 
purchase mortgages in metropolitan areas that are for housing 
affordable to low- and moderate-income families for 2005, rising to 46 
percent in 2006, 47 percent in 2007, and 47 percent in 2008.
    A short discussion of the statutory factors reviewed to establish 
the Goal follows. More detailed information analyzing each of the 
statutory factors is provided in Appendix A, ``Departmental 
Considerations to Establish the Low- and Moderate-Income Housing 
Goal,'' and Appendix D, ``Estimating the Size of the Conventional 
Conforming Market for each Housing Goal.''
a. Market Estimate for the Low- and Moderate-Income Housing Goal
    The Department estimates that dwelling units serving low- and 
moderate-income families will account for 51-57 percent of total units 
financed in the overall conventional conforming mortgage market during 
the period 2005 through 2008. HUD has developed this range, rather than 
a specific point estimate, to account for the projected effects of 
different economic and affordability conditions that can reasonably be 
anticipated. HUD estimates that low- and moderate-income share of the 
market averaged 57 percent between 1999 and 2002.
b. Past Performance of the GSEs under the Low- and Moderate-Income 
Housing Goal
    As discussed above, a number of changes in Goal-counting procedures 
were adopted as part of HUD's Housing Goals 2000 final rule. Thus, it 
is necessary to provide information using several different measures in 
order to track performance on the Low- and Moderate-Income Housing Goal 
over the 1996-2002 period. Table 3 shows performance under these 
measures.
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    Specifically, the following changes were made in counting 
procedures for measuring performance on the Low- and Moderate-Income 
Housing Goal for 2001-03. HUD:
    (a) Established ``Bonus points'' (awarding double credit) for 
purchases of low- and moderate-income mortgages on small (5-50 unit) 
multifamily properties and, above a threshold level, mortgages on 2-4 
unit owner-occupied properties;
    (b) Established a ``temporary adjustment factor'' (1.35 units 
credit, as revised by Congress for 2001-03 from HUD's 1.2 unit credits 
in the 2000 rule) that applied to Freddie Mac's purchases (but not 
Fannie Mae's purchases) of low- and moderate-income mortgages on large 
(more than 50-unit) multifamily properties; and
    (c) Revised procedures that HUD had instituted regarding the 
treatment of missing data on unit affordability, the use of imputed or 
proxy rents for determining Goal credit for multifamily mortgages, and 
the eligibility for Goals credit for certain qualifying government-
backed loans.
    Based on the counting rules in effect at that time for 1996-2000, 
as shown under ``official performance'' for 1996-2000 in Table 3, Low- 
and Moderate-Income Housing Goal performance for Fannie Mae was 
consistently in the 44-46 percent range over the 1996-1999 period, 
before jumping to a peak of 49.5 percent in 2000. Freddie Mac's 
performance started at a lower level, but then increased in several 
steps, from 41-43 percent in 1996-98 to 46.1 percent in 1999, and a 
record level of 49.9 percent in 2000. That was the only year prior to 
2001 in which Freddie Mac's performance has exceeded Fannie Mae's 
performance on this Goal.
    Based on the then current counting rules, including the bonus 
points and TAF, as shown under ``official performance'' in Table 3, 
Low- and Moderate-Income Housing Goal performance in 2001 was 51.5 
percent for Fannie Mae and 53.2 percent for Freddie Mac. Low- and 
Moderate-Income Housing Goal performance in 2002 was 51.8 percent for 
Fannie Mae and 51.4 percent for Freddie Mac.
    Immediately beneath the official Low- and Moderate-Income Housing 
Goal performance percentages in Table 3 are figures showing the GSEs' 
low- and moderate-income purchase percentages on a consistent basis for 
the entire 1996-2002 period. The assumptions used were the scoring 
rules established in HUD's Housing Goals 2000 Final Rule except that 
bonus points and the Freddie Mac Temporary Adjustment Factor (which 
were terminated at the end of 2003) are not applied. These figures are 
termed the ``2001-03 baseline assumptions.'' For 1996-2000 these 
figures differ from the official performance figures because they 
incorporate the revised counting procedures described under point (c), 
above, which were not reflected in the official performance figures at 
that time. For 2001 and 2002 both sets of figures incorporate the 
revised counting procedures, but the baseline does not incorporate the 
bonus points and the Freddie Mac Temporary Adjustment Factor.
    In terms of the 2001-2003 baseline measure, both Fannie Mae and 
Freddie Mac's low- and moderate-income performance reached its maximum 
in 2000 (Fannie Mae at 51.3 percent and Freddie Mac at 50.6 percent) 
before declining somewhat in 2001 and 2002. Both GSEs' baseline 
performance in 2001 exceeded the level attained in 1999. However, 
Freddie Mac's baseline performance fell further in 2002, to 
approximately the same level as in 1999. Fannie Mae's baseline 
performance was essentially unchanged in 2002.
    Overall, both GSEs' performance exceeded HUD's Low- and Moderate-
Income Housing Goals by significant margins in 1996-99, and by wide 
margins in 2000. New, higher Goals were established for 2001-03, and 
despite somewhat lower performance than the level attained in 2000, 
both GSEs' official performance exceeded the new goal levels in 2001 
and 2002, with the inclusion of the bonus points and the TAF.
    The decline in baseline performance in 2001 and 2002 can be 
attributed in large measure to the mortgage refinance wave that 
occurred in those years. Fannie Mae's overall volume of mortgage 
purchases (in terms of numbers of housing units) rose from 2.2 million 
in 2000 to 4.7 million in 2001, and then to 6.0 million in 2002. 
Similarly, Freddie Mac's volume rose from 1.6 million in 2000 to 3.3 
million in 2001, and then to 4.3 million in 2002. For each GSE the 
increase in volume each year can be largely attributed to increases in 
purchase volumes for refinance mortgages relative to home purchase 
mortgages. For each GSE, the fraction of mortgages that qualified as 
Low- and Moderate-Income was less for refinance mortgages than for home 
purchase mortgages.
    For 2005-2008 HUD does not propose to change the current procedures 
regarding the treatment of missing data on unit affordability, the use 
of imputed or proxy rents for determining Goal credit for multifamily 
mortgages, or the eligibility for Goal credit of certain qualifying 
government-backed loans. That is, the Department does not plan to 
change the 2001-03 baseline assumptions for scoring loans under the 
Low- and Moderate-Income Housing Goal.
    Beneath the 2001-03 baseline figures in Table 3 is another row of 
figures designated ``With 2005 Assumptions.'' These figures show the 
effects of applying 2000 Census data and the new specification of 
Metropolitan Statistical Areas released by the Office of Management and 
Budget in 2003 to the measurement of Low- and Moderate-Income purchase 
percentages with the same counting rules that were used for the 2001-03 
baseline. The effect is to reduce the Goal-qualifying percentage by an 
average of 0.5 percentage points for Fannie Mae and 0.8 percentage 
points for Freddie Mac, over the four-year period.
c. Proposed Low- and Moderate-Income Home Purchase Subgoal for 2005-
2008
    The Department proposes to establish a Subgoal of 45 percent of 
each GSE's purchases of home purchase mortgages on single-family owner-
occupied properties in metropolitan areas which are for low- and 
moderate-income families in 2005, with this Subgoal rising to 46 
percent in 2006 and 47 percent in both 2007 and 2008. The purpose of 
this Subgoal is to encourage the GSEs to increase their acquisitions of 
home purchase loans for low- and moderate-income families, many of whom 
are expected to enter the homeownership market over the next few years. 
If the GSEs meet this Subgoal, in 2005 they will be leading the primary 
market by approximately one percentage point, based on the income 
characteristics of home purchase loans reported in HMDA. Between 1999 
and 2002, HMDA data show that low- and moderate-income families 
accounted for an average of 44.3 percent of single-family-owner loans 
originated in the conventional conforming market of metropolitan areas. 
Loans in the B&C portion of the subprime market are not included in 
these averages. To reach the 45-percent Subgoal for 2005, both GSEs 
must improve their average performance, as shown in Table 2--Fannie Mae 
by about one percentage point over its average performance of 44.2 
percent during 2001 and 2002, and Freddie Mac by 2.4 percentage points 
over its average performance of 42.6 percent; these required 
improvements will increase further by one percentage point in 2006 and 
an additional one percentage point in 2007-08 under HUD's proposal.

[[Page 24254]]

    As explained above, HUD will be re-benchmarking its median incomes 
for metropolitan areas and non-metropolitan counties based on 2000 
Census median incomes, and will be incorporating the effects of the new 
OMB metropolitan area definitions. HUD projected the effects of these 
two changes on the low- and moderate-income shares of the single-
family-owner market for the years 1999-2002. These estimates will be 
referred to as ``projected data'' while the 1990-based data reported 
above will be referred to as ``historical data.'' The average low-mod 
share of the home purchase market (without B&C loans) was 43.1 percent 
based on projected data, as compared with 44.3 percent based on 
historical data. Thus, based on projected data, the proposed 45-percent 
Home Purchase Subgoal for 2005 is approximately two percentage points 
above the 1999-2002 market average. Fannie Mae's average low-mod 
performance between 1999 and 2002 based on the projected data was 41.4 
percent, compared with 42.5 percent based on historical data. To reach 
the 45-percent Subgoal based on projected data, Fannie Mae would have 
to improve its performance in 2005 by 2.3 percentage points over its 
projected average performance of 42.7 percent in 2001 and 2002, or by 
1.4 percentage points over its projected 2002 low-mod performance of 
43.6 percent. Freddie Mac's average low-mod performance between 1999 
and 2002 based on the projected data was 40.9 percent, compared with 
42.3 percent based on historical data. To reach the 45-percent Subgoal 
based on projected data, Freddie Mac would have to improve its 
performance in 2005 by 4.0 percentage points over its projected average 
performance of 41.0 percent in 2001 and 2002, or by 2.9 percentage 
points over its projected 2002 low-mod performance of 42.1 percent.
    Section II.B.2 of this preamble and Section I of Appendix A discuss 
the reasons why the Department is establishing the Subgoal for low- and 
moderate-income loans, as follows: (1) The GSEs' have the resources and 
the ability to lead the market in providing mortgage funding for low- 
and moderate-income families; (2) the GSEs have generally not led the 
market, even though they have the ability to do so; (3) troublesome 
disparities in our housing and mortgage markets indicate a continuing 
need for increased GSE activity; and (4) there are ample opportunities 
for the GSEs to improve their low- and moderate-income performance in 
the home purchase market. Although single-family-owner mortgages 
comprise the ``bread-and-butter'' of their business, the GSEs have 
historically lagged behind the primary market in financing mortgages 
for low- and moderate-income families. Because home purchase loans 
account for a major share of the GSEs' purchases, the establishment of 
this Subgoal will aid their performance under the overall Low- and 
Moderate-Income Housing Goal.
    For the foregoing reasons, the Department believes that the GSEs 
can do more to raise the share of their home loan purchases serving 
low- and moderate-income families. This can be accomplished by building 
on efforts that the enterprises have already started, including their 
new affordable lending products, their many partnership efforts, their 
outreach to inner city neighborhoods, their incorporation of greater 
flexibility into their underwriting guidelines, and their purchases of 
seasoned CRA loans. A wide variety of quantitative and qualitative 
indicators indicate that the GSEs' have the resources and financial 
strength to improve their affordable lending performance enough to lead 
the market serving low- and moderate-income families.
d. Proposed Goal Levels for 2005-2008
    The Department is proposing to increase the Low- and Moderate-
Income Housing Goal to 52 percent for 2005, 53 percent in 2006, 55 
percent in 2007, and 57 percent in 2008. The reasons for increasing the 
Low- and Moderate-Income Housing Goal are discussed in Section a, 
above. While the GSEs have lagged the primary market in funding low- 
and moderate-income loans, they appear to have ample room to improve 
their performance in that market. The GSEs' mortgage purchases between 
1999 and 2002 accounted for 49 percent of the total (single-family and 
multifamily) conforming mortgage market, but they accounted for only 42 
percent of the low- and moderate-income market. A wide variety of 
quantitative and qualitative indicators demonstrate that the GSEs' have 
the expertise, resources and financial strength to improve their low- 
and moderate-income lending performance and close their gap with the 
market.
3. 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 the proposed new housing goal level 
for the Underserved Areas Housing Goal.
    The Underserved Areas Housing Goal focuses on areas of the nation 
currently underserved by the mortgage finance system. The 1995 rule 
provided that mortgage purchases count toward the Underserved Areas 
Housing Goal if such purchases finance properties that are located in 
underserved census tracts. At 24 CFR 81.2 of HUD's current rules, HUD 
defines ``underserved areas'' for metropolitan areas (in central cities 
and other underserved areas) as census tracts where either: (1) the 
tract median income is at or below 90 percent of the area median income 
(AMI); or (2) the minority population is at least 30 percent and the 
tract median income is at or below 120 percent of AMI. The AMI ratio is 
calculated by dividing the tract median income by the MSA median 
income. The minority 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 Underserved Areas Housing 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 median 
incomes for the non-metropolitan portions of the state or of the nation 
as a whole; 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 greater of the median incomes for the non-metropolitan 
portions of the state or of the nation as a whole.
    This proposed rule bases its proposed level for the Underserved 
Areas Housing Goal on 2000 Census data on area median incomes and 
minority percentages for census tracts, counties, MSAs, and the non-
metropolitan portions of states and of the entire nation. HUD's 
analysis, which is sketched below and described in greater detail in 
Appendix B, has revealed that the effect of using 2000 Census data 
rather than 1990 data to determine whether areas are underserved 
increase the percentages of the GSEs' mortgage purchases in underserved 
areas by an estimated average of 5 percentage points for Fannie Mae and 
4 percentage points for Freddie Mac, based on the geographic locations 
of the GSEs' mortgage purchases in 1999 through 2002. This change 
reflects geographical shifts in population concentrations by income and 
minority status from 1990 to 2000. It is for this reason that HUD's 
proposed level of the Underserved Areas Housing Goal is greater than 
the existing level by several percentage points more than the increase 
in the other two Goals.

[[Page 24255]]

    After analyzing the statutory factors, this proposed rule would: 
(a) Establish a Goal of 38 percent for the percentage of the total 
number of dwelling units financed by each GSE's mortgage purchases for 
properties located in underserved areas for 2005, 39 percent for 2006 
and 2007, and 40 percent for 2008; (b) establish census tracts as the 
spatial basis for establishing whether properties in non-metropolitan 
(rural) areas count toward the Underserved Areas Housing Goal, in place 
of counties as in the definition stated above, for the reasons 
described below; and (c) also establish a Subgoal of 33 percent of the 
total number of dwelling units financed by each GSE's purchases of home 
purchase mortgages in metropolitan areas for properties located in 
underserved areas of metropolitan areas for 2005, rising to 34 percent 
for 2006, and 35 percent for 2007 and 2008;
    A short discussion of the statutory factors reviewed in 
establishing the Goal 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 Underserved Areas Housing Goal
    The Department estimates that dwelling units in underserved areas 
will account for 35-40 percent of total units financed in the overall 
conventional conforming mortgage market during the period 2005 through 
2008. HUD has developed this range, rather than a specific point 
estimate, to accommodate the projected effects of different economic 
and affordability conditions that can reasonably be anticipated. HUD 
estimates that the underserved areas market averaged 39 percent between 
1999 and 2002.
b. Past Performance of the GSEs under the Underserved Areas Housing 
Goal
    As discussed above, a number of changes in goal-counting procedures 
were adopted as part of HUD's Housing Goals 2000 final rule. Thus it is 
necessary to provide information using several different measures in 
order to track changes in the GSEs' performance on the Underserved 
Areas Housing Goal over the 1996-2002 period. These are shown in Table 
4. The same changes in counting rules described for the Low- and 
Moderate-Income Housing Goal are applicable to the Underserved Areas 
Housing Goal.
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[[Page 24257]]

    Based on the counting rules in effect at that time, as shown under 
``official performance'' for 1996-2000 in Table 4, Underserved Areas 
Housing Goal performance for Fannie Mae generally fluctuated in the 
range between 27 and 29 percent over the 1996-99 period, before rising 
to a peak of 31.0 percent in 2000. Freddie Mac's performance started at 
a lower level, but then increased in several steps, from 25-26 percent 
in 1996-98 to 27.5 percent in 1999, and a record level of 29.2 percent 
in 2000. Freddie Mac's performance in 1999 was the only year prior to 
2001 in which it exceeded Fannie Mae's performance on this Goal.
    Based on current counting rules, including the bonus points and the 
TAF, as shown under ``official performance'' for 2001 in Table 4, 
Underserved Areas Housing Goal performance in 2001 was 32.6 percent for 
Fannie Mae and 31.7 percent for Freddie Mac. Underserved Areas Housing 
Goal performance in 2002 was 32.8 percent for Fannie Mae and 31.9 
percent for Freddie Mac.
    Immediately beneath the official Underserved Areas Housing Goal 
performance percentages in Table 4 are figures showing the GSEs' 
purchase percentages under this Goal on a consistent basis for the 
entire 1996-2002 period. The assumptions used were the scoring rules 
established in HUD's Housing Goals 2000 Final Rule, except that bonus 
points and the Freddie Mac Temporary Adjustment Factor (which 
terminated at the end of 2003) are not applied. These figures are 
termed the ``2001-03 baseline'' assumptions. For 1996-2000 these 
figures differ from the official performance figures because they 
incorporate the revised counting procedures, which were not reflected 
in the official performance figures at that time. For 2001 and 2002 
both sets of figures incorporate the revised counting procedures, but 
the baseline does not incorporate the bonus points and Freddie Mac 
Temporary Adjustment Factor.
    In terms of the 2001-2003 baseline measure, both Fannie Mae and 
Freddie Mac's Underserved Areas Housing Goal performance reached its 
maximum in 2000 (Fannie Mae at 31.0 percent and Freddie Mac at 29.2 
percent) before declining somewhat in 2001 and 2002. Both GSEs' 
baseline performance in 2001 and 2002 exceeded the level attained in 
1999.
    Overall, both GSEs' official performance exceeded their Underserved 
Areas Housing Goal by significant margins in 1996-99, and by wide 
margins in 2000. New, higher Goals were established for 2001-03, and 
despite somewhat lower performance than the level attained in 2000 
(largely due to the 2001-02 refinance wave), both GSEs' performance 
exceeded the new Goal levels in 2001 and 2002.
    Appendix B includes a comprehensive analysis of the GSEs' 
performance in funding mortgages for single-family-owner properties in 
underserved areas. (The data reported there are based on 2000 Census 
geography, which produces underserved area figures slightly over five 
percentage points higher than 1990-based geography.) Between 1999 and 
2002, 28.3 percent of Freddie Mac's purchases and 29.5 percent of 
Fannie Mae's purchases financed properties in underserved 
neighborhoods, compared with 31.5 percent home purchase loans 
originated in the conventional conforming market (excluding B&C loans). 
Thus, Freddie Mac performed at 90 percent of the market level, while 
Fannie Mae performed at 94 percent of the market level--both results 
similar to those reported in Appendix B for underserved areas based on 
1990 Census geography. The 2000-based results also show that Fannie Mae 
has improved its performance and matched the primary market in funding 
underserved areas during 2002. The share of Fannie Mae's purchases 
going to underserved areas increased from 25.7 in 1999 to 32.3 percent 
in 2002, which placed it at the market level of 32.3 percent. However, 
the 2000-based results show that, like Freddie Mac, Fannie Mae's 
longer-term performance (since 1996) as well as its recent average 
performance (1999 to 2001) has consistently been below market levels. 
But, it is encouraging that Fannie Mae significantly improved its 
performance relative to the market during the first two years of HUD's 
higher Housing Goal levels.
    In evaluating the GSEs' past performance, it should be noted that 
while borrowers in underserved metropolitan areas tend to have much 
lower incomes than borrowers in other areas, this does not mean that 
GSE mortgage purchases in underserved areas must necessarily be 
mortgages on housing for lower income families. Between 1999 and 2001, 
housing for above median-income households accounted for nearly 60 
percent of the single-family owner-occupied mortgages the GSEs 
purchased in underserved areas.
    Beneath the 2001-03 baseline figures in Table 4 are two additional 
rows of figures designated ``2005 Assumptions.'' These figures show the 
effects of applying 2000 Census data and the new specification of 
Metropolitan Statistical Areas released by the Office of Management and 
Budget in 2003 to the identification of underserved areas for purposes 
of measuring historical GSE goal performance. The second of the two 
lines also incorporates the effects of the Department's proposed change 
from counties to census tracts as the basis for identifying underserved 
areas outside of metropolitan areas beginning in 2005.
    HUD's determination of underserved areas for purposes of computing 
the GSEs' performance on the Underserved Areas Housing Goal has through 
2002 been based on area median incomes and area minority percentages 
from the 1990 Census. HUD applied the existing numerical thresholds for 
minority percentages and median incomes to 2000 Census data and 
ascertained that the proportion of underserved census tracts and the 
proportion of housing units in underserved census tracts in 
metropolitan areas increases significantly from 1990 levels: from 47.5 
percent to 54.9 percent of census tracts underserved and from 44.3 
percent to 52.5 percent of population in underserved census tracts 
(including the effects of the 2003 re-specification of Metropolitan 
Statistical Areas). Comparable shifts at the county level in non-
metropolitan areas were found to be of much smaller magnitude. Further, 
HUD estimated the spatial distribution of GSE mortgage purchases across 
metropolitan census tracts and non-metropolitan counties for recent 
years. The findings were that for 2000, 2001, and 2002, Fannie Mae's 
performance figures are an estimated 7.2 percent, 6.0 percent, and 5.5 
percent higher in terms of 2000 Census geography than with 1990 Census 
geography. The corresponding figures for Freddie Mac are 5.6 percent, 
5.1 percent, and 5.1 percent larger, respectively. With a further shift 
to tract-based definitions the figures for Fannie Mae are reduced by 
0.7 percentage points in each of the three years, and for Freddie Mac 
0.7, 0.8, and 0.7 percentage points, respectively. HUD has taken 
account of these shifts in establishing the level of the Underserved 
Areas Housing Goal for 2005 and beyond.
    HUD originally adopted its current county-based definition for 
targeting GSE purchases to underserved non-metropolitan areas primarily 
based on information that rural lenders did not perceive their market 
areas in terms of census tracts, but rather, in terms of counties. A 
further concern was an apparent lack of reliability of geocoding 
software applied to non-metropolitan areas. Recent research summarized 
in Appendix B indicates that a tract-based

[[Page 24258]]

system would improve the extent to which the underserved area 
definition distinguishes areas by key socioeconomic and demographic 
characteristics such as median family income, poverty, unemployment, 
school dropout rates, and minority populations. Under a tract-based 
definition underserved areas stand out more as areas of lower income 
and low economic activity and as having somewhat larger minority 
population proportions. A tract-based definition would also improve the 
targeting of the goal to areas with relatively greater housing needs. 
Based on these findings, which are detailed in Appendix B, HUD is 
proposing to re-specify the definition of underserved areas within non-
metropolitan (rural) areas to be based on census tracts rather than 
counties.
c. Proposed Underserved Areas Home Purchase Subgoal for 2005-2008
    The Department believes the GSEs can play a leadership role in 
underserved markets. To facilitate this leadership, the Department is 
proposing a Subgoal of 33 percent for each GSE's acquisitions of home 
purchase mortgages on properties located in the underserved census 
tracts of metropolitan areas for 2005, rising to 34 percent in 2006 and 
35 percent in 2007 and 2008. The purpose of this Subgoal is to 
encourage the GSEs to improve their purchases of mortgages for 
homeownership in underserved areas, thus providing additional credit 
and capital for neighborhoods that historically have not been 
adequately served by the mortgage industry. If the GSEs meet this 
Subgoal, they will be leading the primary market, based on the census 
tract characteristics of home purchase loans reported in HMDA. Between 
1999 and 2002, HMDA data show that underserved areas accounted for 32.3 
percent of single-family-owner loans originated in the conventional 
conforming market of metropolitan areas. To reach the 33 percent 
Subgoal for 2005, both GSEs would have to improve their performance, as 
shown in Table 2--Fannie Mae by 1.9 percentage points over its average 
performance of 31.1 percent, and Freddie Mac by 3.5 percentage points 
over its average performance of 29.5 percent during 2001 and 2002. 
These required improvements would increase further by one percentage 
point in 2006 and by an additional one percentage point in 2007-08 
under HUD's proposal. The Subgoal applies only to the GSEs' purchases 
in metropolitan areas because the HMDA-based market benchmark is only 
available for metropolitan areas.
    Section II.B.2 of this preamble and Section I of Appendix B discuss 
the reasons why the Department is establishing a Subgoal for home 
purchase mortgages in underserved areas namely: (1) The GSEs' have the 
resources and the ability to lead the market in providing funding in 
underserved neighborhoods; (2) the GSEs have not led the market, even 
though they have the ability to do so; (3) troublesome disparities in 
our housing and mortgage markets indicate a continuing need for 
increased GSE activity; and (4) there are ample opportunities for the 
GSEs to improve their underserved area performance in the home purchase 
market. Although single-family-owner mortgages comprise the ``bread and 
butter'' of the GSEs' business, the GSEs have lagged behind the primary 
market in financing properties in underserved areas. For the foregoing 
reasons, the Secretary believes that the GSEs can do more to raise the 
share of their home loan purchases in underserved areas. This can be 
accomplished by building on efforts that the enterprises have already 
started, including their new affordable lending products, their many 
partnership efforts, their outreach to inner city neighborhoods, their 
incorporation of greater flexibility into their underwriting 
guidelines, and their purchases of seasoned CRA loans. A wide variety 
of quantitative and qualitative indicators demonstrate that the GSEs 
have the resources and financial strength to improve their affordable 
lending performance enough to lead the market in underserved areas.
d. Proposed Goal Levels for 2005-2008
    The Department is proposing to increase the Underserved Areas 
Housing Goal to 38 percent for 2005, 39 percent for 2006 and 2007, and 
40 percent for 2008. The reasons for increasing the Underserved Areas 
Housing Goal are discussed in Sections I.C and II.A of this preamble. 
While the GSEs have lagged the primary market in funding loans in 
underserved areas, they appear to have ample room to improve their 
performance in that market. The GSEs' mortgage purchases between 1999 
and 2002 accounted for 49 percent of the total (single-family and 
multifamily) conforming mortgage market, but they accounted for only 41 
percent of the underserved areas market. A wide variety of quantitative 
and qualitative indicators demonstrate that the GSEs have the 
expertise, resources and financial strength to improve their 
performance in underserved areas and to close their gap with the 
market.
4. Special Affordable Housing Goal, Sec. 81.14
    This section discusses the Department's consideration of the 
statutory factors in arriving at the proposed 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 analyzing the statutory factors, this proposed rule would 
establish: (a) A Goal of 22 percent for the percentage of the total 
number of dwelling units financed by each GSE's mortgage purchases that 
are for special affordable housing, affordable to very low-income 
families and families living in low-income areas for 2005, rising to 24 
percent in 2006, 26 percent in 2007, and 28 percent in 2008; (b) a 
Subgoal of 1 percent of each GSE's combined annual average mortgage 
purchases in 2000, 2001, and 2002, for each GSE's special affordable 
mortgage purchases that are for multifamily housing in 2005-2008; and 
(c) a Subgoal of 17 percent of the total number of each GSE's purchases 
of home purchase mortgages in metropolitan areas that are for housing 
affordable to very low income families and low-income families in low-
income areas for 2005, rising to 18 percent in 2006, 19 percent in 
2007, and 19 percent in 2008.
    A short discussion of the statutory factors for establishing the 
Goal follows. Additional information analyzing each of the statutory 
factors is provided in Appendix C, ``Departmental Considerations to 
Establish the Special Affordable Housing Goal,'' and Appendix D, 
``Estimating the Size of the Conventional Conforming Market for Each 
Housing Goal.''
a. Market Estimate for the Special Affordable Housing Goal
    The Department estimates that dwelling units serving very low-
income families and low-income families living in low-income areas will 
account for 24-28 percent of total units financed in the overall 
conventional conforming mortgage market during the period 2005 through 
2008. HUD has developed this range, rather than a point estimate, to 
account for the projected effects of different economic conditions that 
can reasonably be anticipated. HUD also estimates that the special 
affordable market averaged 28 percent between 1999 and 2002.
b. Past Performance of the GSEs Under the Special Affordable Housing 
Goal
    As discussed above, a number of changes in Goal-counting procedures

[[Page 24259]]

were adopted as part of HUD's Housing Goals 2000 final rule. Thus, it 
is necessary to provide information using several different measures in 
order to track changes in performance on the Special Affordable Housing 
Goal over the 1996-2002 period. These are shown in Table 5.
BILLING CODE 4210-27-P

[[Page 24260]]

[GRAPHIC] [TIFF OMITTED] TP03MY04.005

BILLING CODE 4210-27-C

[[Page 24261]]

    Based on the counting rules in effect at that time, as shown under 
``official performance'' for 1996-2000 in Table 5, Special Affordable 
Housing Goal performance for Fannie Mae generally fluctuated in the 
range between 14 and 17 percent over the 1996-99 period, before rising 
to a peak of 19.2 percent in 2000. Freddie Mac's performance started at 
a lower level, but then increased in several steps, from 14-16 percent 
in 1996-98 to 17.2 percent in 1999, and to a record level of 20.7 
percent in 2000. That was the only year prior to 2001 in which Freddie 
Mac's performance exceeded Fannie Mae's performance on this Goal.
    Based on current counting rules, as shown under ``official 
performance'' for 2001 in Table 5, Special Affordable Housing Goal 
performance in 2001 was 21.6 percent for Fannie Mae and 22.6 percent 
for Freddie Mac. Special Affordable Housing Goal performance in 2002 
was 21.4 percent for Fannie Mae and 21.4 percent for Freddie Mac.
    Immediately beneath the official Special Affordable Housing Goal 
performance percentages in Table 5 are figures showing the GSEs' 
special affordable purchase percentages on a consistent basis for the 
entire 1996-2002 period. The assumptions used were the scoring rules 
established in HUD's Housing Goals 2000 Final Rule except that bonus 
points and the Freddie Mac Temporary Adjustment Factor (which were 
terminated at the end of 2003) are not applied. These are termed the 
``2001-03 baseline'' assumptions. In terms of this measure, both Fannie 
Mae and Freddie Mac's special affordable performance reached its 
maximum in 2000 (Fannie Mae at 21.4 percent and Freddie Mac at 21.0 
percent) before declining somewhat in 2001 and then declining further 
in 2002. Both GSEs' baseline performance in 2002 exceeded the level 
attained in 1999.
    Overall, both GSEs' performance exceeded HUD's Special Affordable 
Housing Goals by significant margins in 1996-99, and by wide margins in 
2000. New, higher Goals were established for 2001-03, and despite 
somewhat lower performance than the level attained in 2000 (largely due 
to the 2001-02 refinance wave, as discussed under the Low- and 
Moderate-Income Housing Goal), both GSEs' performance exceeded the new 
Goal levels in 2001-02.
    The Special Affordable Housing Goal is designed, in part, to ensure 
that the GSEs maintain a consistent focus on serving the low- and very 
low-income portion of the housing market where housing needs are 
greatest. Appendices A and B use HMDA data and GSE loan-level data for 
home purchase mortgages on single-family owner-occupied properties in 
metropolitan areas to compare the GSEs' performance in special 
affordable lending to the performance of depositories and other lenders 
in the conventional conforming market. There are two main findings with 
respect to the special affordable category. First, Fannie Mae and 
Freddie Mac have historically lagged depositories and the overall 
market in providing mortgage funds for special affordable housing. 
Between 1993 and 2002, 11.8 percent of Freddie Mac's mortgage 
purchases, 12.7 percent of Fannie Mae's purchases, 15.4 percent of 
loans originated by depositories, and 15.4 percent of loans originated 
in the conventional conforming market (without estimated B&C loans) 
were for special affordable housing.
    Second, while both GSEs have improved their performance over the 
past few years, Fannie Mae has made more progress than Freddie Mac in 
closing its gap with the market. The share of Fannie Mae's purchases 
going to special affordable loans increased from 12.5 percent in 1999 
to 16.3 percent in 2002, the latter figure being at the 2002 market 
level of 16.3 percent. The share of Freddie Mac's purchases going to 
special affordable loans increased from 12.8 percent in 1999 to 15.8 
percent in 2002, the latter figure being below the 2002 market level of 
16.3 percent.
    Section G in Appendix A discusses the role of the GSEs both in the 
overall special affordable market and in the different segments 
(single-family owner, single-family rental, and multifamily rental) of 
the special affordable market. The GSEs' special affordable purchases 
accounted for 35 percent of all special affordable owner and rental 
units that were financed in the conventional conforming market between 
1999 and 2002. The GSEs' 35-percent share of the special affordable 
market was below their 49-percent share of the overall market. Even in 
the owner market, where the GSEs account for 57 percent of the market, 
their share of the special affordable market was only 49 percent. While 
the GSEs improved their market shares during 2002, the analysis 
suggests that the GSEs are not leading the single-family market in 
purchasing loans that qualify for the Special Affordable Housing Goal. 
There is room and ample opportunity for the GSEs to improve their 
performance in purchasing affordable loans at the lower-income end of 
the market.
    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, between 1999 and 
2002, 53 percent of units financed by Fannie Mae's multifamily mortgage 
purchases met the Special Affordable Housing Goal, representing 27 
percent of units counted toward the Special Affordable Housing Goal, 
during a period when multifamily units represented only 10 percent of 
its total purchase volume. For Freddie Mac, 49 percent of units 
financed by multifamily mortgage purchases met the Special Affordable 
Housing Goal, representing 23 percent of units counted toward the 
Special Affordable Housing Goal, during a period when multifamily units 
represented only 9 percent of its total purchase volume.
c. Proposed Special Affordable Home Purchase Subgoal for 2005-2008
    The Secretary believes the GSEs can play a leadership role in the 
special affordable market generally and the home purchase special 
affordable market in particular. Thus, the Department is proposing a 
Subgoal of 17 percent for each GSE's purchases of home purchase 
mortgages for special affordable housing located in metropolitan areas 
for 2005, rising to 18 percent in 2006, and 19 percent in 2007 and 
2008. The purpose of this Subgoal is to encourage the GSEs to improve 
their purchases of home purchase mortgages on special affordable 
housing, thus expanding homeownership opportunities for very-low-income 
borrowers and low-income borrowers in low-income areas, including 
minority first-time homebuyers who are expected to enter the housing 
market over the next few years. If the GSEs meet this Subgoal, they 
will be leading the primary market, based on the income characteristics 
of home purchase loans reported in HMDA. Between 1999 and 2002, HMDA 
data show that special affordable housing accounted for an average of 
16.4 percent of single-family-owner home purchase loans originated in 
the conventional conforming market in metropolitan areas. Loans in the 
B&C portion of the subprime market are not included in these averages. 
To reach the 17 percent Subgoal, both GSEs would have to improve their 
performance in 2005, as shown in Table 2--Fannie Mae by 1.4 percentage 
points over its average performance of 15.6 percent during 2001 and 
2002, and Freddie Mac by 1.9 percentage points over its performance of 
15.1 percent during the same period. These required improvements would 
increase further by one percentage point in 2006 and by an additional 
one

[[Page 24262]]

percentage point in 2007-08 under HUD's proposal. As discussed 
previously, the Subgoal applies only to the GSEs' purchases in 
metropolitan areas because the HMDA-based market benchmark is only 
available for metropolitan areas.
    Section II.B.2 of this preamble and Section D of Appendix C discuss 
reasons why the Department set the Subgoal for special affordable 
loans.
d. Special Affordable Housing Goal: Multifamily Subgoals
    Based on the GSEs' past performance on the Special Affordable 
Multifamily Subgoals, and on the outlook for the multifamily mortgage 
market, HUD is proposing that these Subgoals be retained for the 2005-
2008 period. Unlike the overall Goals, which are expressed in terms of 
minimum Goal-qualifying percentages of total units financed, these 
Subgoals for 2001-03 and in prior years have been expressed in terms of 
minimum dollar volumes of Goal-qualifying multifamily mortgage 
purchases. Specifically, each GSE's special affordable multifamily 
Subgoal is currently equal to 1.0 percent of its average total (single-
family plus multifamily) mortgage volume over the 1997-99 period. Under 
this formulation, in October 2000 the Subgoals were set at $2.85 
billion per year for Fannie Mae and $2.11 billion per year for Freddie 
Mac, in each of calendar years 2001 through 2003. These Subgoals are 
also in effect for 2004. These represented increases from the Goals for 
1996-2000, which were $1.29 billion annually for Fannie Mae and $0.99 
billion annually for Freddie Mac.
    HUD's Determination. The multifamily mortgage market and both GSEs' 
multifamily transactions volume grew significantly over the 1993-2002 
period, indicating that both enterprises have provided increasing 
support for the multifamily market, and that they have the ability to 
continue to provide further support for the market.
    Specifically, Fannie Mae's total eligible multifamily mortgage 
purchase volume increased from $4.6 billion in 1993 to $12.5 billion in 
1998, and then jumped sharply to $18.7 billion in 2001 and $18.3 
billion in 2002. Its special affordable multifamily mortgage purchases 
followed a similar path, rising from $1.7 billion in 1993 to $3.5 
billion in 1998 and $4.0 billion in 1999, and also jumping sharply to 
$7.4 billion in 2001 and $7.6 billion in 2002. As a result of its 
strong performance, Fannie Mae's purchases have been at least twice its 
minimum subgoal in every year since 1997--247 percent of the Subgoal in 
that year, 274 percent in 1998, 313 percent in 1999, 294 percent in 
2000, and, under the new Subgoal level, 258 percent in 2001, and 266 
percent in 2002.
    Freddie Mac's total eligible multifamily mortgage purchase volume 
increased even more sharply, from $0.2 billion in 1993 to $6.6 billion 
in 1998, and then jumped further in 2001 to $11.8 billion and $18.3 
billion in 2002. Its special affordable multifamily mortgage purchases 
followed a similar path, rising from $0.1 billion in 1993 to $2.7 
billion in 1998, and also jumping sharply to $4.6 billion in 2001 and 
$5.2 billion in 2002. As a result of its strong performance, Freddie 
Mac's purchases have also been at least twice its minimum Subgoal in 
every year since 1998--272 percent of the Subgoal in that year, 229 
percent in 1999, 243 percent in 2000, and, under the new Subgoal level, 
220 percent in 2001, and 247 percent in 2002.
    The Special Affordable Multifamily Subgoals set forth in this 
proposed rule are reasonable and appropriate based on the Department's 
analysis of this market. The Department's decision to retain these 
Subgoals is based on HUD's analysis which indicates that multifamily 
housing still serves the housing needs of lower-income families and 
families in low-income areas to a greater extent than single-family 
housing. By retaining the Special Affordable Multifamily Subgoal, the 
Department ensures that the GSEs continue their activity in this 
market, and that they achieve at least a minimum level of special 
affordable multifamily mortgage purchases that are affordable to lower-
income families. The Department proposes to retain each GSE's Special 
Affordable Multifamily Subgoal at 1.0 percent of its average annual 
dollar volume of total (single-family and multifamily) mortgage 
purchases over the 2000-2002 period. In dollar terms, the Department's 
proposal is $5.49 billion per year in special affordable multifamily 
mortgage purchases for Fannie Mae, and $3.92 billion per year in 
special affordable multifamily mortgage purchases for Freddie Mac. 
These Subgoals would be less than actual special affordable multifamily 
mortgage purchase volume in 2001 and 2002 for both GSEs. Thus, the 
Department believes that they would be feasible for the 2005-2008 
period.
e. Proposed Special Affordable Housing Goal Levels for 2005-2008
    The Department is proposing to increase the Special Affordable 
Housing Goal to 22 percent for 2005, 24 percent for 2006, 26 percent 
for 2007, and 28 percent for 2008. The reasons for increasing the 
Special Affordable Housing Goal are discussed above in this preamble. 
Since the GSEs have historically lagged the primary market in funding 
special affordable loans, they have ample room to improve their 
performance in that market. The GSEs' mortgage purchases between 1999 
and 2002 accounted for 49 percent of the total (single-family and 
multifamily) conforming mortgage market, but they accounted for only 35 
percent of the special affordable market. A wide variety of 
quantitative and qualitative indicators demonstrate that the GSEs have 
the expertise, resources and financial strength to improve their 
special affordable lending performance and close their gap with the 
market.

C. Subpart I--Other Provisions

    Section 81.102--Independent verification authority.
    See Section II of this preamble for a complete discussion of the 
Department's proposal to amend Sec. 81.102 to provide additional means 
of verifying and enforcing GSE data submissions.

IV. Findings and Certifications

Executive Order 12866

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

Congressional Review of Major Proposed Rules

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

Paperwork Reduction Act

    HUD's collection of information on the GSEs' activities has been 
reviewed and authorized by the Office of Management and Budget (OMB) 
under the Paperwork Reduction Act of 1995 (44 U.S.C. 3501-3520), as 
implemented

[[Page 24263]]

by OMB in regulations at 5 CFR part 1320. The OMB control number is 
2502-0514.

Environmental Impact

    This proposed 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. Accordingly, under 24 CFR 
50.19(c)(1) of HUD's regulations, this proposed rule is categorically 
excluded from environmental review under the National Environmental 
Policy Act of 1969 (42 U.S.C. 4321).

Regulatory Flexibility Act

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

Executive Order 13132, Federalism

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

Unfunded Mandates Reform Act

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

List of Subjects in 24 CFR Part 81

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

    For the reasons discussed in the preamble, HUD proposes to amend 24 
CFR part 81 as follows:

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

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


Sec. 81.2  Definitions.

* * * * *
    Home Purchase Mortgage means a residential mortgage for the 
purchase of an owner-occupied single-family property.
* * * * *
    Metropolitan area means a metropolitan statistical area (``MSA''), 
or a portion of such an area for which median family income estimates 
are published annually by HUD.
    Minority means any individual who is included within any one or 
more of the following racial and ethnic categories:
    (1) American Indian or Alaskan Native--a person having origins in 
any of the original peoples of North and South America (including 
Central America), and who maintains tribal affiliation or community 
attachment;
    (2) Asian--a person having origins in any of the original peoples 
of the Far East, Southeast Asia, or the Indian subcontinent, including, 
for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, 
the Philippine Islands, Thailand, and Vietnam;
    (3) Black or African American--a person having origins in any of 
the black racial groups of Africa;
    (4) Hispanic or Latino--a person of Cuban, Mexican, Puerto Rican, 
South or Central American, or other Spanish culture or origin, 
regardless of race; and
    (5) Native Hawaiian or Other Pacific Islander--a person having 
origins in any of the original peoples of Hawaii, Guam, Samoa, or other 
Pacific Islands.
* * * * *
    Underserved area means * * *
    (2) For purposes of the definition of ``Rural area,'' a whole 
census tract, a Federal or State American Indian reservation or tribal 
or individual trust land, or the balance of a census tract excluding 
the area within any Federal or State American Indian reservation or 
tribal or individual trust land, having:
    (i) A median income at or below 120 percent of the greater of the 
State non-metropolitan median income or the nationwide non-metropolitan 
median income and a minority population of 30 percent or greater; or
    (ii) A median income at or below 95 percent of the greater of the 
State non-metropolitan median income or nationwide non-metropolitan 
median income.
* * * * *
    3. In Sec. 81.12, revise the last sentence of paragraph (b) and 
revise paragraph (c), to read as follows:


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

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

[[Page 24264]]

metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Low- and Moderate-Income Housing Goal in the year 2006 unless otherwise 
adjusted by HUD in accordance with FHEFSSA;
    (3) For the year 2007, 55 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Low- and 
Moderate-Income Housing Home Purchase Subgoal, 47 percent of the total 
number of home purchase mortgages in metropolitan areas financed by 
that GSE's mortgage purchases shall be home purchase mortgages in 
metropolitan areas which count toward the Low- and Moderate-Income 
Housing Goal in the year 2007 unless otherwise adjusted by HUD in 
accordance with FHEFSSA;
    (4) For the year 2008, 57 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Low- and 
Moderate-Income Housing Home Purchase Subgoal, 47 percent of the total 
number of home purchase mortgages in metropolitan areas financed by 
that GSE's mortgage purchases shall be home purchase mortgages in 
metropolitan areas which count toward the Low- and Moderate-Income 
Housing Goal in the year 2008 unless otherwise adjusted by HUD in 
accordance with FHEFSSA; and
    (5) For the year 2009 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2009 and thereafter, 
the annual goal for each of those years shall be 57 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years. In addition, as a Low and Moderate 
Income Housing Home Purchase Subgoal, 47 percent of the total number of 
home purchase mortgages in metropolitan areas financed by that GSE's 
mortgage purchases shall be home purchase mortgages in metropolitan 
areas which count toward the Low- and Moderate-Income Housing Goal in 
each of those years unless otherwise adjusted by HUD in accordance with 
FHEFSSA.
    4. In Sec. 81.13, revise the last sentence of paragraph (b) and 
revise paragraph (c), to read as follows:


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

* * * * *
    (b) Factors. * * * A statement documenting HUD's considerations and 
findings with respect to these factors, entitled ``Departmental 
Considerations to Establish the Central Cities, Rural Areas, and Other 
Underserved Areas Housing Goal,'' was published in the Federal Register 
on [date of publication of final rule in the Federal Register].
    (c) Goals. The annual goals for each GSE's purchases of mortgages 
on housing located in central cities, rural areas, and other 
underserved areas are:
    (1) For the year 2005, 38 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 
33 percent of the total number of home purchase mortgages in 
metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
in the year 2005 unless otherwise adjusted by HUD in accordance with 
FHEFSSA;
    (2) For the year 2006, 39 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 
34 percent of the total number of home purchase mortgages in 
metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
in the year 2006 unless otherwise adjusted by HUD in accordance with 
FHEFSSA;
    (3) For the year 2007, 39 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 
35 percent of the total number of home purchase mortgages in 
metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
in the year 2007 unless otherwise adjusted by HUD in accordance with 
FHEFSSA;
    (4) For the year 2008, 40 percent of the total number of dwelling 
units financed by that GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. In addition, as a Central 
Cities, Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 
35 percent of the total number of home purchase mortgages in 
metropolitan areas financed by that GSE's mortgage purchases shall be 
home purchase mortgages in metropolitan areas which count toward the 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
in the year 2008 unless otherwise adjusted by HUD in accordance with 
FHEFSSA; and
    (5) For the year 2009 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2009 and thereafter, 
the annual goal for each of those years shall be 40 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years. In addition, as a Central Cities, 
Rural Areas, and Other Underserved Areas Home Purchase Subgoal, 35 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by that GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Central Cities, 
Rural Areas, and Other Underserved Areas Housing Goal in each of those 
years unless otherwise adjusted by HUD in accordance with FHEFSSA.
* * * * *
    5. In Sec. 81.14, revise the last sentence of paragraph (b) and 
revise paragraph (c), to read as follows:


Sec. 81.14  Special Affordable Housing Goal.

* * * * *
    (b) * * * A statement documenting HUD's considerations and findings 
with respect to these factors, entitled ``Departmental Considerations 
to Establish the Special Affordable Housing Goal,'' was published in 
the Federal Register on [date of publication of final rule in the 
Federal Register].
    (c) Goals. The annual goals for each GSE's purchases of mortgages 
on rental and owner-occupied housing meeting the then-existing, 
unaddressed needs of and affordable to low-income families in low-
income areas and very low-income families are:
    (1) For the year 2005, 22 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2005 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in

[[Page 24265]]

accordance with FHEFSSA. In addition, as a Special Affordable Housing 
Home Purchase Subgoal, 17 percent of the total number of home purchase 
mortgages in metropolitan areas financed by each GSE's mortgage 
purchases shall be home purchase mortgages in metropolitan areas which 
count toward the Special Affordable Housing Goal in the year 2005 
unless otherwise adjusted by HUD in accordance with FHEFSSA;
    (2) For the year 2006, 24 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2006 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single-family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in accordance with FHEFSSA. In 
addition, as a Special Affordable Housing Home Purchase Subgoal, 18 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in the year 2006 unless otherwise adjusted by 
HUD in accordance with FHEFSSA;
    (3) For the year 2007, 26 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2007 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single-family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in accordance with FHEFSSA. In 
addition, as a Special Affordable Housing Home Purchase Subgoal, 19 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in the year 2007 unless otherwise adjusted by 
HUD in accordance with FHEFSSA;
    (4) For the year 2008, 28 percent of the total number of dwelling 
units financed by each GSE's mortgage purchases unless otherwise 
adjusted by HUD in accordance with FHEFSSA. The goal for the year 2008 
shall include mortgage purchases financing dwelling units in 
multifamily housing totaling not less than 1.0 percent of the average 
annual dollar volume of combined (single-family and multifamily) 
mortgages purchased by the respective GSE in 2000, 2001, and 2002, 
unless otherwise adjusted by HUD in accordance with FHEFSSA. In 
addition, as a Special Affordable Housing Home Purchase Subgoal, 19 
percent of the total number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in the year 2008 unless otherwise adjusted by 
HUD in accordance with FHEFSSA; and
    (5) For the year 2009 and thereafter HUD shall establish annual 
goals. Pending establishment of goals for the year 2009 and thereafter, 
the annual goal for each of those years shall be 28 percent of the 
total number of dwelling units financed by each GSE's mortgage 
purchases in each of those years. The goal for each such year shall 
include mortgage purchases financing dwelling units in multifamily 
housing totaling not less than 1.0 percent of the annual average dollar 
volume of combined (single-family and multifamily) mortgages purchased 
by the respective GSE in the years 2000, 2001, and 2002. In addition, 
as a Special Affordable Housing Home Purchase Subgoal, 19 percent of 
the total number of home purchase mortgages in metropolitan areas 
financed by each GSE's mortgage purchases shall be home purchase 
mortgages in metropolitan areas which count toward the Special 
Affordable Housing Goal in each of those years unless otherwise 
adjusted by HUD in accordance with FHEFSSA.
* * * * *
    6. Add Sec. 81.15(i), to read as follows:


Sec. 81.15  General requirements.

* * * * *
    (i) Counting mortgages toward the Home Purchase Subgoals. (1) 
General. The requirements of this section, except for paragraphs (b) 
and (e) of this section, shall apply to counting mortgages toward the 
Home Purchase Subgoals at Secs. 81.12-81.14. However, performance under 
the Subgoals shall be counted using a fraction that is converted into a 
percentage for each Subgoal and the numerator of the fraction for each 
Subgoal shall be the number of home purchase mortgages in metropolitan 
areas financed by each GSE's mortgage purchases in a particular year 
that count towards achievement of the applicable housing goal. The 
denominator of each fraction shall be the total number of home purchase 
mortgages in metropolitan areas financed by each GSE's mortgage 
purchases in a particular year. For purposes of each Subgoal, the 
procedure for addressing missing data or information, as set forth in 
paragraph (d) of this section, shall be implemented using numbers of 
home purchase mortgages in metropolitan areas and not single-family 
owner-occupied dwelling units.
    (2) Special counting rule for mortgages with more than one owner-
occupied unit. For purposes of counting mortgages toward the Home 
Purchase Subgoals, where a single home purchase mortgage finances the 
purchase of two or more owner-occupied units in a metropolitan area, 
the mortgage shall count once toward each Subgoal that applies to the 
GSE's mortgage purchase.
    7. Remove and reserve Sec. 81.16(c)(1) and (c)(11).
    8. Revise Sec. 81.102 to read as follows:


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

    (a) Independent verification authority. The Secretary may 
independently verify the accuracy and completeness of the data, 
information, and reports provided by each GSE, including conducting on-
site verification, when such steps are reasonably related to 
determining whether a GSE is complying with 12 U.S.C. 4541'4589 and the 
GSE's Charter Act.
    (b) Certification. The senior officer of each GSE who is 
responsible for submitting to HUD the AHAR under section 309(m) and (n) 
of the Fannie Mae Act or section 307(e) and (f) of the Freddie Mac 
Charter Act, as applicable, or for submitting to HUD such other 
report(s), data submission(s), or information for which certification 
is requested in writing by HUD (``GSE Certifying Official'') shall 
certify in connection with each such report(s), data submission(s) or 
information that:
    (1) The GSE Certifying Official has reviewed the particular AHAR, 
other report(s), data submission(s) or information;
    (2) To the best of the GSE Certifying Official's knowledge and 
belief, the particular AHAR, other report(s), data submission(s) or 
information are current, complete and do not contain any untrue 
statement of a material fact;
    (3) To the best of the GSE Certifying Official's knowledge and 
belief, the particular AHAR, other report(s), data submission(s) or 
information fairly present in all material respects the GSE's 
performance, as required to be reported by section 309(m) or (n) of the

[[Page 24266]]

Fannie Mae Act or section 307(e) or (f) of the Freddie Mac Charter Act, 
or other applicable legal authority; and
    (4) To the best of the GSE Certifying Official's knowledge and 
belief, the GSE has identified in writing any areas in which the GSE's 
particular AHAR, other report(s), data submission(s) or information may 
differ from HUD's written articulations of its counting rules 
including, but not limited to, the regulations under this part, and any 
other areas of ambiguity.
    (c) Adjustment to correct current year-end errors, omissions or 
discrepancies. If HUD finds errors, omissions or discrepancies in a 
GSE's current year-end data submissions (including data reported in the 
GSE's AHAR under section 309(m) and (n) of the Fannie Mae Act or 
section 307(e) and (f) of the Freddie Mac Charter Act, as applicable) 
relative to HUD's regulations or other guidance, HUD will first notify 
the GSE by telephone or e-mail transmission of each such error, 
omission or discrepancy. The GSE must respond within five business days 
of such notification. If each error, omission or discrepancy is not 
resolved to HUD's satisfaction, HUD will then notify the GSE in writing 
and seek clarification or additional information to correct the error, 
omission or discrepancy. The GSE shall have 10 business days (or such 
longer period as HUD may establish, not to exceed 30 business days) 
from the date of this written notice to respond in writing to the 
request. If the GSE fails to submit a written response to HUD within 
this period, or if HUD determines that the GSE's written response fails 
to explain or correct each error, omission or discrepancy in its 
current year-end reported data to HUD's satisfaction, HUD will 
determine the appropriate adjustments to the numerator and the 
denominator of the applicable housing goal(s) and Subgoal(s). Should 
the Department determine that additional enforcement action against the 
GSE is warranted, it may pursue additional remedies under paragraph (e) 
of this section.
    (d) Adjustment to correct prior year reporting errors, omissions or 
discrepancies.
    (1) General. HUD may, in accordance with its authority in 12 U.S.C. 
4566(a) to measure the extent of compliance with the housing goals, 
adjust a GSE's current year-end performance under a housing goal to 
deduct credit under the current goals and/or Subgoals to the extent 
caused by errors, omissions or discrepancies in a GSE's prior year's 
data submissions (including the AHAR under section 309(m) and (n) of 
the Fannie Mae Act or section 307(e) and (f) of the Freddie Mac Charter 
Act, as applicable) that result in an overstatement of GSE housing goal 
performance.
    (2) Applicability. This paragraph applies to errors, omissions or 
discrepancies in a GSE's data submissions, including its AHAR, as 
provided in this section. It does not apply to the process applicable 
to HUD's review of current year performance, as described in paragraph 
(c) of this section.
    (3) Limitations. This paragraph applies only to GSE reporting 
periods occurring on or after [effective date of final rule].
    (4) Procedural requirements. In the event HUD determines that an 
adjustment to correct an error, omission or discrepancy in a GSE's 
prior year's data submissions (including data reported in the AHAR), as 
provided in paragraph (d)(1) of this section is warranted, it will 
provide the GSE with an initial letter containing its written findings 
and determinations within 24 months of the end of the relevant GSE 
reporting year. The GSE shall have an opportunity, not to exceed 30 
days from the date of HUD's initial letter, to respond in writing, with 
supporting documentation, to contest the initial determination that 
there were errors in a prior year's data submissions (including the 
AHAR). HUD shall then issue a final determination letter within 60 days 
of the date of the GSE's written response. HUD may, upon a 
determination of good cause, extend the period for issuing a final 
determination letter by an additional 30 days.
    (5) Adjustments. If the GSE failed to submit a written response to 
HUD's initial determination letter within the 30-day time period, or 
if, after reviewing a GSE's written response to the initial 
determination letter, HUD determines that a GSE's prior year's data 
submissions (including data reported in the AHAR as provided in 
paragraph (d)(1) of this section) resulted in an overstatement of its 
performance under one or more housing goals or Subgoals for a previous 
reporting period, HUD will direct the GSE to correct the overstatement 
by adjusting its level of performance under the applicable housing 
goal(s) and/or Subgoal(s) in the current year AHAR prior to submitting 
such report to HUD. The adjustment will be made by excluding the number 
of units or mortgages that HUD has determined were erroneously counted 
in a previous year from the numerator (but not the denominator) of each 
applicable housing goal and/or Subgoal. The GSE shall reflect the 
adjustment in its AHAR for the current year, as directed by HUD.
    (6) Effect of failure to meet a housing goal, or substantial 
probability of such failure.
    (i) Procedural requirements. In the event HUD determines that a GSE 
has failed, or that there is a substantial probability that the GSE 
will fail, to meet any housing goal(s) in the current reporting year as 
a result of an adjustment under paragraph (d) (5) of this section for 
previously overstated housing goals performance, HUD shall provide 
written notice to the GSE and otherwise comply with the procedural 
requirements set forth in 12 U.S.C. 4566(b).
    (ii) Remedies. If HUD determines pursuant to 12 U.S.C. 4566(b) that 
a GSE has failed, or that there is a substantial probability that the 
GSE will fail, any housing goal(s) in the current reporting year as a 
result of an adjustment under paragraph (d) (5) of this section to 
correct for an overstatement of a prior year's goals performance, and 
that the achievement of the housing goal was or is feasible, it may 
pursue one or both of the following remedies:
    (A) Housing plan. HUD may require the GSE to submit a housing plan 
for approval by the Secretary pursuant to 12 U.S.C. 4566(c) and 
Sec. 81.22; and
    (B) Additional enforcement options. HUD may, after complying with 
the procedural requirements set forth in subpart G of this part, seek a 
cease-and-desist order or civil money penalties against the GSE as 
described in paragraph (e) of this section.
    (e) Additional enforcement options. (1) General. In the event the 
Secretary determines, either as a result of its independent 
verification authority described in paragraph (a) of this section or by 
other means, that the data submissions, information or report(s) 
submitted by a GSE to HUD pursuant to subpart E of this part, section 
309(m) or (n) of the Fannie Mae Charter Act, or section 307(e) and (f) 
of the Freddie Mac Charter Act, as applicable, are not current, are 
incomplete or otherwise contain an untrue statement of material fact, 
the Secretary may regard this as equivalent to the GSE's failing to 
submit such data and, accordingly, may take the enforcement action 
authorized under paragraph (e)(2) of this section.
    (2) Remedies. After HUD makes a final determination pursuant to 
paragraph (e) of this section that a GSE has submitted report(s), data 
submission(s) or information that are not current, are incomplete, or 
that contain untrue statement(s) of material fact, it may pursue any or 
all of the following remedies:

[[Page 24267]]

    (i) HUD may obtain a cease-and-desist order against the GSE for 
failing to submit the report(s), data submission(s) or information, as 
applicable, required by subsection (m) or (n) of section 309 of the 
Fannie Mae Charter Act or subsection (e) or (f) of the Freddie Mac 
Charter Act, and as authorized by 12 U.S.C. 4581(a)(3), Sec. 81.82, and 
subpart E of this part;
    (ii) HUD may seek civil money penalties against the GSE for failing 
to submit the report(s), data submissions, or information, as 
applicable, required by subsection (m) or (n) of section 309 of the 
Fannie Mae Charter Act or subsection (e) or (f) of the Freddie Mac 
Charter Act, and as authorized by 12 U.S.C. 4585(a)(3), 24 CFR 81.83 
and Subpart E of this part.
    (iii) HUD may seek any other remedies or penalties against the GSE 
that may be available to the Secretary by virtue of the GSE's failure 
to provide data submissions, information and/or report(s) in accordance 
with the requirements of this section.
    (3) Procedures. HUD shall comply with the procedures set forth in 
Subpart G of this part in connection with any enforcement action that 
it initiates against a GSE under this paragraph.

    Dated: April 2, 2004.
John C. Weicher,
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

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

1. Establishment of Low- and Moderate-Income Goal

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

2. Underlying Data

    In considering the statutory factors in establishing these 
goals, HUD relied on data from the 2001 American Housing Survey, the 
2000 Censuses of Population and Housing, the 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 1993-2002 in accordance with 
the goal counting provisions established by the Department in the 
December 1995 and October 2000 rules (24 CFR part 81).

3. Conclusions Based on Consideration of the Factors

    The discussion of the first two factors covers a range of topics 
on housing needs and economic and demographic trends that are 
important for understanding mortgage markets. Information is 
provided which describes the market environment in which the GSEs 
must operate (for example, trends in refinancing activity). In 
addition, the severe housing problems faced by lower-income families 
are discussed, as are the barriers that minorities face when 
attempting to become homeowners. This discussion serves to provide 
useful background information for the discussion of the Underserved 
Areas and Special Affordable Housing Goals in Appendixes B and C, as 
well as for the Low- and Moderate-Income Housing Goal in this 
Appendix.
    The third factor (past performance) and the fifth factor 
(ability of the GSEs to lead the industry) are also discussed in 
some detail in this Appendix. With respect to home purchase 
mortgages, the past performance of the GSEs and their ability to 
lead the industry are examined for all three housing goals; that 
analysis provides the basis for establishing the three subgoals for 
the GSEs' acquisitions of home loans on single-family-owner 
properties.
    The fourth factor (size of the market) and the sixth factor 
(need to maintain the GSEs' sound financial condition) are mentioned 
only briefly in this Appendix. Detailed analyses of the fourth 
factor and the sixth factor are contained in Appendix D and in the 
economic analysis of this rule, respectively.
    The factors are discussed in sections B through H of this 
appendix. Section I summarizes the findings and presents the 
Department's conclusions concerning the Low- and Moderate-Income 
Housing Goal. Section I also gives the rationale for a low- and 
moderate-income subgoal for home purchase loans.
    The consideration of the factors in this Appendix has led the 
Secretary to the following conclusions:
     Changing population demographics will result 
in a need for primary and secondary mortgage markets to meet 
nontraditional credit needs, respond to diverse housing preferences, 
and overcome information and other barriers that many immigrants and 
minorities face. Growing housing demand from immigrants (both those 
who are already here and those projected to come) and non-
traditional homebuyers will help to offset declines in the demand 
for housing caused by the aging of the population. Immigrants and 
other minorities--who accounted for nearly 40 percent of the growth 
in the nation's homeownership rate over the past five years--will be 
responsible for almost two-thirds of the growth in the number of new 
households over the next ten years. As these demographic factors 
play out, the overall effect on housing demand will likely be 
sustained growth and an increasingly diverse household population 
from which to draw new renters and homeowners.
     Despite the record national homeownership 
rate of 67.9 percent in 2002, much lower rates prevailed for 
minorities, especially for African-American households (47.9 
percent) and Hispanics (48.2 percent), and these lower rates are 
only partly accounted for by differences in income, age, and other 
socioeconomic factors.
     In addition to low incomes, barriers to 
homeownership that disproportionately affect minorities and 
immigrants include lack of capital for down payments and closing 
costs, poor credit history, lack of access to mainstream lenders, 
little understanding of the home buying process, and continued 
discrimination in housing markets and mortgage lending.
     A HUD-published study of discrimination in 
the rental and owner markets found that while differential treatment 
between minority and white home seekers had declined over the past 
ten years, it continued at an unacceptable level in the year 2000. 
In addition, disparities in mortgage lending continued across the 
nation in 2002, when the loan denial rate was 7.8 percent for white 
mortgage applicants, but 20.1 percent for African Americans and 15.5 
percent for Hispanics.\1\
---------------------------------------------------------------------------

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

     Americans with the lowest incomes face 
persistent housing problems. Recent HUD analysis reveals that in 
2001, 5.1 million households had ``worst case'' housing needs, 
defined as housing costs greater than 50 percent of household income 
or severely inadequate housing among unassisted very-low-income 
renter households. Among these households, 90 percent had a severe 
rent burden, 6 percent lived in severely inadequate housing, and 4 
percent suffered from both problems.

[[Page 24268]]

     Over the past ten years, there has been a 
``revolution in affordable lending'' that has extended homeownership 
opportunities to historically underserved households. Fannie Mae and 
Freddie Mac have been a substantial part of this ``revolution in 
affordable lending.'' During the mid-to-late 1990s, they added 
flexibility to their underwriting guidelines, introduced new low-
down-payment products, and worked to expand the use of automated 
underwriting in evaluating the creditworthiness of loan applicants. 
HMDA data suggest that the industry and GSE initiatives are 
increasing the flow of credit to underserved borrowers. Between 1993 
and 2002, conventional loans to low-income and minority families 
increased at much faster rates than loans to upper-income and non-
minority families.
     The Low- and Moderate-Income Goal was set at 
50 percent beginning in 2001. Effective on January 1, 2001, several 
changes in counting requirements came into effect, including (1) 
``bonus points'' (double credit) for purchases of mortgages on small 
(5-50 unit) multifamily properties and, above a threshold level, 
mortgages on 2-4 unit owner-occupied properties; and (2) a 
``temporary adjustment factor'' (1.35 unit credit) for Freddie Mac's 
purchases of mortgages on large (more than 50 units) multifamily 
properties. With these two counting rules, Fannie Mae's performance 
was 51.5 percent in 2001 and 51.8 percent in 2002, and Freddie Mac's 
performance was 53.2 percent in 2001 and 51.4 percent in 2002; thus, 
both GSEs surpassed this higher goal in both years.
     The bonuses and temporary adjustment factor 
expired at the end of 2003. Without these rules, Fannie Mae's 
performance would have been 51.3 percent in 2000, 49.2 percent in 
2001, and 49.0 percent in 2002. Freddie Mac's performance would have 
been 50.6 percent in 2000, 47.7 percent in 2001, and 46.5 percent in 
2002. Thus, both Fannie Mae and Freddie Mac would have surpassed the 
50 percent goal in 2000 and fallen short in 2001 and 2002.
     This Appendix includes a comprehensive 
analysis of each GSE's performance in funding home purchase 
mortgages for borrowers and neighborhoods covered by the three 
housing goals--special affordable and low- and moderate-income 
borrowers and underserved areas. In addition, the role of the GSEs 
in the first-time homebuyer market is examined. While Freddie Mac 
has improved its affordable lending performance in recent years, it 
has consistently lagged the conventional conforming market in 
funding affordable home purchase loans for borrowers and 
neighborhoods targeted by the housing goals. However, Freddie Mac's 
recent performance (1999-2002) has been much closer to the market 
than its earlier performance.
     In general, Fannie Mae's affordable lending 
performance has been better than Freddie Mac's. But like Freddie 
Mac, Fannie Mae's average performance during past periods (e.g., 
1993-2002, 1996-2002, 1999-2002) has been below market levels. 
However, it is encouraging that Fannie Mae markedly improved its 
affordable lending performance relative to the market during 2001 
and 2002, the first two years of HUD's higher housing goal levels. 
Fannie Mae's average performance during 2001 and 2002 approached the 
market on the special affordable and underserved areas categories 
and matched the market on the low-mod category. Under one measure of 
GSE and market activity, Fannie Mae matched the market during 2002 
on the special affordable category and slightly outperformed the 
market on the low-mod and underserved areas categories. In this 
case, which is referred to in the text as the ``purchase year'' 
approach, Fannie Mae's performance is based on comparing its 
purchases of all loans (both seasoned loans and newly-originated 
mortgages) during a particular year with loans originated in the 
market in that year. When Fannie Mae's performance is measured on an 
``origination year'' basis (that is, allocating Fannie Mae's 
purchases in a particular year to the year that the purchased-loan 
was originated), Fannie Mae matched the market in the low- and 
moderate-income category during 2002, and lagged the market slightly 
on the other two categories.
     Both Fannie Mae and Freddie lag the 
conventional conforming market in funding first-time homebuyers, and 
by a rather wide margin. Between 1999 and 2001, first-time 
homebuyers accounted for 27 percent of each GSE's purchases of home 
loans, compared with 38 percent for home loans originated in the 
conventional conforming market.
     The GSEs have accounted for a significant 
share of the total (government as well as conventional) market for 
home purchase loans, but their market share for each of the 
affordable lending categories (e.g., low-income borrowers and census 
tracts, high-minority census tracts) has been less than their share 
of the overall market.
     The GSEs also account for a very small share 
of the market for important groups such as minority first-time 
homebuyers. Considering the total mortgage market (both government 
and conventional loans), it is estimated that the GSEs purchased 
only 14 percent of loans originated between 1999 and 2001 for 
African-American and Hispanic first-time homebuyers, or one-third of 
their share (42 percent) of all home purchase loans originated 
during that period. Considering the conventional conforming market 
and the same time period, it is estimated that the GSEs purchased 
only 31 percent of loans originated for African-American and 
Hispanic first-time homebuyers, or approximately one-half of their 
share (57 percent) of all home purchase loans in that market. The 
GSEs' small share of the first-time homebuyer market could be due to 
the preponderance of high (over 20 percent) downpayment loans in 
their mortgage purchases.
     This Appendix discusses the dynamic nature of 
the single-family mortgage market and the numerous changes that that 
this market has undergone over the past few years. Some important 
trends that will likely factor into the GSEs' performance in meeting 
the needs of underserved borrowers include the growth of the 
subprime market, the increasing use of automated underwriting 
systems, and the introduction of risk-based pricing into the market.
     The long run outlook for the multifamily 
rental market is sustained, moderate growth, based on favorable 
demographics. The minority population, especially Hispanics, 
provides a growing source of demand for affordable rental housing. 
``Lifestyle renters'' (older, middle-income households) are also a 
fast-growing segment of the rental population. Provision of 
affordable housing, however, will continue to challenge suppliers of 
multifamily rental housing and policy makers at all levels of 
government. Low incomes combined with high housing costs define a 
difficult situation for millions of renter households. Housing cost 
reductions are constrained by high land prices and construction 
costs in many markets. Government action--through land use 
regulation, building codes, and occupancy standards--are major 
contributors to those high costs.
     The market for financing multifamily 
apartments has grown to record volumes. Fannie Mae and Freddie Mac 
have been among those boosting volumes and introducing new programs 
to serve the multifamily market. Fannie Mae's multifamily purchases 
jumped from about $10 billion in 1999 and 2000 to $18.7 billion 
during the heavy refinancing year of 2001, and $18.3 billion in 
2002.
     Freddie Mac has re-entered the multifamily 
market, after withdrawing for a time in the early 1990s. Concerns 
regarding Freddie Mac's multifamily capabilities no longer constrain 
its performance with regard to the housing goals. Freddie Mac's 
multifamily purchases increased from a relatively low $3 billion in 
1997 to approximately $7 billion during the next three years (1998 
to 2000), before rising further to $11.9 billion in 2001 and $13.3 
billion in 2002.
     The overall presence of both GSEs in the 
rental mortgage market falls short of their involvement in the 
single-family owner market. Between 1999 and 2002, the GSEs' 
purchases totaled for 57 percent of the owner market, but only 27 
percent of the single-family rental market and 30 percent of the 
multifamily market. Certainly there is room for expansion of the 
GSEs in supporting the nation's rental markets, and that expansion 
is needed if the GSEs are to make significant progress in closing 
the gaps between the affordability of their mortgage purchases and 
that of the overall conventional conforming market.
     Considering both owner and rental properties, 
the GSEs' presence in the goals-qualifying market has been 
significantly less than their presence in the overall conventional 
conforming mortgage market. Specifically, HUD estimates that the 
GSEs accounted for 49 percent of all owner and rental units financed 
in the primary market between 1999 and 2002, but only 32 percent of 
units qualifying for the low-mod goal, 41 percent of units 
qualifying for the underserved areas goal, and 35 percent of units 
qualifying for special affordable goal.

B. Factor 1: National Housing Needs

    This section reviews the general housing needs of lower-income 
families that exist today and are expected to continue in the

[[Page 24269]]

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

1. Homeownership Gaps

    Despite recent record homeownership rates, many Americans, 
including disproportionate numbers of racial and ethnic minorities, 
are shut out of homeownership opportunities. Although the national 
homeownership rate for all Americans stood at 68.3 percent at the 
end of 2003, the rate for minority households was lower--for 
example, just 48.5 percent of African-American households and 48.3 
percent of Hispanic households owned a home. Differences in income 
and age between minorities and whites do not fully explain these 
gaps. The Joint Center for Housing Studies estimated that if 
minorities owned homes at the same rates as whites of similar age 
and income, a homeownership gap of 10 percentage points would still 
exist.\2\
---------------------------------------------------------------------------

    \2\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2003, 2003, p. 16.
---------------------------------------------------------------------------

a. Importance of Homeownership

    Homeownership is one of the most common forms of property 
ownership as well as savings.\3\ Historically, home equity has been 
the largest source of wealth for most Americans, and wealth gains in 
housing have been more widely distributed among the population than 
gains in the stock market.\4\ With stocks appreciating faster than 
home prices over the past decade, home equity as a share of family 
assets fell from 38 percent in 1989 to 33 percent in 1998.\5\ Many 
of the gains in the stock market were erased after 1999 however, and 
housing returned to its place as the most significant asset in the 
household balance sheet in 2001.\6\ Even with a bull market through 
most of the 1990s, 59 percent of all homeowners in 1998 held more 
than half of their net wealth in the form of home equity.\7\ Among 
low-income homeowners (household income less than $20,000), home 
equity accounted for about 72 percent of household wealth, and 
approximately 55 percent for homeowners with incomes between $20,000 
and $50,000. Median net wealth for low-income homeowners under 65 
was twelve times that of a similar renter.\8\ Thus a homeownership 
gap continues to translate directly into a wealth gap.
---------------------------------------------------------------------------

    \3\ According to the National Association of Realtors, Housing 
Market Will Change in New Millennium as Population Shifts, November 
7, 1998. Forty-five percent of U.S. household wealth was in the form 
of home equity in 1998. Since 1968, home prices have increased each 
year, on average, at the rate of inflation plus two percentage 
points
    \4\ Todd Buchholz, ``Safe At Home: The New Role of Housing in 
the U.S. Economy,'' a paper commissioned by the Homeownership 
Alliance, 2002.
    \5\ Federal Reserve Board, ``Recent Changes in U.S. Family 
Finances: Results from the 1998 Survey of Consumer Finances,'' 
January 2000, p. 15.
    \6\ Mark Zandi, ``Housing's Rising Contribution,'' June 2002, p. 
5.
    \7\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 1998.
    \8\ U.S Department of Housing and Urban Development, ``Economic 
Benefits of Increasing Minority Homeownership,'' p. 7.
---------------------------------------------------------------------------

    High rates of homeownership support economic stability within 
housing and related industries, sectors that contributed nearly one-
half of the total gain in real GDP in 2001.\9\ In addition to 
economic benefits such as jobs and residential investment, studies 
show that the better living environment associated with owning a 
home has positive impacts on children, in terms of lower rates of 
teenage pregnancy and higher reading other test scores. The current 
literature substantiates that the benefits of homeownership extend 
beyond individual homeowners and their families to society at large. 
Homeownership promotes social and community stability by increasing 
the number of stakeholders and reducing disparities in the 
distributions of wealth and income. The empirical literature is 
generally supportive of a relationship between homeownership and 
greater investment in property.\10\ Homeownership is also associated 
with neighborhood stability (lower mobility), greater participation 
in voluntary and political activities,\11\ and links to 
entrepreneurship.\12\
---------------------------------------------------------------------------

    \9\ Mark Zandi, ``Housing's Rising Contribution,'' June 2002, p. 
3.
    \10\ Robert Dietz and Donald Haurin, ``The Social and Private 
Consequences of Homeownership,'' May 2001, p. 51.
    \11\ William M. Rohe, George McCarthy, and Shannon Van Zandt, 
``The Social Benefits and Costs of Homeownership,'' May 2000, p. 31.
    \12\ U.S. Department of Housing and Urban Development, 
``Economic Benefits of Increasing Minority Homeownership,'' p. 8-9.
---------------------------------------------------------------------------

b. Barriers to Homeownership \13\
---------------------------------------------------------------------------

    \13\ For a discussion of the causes of existing disparities in 
homeownership, see the various articles in Nicolas P. Retsinas and 
Eric S. Belsky (Eds), Low-Income Homeownership: Examining the 
Unexamined Goal, Washington, D.C.: Brookings Institution Press, 
2002.
---------------------------------------------------------------------------

    Insufficient income, high debt burdens, and limited savings are 
obstacles to homeownership for younger families. As home prices 
skyrocketed during the late 1970s and early 1980s, real incomes also 
stagnated, with earnings growth particularly slow for blue collar 
and less educated workers. Through most of the 1980s, the 
combination of slow income growth and increasing rents made saving 
for home purchase more difficult, and relatively high interest rates 
required large fractions of family income for home mortgage 
payments. Thus, during that period, fewer households had the 
financial resources to meet down payment requirements, closing 
costs, and monthly mortgage payments.
    Economic expansion and lower mortgage rates substantially 
improved homeownership affordability during the 1990s. Many young, 
low-income, and minority families who were closed out of the housing 
market during the 1980s re-entered the housing market during the 
last decade. Even with an economic slowdown in 2000-2001, 
improvements in affordability were seen in 2001 as lower interest 
rates and modest income growth reduced the average monthly mortgage 
payment from its year-ago level.\14\ However, many households still 
lack the earning power to take advantage of today's home buying 
opportunities. Several trends have contributed to the reduction in 
the real earnings of young adults without college education over the 
last 15 years, including technological changes that favor white-
collar employment, losses of unionized manufacturing jobs, and wage 
pressures exerted by globalization. Over 42 percent of the nation's 
population between the ages of 25 and 34 had no advanced education 
in 2000\15\ and were therefore at risk of being unable to afford 
homeownership. African Americans and Hispanics, who have lower 
average levels of educational attainment than whites, are especially 
disadvantaged by the erosion in wages among less educated workers.
---------------------------------------------------------------------------

    \14\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2002, p. 14.
    \15\ U.S. Census Bureau, Current Population Survey, March 2000.
---------------------------------------------------------------------------

    Immigrants and other minorities, who accounted for nearly 40 
percent of the growth in the homeownership rate over the past five 
years, will be responsible for two-thirds of the growth in new 
households over the next ten years. These groups have unique housing 
needs and face numerous hurdles in becoming homeowners. In addition 
to low income, barriers to homeownership that disproportionately 
affect minorities and immigrants include:
     Lack of capital for down payment and closing 
costs;
     Poor credit history;
     Lack of access to mainstream lenders;
     Complexity and fear of the home buying 
process; and,
     Continued discrimination in housing markets 
and mortgage lending.
    (i) Lack of Cash for Down Payment. In the 2002 Fannie Mae 
National Housing Survey, 40 percent of Hispanics reported not having 
enough money for a down payment as an obstacle to buying a home 
versus 32 percent of all Americans.\16\ A study by Gyourko, 
Linneman, and Wachter found significant racial differences in 
homeownership rates in ``wealth-constrained'' households while 
finding no racial differences in homeownership rates among 
households with wealth sufficient to meet down payment and closing 
costs.\17\ Minorities and immigrants are much less likely to receive 
gifts and inheritances from their parents to assist them in becoming 
a homeowner.
---------------------------------------------------------------------------

    \16\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 
11.
    \17\ Joseph Gyourko, Peter Linneman, and Susan Wachter. 
``Analyzing the Relationships among Race, Wealth, and Home Ownership 
in America,'' Journal of Housing Economics 8 (2), p. 63-89, as 
discussed in Thomas P. Boehm and Alan M. Schlottmann. ``Housing and 
Wealth Accumulation: Intergenerational Impacts,'' in Low-Income 
Homeownership: Examining the Unexamined Goal, Brookings Institution 
Press (2002), p. 408.
---------------------------------------------------------------------------

    (ii) Poor Credit History. Poor credit history also 
differentially affects minority

[[Page 24270]]

households. In the same Fannie Mae survey, nearly a third of 
African-American respondents said their credit rating would be an 
obstacle to buying a home versus 23 percent of all Americans.\18\ 
Because African-American and Hispanic borrowers are more likely than 
others to have little traditional credit history or a poorer credit 
history, they face increased difficulties in being accepted for 
mortgage credit. This is because credit history scores (such as a 
FICO score) are a major component of the new automated mortgage 
scoring systems. These systems are more likely to refer minority 
borrowers for more intensive manual underwriting, rather than to 
automatically accept them for the less costly, expedited processing. 
In these situations, there is the additional concern that 
``referred'' borrowers may not always receive a manual underwriting 
for the loan that they initially applied for, but rather be directed 
to a high-cost subprime loan product.
---------------------------------------------------------------------------

    \18\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 
11.
---------------------------------------------------------------------------

    (iii) Lack of Access to Mainstream Lenders. Minorities face 
heightened barriers in accessing credit because of their often 
limited access to mainstream lenders. Access to lenders becomes 
difficult when mainstream financial institutions are not located in 
neighborhoods where minorities live. The growth in subprime lending 
over the last several years has benefited credit-impaired 
borrowers--those who may have blemishes in their credit record, 
insufficient credit history, or non-traditional credit sources. 
Subprime lenders have allowed these borrowers to access credit that 
they could not otherwise obtain in the prime credit market. However, 
studies by HUD, The Woodstock Institute and others have shown that 
subprime lending is disproportionately concentrated in low-income 
and minority neighborhoods.\19\ While these studies recognize that 
differences in credit behavior explain some of the disparities in 
subprime lending across neighborhoods, they argue that the absence 
of mainstream lenders has also contributed to the concentration of 
subprime lending in low-income and minority neighborhoods. More 
competition by prime lenders in inner city neighborhoods could lower 
the borrowing costs of families who currently have only the option 
of a high-cost subprime loan. This issue of the lack of mainstream 
lenders in inner city neighborhoods is discussed further in 
subsection 2, below, in connection with disparities between 
neighborhoods.
---------------------------------------------------------------------------

    \19\ See Dan Immergluck, Stark Differences: The Explosion of the 
Subprime Industry and Racial Hypersegmentation in Home Equity 
Lending. Woodstock Institute, October 2000; and Daniel Immergluck 
and Marti Wiles, Two Steps Back: The Dual Mortgage Market, Predatory 
Lending, and the Undoing of Community Development, Woodstock 
Institute, Chicago, IL, November 1999. For a national analyses, see 
the HUD report Unequal Burden: Income and Racial Disparities in 
Subprime Lending in America, April 2000; and Randall M. Scheessele, 
Black and White Disparities in Subprime Mortgage Refinance Lending, 
Housing Finance Working Paper No. HF-114, Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, April 2002.
---------------------------------------------------------------------------

    (iv) Complexity and Fear of Home Buying Process. An additional 
barrier to homeownership is fear and a lack of understanding about 
the buying process and the risks of ownership. Many Americans could 
become homeowners if provided with information to correct myths, 
misinformation, and concerns about the mortgage process. Some 
potential homeowners, particularly minorities, are unaware that they 
may already qualify for a mortgage they can afford. The 2002 Fannie 
Mae survey revealed that 30 percent of Americans believe erroneously 
that they need to pay 20 percent of the cost of a home up-front. In 
addition, Fannie Mae reported that half of Americans are only 
``somewhat'' or ``not at all'' comfortable with mortgage terms.\20\ 
Freddie Mac reports that six of 10 Hispanics are uncomfortable with 
home buying terminology, and think they need ``perfect credit'' to 
buy; and less than four in 10 are aware that lenders are not 
required by law to give them the lowest interest rate possible.\21\ 
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.\22\
---------------------------------------------------------------------------

    \20\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 9.
    \21\ See ``Immigration Changes Won't Hurt Housing,'' in National 
Mortgage News, January 27, 2003, page 8.
    \22\ Donald S. Bradley and Peter Zorn, ``Fear of Homebuying: Why 
Financially Able Households May Avoid Ownership,'' Secondary 
Mortgage Markets, 1996.
---------------------------------------------------------------------------

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

2. Disparities in Housing and Mortgage Markets

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

    \23\ Margery Austin Turner, Stephen L. Ross, George Galster, and 
John Yinger, ``Discrimination in Metropolitan Housing Markets,'' The 
Urban Institute Press, November 2002.
---------------------------------------------------------------------------

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

    \24\ Martin D. Abravanel and Mary K. Cunningham, How Much Do We 
Know? Public Awareness of the Nation's Fair Housing Laws. A report 
prepared for HUD by the Urban Institute, Washington, DC, April 2002.
---------------------------------------------------------------------------

    Mortgage Lending Market. Research based on Home Mortgage 
Disclosure Act (HMDA) data suggests pervasive and widespread 
disparities in mortgage lending across the Nation. For 2001, the 
mortgage denial rate for white mortgage applicants was 23 percent, 
while 36 percent of African-American and 35 percent of Hispanic 
applicants were denied.
    Two recent HUD-sponsored studies of paired-testing at the 
mortgage pre-application stage also points to discrimination by 
mortgage lenders. Based on its review of pair tests conducted by the 
National Fair Housing Alliance, the Urban Institute concluded that 
differential treatment discrimination at the pre-application level 
occurred at significant levels in at least some cities.\25\ 
Minorities were less likely to receive information about loan 
products, received less time and information from loan officers, and 
were quoted higher interest rates in most of the cities where tests 
were conducted. A second HUD-sponsored study by the Urban Institute 
used the paired testing methodology in Los Angeles and Chicago and 
found similar results. African Americans and Hispanics faced a 
significant risk of unequal treatment when they visited mainstream 
mortgage lending institutions to make pre-application inquiries.\26\
---------------------------------------------------------------------------

    \25\ Margery Austin Turner, John Yinger, Stephen Ross, Kenneth 
Temkin, Diane Levy, David Levine, Robin Ross Smith, and Michelle 
deLair, What We Know About Mortgage Lending Discrimination. The 
Urban Institute, contract report for the Department of Housing and 
Urban Development, December 1998.
    \26\ Margery Austin Turner, All Other Things Being Equal: A 
Paired Testing Study of Mortgage Lending Institutions, The Urban 
Institute Press, April 2002.

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

[[Page 24271]]

    Several possible explanations for these lending disparities have 
been suggested. A study by the Boston Federal Reserve Bank found 
that racial disparities cannot be explained by reported differences 
in creditworthiness.\27\ In other words, minorities are more likely 
to be denied than whites with similar credit characteristics, which 
suggests lender discrimination. In addition, loan officers, who may 
believe that race is correlated with credit risk, may use race as a 
screening device to save time, rather than devote effort to 
distinguishing the creditworthiness of the individual applicant.\28\ 
This violates the Fair Housing Act.
---------------------------------------------------------------------------

    \27\ Alicia H. Munnell, Geoffrey M.B. Tootell, Lynn E. Browne, 
and James McEneaney, ``Mortgage Lending in Boston: Interpreting HMDA 
Data,'' American Economic Review, 86, March 1996.
    \28\ See Charles W. Calomeris, Charles M. Kahn and Stanley D. 
Longhofer, ``Housing Finance Intervention and Private Incentives; 
Helping Minorities and the Poor,'' Journal of Money, Credit and 
Banking, 26, August 1994, pp. 634-74, for more discussion of this 
phenomenon, which is called ``statistical discrimination''
---------------------------------------------------------------------------

    Underwriting rigidities may fail to accommodate creditworthy 
low-income or minority applicants. For example, under traditional 
underwriting procedures, applicants who have conscientiously paid 
rent and utility bills on time but have never used consumer credit 
would be penalized for having no credit record. Applicants who have 
remained steadily employed, but have changed jobs frequently, would 
also be penalized. As discussed in Section C below, lenders, private 
mortgage insurers, and the GSEs have been adjusting their 
underwriting guidelines to take into account these special 
circumstances of lower-income families. Many of the changes recently 
undertaken by the industry focused on finding alternative 
underwriting guidelines to establish creditworthiness that do not 
disadvantage creditworthy minority or low-income applicants. 
However, because of the enhanced roles of credit scoring and 
automated underwriting in the mortgage origination process, it is 
unclear to what degree the reduced rigidity in industry standards 
will benefit borrowers who have been adversely impacted by the 
traditional guidelines as discussed in section C.7, some industry 
observers have expressed a concern that the greater flexibility in 
the industry's written underwriting guidelines may not be reflected 
in the numerical credit and mortgage scores which play a major role 
in the automated underwriting systems that the GSEs and others have 
developed.
    Disparities Between Neighborhoods. Mortgage credit also appears 
to be less accessible in low-income and high-minority neighborhoods. 
As discussed in Appendix B, 2001 HMDA data show that mortgage denial 
rates are nearly twice as high in census tracts with low-income and/
or high-minority composition, as in other tracts (16.8 percent 
versus 8.7 percent). Numerous studies have found that mortgage 
denial rates are higher in low-income census tracts, even accounting 
for other loan and borrower characteristics.\29\ These geographical 
disparities can be the result of cost factors, such as the 
difficulty of appraising houses in these areas because of the 
paucity of previous sales of comparable homes. Sales of comparable 
homes may also be difficult to find due to the diversity of central 
city neighborhoods. The small loans prevalent in low-income areas 
are less profitable to lenders because up-front fees to loan 
originators are frequently based on a percentage of the loan amount, 
although the costs incurred are relatively fixed. As noted above, 
racial disparities in mortgage access may be due to the fact that 
mainstream lenders are not doing business in certain inner city 
neighborhoods. There is evidence that mainstream lenders active in 
white and upper-income neighborhoods are much less active in low-
income and minority neighborhoods--often leaving these neighborhoods 
to unregulated subprime lenders. Geographical disparities in 
mortgage lending are discussed further in Section C.8 below (which 
examines subprime lending) and in Appendix B (which examines the 
Underserved Areas Goal).
---------------------------------------------------------------------------

    \29\ Robert B. Avery, Patricia E. Beeson and Mark E. Sniderman, 
Understanding Mortgage Markets: Evidence from HMDA, Working Paper 
Series 94-21, Federal Reserve Bank of Cleveland, December 1994.
---------------------------------------------------------------------------

3. Affordability Problems and Worst Case Housing Needs

    The severe affordability problems faced by low-income homeowners 
and renters are documented in HUD's ``Worst Case Housing Needs'' 
reports. These reports, which are prepared biennially for Congress, 
are based on the American Housing Survey (AHS), conducted every two 
years by the Census Bureau for HUD. The latest detailed report 
analyzes data from the 1999 AHS. Although it focuses on the housing 
problems faced by very-low-income renters, it also presents basic 
data on families and households in owner-occupied housing.\30\
---------------------------------------------------------------------------

    \30\ HUD has published an update on ``worst case housing 
needs,'' which found that the number of such households rose from 
4.86 million in 1999 to 5.07 million in 2001. However, detailed 
tables for 2001 have not been published.
---------------------------------------------------------------------------

    The ``Worst Case'' report measures three types of problems faced 
by homeowners and renters:
    1. Cost or rent burdens where housing costs or rent exceed 50 
percent of income (a ``severe burden'') or range from 31 percent to 
50 percent of income (a ``moderate burden'');
    2. The presence of physical problems involving plumbing, 
heating, maintenance, hallway, or the electrical system, which may 
lead to a classification of a residence as ``severely inadequate'' 
or ``moderately inadequate;'' and,
    3. Crowded housing, where there is more than one person per room 
in a residence.
    The study reveals that in 1999, 4.9 million households had 
``worst case'' housing needs, defined as housing costs greater than 
50 percent of household income or severely inadequate housing among 
unassisted very-low-income renter households. Among the 34 million 
renters in all income categories, 6.3 million (19 percent) had a 
severe rent burden and over one million renters (3 percent) lived in 
housing that was severely inadequate.

a. Problems Faced by Owners

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

    \31\ Very-low-income households are defined as those whose 
income, adjusted for household size, does not exceed 50 percent of 
HUD-adjusted area median income. This differs from the definition 
adopted by Congress in the GSE Act of 1992, which uses a cutoff of 
60 percent and which does not adjust income for family size for 
owner-occupied dwelling units.
---------------------------------------------------------------------------

    Over time the percentage of owners faced with severe or moderate 
physical problems has decreased, as has the portion living in 
overcrowded conditions. However, affordability problems have become 
more common--the shares facing severe (moderate) cost burdens were 
only 3 percent (5 percent) in 1978, but rose to 5 percent (11 
percent) in 1989 and 8 percent (13 percent) in 1999. The increase in 
affordability problems apparently reflects a rise in mortgage debt 
in the late 1980s and early 1990s, from 21 percent of homeowners' 
equity in 1983 to 36 percent in 1995.\32\ 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.\33\ As a result of the increased incidence of severe and 
moderate cost burdens, the share of owners reporting no problems 
fell from 84 percent in 1978 to 78 percent in 1989 and 75 percent in 
1999.
---------------------------------------------------------------------------

    \32\ Edward N. Wolff, ``Recent Trends in the Size Distribution 
of Household Wealth,'' The Journal of Economic Perspectives, 12(3), 
(Summer 1998), p. 137.
    \33\ Joint Center for Housing Studies, The State of the Nation's 
Housing: 2000, June 2000, p. 24.
---------------------------------------------------------------------------

b. Problems Faced by Renters

    Problems of all three types listed above are more common among 
renters than among homeowners. In 1999 there were 6.3 million renter 
households (19 percent of all renters) who paid more than 50 percent 
of their income for rent.\34\ Another 7.1 million faced a moderate 
rent burden. Thus in total 40 percent of renters paid more than 30 
percent of their income for rent.
---------------------------------------------------------------------------

    \34\ Rent is measured in this report as gross rent, defined as 
contract rent plus the cost of any utilities that are not included 
in contract rent.
---------------------------------------------------------------------------

    Among very-low-income renters, 71 percent faced an affordability 
problem, including 40 percent who paid more than half of their 
income in rent. Almost one-third (31 percent) of renters with 
incomes between 51 percent and 80 percent of area median

[[Page 24272]]

family income also paid more than 30 percent of their income for 
rent.
    Affordability problems have increased over time among renters. 
The shares of renters with severe or moderate rent burdens rose from 
32 percent in 1978 to 36 percent in 1989 and 40 percent in 1999.
    The share of households living in inadequate housing in 1999 was 
higher for renters (11 percent) than for owners (4 percent), as was 
the share living in overcrowded housing (5 percent for renters, but 
only 1 percent for owners). Crowding and inadequate housing were 
more common among lower-income renters, but among even the lowest 
income group, affordability was the dominant problem. The prevalence 
of inadequate and crowded rental housing diminished over time until 
1995, while affordability problems grew.
    Other problems faced by renters discussed in the most recent 
detailed ``Worst Case'' report include a sharp decline (of 2.3 
million, or 14 percent) between 1991 and 1999 in the number of 
rental units affordable to very-low-income families, and a worsening 
of the national shortage of units affordable and available to 
extremely-low-income families (those with incomes below 30 percent 
of area median income). Shortages of units affordable and available 
to extremely-low-income households were most pressing in the West 
and Northeast, especially in metropolitan areas in those regions.

4. Rehabilitation and Other National Housing Needs

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

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

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

1. Recent Trends in the Housing Market

    While most other sectors of the economy were weak or declining 
during 2001 and 2002, the housing sector showed remarkable strength. 
Despite the recession in 2001, factors such as record-low interest 
rates and continued price stability contributed to a record year in 
the housing market. In 2002, the U.S. economy moved into recovery 
with real GDP growing 2.4 percent. In October 2002, the 30-year home 
mortgage rate slipped below 6 percent for the first time since the 
mid-1960s. Favorable financing conditions and solid increases in 
house prices were the key supports to another record housing market 
during 2002. In fact, the year 2002 was among the strongest years 
experienced by the housing industry. By the end of 2002 the industry 
set many new records in single-family permits, new home sales, 
existing home sales, interest rates, and homeownership. Other 
indicators--total permits, starts, completions, and affordability--
reached levels that were among the highest in the past two decades.
    Single-Family Permits, Starts, and Completions. Builders took 
out 1,319,100 single-family permits in 2002, up 6.8 percent from 
2001. The 2002 level was the highest number of single-family permits 
ever reported in the 43-year history of this series. Single-family 
starts totaled 1,359,700 housing units, up 6.8 percent from 2001, 
and the highest number of single-family starts since 1978. 
Construction was completed on 1,328,400 single-family housing units, 
up 5.8 percent from 2001. This is the highest number of single-
family completions in 24 years.
    Sales of New and Existing Homes. After leveling out in 2000, 
housing sales have boomed in the past two years, reaching a record 
high in 2001 and again in 2002. New home sales, which increased an 
average 6.3 percent per year between 1992 and 2002, reached a record 
high of 976,000 units in 2002, an increase of 7.5 percent over 2001 
sales. The market for new homes has been strong throughout the 
nation.
    The National Association of Realtors reported that nearly 5.6 
million existing homes were sold in 2002, overturning the old record 
set in 2001 by 5 percent, and setting an all-time high in the 34-
year history of the series. Sales of existing homes reached record 
levels in three of the four major regions of the nation and came 
within 96 percent of the record in the Northeast in 2001. Combined 
new and existing home sales also set a national record of 6.2 
million last year.
    One of the strongest sectors of the housing market in past years 
had been manufactured homes, but that sector has declined recently. 
Between 1991 and 1996, manufactured home shipments more than 
doubled, peaking in 1998 at 373,000. However, shipments fell more 
than 20 percent in both 2000 and 2001. In 2002, the industry shipped 
169,000 new manufactured homes, down 12.4 percent from 2001. This 
was the lowest number of manufactured home shipments since 1963.
    Homeownership Rate. In 1980, 65.6 percent of Americans owned 
their own home, but due to the unsettled economic conditions of the 
1980s, this share fell to 63.8 percent by 1989. But since 1994, 
gains in the homeownership rate have occurred in each year, with the 
rate reaching another record mark of 67.9 percent in 2002. The 
number of households owning their own home in 2002 was 10.6 million 
greater than in 1994.
    Gains in homeownership have been widespread over the last eight 
years.\35\ As a result, the homeownership rate rose from:
---------------------------------------------------------------------------

    \35\ Homeownership rates prior to 1993 are not strictly 
comparable with those beginning in 1993 because of a change in 
weights from the 1980 Census to the 1990 Census.
---------------------------------------------------------------------------

     42.0 percent in 1993 to 47.9 percent in 2002 
for African-American households,
     39.4 percent in 1993 to 48.2 percent in 2002 
for Hispanic households,
     73.7 percent in 1993 to 78.9 percent in 2002 
for married couples with children,
     65.1 percent in 1993 to 68.6 percent in 2002 
for household heads aged 35-44, and
     48.9 percent in 1993 to 51.8 percent in 2002 
for central city residents.
    However, as these figures demonstrate, sizable gaps in 
homeownership remain.
    Economy/Housing Market Prospects. The economy grew at a rate of 
2.2 percent in 2002 and was less robust than in past U.S. 
recoveries.\36\ In response, the Federal Reserve has lowered 
interest rates to record lows, supporting housing affordability.
---------------------------------------------------------------------------

    \36\ National Association of Realtors, ``Near Record Home Sales 
Projected for 2003,'' December 3, 2002.
---------------------------------------------------------------------------

    The Blue Chip consensus forecast for real GDP growth is 4.2 
percent for 2004.\37\ The Congressional Budget Office (CBO) \38\ 
projects

[[Page 24273]]

that real GDP will grow at an average rate of 3.3 percent from 2005 
through 2008, down from their forecasted rate of 3.8 percent in 
2004. Inflation, as measured by the Consumer Price Index (CPI), is 
projected to remain modest during the same period, averaging 2.5 
percent. The unemployment rate is expected to ease from 2003-2004 
levels, averaging 5.4 percent over the forecast period. The 
remainder of this subsection focuses on future prospects for the 
housing market.
---------------------------------------------------------------------------

    \37\ Blue Chip Economic Indicators, Vol. 28, No. 11, November 
10, 2003.
    \38\ Real GDP, unemployment, inflation, and treasury note 
interest rate projections are obtained for fiscal years 2003-2013 
from The Budget and Economic Outlook: An Update, Washington, DC 
Congressional Budget Office. (August 2003). http://www.cbo.gov/showdoc.cfm.
---------------------------------------------------------------------------

    Fannie Mae expects existing home sales to reach a record level 
of 6 million in 2003 and decline only slightly to 5.7 million in 
2004 and 2005.\39\ Projected at 1.84 million in 2003, the National 
Association of Home Builders expects housing starts to decline to 
1.77 million in 2004 and 1.71 million in 2005.\40\ The Mortgage 
Bankers Association forecasts that 2004 housing starts will total 
1.73 million units and the 30-year fixed mortgage rate will average 
6.1 percent.\41\ After more than doubling from a relative trough in 
2000 to an estimated $2.6 trillion in 2002, Fannie Mae forecasts 
that mortgage originations will rise to a record high $3.7 trillion 
in 2003 before dropping to $1.8 trillion in 2004 and $1.5 trillion 
in 2005.\42\
---------------------------------------------------------------------------

    \39\ Fannie Mae, ``Berson's Economic and Mortgage Market 
Development Outlook,'' December 2003. http://www.fanniemae.com/media/pdd/berson/monthly2003/121203.pdf.
    \40\ http://www.nahb.org.
    \41\ Mortgage Bankers Association of America, Mortgage Finance 
Forecast, December 17, 2003. http://www.mbaa.org/marketdata/forecasts/mffore1103.pdf.
    \42\ Fannie Mae, ``Berson's Economic and Mortgage Market 
Development Outlook,'' December 2003.
---------------------------------------------------------------------------

2. Underlying Demographic Conditions

    Between 2000 and 2025, the U.S. population is expected to grow 
by an average of 2.5 million per year.\43\ This will likely result 
in 1.1 million new households per year, increasing the number of 
households 26 percent in the period, and creating a continuing need 
for additional housing.\44\ This section discusses important 
demographic trends behind these overall household numbers that will 
likely affect housing demand in the future. These demographic forces 
include the baby-boom, baby-bust and echo baby-boom cycles; 
immigration trends; non-traditional and single households; ``trade-
up buyers;'' and the growing income inequality between people with 
different levels of education. HUD's Office of Policy Development 
and Research funded a study, Issue Papers on Demographic Trends 
Important to Housing, which analyzes effects of demographic 
conditions on the housing market. The findings are presented 
throughout the sections that follow.\45\
---------------------------------------------------------------------------

    \43\ U.S. Census Bureau, Population Projections Table NP-T1.
    \44\ Martha Farnsworth Riche, ``How Changes in the Nation's Age 
and Household Structure Will Reshape Housing Demand in the 21st 
Century,'' in Issue Papers on Demographic Trends Important to 
Housing, Urban Institute Final Report to the Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, September 2002, p. 5.
    \45\ Barry Chiswick, Paul Miller, George Masnick, Zhu Xiao Di, 
and Martha Farnsworth Riche, Issue Papers on Demographic Trends 
Important to Housing. Urban Institute Final Report to the Office of 
Policy Development and Research, U.S. Department of Housing and 
Urban Development, September 2002.
---------------------------------------------------------------------------

    As explained below, the role of traditional first-time 
homebuyers, 25-to-34 year-old married couples, in the housing market 
will be smaller in the current decade due to the aging of the 
population. For the first time in history, the population will have 
roughly equal numbers of people in every age group. Between 2000 and 
2025, the Census Bureau projects that the largest growth in 
households will occur among householders 65 and over.\46\ Thus, an 
increasing percentage of the population will be past their 
homebuying peak in the next two decades. However, because 
homeownership rates do not peak until population groups reach 65 to 
74 years of age, this age cohort will continue to provide housing 
demand. According to Riche, the increasing presence of older 
households should increase the proportion of the population that 
owns, rather than rents housing.\47\
---------------------------------------------------------------------------

    \46\ Martha Farnsworth Riche, ``How Changes in the Nation's Age 
and Household Structure Will Reshape Housing Demand in the 21st 
Century,'' in Issue Papers on Demographic Trends Important to 
Housing. Urban Institute Final Report to the U.S. Department of 
Housing and Urban Development, September 2002, p. 4.
    \47\ Ibid. p. 6.
---------------------------------------------------------------------------

    Growing housing demand from immigrants and non-traditional 
homebuyers will help to offset declines in the demand for housing 
caused by the aging of the population. Riche's study estimates that 
minorities will account for two-thirds of the growth in U.S. 
households over the next 25 years, and by 2025, non-family 
households will make up a third of all households. The ``echo baby-
boom'' (that is, children of the baby-boomers) will also add to 
housing demand in the current and next decades. Finally, the growing 
income inequality between people with and without a post-secondary 
education will continue to affect the housing market.
    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.\48\
---------------------------------------------------------------------------

    \48\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 1998, p. 14.
---------------------------------------------------------------------------

    As the youngest of the baby-boomers (those born in the 1960s) 
reached their peak home buying years in the 1990s, housing became 
more affordable. While this cohort has achieved a homeownership rate 
equal to the middle baby-boomers, they live in larger, more 
expensive homes. As the baby-boom generation ages, demand for 
housing from this group is expected to wind down.\49\
---------------------------------------------------------------------------

    \49\ Ibid. p. 15.
---------------------------------------------------------------------------

    The baby-boom generation was followed by the baby-bust 
generation, from 1965 through 1977. Since this population cohort is 
smaller than that of the baby boom generation, it reduced housing 
demand in the preceding decade and is expected to do the same in the 
current decade, though, as discussed below, other factors kept the 
housing market very strong in the 1990s. However, the echo baby-boom 
generation (the children of the baby-boomers, who were born after 
1977), while smaller than the baby-boom generation, will reach peak 
home buying age later in the first decade of the millennium.
    Immigrant Homebuyers. Past, present, and future immigration will 
also contribute to gains in the homeownership rate. During the 
1990s, 9.8 million legal immigrants entered the United States, as 
compared to 6.3 million entering in the 1980s and 4.2 million during 
the 1970s. Overall, the increase in the immigrant population 
directly accounted for 35 percent of the nation's rise in population 
in the 1990s.\50\ As a result, the foreign-born population of the 
United States more than tripled from 9.6 million in 1970 to 31.1 
million in 2000. Immigrants who become citizens buy homes at rates 
nearly as high as their same-aged native-born counterparts. 
Moreover, U.S.-born children of immigrants often have higher 
homeownership rates than the same-age children of native-born 
parents.\51\ However, there are concerns about the assimilation into 
homeownership of recent Hispanic immigrants who are less educated 
than earlier cohorts of immigrants. Many immigrants also locate in 
high-priced housing markets, which makes it more difficult for them 
to achieve homeownership.
---------------------------------------------------------------------------

    \50\ Federation for American Immigration Reform, < http://www.fairus.org/html/042us604.htm#ins , site visited 
December 13, 2002.
    \51\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2002, pp. 16-17.
---------------------------------------------------------------------------

    Although net foreign immigration is projected to decline in the 
current decade after 2002, high levels of immigration in the late 
1980s and throughout the 1990s will have lasting positive effects on 
housing demand. New immigration in the current and next decades is 
projected to create 6.9 million net new households, but the majority 
of household growth in the period (16.9 million) will come from 
people already resident in the U.S. including the foreign-born 
population.\52\ While immigrants tend to rent their first homes upon 
arriving in the United States, homeownership rates are substantial 
for those that have lived here for at least 6 years. In 1996, the 
homeownership

[[Page 24274]]

rate for recent immigrants was 14.7 percent while it was 66.9 
percent for foreign-born naturalized citizens after six years.\53\ 
Higher-than-average foreign-born fertility rates and high rates of 
homeownership for immigrants living in the country for several years 
and among the children of immigrants suggest that past immigration 
will continue to create housing demand.
---------------------------------------------------------------------------

    \52\ George S. Masnick and Zhu Xiao Di, ``Projections of U.S. 
Households By Race/Hispanic Origin, Age, Family, Type, and Tenure to 
2020: A Sensitivity Analysis,'' in Issue Papers on Demographic 
Trends Important to Housing. Urban Institute Final Report to the 
U.S. Department of Housing and Urban Development, September 2002, p. 
5.
    \53\ Fred Flick and Kate Anderson, ``Future of Housing Demand: 
Special Markets,'' Real Estate Outlook, 1998, p. 6.
---------------------------------------------------------------------------

    Past and future immigration will lead to increasing racial and 
ethnic diversity, especially among the young adult population. As 
immigrant minorities account for a growing share of first-time 
homebuyers in many markets, HUD and others will have to intensify 
their focus on removing discrimination from the housing and mortgage 
finance systems. The need to meet nontraditional credit needs, 
respond to diverse housing preferences, and overcome the information 
barriers that many immigrants face will take on added importance. In 
order to address these needs, the mortgage industry must offer 
innovative products and improve outreach efforts to attract minority 
homebuyers.
    Nontraditional and Single Homebuyers. While overall growth in 
new households has slowed down, nontraditional households have 
become more important in the homebuyer market. As the population 
ages both relatively and absolutely, the nation's households will 
become smaller and more diverse. Riche notes that in 2000, 
traditional family households represented fewer than one in four 
households and were surpassed by both single-person households and 
married couples without children. With later marriages and more 
divorces, single-parent and single-person households have increased 
rapidly. In fact, single-parent households grew from 4 percent of 
family households in 1950 to 12 percent in 2000. Single-person 
households are now the nation's second most numerous household type, 
accounting for over 25 percent of all households. In the future, 
longer life expectancies and the continuing preference for one or 
two children will make households without children even more 
numerous. Projected to compose 80 percent of all households by 2025, 
nontraditional family households will play an increasingly important 
role in the housing market.\54\
---------------------------------------------------------------------------

    \54\ Riche, 2002, p. 1.
---------------------------------------------------------------------------

    Trade-up Buyers. Due to weak house price appreciation, 
traditional ``trade-up buyers'' stayed out of the market during the 
early 1990s. Their absence may explain, in part, the large 
representation of nontraditional homebuyers during that period. 
However, since 1995 home prices have increased more than 30 
percent.\55\ The greater equity resulting from recent increases in 
home prices should lead to a larger role for ``trade-up buyers'' in 
the housing market during the next 10 to 15 years. In addition, the 
growing number of higher-income, mid-life households will increase 
households' potential to ``trade up'' to more expensive housing.\56\
---------------------------------------------------------------------------

    \55\ Average new-home price: U.S. Census Bureau, < http://www.census.gov/const/uspriceann.pdf 
    \56\ Riche, 2002, p.17.
---------------------------------------------------------------------------

    Growing Income Inequality. The Census Bureau recently reported 
that the top 5 percent of American households received 22.4 percent 
of aggregate household income in 2001, up from 21.4 percent in 1998 
and up sharply from 16.1 percent in 1977. The share accruing to the 
lowest 80 percent of households fell from 56.5 percent in 1977 to 
50.8 percent in 1998 and again to 49.8 percent in 2001. The share of 
aggregate income accruing to households between the 80th and 95th 
percentiles of the income distribution was virtually unchanged from 
1977 to 2001.\57\
---------------------------------------------------------------------------

    \57\ All data in this paragraph are from the U.S. Census 
Bureau's Historical Income Table H2.
---------------------------------------------------------------------------

    The increase in income inequality over past decades has been 
especially significant between those with and those without post-
secondary education. The Census Bureau reports that by 1999, the 
annual earnings of workers with a bachelor's degree were 1.8 times 
the annual earnings of workers with a high school education.\58\ The 
inflation-adjusted median earnings of high school graduates were at 
the same level in 2001 as in 1991 while the earnings of bachelor 
degree-holders rose nearly 9 percent over the same period.\59\
---------------------------------------------------------------------------

    \58\ Jennifer Cheeseman Day and Eric C. Newburger, The Big 
Payoff: Educational Attainment and Synthetic Estimates of Work-Life 
Earnings, U.S. Bureau of the Census, Current Population Reports P23-
210, July 2002, p.3.
    \59\ U.S. Census Bureau, Historical Income Table H13.
---------------------------------------------------------------------------

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

3. Basic Trends in the Single-Family Mortgage Market

    Mortgage lending in the nation is growing at unprecedented 
levels. Residential mortgage originations soared to $2.5 trillion in 
2002, a 22 percent increase over the previous record of $2.06 
trillion set in 2001.\60\ This boom in lending can be attributed to 
low mortgage interest rates and a record number of refinances. 
Approximately 40 percent of mortgage debt outstanding, or $2.5 
trillion, was refinanced during the 2001-02 refinance boom. The last 
refinancing record was set in 1998 when roughly 20 percent of 
mortgage debt outstanding was refinanced.\61\ This section focuses 
on recent interest rate trends, the refinance market, the home 
purchase market, and first-time homebuyers. The section concludes by 
examining the GSEs' acquisitions as a share of the primary single-
family mortgage market, and provides mortgage market prospects.
---------------------------------------------------------------------------

    \60\ ``Mortgage Originations Hit Record-Busting $2.5 Trillion in 
2002, IMF Numbers Reveal,'' Inside Mortgage Finance, January 24, 
2003, p. 3.
    \61\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 2.
---------------------------------------------------------------------------

a. Mortgage Characteristics

    Interest Rate Trends and Volatility. Historically low mortgage 
interest rates in the late 1990s and 2001-2003 helped maintain 
consumer confidence in the housing sector as the economy emerged 
from its first recession in almost a decade. After high and 
fluctuating mortgage rates in the 1980s and early 1990s, recent 
years have seen a period of lower and more stable rates. The 1980s 
began with interest rates on mortgages for new homes above 12 
percent but quickly rose to more than 15 percent.\62\ By 1987-88, 
rates dipped into single digits but were rising again by 1989-90. 
Rates declined in the early 1990s, reaching a low of 6.8 percent in 
late 1993. An upturn in rates in 1994 and 1995 peaked at 8.3 percent 
in early 1995. By 1998, 30-year fixed conventional mortgages 
averaged 6.95 percent, the lowest level since 1968 but saw a rise in 
1999 to 7.44 percent. Mortgage rates then continued to rise in 2000, 
averaging 8.05 percent for the year, before falling to a low of 6.62 
percent in October 2001 and averaging 6.97 percent for 2001 as a 
whole.\63\ Rates averaged 6.54 percent during 2002, reaching a low 
of 6.05

[[Page 24275]]

percent in December of that year. Falling further to 5.23 in June of 
2003, mortgage interest rates remained low throughout last year, 
averaging 5.79 through September.\64\
---------------------------------------------------------------------------

    \62\ Interest rates in this section are effective rates paid on 
conventional home purchase mortgages on new homes, based on the 
Monthly Interested 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.
    \63\ U.S. Housing Market Conditions, 2nd Quarter 2002, August 
2002, Table 14.
    \64\ Mortgage Bankers Association website. MBA Weekly Survey of 
Mortgage Applications, Monthly Average Interest Rates on 30-Year 
Fixed-Rate Mortgages. http://www.mortgagebankers.org/marketdata/index.html.
---------------------------------------------------------------------------

    Other Loan Terms. When mortgage rates are low, most homebuyers 
prefer to lock in a fixed-rate mortgage (FRM). Adjustable-rate 
mortgages (ARMs) are more attractive when rates are high, because 
they carry lower rates than FRMs and because buyers may hope to 
refinance to a FRM when mortgage rates decline. The Federal Housing 
Finance Board (FHFB) reports that the ARM share of the market fell 
from 20 percent in 1993 to a record low of 12 percent in 1998, 
before rising back to 21 percent in 1999. The ARM share continued to 
rise to 24 percent in 2000, but then fell dramatically to a low of 
12 percent in 2001 as mortgage rates decreased.
    In 2001, the term-to-maturity was 30 years for 83 percent of 
conventional home purchase mortgages, after steadily climbing to a 
high of 90 percent in 2000. The other maturities in 2001 included 15 
years (13 percent), 20 years (3 percent), and 25 years (1 percent).
    Low- and no-point mortgages continue to be a popular option for 
mortgage purchases. FHFB reports that average initial fees and 
charges (``points'') have decreased from 2.5 percent of loan balance 
in the mid-1980s to 2 percent in the late-1980s, 1.5 percent in the 
early 1990s, and less than 1 percent in 1995-97. The downward trend 
continued throughout the late 1990s with the average initial fees 
and charges reaching a low of one-half percent in 2001. Coupled with 
declining interest rates, these lower transactions costs have 
increased the propensity of homeowners to refinance their 
mortgages.\65\
---------------------------------------------------------------------------

    \65\ This is discussed in more detail in Paul Bennett, Richard 
Peach, and Stavros Peristani, Structural Change in the Mortgage 
Market and the Propensity to Refinance, Staff Report Number 45, 
Federal Reserve Bank of New York, September 1998.
---------------------------------------------------------------------------

    Another major change in the conventional home mortgage market 
has been the proliferation of high loan-to-value ratio (LTV) 
mortgages. According to data from the Federal Housing Finance Board, 
loans with LTVs greater than 90 percent (that is, down payments of 
less than 10 percent) made up less than 10 percent of the market in 
1989-91, but 25 percent of the market in 1994-97, gradually 
decreasing to an average of 21 percent of the market in 2001. Loans 
with LTVs less than or equal to 80 percent fell from three-quarters 
of the market in 1989-91 to an average of 56 percent of the market 
in 1994-97, but then rose to an average of 63 percent of mortgages 
originated in 1998-2001. As a result, the average LTV rose from 75 
percent in 1989-91 to nearly 80 percent in 1994-97, and then 
declined to 76.2 percent in 2001.\66\
---------------------------------------------------------------------------

    \66\ Other sources of data on loan-to-value ratios such as the 
American Housing Survey and the Chicago Title and Trust Company 
indicate that high-LTV mortgages are somewhat more common in the 
primary market than the Finance Board's survey. However, the Chicago 
Title survey does not separate FHA-insured loans from conventional 
mortgages. In addition, the statistics cited above pertain only to 
home purchase mortgages. Refinance mortgages generally have shorter 
terms and lower loan-to-value ratios than home purchase mortgages.
---------------------------------------------------------------------------

b. Refinance Mortgages

    Refinancing has fueled the growth in total mortgage 
originations, which were $638 billion in 1995 (a period of low 
refinance activity), but topped $2.5 trillion in 2002 (a period of 
heavy refinance activity). The refinance share of total mortgage 
originations rose to 50 percent in 1998, then decreased to 19 
percent in 2000 before jumping to 57 percent in 2001.\67\ Over the 
past ten years, refinance booms occurred three times, during 1992-
93, 1998, and 2001-02. During the 2001-02 refinance boom, 
approximately 40 percent of the $2.5 trillion in mortgage debt 
outstanding was refinanced. The last refinancing record was set in 
1998 when roughly 20 percent of mortgage debt outstanding was 
refinanced.\68\
---------------------------------------------------------------------------

    \67\ The source for the refinance share and total mortgage 
originations was the Mortgage Bankers Association.
    \68\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 2.
---------------------------------------------------------------------------

    In 1989-90 interest rates exceeded 10 percent, and refinancings 
accounted for less than 25 percent of total mortgage 
originations.\69\ 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.
---------------------------------------------------------------------------

    \69\ Refinancing data is taken from Freddie Mac's monthly 
Primary Mortgage Market Survey.
---------------------------------------------------------------------------

    The refinance wave subsided after 1993, because most homeowners 
who found it beneficial to refinance had already done so and because 
mortgage rates rose once again.\70\ Total single-family mortgage 
originations bottomed out at $638 billion in 1995, when the 
refinance share was only 21 percent. Total originations, driven by 
the volume of refinancings, amounted to $1.507 trillion in 1998, 
nearly 50 percent higher than the previous record level of $1.02 
trillion attained in 1993.
---------------------------------------------------------------------------

    \70\ There is some evidence that lower-income borrowers did not 
participate in the 1993 refinance boom as much as higher-income 
borrowers--see Paul B. Manchester, Characteristics of Mortgages 
Purchased by Fannie Mae and Freddie Mac: 1996-97 Update, Housing 
Finance Working Paper No. HF-006, Office of Policy Development and 
Research, Department of Housing and Urban Development, August 1998, 
pp. 30-32.
---------------------------------------------------------------------------

    The refinance wave from late 1997 through early 1999 reflected 
other factors besides interest rates, including greater borrower 
awareness of the benefits of refinancing, a highly competitive 
mortgage market, and the enhanced ability of the mortgage industry, 
utilizing automated underwriting and mortgage origination systems to 
handle an unprecedented volume of originations. The refinance share 
decreased to 19 percent in 2000 before jumping to a record 57 
percent in 2001.
    Historically low interest rates and declining mortgage 
transaction costs have driven the latest refinancing boom. Given 
these conditions, the after-tax cost saving on a new, lower-rate 
loan is much greater than the transaction costs of refinancing. In 
addition, the appreciation of housing prices has also contributed to 
the increase in refinancing. Over the past five years, the value of 
housing rose by approximately $5 trillion, and the rise in value has 
enabled lenders to service refinancing homeowners because of greater 
confidence in the creditworthiness of borrowers.\71\
---------------------------------------------------------------------------

    \71\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 4.
---------------------------------------------------------------------------

    Over the past few years, homeowners have become more willing to 
draw on the rising equity in their homes. According to Fannie Mae's 
2002 National Housing Survey, homeowners that refinanced during 2001 
withdrew about $110 billion in accumulated home equity wealth.\72\ 
Freddie Mac estimates that more than one-half of all refinance 
mortgages in the past two years involved cash-out refinancing.\73\
---------------------------------------------------------------------------

    \72\ Fannie Mae, 2002 Fannie Mae National Housing Survey. < 
http://www.fanniemae.com/global/pdf/media/survey/survey2002 
, September 4, 2002, p. 2.
    \73\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 4.
---------------------------------------------------------------------------

    The refinancing boom contributed to an estimated one-fifth of 
the national economy's real GDP growth since late 2000.\74\ During 
2001 and 2002, roughly $270 billion was raised in cash-out 
refinancing. Approximately one-half of cash from cash-out 
refinancing has enabled consumers to finance more spending for 
expenses such as home improvements, medical payments, education, and 
vehicles during a weakened economy. Roughly one-third of the cash 
from cash-out refinancing has allowed consumers to repay other 
debt.\75\ The remaining cash from cash-out refinancing has enabled 
consumers to invest in other assets. Refinancing households save 
approximately $10 billion in their annual interest payments on their 
mortgage and consumer installment liabilities.
---------------------------------------------------------------------------

    \74\ Mark M. Zandi, ``Refinancing Boom,'' Regional Finance 
Review, December 2002, p. 11.
    \75\ Ibid. p. 14.
---------------------------------------------------------------------------

    Although the refinancing boom may quickly fade if mortgage rates 
rise in 2004, the boom will have lingering effects. Mortgage 
borrowers that were able to secure low long-term interest rates 
through fixed rate mortgages will have more of their budgets to 
spend on other items. Meanwhile, cash-out borrowers, who are just 
receiving their money, will spend this year. It must be noted there 
is some concern regarding the potential for increased credit risk 
stemming from mortgage debt from cash out borrowers. According to a 
2002 Regional Finance Review article, the mortgage liabilities of 
households have been growing at a rate more than double the growth 
in household incomes. However, this potential credit risk is 
moderated by the strong growth in housing values. The ratio of 
mortgage debt to housing

[[Page 24276]]

values, the aggregate loan-to-value ratio, has remained fairly 
stable for a decade.\76\
---------------------------------------------------------------------------

    \76\ Economy.com, ``The Economic Contribution of the Mortgage 
Refinancing Boom,'' December 2002, p. 9.
---------------------------------------------------------------------------

c. Home Purchase Mortgages

    The volume of home purchase mortgages was $505 billion in 1995, 
rose to $848 billion in 1999, and remained in the $829-$873 billion 
range between 1999-2001 before jumping to $1.02 trillion in 2002 and 
$1.30 trillion in 2003. The Mortgage Bankers Association (MBA) 
forecasts that the home purchase volume will be $1.34 trillion in 
2004 as the home purchase share rises to 54 percent of all 
originations.\77\ The home purchase share of total mortgage 
originations was 79 percent in 1995, declined to 50 percent in 1998, 
rose to 81 in 2000, and sharply fell to 43 percent in 2001, 41 in 
2002, and 34 percent in 2003, as refinance mortgage volume grew. 
This section discusses the important issue of housing affordability 
and then examines the value of homeownership as an investment.
---------------------------------------------------------------------------

    \77\ Mortgage Bankers Association, ``Mortgage Finance 
Forecast'', March 15, 2004. http://www.mortgagebankers.org/marketdata/forecasts/mffore1203.pdf.
---------------------------------------------------------------------------

    The National Association of Realtors (NAR) has developed a 
housing affordability index, calculated as the ratio of median 
household income to the income needed to qualify for a median price 
home (the latter income is called the ``qualifying income''). In 
1993, NAR's affordability index was 133, which meant that the median 
family income of $37,000 was 33 percent higher than that income 
needed to qualify for the median priced home. Housing affordability 
remained at about 130 for 1994-97, with home price increases and 
somewhat higher mortgage rates being offset by gains in median 
family income.\78\ Falling interest rates and higher income led to 
an increase in affordability to 143 in 1998, reflecting the most 
affordable housing in 25 years. Affordability remained high in 1999, 
despite the increase in mortgage rates. NAR's affordability index 
declined from 140 in 1999 to 129 in 2000 as mortgage rates 
increased. The index turned upward to 136 in 2001 as mortgage rates 
fell and maintained this average in 2002, before rising further to 
140 in 2003.\79\
---------------------------------------------------------------------------

    \78\ Housing affordability varies markedly between regions, 
ranging in January 2004 from 194 in the Midwest to 107 in the West, 
with the South and Northeast falling in between.
    \79\ National Association of REALTORS. Housing Affordability 
Index, http://www.realtor.org/Research.nsf/Pages/HousingInx, 2003.
---------------------------------------------------------------------------

    Although the share of home purchase loans for lower-income 
households and/or households living in lower-income communities 
increased over the past decade, affordability still remains a 
challenge for many. The median sales price of existing single-family 
homes in the United States continues to rise, reaching $158,100 in 
2002 and $170,000 in 2003. The production of affordable housing and 
low interest rates could offset the negative impact of rising house 
prices, which undermine housing affordability for many Americans, 
particularly in several high-cost markets on the east and west 
coasts.
    As discussed earlier, barriers are preventing many potential 
homeowners from becoming homeowners, thus reducing the possible 
amount of home purchase loans. While the strong housing sector has 
provided financial security for many Americans, a 2002 Fannie Mae 
survey found that ``information barriers still keep many financially 
qualified families-particularly minority Americans from becoming 
homeowners or obtaining the lowest-cost financing available to 
them.'' \80\
---------------------------------------------------------------------------

    \80\ Fannie Mae, September 4, 2002, p. 2.
---------------------------------------------------------------------------

    These homeownership barriers pose a serious problem for many 
Americans who view homeownership as a smart, safe, long-term 
investment, rating homeownership as a better investment than the 
stock market. Home equity is the single most important asset for 
approximately two-thirds of American households that are homeowners. 
Considering that half of all homeowners held at least 50 percent of 
their net wealth in home equity in 1998, increasing housing 
affordability is important for many Americans.\81\
---------------------------------------------------------------------------

    \81\ Ibid.
---------------------------------------------------------------------------

    First-time Homebuyers. First-time homebuyers are a driving force 
in the nation's mortgage market. The current low interest rates have 
made it an opportune time for first-time homebuyers, which are 
typically people in the 25-34 year-old age group that purchase 
modestly priced houses. As the post-World War II baby boom 
generation ages, the percentage of Americans in this age group 
decreased from 28.3 percent in 1980 to 25.4 percent in 1992.\82\ 
Even though this cohort is smaller, first-time homebuyers increased 
their share of home sales. According to Chicago Title data for major 
metropolitan areas, the first-time buyer share of the homebuyer 
market increased from roughly 40 percent in the beginning of the 
1990s to 45-47 percent during the-mid and late 1990s.\83\ Since the 
late 1990s, industry survey data suggest that the first-time 
homebuyer percentage has decreased slightly. In the first quarter of 
2003, the share of all home purchases by first-time homebuyers was 
40 percent compared to 42 percent in 2001.\84\
---------------------------------------------------------------------------

    \82\ 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.
    \83\ Chicago Title and Trust Family of Insurers, Who's Buying 
Homes in America, 1998.
    \84\ National Association of Realtors. ``New NAR Survey of Home 
Buyers and Sellers Shows Growing Web Use in a Dynamic Housing 
Market.'' http://www.realtor.org.
---------------------------------------------------------------------------

    In the 1990s, lenders developed special programs targeted to 
first-time homebuyers and revised their underwriting standards to 
enhance homeownership opportunities for low-income families with 
special circumstances. The disproportionate growth in the number of 
first-time homebuyers and minority homebuyers largely drove the 
rising trend in total home purchases. Analysis of the American 
Housing Survey (AHS) indicates there were 1.3 million new first-time 
homebuyers during 1991, in comparison with over two million in each 
year between 1996 and 2001. In addition, first-time homebuyers 
comprised approximately 60 percent of all minority home purchases 
during the 1990s, compared with about 35 percent of all home 
purchases by non-Hispanic white families.
    In comparison to repeat homebuyers, first-time homebuyers are 
more likely to be younger, have lower incomes, and purchase less 
expensive houses. According to the AHS, more than one-half or first-
time homebuyers were below the age of 35, compared with less than 
one-quarter of repeat buyers in the 1990s. Thirty-nine percent of 
first-time buyers had incomes below 80 percent of the median 
compared to 30 percent of repeat buyers. Fifty-four percent of 
first-time buyers purchased homes priced below $100,000, compared to 
37 percent of repeat buyers. Minorities comprise a higher proportion 
of first-time buyers (32 percent) compared to repeat buyers (14 
percent). Compared to repeat buyers, first-time homebuyers are more 
likely to purchase a home in the central city and more likely to be 
a female-headed household.\85\
---------------------------------------------------------------------------

    \85\ U.S. Housing Market Conditions, 3rd Quarter 2001, November 
2001, Table 4.
---------------------------------------------------------------------------

    The National Association of Realtors reports that the average 
first-time homebuyer in the first quarter of 2003 was 32 years old 
with a household income of $54,800, compared to an average age of 46 
years and average household income of $74,600 for repeat buyers. The 
average first-time homebuyers made a downpayment of 6 percent on a 
home that cost $136,000 while the average repeat buyer made a 
downpayment of 23 percent on a home costing $189,000. In the NAR 
survey, 37 percent of first-time homebuyers were single compared to 
28 percent of repeat buyers.\86\
---------------------------------------------------------------------------

    \86\ National Association of Realtors. ``New NAR Survey of Home 
Buyers and Sellers Shows Growing Web Use in a Dynamic Housing 
Market.'' http://www.realtor.org.
---------------------------------------------------------------------------

    Many African Americans and Hispanics are likely to purchase 
homes in the coming years, contributing to the number of first-time 
home-buyers fueling growth in the housing sector. The number of 
homeowners will rise by an average of 1.1 million annually over the 
next two decades. The sizeable rise in the foreign-born population 
since the 1970's coupled with the increase in Latin American and 
Asian immigration will also contribute much to this growth.\87\
---------------------------------------------------------------------------

    \87\ Joint Center for Housing Studies at Harvard University, 
State of the Nation's Housing 2002, p.2.
---------------------------------------------------------------------------

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

    Purchases by the GSEs of single-family mortgages amounted to 
$519 billion during the heavy refinancing year of 1993, stood at 
$215 billion in 1995, and were at $618 billion during the heavy 
refinancing year of 1998. Purchases then fell to $395 billion in 
2000 before reaching record levels during the heavy refinancing 
years of 2001 ($961 billion) and 2002 ($1,090 billion). Purchases by 
Fannie Mae decreased from $316 billion in 1999 to $227 billion in 
2000, before rising to $568 billion in 2001 and $848 billion in 
2002. Freddie Mac's single-family mortgage purchases followed a 
similar trend, falling

[[Page 24277]]

from $233 billion in 1999 to $168 billion in 2000, and then rising 
to $393 billion in 2001 and $475 billion in 2002.\88\
---------------------------------------------------------------------------

    \88\ The source of the GSE data for 2001 and earlier years is 
the Office of Federal Housing Enterprise Oversight (OFHEO), Report 
to Congress, 2002 (see Tables 1 and 11). The 2002 data are taken 
from ``Fannie and Freddie Roll to Nearly $1.5 Trillion in New 
Business, Portfolios Continue Growing'' in Inside Mortgage Finance, 
January 31, 2003, pages 6-7. It should be noted that the Inside 
Mortgage Finance data for 2001 was 13 percent higher than the OFHEO 
data for 2001; therefore, the 2002 data may be overstated.
---------------------------------------------------------------------------

    The Office of Federal Housing Enterprise Oversight (OFHEO) 
estimates that the GSEs' share of total originations in the 
conventional single-family mortgage market, measured in dollars, 
declined from 37 percent in 1996 to 32 percent in 1997--well below 
the peak of 51 percent attained in 1993. OFHEO attributes the 1997 
downturn in the GSEs' role to increased holdings of mortgages in 
portfolio by depository institutions and to increased competition 
with Fannie Mae and Freddie Mac by private label issuers. However, 
OFHEO estimates that the GSEs' share of the conventional market 
rebounded sharply in 1998-99, to 43-42 percent. The GSEs' share then 
decreased to approximately 30 percent of the single-family 
conventional mortgages originated in 2000, and then increased 
sharply to 40 percent in 2001. Total GSE purchases, including loans 
originated in prior years, amounted to 46 percent of conventional 
originations in 2001.\89\
---------------------------------------------------------------------------

    \89\ Office of Federal Housing Enterprise Oversight. ``Mortgage 
Markets and The Enterprises in 2001,'' August 2002, p. 13
---------------------------------------------------------------------------

e. Mortgage Market Prospects

    The Mortgage Bankers Association (MBA) reports that mortgage 
originations in 2001 were $2.0 trillion, which is almost twice the 
volume of originations in 2000. Mortgage originations then increased 
to record levels of $2.5 trillion in 2002 and $3.8 trillion in 2003, 
with refinancings representing 66 percent of originations and the 
purchase volume amounting to $1.3 trillion. Estimates indicate that 
ARMs accounted for 19 percent of total mortgage originations in 
2003.\90\ In its March 15, 2004 forecast, MBA predicts that single-
family mortgage originations will amount to $2.5 trillion in 2004 
and $1.9 trillion in 2005, with refinancings representing 46 percent 
and 25 percent of originations respectively.
---------------------------------------------------------------------------

    \90\ Mortgage market projections from the MBA's MBA Mortgage 
Finance Forecast, December 17, 2003. 2000 and 2001 numbers from the 
MBA's MBA Mortgage Finance Forecast, January 10, 2002.
---------------------------------------------------------------------------

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

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

a. Lowering Down Payments and Up-Front Costs

    Numerous studies have concluded that saving enough cash for a 
down payment and for up-front closing costs is the greatest barrier 
that low-income and minority families face when considering 
homeownership.\91\ To assist in overcoming this barrier, the 
industry (including lenders, private mortgage insurers and the GSEs) 
began offering in 1994 mortgage products that required down payments 
of only 3 percent, plus points and closing costs. Other industry 
efforts to reduce borrowers' up-front costs included zero-point-
interest-rate mortgages and monthly insurance premiums with no up 
front component. These new plans eliminated large up-front points 
and premiums normally required at closing.
---------------------------------------------------------------------------

    \91\ See Charles, K. K. and E. Hurst (2002). ``The Transition to 
Home Ownership and the Black-White Wealth Gap.'' The Review of 
Economics and Statistics, 84(2): 281-297; Mayer, C. and G. 
Engelhardt (1996). ``Gift Down Payments and Housing Affordability.'' 
Journal of Housing Research, 7(1): 59-77; and Quercia, R. G., G. W. 
McCarthy, et al. (2003). ``The Impacts of Affordable Lending Efforts 
on Homeownership Rates.'' Journal of Housing Economics, 12(1): 29-
59.
---------------------------------------------------------------------------

    During 1998, Fannie Mae introduced its ``Flexible 97'' and 
Freddie Mac introduced its ``Alt 97'' low down payment lending 
programs. Under these programs, borrowers were required to put down 
only 3 percent of the purchase price. The down payment, as well as 
closing costs, could be obtained from a variety of sources, 
including gifts, grants or loans from a family member, the 
government, a non-profit agency and loans secured by life insurance 
policies, retirement accounts or other assets. Fannie Mae continues 
to offer the ``Flexible'' line of products, and Freddie Mac 
continues to list ``Alt 97.''
    In 2000, Fannie Mae launched the ``MyCommunityMortgage'' suite 
of products, which provides high loan-to-value product options for 
low- and moderate-income borrowers. In 2002, Fannie Mae purchased or 
securitized more than $882.5 million of MyCommunityMortgage 
products, which helped provide affordable housing solutions for 
7,866 households. In addition, Fannie Mae created new tailored 
solutions to MyCommunityMortgage including a rural housing program, 
a ``Community Solutions'' program offering flexible income 
requirements consistent with targeted professions and an ``Energy 
Efficient Mortgage'' program.\92\
---------------------------------------------------------------------------

    \92\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
pp. 8-9.
---------------------------------------------------------------------------

    Fannie Mae also expanded its ``Flexible'' product line with the 
``Flexible 100'' product, which eliminates the requirement for a 
down payment by providing 100 percent loan-to-value financing. The 
borrower is required to make at least a three percent contribution 
to closing costs; the funds for the contribution may come from a 
variety on sources such as gifts, grants, or unsecured loans from 
relatives, employers, public agencies, or nonprofits. Lenders 
delivered 17,206 ``Flexible 100'' loans to Fannie Mae totaling $2.2 
billion in 2001.\93\
---------------------------------------------------------------------------

    \93\ Fannie Mae, 2001 Annual Housing Activities Report, 2002, 
pp. 5-7.
---------------------------------------------------------------------------

    In 2001, Fannie Mae launched the eZ AccessTM product 
pilot. This product is targeted to 11 underserved markets and allows 
lenders to qualify borrowers who may have less than perfect credit 
and limited available funds for down payment. Through December 2002, 
eZ Access helped 400 underserved families through Fannie Mae's 
purchase of $57.1 million in loans.\94\
---------------------------------------------------------------------------

    \94\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, p. 
8.
---------------------------------------------------------------------------

    In 2000, Freddie Mac introduced its ``Freddie Mac 100'' product, 
which is designed to assist borrowers who have good credit but lack 
the ability to provide a large down payment. ``Freddie Mac 100'' 
allows a 100 percent loan-to-value ratio with the condition that the 
borrower has the funds for closing costs. Another Freddie Mac 
product, ``Affordable Gold 100'' provides 100 percent financing to 
low- and moderate-income borrowers for the purchase price of a home 
in California. ``Affordable Gold 100'' combines mortgage insurance 
benefits provided by a state insurance fund, the secondary mortgage 
market, and a team of the nation's leading mortgage lenders.\95\
---------------------------------------------------------------------------

    \95\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p.57.
---------------------------------------------------------------------------

b. Partnerships--Fannie Mae

    In addition to developing new affordable products, lenders and 
the GSEs have been entering into partnerships with local governments 
and nonprofit organizations to increase mortgage access to 
underserved borrowers. Fannie Mae's partnership offices in 54 
central cities, which coordinate Fannie Mae's programs with local 
lenders and affordable housing groups, are an example of this 
initiative.
    Fannie Mae continues to reach out to national groups and work 
with local affiliates

[[Page 24278]]

to expand homeownership. In 2002, Fannie Mae enhanced 5 partnerships 
with national organizations and maintained 13 national partnership 
agreements. For example, Fannie Mae maintains a partnership with the 
National Urban League (NUL) and the Chase Manhattan Mortgage 
Corporation to increase NUL's homeownership counseling capacity by 
providing the necessary technology and tools to support the effort, 
and to purchase $50 million in mortgage products over five years 
that are specifically targeted to African Americans and other 
minorities in underserved areas. In 2002, NUL originated $20 million 
in loans. Another example is Fannie Mae's partnership with the AFL-
CIO Housing Investment Trust (HIT) and Countrywide Mortgage, which 
launched ``HIT HOME'' in 2001. HIT HOME is an affordable home 
mortgage initiative that targets 13 million union members in 16 
cities throughout the nation to provide union members with a variety 
of affordable mortgage choices that enable them to qualify for 
competitively priced loans with new re-payment terms. As of December 
2002, over $244 million in loans have been originated through this 
initiative, serving 2,076 households.\96\
---------------------------------------------------------------------------

    \96\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
pp. 12-15.
---------------------------------------------------------------------------

    In order to meet the needs of underserved and low- and moderate-
income populations, Fannie Mae has targeted specific populations for 
initiatives. These include minority and women-owned lenders (MWOL), 
Native Americans, working Americans, and borrowers served by 
community development financial institutions and public housing 
agencies. In 2002, through the MWOL Initiative, Fannie Mae purchased 
$9 billion in mortgages originated by MWOLs; 97% of this amount 
reached minority households. The Employer Assisted Housing 
Initiative reached 116 employers in 2002 in industries ranging from 
health care to education. The Community Development Financial 
Institutions Initiative committed to invest $17.1 million in 2002, 
which was expected to generate more than 980 additional units of 
affordable housing. The Section 8 Homeownership Initiative helped 35 
families make the transition from Section 8 rental housing to 
homeownership in 2002. The Native American Initiative has served 
more than 3,376 Native American families living on reservations and 
trust lands since its inception, while providing $290 million in 
mortgage financing.\97\
---------------------------------------------------------------------------

    \97\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
pp. 16-18.
---------------------------------------------------------------------------

    Fannie Mae's American Dream Commitment's Opportunity for All 
Strategy and National Minority Homeownership Initiative has pledged 
to contribute at least $700 billion in private capital to serve 4.6 
million families towards President George W. Bush's goal of 
expanding homeownership to 5.5 million new minority Americans by the 
end of the decade.\98\ This marks a 66% increase in Fannie Mae's 
earlier commitment of $420 billion. Towards this goal, in 2002, 
Fannie Mae announced 10 new lender partnerships, bringing the total 
number of lenders committed since 2000 to 16, with an estimated $180 
billion of American Dream Commitment business pledged to be 
delivered. Examples of lender partnerships under this initiative 
include J.P. Morgan Chase & Co. with a $35 billion national 
investment initiative designed to increase homeownership 
opportunities for underserved communities and improve affordable 
homeownership options for immigrants and minorities, and Bank One 
with a $12.5 billion community lending alliance to help low- and 
moderate-income families purchase homes with a total designated 
commitment of at least 25% toward increasing homeownership among 
minorities.\99\
---------------------------------------------------------------------------

    \98\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, p. 
15.
    \99\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
pp. 15-16.
---------------------------------------------------------------------------

    Through these partnerships, a strategic effort was made to 
eliminate language, credit, and other barriers to minority 
homeownership and to reach underserved communities. In 2002, Fannie 
Mae helped serve 984,276 minority families by providing $136.2 
billion in mortgage financing.\100\ According to Fannie Mae, its 
lending partners realize that multicultural markets may differ from 
traditional markets, and thus they offer various flexible mortgage 
products to reach out to minority and immigrant homebuyers. Some of 
these mortgage products require only a $500 contribution from the 
borrower for closing costs. Others have flexible qualifying 
guidelines that use alternative sources of income like rent and 
part-time employment.\101\
---------------------------------------------------------------------------

    \100\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, p 
5.
    \101\ Fannie Mae, ``Minority Homeownership,'' 2002.
---------------------------------------------------------------------------

c. Partnerships--Freddie Mac

    Freddie Mac does not have a partnership office structure similar 
to Fannie Mae's, but it has undertaken a number of initiatives in 
specific metropolitan areas.\102\ In 2001, Freddie Mac joined the 
Congressional Black Caucus to launch a new initiative, ``With 
Ownership Wealth,'' designed to increase African-American 
homeownership with one million new families by 2005; Freddie Mac has 
pledged to purchase qualified mortgages originated under this 
initiative.\103\ In 2002, Freddie Mac launched more than 30 new 
alliances and initiatives and continued working with existing 
alliances.\104\ Freddie Mac has partnered with the National Council 
of La Raza (NCLR), 20 community based NCLR affiliated housing 
counseling organizations, the National Association of Hispanic Real 
Estate Professionals (NAHREP), EMT Applications and participating 
Freddie Mac Seller/Servicers including Bank of America, U.S. Bank 
and Wells Fargo Home Mortgage on the ``En Su Casa'' initiative. This 
$200 million homeownership initiative combines technology tools with 
flexible mortgage products to meet the needs of Hispanic borrowers. 
Mortgage products include low down payments, flexible credit 
underwriting and debt-to-income ratios, and streamlined processing 
for resident alien borrowers.\105\
---------------------------------------------------------------------------

    \102\ Freddie Mac, News Release, January 15, 1999.
    \103\ Freddie Mac, 2002, pp. 41-42, and Freddie Mac, 2002 Annual 
Housing Activities Report, 2003, p. 62.
    \104\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 60.
    \105\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 61.
---------------------------------------------------------------------------

    In 2002, Freddie Mac joined with the City of Boston and the U.S. 
Conference of Mayors to make available the ``Don't Borrow Trouble'' 
predatory lending educational campaign to approximately 1,100 
cities. In addition, Freddie Mac joined with Rainbow/PUSH and the 
National Urban League to promote the ``CreditSmartSM'' 
financial educational curriculum that helps consumers understand, 
obtain and maintain good credit, thereby preparing them for 
homeownership and other personal financial goals. In 2002, Freddie 
Mac also joined with the American Community Bankers and the Credit 
Union National Association in strategic alliances that will better 
enable member banks and credit unions access to the secondary 
market.\106\
---------------------------------------------------------------------------

    \106\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
pp. 35-38.
---------------------------------------------------------------------------

    In June 2002, President George W. Bush challenged the nation's 
housing industry to invest more than $1 trillion to make 
homeownership a reality for 5.5 million more minority households for 
the decade. Freddie Mac responded to the challenge with ``Catch the 
Dream,'' which is a comprehensive set of 25 major initiatives aimed 
at accelerating the growth in minority homeownership. The 
initiatives range from homebuyer education and outreach to new 
technologies with innovative mortgage products. Catch the Dream 
represents a collaborative effort with lenders, nonprofit housing 
and community-based organizations, and other industry participants 
to expand homeownership opportunities for America's minorities.\107\ 
Freddie Mac has committed to providing $400 billion in mortgage 
financing for minority families by the end of the decade.\108\ In 
2002, Freddie Mac purchased mortgages for 576,000 minority families, 
a total of 17.3% of their single-family, owner-occupied mortgage 
purchases for the year.\109\ In addition, in 2002, minority- or 
women-owned lenders comprised 2.7% of Freddie Mac's network of 
lenders. $5.5 billion in loans were purchased from these lenders, 
financing housing for 45,000 families.\110\
---------------------------------------------------------------------------

    \107\ Freddie Mac. Corporate Information. ``Our Homeownership 
Commitment.'' http://www.freddiemac.com/corporate/about/dream/expanding_minority_homeownership.htm.
    \108\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 28.
    \109\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 32.
    \110\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 15.
---------------------------------------------------------------------------

    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.

[[Page 24279]]

d. Underwriting and GSE Purchase Guidelines

    Lenders, mortgage insurers, and the GSEs have also been 
modifying their mortgage underwriting standards to address the needs 
of families who have historically found it difficult to qualify 
under traditional guidelines. In addition to the changes in 
underwriting standards, the use of automated underwriting has 
dramatically transformed the mortgage application process. This 
section focuses on changes to traditional underwriting standards and 
recent GSE initiatives for credit-impaired borrowers. Subsequent 
sections will provide more details on the impact of automated 
underwriting.
    The GSEs modified their underwriting standards to address the 
needs of families who find qualifying under traditional guidelines 
difficult. The goal of these underwriting changes is not to loosen 
underwriting standards, but rather to identify creditworthiness by 
alternative means that more appropriately measures the unique 
circumstances of low-income, immigrant, and minority households. 
Examples of changes that the GSEs and others in the industry have 
made to their underwriting standards include the following:
     Using a stable income standard rather than a 
stable job standard (or minimum period of employment). This 
particularly benefits low-skilled applicants who have successfully 
remained employed, even with frequent job changes.
     Using an applicant's history of rent and 
utility payments as a measure of creditworthiness. This measure 
benefits lower-income applicants who have not established a credit 
history.
     Allowing pooling of funds for qualification 
purposes. This change benefits applicants with extended family 
members. Freddie Mac, for example, allows income from relatives who 
live together to pool their funds to cover downpayment and closing 
costs and to combine their incomes for use in calculating the 
borrower's stable monthly income.
    These underwriting changes have been accompanied by 
homeownership counseling to ensure homeowners are ready for the 
responsibilities of homeownership. In addition, the industry has 
engaged in intensive loss mitigation to control risks.
    In 1999, HUD commissioned a study by the Urban Institute to 
examine the underwriting criteria that the GSEs use when purchasing 
mortgages from primary lenders.\111\ According to the study, while 
the GSEs had improved their ability to serve low- and moderate-
income borrowers, it did not appear at that time that they had gone 
as far as some primary lenders to serve these borrowers. From the 
Urban Institute's discussion with lenders, it was found that primary 
lenders were originating mortgages to lower-income borrowers using 
underwriting guidelines that allow lower down payments, higher debt-
to-income ratios and poorer credit histories than allowed by the 
GSEs' guidelines.
---------------------------------------------------------------------------

    \111\ Kenneth Temkin, Roberto Quercia, George Galster, and 
Sheila O' Leary, A Study of the GSEs' Single Family Underwriting 
Guidelines: Final Report. Washington DC: U.S. Department of Housing 
and Urban Development, April 1999.
---------------------------------------------------------------------------

    From this and other evidence, the Urban Institute concluded that 
the GSEs were lagging the market in servicing low- and moderate-
income and minority borrowers. Furthermore, the Urban Institute 
found ``that the GSEs'' efforts to increase underwriting flexibility 
and outreach has been noticed and is applauded by lenders and 
community advocates. Despite the GSEs' efforts in recent years to 
review and revise their underwriting criteria, however, they could 
do more to serve low- and moderate-income borrowers and to minimize 
disproportionate effects on minorities.''\112\ Since the Urban 
Institute study, Freddie Mac and Fannie Mae have been playing a 
larger role in financing low-income and minority borrowers. (See 
Section E.2.)
    In addition to offering low-down-payment programs, the GSEs' 
recent efforts have also centered around their automated 
underwriting systems and their treatment of borrowers with blemished 
credit, the latter being perhaps the most controversial underwriting 
issue over the past few years. Freddie Mac recently launched a 
variety of new products aimed at providing borrowers with impaired 
credit more mortgage product choices. The new products include: 
``CreditWorks,'' which helps borrowers with excessive debt and 
impaired credit to qualify for a prime market rate mortgage more 
quickly than before, and ``LeasePurchase Plus Initiative,'' which 
provides closing cost and down payment assistance in addition to 
extensive counseling for borrowers who have had bad credit or who 
have never established a credit history.\113\ During 2002, Freddie 
Mac entered into several new markets under the ``LeasePurchase Plus 
Initiative'' and purchased more than $16 million in loans.\114\
---------------------------------------------------------------------------

    \112\ Temkin, et al. 1999, p. 28.
    \113\ Freddie Mac, 2001 Annual Housing Activities Report, 2002, 
p. 28.
    \114\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 35.
---------------------------------------------------------------------------

    According to Freddie Mac, its automated underwriting system, 
``Loan Prospector'' has reduced costs, made approving mortgages 
easier and faster, and increased the consistency of the application 
of objective underwriting criteria. In addition, Freddie Mac states 
that ``Loan Prospector'' extends the benefits of the mortgage 
finance system to borrowers with less traditional credit profiles 
and limited savings by more accurately measuring risk. Freddie Mac 
reports that its automated underwriting system, Loan Prospector, has 
resulted in higher approval rates for minority borrowers than under 
traditional manual underwriting because of improved predictive 
powers. As mentioned in Section C.7, the 2000 version of LP approved 
87.1 percent of loans generated through affordable housing programs, 
compared to 51.6 percent approved by manual underwriting. The 
Freddie Mac study found automated mortgage scoring less 
discriminatory and more accurate in predicting risk. However, as 
noted below in the automated mortgage scoring section, there are 
concerns that the codification of certain underwriting guidelines 
could result in unintentional discrimination or disparate treatment 
across groups. In response to the potential disparate impact of 
automated underwriting, Freddie Mac have launched initiatives to 
make the mortgage process more transparent by disclosing both credit 
and non-credit factors that Loan Prospector consider when evaluating 
a loan application. In 2000, Freddie Mac launched an initiative that 
published a list of all of the factors that Loan Prospector uses to 
analyze loans, and put the list on the Freddie Mac Web site.\115\
---------------------------------------------------------------------------

    \115\ Ibid. p. 57.
---------------------------------------------------------------------------

    In 2002, Fannie Mae released two versions of its automated 
underwriting service, ``Desktop Underwriter'' (DU), to expand its 
mortgage product offerings and to update underwriting guidelines. 
These enhancements--labeled DU 5.2 and DU 5.2.1--increased 
homeownership opportunities for low- and moderate-income borrowers 
and borrowers with small downpayments by enhancing DU's risk 
assessment capabilities for certain high loan-to-value loans. For 
example, DU 5.2.1 enhanced its Expanded ApprovalTM 
policies to allow 100 percent loan-to-value limited cash-out 
refinances and the origination of 5/1 ARMs.\116\ The Expanded 
Approval feature and Timely Payment Rewards option in DU were 
created by Fannie Mae in 1999 to enable lenders to more 
comprehensively review a borrower's creditworthiness. The Timely 
Payment Rewards option reduces the interest rate of qualified 
borrowers of up to one percent after making timely mortgage payments 
for a given time period.\117\ With these options, lenders can offer 
mortgage loans to many borrowers previously unable to receive 
financing from a mainstream lender. A borrower who is recommended 
for approval for either of these features would be eligible for an 
initial mortgage rate that is lower than that available through the 
subprime market.\118\ Automated mortgage scoring and the potential 
for disparate impacts on borrowers will be further discussed in a 
later section.
---------------------------------------------------------------------------

    \116\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 10.
    \117\ Ibid. p. 6.
    \118\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 32.
---------------------------------------------------------------------------

5. Affordable Single-Family Lending: Data Trends

a. 1993-2002 Lending Trends

    HMDA data suggest that the industry and GSE initiatives are 
increasing the flow of credit to underserved borrowers. Between 1993 
and 2002, conventional loans to low-income and minority families 
increased at much faster rates than loans to higher income and non-
minority families. As shown below, conventional home purchase 
originations to African Americans more than doubled between 1993 and 
2002 and those to Hispanic borrowers more than tripled. Home loans 
to low-income borrowers and to low-income and high-minority census 
tracts also more than doubled during this period.

[[Page 24280]]



------------------------------------------------------------------------
                                                        1993-2002 Growth
                                      1993-2002 Growth        rate:
                                       rate: all home     conventional
                                        loans  P (per     home loans  P
                                            cent)          (per cent)
------------------------------------------------------------------------
African-American Borrowers..........                80               133
Hispanic Borrowers..................               186               245
White Borrowers.....................                30                43
Low-Income Borrower (Less than 80%                  91               119
 of AMI)............................
Upper-Income Borrower (More than                    66                81
 120% of AMI).......................
Low-Income Census Tract.............                99               143
Upper-Income Census Tract...........                64                78
High-Minority Tract (50% or more                   113               167
 minority)..........................
Predominantly-White Tract (Less than                53                64
 10% minority)......................
------------------------------------------------------------------------

GSE purchases showed similar trends, as indicated by the following 
1993-to-2002 percentage point increases for metropolitan areas: 
African-American borrowers (193 percent), Hispanic borrowers (208 
percent), and low-income borrowers (193 percent). While their annual 
purchases of all home loans increased by 57 percent between 1993 and 
2001, their purchases of mortgages that qualify for the three 
housing goals increased as follows: Special affordable by 264 
percent; low- and moderate-income by 142 percent; and underserved 
areas by 112 percent.
    While low interest rates and economic expansion certainly played 
an important role in the substantial increase in conventional 
affordable lending in recent years, most observers believe that the 
efforts of lenders, private mortgage insurers, and the GSEs were 
also important contributors. In addition, many observers believe 
that government initiatives such as the GSE housing goals and the 
Community Reinvestment Act have also played a role in the growth of 
affordable lending over the past 10 years.

b. Affordable Lending Shares by Major Market Sector

    Section E below compares the GSEs' performance with the 
performance of primary lenders in the conventional conforming 
market. To provide a useful context for that analysis, this section 
examines the role of the conventional conforming market in funding 
low-income and minority families and their neighborhoods. 
Information on the mortgage market's funding of homes purchased by 
first-time homebuyers is also provided. In addition, this section 
compares the GSEs with other sectors of the mortgage market. The 
important role of FHA in the affordable lending market is 
highlighted and questions are raised about whether the conventional 
conforming market could be doing a better job helping low-income and 
minority borrowers obtain access to mortgage credit.
    Table A.1 reports borrower characteristics and Table A.2 reports 
neighborhood characteristics for home purchase mortgages insured by 
FHA, purchased by the GSEs, originated by depository institutions 
(mainly banks and thrift), and originated in the conventional 
conforming market and in the total market for owner-occupied 
properties in metropolitan areas.\119\ In this case, the ``total'' 
market consists of both the conventional conforming market and the 
government (mainly FHA and VA loans) market; ``jumbo'' loans above 
the conventional conforming loan limit are excluded from this 
analysis.\120\
BILLING CODE 4210-22-P
---------------------------------------------------------------------------

    \119\ Table A.3 also provides the same average (1999 to 2002) 
information as Tables A.1 and A.2 but for total (both home purchase 
and refinance) loans. Thus, it provides a complete picture of 
overall mortgage activity.
    \120\ The ``Total Market'' is defined as all loans (including 
both government and conventional) below the conforming loan limit of 
$240,000 in 1999, $252,700 in 2000, $275,000 in 2001, and $300,700 
in 2002.

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BILLING CODE 4210-27-C

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    HMDA is the source of the FHA, depository, and market data, 
while the GSEs provide their own data. Low-income, African-American, 
Hispanic, and minority borrowers are covered in Table A.1. Table A.2 
provides information on four types of neighborhoods--low-income 
census tracts, tracts where minorities (or African Americans) 
account for more than 30 percent of the census tract population, and 
underserved areas as defined by HUD. The average data reported in 
Tables A.1 and A.2 for the years 1999 to 2002 offer a good summary 
of recent lending to low-income and minority borrowers and their 
communities.\121\ Individual year data are also provided.
---------------------------------------------------------------------------

    \121\ The affordable market shares reported in Table A.1 for the 
``Conventional Conforming Market W/O B&C'' were derived by excluding 
the estimated number of B&C loans from the market data reported by 
HMDA. Because B&C lenders operate mainly in the refinance sector, 
excluding these loans from the conforming market has litte impact on 
the home purchase percentages reported in Table A.1. The method for 
excluding B&C loans is explained in Section E below and Appendix D.
---------------------------------------------------------------------------

    The focus of different market sectors on affordable lending is 
summarized by the percentages reported in Tables A.1 and A.2. These 
percentages show each sector's ``distribution of business,'' defined 
as the share of loans originated (or, for the GSEs, purchased) that 
had a particular borrower or neighborhood characteristic. The 
interpretation of the ``distribution of business'' percentages can 
be illustrated using the FHA percentage for low-income borrowers: 
Between 1999 and 2002, 50.7 of all FHA-insured home purchase loans 
in metropolitan areas were originated for borrowers with an income 
less than 80 percent of the local area median income. These 
percentages are to be contrasted with ``market share'' percentages, 
which are presented below in Section E. A ``market share'' 
percentage is the share of loans with a particular borrower or 
neighborhood characteristic that was funded by a particular market 
sector (e.g., FHA-insured, GSEs, depositories). As will discussed 
below, FHA's ``market share'' for low-income borrowers during the 
1999-to-2002 period was estimated to be 26 percent which is 
interpreted as follows: Of all home purchase loans originated for 
low-income borrowers in metropolitan areas between 1999 and 2002, 26 
percent were FHA-insured loans. Thus, in this example, the 
``distribution of business'' percentage measures the importance (or 
concentration) of low-income borrowers in FHA's overall business 
while the ``market share'' percentage measures the importance of FHA 
to the market's overall funding of loans for low-income borrowers. 
Both concepts are important for evaluating performance--for an 
industry sector such as FHA or the GSEs to have a significant impact 
on lending to a targeted group, that sector's business must be 
concentrated on the targeted group and that sector must be of some 
size. The discussion below will focus on the degree to which 
different mortgage sectors concentrate on targeted groups, while 
Section E will also provide estimates of market shares.
    The main insights from the ``distribution of business'' 
percentages in Tables A.1 and A.2 pertain to four topics.
    (i) FHA-Insured Loans. FHA has traditionally been the mechanism 
used by borrowers who face difficulty obtaining mortgage financing 
in the private conventional market. FHA has long been recognized as 
the major source of funding for first-time, low-income and minority 
homebuyers who are not often able to raise cash for large 
downpayments.\122\ Tables A.1 and A.2 show that FHA places much more 
emphasis on affordable lending than the other market sectors. 
Between 1999 and 2002, low-income borrowers accounted for 50.7 
percent of FHA-insured loans, compared with 27.1 percent of the home 
loans purchased by the GSEs, 29.2 percent of home loans originated 
by depositories, and 29.5 percent of all originations in the 
conventional conforming market (see Table A.1 ). Likewise, 40.9 
percent of FHA-insured loans were originated in underserved census 
tracts, while only 23.5 percent of the GSE-purchased loans, 25.7 
percent of home loans originated by depositories, and 26.5 percent 
of conventional conforming loans were originated in these tracts 
(see Table A.2).\123\ As discussed in Section E, FHA's share of the 
minority lending market is particularly high. While FHA insured only 
18 percent of all home purchase mortgages originated below the 
conforming loan limit in metropolitan areas between 1999 and 2002, 
it is estimated that FHA insured 33 percent of all home loans 
originated for African-American and Hispanic borrowers.
---------------------------------------------------------------------------

    \122\ Almost two-thirds of the borrowers with an FHA-insured 
home purchase loan make a downpayment less than five percent, and 
over 80 percent are first-time home buyers. For discussions of the 
role of FHA in the mortgage market, see (a) Harold L. Bunce, Charles 
A. Capone, Sue G. Neal, William J. Reeder, Randall M. Scheessele, 
and Edward J. Szymanoski, An Analysis of FHA's Single-Family 
Insurance Program, Office of Policy Development and Research, U.S. 
Department of Housing and Urban Development, 1995; and (b) Office of 
Policy Development and Research, ``FHA's Impact on Homeownership 
Opportunities for Low-Income and Minority Families During the 1990s' 
Issue Brief IV, U.S. Department of Housing and Urban Development, 
December 2000. For data on the credit characteristics of FHA 
borrowers, see Harold L. Bunce, William J. Reeder and Randall 
Scheessele, ``Understanding Consumer Credit and Mortgage Scoring: A 
Work in Progress at HUD'', U.S. Department of Housing and Urban 
Development, Unpublished Paper, 1999.
    \123\ FHA, which focuses on low downpayment loans and also 
accepts borrowers with credit blemishes, experiences higher mortgage 
defaults than conventional lenders and the GSEs. Still, the FHA 
system is actuarially sound because it charges an insurance premium 
that covers the higher default costs. For the results of FHA's 
actuarial analysis, see Deloitte & Touche, Actuarial Review of MMI 
Fund as of FY 2000, report for the U.S. Department of Housing and 
Urban Development, January 2001.
---------------------------------------------------------------------------

    (ii) Conventional and GSE Minority Lending. The affordable 
lending shares for the conventional conforming sector are low for 
minority borrowers, particularly African-American and Hispanic 
borrowers. These borrowers accounted for only 14.3 percent of all 
conventional conforming loans originated between 1999 and 2002, 
compared with 34.7 percent of FHA-insured loans and 18.8 percent of 
all loans originated in the total (government and conventional 
conforming) market. Not surprisingly, the minority lending 
performance of conventional lenders has been subject to much 
criticism. Recent studies contend that primary lenders in the 
conventional market are not doing their fair share of minority 
lending which forces minorities, particularly African-American and 
Hispanic borrowers, to rely on more costly FHA and subprime 
loans.\124\ Thus, it appears that conventional lenders could be 
doing a better job helping minority borrowers obtain access to 
mortgage credit.
---------------------------------------------------------------------------

    \124\ See Green and Associates, Fair Lending in Montgomery 
County: A Home Mortgage Lending Study, a report prepared for the 
Montgomery County Human Relations Commission, March 1998; and Calvin 
Bradford, Crisis in De ja vu: A Profile of the Racial Patterns in 
Home Purchase Lending in the Baltimore Market. Report for The Public 
Justice Center, May 2000; and The Patterns of GSE Participation in 
Minority and Racially Changing Markets Reviewed from the Context of 
Levels of Distress Associated with High Levels of FHA Lending, GSE 
Study No. 11, U.S. Department of Housing and Urban Development, 
September 2000. For analysis suggesting some minorities receiving 
FHA loans could qualify for conventional loans, see Anthony 
Pennington-Cross, Anthony Yezer, and Joseph Nichols, Credit Risk and 
Mortgage Lending: Who Uses Subprime and Why? Working Paper No. 00-
03. Research Institute for Housing America, 2000. Also see the 
series of recent studies concerning the lack of mainstream lenders 
in minority neighborhoods.
---------------------------------------------------------------------------

     The GSEs' funding of minority loans can be 
compared with mortgages originated for minority borrowers in the 
conventional conforming market, although the latter may be a poor 
benchmark, as discussed above. Between 1999 and 2002, home purchase 
loans to African-American and Hispanic borrowers accounted for 10.3 
percent of Freddie Mac's purchases, 13.0 percent of Fannie Mae's 
purchases, and 14.3 percent of loans originated in the conventional 
conforming market (or 13.7 percent if B&C loans are excluded from 
the market definition). Thus, since 1999, the African-American and 
Hispanic share of the GSEs' purchases has been lower than the 
corresponding share for the conventional conforming market.\125\
---------------------------------------------------------------------------

    \125\ For a comprehensive analysis of the GSEs' purchases of 
minority loans through 1999, see Harold L. Bunce, An Analysis of GSE 
Purchases of Mortgages for African-American Borrowers and their 
Neighborhoods, Housing Finance Working Paper No. 11, Office of 
Policy Development and Research, HUD, December 2000.
---------------------------------------------------------------------------

     As the above comparisons show, Fannie Mae has 
had a much better record than Freddie Mac in funding loans for 
minority families. And Fannie Mae significantly increased its 
purchases of loans for African-American and Hispanic borrowers 
during 2001, raising the share of its purchases to market levels--
13.7 percent for both Fannie Mae and the conforming market (without 
B&C loans). In 2002, Fannie Mae surpassed the conventional 
conforming market in funding African-American and Hispanic 
borrowers--a 15.8 percent share for Fannie Mae and a 15.2 share for 
the market. When all minority borrowers are considered, Fannie Mae 
has purchased mortgages for

[[Page 24285]]

minority borrowers at a higher rate (years 2001 and 2002) than these 
loans were originated by primary lenders in the conventional 
conforming market (without B&C loans). Freddie Mac, on the other 
hand, lagged behind both the market and Fannie Mae in funding loans 
for minority borrowers during 2001 and 2002, as well as during the 
entire 1999-to-2002 period. The share of Freddie Mac's purchases for 
African-American and Hispanic borrowers declined from 10.9 percent 
in both 2000 and 2001 to 10.1 percent in 2002.
     Considering the minority census tract data 
reported in Table A.2, Fannie Mae lagged behind the conforming 
market (without B&C loans) in high-minority neighborhoods and in 
high-African-American neighborhoods during the 1999-to-2002 period. 
However, Fannie Mae improved its mortgage purchases in African-
American neighborhoods during 2001 and 2002 to exceed market levels 
by 0.1 percentage point (e.g., 4.7 percent of Fannie Mae's purchases 
and 4.6 percent of market originations were in high African-American 
tracts in 2002). And during 2001 and 2002, Fannie Mae also purchased 
loans in high-minority census tracts at a higher rate than loans 
were originated by conventional lenders in these tracts. While 
Freddie Mac has generally lagged the primary market in funding 
minority neighborhoods, note in Table A.2 that high African-American 
tracts increased from 3.9 percent of Freddie Mac's purchases in 2001 
to 5.3 percent in 2002, placing Freddie Mac above the conventional 
conforming market level (4.6 percent) in 2002.
    (iii) Low-Income Lending by the GSEs. Information is also 
provided on the GSEs' purchases of home loans for low-income 
borrowers (A.1) and for families living in low-income neighborhoods 
(A.2). Historically, the GSEs have lagged behind the conventional 
conforming market in funding affordable loans for these groups. 
During the 1999-to-2002 period, low-income borrowers (census tracts) 
accounted for 27.2 (9.6) percent of Freddie Mac's purchases, 27.1 
(9.8) percent of Fannie Mae's purchases, 29.2 (11.1) percent of 
loans originated by depositories, and 29.3 (11.1) percent of home 
loans originated by conventional conforming lenders (without B&C 
loans). By the end of this period, Fannie Mae had significantly 
improved its performance relative to the market. In 2002, low-income 
borrowers (census tracts) accounted for 29.7 (11.0) of Fannie Mae's 
purchases, compared with 29.6 (11.1) percent for the conforming 
market. It is also interesting that even though Freddie Mac lagged 
the market in funding home loans for low-income borrowers during 
2002 (28.6 percent versus 29.6 percent), it surpassed the market in 
financing properties in low-income census tracts (11.3 percent 
versus 11.1 percent). A more complete analysis of the GSEs' recent 
improvements in purchasing home loans that qualify for the housing 
goals is provided below in Section E.
    (iv) Depositories. Within the conventional conforming market, 
depository institutions (mainly banks and thrifts) are important 
providers of affordable lending for lower-income families and their 
neighborhoods.\126\ Between 1999 and 2002, underserved areas 
accounted for 26.8 percent of loans held in depository portfolios, 
which compares favorably with the underserved areas percentage (26.5 
percent) for the overall conventional conforming market.\127\ 
Depository lenders have extensive knowledge of their communities and 
direct interactions with their borrowers, which may enable them to 
introduce flexibility into their underwriting standards without 
unduly increasing their credit risk. The Community Reinvestment Act 
provides an incentive for banks and thrifts to initiate affordable 
lending programs with underwriting flexibility and to reach out to 
lower income families and their communities.\128\ Many of the CRA 
loans are held in portfolio by lenders, rather than sold to Fannie 
Mae or Freddie Mac.\129\
---------------------------------------------------------------------------

    \126\ Tables A.1, A.2, and A.3 include data for all home loans 
originated by depositories as well as for the subset of loans 
originated but not sold, the latter being a proxy for loans held in 
depository portfolios. (See the notes to Table A.1 for definitions 
of the depository data.)
    \127\ However, as shown in Table A.1 , depository institutions 
resemble other conventional lenders in their relatively low level of 
originating loans for African-American, Hispanic and minority 
borrowers. Within the conventional conforming market, Fannie Mae has 
done a better job than depositories in funding minority borrowers, 
particularly Hispanic borrowers and minority borrowers as a group. 
During the last two years, Fannie Mae has also funded African-
American borrowers at a higher rate than have depository 
institutions.
    \128\ CRA loans are typically made to low-income borrowers 
earning less than 80 percent of area median income, and in moderate-
income neighborhoods. For a comprehensive analysis of CRA and its 
impact on affordable lending, see Robert E. Litan, Nicolas P. 
Retsinas, Eric S. Belsky and Susan White Haag, The Community 
Reinvestment Act After Financial Modernization: A Baseline Report, 
U.S. Department of Treasury, 2000.
    \129\ Evidence is growing that CRA-type lending to low-income 
families can be profitable, particularly when combined with 
intensive loss mitigation efforts to control credit risk. In a 
survey conducted by the Federal Reserve, lenders reported that most 
CRA loans are profitable although not as profitable as the lenders' 
standard products. See Board of Governors of the Federal Reserve 
System. The Performance and Profitability of CRA-Related Lending. 
Washington, DC, 2000.
---------------------------------------------------------------------------

    (v) First-time Homebuyers. As explained in Section E, market 
information on first-time homebuyers is not as readily available as 
the HMDA data reported in Tables A.1 and A.2 on the income and 
racial characteristics of borrowers and census tracts served by the 
mortgage market. However, the limited market data that are available 
from the American Housing Survey, combined with the first-time 
homebuyer data reported by FHA and the GSEs, indicate a rather large 
variation in the funding of first-time homebuyers across the 
different sectors of the mortgage market. Based on the American 
Housing Survey (AHS), it is estimated that first-time homebuyers 
accounted for 42.3 percent of all home purchase loans originated 
throughout the market between 1999 and 2001,\130\ and for 37.6 
percent of home loans originated in the conventional conforming 
market. The AHS defines a first-time homebuyer as someone who has 
never owned a home. Using a more liberal definition of a first-time 
homebuyer (someone who has not owned a home in the past three 
years), FHA reports that first-time homebuyers accounted for 80.5 
percent of all home loans that it insured between 1999 and 2001 and 
the GSEs report that first-time homebuyers accounted for 26.5 
percent of the home loans purchased by each GSE during that same 
period. Given FHA's low downpayment requirements, it is not 
surprising that FHA focuses on first-time homebuyers. The GSEs, on 
the other hand, fall at the other end of the continuum, with their 
first-time homebuyer share (26.5 percent) falling far short of the 
first-time homebuyer share (37.6 percent) of the conventional 
conforming market. Section E will include a more detailed comparison 
of the GSEs and the conventional conforming market in serving first-
time homebuyers. In addition, Section E will conduct a market share 
analysis that examines the funding of minority first-time 
homebuyers. Consistent with the earlier discussion, that analysis 
suggests that conventional lenders and the GSEs have played a 
relatively small role in the market for minority first-time 
homebuyers. One analysis reported in Section E estimates that 
mortgage purchases by the GSEs between 1999 and 2001 totaled 41.5 
percent of all home loans originated, but they accounted for only 
14.3 percent of home loans originated for first-time African-
American and Hispanic homebuyers.
---------------------------------------------------------------------------

    \130\ In this case, the market includes all government and 
conventional loans, including jumbo loans.
---------------------------------------------------------------------------

c. Community Reinvestment Act

    The Community Reinvestment Act (CRA) requires depository 
institutions to help meet the credit needs of their 
communities.\131\ CRA loans are typically made to low-income 
borrowers earning less than 80 percent of area median income, and in 
moderate-income neighborhoods. CRA provides an incentive for lenders 
to initiate affordable lending programs with underwriting 
flexibility. CRA loans are usually smaller than typical conventional 
mortgages and also are more likely to have a higher LTV, higher 
debt-to-income ratios and no payment reserves, and may not be 
carrying private mortgage insurance (PMI). Generally, at the time 
CRA loans are originated, many do not meet the underwriting 
guidelines required in order for them to be purchased by one of the 
GSEs. Therefore, many of the CRA loans are held in portfolio by 
lenders, rather than sold to Fannie Mae or Freddie Mac. Evidence is 
growing that CRA-type lending to low-income families can be 
profitable, particularly when combined with intensive loss 
mitigation efforts to control credit risk. In a recent survey 
conducted by the Federal Reserve, lenders reported that most CRA

[[Page 24286]]

loans are profitable although not as profitable as the lenders' 
standard products.\132\
---------------------------------------------------------------------------

    \131\ For a comprehensive analysis of CRA and its impact on 
affordable lending, see Robert E. Litan, Nicolas P. Retsinas, Eric 
S. Belsky and Susan White Haag, The Community Reinvestment Act After 
Financial Modernization: A Baseline Report, U.S. Department of 
Treasury, 2000.
    \132\ Board of Governors of the Federal Reserve System. The 
Performance and Profitability of CRA-Related Lending. Washington, 
DC, 2000.
---------------------------------------------------------------------------

    Some anticipate that the big growth market over the next decade 
for CRA-type lending will be urban areas. There has been some 
movement of population back to cities, consisting of aging Baby 
Boomers (so-called ``empty nesters''), the children of Baby Boomers 
(the Echo Boomers aged 18-25), and immigrants, particularly 
Hispanics but also Asians.\133\ The current low homeownership in 
inner cities (compared with the suburbs) also suggests that urban 
areas may be a potential growth market for lenders. Lenders are 
beginning to recognize that urban borrowers are different from 
suburban borrowers. A new or recent immigrant may have no credit 
history or, more likely, a loan-worthy credit history that can't be 
substantiated by the usual methods.\134\ Products for duplexes and 
four-plexes are not the same as a mortgage for a subdivision house 
in the suburbs. Programs are being implemented to meet the unique 
needs of urban borrowers. One program emphasizing urban areas was 
initiated by the American Community Bankers (ACB). Under the ACB 
program, which made $16.2 billion in loans in 2002, lenders 
originated a variety of affordable products for first-time 
homebuyers and non-traditional borrowers that are then sold to 
Fannie Mae, Freddie Mac, Countrywide, or other investors that are 
partnering with the ACB. It is reported that some lenders are making 
these non-traditional loans for the first time.
---------------------------------------------------------------------------

    \133\ This discussion of urban lending draws from Jeff Siegel, 
``Urban Lending Helps Increase Volume and Meet CRA Requirements,'' 
Secondary Marketing Executive, February 2003, pp. 21-23.
    \134\ Ibid.
---------------------------------------------------------------------------

    For banks and thrifts, selling their CRA loans will free up 
capital to make new CRA loans. As a result, the CRA market segment 
provides an opportunity for Fannie Mae and Freddie Mac to expand 
their affordable lending programs. Section E.3c below presents data 
showing that purchasing targeted seasoned loans has been one 
strategy that Fannie Mae has chosen to improve its goals 
performance. Fannie Mae has been offering CRA programs since mid-
1997, when it launched a pilot program, ``Community Reinvestment Act 
Portfolio Initiative,'' for purchasing seasoned CRA loans in bulk 
transactions, taking into account track record as opposed to relying 
just on underwriting guidelines. Fannie Mae also started another 
pilot program in 1998, involving purchases of CRA loans on a flow 
basis, as they are originated. By 2001, Fannie Mae was investing 
$10.3 billion in initiatives targeted to aid financial institutions 
in meeting their CRA obligations. One CRA-eligible product in 2002 
included the MyCommunityMortgage suite, which provides flexible 
product options for low- to moderate-income borrowers purchasing 
one- to four-unit homes.\135\ In 2002, Fannie Mae purchased or 
securitized more than $882.5 million of MyCommunityMortgage 
products, which helped provide affordable housing solutions for 
7,866 households.\136\ In addition, Freddie Mac is also purchasing 
seasoned affordable mortgage portfolios originated by depositories 
to help meet their CRA objectives. In 2002, Freddie Mac developed 
credit enhancements that enable depositories to profitably sell 
their loans to Freddie Mac--these transactions facilitate targeted 
affordable lending activity by providing immediate liquidity. 
Freddie Mac also increased its ability to purchase smaller 
portfolios opening this option to many community banks that 
otherwise would not have an outlet for their portfolios.\137\ The 
billions of dollars worth of CRA loans that will be originated, as 
well as the CRA loans being held in bank and thrift portfolios, 
offer both GSEs an opportunity to improve their performance in the 
single-family area.
---------------------------------------------------------------------------

    \135\ Fannie Mae, (2002), p. 5.
    \136\ Fannie Mae, 2002 Annual Housing Activities Report, p. 9.
    \137\ Fannie Mae, 2002 Annual Housing Activities Report, p. 59.
---------------------------------------------------------------------------

6. Potential Homebuyers

    While the growth in affordable lending and homeownership has 
been strong in recent years, attaining this Nation's homeownership 
goals will not be possible without tapping into the vast pool of 
potential homebuyers. Due to record low interest rates, expanded 
homeownership outreach, and new flexible mortgage products, the 
homeownership rate reached an annual record of 67.9 percent in 2002, 
reaching 68.3 percent in the fourth quarter of 2002. This section 
discusses the potential for further increases beyond those resulting 
from current demographic trends.
    The potential homeowner population over the next decade will be 
highly diverse, as growing housing demand from immigrants (both 
those who are already here and those projected to come) and non-
traditional homebuyers will help to offset declines in the demand 
for housing caused by the aging of the population. As noted in the 
above discussion of CRA, many of these potential homeowners will be 
located in urban areas. Immigrants and other minorities--who 
accounted for nearly 40 percent of the growth in the nation's 
homeownership rate over the past five years--will be responsible for 
almost two-thirds of the growth in the number of new households over 
the next ten years (between 2000 and 2010), as well as over the next 
25 years (between 2000 and 2025).\138\ By 2025, non-family 
households will make up a third of all households. Non-Hispanic 
white and traditional households will contribute only one-third and 
one-tenth of the growth in new households, respectively. Fannie Mae 
staff report that between 1980 and 1995, the number of new immigrant 
owners increased by 1.4 million; and between 1995 and 2010, that 
figure is expected to rise to by more than 50 percent to 2.2 
million. These trends do not depend on the future inflow of new 
immigrants, as immigrants don't enter the housing market until they 
have been in this country for eleven years. As noted by Fannie Mae 
staff, ``there are enough immigrants already in this country to keep 
housing strong for at least six and perhaps even 10 more years.'' 
\139\ As these demographic factors play out, the overall effect on 
housing demand will likely be sustained growth and an increasingly 
diverse household population from which to draw new homeowners.
---------------------------------------------------------------------------

    \138\ This section draws from ``Immigration Changes Won't Hurt 
Housing,'' Nation Mortgage News, January 27, 2003, p. 8.
    \139\ Ibid.
---------------------------------------------------------------------------

    Surveys indicate that these demographic trends will be 
reinforced by the fact that most Americans desire, and plan, to 
become homeowners. According to the 2002 Fannie Mae Foundation 
annual National Housing Survey, Americans rate homeownership as the 
best investment they can make, far ahead of 401Ks, retirement 
accounts, and stocks. The percentage of Americans who said it was a 
good time to buy a home was at its highest level since 1994 at 75 
percent, a jump of 21 percentage points since May 2001.\140\ In 
addition, the survey found that 27 percent of Americans report they 
are likely to buy in the next three years, and 23 percent of those 
have started to save or have saved enough money for a down 
payment.\141\
    Further increases in the homeownership rate depend on whether or 
not recent gains in the home owning share(s) of specific groups are 
maintained. Minorities accounted for 17 percent of owner households 
in 2001, but the Joint Center for Housing Studies reports that 
minorities were responsible for more than 40 percent (a total of 5.2 
million) of the net growth in homeowners between 1993 and 2002.\142\ 
As reported by the Fannie Mae survey, 42 percent of African-American 
families reported that they were ``very or fairly likely'' to buy a 
home in the next three years, up from 38 percent in 1998 and 25 
percent in 1997. Among Hispanics and Hispanic immigrants, the 
numbers reached 37 percent and 34 percent respectively. The 2002 
survey also reports that more than half of Hispanic renters cite 
homeownership as being ``one of their top priorities.'' In addition, 
nearly a third (31 percent) of baby boomers said they are ``very or 
fairly likely'' to buy a home in the next three years.
---------------------------------------------------------------------------

    \140\ Fannie Mae, Fannie Mae National Housing Survey, 2002, p. 
6.
    \141\ Ibid. p. 8.
    \142\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 2003, p. 15.
---------------------------------------------------------------------------

    In spite of these trends, potential minority homebuyers see more 
obstacles to buying a home, compared with the general public. 
Typically, the primary barriers to ownership are credit issues and a 
lack of funds for a downpayment and closing costs. But Freddie Mac 
staff emphasize that ``immigrants and minorities face additional 
hurdles, including a lack of affordable housing, little 
understanding of the home buying process, and continuing financial 
obligations in their home countries.'' \143\ In the Fannie Mae 
survey, minority groups reported misconceptions about the difficulty 
of becoming a homeowner such as beliefs about the amount of down 
payment required and mortgage lending practices, a lack of 
confidence about the homebuying process, poor credit ratings, and 
language barriers. In addition, there are continuing concerns about 
the limited education and low-income levels

[[Page 24287]]

of recent immigrants and other minorities. Thus, the new group of 
potential homeowners will have unique needs. To tap this potential 
homeowner population, the mortgage industry will have to address 
these needs on several fronts, such as expanding education and 
outreach efforts, introducing new products, and adjusting current 
underwriting standards to better reflect the special circumstances 
of these new households.
---------------------------------------------------------------------------

    \143\ ``Immigration Changes. * * *'' Op. cit.
---------------------------------------------------------------------------

    The Bush administration has outlined a plan to expand minority 
homeownership by 5.5 million families by the end of the decade. The 
Joint Center for Housing Studies has stated that if favorable 
economic and housing market trends continue, and if additional 
efforts to target mortgage lending to low-income and minority 
households are made, the overall homeownership rate could reach 70 
percent by 2010.\144\
---------------------------------------------------------------------------

    \144\ Joint Center for Housing Studies of Harvard University, 
State of the Nation's Housing 1998, p. 20.
---------------------------------------------------------------------------

7. Automated Underwriting Systems and Mortgage Scorecards

    This, and the following two sections, discuss special topics 
that have impacted the primary and secondary mortgage markets in 
recent years. They are automated mortgage scoring, subprime loans, 
and risk-based pricing. The GSEs' use of automated underwriting and 
mortgage scoring systems was briefly discussed in the earlier 
section on underwriting standards. This section expands on issues 
related to automated underwriting, a process that has spread 
throughout the mortgage landscape over the past five years, due 
mainly to the efforts of Fannie Mae and Freddie Mac.
    According to Freddie Mac economists, automated mortgage scoring 
has enabled lenders to expand homeownership opportunities, 
particularly for underserved populations.\145\ There is growing 
evidence that automated mortgage scoring is more accurate than 
manual underwriting in predicting borrower risks. Mortgage 
scorecards express the probability that an applicant will default as 
a function of several underwriting variables such as the level of 
down payment, monthly-payment-to-income ratios, cash reserves, and 
various indicators of an applicant's creditworthiness or credit 
history. Mortgage scorecards are statistically estimated regression-
type equations, based on historical relationships between mortgage 
foreclosures (or defaults) and the underwriting variables. The level 
of down payment and credit history indicators, such as a FICO score, 
are typically the most important predictors of default in mortgage 
scoring systems.
---------------------------------------------------------------------------

    \145\ Peter M. Zorn, Susan Gates, and Vanessa Perry, ``Automated 
Underwriting and Lending Outcomes: The Effect of Improved Mortgage 
Risk Assessment on Under-Served Populations. Program on Housing and 
Urban Policy,'' Conference Paper Series, Fisher Center for Real 
Estate and Urban Economics. University of California Berkeley, 2001, 
p. 5.
---------------------------------------------------------------------------

    This increased accuracy in risk assessment of mortgage 
scorecards has allowed risk managers to set more lenient risk 
standards, and thus originate more loans to marginal applicants. 
Applicants who would otherwise be rejected by manual underwriting 
are being qualified for mortgages with automated mortgage scoring in 
part because the scorecard allows an applicant's weaker areas to be 
offset by stronger characteristics. Typically, applicants whose 
projected monthly debt payment (mortgage payment plus credit card 
payment plus automobile loan payment and so on) comprise a high 
percentage of their monthly income would be turned down by a 
traditional underwriting system that relied on fixed debt-to-income 
ratios (such as 36 percent). In a mortgage scoring system, these 
same applicants might be automatically accepted for a loan due to 
their stellar credit record or to their ability to raise more cash 
for a down payment. The entity funding or insuring the mortgage 
(i.e., a lender, private mortgage insurer, or a GSE) allows these 
positive characteristics to offset the negative characteristics 
because its confidence in the ability of the empirically-based 
mortgage scorecard to accurately identify those applicants who are 
more likely or less likely to eventually default on their loan.
    Automated mortgage scoring was developed as a high-tech tool 
with the purpose of identifying credit risks in a more efficient 
manner. Automated mortgage scoring has grown as competition and 
decreased profit margins have created demands to reduce loan 
origination costs. As a result, automated mortgage scoring has 
become the predominant (around 60 to 70 percent) mortgage 
underwriting method.\146\ As time and cost are reduced by the 
automated system, the hope was that more time would be devoted by 
underwriters to qualifying marginal loan applicants that are 
referred by the automated system for a more intensive, manual 
underwriting 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.
---------------------------------------------------------------------------

    \146\ John W. Straka, ``A Shift in the Mortgage Landscape: The 
1990s Move to Automated Credit Evaluations,'' Journal of Housing 
Research, 2000, (11)2: p. 207.
---------------------------------------------------------------------------

    As explained above, automated mortgage scoring allows tradeoffs 
between risk factors to be quantified more precisely, providing the 
industry more confidence in ``pushing the envelope'' of acceptable 
expected default rates. The GSEs' willingness to offer low-down-
payment programs was based on their belief that their scoring models 
could identify the more creditworthy of the cash-constrained 
applicants. The GSEs' new ``timely reward'' products for subprime 
borrowers (discussed later) are integrated with their mortgage 
scoring systems. Automated mortgage scoring presents the opportunity 
to remove discrimination from mortgage underwriting, to accept all 
applicants, and to bring fair, objective, statistically based 
competitive pricing, greatly reducing costs for all risk groups. 
Some institutions have sought to better model and automate marginal 
and higher-risk loans, which have tended to be more costly to 
underwrite and more difficult to automate.\147\
---------------------------------------------------------------------------

    \147\ Ibid. pp. 208-217.
---------------------------------------------------------------------------

    Along with the promise of benefits, however, automated mortgage 
scoring has raised concerns. These concerns are related to the 
possibility of disparate impact and the proprietary nature of the 
mortgage score inputs. The first concern is that low-income and 
minority homebuyers will not score well enough to be accepted by the 
automated underwriting system, resulting in their getting fewer 
loans. African-American and Hispanic borrowers, for example, tend to 
have a poorer credit history record than other borrowers, which 
means they are more likely to be referred (rather than automatically 
accepted) by automated mortgage scoring systems that rely heavily on 
credit history measures such as a FICO score. There is also a 
significant statistical relationship between credit history scores 
and the minority composition of an area, after controlling for other 
locational characteristics.\148\
---------------------------------------------------------------------------

    \148\ Robert B. Avery, Raphael W. Bostic, Paul S. Calem, and 
Glenn B. Canner, Credit Scoring: Issues and Evidence from Credit 
Bureau Files, mimeo, 1998, p. 24.
---------------------------------------------------------------------------

    The second concern relates to the ``black box'' nature of the 
scoring algorithm. The scoring algorithm is proprietary and 
therefore it is difficult for applicants to know the reasons for 
their scores. However, it should be noted that the GSEs have taken 
steps to make their automated underwriting systems more transparent. 
Both Fannie Mae and Freddie Mac have published the factors used to 
make loan purchase decisions in Desktop Underwriter and Loan 
Prospector, respectively. In response to criticisms aimed at using 
FICO scores in mortgage underwriting, Fannie Mae's new 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.\149\
---------------------------------------------------------------------------

    \149\ Fannie Mae, September 4, 2002, p. 33.
---------------------------------------------------------------------------

    With automated mortgage scoring replacing traditional manual 
underwriting comes the fear that the loss of individual attention 
poses a problem for people who have inaccuracies on their credit 
report or for members of cultural groups or recent immigrants who do 
not use traditional credit and do not have a credit score. Some 
subprime lenders and underwriters have claimed that their manual 
underwriting of

[[Page 24288]]

high-risk borrowers cannot be automated with mortgage scoring. 
Although automated mortgage scoring has greatly reduced the cost of 
many lower-risk loans that are easier to rate, the cost of manually 
underwriting gray-area and higher-risk applicants still remains 
high.\150\ There is also the fear that applicants who are referred 
by the automated system will not be given the full manual 
underwriting for the product that they initially applied for--rather 
they might be pushed off to higher priced products such as a 
subprime or FHA loan. In this case, the applicant may have had 
special circumstances that would have been clarified by the 
traditional manual underwriting, thus enabling the applicant to 
receive a prime loan consistent with his or her creditworthiness.
---------------------------------------------------------------------------

    \150\ Kenneth Temkin, Jennifer E.H. Johnson, and Diane Levy, 
Subprime Markets, The Role of GSEs, and Risk-Based Pricing, 
Washington: The Urban Institute. Report Prepared for the U.S. 
Department of Housing and Urban Development, 2002.
---------------------------------------------------------------------------

    Banking regulators and legal analysts acknowledge the value of 
automated mortgage scoring, although some skeptics have noted 
concerns regarding fair lending, potential fraud, privacy issues, 
and the ability of models to withstand changing economic 
conditions.\151\ With the rise of automated mortgage scoring, the 
great difference in Internet usage known as the ``digital divide'' 
could result in informational disadvantages for less educated and 
lower-income consumers. In addition to the digital divide, the lack 
of financial literacy in the United States may also result in a 
disparate impact on low-income and minority borrowers.\152\
---------------------------------------------------------------------------

    \151\ Allen J. Fishbein, ``Is Credit Scoring a Winner for 
Everyone?'' Stone Soup, 2000, 14(3): pp. 14-15. See also Fitch IBCA, 
Inc., Residential Mortgage Credit Scoring, New York, 1995 and Jim 
Kunkel, ``The Risk of Mortgage Automation,'' in Mortgage Banking, 
1995, 57(8): pp. 69-76.
    \152\ Zorn et al., 2001, pp. 19-20.
---------------------------------------------------------------------------

    2002 Urban Institute Study. The Urban Institute submitted a 
report to HUD in 2002 on subprime markets, the role of GSEs, and 
risk-based pricing.\153\ The study took a preliminary look at the 
use of automated underwriting systems for a small sample of lenders. 
After conducting interviews with both subprime and prime lenders, 
the report noted that all of the lenders in the study had 
implemented some type of automated underwriting system. These 
lenders stated that automated underwriting raised their business 
volume and streamlined their approval process. In addition, the 
lenders reported they were able to direct more underwriting 
resources to borderline applications despite an increase in business 
volume.
---------------------------------------------------------------------------

    \153\ Kenneth Temkin, Jennifer E.H. Johnson, and Diane Levy, 
Subprime Markets, The Role of GSEs, and Risk-Based Pricing, 
Washington: The Urban Institute. Report Prepared for the U.S. 
Department of Housing and Urban Development, 2002.
---------------------------------------------------------------------------

    Even with the use of automated mortgage scoring, the lenders in 
the study continued to conduct at least a cursory review to validate 
the application material. The majority of the lenders still used 
manual underwriting to originate loans not recommended for approval 
with automated mortgage scoring. The lenders reported they 
formulated their policies and procedures to make certain that 
borrowers receive the best mortgage, according to product 
eligibility. This study will be further referenced in a following 
section regarding subprime markets.
    2001 Freddie Mac Study. According to a Freddie Mac study 
published by the Fisher Center for Real Estate and Urban Economics 
at University of California at Berkeley, underserved populations 
have benefited from automated mortgage scoring because of the 
increased ability to distinguish between a range of credit risks. In 
this paper, Freddie Mac economists compared the manual and automated 
mortgage scoring approval rates of a sample of minority loans 
originated in 1993-94 and purchased by Freddie Mac. While manual 
underwriters rated 51 percent of the minority loans in the sample as 
accept, automated mortgage scoring would have rated 79 percent of 
the loans as accept.\154\
---------------------------------------------------------------------------

    \154\ Zorn, et al., 2001, pp. 14-15.
---------------------------------------------------------------------------

    In comparison to manual underwriting, this study found automated 
mortgage scoring not only less discriminatory but also more accurate 
in predicting risk. Two versions of Freddie Mac's automated 
underwriting system, Loan Prospector (LP), were used to review three 
groups of mortgage loans purchased by Freddie Mac.\155\ The study 
found that LP was a highly accurate predictor of mortgage default. 
The resulting improved accuracy translates into benefits for 
borrowers, who would otherwise be rejected by manual underwriting to 
qualify for mortgages.
---------------------------------------------------------------------------

    \155\ Ibid. p. 5.
---------------------------------------------------------------------------

    Analysis of the first group of loans showed that loans rated as 
``caution'' were four times more likely to default than the average 
for all loans. Minority borrowers whose loans were rated as 
``caution'' were five times more likely to default, and low-income 
borrowers whose loans were rated as ``caution'' were four times more 
likely to default than the average for all loans. The 2000 version 
of LP approved 87.1 percent of loans generated through affordable 
housing programs, compared to a 51.6 percent approval rate when the 
same loans were assessed using manual underwriting procedures. 
Further, the study found LP more accurate than manual underwriting 
at predicting default risk even with a higher approval rate. The 
study also demonstrated that Freddie Mac's year 2000 version of LP 
was more accurate in predicting risk than its 1995 version.
    Concluding Observations. Automated underwriting has enabled 
lenders to reach new markets and expand homeownership opportunities, 
as illustrated by the 2001 Freddie Mac study. Increased accuracy 
with automated mortgage scoring has led to the development of new 
mortgage products that would have been previously considered too 
risky. For example, Freddie Mac uses Loan Prospector to approve Alt 
A loans, which tend to have nontraditional documentation; A-minus 
loans, which pose a higher risk of default; and other higher-risk 
mortgages, like 100 percent LTV loans. Both GSEs have and continue 
to add new products to develop their automated underwriting systems 
to reach more marginal borrowers.
    Despite the gains in automated mortgage scoring and other 
innovations, minorities are still less likely to be approved for a 
loan. The difference in minority and non-minority accept rates may 
reflect greater social inequities in financial capacity and credit, 
which are integral variables in both manual and automated 
underwriting. In the future, the accuracy of automated mortgage 
scoring will hinge on updating the models and making them more 
predictive while reducing the disparate impact on low-income and 
minority borrowers.\156\ The fairness of automated scoring systems 
will also depend importantly on whether referred applicants receive 
a traditional manual underwriting for the loan that they initially 
applied for, rather than being immediately offered a higher priced 
loan that does not recognize their true creditworthiness.
---------------------------------------------------------------------------

    \156\ Ibid. pp. 18-19.
---------------------------------------------------------------------------

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

8. Subprime Lending

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

a. The Growth and Characteristics of Subprime Loans

    The subprime market has grown rapidly over the past several 
years, increasing from an estimated $35 billion in 1994 to $160 
billion in 1999 and $173.3 billion in 2001, before rising to $213 
billion in 2002. The subprime share of total market originations 
rose from 4.6 percent in 1994 to a high of 15 percent in 1999, and 
then fell to 8.5 percent in both 2001 and 2002.\157\ Various factors 
have led to the rapid growth in the subprime market: federal 
legislation preempting state restrictions on allowable rates and 
loan features, the tax reform act of 1986 which encouraged tax-
exempt home equity financing of consumer debt, increased demand for 
and availability of consumer debt, a substantial increase in 
homeowner equity due to house price appreciation, and a ready supply 
of available funds through

[[Page 24289]]

Wall Street securitization.\158\ It is important to note that 
subprime lending grew in the 1990s mostly without the assistance of 
Fannie Mae and Freddie Mac.
---------------------------------------------------------------------------

    \157\ Subprime origination data are from Inside Mortgage 
Finance. For the 2002 estimates, see ``Subprime Origination Market 
Shows Strong Growth in 2002,'' Inside B&C Lending, published by 
Inside Mortgage Finance, February 3, 2003, page 1.
    \158\ Temkin et. al, 2002, p.1.
---------------------------------------------------------------------------

    Generally, there are three different types of products available 
for subprime borrowers. These include: home purchase and refinance 
mortgages designed for borrowers with poor credit histories; ``Alt 
A'' mortgages that are usually originated for borrowers who are 
unable to document all of the underwriting information but who may 
have solid credit records; and high loan-to-value mortgages 
originated to borrowers with fairly good credit. Fannie Mae and 
Freddie Mac are more likely to serve the first two types of subprime 
borrowers.\159\
---------------------------------------------------------------------------

    \159\ Kenneth Temkin, Jennifer E.H. Johnson, Diane Levy, 
Subprime Markets, The Role of GSEs, and Risk Based Pricing, 
Washington: The Urban Institute. Report Prepared for the Department 
of Housing and Urban Development, 2002, p. 4.
---------------------------------------------------------------------------

    Borrowers use subprime loans for various purposes, which include 
debt consolidation, home improvements, and an alternative source of 
consumer credit. Between 1999 and 2001, about two-thirds of subprime 
loans were refinance loans. It has been estimated that 59 percent of 
refinance loans were ``cash out'' loans.\160\ According to a joint 
HUD-Treasury report, first liens accounted for more than three out 
of four loans in the subprime market.
---------------------------------------------------------------------------

    \160\ U.S. Department of Housing and Urban Development/U.S. 
Department of the Treasury, Curbing Predatory Lending Report, 2000, 
p. 31.
---------------------------------------------------------------------------

    The subprime market is divided into different risk categories, 
ranging from least risky to most risky: A-minus, B, C, and D. While 
there are no clear industry standards for defining the subprime risk 
categories, Inside Mortgage Finance defines them in terms of FICO 
scores--580-620 for A-minus, 560-580 for B, 540-560 for C, and less 
than 540 for D. The A-minus share of the subprime market rose from 
61.6 percent in 2000 to 70.7 percent in 2001.\161\ For the first 
nine months of 2002, the A-minus share accounted for 74 percent of 
the market, while the B share accounted for 11 percent, the C share 
accounted for 7.2 percent, and the D share accounted for 7.9 percent 
of the market.\162\
---------------------------------------------------------------------------

    \161\ ``Wholesale Dominates Subprime Market Through 3rd Quarter 
'02,'' Inside B&C Lending, published by Inside Mortgage Finance, 
December 16, 2002, pp. 1-2.
    \162\ Inside B&C Lending, November 16, 2002, p. 2.
---------------------------------------------------------------------------

    Delinquency rates by type of subprime loan are as follows: 3.36 
percent for A-minus loans, 6.67 percent for B, 9.22 percent for C, 
and 21.03 percent for D, according to the Mortgage Information 
Corporation.\163\ Because of their higher risk of default, subprime 
loans typically carry much higher mortgage rates than prime 
mortgages. Recent quotes for a 30-year Fixed Rate Mortgage were 8.85 
percent for A-minus (with an 85 percent LTV), 9.10 percent for B 
credit (with an 80 percent LTV), and 10.35 percent for C credit 
(with a 75 percent LTV).\164\ As the low loan-to-value (LTV) ratios 
indicate, one loss mitigation technique used by subprime lenders is 
a high down payment requirement. Some housing advocates have 
expressed concern that the perceptions about the risk of subprime 
loans may not always be accurate, for example, creditworthy 
borrowers in inner city neighborhoods may be forced to use subprime 
lenders because mainstream lenders are not doing business in their 
neighborhoods (see below).
---------------------------------------------------------------------------

    \163\ Mortgage Information Corporation, The Market Pulse, Winter 
2001, pp. 4-6.
    \164\ Inside B&C Lending, published by Inside Mortgage Finance, 
February 17, 2003, page 13.
---------------------------------------------------------------------------

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

b. The Neighborhood Concentration of Subprime Lending

    The growth in subprime lending over the last several years has 
benefited credit-impaired borrowers as well as those borrowers who 
choose to provide little documentation for underwriting. However, 
studies showing that subprime lending is disproportionately 
concentrated in low-income and minority neighborhoods have raised 
concerns about whether mainstream lenders are adequately serving 
these neighborhoods. A study of subprime lending in Chicago by The 
Woodstock Institute concluded that a dual, hyper-segmented mortgage 
market existed in Chicago, as mainstream lenders active in white and 
upper-income neighborhoods were much less active in low-income and 
minority neighborhoods--effectively leaving these neighborhoods to 
unregulated subprime lenders.\165\ As part of the HUD-Treasury Task 
Force on Predatory Lending, HUD's Office of Policy Development and 
Research released a national level study--titled Unequal Burden: 
Income and Racial Disparities in Subprime Lending in America--that 
showed families living in low-income and African-American 
neighborhoods in 1998 relied disproportionately on subprime 
refinance lending, even after controlling for neighborhood income. 
An update of that analysis for the year 2000 yields the following 
trends: \166\
---------------------------------------------------------------------------

    \165\ Daniel Immergluck, The Predatory Lending Crisis in 
Chicago: The Dual Mortgage Market and Local Policy, testimony before 
the Chicago City Council, April 5, 2000. Immergluck found that 
subprime lenders received 74 percent of refinance applications in 
predominantly black tracts compared to 21 percent in predominantly 
white tracts in 1998. According to Immergluck, these racial 
disparities provide evidence that the residential finance market in 
Chicago is hypersegmented, resulting in the increased likelihood 
that minorities receive mortgage credit from a subprime, rather than 
a prime, lender in Chicago. Also see Daniel Immergluck, Stark 
Differences: The Explosion of the Subprime Industry and Racial 
Hypersegmentation in Home Equity Lending, Woodstock Institute, 
October 2000.
    \166\ See Randall M. Scheessele, Black and White Disparities in 
Subprime Mortgage Refinance Lending, Housing Finance Working Paper 
HF-014, Office of Policy Development and Research, U.S. Department 
of Housing and Urban Development, April 2002.
---------------------------------------------------------------------------

     In 2000, 36 percent of refinance mortgages in 
low-income neighborhoods were subprime, compared with only 16 
percent in upper-income neighborhoods.
     Subprime lending accounted for 50 percent of 
refinance loans in majority African-American neighborhoods--compared 
with only 21 percent in predominantly white areas (less than 30 
percent of population is African-American).
     The most dramatic view of the disparity in 
subprime lending comes from comparing homeowners in upper-income 
African-American and white neighborhoods. Among homeowners living in 
the upper-income white neighborhoods, only 16 percent turned to 
subprime lenders in 2000. But 42 percent of homeowners living in 
upper-income African-American neighborhoods relied upon subprime 
refinancing which is substantially more than the rate (30 percent) 
for homeowners living in low-income white neighborhoods.
     Similar results are obtained when the 
analysis is conducted for borrowers instead of neighborhoods. Upper-
income African-American borrowers are twice as likely as low-income 
white borrowers to have subprime loans. Over one-half (54 percent) 
of low-income African-American borrowers turn to subprime lenders, 
as does over one-third (35 percent) of upper-income African-American 
borrowers. By comparison, only 24 percent of low-income white 
borrowers and 12 percent of upper-income white borrowers, rely upon 
subprime lenders for their refinance loans.\167\
---------------------------------------------------------------------------

    \167\ For an update to 2001, see The Association of Community 
Organizers for Reform Now (ACORN), Separate and Unequal Predatory 
Lending in America, 2002. In 2001, subprime lenders originated 27.8 
percent of all conventional refinance loans for African-Americans, 
13.6 percent for Hispanic homeowners, and just 6.3 percent for white 
homeowners. Overall, African-Americans were 4.4 times more likely to 
use a subprime lender than whites, and Hispanics were 2.2 times more 
likely to do so.
---------------------------------------------------------------------------

    It does not seem likely that these high market shares by 
subprime lenders in low-income and African-American neighborhoods 
can be justified by a heavier concentration of households with poor 
credit in these neighborhoods. Rather it appears that subprime 
lenders may have attained such high market shares by serving areas 
where prime lenders do not have a significant presence. The above 
finding that upper-income black borrowers rely more heavily on the 
subprime market than low-income white borrowers suggests that a 
portion of subprime lending is occurring with borrowers whose credit 
would qualify them for lower cost conventional prime loans. A lack 
of competition from prime lenders in low-income and minority 
neighborhoods has increased the chances that borrowers in these 
communities are paying a high cost for credit. As explained

[[Page 24290]]

next, there is also evidence that the higher interest rates charged 
by subprime lenders cannot be fully explained solely as a function 
of the additional risks they bear. Thus, a greater presence by 
mainstream lenders could possibly reduce the high up-front fees and 
interest rates being paid by residents of low-income and minority 
neighborhoods.
    The Freddie Mac study presented evidence that subprime loans 
bear interest rates that are higher than necessary to offset the 
higher credit risks of these loans.\168\ The study compared (a) the 
interest rate on subprime loans rated A-minus by the lenders 
originating these loans with (b) the interest rates on prime loans 
purchased by Freddie Mac and rated A-minus by a Freddie Mac 
underwriting model. Despite the fact that both loan groups were 
rated A-minus, on average the subprime loans bore interest rates 
that were 215 basis points higher. Even assuming that the credit 
risk of the subprime loans was in fact higher than the prime loans, 
the study could not account for such a large discrepancy in interest 
rates. Assuming that default rates might be three to four times 
higher for the subprime loans would account for a 90 basis point 
interest rate differential. Assuming that servicing the subprime 
loans would be more costly would justify an additional 25 basis 
point differential. But even after allowing for these possible 
differences, the Freddie Mac researchers concluded that the subprime 
loans had an unexplained interest rate premium of 100 basis points 
on average.\169\
    Banking regulators have recognized the link between the growth 
in subprime lending and the absence of mainstream lenders and have 
urged banks and thrifts that lending in these neighborhoods not only 
demonstrates responsible corporate citizenship but also profitable 
lending. Ellen Seidman, former Director of the Office of Thrift 
Supervision, stated that, ``Many of those served by the subprime 
market are creditworthy borrowers who are simply stuck with subprime 
loans or subprime lenders because they live in neighborhoods that 
have too few credit or banking opportunities.''
---------------------------------------------------------------------------

    \168\ Howard Lax, Michael Manti, Paul Raca, and Peter Zorn, 
``Subprime Lending: An Investigation of Economic Efficiency,'' 
February 25, 2000.
    \169\ It should also be noted that higher interest rates are 
only one component of the higher cost of subprime loans since 
borrowers also often face higher origination points. The Freddie Mac 
study did not find a large differential between prime and subprime 
loans in points paid, but the study notes that subprime loans often 
have points rolled into the loan principal, which cannot be 
identified with their data.
---------------------------------------------------------------------------

    With respect to the question of whether borrowers in the 
subprime market are sufficiently creditworthy to qualify for more 
traditional loans, Freddie Mac has said that one of the promises of 
automated underwriting is that it might be better able to identify 
borrowers who are unnecessarily assigned to the high-cost subprime 
market. Freddie Mac has estimated that 10-30 percent of borrowers 
who obtain mortgages in the subprime market could qualify for a 
conventional prime loan through Loan Prospector, Freddie Mac's 
automated underwriting system.\170\ Fannie Mae has stated that half 
of all mortgage borrowers steered to the high-cost subprime market 
are in the A-minus category, and therefore are prime candidates for 
Fannie Mae.\171\
---------------------------------------------------------------------------

    \170\ Freddie Mac, We Open Doors for America's Families, Freddie 
Mac's Annual Housing Activities Report for 1997, March 16, 1998, p. 
23.
    \171\ Rommy Fernandez, ``Fannie Mae Eyes Half of the Subprime 
Market,'' in The American Banker, March 1, 2002. Also see ``Fannie 
Mae Vows More Minority Lending,'' Washington Post, March 16, 2000, 
p. EO1.
---------------------------------------------------------------------------

c. Predatory Lending

    Predatory lending has been a disturbing part of the growth in 
the subprime market. Although questions remain about its magnitude, 
predatory lending has turned homeownership into a nightmare for far 
too many households. The growing incidence of abusive practices has 
been stripping borrowers of their home equity, threatening families 
with foreclosure, and destabilizing neighborhoods. Also, in some 
cities, there are indications that unscrupulous realtors, mortgage 
brokers, appraisers, and lenders are duping some FHA borrowers into 
purchasing homes at an inflated price or with significant 
undisclosed repairs. The problems associated with home equity fraud 
and other mortgage abuses are not new ones, but the extent of this 
activity seems to be increasing. The expansion of predatory lending 
practices along with subprime lending is especially troubling since 
subprime lending is disproportionately concentrated in low- and 
very-low income neighborhoods, and in African-American 
neighborhoods.
    The term ``predatory lending'' is a short hand term that is used 
to encompass a wide range of abuses. While there is broad public 
agreement that predatory lending should have no place in the 
mortgage market, there are differing views about the magnitude of 
the problem, or even how to define practices that make a loan 
predatory. The joint HUD-Treasury report, Curbing Predatory Home 
Mortgage Lending, concluded that a loan can be predatory when 
lenders or brokers: charge borrowers excessive, often hidden fees 
(called ``packing fees''); successively refinance loans at no 
benefit to the borrower (called ``loan flipping''); make loans 
without regard to a borrower's ability to repay; and, engage in 
high-pressure sales tactics or outright fraud and deception. These 
practices are often combined with loan terms that, alone or in 
combination, are abusive or make the borrower more vulnerable to 
abusive practices. Vulnerable populations, including the elderly and 
low-income individuals, and low-income or minority neighborhoods, 
appeared to be especially targeted by unscrupulous lenders.
    One consequence of predatory lending is that borrowers are 
stripped of the equity in their homes, which places them at an 
increased risk of foreclosure. In fact, high foreclosure rates for 
subprime loans provide the most concrete evidence that many subprime 
borrowers are entering into mortgage loans that they simply cannot 
afford. The high rate of foreclosures in the subprime market has 
been documented by HUD and others in recent research studies.\172\ 
These studies have found that foreclosures by subprime lenders grew 
rapidly during the 1990s and now exceed the subprime lenders' share 
of originations. In addition, the studies indicate that foreclosures 
of subprime loans occur much more quickly than foreclosures on prime 
loans, and that they are concentrated in low-income and African-
American neighborhoods. Of course, given the riskier nature of these 
loans, a higher foreclosure rate would be expected. With the 
information available it is not possible to evaluate whether the 
disparities in foreclosure rates are within the range of what would 
be expected for loans prudently originated within this risk class. 
But findings from these studies about the high rate of mortgage 
foreclosure associated with subprime lending reinforce the concern 
that predatory lending can potentially have devastating effects for 
individual families and their neighborhoods.
---------------------------------------------------------------------------

    \172\ For an overview of these studies, see Harold L. Bunce, 
Debbie Gruenstein, Christopher E. Herbert, Randall M. Scheessele, 
Subprime Foreclosures: The Smoking Gun of Predatory Lending, 2000. 
Also see Abt Associates Inc., Analyzing Trends in Subprime 
Originations and Foreclosures: A Case Study of the Atlanta Metro 
Area, February 2000 and Analyzing Trends in Subprime Originations 
and Foreclosures: A Case Study of the Boston Metro Area, September 
2000; National Training and Information Center, Preying on 
Neighborhoods: Subprime Mortgage Lenders and Chicagoland 
Foreclosures, 2000; and the HUD study, Unequal Burden in Baltimore: 
Income and Racial Disparities in Subprime Lending, May 2000.
---------------------------------------------------------------------------

    At this time, there are open questions about the effectiveness 
of the different approaches being proposed for eradicating predatory 
lending and the appropriate roles of different governmental 
agencies--more legislation versus increased enforcement of existing 
laws, long-run financial education versus mortgage counseling, 
Federal versus state and local actions. In its recent issuance of 
predatory lending standards for national banks, the Office of the 
Comptroller of the Currency (OCC) cited the efforts of Fannie Mae 
and Freddie Mac' in reducing predatory lending.\173\ The OCC advised 
banks against abusive practices, such as rolling single-premium life 
insurance into a loan. The agency cited guidelines developed by 
Fannie Mae and Freddie Mac as a ``useful reference'' or starting 
point for national banks. Following publication of HUD's proposed 
2000 Rule inviting comments on disallowing goals credit for high 
cost mortgage loans, Fannie Mae and Freddie Mac told lenders they 
would no longer purchase loans with certain abusive practices, such 
as excessive fees and failing to consider a borrower's ability to 
repay the debt.
---------------------------------------------------------------------------

    \173\ ``OCC Cites Fannie, Freddie Predatory Lending Rules As 
Model,'' Dow Jones Business News, February 25, 2003.
---------------------------------------------------------------------------

    It is important to re-emphasize that predatory lending generally 
occurs in neighborhoods where borrowers have limited access to 
mainstream lenders. While predatory lending can occur in the prime 
market, it is ordinarily deterred in that market by competition 
among lenders, greater homogeneity in loan terms and greater 
financial information among

[[Page 24291]]

borrowers. Thus, one solution to address this problem would be to 
encourage more mainstream lenders to do business in our inner city 
neighborhoods.

d. Purchases of Subprime Mortgages by the GSEs

    Fannie Mae and Freddie Mac have shown increasing interest in the 
subprime market since the latter half of the 1990s. The GSEs entered 
this market by purchasing securities backed by non-conforming loans. 
Freddie Mac, in particular, increased its subprime business through 
structured transactions, with Freddie Mac guaranteeing the senior 
classes of senior/subordinated securities. The two GSEs also 
purchase subprime loans on a flow basis. Fannie Mae began purchasing 
subprime loans through its Timely Payment Reward Mortgage program in 
June 1999, and Freddie Mac rolled out a similar product, Affordable 
Merit Rate, in May 2000 (described below). In addition to purchasing 
subprime loans for borrowers with blemished credit, the GSEs also 
purchase another non-conforming loan called an Alternative-A or 
``Alt-A'' mortgage. These mortgages are made to prime borrowers who 
do not want to provide full documentation for loans. The GSEs' 
interest in the subprime market has coincided with a maturation of 
their traditional market (the conforming conventional mortgage 
market), and their development of mortgage scoring systems, which 
they believe allows them to accurately model credit risk. Although 
the GSEs account for only a modest share of the subprime market 
today, some market analysts estimate that they could purchase as 
much as half of the overall subprime market in the next few 
years.\174\
---------------------------------------------------------------------------

    \174\ Temkin et al., 2002, p. 1.
---------------------------------------------------------------------------

    Precise information on the GSEs' purchases of subprime loans is 
not readily available. Data can be pieced together from various 
sources, but this can be a confusing exercise because of the 
different types of non-conforming loans (Alt-A and subprime) and the 
different channels through which the GSEs purchase these loans 
(through securitizations and through their ``flow-based'' product 
offerings). Freddie Mac, which has been the more aggressive GSE in 
the subprime market, purchased approximately $12 billion in subprime 
loans during 1999--$7 billion of A-minus and alternative-A loans 
through its standard flow programs and $5 billion through structured 
transactions.\175\ In 2000, Freddie Mac purchased $18.6 billion of 
subprime loans on a flow basis in addition to another $7.7 billion 
of subprime loans through structured transactions.\176\ Freddie Mac 
securitized $9 billion in subprime and Alt-A product in 2001 and 
$11.1 billion in 2002.
---------------------------------------------------------------------------

    \175\ David A. Andrukonis, ``Entering the Subprime Arena,'' 
Mortgage Banking, May 2000, pp. 57-60.
    \176\ Subprime Lenders Mixed on Issue of GSE Mission Creep,'' 
Inside B and C Lending, March 19, 2001.
---------------------------------------------------------------------------

    Fannie Mae initiated its Timely Payments product in September 
1999, under which borrowers with slightly damaged credit can qualify 
for a mortgage with a higher interest rate than prime borrowers. 
Under this product, a borrower's interest rate will be reduced by 
100 basis points if the borrower makes 24 consecutive monthly 
payments without a delinquency. Fannie Mae has revamped its 
automated underwriting system (Desktop Underwriter) so loans that 
were traditionally referred for manual underwriting are now given 
four risk classifications, three of which identify potential 
subprime (A-minus) loans.\177\ Fannie purchased about $600 million 
of subprime loans on a flow basis in 2000.\178\ Fannie Mae 
securitized around $0.6 billion in subprime mortgages in 2000, 
before increasing to $5.0 billion in 2001 and 7.3 billion in 
2002.\179\
---------------------------------------------------------------------------

    \177\ See Lederman, et al., Op cit.
    \178\ Kenneth Temkin, Jennifer E. H. Johnson, and Diane K. Levy, 
``Subprime Markets, the Role of GSEs, and Risk-Based Pricing,'' 
Urban Institute, August 2001, p. 1.
    \179\ Inside Mortgage Finance's, ``Inside MBS & ABS,'' December 
15, 2000 and March 8, 2002.
---------------------------------------------------------------------------

    In terms of total subprime activity (both flow and 
securitization activities), Fannie Mae purchased $9.2 billion in 
2001 and over $15 billion in 2002, the latter figure representing 
about 10 percent of the market, according to Fannie Mae staff.\180\
---------------------------------------------------------------------------

    \180\ Statement by Mercy Jimenez of Fannie Mae in ``Fannie Mae: 
Forges Ahead in Subprime,'' Secondary Marketing Executive, February 
2003, p.15.
---------------------------------------------------------------------------

    A greater GSE role in the subprime lending market will most 
likely have a significant impact on the subprime market. Currently, 
the majority of subprime loans are not purchased by GSEs, and the 
numbers of lenders originating subprime loans typically do not issue 
a large amount of prime loans. Partly in response to higher 
affordable housing goals set by HUD in its new rule set in 2000, the 
GSEs are increasing their business in the subprime market. In the 
2000 GSE Rule, HUD identified subprime borrowers as a market that 
can assist Fannie Mae and Freddie Mac in reaching their higher 
affordable housing goals while also helping establish more 
standardization in the subprime market. According to an Urban 
Institute study in 2002, many subprime lenders believe that 
successful companies serving high-risk borrowers need to have 
specialized expertise in outreach, servicing, and underwriting, 
which is lacking among most prime lenders.\181\ These lenders do not 
believe the more standardized approaches of prime lenders and the 
GSEs will work with subprime borrowers, who require the more 
customized and intensive origination and loan servicing processes 
currently offered by experienced subprime lenders.
---------------------------------------------------------------------------

    \181\ Temkin et al., 2002, p. 1
---------------------------------------------------------------------------

    As noted above, both Fannie Mae and Freddie Mac make the claim 
that the subprime market is inefficient, pointing to evidence 
indicating that subprime borrowers pay interest rates, points, and 
fees in excess of the increased costs associated with serving 
riskier borrowers in the subprime market. \182\ A recent Freddie Mac 
study found automated mortgage scoring less discriminatory and more 
accurate in predicting risk than manual systems such as those 
currently used by subprime lenders.\183\ According to Fannie Mae, 
although a high proportion of borrowers in the subprime market could 
qualify for less costly prime mortgages, it remains unclear why 
these borrowers end up in the subprime market.\184\ Fannie Mae and 
Freddie Mac believe they can bring more efficiency to the subprime 
market by creating standardized underwriting and pricing guidelines 
in the subprime market. An expanded GSE presence in the subprime 
market could be of significant benefit to lower-income and minority 
families if it attracted more mainstream lenders and competition to 
those inner-city neighborhoods that are currently served mainly by 
subprime lenders.
---------------------------------------------------------------------------

    \182\ See Lax et al., 2000.
    \183\ Zorn, et al., 2001, p. 5.
    \184\ Fannie Mae, Remarks Prepared for Delivery by Franklin 
Raines, Chairman and CEO of Fannie Mae to the National Community 
Reinvestment Coalition. Washington, DC, March 20, 2000.
---------------------------------------------------------------------------

    Many subprime lenders do not think it is appropriate for Fannie 
Mae and Freddie Mac to increase their role in the subprime market 
because they do not view the subprime market as inefficient. Some 
officials in subprime mortgage markets claim the higher prices paid 
by borrowers in the subprime market appropriately reflect the risks 
that come from extending credit to riskier borrowers. These 
officials believe it is unfair for GSEs to enter an efficient, 
private market that provides a necessary service to credit-impaired 
borrowers. Opponents of a larger GSE role in the subprime market 
argue GSEs have an unfair competitive advantage because they can 
secure capital at cheaper rates.\185\ Because the GSEs have a 
funding advantage over other market participants, they have the 
ability to under price their competitors and increase their market 
share.\186\ 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. Many subprime lenders fear they will be 
unfairly driven out of business as the GSEs increase their role in 
the subprime market.
---------------------------------------------------------------------------

    \185\ Temkin et al., 2002, p. 1.
    \186\ For an explanation of the GSEs funding advantage see 
Government Sponsorship of FNMA and FHLMC, United States Department 
of the Treasury, July 11, 1996.
---------------------------------------------------------------------------

9. Risk-Based Pricing

    The expanded use of automated underwriting and the initial uses 
of risk-based pricing are changing the mortgage lending environment, 
often blurring the distinctions between the prime and subprime 
market. Prime lenders are now using automated underwriting systems 
that are being adapted to facilitate risk-based pricing. For some 
time, the majority of prime mortgage borrowers have received loan 
rates based on average cost pricing. Generally, borrowers receive 
roughly the same Annual Percentage Rate \187\ (APR), regardless of 
the risk of loss to the lender. The risk of all borrowers is 
averaged together, and the price is determined by the average risk.
    In contrast, risk-based pricing enables mortgage lenders to 
offer each borrower an individualized interest rate based on his or 
her risk. Or, more broadly, to offer interest rates based on whether 
or not the borrower

[[Page 24292]]

falls into a certain category of risk, such as specific loan-to-
value and FICO score combination or specified mortgage score range. 
Lenders could also set the interest rate based on various factors 
including the probability of prepayment and characteristics of the 
underlying collateral, as well as the default risk of the borrower. 
Borrowers that pose a lower risk of loss to the lender would then be 
charged a comparatively lower rate than those borrowers with greater 
risk. Rather than lower risk borrowers cross-subsidizing higher risk 
borrowers like in average cost pricing, lower risk borrowers pay a 
relatively lower rate.
---------------------------------------------------------------------------

    \187\ Annual Percentage Rate takes into account points, fees, 
and the periodic interest rate.
---------------------------------------------------------------------------

    In response to the expanded use of automated underwriting and 
pressures from the GSEs, other purchasers of loans, mortgage 
insurers, and rating firms, lenders are increasing their use of 
risk-based pricing.\188\ In today's markets, some form of 
differential pricing exists for the various subprime categories, for 
new products targeted at credit-impaired borrowers (such as Fannie 
Mae's Timely Payments product), and for private mortgage insurance 
across all credit ranges. For example, private mortgage insurers use 
FICO scores and ``Accept'' determinations from the GSEs'' automated 
underwriting systems to make adjustments to insurance premiums.\189\ 
Rating agencies vary subordination requirements based on the credit 
qualify of the underlying collateral.
---------------------------------------------------------------------------

    \188\ Temkin et al., 2002, p. 29.
    \189\ For example, see Radian's product offerings at http://www.radiangroupinc.com.
---------------------------------------------------------------------------

    Many believe there is cross-subsidization within the crude risk 
categories used in today's market. For example, some of the better 
quality subprime borrowers in the A-minus category may be 
inappropriately assigned to the subprime market. The GSEs and others 
are attempting to learn more about the subprime market, and their 
initial efforts suggest that there will be an increase in the use of 
risk-based pricing within this market, although it is recognized 
that the expansion of risk-based pricing depends importantly on 
these parties gaining a better understanding of the subprime 
borrower and the ability of their mortgage scoring systems to 
predict risk within this market. It must be noted that the power of 
the underlying algorithm in automated underwriting systems 
determines the ability of these systems to accurately predict risk 
and set prices.
    If prime lenders adopted risk-based pricing, many would be 
willing to lend to riskier subprime borrowers because their risk 
would now be offset with an increase in price. In theory, the 
mortgage market should expand because all mortgages will be approved 
at a price commensurate with risk, rather than setting a risk floor 
and approving no one beneath the floor. Risk-based pricing could 
also expand the prime lenders' market by enabling them to reach a 
new group of underserved customers.\190\ Taking advantage of GSEs' 
lower cost of capital, GSEs may be able to offer borrowers who could 
not afford a rate in the subprime market a rate they can afford 
resulting from risk-based pricing.
---------------------------------------------------------------------------

    \190\ Vanessa Bush, ``Risk-Based Pricing Trend Could Make 
Mortgage Lending More Efficient,'' America's Community Banker, 
October 1, 1998.
---------------------------------------------------------------------------

    Risk-based pricing also poses challenges on the mortgage market 
because some of the more risky borrowers (who are currently cross-
subsidized by less risky borrowers) may not be able to afford their 
higher, risk-based interest rate. Also, the adoption of an automated 
risk-based pricing system may have an uncertain effect on minority 
groups, who tend to have lower credit scores, as discussed earlier. 
On the other hand, if minorities are eligible for prime financing, 
the cost of financing minorities may fall as will the potential for 
subprime lenders to draw minorities to their higher-priced products.
    As the GSEs become more comfortable with subprime lending, the 
line between what today is considered a subprime loan versus a prime 
loan will likely deteriorate, making expansion by the GSEs look more 
like an increase in the prime market. This melding of markets could 
occur even if many of the underlying characteristics of subprime 
borrowers and the market's evaluation of the risks posed by these 
borrowers remain unchanged. Increased involvement by the GSEs in the 
subprime market will result in more standardized underwriting 
guidelines and the increased participation of traditional lenders. 
In fact, there are indications that mainstream players are already 
increasing their activity in this market. According to staff from 
Moody's Investors Service, the growing role of large mortgage 
aggregators in the subprime market has been a key factor in the 
improving credit qualify on deals issued in 2002.\191\ According to 
a representative from Washington Mutual, subprime credit qualify has 
also improved as lenders carve out new loan categories that fall 
somewhere between the large Alt A market and traditional subprime 
business.\192\ As the subprime market becomes more standardized, 
market efficiencies will reduce borrowing costs. Lending to credit-
impaired borrowers will, in turn, increasingly make good business 
sense for the mortgage market.
---------------------------------------------------------------------------

    \191\ ``Improving Credit Quality, Maturing Business Stoke 
Confidence in Subprime MBS Market,'' Inside MBS & ABS, published by 
Inside Mortgage Finance, February 21, 2003.
    \192\ Ibid.
---------------------------------------------------------------------------

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

1. Introduction

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

2. The Multifamily Rental Housing Market: 2000-2003

    The definition of ``good'' market conditions in multifamily 
rental housing depends on one's perspective. Investors and lenders 
like low vacancies, steady rent increases, and rising property 
values. Developers like strong demand for new construction and 
favorable terms on construction financing. Consumers, in contrast, 
prefer low rents and a wide selection of available apartments.
    The mid- to late-1990s were among the most successful of recent 
history, in that apartment market conditions were generally good for 
all of these interest groups. Investment returns were favorable, 
construction volumes were steady at sustainable levels, and many 
consumers had income gains in excess of their rent increases.
    Market conditions for multifamily rental housing began to weaken 
toward the end of 2000. Early warnings came from the publicly traded 
apartment companies, some of which reported easing in demand growth 
in the first months of 2001, coinciding with a slowdown in job 
growth to its lowest level since 1992.
    By the second quarter of 2001, most apartment market indicators 
were reflecting the slowdown. Vacancies were up, approaching 10 
percent for all multifamily (5+ units in structure) rental housing, 
according to the Census Bureau, and about half that rate among the 
larger apartment properties monitored by private market research 
firms. The FDIC's Survey of Real Estate Trends detected the first 
signs of weakening in the first half of 2001, followed by a big 
falloff in second half of the year and a continuing slide in the 
first half of 2002.
    Apartments--especially those serving the top end of the rental 
market--appear to have

[[Page 24293]]

performed worse than other rental housing in the past four years, 
after several years of rent growth and occupancies surpassing the 
rental market averages. The multifamily vacancy rate has increased 
more than the overall rental market vacancy rate in each of the 
years 2000, 2002, and 2003. In 2001, the vacancy rates increased at 
an equivalent rate. For example, the Census Bureau's estimate of a 
1.2 percentage point increase in vacancies for apartments in the 
year ending in the third quarter of 2003 exceeds the overall rental 
vacancy rate of .9%. Similarly, while rent growth has decelerated 
slightly for all rental housing according to the CPI, industry 
surveys of apartment rents show year-over-year declines in rents in 
many local markets.\193\ In 2003, asking rents remained flat 
nationally, as multifamily completions declined 5 percent.\194\
---------------------------------------------------------------------------

    \193\ See, for example, Marcus & Millichap Research Services, 
National Apartment Report, January 2003.
    \194\ Marcus & Millichap Research Services, National Apartment 
Report, January 2004.
---------------------------------------------------------------------------

a. Apartment Demand and Supply

    The primary reason for the softening in the multifamily rental 
market has been a reduction in the growth of consumer demand for 
apartment housing. The general slowdown in economic activity meant 
fewer apartment customers, with less money, than if the economy were 
vigorously expanding. Persistent low interest rates have also 
enticed renters into the home purchase market as evidenced by the 
U.S. homeownership rate, which grew to 68.4 percent in 2003, further 
contributing to a weakness in rental demand.
    The reduced demand is most evident in the national statistics on 
employment. Job growth began decelerating in late 2000 and 
throughout 2001, turning negative late that year. The largest year-
over-year job loss of the economic downturn occurred in February 
2002, and year-over-year losses have continued through October 2003. 
Apartment demand seems particularly sensitive to labor market 
conditions, given the importance of rental housing to mobile 
individuals and families accepting new jobs or transfers. Reis, 
Inc., a real estate market research firm, estimates that the total 
number of occupied apartments (in properties with 40+ units) 
actually declined in both 2001 and 2002 in the large markets 
nationwide that are monitored by the company.\195\
---------------------------------------------------------------------------

    \195\ ``Apartment Landlords Gather to Dreary Outlook for 
Sector,'' Wall Street Journal, January 15, 2003, Section B.
---------------------------------------------------------------------------

    Households, not jobs, fill apartments, and for this reason 
household formations are a preferable indicator of demand for 
apartments as well as other types of housing. The Census Bureau 
estimates that the total number of renter households nationwide has 
been essentially unchanged at approximately 34.8 million since 1996. 
Yet during the late 1990s apartment demand was expanding, and 
apartments were apparently picking up market share from other rental 
housing. The past two or three years may have seen a reversal of 
that trend in share.
    Long-term demographic trends are expected to be favorable for 
rental housing demand.\196\ The maturing of the ``Baby Boom Echo'' 
generation will increase the number of persons under age 25 who will 
seek rental housing, immigration is expected to continue to fuel 
demand for rental housing, and minority populations, while 
increasing their homeownership rates, are growing and will 
contribute to higher absolute demand for rental housing. Thus 
demographic trends support an improvement in the long-run demand for 
rental demand, which is likely to include higher multifamily rental 
demand.
---------------------------------------------------------------------------

    \196\ Mortgage Bankers Association of America, ``MBA News Link: 
Rental Market Demographics ``Favorable,'' Report Says,'' January 
2003.
---------------------------------------------------------------------------

    Supply growth has been maintained, even though the current 
reduced multifamily demand warrants less new construction. Total 
multifamily starts (2+ units) have been running approximately 325-
to-350 thousand annually for the past six years, according to Census 
Bureau statistics, adding about 1 percent annually to the total 
multifamily stock. Most of these new units are built for rental use, 
with only about 20 percent in recent years reported as being built 
as for-sale condominium units.
    The reduced short-term demand has shown through in absorption 
speeds for new apartments. The percentage of newly completed 
unfurnished apartments rented within three months of completion fell 
from 71 percent during the first quarter of 2000 to 64 percent 
during the first quarter of 2001 and to 58 percent during the first 
quarter of 2002, according to the Census Bureau. This percentage 
rose slightly to 59 percent in the first quarter of 2003.

b. Performance by Market Segments

    Some segments of the multifamily rental market have been more 
affected than others by the recent softening. As mentioned earlier, 
the top end of the apartment market seems especially hard hit, as 
measured by rising vacancies and reduced rent growth. This segment 
is particularly dependent on job growth and transfers for new 
customers, and is particularly vulnerable to losses of residents and 
prospective customers to home purchase. According to reports by 
apartment REITs and other investors, these top-end properties have 
not been getting the job-related in-movers, but have still been 
losing a lot of customers to home purchase. These properties 
generally have annual resident turnover rates of above 50 percent, 
and thus are particularly quickly influenced by changes in demand. 
Furthermore, this is the segment of the apartment market into which 
most of the new construction is built.
    Performance has varied geographically as well. Some of the 
coastal markets, especially in Northern California, saw the double-
digit rent increases of the late 1990s replaced by double-digit 
declines, before stabilizing more recently. ``Supply constrained 
markets'' had been preferred by apartment investors during the 
1990s, but recent market performance has reminded investors and 
analysts that all markets have their day. For example, Houston 
posted the biggest year-over-year rent increase of any major 
apartment market in 2001, despite a long-run history of moderate 
rent growth and few barriers to new apartment construction. Rent 
changes in the 27 metropolitan markets for which estimates are 
available from the CPI ranged from a low of -0.3 percent to a high 
of 6.7 percent in the first half of 2003 relative to a year earlier. 
And across the 75 metropolitan areas for which rental vacancy rates 
(apartments plus other rentals combined) are available, rates for 
the year 2002 ranged from 2.4 percent to 15.4 percent, according to 
the Census Bureau. In a historical context, this variation is 
moderate, although up somewhat since the late 1990s.
    Conditions in the ``affordable'' segment of the apartment market 
are harder to track than in the high-end segment because of lesser 
investor interest and analyst coverage. Data for the late 1990s 
analyzed by the National Housing Conference saw affordability 
problems continuing, although a study of apartment renters by the 
National Multi Housing Council saw some improvement in affordability 
during the strong economic growth of 1997-1999.\197\ Other work 
noted that rent to income ratios for the lowest income quintile of 
renters rose during the late 1990s even as these ratios were stable 
or declining for other renters.\198\ Harvard's State of the Nation's 
Housing report for 2002 highlighted the variability of the 
affordability problem from place to place.\199\
---------------------------------------------------------------------------

    \197\ Center for Housing Policy/National Housing Conference, 
``Housing America's Working Families: A Further Exploration,'' New 
Century Housing, Vol. 3, No. 1, March 2002; Mark Obrinsky and Jill 
Meron, ``Housing Affordability: The Apartment Universe,'' National 
Multi Housing Council, 2002.
    \198\ ``Housing Affordability in the United States: Trends, 
Interpretations, and Outlook,'' a report prepared for the Millennial 
Housing Commission by J. Goodman, November, 2001.
    \199\ Joint Center for Housing Studies of Harvard University, 
The State of the Nation's Housing, 2002.
---------------------------------------------------------------------------

    Little research is available on affordability trends since 1999. 
However, tabulations from the 2001 American Housing Survey indicate 
that income growth between 1999 and 2001 in the lowest quintile of 
renter households continued to lag that of higher income renters, 
and fell short of the average rent increases during this period. 
Together, these statistics suggest that affordability has 
deteriorated early this decade among at least this group of very 
low-income renters. Other work using the AHS found that the number 
of low-to moderate-income working families with severe rental cost 
burdens increased 24 percent between 1999 and 2001.\200\
    The low-income housing tax credit (LIHTC) continues to finance 
much of the newly built multifamily rental housing that is 
affordable to households with moderate income. Restricted to 
households with incomes no greater than 60 percent of the local 
median, this program financed approximately 75,000 units in 2001, 
according to the National Council of State Housing Agencies, after 
running in the mid- to high-60 thousand range the previous three 
years. About 70 percent of these units are newly built, and the rest 
are renovations of existing units.
---------------------------------------------------------------------------

    \200\ Center for Housing Policy/National Housing Conference, 
``America's Working Families and the Housing Landscape 1997-2001,'' 
New Century Housing, Vol. 3, No. 2, November 2002.
---------------------------------------------------------------------------

    Expenditures for improvements to existing rental apartments have 
grown in recent years.

[[Page 24294]]

In 2001 the total of $11.3 billion was nearly twice the figure of 
three years earlier, according to the Census Bureau, and more than a 
third as large as construction spending for newly built multifamily 
structures, including owner-occupied condos. Many of these 
improvements are to older properties in high-demand neighborhoods. 
Improvements to the physical structures have external benefits. But 
often the renovations are in connection with re-positionings that 
move the apartments into a higher rent range and bring changes in 
the demographic composition of the resident base.
    In 2002, expenditures on total improvements to existing 
apartments declined to $9.8 billion, while new construction spending 
increased $2 billion. This shift further suggests a re-positioning 
to apartments with a higher rent range. Excluding units financed 
with tax credits or other subsidies, most of the multifamily rental 
construction in recent years has been targeted on the upper end of 
the market, often the only segment for which unsubsidized new 
construction is economically feasible. The median asking rent on new 
unfurnished apartments completed in 2001 was $877, up 11 percent 
over the previous two years. In 2002 median asking rent for these 
properties was $905. Of those units brought to market in 2002, 45 
percent were at rents at or above $950.

3. Multifamily Financing Trends

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

a. Lending Volume

    Total multifamily mortgage debt outstanding increased 9.5 
percent in 2000 (Q4/Q4), 11.4 percent in 2001, and 8.6 percent in 
2002, according to the Federal Reserve's Flow of funds accounts. 
This trend continued through the third quarter of 2003, which saw a 
12.4 percent annualized increase. The dollar volumes were above 
those of any previous year, and far exceeded the lending volumes of 
all years other than 1998 and the frenzied period 1985-86. The pace 
has picked up slightly in 2003, with figures through the first two 
quarters indicating annualized growth of about 9 percent. 
Furthermore, a survey by the Mortgage Bankers Association of America 
shows that of 48 member firms surveyed, representing all large 
mortgage banking firms and a cross section of smaller mortgage 
companies, multifamily origination volume increased by 16 percent in 
2002--from $35 billion in 2001 to $41 billion in 2002.
    The apparent inconsistency between current market fundamentals 
and financing can be explained by low interest rates. The same 
financial forces that lowered the mortgage rates for home purchasers 
to record lows by 2002 also reduced the financing costs of 
multifamily properties. The ten year Treasury yield, a common 
benchmark for multifamily loan pricing, fell to a 45-year low of 3.3 
percent in June 2003 from 6.3 percent as recently as the end of 
1999.
    Another feature boosting investor demand for apartment 
properties and the resulting demand for debt to finance those 
purchases has been the lack of attractive returns on many financial 
assets and other alternative investments. Despite the current weak 
performance of apartments, investors apparently are looking through 
to the long-run outlook for these assets, which is generally thought 
to be favorable, as indicated most recently by investor surveys 
fielded by the Urban Land Institute and by LendLease and 
PriceWaterhouseCoopers.\201\
---------------------------------------------------------------------------

    \201\ Urban Land Institute, The ULI Forecast, 2002; Lendlease 
and Prive WaterhouseCoopers, Emerging Trends in Real Estate, 2003.
---------------------------------------------------------------------------

    The net change in mortgage debt outstanding is defined as loan 
originations less repayments and charge offs. As discussed in 
Appendix D, net change is a lower bound on originations. By all 
accounts, originations--for which no single source of estimates is 
available--are much higher than net change in most years. High 
levels of refinancings of existing multifamily mortgages in recent 
years has been a factor in originations exceeding the net change in 
debt outstanding.
    Most mortgage lending is in the ``conventional'' market. 
Multifamily loan programs of the Federal Housing Administration 
accounted about $7 billion in new insured mortgages in fiscal year 
2003--up from $6 billion in fiscal year 2002 and $5 billion in 
fiscal 2001. Despite the recent increase in FHA originations, and 
the likely continued strong performance for FHA multifamily programs 
in the foreseeable future,\202\ FHA remains but a small portion of 
the total multifamily mortgage market. Outstanding FHA-insured 
multifamily mortgage debt was $55 billion at the end of the first 
quarter of 2003--only about 11 percent of all multifamily mortgage 
debt outstanding.
---------------------------------------------------------------------------

    \202\ Merrill Lynch, A New Look at FHA Prepayments and Defaults, 
September 2002.
---------------------------------------------------------------------------

    Multifamily lending has been spurred by new apartment 
construction, property sales, and refinancings. New multifamily 
construction was valued at $32.6 billion in 2002, according to the 
Census Bureau, up 14 percent from 2000. The number of new 
multifamily units completed over this period actually declined 6 
percent, and the increased expenditures reflect higher costs per 
unit. The increase in asking rents described earlier suggests higher 
property values and greater debt carrying capacity.

b. Property Sales and Refinancings

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

c. Sources of Financing and Credit Quality

    The sources of funding of multifamily mortgages shifted somewhat 
in the past few years, judging from the Flow of Funds accounts. As 
shown in Table A.4, four categories of lenders have dominated 
multifamily mortgage lending since the mid-1990s. Of those four, 
commercial banks have played a lesser, although still substantial, 
role in recent years, providing 20 percent of the $86 billion in net 
additional funding of multifamily mortgages during 2000 and 2001.

[[Page 24295]]

The portfolio holdings of the GSEs, by contrast, have been much more 
important than during the last half of the 1990s. Mortgage backed 
securities, both from the GSEs and especially from other issuers, 
accounted for proportionally less of the growth in 2000-01 than in 
1995-99, but between them still accounted for nearly half of all the 
net credit extensions. Some slight broadening of the base of 
multifamily lending in the past two years, as these four lender 
groups accounted for only 85 percent of the net credit extended in 
2000 and 2001, compared to all of it in the previous five-year 
period.
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[[Page 24297]]

    The market values of apartment properties have generally held up 
well, although the most recent indicators suggest some flattening. 
Properties in the portfolios of pension funds continued to 
appreciate into the second half of 2002, according to the National 
Council of Real Estate Investment Fiduciaries, although at a reduced 
annual rate of less than 2 percent. And the sales price per square 
foot of ``Class A'' properties monitored by Global Real Analytics 
rose until turning down in early 2002, posting a 1.6 percent year 
over year decline in the second quarter.
    The continuing value of collateral has helped keep loan quality 
high on multifamily mortgages. Delinquency rates from all major 
reporters are at or near record lows, and well below the rates 
reported for single-family mortgages and commercial properties. At 
commercial banks, the FDIC reports a non-current loan percentage of 
0.38 in the second quarter of 2002. In life insurance company 
portfolios only .05 percent of residential mortgages were overdue at 
the end of 2002, and as of the third quarter of 2002 the GSEs were 
both reporting similarly miniscule delinquency rates of below 0.1 
percent; all of these rates are below those of a year earlier.
    Multifamily lenders have remained cautious in their underwriting 
and, together with their regulators, have avoided repeating the 
mistakes of the 1980s. Many of the senior loan officers surveyed 
quarterly by the Federal Reserve have reported tightening their 
terms on commercial mortgages, and that shift likely has occurred in 
their multifamily lending as well. Perhaps the best indicator of 
discipline in multifamily lending is the fact that, despite the 
strong apartment demand during the last half of the 1990s, 
construction never rose above its long-run sustainable level, unlike 
the rampant overbuilding that plagued the industry in the mid- and 
late-1980s.

4. Recent GSE Involvement in Multifamily Finance

    As the multifamily mortgage market has expanded since 1999, 
Fannie Mae and Freddie Mac have increased their lending, picked up 
market share, introduced new programs, and enhanced others.
    Beginning with their whole loans, the GSEs added 34 percent to 
their combined holdings of multifamily loans in 2001, and another 26 
percent in 2002 (see Table A.6 below). The growth in multifamily MBS 
volume was nearly as dramatic, increasing 26 percent in 2001 and 
another 14 percent in 2002. The gains resulted in the GSEs 
increasing their share (whole loans and securities combined) of all 
multifamily debt outstanding to 22.8 percent by the third quarter of 
2003, up from 19 percent at year-end 2001, 15 percent at year-end 
1999 and 11 percent at the end of 1995. By this combined measure of 
portfolio holdings and MBS outstanding, at year-end 2002 Fannie Mae 
had nearly twice ($65 billion versus $37 billion) the multifamily 
business of Freddie Mac, although Freddie was growing its 
multifamily business more rapidly (67 percent increase between 2000 
and 2002, compared to 46 percent increase for Fannie Mae).
    Measures that focus on new multifamily activity, specifically 
gross mortgage purchase volumes and new security issuance, vary 
across recent years and between the GSEs. For the GSEs combined, 
these measures of current business activity show sharp gains of over 
70 percent in 2001, following small decreases in activity in 2000. 
In 2002, the GSEs combined posted small declines for both measures. 
Measures of multifamily gross mortgage purchases and new security 
issuance diverged for the two GSEs in 2002. Fannie Mae experienced 
declines in these balance sheet and new business indicators in 2002 
while Freddie Mac experienced gains, particularly in new security 
issuance. As discussed earlier, the credit quality of GSE 
multifamily loans has remained very high even with the large gains 
in loan volume.
    Despite the substantial pickup in GSE multifamily activity, the 
position of these companies in the multifamily mortgage market 
remains well below their dominance in single-family mortgage 
finance. At the end of 2002, the GSEs' market share of single family 
debt outstanding was 44 percent, twice the share of multifamily debt 
held or securitized by these two companies, according to Federal 
Reserve statistics. Furthermore, the multifamily share of all 
housing units financed by the GSEs combined has declined from its 
1997 level (Table A.5), although the annual statistics are heavily 
influenced by the volume of refinancings in the single-family 
market, which spiked in 1998 and again in 2001 and 2002 in response 
to the big decline in mortgage rates in those years. Because of 
lock-out agreements and other loan covenants, multifamily loans are 
not as prone to rate-induced refinancings as are single-family 
mortgages.
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[[Page 24298]]

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[[Page 24299]]



a. Contrasting Business Models

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

[[Page 24300]]

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BILLING CODE 4210-27-C

[[Page 24301]]

    The differing emphasis on portfolio holdings and securities 
issuance is related to the GSEs' contrasting approaches to credit 
underwriting.\203\ Fannie Mae has long had risk-sharing arrangements 
with its multifamily loan originators, and currently has over 25 
Delegated Underwriters and Servicers who are authorized to originate 
loans meeting Fannie Mae's requirements for sale to the GSE without 
prior approval of individual transactions. These ``DUS'' lenders 
retain part of the credit risk on the loans sold to Fannie.
---------------------------------------------------------------------------

    \203\ ``No Mistaking GSEs for Twins in Multifamily,'' American 
Banker, October 2, 2002.
---------------------------------------------------------------------------

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

b. Affordable Multifamily Lending

    Because most of the GSEs' multifamily lending is on properties 
affordable to households with low- or moderate incomes, financing of 
affordable multifamily housing by the GSEs has increased almost as 
much as their total multifamily lending. Approximately 86 percent of 
Fannie Mae's multifamily lending volume in 2002 qualified as 
affordable to low- or moderate income households, according to 
Fannie Mae's annual Housing Activity Report, as did 93 percent of 
Freddie Mac's multifamily units financed. For the entire multifamily 
rental market, HUD estimates that 90 percent of all housing units 
qualify as affordable to families at 100 percent of the area median, 
the standard upon which the low- and moderate-income housing goal is 
defined.
    Owing to this high propensity to qualify as affordable lending, 
financing of multifamily rental housing is especially important for 
the GSEs attainment of their affordable housing goals. Less than 8 
percent of the units financed by the GSEs in 2002 were multifamily 
rentals, as described above. Yet 15 percent of the units qualifying 
as low- and moderate-income purchases were multifamily, according to 
Table 1 of the GSEs' activity reports for 2002.
    The GSEs increased the volume of their affordable multifamily 
lending dramatically in 2001, the first year of the new, higher 
affordable housing goals set for the GSEs. As measured by number of 
units financed, the total affordable lending (shown in the ``low-mod 
total'' rows of Table A.7) more than doubled from a year earlier, 
especially after application of the upward adjustment factor 
authorized for Freddie Mac in the 2000 Rule. In 2002, the GSEs 
maintained a high volume of affordable multifamily lending with 
Fannie Mae showing a slight decrease and Freddie Mac a slight 
increase.
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[[Page 24302]]

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BILLING CODE 4210-27-C

[[Page 24303]]

    The figures in Table A.7 are exclusive of the ``Temporary 
Adjustment Factor (TAF)'' granted to Freddie Mac as part of the 2000 
Rule. The TAF was a response to Freddie Mac's limited opportunities 
for refinancing business because of its minimal involvement in the 
multifamily market in the early and mid-1990s. \204\ The TAF, which 
expired at the end of 2003, provided a 20 percent upward adjustment 
to multifamily units in properties with 50 or more units, for 
purposes of the affordable housing goals.
---------------------------------------------------------------------------

    \204\ For background information on the Freddie Mac TAF, see 
pages 65054 and 65067-65068 of the 2000 Rule.
---------------------------------------------------------------------------

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

c. Multifamily Initiatives of the GSEs

    Fannie Mae and Freddie Mac have taken a number of steps since 
2000 to expand their multifamily lending and to respond specifically 
to the goals established in the 2000 Rule. These initiatives are 
summarized in the annual activity reports filed by the GSEs.\205\
---------------------------------------------------------------------------

    \205\ Fannie Mae's 2002 Annual Housing Activities Report, pages 
24-27; Freddie Mac's Annual Housing Activities Report for 2002, 
pages 41-47.
---------------------------------------------------------------------------

    One focus of the 2000 Rule was on lending to small (5-to-50 
units) multifamily properties, which the Rule identified as an 
underserved market. HUD-sponsored research has found that the supply 
of mortgage credit to small properties was impeded by the 
substantial fixed costs of multifamily loan originations, by owners' 
insufficient documentation of property income and expense, and by 
the limited opportunities for fees for underwriting and servicing 
small loans.\206\ As a result, many multifamily lenders focus on 
larger properties, which were found to have more loan products 
available to them and to pay lower interest rates than did small 
properties.
---------------------------------------------------------------------------

    \206\ Abt Associates Inc., An Assessment of the Availability and 
Cost of Financing for Small Mulifamily Properties, a report prepared 
for the U.S. Department of Housing and Urban Development, Office of 
Policy Development and Research, August 2001.
---------------------------------------------------------------------------

    In an attempt to promote the supply of credit to small 
properties, the 2000 Rule provided incentives for the GSEs to step 
up their involvement in this segment of the multifamily mortgage 
market. The incentives likely contributed to the huge increases in 
small property lending posted by both Fannie Mae and Freddie Mac in 
2001 and continuing into 2002 (Table A.7). The combined total of 
these units financed in 2001 and 2002 was almost 8 times those 
financed in the previous two years. This lifted the percentage of 
all GSE multifamily lending that was on small properties to their 
highest levels ever.
    Programs introduced or enhanced by the GSEs in the past two 
years have contributed to these striking numerical results. 
Delegated Underwriting and Servicing (DUS) is Fannie Mae's principle 
product line for purchasing individual multifamily loans. This 
product line is offered through 26 lenders with expertise in 
financing multifamily properties. In 2002, 92% of the DUS loan 
activity served affordable housing needs, 41% of DUS loans in 
underserved markets, and 51% addressed ``special affordable'' 
needs.\207\ Fannie Mae markets its specialized 3MaxExpress product 
line for loans worth less than or equal to $3 million. This program 
helped secure $4.1 billion in financing since 2001, which has 
assisted 130,000 families living in small multifamily 
properties.\208\ Fannie Mae additionally has federal Low-Income 
Housing Tax Credit (LIHTC) programs and special financing projects 
for special use properties such as Seniors Housing.\209\
---------------------------------------------------------------------------

    \207\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 25.
    \208\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 25.
    \209\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 26-27.
---------------------------------------------------------------------------

    During 2002, Freddie Mac used innovative financing structures 
combined with prudent, flexible multifamily lending practices, which 
were targeted at affordable initiatives through its Program Plus 
network of lenders resulting in record levels of multifamily 
mortgage purchases. The GSEs face strong competition in this market 
from small banks and other depository institutions that prefer to 
hold these loans in their own portfolios.\210\
---------------------------------------------------------------------------

    \210\ ``Fannie Courting Multifamily Sellers; Small Banks 
Balking,'' American Banker, January 13, 2003.
---------------------------------------------------------------------------

    The 2000 Rule discussed other ways in which the GSEs might help 
promote financing of affordable multifamily housing. Two of those 
were lending for property rehabilitation and leadership in 
establishing standards for affordable multifamily lending. Many 
affordable properties are old and in need of capital improvements if 
they are to remain in the housing stock. Rehabilitation lending is a 
specialized field, and one in which the GSEs for a variety of 
reasons have not been major players. Less than 1 percent of all GSE 
multifamily lending in 2002 was for property rehabilitation. In 
2002, Fannie Mae hosted its first ever Preservation Advisory Meeting 
with leaders in the housing and real estate finance industry to 
identify best practices and formulate real world solutions to this 
critical policy issue.\211\
---------------------------------------------------------------------------

    \211\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 27.
---------------------------------------------------------------------------

    Setting standards for affordable multifamily lending was 
identified in the 2000 Rule as another area where the GSEs could 
provide greater leadership. It was also noted, based on HUD-
sponsored research underway at that time,\212\ that market 
participants believe the GSEs to be conservative in their approaches 
to affordable property lending and underwriting. Actions described 
in the GSEs' annual activity reports for 2001 and 2002 indicate 
attempts by the GSEs to promote market standards that will reduce 
the transactions costs of multifamily lending while also providing 
programs that have the flexibility needed to deal with unique 
circumstances.
---------------------------------------------------------------------------

    \212\ Abt Associates, ``Study of Multifamily Underwriting and 
the GSEs' Role in the Multifamily Market,'' Final Report to the U.S. 
Department of Housing and Urban Development, Office of Policy 
Development and Research, August 2001.
---------------------------------------------------------------------------

5. Future Prospects

    The outlook for the multifamily rental housing market is marked 
by near-term risks and longer-run optimism, according to most 
observers. The prospects for the next few quarters are dominated by 
the macroeconomy. In particular, job growth, with its implications 
for formations of households, will be a key for the resumption of 
growth in apartment demand. Many forecasters would ascribe to the 
Federal Reserve's forecast of a slight increase in GDP growth to 4.3 
percent in 2004,\213\ while also agreeing with the Fed's warning 
that ``An unusual degree of uncertainty attends the economic outlook 
at present, in large measure, but not exclusively, because of 
potential geopolitical developments.'' \214\
---------------------------------------------------------------------------

    \213\ Federal Reserve, Survey of Professional Forecasters, 
November 2003.
    \214\ Board of Governors of the Federal Reserve System, Monetary 
Policy Report to the Congress, February 11, 2003, page 4.
---------------------------------------------------------------------------

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

[[Page 24304]]

to increase more rapidly than that for other rental housing, owing 
to the likely changes in age composition and reductions in average 
household size. One estimate projects the annual growth in apartment 
households to be one percent.\215\
---------------------------------------------------------------------------

    \215\ Jack Goodman, ``The Changing Demography of Multifamily 
Rental Housing,'' Housing Policy Debate, Winter 1999.
---------------------------------------------------------------------------

a. The Outlook for Multifamily Housing Supply

    Regarding supply, one of the secrets of the success of the 
multifamily sector during the 1990s was that production never rose 
above its long-run sustainable level. The discipline of developers, 
investors, and their lenders that brought that result needs to be 
continued if the apartment market is to maintain stability.
    Multifamily housing may benefit in the future from more 
favorable public attitudes and local land use regulation. Higher 
density housing is a potentially powerful tool for preserving open 
space, reducing sprawl, and promoting transportation alternatives to 
the automobile. The recently heightened attention to these issues 
may increase the acceptance of multifamily rental construction to 
both potential customers and their prospective neighbors.
    Provision of affordable housing will continue to challenge 
suppliers of multifamily rental housing and policy makers at all 
levels of governments. Low incomes combined with high housing costs 
define a difficult situation for millions of renter households. 
Housing cost reductions are constrained by high land prices and 
construction costs in many markets. Government action--through land 
use regulation, building codes, and occupancy standards--are major 
contributors to those high costs, as is widely recognized by market 
participants, including the leaders of the GSEs.\216\ Reflecting the 
preferences of the electorate, these regulated constraints are 
unlikely to change until voter attitudes change.
---------------------------------------------------------------------------

    \216\ Remarks by Franklin D. Raines, Chairman and CEO, Fannie 
Mae, to the Executive Committee of the National Association of Home 
Builders, January 18, 2003. See also Edward Glaeser and Joseph 
Gyourko, ``The Impact of Zoning on Housing Affordability,'' Working 
Paper 8835, National Bureau of Economic Research, March 2002.
---------------------------------------------------------------------------

b. The Future Role of the GSEs

    Regarding the mortgage financing of multifamily rental 
apartments, it is hard to anticipate events that might disrupt the 
flow or alter the sources of mortgage credit to apartments. In the 
past, certain events have triggered such changes--notably the 
savings and loan debacle of the 1980s and Freddie Mac's withdrawal 
from the market following large losses in the early 1990s--but these 
are, by definition, surprises. The current structure and performance 
of the multifamily mortgage market provide some comfort that the 
risks are slight. The lender base is not overly dependent on any one 
institution or lender type for either loan originations or funding. 
Lending discipline appears to have been maintained, given the low 
mortgage delinquency rates even during the weak economy of the past 
two years. The near term outlook of most market participants is for 
ample supply of mortgage financing at historically low interest 
rates.\217\ Yet complacency would be a mistake.
---------------------------------------------------------------------------

    \217\ ``Capital Markets Outlook 2003,'' Apartment Finance Today, 
Vol. 7, No. 1 (January/February 2003).
---------------------------------------------------------------------------

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

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

    This section first discusses each GSE's performance under the 
Low- and Moderate-Income Housing Goal over the 1996-2002 
period.\218\ The data presented are ``official results''--i.e., they 
are based on HUD's analysis of the loan-level data submitted to the 
Department by the GSEs and the counting provisions contained in 
HUD's regulations in 24 CFR part 81, subpart B. As explained below, 
in some cases these ``official results'' differ from goal 
performance reported by the GSEs in the Annual Housing Activities 
Reports (AHARs) that they submit to the Department.
---------------------------------------------------------------------------

    \218\ Performance for the 1993-95 period was discussed in the 
October 2000 rule.
---------------------------------------------------------------------------

    The main finding of this section concerning the overall housing 
goals is that both Fannie Mae and Freddie Mac surpassed the 
Department's Low- and Moderate-Income Housing Goals for each of the 
seven years during this period. Specifically:
     The goal was set at 40 percent for 1996; 
Fannie Mae's performance was 45.6 percent and Freddie Mac's 
performance was 41.1 percent.
     The goal was set at 42 percent for 1997-2000. 
Fannie Mae's performance was 45.7 percent in 1997, 44.1 percent in 
1998, 45.9 percent in 1999, and 49.5 percent in 2000; and Freddie 
Mac's performance was 42.6 percent in 1997, 42.9 percent in 1998, 
46.1 percent in 1999, and 49.9 percent in 2000.
     In the October 2000 rule, the low- and 
moderate-income goal was set at 50 percent for 2001-03. As of 
January 1, 2001, several changes in counting provisions took effect 
for the low- and moderate-income goal, as follows: ``bonus points'' 
(double credit) for purchases of goal-qualifying mortgages on small 
(5-50 unit) multifamily properties and, above a threshold level, 
mortgages on 2-4 unit owner-occupied properties; a ``temporary 
adjustment factor'' (1.20 units credit, subsequently increased by 
Congress to 1.35 units credit) for Freddie Mac's purchases of goal-
qualifying mortgages on large (more than 50 units) multifamily 
properties; changes in the treatment of missing data; a procedure 
for the use of imputed or proxy rents for determining goal credit 
for multifamily mortgages; and eligibility of purchases of certain 
qualifying government-backed loans to receive goal credit. These 
changes are explained below. Fannie Mae's low-mod goal performance 
was 51.5 percent in 2001 and 51.8 percent in 2002, and Freddie Mac's 
performance was 53.2 percent in 2001 and 51.4 percent in 2002, thus 
both GSEs surpassed this higher goal in both years. This section 
discusses the October 2000 counting rule changes in detail below, 
and provides data on what goal performance would have been in 2001-
02 without these changes.\219\
---------------------------------------------------------------------------

    \219\ To separate out the effects of changes in counting rules 
that took effect in 2001, this section also compares performance in 
2001 to estimated performance in 2000 if the 2001 counting rules had 
been in effect in that year.
---------------------------------------------------------------------------

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

1. Performance on the Low- and Moderate-Income Housing Goal in 
1996-2002

    HUD's December 1995 rule specified that in 1996 at least 40 
percent of the number of units financed by each of the GSEs that 
were eligible to count toward the Low- and Moderate-Income Goal 
should qualify as low-or moderate-income, and at least 42 percent of 
such units should qualify in 1997-2000. HUD's October 2000 rule made 
various

[[Page 24305]]

changes in the goal counting rules, as discussed below, and 
increased the Low- and Moderate-Income Goal to 50 percent for 2001-
03.
    Table A.8 shows low-mod goal performance over the 1996-2002 
period, based on HUD's analysis. The table shows that Fannie Mae 
surpassed the goals by 5.6 percentage points and 3.7 percentage 
points in 1996 and 1997, respectively, while Freddie Mac surpassed 
the goals by narrower margins, 1.1 and 0.6 percentage points. During 
the heavy refinance year of 1998, Fannie Mae's performance fell by 
1.6 percentage points, while Freddie Mac's performance rose 
slightly, by 0.3 percentage point. Freddie Mac showed a gain in 
performance to 46.1 percent in 1999, exceeding its previous high by 
3.2 percentage points. Fannie Mae's performance in 1999 was 45.9 
percent, which, for the first time, slightly lagged Freddie Mac's 
performance in that year.
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    Both GSEs exhibited sharp gains in goal performance in 2000--
Fannie Mae's performance increased by 3.6 percentage points, to a 
record level of 49.5 percent, while Freddie Mac's performance 
increased even more, by 3.8 percentage points, which also led to a 
record level of 49.9 percent. Fannie Mae's performance was 51.5 
percent in 2001 and 51.8 percent in 2002; Freddie Mac's performance 
was 53.2 percent in 2001 and 51.4 percent in 2002. However, as 
discussed below, using consistent accounting rules for 2000-02, each 
GSE's performance in 2001-02 was below its performance in 2000.
    The official figures for low-mod goal performance presented 
above differ from the corresponding figures presented by Fannie Mae 
and Freddie Mac in their Annual Housing Activity Reports to HUD by 
0.2-0.3 percentage point in both 1996 and 1997, reflecting minor 
differences in the application of counting rules. These differences 
also persisted for Freddie Mac for 1998-2000, but the goal 
percentages shown above for Fannie Mae for these three years are the 
same as the results reported by Fannie Mae to the Department. Fannie 
Mae reported its performance in 2001 as 51.6 percent and Freddie Mac 
reported its performance as 53.6 percent--both were slightly above 
the corresponding official figures of 51.5 percent and 53.4 percent, 
respectively. For 2002, Fannie Mae's reported performance was the 
same as reported by HUD (51.8 percent), while Freddie Mac's reported 
performance was 51.3 percent, slightly below HUD's official figure 
of 51.4 percent.
    Fannie Mae's performance on the Low- and Moderate-Income Goal 
was in the range between 44 percent and 46 percent between 1996 and 
1999, but jumped sharply in just one year, from 45.9 percent in 1999 
to 49.5 percent in 2000. Freddie Mac's performance was in the range 
between 41 percent and 43 percent between 1996 and 1998, and then 
rose to 46.1 percent in 1999 and 49.9 percent in 2000. As discussed 
above, official performance rose for both GSEs in 2001-02, but this 
was due to one-time changes in the counting rules--abstracting from 
counting rule changes, performance fell for both GSEs.
    Fannie Mae's performance on the Low- and Moderate-Income Goal 
surpassed Freddie Mac's in every year through 1998. This pattern was 
reversed in 1999, as Freddie Mac surpassed Fannie Mae in goal 
performance for the first time, though by only 0.2 percentage point. 
This improved relative performance of Freddie Mac was due to its 
increased purchases of multifamily loans, as it re-entered that 
market, and to increases in the goal-qualifying shares of its 
single-family mortgage purchases. Freddie Mac's performance also 
slightly exceeded Fannie Mae's performance in 2000, 49.9 percent to 
49.5 percent. Freddie Mac's official performance also exceeded 
Fannie Mae's official performance in 2001, but this reflected a 
difference in the counting rules applicable to the two GSEs that was 
enacted by Congress; if the same counting rules were applied to both 
GSEs (that is, Freddie Mac did not receive the 1.35 Temporary 
Adjustment Factor), Fannie Mae's performance would have exceeded 
Freddie Mac's performance, by 51.5 percent to 50.5 percent.
    In 2002, Freddie Mac's performance on the low mod-goal (51.4 
percent) fell short of Fannie Mae's performance (51.8 percent), even 
though Freddie Mac had the advantage of the Temporary Adjustment 
Factor. The gap would have been wider without this factor, and in 
fact Freddie Mac's performance would have been short of the goal, at 
49.2 percent.

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

    A number of changes in the counting rules underlying the 
calculation of low- and moderate-income goal performance took effect 
beginning in 2001, as follows:
     Bonus points for multifamily and single-
family rental properties. During the 2001-03 period the Department 
awarded ``bonus points'' (double credit in the numerator) for goal-
qualifying units in small (5-50 unit) multifamily properties and, 
above a threshold, 2-4 unit owner-occupied properties whose loans 
were purchased by the GSEs. By letters dated December 24, 2003, the 
Department notified the GSEs that these bonus points would not be in 
effect after December 31, 2003.
     Freddie Mac's Temporary Adjustment Factor. As 
part of the Consolidated Appropriations Act of 2000, Congress 
required the Department to award 1.35 units of credit for each unit 
financed in ``large'' multifamily properties (i.e., those with 51 or 
more units) in the numerator in calculating performance on the 
housing goals for Freddie Mac for 2001-03.\220\ This ``temporary 
adjustment factor'' (TAF) did not apply to goal performance for 
Fannie Mae during this period. By letters dated December 24, 2003, 
the Department notified Freddie Mac that this factor would not be in 
effect after December 31, 2003.
---------------------------------------------------------------------------

    \220\ See Congressional Record, December 15, 2000, pp. H12295-
96.
---------------------------------------------------------------------------

     Missing data for single-family properties. In 
the past, if a GSE lacked data on rent for rental units or on 
borrower income for owner-occupied units in single-family properties 
whose mortgages it purchased, such units were included in the 
denominator, but not in the numerator, in calculating goal 
performance. Since some of these units likely would have qualified 
for one or more of the housing goals, this rule lowered goal 
performance. Under the new counting rules for the low- and moderate-
income goal and the special affordable goal that took effect in 
2001, the GSEs are allowed to exclude loans with missing borrower 
income from the denominator if the property is located in a below-
median income census tract. This exclusion is subject to a ceiling 
of 1 percent of total owner-occupied units financed. The enterprises 
are also allowed to exclude single-family rental units with missing 
rental information from the denominator in calculating performance 
for these two goals; there is no ceiling or restriction to 
properties located in below-median income census tracts for this 
exclusion of single-family rental units. No single-family loans can 
be excluded from the denominator in calculating performance on the 
underserved areas goal--that is, if a GSE does not have sufficient 
information to determine whether or not a property is located in an 
underserved area, all units in such a property are included in the 
denominator, but not in the numerator, in calculating performance on 
this goal.
     Missing data and proxy rents for multifamily 
properties. In the past, if a GSE lacked data on rent for rental 
units in multifamily properties whose mortgages it purchased, such 
units were included in the denominator, but not in the numerator, in 
calculating goal performance. Since some of these units likely would 
have qualified for one or more of the housing goals, this rule 
lowered goal performance. Under the new counting rules that took 
effect in 2001, if rent is missing for multifamily units, a GSE may 
estimate ``proxy rents,'' and, up to a ceiling of 5 percent of total 
multifamily units financed, may apply these proxy rents in 
determining whether such units qualify for the low- and moderate 
income goal and special affordable goal. If such proxy rents cannot 
be estimated, these multifamily units are excluded from the 
denominator in calculating performance under these goals. No 
multifamily loans can be excluded from the denominator in 
calculating performance on the underserved areas goal--that is, if a 
GSE does not have sufficient information to determine whether or not 
a property is located in an underserved area, all units in such a 
property are included in the denominator, but not in the numerator, 
in calculating performance on this goal.
     Purchases of certain government-backed loans. 
Prior to 2001, purchases of government-backed loans were not taken 
into account in determining performance on the GSEs' low- and 
moderate-income and underserved area housing goals. That is, all 
such loans were excluded from both the numerator and the denominator 
in calculating goal performance on these two goals, and in 
accordance with Section 1333(b)(1)(A) of the Federal Housing 
Enterprises Financial Safety and Soundness Act of 1992, purchases of 
only certain government-backed loans were included in determining 
performance on the GSEs' special affordable goals. In October 2000 
the Department took steps to encourage the enterprises to play more 
of a role in the secondary market for several types of government-
backed loans where it appeared that greater GSE involvement could 
increase the liquidity of such mortgages. Home equity conversion 
mortgages (HECMs) were developed in the late-1980s by the Federal 
Housing Administration (FHA); these mortgages allow senior citizens 
to draw on the equity in their homes to obtain monthly payments to 
supplement their incomes. Thus purchases of FHA-insured HECMs now 
count toward the low- and moderate-income housing goals if the 
mortgagor's income is less than median income for the area. 
Similarly, purchases of mortgages on properties on tribal lands 
insured under FHA's Section 248 program or HUD's Section 184 program 
may qualify for the GSEs' housing goals. And purchases of mortgages 
under the Rural Housing Service's Single Family Housing Guaranteed 
Loan Program

[[Page 24308]]

may also count toward all of the housing goals.\221\
---------------------------------------------------------------------------

    \221\ Prior to the October 2000 rule, purchases of these 
government-backed mortgages were only eligible for credit under the 
special affordable goal.
---------------------------------------------------------------------------

3. Effects of Changes in the Counting Rules on Goal Performance in 
2001-02

    Because of the changes in the low- and moderate-income goal 
counting rules that took effect in 2001, direct comparisons between 
official goal performance in 2000 and 2001-02 are somewhat of an 
``apples-to-oranges comparison.'' For this reason, the Department 
has calculated what performance would have been in 2000 under the 
2001-03 rules; this may be compared with official performance in 
2001-02--an ``apples-to-apples comparison.'' HUD has also calculated 
what performance would have been in 2001-02 under the 1996-2000 
rules; this may be compared with official performance in 2000--an 
``oranges-to-oranges comparison.'' These comparisons are presented 
in Table A.9.
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    Specifically, Table A.9 shows performance under the low- and 
moderate-income goal in three ways. Baseline A represents 
performance under the counting rules in effect in 1996-2000. 
Baseline B incorporates the technical changes in counting rules--
changes in the treatment of missing data (including use of proxy 
rents), and eligibility for the goals of certain government-backed 
loans. Baseline C incorporates in addition to the technical changes 
the bonus points and, for Freddie Mac, the temporary adjustment 
factor. Baseline B corresponds to the counting approach proposed in 
this rule to take effect in 2005. Boldface figures under Baseline A 
for 1999-2000 and under Baseline C for 2001-02 indicate official 
goal performance, based on the counting rules in effect in those 
years--e.g., for Fannie Mae, 45.9 percent in 1999, 49.5 percent in 
2000, 51.5 percent in 2001, and 51.8 percent in 2002.
     Performance on the Low- and Moderate-Income 
Goal under 1996-2000 Counting Rules Plus Technical Changes. If the 
``Baseline B'' counting approach had been in effect in 2000-02 and 
the GSEs had purchased the same mortgages that they actually did 
purchase in those years, both Fannie Mae and Freddie Mac would have 
surpassed the low- and moderate-income goal in 2000 and fallen short 
in 2001 and 2002. Specifically, Fannie Mae's performance would have 
been 51.3 percent in 2000, 49.2 percent in 2001, and 49.0 percent in 
2002. Freddie Mac's performance would have been 50.6 percent in 
2000, 47.7 percent in 2001, and 46.5 percent in 2002.
     Performance on the Low- and Moderate-Income 
Goal under 2001-2003 Counting Rules. If the 2001-03 counting rules 
had been in effect in 2000-02 and the GSEs had purchased the same 
mortgages that they actually did purchase in those years (i.e., 
abstracting from any behavioral effects of ``bonus points,'' for 
example), both GSEs would have substantially surpassed the low- and 
moderate-income goal in all three years, but both GSEs' performance 
figures would have deteriorated somewhat from 2000 to 2001, and, for 
Freddie Mac, from 2001 to 2002. Specifically, Fannie Mae's 
``Baseline C'' performance would have been 52.5 percent in 2000, 
51.5 percent in 2001, and 51.8 percent in 2002. Freddie Mac's 
performance would have been 55.1 percent in 2000, surpassing its 
official performance level of 53.2 percent in 2001 and 51.4 percent 
in 2002. Measured on this consistent basis, then, Fannie Mae's 
performance fell by 1.0 percentage point in 2001, and Freddie Mac's 
by 1.9 percentage points in 2001 and an additional 1.8 percentage 
points in 2002. These reductions were primarily due to 2001-02 being 
years of heavy refinance activity.
    Details of Effects of Changes in Counting Rules on Goal 
Performance in 2001-02. As discussed above, counting rule changes 
that took effect in 2001 had significant positive impacts on the 
performance of both GSEs on the low- and moderate-income goal in 
that year--3.8 percentage points for Fannie Mae, and 6.0 percentage 
points for Freddie Mac. This section breaks down the effects of 
these changes on goal performance for both GSEs; results are shown 
in Table A.9.
     Freddie Mac. The largest impact of the 
counting rule changes on Freddie Mac's goal performance was due to 
the application of the temporary adjustment factor for purchases of 
mortgages on large multifamily properties, as enacted by Congress; 
this added 2.7 percentage points to goal performance in 2001, as 
shown in Table A.9. Bonus points for purchases of mortgages on small 
multifamily properties added 1.5 percentage points to performance, 
and bonus points for purchase of mortgages on owner-occupied 2-4 
unit rental properties added 1.4 percentage points to performance. 
The remaining impact (0.5 percentage point) was due to technical 
changes in counting rules--primarily, the exclusion of single-family 
units with missing information from the denominator in calculating 
goal performance. Credit for purchases of qualifying government-
backed loans played a minor role in determining Freddie Mac's goal 
performance. These same patterns also appeared in 2002.
     Fannie Mae. The temporary adjustment factor 
applies to Freddie Mac's goal performance, but not to Fannie Mae's 
performance, thus counting rule changes had less impact on its 
performance than on Freddie Mac's performance in 2001. The largest 
impact of the counting rule changes on Fannie Mae's goal performance 
was due to the application of bonus points for purchases of 
mortgages on owner-occupied 2-4 unit rental properties, which added 
1.6 percentage points to performance, and for purchases of mortgages 
on small multifamily properties, which added 0.7 percentage point to 
performance. The remaining impact (1.3 percentage points) was due to 
technical changes--primarily, the exclusion of single-family units 
with missing information from the denominator in calculating goal 
performance.\222\ Credit for purchases of qualifying government-
backed loans and the use of proxy rent for multifamily properties 
played a minor role in determining Fannie Mae's goal performance. 
These same patterns also appeared in 2002 for Fannie Mae.
---------------------------------------------------------------------------

    \222\ Exclusion of loans with missing information had a greater 
impact on Fannie Mae's goal performance than on Freddie Mac's goal 
performance.
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4. Bonus Points for the Low- and Moderate-Income Goal

    As discussed above, the Department established ``bonus points'' 
to encourage the GSEs to step up their activity in 2001-03 in two 
segments of the mortgage market--the small (5-50 unit) multifamily 
mortgage market, and the market for mortgages on 2-4 unit properties 
where 1 unit is owner-occupied and 1-3 units are occupied by 
renters. Bonus points did not apply to purchases of mortgages for 
owner-occupied 1-unit properties, for investor-owned 1-4 unit 
properties, and for large (more than 50 units) multifamily 
properties, although as also discussed above, a ``temporary 
adjustment factor'' applied to Freddie Mac's purchases of qualifying 
mortgages on large multifamily properties.
    Bonus points for small multifamily properties. Each unit 
financed in a small multifamily property that qualified for any of 
the housing goals was counted as two units in the numerator (and one 
unit in the denominator) in calculating goal performance for that 
goal. For example, if a GSE financed a mortgage on a 40-unit 
property in which 10 of the units qualified for the low- and 
moderate-income goal, 20 units would be entered in the numerator and 
40 units in the denominator for this property in calculating goal 
performance.
    Small multifamily bonus points thus encouraged the GSEs to play 
a larger role in this market, and also to purchase mortgages on such 
properties in which large shares of the units qualified for the 
housing goals. Some evidence may be gleaned from the data provided 
to HUD by the GSEs for 2001-02.
    Fannie Mae financed 37,403 units in small multifamily properties 
in 2001 that were eligible for the low- and moderate-income goal, 
and 58,277 such units in 2002, a two-year increase of more than 700 
percent from the 7,196 such units financed in 2000. Small 
multifamily properties also accounted for a greater share of Fannie 
Mae's multifamily business in 2001-02--7.4 percent of total 
multifamily units financed in 2001 and 13.2 percent in 2002, up from 
2.5 percent in 2000. However, HUD's 2000 rule reported information 
from the 1991 Residential Finance Survey that small multifamily 
properties accounted for 37 percent of all multifamily units, thus 
Fannie Mae was still less active in this market than in the market 
for large multifamily properties.\223\
---------------------------------------------------------------------------

    \223\ Federal Register, October 31, 2000, Footnote 145, p. 
65141.
---------------------------------------------------------------------------

    Within the small multifamily market, there was no evidence that 
Fannie Mae targeted affordable properties to a greater extent in 
2001-02 than in 2000. That is, 87 percent of Fannie Mae's small 
multifamily units qualified for the low- and moderate-income goal in 
2000; this fell to 75 percent in 2001, but rose to 89 percent in 
2002.
    Freddie Mac financed 50,299 units in small multifamily 
properties in 2001 that were eligible for the low- and moderate-
income goal and 42,772 such units in 2002, a two-year increase of 
more than 1300 percent from the 2,996 units financed in 2000. Small 
multifamily properties also accounted for a significantly greater 
share of Freddie Mac's multifamily business in 2001--16.1 percent of 
total multifamily units financed in 2001 and 13.4 percent in 2002, 
up from 1.8 percent in 2000.
    Within the small multifamily market, there was some evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001-02 than in 2000. That is, 87 percent of Freddie Mac's small 
multifamily units qualified for the low- and moderate-income goal in 
2000; this rose to 96 percent in 2001 and 94 percent in 2002.
    In summary, then, there is evidence that bonus points for small 
multifamily properties had an impact on Fannie Mae's role in this 
market in 2001-02 and an even larger impact on Freddie Mac's role in 
this market. In addition, Fannie Mae has announced a program to 
increase its role in this market further in future years.\224\
---------------------------------------------------------------------------

    \224\ ``Fannie Courting Multifamily Sellers; Small Banks 
Balking,'' American Banker, January 13, 2003, p. 1.

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[[Page 24311]]

    Bonus points for single-family rental properties. Above a 
threshold, each unit financed in a 2-4 unit property with at least 
one owner-occupied unit (referred to as ``OO24s'' below) that 
qualified for any of the housing goals was counted as two units in 
the numerator (and one unit in the denominator) in calculating goal 
performance for that goal in 2001-03. The threshold was equal to 60 
percent of the average number of such qualifying units over the 
previous five years. For example, Fannie Mae financed an average of 
50,030 low- and moderate-income units in these types of properties 
between 1996 and 2000, and 101,423 such units in 2001. Thus Fannie 
Mae received 71,405 bonus points in this area in 2001--that is, 
101,423 minus 60 percent of 50,030. So 172,828 units were entered in 
the numerator for these properties in calculating low- and moderate-
income goal performance.
    Single-family rental bonus points thus encouraged the GSEs to 
play a larger role in this market, and also to purchase mortgages on 
such properties in which large shares of the units qualified for the 
housing goals. As for small multifamily bonus points, again some 
evidence may be gleaned from the data provided to HUD by the GSEs 
for 2001-02.
    Fannie Mae financed 175,103 units in OO24s in 2001 that were 
eligible for the low- and moderate-income goal and 229,632 such 
units in 2002, a two-year increase of nearly 200 percent from the 
77,930 units financed in 2000. However, Fannie Mae's total single-
family business increased at approximately the same rate as its OO24 
business in 2001 and 2002, thus the share of its business accounted 
for by OO24s was the same in 2001-02 as in 2000--4 percent.
    Within the OO24 market, there was no evidence that Fannie Mae 
targeted affordable properties to a greater extent in 2001-02 than 
in 2000. That is, approximately 55-60 percent of Fannie Mae's OO24 
units qualified for the low- and moderate-income goal in each of 
these three years.
    Freddie Mac financed 96,050 units in OO24s in 2001 that were 
eligible for the low- and moderate-income goal and 146,222 such 
units in 2002, also a two-year increase of nearly 200 percent from 
the 49,993 units financed in 2000. However, Freddie Mac's total 
single-family business increased at approximately the same rate as 
its OO24 business in 2001-02, thus the share of its business 
accounted for by OO24s was the same in 2002 as in 2000--4 percent.
    As for Fannie Mae, within the OO24 market there was no evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001-02 than in 2000. That is, 68-69 percent of Fannie Mae's OO24 
units qualified for the low- and moderate-income goal in each year 
from 2000 through 2002.

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

    Background. Scoring of housing units under the Low- and 
Moderate-Income Housing Goal is based on data for mortgagors' 
incomes for owner-occupied units, rents for rental units, and area 
median incomes, as follows:
    For single-family owner-occupied units:
     The mortgagors' income at the time of 
mortgage origination.
     The median income of an area specified as 
follows: (i) For properties located in Metropolitan Statistical 
Areas (MSAs), the area is the MSA; and (ii) for properties located 
outside of MSAs, the area is the county or the non-metropolitan 
portion of the State in which the property is located, whichever has 
the larger median income, as of the year of mortgage origination 
(which may be for the current year or a prior year).
    For rental units in single-family properties with rent data are 
available (assuming no income data available for actual or 
prospective tenants):
     The unit rent (or average rent for units of 
the same type) at the time of mortgage origination.
     The area median income as specified for 
single-family owner-occupied units.
    For rental units in multifamily properties where rent data are 
available.
     The unit rent (or the average rent for units 
of the same type) at the time of mortgage acquisition by the GSE.
     The area median income as specified for 
single-family owner-occupied units, but as of the year the GSE 
acquired the mortgage.
    For rental units in multifamily properties where rent data are 
not available, the GSE may apply HUD-estimated rents which are based 
on the following area data;
     The median rent in the census tract where the 
property is located, as of the most recent decennial census.
     The area median income as specified for 
single-family owner-occupied units, but as of the most recent 
decennial census.
    Thus, scoring loans under the Low- and Moderate-Income Goal 
requires a data series showing annual median incomes for MSAs, non-
metropolitan counties, and the non-metropolitan portions of states; 
and decennial census data on median incomes for census tracts.\225\
---------------------------------------------------------------------------

    \225\ In New England, MSAs were defined through mid-2003 in 
terms of Towns rather than Counties, and the portion of a New 
England county outside of any MSA was regarded as equivalent to a 
county in establishing the metropolitan or non-metropolitan location 
of a property. The MSA definitions established by the Office of 
Management and Budget (OMB) in June, 2003 defined MSAs in New 
England in terms of counties.
---------------------------------------------------------------------------

    For scoring loans purchased by the GSEs year-by-year from 1993 
through 2002, area median income estimates produced by HUD's 
Economic and Market Analysis Division were used. An example will 
illustrate the estimation procedure. To generate the area median 
income estimates that were used to score GSE loans in 2002, data 
from the 1990 census on 1989 area median incomes were adjusted to 
2002 using Bureau of Labor Statistics survey data on rates of change 
in average incomes for MSAs and counties between 1989 and 1999, data 
from the Census Bureau's Current Population Survey on rates of 
change in median family incomes for the nine Census Divisions 
between 1989 and 2000, and an assumed 4.0 percent per year inflation 
factor between 2000 and 2002.226, 227
---------------------------------------------------------------------------

    \226\ The procedure is explained in detail in annual releases 
entitled ``HUD Methodology for Estimating FY [year] Median Family 
Incomes'' for years 1993 through 2002, issued by the Economic and 
Market Analysis Division, Office of Economic Affairs, PD&R, U.S. 
Department of Housing and Urban Development.
    \227\ The procedure applicable to the decennial census data used 
to generate estimated rents is explained in connection with data 
used to define Underserved Areas in Appendix B.
---------------------------------------------------------------------------

    2005 Procedure. Relative to the above procedure, scoring of 
loans purchased by the GSEs in and after 2005 will be affected by 
two factors. First, the Economic and Market Analysis Division has 
begun to incorporate data from the 2000 census into its procedure 
for estimating annual area median incomes and American Community 
Survey data are becoming available at increasingly finer levels of 
geographical detail for use in annual updating. Beginning in 2005 
Bureau of Labor Statistics data on rates of inflation in average 
wages will not be used. For 2005, the procedure for estimating area 
median incomes will be to adjust 2000 census data on 1999 area 
median incomes to 2003 using data from the Census Bureau's American 
Community Survey (ACS) on rates of change in average incomes for 
States between 1999 and 2003, with a further adjustment to 2005 
based on an appropriate annual inflation factor.\228\ Increasingly 
more detailed ACS data will be available and will be used in 
subsequent years, as ACS estimates for metropolitan and micropolitan 
areas and counties become available.
---------------------------------------------------------------------------

    \228\ Transition from the 2002 methodology to the 2005 
methodology is occurring in stages in 2003 and 2004. To generate the 
area median income estimates used to score GSE loans in 2003, data 
from the 2000 census on 1999 area median incomes were adjusted to 
2001 using Bureau of Labor Statistics survey data on rates of change 
in average incomes for MSAs and counties between 1999 and 2000, data 
on rates of change in median incomes for the United States and 
individual States between 1999 and 2001 from Census Bureau's Current 
Population Survey and American Communities Survey, and an assumed 
3.5 percent per year inflation factor between 2001 and 2003. (See 
``HUD Methodology for Estimating FY 2003 Median Family Incomes,'' 
issued by the Economic and Market Analysis Division, op cit.) A 
similar procedure has been used to generate area median income 
estimates for scoring GSE loans in 2004.
---------------------------------------------------------------------------

    The second factor is the Office of Management and Budget's June, 
2003, re-specification of MSA boundaries based on analysis of 2000 
census data.\229\
---------------------------------------------------------------------------

    \229\ HUD has deferred application of the 2003 MSA specification 
to 2005, pending completion of the present rulemaking process.
---------------------------------------------------------------------------

    Analysis. For purposes of specifying the level of the Low- and 
Moderate-Income Housing Goal, HUD developed a methodology for 
scoring loans purchased by the GSEs in past years through 2002 as 
though the re-benchmarking of area median income estimates to the 
2000 census and the 2003 re-designation of MSAs had been in effect 
and HUD had been using an ACS-based estimation procedure at the time 
the estimates for these years were prepared. For this purpose, HUD 
created a series of annual estimates of median incomes for MSAs, 
non-metropolitan counties, and the non-metropolitan portions of 
states. For 2000, the estimates were 1999 census medians trended by 
three-fourths of the 4.0 percent annual

[[Page 24312]]

trending factor (to adjust the figures from mid-1999 to April 1, 
2000). For 2001, the estimates were based on one-and-three-fourths 
years of trending, since no data would have been available to use 
for updating. The 2002 estimates would have used one year of data 
and 1.75 years of trending. The 2003 estimates would have used two 
years of data plus 1.75 years of trending. Area median incomes from 
1989 to 1999 were estimated based on trend-lines between 1989 and 
1999 census data. The 2003 OMB MSA designations were applied.
    The resulting estimates of area median incomes for MSAs, non-
metropolitan counties, and the non-metropolitan parts of States, 
were used to re-score loans purchased by the GSEs between 1999 and 
2002, and were used further in estimating the share of loans 
originated in metropolitan areas that would be eligible to score 
toward the Low- and Moderate-Income Housing Goal, from HMDA data. 
The results of the retrospective GSE analysis are provided in Table 
A.10. The results of the GSE-HMDA comparative analysis are presented 
in the next section.
    Table A.10 shows three sets of estimates for each GSE, based 
respectively on the counting rules in place in 2001-2002 (but 
disregarding the bonus points and Temporary Adjustment Factor), on 
the addition of 2000 census re-benchmarking, and finally on the 
addition of both 2000 census re-benchmarking and 2003 MSA 
specification.
BILLING CODE 4210-27-C

[[Page 24313]]

[GRAPHIC] [TIFF OMITTED] TP03MY04.015

BILLING CODE 4210-27-C

[[Page 24314]]

6. GSEs Compared With the Primary Conventional Conforming Mortgage 
Market

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

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

    There are six main findings from this analysis concerning the 
GSEs' purchases of single-family-owner mortgages:
    1. While Freddie Mac has improved its affordable lending 
performance in recent years, it has consistently lagged the 
conventional conforming market in funding affordable home purchase 
loans for special affordable and low-moderate-income borrowers and 
underserved neighborhoods targeted by the housing goals.\230\ 
However, Freddie Mac's recent performance (2001 and 2002) has been 
much closer to the market than its earlier performance.
---------------------------------------------------------------------------

    \230\ The ``affordable lending performance'' of Fannie Mae and 
Freddie Mac refers to the performance of the GSEs in funding loans 
for low-income and underserved borrowers through their purchase (or 
guarantee) of loans originated by primary lenders. It does not, of 
course, imply that the GSEs themselves are lenders originating loans 
in the primary market.
---------------------------------------------------------------------------

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

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

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

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

    The longer-run performance of the GSEs is examined between 1993 
and 2002 (which covers the period since the housing goals were put 
into effect) and between 1996 and 2002 (which covers the period 
under the current definitions of the housing goals). Of the two 
borrower-income goals, the analysis below will typically focus on 
the special affordable category, which is a more targeted category 
than the rather broadly defined low- and moderate-income category.
    (1) Since the early nineties, the mortgage industry has 
introduced new affordable lending programs and has allowed greater 
flexibility in underwriting lower-income loans. There is evidence 
that these programs are paying off in terms of more mortgages for 
low-income and minority borrowers. As noted earlier, Fannie Mae and 
Freddie Mac have played an active role in this upsurge of affordable 
lending, as indicated by the high growth rates of their goals-
qualifying business.
     Between 1993 and 2002, the GSEs' purchases of 
home loans in metropolitan areas increased by 57 percent.\231\ Their 
purchases of home loans for the three housing goals increased at 
much higher rates--264 percent for special affordable loans, 142 
percent for low- and moderate-income loans, and 112 percent for 
loans in underserved census tracts.
---------------------------------------------------------------------------

    \231\ Throughout this analysis, the terms ``home loan'' and 
``home mortgage'' will refer to a ``home purchase loan,'' as opposed 
to a ``refinance loan.'' As noted earlier, the mortgage data 
reported in this paper are for metropolitan areas, unless stated 
otherwise. Restricting the GSE data to metropolitan areas is 
necessary to make it comparable with the HMDA-reported conventional 
primary market data, which is more reliable for metropolitan areas. 
The analysis of first-time homebuyers in Sections E.9 and E.12 cover 
both metropolitan and non-metropolitan areas.
---------------------------------------------------------------------------

    (2) Both Fannie Mae and Freddie Mac have improved their 
purchases of affordable loans since the housing goals were put in 
place, as indicated by the increasing share of their business going 
to the three goals-qualifying categories. (See Table A.15 in Section 
E.9.)
     Between 1992 and 2002, the special affordable 
share of Fannie Mae's business more than doubled, rising from 6.3 
percent to 16.3 percent, while the underserved areas share increased 
more modestly, from 18.3 percent to 26.7 percent. The figures for 
Freddie Mac are similar. The special affordable share of Freddie 
Mac's business rose from 6.5 percent to 15.8 percent, while the 
underserved areas share also increased but more modestly, from 18.6 
percent to 25.8 percent.
    (3) While both GSEs improved their performance, they have lagged 
the primary

[[Page 24315]]

market in providing affordable loans to low-income borrowers and 
underserved neighborhoods. Freddie Mac's average performance, in 
particular, fell far short of market performance during the 1990s. 
Fannie Mae's average performance was better than Freddie Mac's 
during the 1993-2002 period as well as during the 1996-2002 period, 
which covers the period under HUD's currently-defined housing goals.
     Between 1993 and 2002, 11.8 percent of 
Freddie Mac's mortgage purchases were for special affordable 
borrowers, compared with 12.7 percent of Fannie Mae's purchases, 
15.4 percent of loans originated by depositories, and 15.4 percent 
of loans originated in the conventional conforming market (without 
estimated B&C loans).\232\
---------------------------------------------------------------------------

    \232\ Unless otherwise noted, the conventional conforming market 
data reported in this section exclude an estimate of B&C loans; the 
less-risky A-minus portion of the subprime market is included in the 
market definition. See Section E.7 and Appendix D for a discussion 
of primary market definitions and the uncertainty surrounding 
estimates of the number of B&C loans in HMDA data. As noted there, 
B&C loans are much more likely to be refinance loans rather than 
home purchase loans.
---------------------------------------------------------------------------

     Considering the underserved areas category 
for the 1996-2002 period, 21.7 percent of Freddie Mac's purchases 
financed properties in underserved neighborhoods, compared with 23.5 
percent of Fannie Mae's purchases, 24.9 percent of loans originated 
by depositories, and 25.4 percent of loans originated in the 
conventional conforming market.

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

    The recent performance of the GSEs is examined for the four-year 
period between 1999 and 2002 and then for 2001 and 2002, which were 
the first two years that the GSEs operated under the higher goal 
targets established by HUD in the 2000 Rule. As explained below, the 
most interesting recent trend concerned Fannie Mae, which improved 
its performance during 2001 and 2002, at a time when the 
conventional conforming market was showing little change in 
affordable lending.
    (4) During the recent 1999-to-2002 period, both Fannie Mae and 
Freddie Mac fell significantly below the market in funding 
affordable loans.
     Between 1999 and 2002, special affordable 
loans accounted for 14.4 percent of Fannie Mae's purchases, 14.5 
percent of Freddie Mac's purchases, and 16.4 percent of loans 
originated in the market; thus, the ``Fannie-Mae-to-market'' ratio 
was 0.88 and the ``Freddie-Mac-to-market'' ratio was also 0.88.
     During the same period, underserved area 
loans accounted for 24.0 percent of Fannie Mae's purchases, 22.9 
percent of Freddie Mac's purchases, and 25.8 percent of loans 
originated in the market; the ``Fannie-Mae-to-market'' ratio was 
0.93 and the ``Freddie-Mac-to-market'' ratio was only 0.89.\233\
---------------------------------------------------------------------------

    \233\ Fannie Mae had a particularly poor year during 1999. 
Therefore, the text also reports averages for 2000-2002, dropping 
the year 1999 (see Table A.13 in Section E.9). While Fannie Mae's 
performance is closer to the market, it continues to fall below 
market levels during the 2000-2002 period.
---------------------------------------------------------------------------

    (5) After experiencing declines from 1997 to 1999, Fannie Mae's 
affordable lending performance improved between 2000 and 2002.
     After declining from 23.0 percent in 1997 to 
20.4 percent in 1999, the share of Fannie Mae's purchases financing 
properties in underserved areas jumped by three percentage points to 
23.4 percent in 2000, and then increased further to 26.7 percent by 
2002.
     After declining from 13.2 percent in 1998 to 
12.5 percent in 1999, the share of Fannie Mae's purchases going to 
special affordable loans rebounded to 13.3 percent in 2000, 14.9 
percent in 2001, and 16.3 percent in 2002.
    (6) Freddie Mac's performance on the two borrower-income 
categories improved between 2000 and 2002, but not as much as Fannie 
Mae's performance. Freddie Mac's performance on the underserved 
areas category increased substantially between 2001 and 2002.
     The share of Freddie Mac's single-family-
owner business going to special affordable home loans increased from 
9.2 in 1997 to 14.7 percent in 2000 before falling to 14.4 percent 
in 2001 and rising to 15.8 percent in 2001.
     Freddie Mac's purchases of underserved area 
loans increased at a modest rate from 19.8 percent in 1997 to 22.3 
percent in 2001, before sharply jumping to 25.8 percent in 2002.
    (7) The long-standing pattern of Fannie Mae outperforming 
Freddie Mac was reversed during 1999 and 2000. But that pattern 
returned in 2001 and 2002 when Fannie Mae outperformed Freddie Mac 
on all three goals-qualifying categories.
     Fannie Mae and Freddie Mac had practically 
the same performance in 1992 on the three housing goal categories--
special affordable loans accounted for 6.3 percent of Fannie Mae's 
purchases and 6.5 percent of Freddie Mac's purchases, for a 
``Fannie-Mae-to-Freddie-Mac'' ratio of 0.97. The 1992 ratio for 
underserved areas was also 0.98 and that for low-mod, 1.02. 
Reflecting Fannie Mae's much better performance, the special 
affordable ``Fannie-Mae-to-Freddie-Mac'' ratio had risen to 1.27 by 
1997, the underserved area ratio to 1.17, and the low-mod ratio to 
1.10.
     However, in 1999, the ``Fannie-Mae-to-
Freddie-Mac'' ratio for each of the three goals-qualifying 
categories fell to slightly below one. 1999 was the first year since 
1992 that Freddie Mac had outperformed Fannie Mae in purchasing 
affordable home loans (although only by a very slight margin).
     In 2000, Freddie Mac's sharper increases in 
special affordable and low-mod purchases further reduced the 
``Fannie-Mae-to-Freddie-Mac'' ratios for these two categories to 
0.90 and 0.96, respectively. Fannie Mae's sharper increase in 
underserved areas funding resulted in the ``Fannie-Mae-to-Freddie-
Mac'' ratio rising from slightly below one (0.98) in 1999 to 1.06 in 
2000.
     Fannie Mae's stronger performance during 2001 
and 2002 returned the ``Fannie-Mae-to-Freddie-Mac'' ratios for 
special affordable and low-mod loans to above one (1.03 for both), 
indicating better performance for Fannie Mae. The ``Fannie-Mae-to-
Freddie-Mac'' ratio (1.03) for the underserved area category 
remained above one in 2002.
    (8) While Freddie Mac has consistently improved its performance 
relative to the market, it continued to lag the market in funding 
affordable home loans in 2001 and 2002.
     Unlike Fannie Mae, Freddie Mac had not made 
any progress through 1997 in closing its gap with the market. The 
``Freddie Mac-to-market'' ratio for the special affordable category 
actually declined from 0.63 in 1992 to 0.59 in 1997. But Freddie 
Mac's sharp improvement in special affordable purchases resulted in 
the ``Freddie-Mac-to-market'' ratio rising to 0.88 by 2000. After 
declining from 0.84 in 1992 to 0.80 in 1997, the ``Freddie-Mac-to-
market'' ratio for underserved areas had risen only modestly to 0.84 
by the year 2000. Thus, Freddie Mac's improvements prior to 2001 
allowed it to close its gap with the market, mainly for the special 
affordable category where its gap had been the widest.
     During 2001 and 2002, Freddie Mac continued 
to close its gap with the market. By 2002, all three ``Freddie-Mac-
to-market'' ratios were higher than in 2000, although they continued 
to fall below one: special affordable (0.97), low-mod (0.97), and 
underserved areas (0.98). Thus, during 2002, Freddie Mac lagged the 
market on all three goals-qualifying categories.
    (9) Through 1998, Fannie Mae had significantly improved its 
performance relative to the market. But as a result of shifts in its 
purchases of affordable loans, Fannie Mae lagged the market even 
further in 2000 than it had in some earlier years. During 2001 and 
2002, Fannie Mae again improved its performance relative to the 
market.
     The above analysis and the data reported 
under this specific finding (9) are based on the ``purchase year'' 
approach for measuring GSE activity. The purchase year approach 
assigns GSE purchases of both prior-year (seasoned) and newly-
originated mortgages to the calendar year in which they were 
purchased by the GSE; this results in an inconsistency with the 
HMDA-reported market data, which covers only newly-originated 
mortgages. Sections E.9 and E.10 also report the results of an 
alternative ``origination year'' approach that assigns GSE purchases 
to their year of origination, placing them on a more consistent 
basis with the HMDA-reported market data. The findings from the 
origination-year approach are discussed under specific finding (10).
     Fannie Mae's decline in performance during 
1999 resulted in the ``Fannie-Mae-to-market'' ratio falling sharply 
to 0.74 for special affordable and to 0.81 for underserved areas. In 
2000, Fannie Mae improved and reversed its declining trend, as the 
``Fannie-Mae-to-market'' ratios increased to 0.79 for special 
affordable purchases and to 0.89 for underserved area purchases.
     During 2001, Fannie Mae increased its special 
affordable percentage by 1.6 percentage points to 14.9 percent, 
which was only 0.7 percentage point below the market's performance 
of 15.6 percent. Fannie Mae

[[Page 24316]]

increased its low-mod percentage from 40.8 percent to 42.9 percent 
at the same time that the low-mod share of the primary market was 
falling from 44.4 percent to 42.9 percent, placing Fannie Mae at the 
market's performance. Similarly, Fannie Mae increased its 
underserved area percentage from 23.4 percent in 2000 to 24.4 
percent in 2001 while the underserved area share of the primary 
market was falling from 26.4 percent to 25.2 percent, placing Fannie 
Mae at 0.8 percentage point from the market's performance.
     During 2002, Fannie Mae continued to improve 
its performance on all three goals categories. Using the purchase-
year approach to measure GSE performance, Fannie Mae matched the 
market on the special affordable category (16.3 percent for both), 
led the market on the low-mod category (45.3 percent for Fannie Mae 
compared with 45.2 percent for the market), and led the market on 
the underserved area category (26.7 percent for Fannie Mae versus 
26.4 percent for the market). As explained in the next specific 
finding, measuring Fannie Mae's performance on the more consistent 
origination-year basis gives somewhat different results.
    (10) This analysis addresses several technical issues involved 
in measuring GSE performance. The above analysis was based on the 
``purchase year'' approach, as defined in (9) above. An alternative 
``origination year'' approach has also been utilized, which assigns 
GSE purchases to their year of origination, placing them on a more 
consistent basis with the HMDA-reported market data. While the 
average results (e.g., 1999-2002 GSE performance) are similar under 
the two reporting approaches, GSE performance in any particular year 
can be affected, depending on the extent to which the GSE has 
purchased goals-qualifying seasoned loans in that particular year.
     The choice of which approach to follow 
particularly affected conclusions about Fannie Mae's performance 
relative to the market. Under the origination-year approach, Fannie 
Mae lagged the market on all three housing goal categories during 
2001 and on the special affordable and underserved area categories 
during 2002. In 2002, Fannie Mae essentially matched the market on 
the low-mod category (45.4 percent for Fannie Mae compared with 45.2 
percent of the market).

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

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

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

    (12) The GSEs' acquisitions of total loans (including refinance 
loans as well as home purchase loans) were also examined. The main 
results indicate that while the GSEs have improved their performance 
they have consistently lagged the market in funding loans (home 
purchase and refinance) that qualify for the housing goals. (See 
Table A.20 of Section E.10, which is based on the purchase-year 
approach for measuring GSE activity.)
     1999-2002. During the recent 1999-to-2002 
period, both Fannie Mae and Freddie Mac fell significantly below the 
market in funding affordable loans. Between 1999 and 2002, special 
affordable loans accounted for 13.8 percent of Fannie Mae's 
purchases, 13.8 percent of Freddie Mac's purchases, and 15.7 percent 
of loans originated in the market; thus, the ``Fannie-Mae-to-
market'' ratio and the ``Freddie-Mac-to-market'' ratio were each 
0.88 during this period.
     During the same period, underserved area 
loans accounted for 23.8 percent of Fannie Mae's purchases, 23.1 
percent of Freddie Mac's purchases, and 25.7 percent of loans 
originated in the market; thus, the ``Fannie-Mae-to-market'' ratio 
was 0.93 and the ``Freddie-Mac-to-market'' ratio was 0.90.\234\
---------------------------------------------------------------------------

    \234\ As explained in Section E.9, deducting B&C loans from the 
market totals has more impact on the market percentages for total 
(both home purchase and refinance) loans than for only home purchase 
loans. The effects of excluding B&C loans from the total market can 
be seen by comparing the third and sixth columns of data in Table 
A.19 in Section E.10.
---------------------------------------------------------------------------

     2002. During this year of heavy refinancing, 
Fannie Mae's performance approached but fell below market 
performance. The ``Fannie-Mae-to-market'' ratios were 0.98 for 
special affordable loans, 0.99 for low-mod loans, and 0.99 for 
underserved area loans. The ``Freddie-Mac-to-market'' ratios were 
0.04-0.05 lower: 0.93 for special affordable loans, 0.94 for low-mod 
loans, and 0.94 for underserved area loans.

(b.5)  GSE Market Shares

    This analysis includes an expanded ``market share'' analysis 
that documents the GSEs' contribution to important segments of the 
home purchase and first-time homebuyer markets.
    (13) The GSEs account for a significant share of the total 
(government as well as conventional conforming) market for home 
purchase loans. However, the GSEs' market share for each of the 
affordable lending categories is much less than their share of the 
overall market.
     The GSEs' purchases were estimated to be 46 
percent of all home loans originated in metropolitan areas between 
1999 and 2002 but only 29 percent of loans originated for African-
American and Hispanic borrowers, 37 percent of loans originated for 
low-income borrowers, and 36 percent for properties in underserved 
areas. The GSEs' market share for the various affordable lending 
categories increased during 2001 and 2002, but the above-mentioned 
pattern remained.
     A study by staff from the Federal Reserve 
Board suggests that the GSEs have a much more limited role in the 
affordable lending market than is suggested by the data presented 
above.\235\ The Fed study, which combined market share, downpayment, 
and default data, concluded that the GSEs play a very minimal role 
in providing credit support and assuming credit risk for low-income 
and minority borrowers; for example, the study concluded that in 
1995 the GSEs provided only four percent of the credit support going 
to African-Americans and Hispanic borrowers.
---------------------------------------------------------------------------

    \235\ See Glenn B. Canner, Wayne Passmore, and Brian J. Surette, 
``Distribution of Credit Risk Among Providers of Mortgages to Lower-
Income and Minority Homebuyers'' in Federal Reserve Bulletin, 
82(12): 1077-1102, December, 1996.
---------------------------------------------------------------------------

     Section V of this study begins to reconcile 
these different results by examining the role of the GSEs in the 
first-time homebuyer market and the downpayment characteristics of 
mortgages purchased by the GSEs.
    (14) The market role of the GSEs appears to be particularly low 
in important market segments such as minority first-time homebuyers.
     Recent analysis has estimated that the GSEs' 
share of the market for first-time African-American and Hispanic 
homebuyers was only 14.3 percent between 1999 and 2001, or about 
one-third of their share (41.5 percent) of all home purchases during 
that period. This analysis includes the total market, including 
government and conventional loans.
     A similar market share analysis was conducted 
for the conventional conforming market. Between 1999 and 2001, the 
GSEs' purchases accounted for 56.6 percent of all home loans 
originated in the conventional conforming market of both 
metropolitan areas and non-metropolitan areas. Their purchases of 
first-time homebuyer loans, on the other hand, accounted for only 
39.8 percent of all first-time homebuyer loans originated in that 
market.
     The GSEs have funded an even lower share of 
the minority first-time homebuyer market in the conventional 
conforming market. Between 1999 and 2001, the GSEs purchases of 
African-American and Hispanic first-time homebuyer loans represented 
30.9 percent of the conventional conforming market for these loans. 
Thus, while the GSEs have accounted for 56.6 percent of all home 
loans in the conventional conforming market, they have accounted for 
only 30.9 percent of loans originated in that market for African-
American and Hispanic first-time homebuyers.
    (15) A noticeable pattern among the lower-income-borrower loans 
purchased by the GSEs is the predominance of loans with high 
downpayments. This pattern of purchasing mainly high downpayment 
loans is one factor explaining why the Fed study found such a small 
market role for the GSEs. It may be the explanation for the small 
role of Fannie Mae and Freddie Mac in the first-time homebuyer 
market. Further study of this issue is needed.
     During 2001 and 2002, approximately 50 
percent of Fannie Mae's special affordable, low-mod, and underserved 
areas loans had downpayments of at least 20 percent, a percentage 
only slightly smaller than the corresponding percentage (53 percent) 
for all Fannie Mae's home loan purchases. Similar patterns of high 
downpayments on the goals-qualifying loans were evident in Freddie

[[Page 24317]]

Mac's 2001 and 2002 purchases, as well as in prior years for both 
GSEs.

(b.6)  Additional Findings

    This analysis examines two additional topics related to minority 
first-time homebuyers and the use of HMDA data for measuring the 
characteristics of loans originated in the conventional conforming 
market.
    (16) The share of the GSEs' purchases for minority first-time 
homebuyers was much less than the share of newly-originated 
mortgages in the conventional conforming market for those 
homebuyers.
     Between 1999 and 2001, minority first-time 
homebuyers accounted for 6.6 percent of Fannie Mae's purchases of 
home loans, 5.8 percent of Freddie Mac's purchases, and 10.6 percent 
of home loans originated in the conventional conforming market. For 
this subgroup, Fannie Mae's performance is 62 percent of market 
performance, while Freddie Mac's performance is 55 percent of market 
performance.
    (17) Some studies have concluded that HMDA data overstate the 
share of market loans going to low-income borrowers and underserved 
areas. This analysis does not support that conclusion.
     This analysis compares the low-income and 
underserved areas characteristics of the GSEs' purchases of newly-
originated (``current-year'') loans as reported both by the GSEs'' 
own data and by HMDA data.\236\ For recent years, HMDA data on loans 
sold to the GSEs do not always have higher percentages of low-income 
and underserved areas loans than the GSEs' own data on their 
purchases of newly-originated mortgages. For example, from 1996-
2002, both HMDA and Fannie Mae reported that special affordable 
loans accounted for about 13 percent of Fannie Mae's purchases of 
newly-originated loans. HMDA reported a 21.9 underserved areas 
percentage for Fannie Mae, which was rather similar to the 
underserved areas percentage (22.4 percent) reported by Fannie Mae 
itself. Given that similar patterns were observed for Freddie Mac's 
mortgage purchases, it appears that there is no upward bias in the 
HMDA-based market benchmarks used in this study.
---------------------------------------------------------------------------

    \236\ In this comparison, a higher special affordable percentage 
for HMDA-reported mortgage originations that lenders report as also 
being sold to the GSEs--as compared with the special affordable 
percentage for newly-originated mortgages that the GSEs report as 
being actually purchased by them--would suggest that HMDA market 
data are biased; that is, in this situation, the special affordable 
percentage for all mortgage originations reported in HMDA would 
likely be larger than the special affordable percentage for all new 
mortgage originations, including those not reported in HMDA as well 
as those reported in HMDA.
---------------------------------------------------------------------------

7. Definition of Primary Market

    Conventional Conforming Market. The market analysis section is 
based mainly on HMDA data for mortgages originated in the 
conventional conforming market of metropolitan areas during the 
years 1992 to 2002. Only conventional loans with a principal balance 
less than or equal to the conforming loan limit are included; the 
conforming loan limit was $300,700 in 2002--these are called 
``conventional conforming loans.'' The GSEs'' purchases of FHA-
insured, VA-guaranteed, and Rural Housing Service loans are excluded 
from this analysis. The conventional conforming market is used as 
the benchmark against which to evaluate the GSEs because that is the 
market definition Congress requires that HUD consider when setting 
the affordable housing goals. However, as discussed in Section II, 
some have questioned whether lenders in the conventional market are 
doing an adequate job meeting the credit needs of minority 
borrowers, which suggests that this market provides a low 
benchmark.\237\
---------------------------------------------------------------------------

    \237\ The market definition in this section is narrower than the 
``Total Market'' data presented earlier in Tables A.1 and A.2, which 
included all home loans below the conforming loan limit, that is, 
government loans as well as conventional conforming loans. The 
market share analysis reported in Section E.12 also examine the 
GSEs' role in the overall market.
---------------------------------------------------------------------------

    Manufactured Housing Loans. In their comments on the proposed 
2000 Rule, both GSEs raised questions about whether loans on 
manufactured housing should be excluded when comparing the primary 
market with the GSEs. The GSEs purchase these loans, but they have 
not played a significant role in the manufactured housing loan 
market. As emphasized by HUD in its 2000 GSE Rule, manufactured 
housing is an important source of home financing for low-income 
families and for that reason, should be included in any analysis of 
affordable lending. However, for comparison purposes, data are also 
presented for the primary market defined without manufactured 
housing loans. Because this analysis focuses on metropolitan areas, 
it does not include the substantial number of manufactured housing 
loans originated in non-metropolitan areas.
    Subprime Loans. Both GSEs also raised questions about whether 
subprime loans should be excluded when comparing the primary market 
with their performance. In its final 2000 GSE Rule, HUD argued that 
borrowers in the A-minus portion of the subprime market could 
benefit from the standardization and lower interest rates that 
typically accompany an active secondary market effort by the GSEs. 
A-minus loans are not nearly as risky as B&C loans and the GSEs have 
already started purchasing A-minus loans (and likely the lower ``B'' 
grade subprime loans as well). The GSEs themselves have mentioned 
that a large portion of borrowers in the subprime market could 
qualify as ``A credit.'' This analysis includes the A-minus portion 
of the subprime market, or conversely, excludes the B&C portion of 
that market.
    Unfortunately, HMDA does not identify subprime loans, much less 
separate them into their A-minus and B&C components.\238\ Randall M. 
Scheessele at HUD has identified approximately 200 HMDA reporters 
that primarily originate subprime loans and account for about 60-70 
percent of the subprime market.\239\ To adjust HMDA data for B&C 
loans, this analysis follows HUD's 2000 Rule which assumed that the 
B&C portion of the subprime market accounted for one-half of the 
loans originated by the subprime lenders included in Scheessele's 
list.\240\ As shown below, the effects of adjusting the various 
market percentages for B&C loans are minor mostly because the 
analysis in this section focuses on home purchase loans, which 
historically have accounted for less than one quarter of the 
mortgages originated by subprime lenders--the subprime market is 
mainly a refinance market.\241\
---------------------------------------------------------------------------

    \238\ And there is some evidence that many subprime loans are 
not even reported to HMDA, although there is nothing conclusive on 
this issue. See Fair Lending/CRA Compass, June 1999, p. 3.
    \239\ The list of subprime lenders as well as Scheessele's list 
of manufactured housing lenders are available at http://www.huduser.org/publications/hsgfin.html.
    \240\ The one-half estimate is conservative as some observers 
estimate that B&C loans account for only 30-40 percent of the 
subprime market. However, varying the B&C share from 50 percent to 
30 percent does not significantly change the following analysis of 
home purchase loans because subprime loans are mainly for refinance 
purposes. Overstating the share of B&C loans in this manner also 
allows for any differences in HMDA reporting of different types of 
loans--for example, if B&C loans account for 35 percent of all 
subprime loans, then assuming that they account for 50 percent is 
equivalent to assuming that B&C loans are reported in HMDA at 70 
percent of the rate of other loans.
    \241\ The reductions in the market shares are more significant 
for total loans, which include refinance as well as home purchase 
loans; for data on total loans, see Table A.19 in Section 10. 
Subprime lenders have been focusing more on home purchase loans 
recently. The home purchase share of loans originated by the 
subprime lenders in Scheessele's list increased from 26 percent in 
1999 to 36 percent in 2000 before dropping to about 30 percent 
during the heavy refinancing years of 2001 and 2002.
---------------------------------------------------------------------------

    Lender-Purchased Loans in HMDA. When analyzing HMDA data, Fannie 
Mae includes in its market totals those HMDA loans identified as 
having been purchased by the reporting lender, above and beyond 
loans that were originated by the reporting lender.\242\ Fannie Mae 
contends that there are a subset of loans originated by brokers and 
subsequently purchased by wholesale lenders that are neither 
reported by the brokers nor the wholesale lenders as originations 
but are reported by the wholesale lenders as purchased loans. 
According to Fannie Mae, these HMDA-reported purchased loans should 
be added to HMDA-reported originated loans to arrive at an estimate 
of total mortgage originations.
---------------------------------------------------------------------------

    \242\ In 2001 (2002), lenders reported in HMDA that they 
purchased 851,735 (906,684) conventional conforming, home purchase 
loans in metropolitan areas; this compares with 2,763,230 
(2,929,197) loans that these same lenders reported that they 
originated in metropolitan areas.
---------------------------------------------------------------------------

    This rule's market definition includes only HMDA-reported 
originations; purchased loans are excluded from the market 
definition. While some purchased loans may not be reported as 
originations in HMDA (the Fannie Mae argument), there are several 
reasons for assuming that most HMDA-reported purchased loans are 
also reported in HMDA as market originations. First, Fed staff have 
told HUD that including purchased loans would result in double 
counting mortgage originations.\243\ Second,

[[Page 24318]]

comparisons of HMDA-reported FHA data with data reported by FHA 
supports the Fed's conclusion. For instance, FHA's own data indicate 
that during 2001 FHA insured 752,319 home purchase loans in 
metropolitan areas; the sum of HMDA-reported purchased home loans 
and HMDA-reported originated home loans in metropolitan areas alone 
yields a much higher figure of 845,176 FHA-insured loans during 
2001.\244\ While these calculations are for the FHA market (rather 
than the conventional market), they suggest that including HMDA-
reported purchased loans in the market definition would overstate 
mortgage origination totals. Third, Abt Associates surveyed nine 
wholesale lenders and questioned them concerning their guidelines 
for reporting in HMDA loans purchased from brokers. Most of these 
lenders said brokered loans were reported as originations if they 
[the wholesale lender] make the credit decision; this policy is 
consistent with the Fed's guidelines for HMDA reporting. Abt 
Associates concluded that ``brokered loans do seem more likely to be 
reported as originations * * *.'' \245\
---------------------------------------------------------------------------

    \243\ See Randall M. Scheeselle, HMDA Coverage of the Mortgage 
Market, Housing Finance Working Paper No. HF-007. Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, July, 1998.
    \244\ In this example, HMDA-reported purchased loans insured by 
FHA have been reduced from 411,930 to 100,251 by a procedure that 
accounts for missing data and overlapping purchased and originated 
loans. See Harold L. Bunce, The GSEs' Funding of Affordable Loans: A 
2000 Update, Working Paper HF-013, Office of Policy and Development 
and Research, HUD, April 2002, for an alternative analysis showing 
that a market estimate based on adding HMDA-reported purchased loans 
to HMDA-reported originations would substantially overstate the 
volume of FHA mortgage originations in metropolitan areas.
    \245\ See Chapter III, ``Reporting of Brokered and Correspondent 
Loans under HMDA'', in Exploratory Study of the Accuracy of HMDA 
Data, by Abt Associates Inc. under contract for the Office of Policy 
Development and Research, HUD, February 12, 1999, page 18.
---------------------------------------------------------------------------

    Finally, it should be noted that including purchased loans in 
the market definition does not significantly change the goals-
qualifying shares of the market, mostly because borrower income data 
are missing for the majority of purchased loans. In addition, the 
low-income and underserved area shares for purchased and originated 
loans are rather similar. In 2001, the following shares for the 
conventional conforming home purchase market were obtained for 
purchased and originated loans: Low-income (25.8 percent for 
purchased loans, 28.3 percent for market originations), low-mod 
income (41.3 percent, 43.2 percent), and underserved areas (24.2 
percent, 25.8 percent). In 2002, the comparisons were as follows: 
low-income (26.6 percent for purchased loans, 29.7 percent for 
market originations), low-mod income (42.3 percent, 45.3 percent), 
and underserved areas (28.8 percent, 27.2 percent).\246\
---------------------------------------------------------------------------

    \246\ The percentage shares for purchased loans are obtained 
after eliminating purchased loans without data and purchased loans 
that overlap with originated loans. The calculations included 
138,536 purchased loans for 2001 and 182,290 purchased loans for 
2002.
---------------------------------------------------------------------------

8. Technical Issues: Using HMDA Data To Measure the Characteristics 
of GSE Purchases and Mortgage Market Originations \247\
---------------------------------------------------------------------------

    \247\ Readers not interested in these technical issues may want 
to proceed to Section E.9, which compares GSE performance to the 
primary market.
---------------------------------------------------------------------------

    This section discusses important technical issues concerning the 
use of HMDA data for measuring the GSEs' performance relative to the 
characteristics of mortgages originated in the primary market. The 
first issue concerns the reliability of HMDA data for measuring the 
borrower income and census tract characteristics of loans sold to 
the GSEs. Fannie Mae, in particular, contends that HMDA data 
understates the percentages of its business that qualify for the 
three housing goals. In its comments on the proposed 2000 Rule, 
Fannie Mae questioned HUD's reliance on HMDA data for measuring its 
performance. As discussed below, HMDA data on loans sold to the GSEs 
do not include prior-year (seasoned) loans that are sold to the 
GSEs. Since about one-fourth of GSE purchases in any particular year 
involve loans originated in prior years, HMDA data will not provide 
an accurate measure of the goals-qualifying characteristics of the 
GSEs' total purchases when the characteristics of prior-year loans 
differ from those of newly-originated, current-year loans.
    A related issue concerns the appropriate definition of the GSE 
data when making annual comparisons of GSE performance with the 
market. On the one hand, the GSE annual data can be expressed on a 
purchase-year basis, which means that all GSE purchases in a 
particular year would be assigned to that particular year. 
Alternatively, the GSE annual data can be expressed on an 
origination-year basis, which means that GSE purchases in a 
particular year would be assigned to the calendar year that the GSE-
purchased mortgage was originated; for example, a GSE's purchase 
during 2001 of a loan originated in 1999 would be assigned to 1999, 
the year the loan was originated. These two approaches are discussed 
further below.
    A final technical issue concerns the reliability of HMDA for 
measuring the percentage of goals-qualifying loans in the primary 
market. Both GSEs refer to findings from a study by Jim Berkovec and 
Peter Zorn concerning potential bias in HMDA data.\248\ Based on a 
comparison of the borrower and census tract characteristics between 
Freddie-Mac-purchased loans (from Freddie Mac's own data) and loans 
identified in 1993 HMDA data as sold to Freddie Mac, Berkovec and 
Zorn conclude that HMDA data overstate the percentage of 
conventional conforming loans originated for lower-income borrowers 
and for properties located in underserved census tracts. If HMDA 
data overstate the percentage of goals-qualifying loans, then HUD's 
market benchmarks (which are based on HMDA data) will also be 
overstated. The analysis below does not support the Berkovec and 
Zorn findings--it appears that HMDA data do not overstate the share 
of goals-qualifying loans in the market. The discussion below of the 
GSEs' purchases of prior-year and current-year loans also highlights 
the strategy of purchasing seasoned loans that qualify for the 
housing goals. The implications of this strategy for understanding 
recent shifts in the relative performance of Fannie Mae and Freddie 
Mac are discussed below in Section E.9.
---------------------------------------------------------------------------

    \248\ 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.
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a. GSEs' Purchases of ``Prior-Year'' and ``Current-Year'' Mortgages

    There are two sources of loan-level information about the 
characteristics of mortgages purchased by the GSEs--the GSEs 
themselves and HMDA data. The GSEs provide detailed data on their 
mortgage purchases to HUD on an annual basis. As part of their 
annual HMDA reporting responsibilities, lenders are required to 
indicate whether their new mortgage originations or the loans that 
they purchase (from affiliates and other institutions) are sold to 
Fannie Mae, Freddie Mac or some other entity. There have been 
numerous studies by HUD staff and other researchers that use HMDA 
data to compare the borrower and neighborhood characteristics of 
loans sold to the GSEs with the characteristics of all loans 
originated in the market. One question is whether HMDA data, which 
is widely available to the public, provides an accurate measure of 
GSE performance, as compared with the GSEs' own data.\249\ Fannie 
Mae has argued that HMDA data understate its past performance, where 
performance is defined as the percentage of Fannie Mae's mortgage 
purchases accounted for by one of the goal-qualifying categories. As 
explained below, over the past six years, HMDA has provided rather 
reliable national-level information on the goals-qualifying 
percentages for the GSEs' purchases of ``current-year'' (i.e., 
newly-originated) loans, but not for their purchases of ``prior-
year'' loans.\250\
---------------------------------------------------------------------------

    \249\ For another discussion of this issue, see Randall M. 
Scheessele, HMDA Coverage of the Mortgage Market, Housing Finance 
Working Paper HF-007, Office of Policy Development and Research, 
Department of Housing and Urban Development, July 1998. Scheessele 
reports that HMDA data covered 81.6 percent of the loans acquired by 
Fannie Mae and Freddie Mac in 1996. The main reason for the under-
reporting of GSE acquisitions is a few large lenders failed to 
report the sale of a significant portion of their loan originations 
to the GSEs. Also see the analysis of HMDA coverage by Jim Berkovec 
and Peter Zorn. ``Measuring the Market: Easier Said than Done,'' 
Secondary Mortgage Markets. McLean VA: Freddie Mac, Winter 1996, pp. 
18-21; as well as the Berkovec and Zorn study cited in the above 
footnote.
    \250\ Between 1993 and 1996, the GSEs' purchases of prior-year 
loans were not as targeted as they were after 1996; thus, during 
this period, HMDA provided reasonable estimates of the goals-
qualifying percentages of the GSEs' purchases of all (both current-
year and prior-year) loans, with a few exceptions (see Table A.11).
---------------------------------------------------------------------------

    In any given calendar year, the GSEs can purchase mortgages 
originated in that calendar year or mortgages originated in a prior 
calendar year. In 2001 and 2002, for example, purchases of prior-
year mortgages accounted for approximately 20 percent of

[[Page 24319]]

the home loans purchased by each GSE.\251\ HMDA data provide 
information mainly on newly-originated mortgages that are sold to 
the GSEs'that is, HMDA data on loans sold to the GSEs will not 
include many of their purchases of prior-year loans. The 
implications of this for measuring GSE performance can be seen in 
Table A.11, which provides annual data on the borrower and census 
tract characteristics of GSE purchases, as measured by HMDA data and 
by the GSEs' own data. Table A.11 divides each of the GSEs' goals-
qualifying percentages for a particular acquisition year into two 
components, the percentage for ``prior-year'' loans and the 
percentage for ``current-year'' loans.
---------------------------------------------------------------------------

    \251\ During the 1990s, the GSEs increased their purchases of 
seasoned loans; see Paul B. Manchester, Goal Performance and 
Characteristics of Mortgages Purchased by Fannie Mae and Freddie 
Mac, 1998-2000, Housing Finance Working Paper No. HF-015, Office of 
Policy Development and Research, HUD, May 2001.
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BILLING CODE 4210-27-P

[[Page 24320]]

[GRAPHIC] [TIFF OMITTED] TP03MY04.016

BILLING CODE 4210-27-C

[[Page 24321]]

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

b. Reliability of HMDA Data

    With the above explanation of the basic differences between GSE-
reported and HMDA-reported loan information, issues related to the 
reliability of HMDA data can now be discussed. Table A.12 presents 
the same information as Table A.11, except that the data are 
aggregated for the years 1993-5, 1996-2002, and 1999-2002. Comparing 
HMDA-reported data on GSE purchases with GSE-reported current-year 
data suggests that, on average, HMDA data have provided reasonable 
estimates of the goals-qualifying percentages for the GSEs' current-
year purchases (with the exception of Freddie Mac's underserved area 
loans, as discussed below). For example, Fannie Mae reported that 
13.0 percent of the current-year loans it purchased between 1996 and 
2002 were for special affordable borrowers. In their HMDA 
submissions, lenders reported a nearly identical figure of 12.7 
percent for the special affordable share of loans that they sold to 
Fannie Mae. The corresponding numbers for Freddie Mac were 12.4 
percent reported by them and 11.9 percent reported by HMDA. During 
the same period, both Fannie Mae and HMDA reported that 
approximately 22 percent of current-year loans purchased by Fannie 
Mae financed properties in underserved areas. However, Freddie Mac 
reported that 21.0 percent of the current-year loans it purchased 
between 1996 and 2002 financed properties in underserved areas, a 
figure somewhat higher than the 19.5 percent that HMDA reported as 
underserved area loans sold to Freddie Mac during that period.\252\
---------------------------------------------------------------------------

    \252\ Freddie Mac's underserved area figure for 2002 showed a 
particularly large discrepancy--as shown in Table A.11, Freddie Mac 
reported that 25.0 percent of the current-year loans it purchased 
during 2002 financed properties in underserved areas, a figure much 
higher than the 21.4 percent that HMDA reported as underserved area 
loans sold to Freddie Mac during 2002. This is the largest 
discrepancy in Table A.11, and it is not clear what explains it. 
This downward bias for HMDA data, is the opposite of that suggested 
by Berkovec and Zorn, who argued that affordability percentages from 
HMDA data are biased upward.

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BILLING CODE 4210-27-C

[[Page 24323]]

    The facts that the GSE (both Fannie Mae and Freddie Mac) and 
HMDA figures for special affordable and low-mod loans are similar, 
and that the Fannie Mae and HMDA figures for underserved areas are 
similar, suggest that the Berkovec and Zorn conclusions about HMDA 
being upward biased are wrong.\253\ For the 1996-to-2002 period, the 
discrepancies reported in Table A.11 as well as Table A.12 are 
mostly consistent with HMDA being biased in a downward direction, 
not an upward direction as Berkovec and Zorn contend.\254\ In 
particular, the Freddie-Mac-reported underserved area percentage 
being larger than the HMDA-reported underserved area percentage 
suggests a downward bias in HMDA. The more recent and complete 
(Fannie Mae data as well as Freddie Mac data) analysis does not 
support the Berkovec and Zorn finding that HMDA overstates the 
goals-qualifying percentages of the market.\255\
---------------------------------------------------------------------------

    \253\ The data in Table A.12 that support Berkovec and Zorn are 
the 1993-95 special affordable and low-mod data (particularly for 
Freddie Mac) that show HMDA over reporting percentages by more than 
a half percentage point. Otherwise, the data in Table A.12, as well 
as Table A.11, do not present a picture of HMDA's having an upward 
bias in reporting targeted loans. In fact, the recent years' data 
suggest a downward bias in HMDA's reporting of targeted loans.
    \254\ Of course, on an individual year basis, the GSEs' current-
year data can differ significantly from the HMDA-reported data on 
GSE purchases. The other annual data reported in Table A.11 show a 
mixture of results--in some cases the HMDA percentage is larger than 
the GSE--current year'' percentage (e.g., Fannie Mae's special 
affordable purchases in 2000) while in other cases the HMDA 
percentage is smaller than the GSE current year percentage (e.g., 
Freddie Mac's underserved areas purchases in recent years). As noted 
in the text, the differential is typically in the opposite direction 
to that predicted by Berkovec and Zorn, particularly on the 
underserved areas category.
    \255\ Table A.12 also includes aggregates for the more recent 
period, 1999-2002. The ratios of HMDA-reported-to-GSE-reported 
averages for this sub-period are similar to those reported for 1996-
2002.
---------------------------------------------------------------------------

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

    In comparing the GSEs' performance to the primary market, HUD 
has typically expressed the GSEs' annual performance on a purchase-
year basis. That is, all mortgages (including both current-year 
mortgages and prior-year mortgages) purchased by a GSE in a 
particular year are assigned to the year of GSE purchase. The 
approach of including a GSE's purchases of both ``current-year'' and 
``prior-year'' mortgages gives the GSE full credit for their 
purchase activity in the year that the purchase actually takes 
place; this approach is also consistent with the statutory 
requirement for measuring GSE performance under the housing goals. 
However, this approach results in an obvious ``apples to oranges'' 
problem with respect to the HMDA-based market data, which include 
only newly-originated mortgages (i.e., current-year mortgages). To 
place the GSE and market data on an ``apples to apples'' basis, HUD 
has also used an alternative approach that expresses the GSE annual 
data on an origination-year basis. In this case, all purchases by a 
GSE in any particular year would be fully reported but they would be 
allocated to the year that they were originated, rather than to the 
year they were purchased. Under this approach, a GSE's data for the 
year 2000 would not only include that GSE's purchases during 2000 of 
newly-originated mortgages but also any year-2000-originations 
purchased in later years (i.e., during 2001 and 2002 in this 
analysis). This approach places the GSE and the market data on a 
consistent, current-year basis. In the above example, the market 
data would present the income and underserved area characteristics 
of mortgages originated in 2000, and the GSE data would present the 
same characteristics of all year-2000-mortgages that the GSE has 
purchased to date (i.e., through year 2002).\256\
---------------------------------------------------------------------------

    \256\ Under the origination-year approach, GSE performance for 
any specific origination year (say year 2000) at the end of a 
particular GSE purchase year (say year 2002) is subject to change in 
the future years. Table A.16 (in Section E.9 below) reports that 
13.7 percent of year-2000 mortgage originations that Fannie Mae 
purchased through year 2002 qualify as special affordable; the 
special affordable share for the market was 16.8 percent in 2000, 
which indicates that, to date, Fannie Mae has lagged the primary 
market in funding special affordable mortgages originated during 
2000. However, Fannie Mae's special affordable performance could 
change in the future as Fannie Mae continues to purchase year-2000 
originations during 2003 and the following years. Of course, whether 
Fannie Mae's future purchases result in it ever leading the 2000-
year market is not known at this time.
---------------------------------------------------------------------------

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

9. Affordable Lending by the GSEs: Home Purchase Loans

    This section compares the GSEs' affordable lending performance 
with the primary market for the years 1993-2002. The analysis in 
this section begins by presenting the GSE data on a purchase-year 
basis. As discussed above, the GSE data that are reported to HUD 
include their purchases of mortgages originated in prior years as 
well as their purchases of mortgages originated during the current 
year. The market data reported by HMDA include only mortgages 
originated in the current year. This means that the GSE-versus-
market comparisons are defined somewhat inconsistently for any 
particular calendar year. Each year, the GSEs have newly-originated 
loans available for purchase, but they can also purchase loans from 
a large stock of seasoned (prior-year) loans currently being held in 
the portfolios of depository lenders. One method for making the 
purchase-year data more consistent is to aggregate the data over 
several years, instead of focusing on annual data. This provides a 
clearer picture of the types of loans that have been originated and 
are available for purchase by the GSEs. This approach is taken in 
Table A.13, which is discussed below. Another method for making the 
GSE and market data consistent is to express the GSE data on an 
origination-year basis; that approach is taken in Table A.16, which 
is discussed after presenting the annual results on a purchase-year 
basis.

a. Longer-Term Performance, 1993-2002 and 1996-2002

    Table A.13 summarizes the funding of goals-qualifying mortgages 
by the GSEs, depositories and the conforming market for the ten-year 
period between 1993 and 2002. Data are also presented for two 
important sub-periods: 1993-95 (for showing how much the GSEs have 
improved their performance since the early-to-mid 1990s); and 1996-
2002 (for analyzing their performance since the current definitions 
of the housing goals were put into effect). Given the importance of 
the GSEs for expanding homeownership, this section focuses on home 
purchase mortgages, and the next section will examine first-time 
homebuyer loans. Section IV below will briefly discuss the GSEs' 
overall performance, including refinance and home purchase loans. 
Several points stand out concerning the affordable lending 
performance of Freddie Mac and Fannie Mae over the two longer-term 
periods, 1993-2002 and 1996-2002.
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    Freddie Mac lagged both Fannie Mae and the primary market in 
funding affordable home loans in metropolitan areas between 1993 and 
2002. During that period, 11.8 percent of Freddie Mac's mortgage 
purchases were for special affordable (mainly very-low-income) 
borrowers, compared with 12.7 percent of Fannie Mae's purchases, 
15.4 percent of loans originated by depositories,\257\ and 15.4 
percent of loans originated in the conforming market without B&C 
loans.\258\
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    \257\ As shown in Table A.13, the depository percentage is 
higher (16.9 percent) if the analysis is restricted to those newly-
originated loans that depositories do not sell (the latter being a 
proxy for loans held in depositories' portfolios). Note that during 
the recent, 1999-to-2002 period (also reported in Table A.13), there 
is less difference between the two depository figures.
    \258\ Unless stated otherwise, the market in this section is 
defined as the conventional conforming market without estimated B&C 
loans.
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    Although Freddie Mac consistently improved its performance 
during the 1990s, a similar pattern characterized the 1996-2002 
period. During that period, 39.8 percent of Freddie Mac's purchases 
were for low- and moderate-income borrowers, compared with 41.2 
percent of Fannie Mae's purchases, 43.1 percent of loans originated 
by depositories, and 43.6 percent of loans originated in the 
conventional conforming market. Over the same period, 21.7 percent 
of Freddie Mac's purchases financed properties in underserved 
neighborhoods, compared with 23.5 percent of Fannie Mae's purchases, 
24.9 percent of depository originations, and 25.4 percent of loans 
originated in the primary market.
    Fannie Mae's affordable lending performance was better than 
Freddie Mac's over the 1993 to 2002 period as well as during the 
1996 to 2002 period. However, Fannie Mae lagged behind depositories 
and the overall market in funding affordable loans during both of 
these periods (see above paragraph). Between 1996 and 2002, the 
``Fannie-Mae-to-market'' ratio was only 0.84 on the special 
affordable category, obtained by dividing Fannie Mae's performance 
of 13.5 percent by the market's performance of 16.0 percent. Fannie 
Mae's market ratio was 0.94 on the low-mod category and 0.93 on the 
underserved area category. The ``Freddie-Mac-to-market'' ratios were 
lower'0.80 for special affordable, 0.91 for low-mod, and 0.85 for 
underserved areas.
    The above analysis has defined the market to exclude B&C loans, 
which HUD believes is the appropriate market definition. However, to 
gauge the sensitivity of the results to how the market is defined, 
Table A.14 shows the effects on the market percentages for different 
definitions of the conventional conforming market, such as excluding 
manufactured housing loans, small loans, and all subprime loans 
(i.e., the A-minus portion of the subprime market as well as the B&C 
portion). For example, the average special affordable (underserved 
area) market percentage for 1996-2002 would fall by about 0.2 (0.6) 
percentage point if the remaining subprime loans (i.e., the A-minus 
loans) were also excluded from the market totals. Excluding 
manufactured housing loans in metropolitan areas would reduce the 
above market percentage for special affordable (underserved area) 
loans by 1.5 (1.1) percentage points. The above findings with 
respect to the GSEs' longer-term performance are not much affected 
by the choice of market definition.

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b. Recent Performance, 1999-2002

    This and the next subsection focus on the average data for 1999-
2002 in Table A.13 and the annual data reported in Table A.14. As 
explained below, the annual data are useful for showing shifts in 
the relative positions of Fannie Mae and Freddie Mac that began in 
1999, and for highlighting the improvements made by Fannie Mae 
during 2001 and 2002 (which were the first two years under HUD's 
higher goal levels) and by Freddie Mac during 2002. Between 1993 and 
1998, Freddie Mac's performance fell below Fannie Mae's, but a sharp 
improvement in Freddie Mac's performance during 1999 pushed it pass 
Fannie Mae on all three goals-qualifying categories. In 2000, Fannie 
Mae improved its underserved areas performance enough to surpass 
Freddie Mac on that category, while Freddie Mac continued to out-
perform Fannie Mae on the borrower-income categories (special 
affordable and low-mod). During 2001 and 2002, Fannie Mae improved 
its performance enough to surpass Freddie Mac on all three goals-
qualifying categories and to essentially match the market during 
these two years.
    Consider first the average data for 1999-2002 reported in Table 
A.13. During this recent period, Freddie Mac's average performance 
was similar to Fannie Mae's performance for the borrower income 
categories. Between 1999 and 2002, 14.5 percent of Freddie Mac's 
purchases and 14.4 percent Fannie Mae's mortgage purchases consisted 
of special affordable loans, compared with a market average of 16.4 
percent. In addition, Freddie Mac purchased low-mod loans at about 
the same rate as Fannie Mae during this period--42.3 percent for the 
Freddie Mac, 42.5 percent for Fannie Mae, and 44.3 percent for the 
market. Freddie Mac (22.9 percent) purchased underserved area loans 
at a lower rate than Fannie Mae (24.0 percent) and the primary 
market (25.8 percent). As these figures indicate, both Fannie Mae 
and Freddie Mac continued to lag the market during this recent four-
year period. Both GSEs' market ratios were 0.88 for special 
affordable loans and approximately 0.95 for low-mod loans. Although 
less than one (where one indicates equal performance with the 
market), the ``Fannie-Mae-to-market'' ratio (0.93) for the 
underserved area category was higher than the ``Freddie-Mac-to-
market'' ratio (0.89).
    Fannie Mae had an uncharacteristically poor year in 1999. Thus, 
averages for 2000-2002 are also presented in Table A.13, dropping 
1999. These data show an increase in Fannie Mae's performance 
relative to the market, particularly on the special affordable and 
underserved areas categories. Between 2000 and 2002, special 
affordable (underserved area) loans accounted for 15.0 percent (24.9 
percent) of Fannie Mae's purchases, compared with 16.2 percent (26.0 
percent) for the market.
    Table A.14 shows the effects on the market percentages for 1999-
2002 (as well as 2000-2002) of different definitions of the 
conventional conforming market. Excluding manufactured housing loans 
(as well as B&C loans) in metropolitan areas would reduce the 1999-
2002 market percentage for special affordable loans from 16.4 
percent to 15.2 percent, which would raise the GSEs' market ratios 
from approximately 0.88 to 0.95. Similarly, excluding manufactured 
housing loans would reduce the 1999-2002 market percentage for 
underserved areas from 25.8 percent to 25.0 percent, which would 
raise Fannie Mae's market ratio from 0.93 to 0.96 and Freddie Mac's, 
from 0.89 to 0.92. As shown in Table A.14, Fannie Mae is even closer 
to the market averages if the year 1999 is dropped--over the 2000-
2002 period, Fannie Mae's performance on the underserved area 
category is practically at market levels under the alternative 
definitions of the market, and its performance on the special 
affordable and low-mod categories to close to market levels.

c. GSEs' Performance--Annual Data

    Freddie Mac's Annual Performance. As shown by the annual data 
reported in Table A.15, Freddie Mac significantly improved its 
purchases of goals-qualifying loans during the 1990s. Its purchases 
of loans for special affordable borrowers increased from 6.5 percent 
of its business in 1992 to 9.2 percent in 1997, and then jumped to 
14.7 percent in 2000 before falling slightly to 14.4 percent in 2001 
and rising again to 15.8 percent in 2002. The underserved areas 
share of Freddie Mac's purchases increased at a more modest rate, 
rising from 18.6 percent in 1992 to 22.3 percent by 2001; it then 
jumped to 25.8 percent in 2002.
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    With its improved performance, Freddie Mac closed its gap with 
the market in funding goals-qualifying loans. In 2002, special 
affordable loans accounted for 15.8 percent of Freddie Mac's 
purchases and 16.3 percent of loans originated in the conventional 
conforming market, which produces a ``Freddie-Mac-to-market'' ratio 
of 0.97 (15.8 divided by 16.3). Table A.15 shows the trend in the 
``Freddie-Mac-to-market'' ratio from 1992 to 2002 for each of the 
goals-qualifying categories. For the special affordable and low-mod 
categories, Freddie Mac's performance relative to the market 
remained flat (at approximately 0.60 and 0.80, respectively) through 
1997; by 2002, the ``Freddie-Mac-to-market'' ratios had risen to 
0.97 for both the special affordable and low-mod categories.
    Surprisingly, Freddie Mac did not make much progress during the 
1990s closing its gap with the market on the underserved areas 
category. The ``Freddie-Mac-to-market'' ratio for underserved areas 
was approximately the same in 2000 (0.83) as it was in 1992 (0.84). 
While it rose to 0.88 in 2001, that was due more to a decline in the 
market level than to an improvement in Freddie Mac's performance. 
However, due to a substantial increase in Freddie Mac's underserved 
area percentage from 22.3 percent in 2001 to 25.8 percent in 2002, 
Freddie Mac's performance approached market performance (26.4 
percent) during 2002. \259\ In the ten years under the housing 
goals, the year 2002 represented the first time that Freddie Mac's 
performance in purchasing home loans in underserved areas had ever 
been within two percentage points of the market's performance.\260\
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    \259\ Table A.14 reports annual market percentages that exclude 
the effects of manufactured housing, small loans, and subprime 
loans. Freddie Mac's performance is closer to the market average 
under the alternative market definitions, particularly during 2001 
and 2002.
    \260\ Prior to 2002, Freddie Mac's performance on the 
underserved areas category had not approached the market even under 
the alternative market definitions reported in Table A.14.
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    Fannie Mae's Annual Performance. With respect to purchasing 
affordable loans, Fannie Mae followed a different path than Freddie 
Mac. Fannie Mae improved its performance between 1992 and 1998 and 
made much more progress than Freddie Mac in closing its gap with the 
market. In fact, by 1998, Fannie Mae's performance was close to that 
of the primary market for some important components of affordable 
lending. In 1992, special affordable loans accounted for 6.3 percent 
of Fannie Mae's purchases and 10.4 percent of all loans originated 
in the conforming market, giving a ``Fannie Mae-to-market'' ratio of 
0.61. By 1998, this ratio had risen to 0.86, as special affordable 
loans had increased to 13.2 percent of Fannie Mae's purchases and to 
15.4 percent of market originations. A similar trend in market 
ratios can be observed for Fannie Mae on the underserved areas 
category. In 1992, underserved areas accounted for 18.3 percent of 
Fannie Mae's purchases and 22.2 percent of market originations, for 
a ``Fannie Mae-to-market'' ratio of 0.82. By 1998, underserved areas 
accounted for 22.8 percent of Fannie Mae's purchases and 24.2 
percent of market originations, for a higher ``Fannie Mae-to-
market'' ratio of 0.94.\261\
---------------------------------------------------------------------------

    \261\ Freddie Mac, on the other hand, fell further behind the 
market during this period. In 1992, Freddie Mac had a slightly 
higher underserved areas percentage (18.6 percent) than Fannie Mae 
(18.3 percent). However, Freddie Mac's underserved areas percentage 
had only increased to 19.8 percent by 1998 (versus 22.7 percent for 
Fannie Mae). Thus, the ``Freddie Mac-to-market'' ratio fell from 
0.84 in 1992 to 0.82 in 1998.
---------------------------------------------------------------------------

    The year 1999 saw a shift in the above patterns, with Fannie Mae 
declining in overall performance while the share of goals-qualifying 
loans in the market increased. Between 1998 and 1999, the special 
affordable share of Fannie Mae's business declined from 13.2 percent 
to 12.5 percent while this type of lending in the market increased 
from 15.4 percent to 17.0 percent. For this reason, the ``Fannie-
Mae-to-market'' ratio for special affordable loans declined sharply 
from 0.86 in 1998 to 0.74 in 1999. The share of Fannie Mae's 
purchases in underserved areas also declined, from 22.7 percent in 
1998 to 20.4 percent in 1999, which lowered the ``Fannie-Mae-to-
market'' ratio from 0.94 to 0.81.
    After declining in 1999, Fannie Mae's performance rebounded in 
2000, particularly on the underserved areas category. Fannie Mae's 
underserved areas percentage jumped by three percentage points from 
20.4 percent in 1999 to 23.4 percent in 2000. The 2000 figure was 
similar to its level in 1997 but below Fannie Mae's peak 
performances of 24-25 percent during 1994 and 1995. Between 1999 and 
2000, the ``Fannie-Mae-to-market'' ratio for underserved areas 
increased from 0.82 to 0.89. Fannie Mae improved its performance on 
the special affordable goal at a more modest rate. Fannie Mae's 
special affordable percentage increased by 0.8 percentage points 
from 12.5 percent in 1999 to 13.3 percent in 2000. The 2000 figure 
was similar to its previous peak level (13.2 percent) in 1998). The 
``Fannie-Mae-to-market'' ratio for special affordable loans 
increased from 0.74 in 1999 to 0.79 in 2000, with the latter figure 
remaining below Fannie Mae's peak market ratio (0.86) in 1998.
    Fannie Mae continued its improvement in purchasing targeted home 
loans during 2001, at a time when the conventional conforming market 
was experiencing a decline in affordable lending, and again in 2002, 
at a time when the conventional conforming market was increasing 
enough to return approximately to its year-2000 level. Thus, during 
the 2000-to-2002 period, Fannie Mae significantly improved its 
targeted purchasing performance while the primary market originated 
targeted home loans at about the same rate in 2002 as it did in 
2000. As a result, Fannie Mae's performance during 2001 approached 
the market on the special affordable and underserved area categories 
and matched the market on the low-mod category. In 2002, Fannie Mae 
matched the market on the special affordable category, and slightly 
outperformed the market on the low-mod and underserved areas 
categories.
    As shown in Table A.15, Fannie Mae increased its special 
affordable percentage by 1.6 percentage points, from 13.3 percent in 
2000 to 14.9 percent in 2001, and then increased it further to 16.3 
percent in 2002, the latter being the same as the market's 
performance of 16.3 percent. The ``Fannie-Mae-to-market'' ratio for 
special affordable loans jumped from 0.79 in 2000 to 1.00 in 2002. 
Between 2000 and 2001, Fannie Mae increased its low-mod percentage 
from 40.8 percent to 42.9 percent at the same time that the low-mod 
share of the primary market was falling from 44.4 percent to 42.9 
percent, placing Fannie Mae at the market's performance in 2001. 
During 2002, the low-mod share of Fannie Mae's purchases of home 
loans increased further to 45.3 percent, placing Fannie Mae 0.1 
percentage point above the market performance of 45.2 percent. 
Fannie Mae increased its underserved area percentage from 23.4 
percent in 2000 to 24.4 in 2001 percent while the underserved area 
share of the primary market was falling from 26.4 percent to 25.2 
percent, placing Fannie Mae at less than one percentage point from 
the market's performance. The ``Fannie-Mae-to-market'' ratio for 
underserved area loans was 0.97 in 2001. During 2002, the 
underserved area share of Fannie Mae's purchases of home loans 
increased further to 26.7 percent, placing Fannie Mae slightly ahead 
of market performance (26.4 percent).
    Table A.14 reports Fannie Mae's 2001 and 2002 performance under 
alternative definitions of the primary market. As shown there, the 
above results of Fannie Mae's improvement relative to the market 
during 2001 and 2002 are further reinforced when lower market 
percentages are used.
    Changes in the ``Fannie-Mae-to-Freddie-Mac'' Performance Ratio. 
The above discussion documents shifts in the relative performance of 
Fannie Mae and Freddie Mac over the past few years. To highlight 
these changing patterns, Table A.15 reports the ratio of Fannie 
Mae's performance to Freddie Mac's performance for each goals 
category for the years 1992 to 2002. As shown there, the ``Fannie-
Mae-to-Freddie-Mac'' ratio for the special affordable category 
increased from approximately one in 1992 (indicating equal 
performance) to over 1.3 during the 1994-97 period, indicating that 
Fannie Mae clearly out-performed Freddie Mac during this period. 
Between 1997 and 2000, Freddie Mac substantially increased its 
special affordable share (from 9.2 percent to 14.7 percent), causing 
the ``Fannie-Mae-to-Freddie-Mac'' ratio to fall from 1.27 in 1997 to 
0.90 in 2000 (indicating Freddie Mac surpassed Fannie Mae). But 
Fannie Mae's stronger performance during 2001 and 2002 returned the 
ratio to above one (1.03 in both years), indicating slightly better 
performance for Fannie Mae (e.g., 16.3 percent in 2002 versus 15.8 
percent for Freddie Mac). The ``Fannie-Mae-to-Freddie-Mac'' 
performance ratio for low-mod loans followed a similar pattern, 
standing at 1.03 in 2002 (45.3 percent for Fannie Mae versus 44.0 
percent for Freddie Mac).
    Prior to 2000, the ``Fannie-Mae-to-Freddie-Mac'' ratio for 
underserved areas had also followed a pattern similar to that 
outlined above for special affordable loans, but at a lower overall 
level--rising from about one in 1992 (indicating equal performance) 
to approximately 1.2 during the 1994-97

[[Page 24330]]

period, before dropping to slightly below one (0.98) in 1999. 
However, Fannie Mae increased its underserved areas percentage from 
20.4 percent in 1999 to 24.4 percent in 2001 while Freddie Mac only 
increased its percentage from 20.9 percent to 22.3 percent. This 
resulted in the ``Fannie-Mae-to-Freddie-Mac'' ratio rising from 0.98 
in 1999 to 1.09 in 2001. But during 2002, Freddie Mac's underserved 
area percentage jumped by 3.5 percentage points to 25.8 percent, 
while Fannie Mae's increased at a more modest rate (by 2.3 
percentage points) to 26.7 percent, with the result being that the 
``Fannie-Mae-to-Freddie-Mac'' ratio for underserved area loans fell 
from 1.09 in 2001 to 1.03 in 2002.
    To conclude, while Freddie Mac ended the 1990s on a more 
encouraging note than Fannie Mae, the past three years (2000, 2001, 
and 2002) have seen a substantial improvement in Fannie Mae's 
performance on all three goals-qualifying categories. Fannie Mae 
ended the 1990s with a decline in affordable lending performance at 
the same time that Freddie Mac was improving and the share of goals-
qualifying loans was increasing in the market. Both GSEs' 
performance during 2000 was encouraging--Freddie Mac continued to 
improve, particularly with respect to the borrower-income 
categories, while Fannie Mae reversed its declining performance, 
particularly with respect to underserved areas. During 2000, Freddie 
Mac outperformed Fannie Mae on the special affordable and low-mod 
categories, while Fannie Mae purchased a higher percentage of loans 
in underserved areas. During 2001, Fannie Mae continued to improve 
its performance while Freddie Mac's performance remained about the 
same and the market's originations of affordable loans declined 
somewhat. The result was that during 2001 Fannie Mae outperformed 
Freddie Mac on all three goals-qualifying categories, and even 
matched the market on the low-mod category. During 2002, both Fannie 
Mae and Freddie Mac again improved their performance; Fannie Mae 
continued to outperform Freddie Mac and even matched the market on 
the special affordable category and slightly outperformed the market 
on the low-mod and underserved area categories. While Freddie Mac 
lagged the market on all three goals-qualifying categories during 
2002, it had significantly closed its gap with the market by the end 
of 2002, particularly on the underserved area category.
    GSE Purchases of Seasoned Loans. When the GSE data are expressed 
on a purchase-year basis (as in the above analysis), one factor 
which affects each GSE's performance concerns their purchases of 
seasoned (prior-year) loans. As shown in Table A.11, Fannie Mae 
followed a strategy of purchasing targeted seasoned loans between 
1996 and 1998, and again during the past three years--all years when 
Fannie Mae improved its overall affordable lending performance. For 
example, consider Fannie Mae's underserved area performance of 24.4 
percent during 2001, which was helped by its purchases of seasoned 
mortgages on properties located in underserved neighborhoods. The 
underserved area percentage for Fannie Mae's purchases of newly-
originated (current-year) mortgages was only 23.3 percent in 2001, 
or 1.9 percentage points below the market average of 25.2 percent. 
Fannie Mae obtained its higher overall percentage (24.4 percent) by 
purchasing seasoned loans with a particularly high concentration 
(28.3 percent) in underserved areas. Similarly, during 2001, the 
special affordable share of Fannie Mae's purchases of newly-
originated mortgages was only 14.2 percent, or 1.4 percentage points 
below the market average of 15.6 percent. Again, Fannie Mae improved 
its overall performance by purchasing seasoned loans with a high 
percentage (18.1) of special affordable loans, enabling Fannie Mae 
to reduce its gap with the market to 0.7 percentage points--14.9 
percent versus 15.6 percent.
    As shown in Table A.11, Freddie Mac also followed a strategy of 
purchasing seasoned special affordable loans mainly during 2000 and 
2001. Prior to 2000, Freddie Mac had not pursued such a strategy, or 
at least not to the same degree as Fannie Mae. During the 1997-99 
period, Freddie Mac's purchases of prior-year mortgages and newly-
originated mortgages had similar percentages of special affordable 
(and low-mod) borrowers. Over time, there have been small 
differentials between Freddie Mac's prior-year and newly-originated 
mortgages for the underserved areas category but they have been 
smaller than the differentials for Fannie Mae (see Table A.11).

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

    Table A.16 reports GSE purchase data for 1996 to 2002 on an 
origination-year basis. Recall that in this case, mortgages 
purchased by a GSE in any particular calendar year are allocated to 
the year that the mortgage was originated, rather than to the year 
that the mortgage was purchased (as in subsections C.1-C.3 above). 
This approach places the GSE and the market data on a consistent, 
current-year basis, as explained earlier.
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    In general, the comparisons of Freddie Mac's and the market's 
performance are similar to those discussed in Sections E.9.a-c 
above, except for some differences on the special affordable 
category. The ``Freddie Mac to market'' ratios in Table A.16 show 
that Freddie Mac has improved its performance but has also 
consistently lagged the primary market in funding mortgages covered 
by the housing goals.
    The ``Fannie Mae to market'' ratios in Table A.16 show that 
Fannie Mae has improved its performance, and has generally 
outperformed Freddie Mac, but has lagged the primary market in 
funding mortgages covered by the housing goals. Under the 
origination-year approach, Fannie Mae lagged the market on all three 
housing goal categories during 2001 and on the special affordable 
and underserved area categories during 2002. In 2002, low- and 
moderate-income loans accounted for 45.4 percent of Fannie Mae's 
purchases and 45.2 percent of the market originations, placing 
Fannie Mae 0.2 percentage points above the market.

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

    While not a specific housing goal category, mortgages for first-
time homebuyers are an important component of the overall home loan 
market. Making financing available for first-time homebuyers is one 
approach for helping young families enter the homeownership market. 
Therefore, this section briefly compares the GSEs' funding of first-
time homebuyer loans with that of primary lenders in the 
conventional conforming market.
    During the past few years, the GSEs have increased their 
purchases of first-time homebuyer loans. Fannie Mae's annual 
purchases of first-time homebuyer loans increased from approximately 
287,000 in 1999 to 373,000 in 2002, while Freddie Mac's annual 
purchases increased from 199,000 to 259,000 during the same 
period.\262\ However, since 1999, the first-time homebuyer share of 
the GSEs' purchases of home loans has remained relatively flat, 
varying within the 25-28 percent range.\263\
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    \262\ These figures include estimates of first-time homebuyer 
loans for those home purchase loans with a missing first-time 
homebuyer indicator; the estimates were obtained by multiplying the 
GSE's first-time homebuyer share (based only on data with a first-
time homebuyer indicator) by the number of loans with a missing 
first-time homebuyer indicator.
    \263\ The first-time homebuyer share for Fannie Mae was almost 
35 percent between 1996 and 1998; it then dropped to 30 percent in 
1998 and to 26 percent in 1999. The first-time homebuyer share for 
Freddie Mac was approximately 29 percent in 1996 and 1997 before 
dropping to about 25 percent in 1998 and 1999.
---------------------------------------------------------------------------

    Table A.17 compares the first-time homebuyer share of GSE 
purchases with the corresponding share of home loans originated in 
the conventional conforming market. Readers are referred to recent 
work by Bunce and Gardner \264\ for the derivation of the estimates 
of first-time homebuyer market shares reported in Table A.17. This 
analysis does not include year 2002 data because market data from 
the American Housing Survey are not yet available for that year. 
Between 1999 and 2001, first-time homebuyers accounted for 26.5 
percent of Fannie Mae's purchases of home loans, 26.5 percent of 
Freddie Mac's, and 37.6 percent of home loans originated in the 
conventional conforming market. Thus, both Fannie Mae and Freddie 
Mac fell substantially short of the primary market in financing 
first-time homebuyers during this time period. The GSEs' performance 
was only 70.5 percent of market performance (26.5 percent divided by 
37.6 percent).
---------------------------------------------------------------------------

    \264\ See Harold L. Bunce and John L. Gardner, ``First-time 
Homebuyers in the Conventional Conforming Market: The Role of the 
GSEs'' (unpublished paper), January 2004.
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    Table A.17 also reports first-time homebuyer shares for African 
Americans and Hispanics and for all minorities. Between 1999 and 
2001, African-American and Hispanic first-time homebuyers accounted 
for 4.0 percent of Fannie Mae's purchases of home loans, 3.4 percent 
of Freddie Mac's purchases, and 6.9 percent of home loans originated 
in the conventional conforming market. For this subgroup, Fannie 
Mae's performance is 58 percent of market performance, while Freddie 
Mac's performance is 49 percent of market performance. The group of 
all minority first-time homebuyers accounted for 6.6 percent of 
Fannie Mae's purchases of home loans, 5.8 percent of Freddie Mac's 
purchases, and 10.6 percent of home loans originated in the 
conventional conforming market. In this case, Fannie Mae's 
performance is 62 percent of market performance, while Freddie Mac's 
performance is 55 percent of market performance.
    Section E.12 below will continue this examination of first-time 
homebuyers by presenting market share analysis that estimates the 
GSEs' overall importance in the funding of first-time homebuyers.

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

    The Department is proposing to establishing a subgoal of 45 
percent for each GSE's purchases of home purchase loans for low- and 
moderate-income families in the single-family-owner market of 
metropolitan areas for 2005, with the proposed subgoal rising to 46 
percent for 2006 and 47 percent for 2007 and 2008. If the GSEs meet 
this subgoal, they will be leading the primary market by 
approximately one percentage point in 2005 and by three percentage 
points in 2007-08, based on historical data (see below). This home 
purchase subgoal will encourage the GSEs to expand homeownership 
opportunities for lower-income homebuyers who are expected to enter 
the housing market over the next few years. As detailed in Section 
I, there are four specific reasons for establishing this subgoal: 
(1) The GSEs have the expertise, resources, and ability to lead the 
single-family-owner market, which is their ``bread and butter'' 
business; (2) the GSEs have historically lagged the primary market 
for low- and moderate-income loans, not lead it; (3) the GSEs can 
improve their funding of first-time homebuyers and help reduce 
troublesome disparities in homeownership and access to mortgage 
credit; and (4) there are ample opportunities for the GSEs to expand 
their purchases in important and growing market segments such as the 
market for minority first-time homebuyers. Sections E.9 and G of 
this appendix provide additional information on opportunities for an 
enhanced GSE role in the home purchase market and on the ability of 
the GSEs to lead that market.
    As shown in Tables A.13 and A.15, low- and moderate-income 
families accounted for an average of 44.3 percent of home purchase 
loans originated in the conventional conforming market of 
metropolitan areas between 1999 and 2002; the figure is 43.6 percent 
if the average is computed for the years between 1996 and 2002. 
Loans in the B&C portion of the subprime market are excluded from 
these market averages. To reach the proposed 45-percent subgoal for 
2005, both GSEs would have to improve their historical performance--
Fannie Mae by 0.8 percentage points over its average performance of 
44.2 percent in 2001 and 2002, and Freddie by 2.4 percentage points 
over its average performance of 42.6 percent during the same period. 
To reach the 47 percent subgoal in 2007-08, each GSE's performance 
would have to increase by an additional two percentage points.
    As explained earlier, HUD will be re-benchmarking its median 
incomes for metropolitan areas and non-metropolitan counties based 
on 2000 Census median incomes, and will be incorporating the effects 
of the new OMB metropolitan area definitions. As explained in 
Appendix D, HUD projected the effects of these two changes on the 
low- and moderate-income shares of the single-family-owner market 
for the years 1999-2002. These estimates will be referred to as 
``projected data'' while the 1990-based data reported in the various 
tables will be referred to as ``historical data.'' With the 
historical data, the average low-mod share of the conventional 
conforming market (without B&C loans) was 44.3 percent for home 
purchase loans (weighted average of 1999-2002 percentages in Table 
A.13); the corresponding average with the projected data was 43.1 
percent, a differential of 1.2 percentage points. The projected low-
mod percentages for each year between 1999 and 2002 were as follows 
(with the historical percentages from Table A.15 in parentheses): 
44.0 (44.8) percent for 1999; 43.7 (43.7) percent for 2000; 41.6 
(42.9) percent for 2001; and 43.1 (45.2) percent for 2002. The 
differentials between the projected and historical data are larger 
in 2001 (1.3 percentage points) and 2002 (2.1 percentage points) 
than in 1999 (0.8 percentage point) and 2000 (0.7 percentage point). 
It appears that the low-mod share for single-family-owners in the 
conventional conforming market will be at least one percentage point 
less due to the re-benchmarking of area median incomes and the new 
OMB definitions of metropolitan areas. Thus, based on projected 
data, the 45-percent (47 percent) subgoal for 2005 (2007) is 
approximately two (four) percentage points above the 1999-2002 
market average.
    The estimated low-mod percentages between 1999 and 2002 for 
Fannie Mae were as follows (with the historical percentages from 
Table A.15 in parentheses): 39.2 (40.0) percent for 1999; 40.1 
(40.8) percent for 2000; 41.7 (42.9) percent for 2001; and 43.6 
(45.3) percent for 2002; Fannie Mae's average low-mod performance 
between 1999 and 2002 based on the projected data was 41.4 percent, 
compared with 42.5 percent based on historical data. To reach the 
45-percent subgoal (47 percent) subgoal for 2005 (2007) based on 
projected data, Fannie Mae would have to improve its performance by 
2.3 (4.3) percentage points over its estimated average performance 
of 42.7 percent in 2001 and 2002, or by 1.4 (3.4) percentage points 
over its estimated 2002 low-mod performance of 43.6 percent.
    The estimated low-mod percentages between 1999 and 2002 for 
Freddie Mac were as follows (with the historical percentages from 
Table A.15 in parentheses): 40.0 (40.8) percent for 1999; 41.7 
(42.7) percent for 2000; 39.8 (41.3) percent for 2001; and 42.1 
(44.0) percent for 2002; Freddie Mac's average low-mod performance 
between 1999 and 2002 based on the projected data was 40.9 percent, 
compared with 42.3 percent based on historical data. To reach the 
45-percent subgoal based on projected data, Freddie Mac would have 
to improve its performance by 4.0 percentage points over its 
projected average performance of 41.0 percent in 2001 and 2002, or 
by 2.9 percentage points over its projected 2002 low-mod performance 
of 42.1 percent.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for non-metropolitan areas are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices B and C.

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

    Section E.9 examined the GSEs' acquisitions of home purchase 
loans, which is appropriate given the importance of the GSEs for 
expanding homeownership opportunities. To provide a complete picture 
of the GSEs' mortgage purchases in metropolitan areas, Tables A.18, 
A.19, A.20, and A.21 report the GSEs' purchases of all single-
family-owner mortgages, including both home purchase loans and 
refinance loans.\265\
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    \265\ The GSE total (home purchase and refinance) data in Tables 
A.18-A.20 are presented on a purchase-year basis; Table A.21 
presents similar data on an origination-year basis.
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    Table A.18 provides a long-run perspective on the GSEs' overall 
performance. Between 1993 and 2002, as well as during the 1996-2002 
period, each GSE's performance was 80-86 percent of market 
performance for the special affordable category, 91-95 percent of 
market performance for the low-mod category, and 88-92 percent of 
market performance for the underserved areas category. For example, 
between 1996 and 2002, underserved areas accounted for 23.2 percent 
of Fannie Mae's purchases and 22.4 percent of Freddie Mac's 
purchases, compared with 25.5 percent for the conventional 
conforming market (without B&C loans). Similarly, for special 
affordable loans, both GSEs lagged the market during the 1996-2002 
period--Fannie Mae and Freddie Mac averaged approximately 13.0 
percent while the market was over two percentage points higher at 
15.2 percent.
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    Similar to the patterns discussed for home purchase loans, 
Fannie Mae has tended to outperform Freddie Mac. This can be seen by 
examining the various ``Fannie-Mae-to-Freddie-Mac'' ratios in Table 
A.18, which are all equal to or greater than one. Over the recent 
1999-2002 period, Fannie Mae and Freddie Mac continued to lag the 
overall market on all three goals-qualifying categories. Special 
affordable (underserved area) loans averaged 13.8 (23.8) percent of 
Fannie Mae's purchases, 13.8 (23.1) percent of Freddie Mac's 
purchases, and 15.7 (25.7) percent of market originations. 
Considering both GSEs, the market ratio was 0.88 for special 
affordable loans, approximately 0.95 for low-mod loans, and slightly 
over 0.90 for underserved area loans. As with home purchase loans, 
dropping the year 1999 and characterizing recent performance by the 
2000-2002 period improves the performance of both GSEs relative to 
the market, but particularly Fannie Mae. Over the 2000-2002 period, 
the ``Fannie-Mae-to-market'' ratio was 0.93 for Special Affordable 
loans, 0.98 for low-mod loans, and 0.96 for underserved area loans.
    The above analysis has defined the market to exclude B&C loans. 
Table A.19 shows the effects on the market percentages of different 
definitions of the conventional conforming market. For example, the 
average 1999-2002 market share for special affordable (underserved 
areas) loans would fall to 15.1 (25.3) percent if manufactured 
housing loans in metropolitan areas were excluded from the market 
definition along with B&C loans. In this case, the market ratio for 
Fannie Mae (Freddie Mac) would be was 0.91 (0.91) for special 
affordable loans, 0.97 (0.96) for low-mod loans, and 0.94 (0.91) for 
underserved area loans.
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    Shifts in performance occurred during 2001 and 2002, the first 
two years under HUD's higher housing goal targets. Table A.20 shows 
that both GSEs improved their overall performance between 1999 and 
2000, but they each fell back a little during the heavy refinancing 
year of 2001. But the primary market (without B&C loans) experienced 
a much larger decline in affordable lending during the refinancing 
wave than did either of the GSEs. Fannie Mae stood out in 2001 
because of its particularly small decline in affordable lending. 
Between 2000 and 2001, Fannie Mae's special affordable lending fell 
by only 0.6 percentage points while Freddie Mac's fell by 2.8 
percentage points and the market's fell by 3.8 percentage points. 
The corresponding percentage point declines for the underserved 
areas category were 1.0 for Fannie Mae, 1.9 for Freddie Mac, and 4.0 
for the market. By the end of 2001, Fannie Mae led Freddie Mac in 
all three goals-qualifying categories, and had erased its gap with 
the low-mod market, but continued to lag the market on the special 
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    During the refinancing wave of 2002, Fannie Mae improved 
slightly on the special affordable and low-mod categories and 
declined slightly on the underserved area category. Freddie Mac 
showed slight improvement on the special affordable and underserved 
area categories and remained about the same on the low-mod category. 
The market showed the same pattern as Fannie Mae. The end result of 
these changes can be seen by considering the market ratios in Table 
A.20. In 2002, special affordable loans accounted for 14.3 percent 
of Fannie Mae's purchases and 14.6 percent of loans originated in 
the non-B&C portion of the conventional conforming market, yielding 
a ``Fannie-Mae-to-market'' ratio of 0.98. Since Fannie Mae's market 
ratio for the special affordable category stood at 0.79 in 2000, 
Fannie Mae substantially closed its gap with the market during 2001 
and 2002. During this period, Fannie Mae also mostly eliminated its 
market gap for the other two goals-qualifying categories. In 2002, 
underserved area loans accounted for 24.0 percent of Fannie Mae's 
purchases and 24.3 percent of loans originated in the non-B&C 
portion of the conventional conforming market, yielding a ``Fannie-
Mae-to-market'' ratio of 0.99, or approximately one. During 2002, 
low-mod loans accounted for 42.2 percent of Fannie Mae's purchases 
and 42.6 percent of loans originated in the market, yielding a 
``Fannie-Mae-to-market'' ratio of 0.99, or approximately one (also 
note that Fannie Mae slightly outperformed the low-mod market during 
2001). Thus, while Fannie Mae continued to lag the market in 2002 on 
each of the three goals-qualifying categories, it was close to the 
market on the low-mod and underserved area categories, in 
particular.
    Freddie Mac significantly lagged the single-family (home 
purchase and refinance loans combined) market during 2001 and 2002. 
In 2002, the ``Freddie-Mac-to-market'' ratios were 0.93 for special 
affordable loans, 0.94 for low-mod loans, and 0.94 for underserved 
area loans.
    Subprime Loans. Table A.14 in Section E.9 showed that the goals-
qualifying shares of the home purchase market did not change much 
when originations by subprime lenders are excluded from the 
analysis; the reason is that subprime lenders operate primarily in 
the refinance market. Therefore, in this section's analysis of the 
total market (including refinance loans), one would expect the 
treatment of subprime lenders to significantly affect the market 
estimates and, indeed, this is the case. For the year 2001, 
excluding subprime loans reduced the goal-qualifying shares of the 
total market as follows: special affordable, from 15.0 to 13.9 
percent; low-mod, from 42.3 to 40.9 percent; and underserved areas, 
from 25.7 to 23.9 percent. (See Table A.19.) Similar declines take 
place in 2002.
    As explained earlier, the comparisons in this appendix have 
defined the market to exclude the B&C portion of the subprime 
market. Industry observers estimate that A-minus loans account for 
about two-thirds of all subprime loans while the more risky B&C 
loans account for the remaining one-third. As explained earlier, 
this analysis reduces the goal-qualifying percentages from the HMDA 
data by half the differentials between (a) the market (unadjusted) 
and (b) the market without the specialized subprime lenders 
identified by Scheessele. As shown in Table A.19, accounting for B&C 
loans in this manner reduces the year 2001 HMDA-reported goal-
qualifying shares of the total (home purchase and refinance) 
conforming market as follows: special affordable, from 15.0 to 14.5 
percent; low-mod, from 42.3 to 41.6 percent; and underserved areas, 
from 25.7 to 24.9 percent. Obviously, the GSEs' performance relative 
to the market will depend on which market definition is used (much 
as it did with the earlier examples of excluding manufactured 
housing loans in metropolitan areas from the market definition). For 
example, defining the conventional conforming market to exclude 
subprime loans, rather than only B&C loans, would increase Fannie 
Mae's 2002 special affordable (underserved area) market ratio from 
0.98 to 1.01 (0.99 to 1.03). Similarly, it would increase Freddie 
Mac's special affordable (underserved area) market ratio from 0.93 
to 0.96 (0.94 to 0.98). For the broader-defined low-mod category, 
redefining the market to exclude subprime loans, rather than only 
B&C loans, would increase Fannie Mae's (Freddie Mac's) market ratio 
from 0.99 to 1.01 (0.94 to 0.96).
    Table A.21 reports GSE purchase data for total (home purchase 
and refinance) loans on an origination-year basis. The ``Freddie 
Mac-to-market'' ratios in Table A.21 show that Freddie Mac has 
lagged the primary market in funding mortgages covered by the 
housing goals. The ``Fannie Mae-to-market'' ratios in Table A.21 
show that except for the low-mod category in 2002 Fannie Mae has 
lagged the primary market in funding home purchase and refinance 
mortgages covered by the housing goals.
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11. GSE Mortgage Purchases in Individual Metropolitan Areas

    While the above analyses, as well as earlier studies, 
concentrate on national-level data, it is also instructive to 
compare the GSEs' purchases of mortgages in individual metropolitan 
areas (MSAs). In this section, the GSEs' purchases of single-family 
owner-occupied home purchase loans are compared to the market in 
individual MSAs. There are three steps. First, goals-qualifying 
percentages for conventional conforming mortgage originations 
(without B&C loans) are computed for each year and for each MSA, 
based on HMDA data. Second, corresponding goals-qualifying 
percentages are computed for each GSE's purchases for each year and 
for each MSA. These two sets of percentages are the same as those 
used in the aggregate analysis discussed in the above sections. 
Third, the ``GSE-to-market'' ratio is then calculated by dividing 
each GSE percentage by the corresponding market percentage. For 
example, if it is calculated that one of the GSEs' purchases of low- 
and moderate-income loans in a particular MSA is 40 percent of their 
overall purchases in that MSA, while 44 percent of all home loans 
(excluding B&C loans) in that MSA qualify as low-mod, then the GSE-
to-market ratio is 40/44 (or 0.91). The goals-qualifying ratios for 
Fannie Mae and Freddie Mac can be compared for each MSA in a similar 
manner.
    Tables A.22, A.23, and A.24 summarize the performance of the 
GSEs within MSAs for 2000, 2001 and 2002 originations of home 
purchase loans. A GSE's performance is determined to be lagging the 
market if the ratio of the GSE housing goal loan purchases to their 
overall purchases is less than 99 percent of that same ratio for the 
market. (The analysis was conducted where the ``lag'' determination 
is made at 98 percent instead of 99 percent and the results showed 
little change.) In the example given in the above paragraph, that 
GSE would be considered lagging the market. Tables A.22 (2000), A.13 
(2001) and A.24 report the number of MSAs in which each GSE under-
performs the market with respect to each of the three housing goal 
categories. The following points can be made from this data:
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    Fannie Mae's improvement between 2000 and 2002 shows up clearly 
in these tables. In 2000, Fannie Mae lagged the market in 296 (89 
percent) of the 331 MSAs in the purchase of underserved area loans; 
this number decreased to 267 (81 percent) MSAs in 2001 and to 248 
(75 percent) MSAs in 2002. Fannie Mae's improvement was even greater 
for special affordable and low-mod loans; in the latter case, Fannie 
Mae lagged the market in 133 (40 percent) MSAs in 2002, compared 
with 269 (81 percent) MSAs in 2000.
    Freddie Mac's improvement between 2000 and 2002 was greater for 
underserved area loans. In 2000, Freddie Mac lagged the market in 
292 (88 percent) of the 331 MSAs in the purchase of underserved area 
loans; this number decreased to 260 (79 percent) MSAs in 2001 and to 
193 (58 percent) MSAs in 2002. Freddie Macs made less improvement on 
the special affordable and low-mod categories; in the former case, 
Freddie Mac lagged the market in 234 (71 percent) MSAs in 2002, 
compared with 282 (85 percent) MSAs in 2000.
    Freddie Mac outperformed Fannie Mae during 2002 in 65 percent of 
the MSAs, even though Freddie Mac's average national performance was 
below Fannie Mae's in that year (see Table A.16 in Section E.9.d); 
this suggests that Freddie Mac performs better in small MSAs, as 
compared with Fannie Mae. This is also consistent with the fact that 
Fannie Mae lagged the market in 75 percent of the MSAs during 2002, 
even though its average national performance was only slightly below 
market performance (see Table A.16); this suggests Fannie Mae does 
better in large MSAs, as compared with small MSAs.
    In its comments on the 2000 Proposed Rule, Fannie Mae raised 
several concerns about HUD's comparisons between Fannie Mae and the 
primary market at the metropolitan statistical area level. 
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 increases public 
understanding of that GSE's performance.

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

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

a. GSEs' Share of Home Purchase Lending

    Table A.25 reports market share estimates derived by combining 
HMDA market data with GSE and FHA loan-level data. To understand 
these estimates, consider the GSE market share percentage of 46 
percent for ``All Home Purchase Loans'' at the bottom of the first 
column in the table. That market share percentage is interpreted as 
follows:

    It is estimated that home loans acquired by Fannie Mae and 
Freddie Mac during the years 1999 to 2002, totaled 46 percent of all 
home loans originated in metropolitan areas during that period.

It should be noted that ``all home loans'' refers to all government 
(FHA and VA) loans plus all conventional loans less than the 
conforming loan limit; in other words, only ``jumbo loans'' are 
excluded from this analysis.\266\ The analysis is restricted to 
metropolitan areas because HMDA data (the source of the market 
estimates) are reliable only for metropolitan areas. B&C 
originations are included in the market data, since the purpose here 
is to gauge the GSEs' role in the overall mortgage market. As 
discussed in Section E.9, excluding B&C loans, or even all subprime 
loans, would not materially affect this analysis of the home loan 
market since subprime loans are mainly for refinance purposes. The 
analysis below frequently combines purchases by Fannie Mae and 
Freddie Mac since previous sections have compared their performance 
relative to each other.
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    \266\ Following the purchase-year approach used in Sections E.9 
and E.10, the GSE purchase data include their acquisitions of 
``prior-year'' as well as ``current-year'' mortgages, while the 
market data include only newly-originated (or ``current year'') 
mortgages.
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    The GSE market share percentage for ``Low-Income Borrowers'' at 
the top of the first column of Table A.25 has a similar 
interpretation:

    It is estimated that home loans for low-income borrowers 
acquired by Fannie Mae and Freddie Mac between 1999 and 2002 totaled 
37 percent of all home loans originated for low-income borrowers in 
metropolitan areas.

    According to the data in Table A.25, the GSEs account for a major 
portion of the market for targeted groups. For example, purchases by 
Fannie Mae and Freddie Mac represented 37 percent of the low-income-
borrower market and 34-37 percent of the markets in low-income, high-
minority, and underserved census tracts. Thus, access to credit in 
these historically underserved markets depends importantly on the 
purchase activities of Fannie Mae and Freddie Mac. However, the data in 
Table A.25 show that the GSEs' role in low-income and minority markets 
is significantly less than their role in the overall home loan market. 
Fannie Mae and Freddie Mac accounted for 46 percent of all home loans 
but only 36 percent of the loans financing properties in underserved 
neighborhoods. Their market share was even lower for loans to African-
American and Hispanic borrowers--29 percent, or 17 percentage points 
less than the GSEs' overall market share of 46 percent.
    An encouraging finding is that the GSEs have increased their 
presence in the affordable lending market during 2001 and 2002, when 
they accounted for 38-45 percent of the loans financing properties in 
low-income, high-minority, and underserved neighborhoods and for 32-34 
percent of loans for African-American and Hispanic borrowers. These 
market share figures for the GSEs are much higher than their 
performance during the two earlier years, 1999 and 2000.
    To provide additional perspective, Table A.25 also reports market 
share estimates for FHA.\267\ During the 1999-2002 period, FHA's 
overall market share was less than half of the GSEs' market share, as 
FHA insured only 18 percent of all home mortgages originated in 
metropolitan areas. However, FHA's share of the underserved segments of 
the market are not far below the GSEs' share, and in one case actually 
higher by a significant margin. For instance, between 1999 and 2001, 
FHA insured 26 percent of all mortgages originated in low-income census 
tracts, which was only eight percentage points less than the GSEs' 
market share of 34 percent in low-income census tracts. FHA's share of 
the market was particularly high for African-American and Hispanic 
borrowers, as FHA insured 33 percent of all home loans originated for 
these borrowers between 1999 and 2002--a figure four percentage points 
higher than the GSEs' share of 29 percent.\268\ Thus, during the 1999-
2002 period, FHA's overall market share was only two-fifths (39 
percent) of the GSEs' combined market share, but its share of the 
market for loans to African Americans and Hispanics was 14 percent 
larger than the GSEs' share of that market.
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    \267\ As explained in Section E.7, the GSEs' affordable lending 
performance is evaluated relative to the conventional conforming 
market, as required by Congress in the 1992 GSE Act that established 
the housing goals. However, it is insightful to examine their 
overall role in the mortgage market and to contrast them with other 
major sectors of the market such as FHA. There is no intention here 
to imply that the GSEs should purchase the same types of loans that 
FHA insures.
    \268\ As explained in the notes to Table A.25, HMDA data are the 
source of the market figures. It is assumed that HMDA data cover 85 
percent of all mortgage originations in metropolitan areas. If HMDA 
data covered higher (lower) percentages of market loans, then the 
market shares for both the GSEs and FHA would be lower (higher).
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    The data for the two recent years (2001 and 2002) indicate a larger 
market role for Fannie Mae and Freddie Mac relative to FHA. While the 
GSEs continued to have a much larger share of the overall market than 
FHA (48-50 percent for the GSEs versus 14-17 percent for FHA), their 
share of home loans for African Americans and Hispanics jumped to 32-34 
percent during 2001 and 2002, which was higher than the percentage 
share for FHA (27-32 percent). The differentials in market share 
between FHA and the GSEs on the other affordable lending categories 
listed in Table A.25 were lower in 2001 and 2002 than in earlier years.
b. The GSEs' Share of the Total First-Time Homebuyer Market
    This section summarizes two recent analyses of mortgage lending to 
first-time homebuyers; these two studies examine the total mortgage 
market, including both government and conventional loans originated 
throughout the U.S. (i.e., in both metropolitan areas and non-
metropolitan areas). Section E.12.c will summarize a third study of 
first-time homebuyers that focuses on the conventional conforming 
market. All three studies are market share studies that examine the 
GSEs' role in the first-time homebuyer market.
    First, a study by Bunce concluded that the GSEs have played a 
particularly small role in funding minority first-time homebuyers.\269\ 
Because HMDA does not require lenders to report information on first-
time homebuyers, Bunce used data from the American Housing Survey to 
estimate the number of first-time homebuyers in the market. Using 
American Housing Survey data on home purchases from 1997 to 1999, Bunce 
estimated that the GSEs' share of the market for first-time African-
American and Hispanic homebuyers was only 10-11 percent, or less than 
one-third of their share (36 percent) of all home purchases during that 
period. FHA's share of this market was 36 percent, or twice its share 
(18 percent) of all home purchases.\270\ These data highlight the small 
role that the GSEs have played in the important market for minority 
first-time homebuyers.
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    \269\ See Harold L. Bunce, The GSEs' Funding of Affordable 
Loans: A 2000 Update, Housing Finance Working Paper No. HF-013, 
Office of Policy Development and Research, HUD, April 2002.
    \270\ Bunce explains numerous assumptions and caveats related to 
combining American Housing Survey data on homebuyers with FHA and 
GSE data on mortgages. For example, the American Housing Survey 
(AHS) data used by Bunce included both financed home purchases and 
homes purchased with cash. If only financed home purchases were 
used, the market shares of both FHA and the GSEs would have been 
slightly higher (although the various patterns would have remained 
the same). The AHS defines first-time homebuyers as buyers who have 
never owned a home, while FHA and the GSEs define a first-time 
homebuyer more expansively as buyers who have not owned a home in 
the past three years. If it were possible to re-define the FHA and 
GSE data to be consistent with the AHS data, the FHA and GSE first-
time homebuyer shares would be lower (to an unknown degree). For 
additional caveats with the AHS data, also see David A. 
Vandenbroucke, Sue G. Neal, and Harold L. Bunce, ``First-Time 
Homebuyers: Trends from the American Housing Survey,'' November 
2001, U.S. Housing Market Condition, a quarterly publication of the 
Office of Policy Development and Research at HUD. In some years, 
home purchases as measured by the AHS declined while home purchases 
as measured by other data sources (e.g., HMDA) increased. In 
addition, the AHS home purchase data for separate minority groups 
(e.g., African-Americans, Hispanics) sometimes exhibited shifts 
inconsistent with other sources.
---------------------------------------------------------------------------

    Bunce, Neal and Vandenbroucke (BNV) recently updated through 2001 
the study by Bunce. In addition, BNV developed an improved methodology 
that combined industry, HMDA and AHS data to estimate the number of 
first-time homebuyers (by race and ethnicity) in the mortgage market 
during the years 1996 to 2001.\271\ BNV's analysis includes the total 
mortgage

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market, that is, the government, conventional conforming, and jumbo 
sectors of the mortgage market.
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    \271\ BNV's methodology for estimating first-time borrowers 
consists of three steps: (1) Estimate the total number of home 
purchase loans originated during a particular year using a mortgage 
market model that they develop; (2) disaggregate the home purchase 
loans in step (1) into racial and ethnic groups using HMDA data for 
metropolitan areas; and (3) for each racial and ethnic group in step 
(2), estimate the number of first-time homebuyers using mortgage and 
first-time homebuyer information from the American Housing Survey.
---------------------------------------------------------------------------

    Table A.26 presents the key market shares estimated by BNV for the 
GSEs and FHA. The first figure (40.7) in Table A.26 is interpreted as 
follows: purchases of home loans by Fannie Mae and Freddie Mac totaled 
40.7 percent of all home loans financed between 1996 and 2001. Going 
down the first column shows that the GSEs' share of the first-time 
homebuyer market was 24.5 percent during the 1996-to-2001--a market 
share significantly lower than their overall market share of 40.7 
percent.
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    FHA's greater focus on first-time homebuyers is also reflected in 
the market share data reported in Table A.26. While FHA insured only 
16.6 percent of all home loans originated between 1996 and 2001, it 
insured 30.9 percent of all first-time-homebuyer loans during that 
period. The GSEs, on the other hand, accounted for a larger share (40.7 
percent) of the overall home purchase market but a smaller share (24.5 
percent) of the first-time homebuyer market.
    Table A.26 also reports home purchase and first-time homebuyer 
information for minorities. During the more recent 1999-to-2001 period, 
the GSEs' loan purchases represented 41.5 percent of all home mortgages 
but only 24.3 percent of home loans for African-American and Hispanic 
families, and just 14.3 percent of home loans for African-American and 
Hispanic first-time homebuyers. During this period, the GSEs' role in 
the market for first-time African-American and Hispanic homebuyers was 
only one-third of their role in the overall home loan market (14.3 
percent versus 41.5 percent).
    FHA, on the other hand, accounted for a much larger share of the 
minority first-time homebuyer market than it did of the overall 
homebuyer market. Between 1999 and 2001, FHA insured 46.5 percent of 
all loans for African-American and Hispanic first-time homebuyers--a 
market share that was almost three times its overall market share of 
16.4 percent.\272\ While FHA's market share was two-fifths of the GSEs' 
share of the overall home purchase market (16.4 percent versus 41.5 
percent), FHA's market share was over three times the GSEs' share of 
the market for first-time African-American and Hispanic homebuyers 
(46.5 percent versus 14.3 percent). This finding that the GSEs have 
played a relatively minor role in the first-time minority market is 
similar to the conclusion reached by the Fed researchers (see below) 
and Bunce (2002) that the GSEs have provided little credit support to 
this underserved borrower group.
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    \272\ See Bunce, Neal, and Vandenbroucke, op. cit., for 
comparisons of various estimates of the market shares for FHA and 
the GSEs using different data bases and estimation methods. One can 
compare (a) the 1999-2001 market shares for FHA and the conventional 
conforming market in metropolitan areas calculated using the same 
methodology as Table A.25 with (b) the 1999-2001 market share 
estimates reported in Table A.25 for the entire mortgage market 
(including jumbo loans and covering non-metropolitan areas as well 
as metropolitan areas). The results are strikingly consistent. For 
the 1999-to-2001 period, the FHA share of the overall (African 
American and Hispanic) home loan market is estimated to be 19.0 
percent (35.8 percent) under (a) versus 16.4 percent (31.2 percent) 
under (b). Lower percentage shares are expected for (b) because (b) 
includes jumbo loans. For the same period, the GSE share of the 
overall (African American and Hispanic) home loan market is 
estimated to be 46.0 percent (25-28 percent) under (a) versus 41.5 
percent (24.3 percent) under (b).
---------------------------------------------------------------------------

    The results reported in Table A.26 for the year 2001 suggest some 
optimism concerning the GSEs' role in the first-time homebuyer market. 
As explained in earlier sections, both GSEs, but particularly Fannie 
Mae, improved their affordable lending performance during 2001, at a 
time when the overall market's performance was slightly declining. This 
improvement is reflected in the higher first-time market shares for the 
GSEs during the year 2001, compared with the two previous years, 1999 
and 2000 (not reported). The GSEs' share of the market for first-time 
African-American and Hispanic homebuyers jumped from about 11-12 
percent during 1999 and 2000 to 19.7 percent in 2001. Fannie Mae's 
share of this market almost doubled during this period, rising from 7.0 
percent in 1999 to 12.6 percent in 2001. Thus, while the GSEs continue 
to play a relatively small role in the minority first-time homebuyer 
market, during 2001 they improved their performance in this area.\273\
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    \273\ For other analyses of the GSEs' market role, see the 
following study by economists at the Federal Reserve Board: Glenn B. 
Canner, Wayne Passmore, and Brian J. Surette, ``Distribution of 
Credit Risk among Providers of Mortgages to Lower-Income and 
Minority Homebuyers'' in Federal Reserve Bulletin, 82(12): 1077-
1102, December, 1996. This study considered several characteristics 
of the GSEs' loan purchases (such as amount of downpayment) and 
concluded that the GSEs have played a minimal role in providing 
credit support for underserved borrowers.
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c. The GSEs' Share of the Conventional Conforming, First-Time Homebuyer 
Market
    Bunce and Gardner (2004) recently conducted an analysis of first-
time homebuyers for the conventional conforming market. The Bunce and 
Gardner analysis used a similar methodology to the study by Bunce, 
Neal, and Vandenbroucke of first-time homebuyers in the total mortgage 
market. Bunce and Gardner restricted their analysis to the funding of 
first-time homebuyers in the conventional conforming market, which is 
the market where Fannie Mae and Freddie Mac operate. Their market share 
results are summarized in Table A.27.
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    Between 1999 and 2001, the GSEs' purchases accounted for 56.6 
percent of all home loans originated in the conventional conforming 
market of both metropolitan areas and non-metropolitan areas. In other 
words, Fannie Mae and Freddie Mac funded almost three out of every five 
homebuyers entering the conventional conforming market between 1999 and 
2001. Their purchases of first-time homebuyer loans, on the other hand, 
accounted for only 39.8 percent of all first-time homebuyer loans 
originated in that market. Thus, while the GSEs funded approximately 
two out of every five first-time homebuyers entering the conventional 
conforming market, their market share (39.8 percent) for first-time 
homebuyers was only 70 percent of their market share (56.6 percent) for 
all home buyers.
    As shown in Table A.27, the GSEs have funded an even lower share of 
the minority first-time homebuyer market. Between 1999 and 2001, the 
GSEs purchases of African-American and Hispanic first-time homebuyer 
loans represented 30.9 percent of the conventional conforming market 
for these loans. Thus, while the GSEs have accounted for 56.6 percent 
of all home loans in the conventional conforming market, they have 
accounted for only 30.9 percent of loans originated in that market for 
African-American and Hispanic first-time homebuyers.
    The market share data in Table A.27 show some slight differences 
between the Freddie Mac and Fannie Mae in serving minority first-time 
homebuyers. During the 1999-to-2001 period, Freddie Mac's share (11.9 
percent) of the African-American and Hispanic first-time homebuyer 
market was only one-half of its share (24.0 percent) of the home loan 
market. On the other hand, Fannie Mae's share (19.0 percent) of the 
African-American and Hispanic first-time homebuyer market was almost 60 
percent of its share (32.5 percent) of the home loan market. Thus, 
while Fannie Mae performance in serving minority first-time homebuyers 
has been poor, it has been better than Freddie Mac's. This difference 
in performance between Fannie Mae and Freddie Mac was also seen in the 
portfolio percentages reported earlier in Table A.17. Loans for 
African-American and Hispanic first-time homebuyers accounted for 6.9 
percent of Fannie Mae's purchases of home loans between 1999 and 2001, 
a figure higher than Freddie Mac percentage of 5.3 percent. Loans for 
African-American and Hispanic first-time homebuyers accounted for 10.2 
percent of all home loans originated in the conventional conforming 
market.
d. Downpayments on Loans Purchased by the GSEs
    The level of downpayment can be an important obstacle to young 
families seeking their first homes. Examining the downpayment 
characteristics of the mortgages purchased by the GSEs might help 
explain why they have played a rather limited role in the first-time 
homebuyer market.
    Table A.28 reports the loan-to-value (LTV) distribution of home 
purchase mortgages acquired by the GSEs between 1997 and 2002. In Table 
A.29, LTV data are provided for the GSEs' purchases of home loans that 
qualify for the three housing goals'special affordable, low-mod, and 
underserved areas. Three points stand out.

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    First, the GSEs (and particularly Fannie Mae) have recently 
increased their purchases of home loans with low downpayments. After 
remaining about 4 percent of Fannie Mae's purchases between 1997 and 
2000, over-95-percent-LTV loans (or less-than-five-percent downpayment 
loans) jumped to 7.1 percent during 2001 and 7.7 percent in 2002. It is 
interesting that this jump in less-than-five-percent downpayment loans 
occurred in the same years that Fannie Mae improved its purchases of 
loans for low-income homebuyers, as discussed in earlier sections. As a 
share of Freddie Mac's purchases, over-95-percent-LTV loans increased 
from 1.1 percent in 1997 to 5.9 percent in 2000, before falling to 4.3 
percent in 2001 and 4.8 percent in 2002. If the low-downpayment 
definition is expanded to ten percent (i.e., over-90-percent-LTV 
loans), Freddie Mac had about the same percentage (25 percent) of low-
downpayment loans during 2001 as Fannie Mae. In fact, under the more 
expansive definition, Freddie Mac had the same share of over-90-
percent-LTV loans in 2001 as it did in 1997 (about 25 percent), while 
Fannie Mae exhibited only a modest increase in the share of its 
purchases with low downpayments (from 23.2 percent in 1997 to 25.4 
percent in 2001). The share of over-90-percent-LTV loans in Freddie 
Mac's purchases fell sharply from 25.0 percent in 2001 to 21.9 percent 
in 2002, while the share in Fannie Mae's purchases fell more modestly 
from 25.4 percent in 2001 to 24.2 percent in 2002.
    Second, loans that qualify for the housing goals have lower 
downpayments than non-qualifying loans. In 2001 and 2002, over-95-
percent-LTV loans accounted for about 15 percent of Fannie Mae's 
purchases of special affordable loans, 13 percent of low-mod loans, and 
12 percent of underserved area loans, compared with about 7.5 percent 
of Fannie Mae's purchases of all home loans. (See Table A.29.) These 
low-downpayment shares for 2001 and 2002 were almost double those for 
2000 when over-95-percent-LTV loans accounted for 8.4 percent of Fannie 
Mae's purchases of special affordable loans and about 7 percent of its 
purchases of low-mod and underserved area loans. Fannie Mae's low-
downpayment shares during 2001 were higher than Freddie Mac's shares of 
12.3 percent for special affordable loans and about 8 percent for low-
mod and underserved area loans. Between 2001 and 2002, Freddie Mac's 
over-95-percent-LTV shares fell sharply to 4-5 percent for the three 
housing goal categories, while Fannie Mae's shares remained in the 12-
15 percent range. Under the more expansive, over-90-percent-LTV 
definition, almost one-third of Fannie Mae's goals-qualifying purchases 
during 2001 would be considered low downpayment, as would a slightly 
smaller percentage of Freddie Mac's purchases. However, during 2002, 
Freddie Mac's over-90-percent-LTV shares for the goals-qualifying loans 
fell to 23-24 percent.
    Third, a noticeable pattern among goals-qualifying loans purchased 
by the GSEs is the predominance of loans with high downpayments. For 
example, 55.9 percent of special affordable home loans purchased by 
Freddie Mac during 2002 had a downpayment of at least 20 percent, a 
percentage not much lower than the high-downpayment share (59.1 
percent) of all Freddie Mac's home loan purchases. Similarly, 46.8 
percent of the home loans purchased by Fannie Mae in underserved areas 
during 2002 had a 20 percent or higher downpayment, compared with 53.0 
percent of all home loans purchased by Fannie Mae.
    Thus, the data in Tables A.28 and A.29 show a preponderance of high 
downpayment loans, even among lower-income borrowers who qualify for 
the housing goals. The past focus of the GSEs on high-downpayment loans 
provides some insight into a study by staff at the Federal Reserve 
Board who found that the GSEs have offered little credit support to the 
lower end of the mortgage market.\274\ The fact that approximately half 
of the goals-qualifying loans purchased by the GSEs have a downpayment 
of over 20 percent is also consistent with findings reported earlier 
concerning the GSEs' minimal service to first-time homebuyers, who 
experience the most problems raising cash for a downpayment. On the 
other hand, the recent experience of Fannie Mae suggests that 
purchasing low-downpayment loans may be one technique for reaching out 
and funding low-income and minority families who are seeking to buy 
their first home.
---------------------------------------------------------------------------

    \274\ Canner, et al., op. cit.
---------------------------------------------------------------------------

13. Other Studies of the GSEs Performance Relative to the Market

    This section summarizes briefly the main findings from other 
studies of the GSEs' affordable housing performance. These include 
studies by the HUD and the GSEs as well as studies by academics and 
research organizations.
    Freeman and Galster Study.\275\ A recent study by Lance Freeman and 
George Galster uses econometric analysis to test whether the 
Government-Sponsored Enterprises (GSEs) Fannie Mae and Freddie Mac 
purchases of home mortgages in neighborhoods traditionally underserved 
by financial institutions stimulate housing market activity in those 
neighborhoods. Specifically, this study analyzes data of single-family 
home sales volumes and prices of mortgages originated from 1993-1999 in 
Cleveland, OH.
---------------------------------------------------------------------------

    \275\ The Impact of Secondary Mortgage Market and GSE Purchases 
on Underserved Neighborhood Housing Markets: Final Report to HUD. 
July 2002.
---------------------------------------------------------------------------

    The study concludes that aggressive secondary market purchasing 
behavior by non-GSE entities stimulated sales volumes and prices of 
homes in low-income and predominantly minority-occupied neighborhoods 
of Cleveland. The study results also showed a positive relationship 
between home transaction activity and the actions of the secondary 
mortgage market, and concludes that the secondary mortgage market (and 
the non-GSE sector in particular) purchases of mortgages had a positive 
effect on the number of sales transactions one year later. However, the 
study also concludes that although non-GSE purchases of non-home 
purchase mortgages appeared to boost prices one and two years later, no 
consistent impacts of purchasing rates on sales prices could be 
observed. In addition, there was no robust evidence that GSE purchasing 
rates were positively associated with single-family home transactions 
volumes or sales prices during any periods.
    Urban Institute Rural Markets Study.\276\ A study by Jeanette 
Bradley, Noah Sawyer, and Kenneth Temkin uses both quantitative and 
qualitative data to explore the issue of GSE service to rural areas. 
The study first summarizes the existing research on rural lending and 
GSE service to rural areas. It then reviews the current underwriting 
guidelines of Fannie Mae, Freddie Mac, the USDA Rural Housing Service, 
and Farmer Mac, focusing on issues relevant to rural underwriting. The 
GSE public-use database is used to analyze GSE non-metropolitan loan 
purchasing patterns from 1993-2000. Finally, the study presents the 
results of a series of discussions conducted with key national industry 
and lender experts and local experts in three rural sites in south-
central Indiana, southwestern New Mexico and southern New Hampshire 
chosen for the diversity of their region, population, economic 
structures, and housing markets.
---------------------------------------------------------------------------

    \276\ GSE Service to Rural Areas, 2002.
---------------------------------------------------------------------------

    The authors of the study conclude that while Fannie Mae and Freddie 
Mac have increased their lending to rural areas since 1993, their non-
metropolitan loan purchases still lag behind their role

[[Page 24357]]

in metropolitan loan purchases, particularly in regard to the 
percentage of affordable loans. From the discussions with experts, the 
authors of the study make the following policy recommendations: 
underserved populations and rural areas should be specifically targeted 
at the census-tract level; HUD should set manufactured housing goals; 
HUD should consider implementing a survey of small rural lenders or 
setting up an advisory group of small rural lenders in order to 
determine their suggestions for creating stronger relationships between 
the GSEs and rural lenders with the goal of increasing GSE non-
metropolitan purchase rates.
    Urban Institute GSE Impacts Study.\277\ A report by Thomas 
Thibodeau, Brent Ambrose, and Kenneth Temkin analyzes the extent to 
which the GSEs' responses to The Federal Housing Enterprises Financial 
Safety and Soundness Act's (FHEFSSA) affordable housing goals have had 
their intended effect of making low- and moderate-income families 
better off. Specifically the report examines several methodologies 
determining that the conceptual model created by Van Order in 1996 
\278\ provided the most complete description of how the primary and 
secondary markets interact. This model was then applied in a narrow 
scope to capital market outcomes which included GSE market shares and 
effective borrowing costs, and housing market outcomes that include 
low- and moderate-income homeownership rates. Finally, metropolitan 
American Housing Survey (AHS) data for eight cities were used to 
conduct empirical analyses of the two categories of outcomes. These 
cities included areas surveyed in 1992, the year before HUD adopted the 
affordable housing goals, to provide the baseline for the analysis. 
Four metropolitan areas were surveyed in 1992 and again in 1996: 
Cleveland, Indianapolis, Memphis and Oklahoma City. Four cities were 
surveyed in 1992 and again in 1998: Birmingham, Norfolk, Providence and 
Salt Lake City.
---------------------------------------------------------------------------

    \277\ An Analysis of the Effects of the GSE Affordable Goals on 
Low- and Moderate-Income Families, 2001.
    \278\ Van Order, Robert. 1996. ``Discrimination and the 
Secondary Mortgage Market.'' In John Goering and Ronald Wienk, eds. 
Mortgage Discrimination, Race, and Federal Policy. The Urban 
Institute Press, Washington, DC: 335-363.
---------------------------------------------------------------------------

    The study's empirical analysis suggests that the GSE affordable 
goals have helped to make homeownership more attainable for target 
families. The assessment of the effects of the affordable goals on 
capital markets showed that the GSE share of the conventional 
conforming market has increased, especially for lower income borrowers 
and neighborhoods. The study also concludes that the affordable housing 
goals have an impact on the purchase decisions of Fannie Mae and 
Freddie Mac. The study also finds that interest rates are lower in 
markets in which Fannie Mae and Freddie Mac purchase a higher 
proportion of conventional loans. Finally, the study's analysis shows 
that overall lending volume in a metropolitan area increases when the 
GSEs purchase seasoned loans.
    Specifically, that homeownership rates increased at a faster rate 
for low-income families when compared to all families, and that in a 
subset of MSAs, minority homeownership rates also grew faster when 
compared to overall homeownership changes in those MSAs.
    Finally, the affordable housing goal effects were examined for 80 
MSAs in relation to the homeownership rate changes between 1991 and 
1997. The study found that the GSEs, by purchasing loans originated to 
low-income families, helped to reduce the disparity between 
homeownership rates for lower and higher income families, suggesting 
that the liquidity created when the GSEs purchase loans originated to 
low-income families is recycled into more lending targeted to lower 
income homebuyers.
    The authors of the study qualify their results by stating that they 
are based on available data that does not provide the level of detail 
necessary to conduct a fully controlled national assessment.
    Williams and Bond Study.\279\ Richard Williams and Carolyn Bond 
examine GSE leadership of the mortgage finance industry in making 
credit available for low- and moderate-income families. Specifically, 
it asks if the GSEs are doing relatively more of their business with 
underserved markets than other financial institutions, and whether the 
GSEs' leadership helps to narrow the gap in home mortgage lending that 
exists between served and underserved markets. The study uses HMDA data 
for metropolitan areas and the Public Use Data Base at HUD for 
compilations of GSE data sets for the entire nation (GSE PUDB File B) 
to conduct descriptive and multivariate analyses of nationwide lending 
between 1993 and 2000. Additionally, separate analyses are conducted 
that include and exclude loans from subprime and manufactured housing 
lenders.
---------------------------------------------------------------------------

    \279\ Are the GSEs Leading, and if So Do They Have Any 
Followers? An Analysis of the GSEs' Impact on Home Purchase Lending 
to Underserved Markets During the 1990s. University of Notre Dame 
Working Paper and Technical Series Number 2003-2. 2002
---------------------------------------------------------------------------

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

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

    The 1996 Property Owners and Managers Survey reported that 49 
percent of rental units are found in the ``mom and pop shops'' of the 
rental market''single-family'' rental properties, containing 1-4 units. 
These small properties are largely individually-owned and managed, and 
in many cases the owner-managers live in one of the units in the 
property. They include many properties in older cities, in need of 
financing for rehabilitation. Single-family rental units play an 
especially important role in lower-income housing, over half of such 
units are affordable to very low-income families.
    There is not, however, a strong secondary market for single-family 
rental mortgages. While single-family rental properties comprise a 
large segment of the rental stock for lower-income families, they make 
up a small portion of the GSEs' business. In 2001, the GSEs purchased 
$84 billion in mortgages for such properties, but this represented 6 
percent of the total dollar volume of the enterprises' 2002 business 
and 10 percent of total single-family units financed by each GSE. It 
follows that since single-family rentals make up such a small part of 
the GSEs business, they have not penetrated the single-family rental 
market to the same degree that they have penetrated the owner-occupant 
market. Table A.30 in Section G below shows that between 1999 and 2002, 
the GSEs financed 57 percent of

[[Page 24358]]

owner-occupied dwelling units in the conventional conforming market, 
but only 27 percent of single-family rental units.
    There are a number of factors that have limited the development of 
the secondary market for single-family rental property mortgages thus 
explaining the lack of penetration by the GSEs. Little is collectively 
known about these properties as a result of the wide spatial dispersion 
of properties and owners, as well as a wide diversity of 
characteristics across properties and individuality of owners. This 
makes it difficult for lenders to properly evaluate the probability of 
default and severity of loss for these properties.
    Single-family rental properties could be important for the GSEs 
housing goals, especially for meeting the needs of lower-income 
families. In 2002 around 70 percent of single-family rental units 
qualified for the Low- and Moderate-Income Goals, compared with 40 
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 for10 percent of the 
total units (single-family and multifamily) financed by the GSEs.
    Given the large size of this market, the high percentage of these 
units which qualify for the GSEs' housing goals, and the weakness of 
the secondary market for mortgages on these properties, an enhanced 
presence by Fannie Mae and Freddie Mac in the single-family rental 
mortgage market would seem warranted.\280\ Single-family rental housing 
is an important part of the housing stock because it is an important 
source of housing for lower-income households.
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    \280\ 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).
---------------------------------------------------------------------------

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

    The Department estimates that dwelling units serving low- and 
moderate-income families will account for 51-57 percent of total units 
financed in the overall conventional conforming mortgage market during 
2005-2008, the period for which the Low- and Moderate-Income Housing 
Goal is proposed. The market estimates exclude B&C loans and allow for 
much more adverse economic and market affordability conditions than 
have existed recently. Between 1999 and 2002 the low-mod market 
averaged about 57 percent. 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].''\281\
---------------------------------------------------------------------------

    \281\ Senate Report 102-282, May 15, 1992, p. 35.
---------------------------------------------------------------------------

    The Department and independent researchers have published numerous 
studies examining whether or not the GSEs have been leading the single-
family market in terms of their affordable lending performance. This 
research, which is summarized in Section E, concludes that the GSEs 
have generally lagged behind primary lenders in funding first-time 
homebuyers, lower-income borrowers and underserved communities. As 
required by FHEFSSA, the Department has produced estimates of the 
portion of the total (single-family and multifamily) mortgage market 
that qualifies for each of the three housing goals (see Appendix D). 
Congress intended that the Department use these market estimates as one 
factor in setting the percentage target for each of the housing goals. 
The Department's estimate for the size of the Low- and Moderate-Income 
market is 51-57 percent, which is higher than the GSEs' performance on 
that goal.
    This section provides another perspective on the GSEs' performance 
by examining the share of the total conventional conforming mortgage 
market and the share of the goal-qualifying markets (low-mod, special 
affordable, and underserved areas) accounted for by the GSEs' 
purchases. This analysis, which is conducted by product type (single-
family owner, single-family rental, and multifamily), shows the 
relative importance of the GSEs in each of the goal-qualifying markets.

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

    Tables A.30 and A.31 compare GSE mortgage purchases with HUD's 
estimates of the numbers of units financed in the conventional 
conforming market. Table A.30 presents aggregate data for 1999-2002 
while Table A.31 presents more summary market share data for individual 
years 2000 and 2002.\282\ HUD estimates that there were 48,270,415 
owner and rental units financed by new conventional conforming 
mortgages between 1999 and 2002. Fannie Mae's and Freddie Mac's 
mortgage purchases financed 23,580,594 of these dwelling units, or 49 
percent of all dwelling units financed. As shown in Table A.30, the 
GSEs have played a smaller role in the goals-qualifying markets than 
they have played in the overall market. Between 1999 and 2002, new 
mortgages were originated for 27,158,020 dwelling units that qualified 
for the Low- and Moderate-Income Goal; the GSEs low-mod purchases 
financed 11,408,692 dwelling units, or 42 percent of the low-mod 
market. Similarly, the GSEs' purchases accounted for 41 percent of the 
underserved areas market, but only 35 percent of the special affordable 
market. Obviously, the GSEs have not been leading the industry in 
financing units that qualify for the three housing goals. They need to 
improve their performance and it appears that there is ample room in 
the non-GSE portions of the goals-qualifying markets for them to do so. 
For instance, the GSEs were not involved in almost two-thirds of the 
special affordable market during the 1999-to-2002 period.
---------------------------------------------------------------------------

    \282\ Tables A.30 and A.31 examine GSE purchases on a ``going 
forward basis by origination year.'' Specifically, it considers GSE 
purchases of: (a) 1999 mortgage originations during 1999 and 2000; 
(b) 2000 originations during 2000 and 2002; and (c) 2002 
originations during 2002 (and 2002 will be added when those data 
become available in March 2003). In other words, this analysis looks 
at the GSEs' purchases of a particular origination year cohort over 
a two-year period. This approach contrasts with the approach that 
examines GSE purchases on a ``backward looking basis by purchase 
year'', for example, GSE purchases during 1999 of both new 1999 
originations and originations during previous years (the latter 
called ``prior-year'' or seasoned loans). Either approach is a valid 
method for examining GSE purchases; in fact, when analyzing 
aggregated data such as the combined 1999-2002 data in Table A.30, 
the two approaches yield somewhat similar results. HUD's methodology 
for deriving the market estimates is explained in Appendix D. B&C 
loans have been excluded from the market estimates in Tables A.30 
and A.31.
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    While the GSEs are free to meet the Department's goals in any 
manner that they deem appropriate, it is useful to consider their 
performance relative to the industry by property type. The GSEs 
accounted for 57 percent of the single-family owner market but only 30 
percent of the multifamily market and 27 percent of the single-family 
rental market (or a combined 29 percent share of the rental market).
    Single-family Owner Market. As stated in the 2000 Rule, the single-
family-owner market is the bread-and-butter of the GSEs' business, and 
based on the financial and other factors discussed below, the GSEs 
clearly have the ability to lead the primary market in providing credit 
for low- and moderate-income owners of single-family properties. 
However, the GSEs have historically lagged behind the market in funding 
single-family-owner loans that qualify for the housing goals and, as 
discussed in Section E, they have played a rather small role in funding 
minority first-time homebuyers. The market share data reported in Table 
A.30 for the single-family-owner market tell the same story. The GSEs' 
purchases of single-family-owner loans represented 57 percent of all 
single-family-owner loans originated between 1999 and 2002, compared 
with 53 percent of the low-mod loans that were originated, 52 percent 
of underserved area loans, and 49 percent of the special affordable 
loans.
    The data in Table A.31 indicate the GSEs' growing market share 
during the heavy refinance years of 2001 and 2002. For example, the 
GSEs accounted for 62 percent of the overall single-family-owner market 
that year, and 56-58 percent of the markets covered by the three 
housing goal categories. While this improvement is an encouraging 
trend, there are ample opportunities for the GSEs to continue their 
improvement. Almost one-half of the goals-qualifying loans originated 
during 2002 remained available to the GSEs to purchase; there are 
clearly affordable loans being originated that the GSEs can purchase. 
Furthermore, the GSEs' purchases under the housing goals are not 
limited to new mortgages that are originated in the current calendar 
year. The GSEs can purchase loans from the substantial, existing stock 
of affordable loans held in lenders' portfolios, after these loans have 
seasoned and the GSEs have had the opportunity to observe their payment 
performance. In fact, based on Fannie Mae's recent experience, the 
purchase of seasoned loans appears to be one effective strategy for 
purchasing goals-qualifying loans.
    Single-family Rental Market. Single-family rental housing is a 
major source of low-income housing. As discussed in Appendix D, data on 
the size of the primary market for mortgages on these properties is 
limited, but available information indicate that the GSEs are much less 
active in this market than in the single-family owner market. HUD 
estimates that GSE purchases between 1999 and 2002 totaled only 27 
percent of all newly-mortgaged single-family rental units that were 
affordable to low- and moderate-income families.
    As explained in the 2000 Rule, many of these properties are ``mom-
and-pop'' operations, which may not follow financing procedures 
consistent with the GSEs' guidelines. Much of the financing needed in 
this area is for rehabilitation loans on 2-4 unit properties in older 
areas, a market in which the GSEs' have not played a major role. 
However, this sector could certainly benefit from an enhanced role by 
the GSEs, and the data in Table A.30 indicate that there is room for 
such an enhanced role, as approximately three-fourths of this market 
remains for the GSEs to enter.
    Multifamily Market. Fannie Mae is the largest single source of 
multifamily finance in the United States, and Freddie Mac has made a 
solid reentry into this market over the last nine years. However, there 
are a number of measures by which the GSEs lag the multifamily market. 
For example, the share of GSE resources committed to the multifamily 
purchases falls short of the multifamily proportion prevailing in the 
overall mortgage market. HUD estimates that newly-mortgaged units in 
multifamily properties represented almost 14 percent of all (single-
family and multifamily) dwelling units financed between 1999 and 
2002.\283\ As shown in Table A.30, multifamily acquisitions represented 
9 percent of dwelling units financed by the GSEs between 1999 and 2002.
---------------------------------------------------------------------------

    \283\ Based on Table A.30, multifamily properties represented 
14.5 percent of total units financed between 1999 and 2002 (obtained 
by dividing 7,018,044 multifamily units by 48,270,415 ``Total 
Market'' units). Increasing the single-family-owner number in Table 
A.30 by 2,817,258 to account for excluded B&C mortgages increases 
the ``Total Market'' number to 51,087,673 which produces a 
multifamily share of 13.7 percent. See Appendix D for discussion of 
the B&C market.
---------------------------------------------------------------------------

    The GSEs' role in the multifamily market is significantly smaller 
than in single-family. As shown in Table A.30, GSE purchases have 
accounted for 30 percent of newly financed multifamily units between 
1999 and 2002--a market share much lower than their 57 percent share of 
the single-family-owner market. Stated in terms of portfolio shares, 
single-family-owner loans accounted for 83 percent of all dwelling 
units financed by the GSEs during this period, versus 73 percent of all 
units financed in the conventional conforming market.
    While it is recognized that the GSEs have been increasing their 
multifamily purchases, a further enlargement of their role in the 
multifamily market seems feasible and appropriate, particularly in the 
affordable (lower rent) end of the market. As noted in Section D.3, 
market participants believe that the GSEs have been conservative in 
their approaches to affordable multifamily lending and 
underwriting.\284\ Certainly the GSEs face a number of challenges in 
better meeting the needs of the affordable multifamily market. For 
example, thrifts and other depository institutions may sometimes retain 
their best loans in portfolio, and the resulting information 
asymmetries may act as an impediment to expanded secondary market 
transaction volume.\285\ However, the GSEs have demonstrated that they 
have the depth of expertise and the financial resources to devise 
innovative solutions to problems in the multifamily market. The GSEs 
can build on their recent records of increased multifamily lending and 
innovative products to make further in-roads into the affordable 
market. As explained in Section D.3, the GSEs have the expertise and 
market presence to push simultaneously for market standardization and 
for programmatic flexibility to meet the special needs and 
circumstances of the lower-income portion of the multifamily market.
---------------------------------------------------------------------------

    \284\ Abt Associates, op. cit. (August 2002).
    \285\ 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.
---------------------------------------------------------------------------

    Conclusions. While HUD recognizes that some segments of the market 
may be more challenging for the GSEs than others, the data reported in 
Tables A.30 and A.31 show that the GSEs have ample opportunities to 
purchase goals-qualifying mortgages. Furthermore, if a GSE makes a 
business decision to not pursue certain types of goals-qualifying loans 
in one segment of the market, they are free to pursue goals-qualifying 
owner and rental property mortgages in other segments of the market. As 
market leaders, the GSEs should be looking for innovative ways to 
pursue this business. Furthermore, there is evidence that the GSEs can 
earn reasonable returns on their goals business. The Regulatory 
Analysis that accompanies this proposed rule provides evidence that

[[Page 24362]]

the GSEs can earn financial returns on their purchases of goals-
qualifying loans that are only slightly below their return on equity 
from their normal business.

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

    This section discusses several qualitative factors that are 
indicators of the GSEs' ability to lead the industry in affordable 
lending. It discusses the GSEs' role in the mortgage market; their 
ability, through their underwriting standards, new programs, and 
innovative products, to influence the types of loans made by private 
lenders; their development and utilization of state-of-the-art 
technology; the competence, expertise and training of their staffs; and 
their financial resources.
a. Role in the Mortgage Market
    The GSEs have played a dominant role in the single-family mortgage 
market. As reported in Section C.3, mortgage purchases by the GSEs 
reached extraordinary levels in 2001 and 2003. Purchases by Fannie Mae 
stood at $568 billion in 2001 and $848 billion in 2002. Freddie Mac's 
single-family mortgage purchases were $393 billion in 2001 and $475 
billion in 2002. The Office of Federal Housing Enterprise Oversight 
(OFHEO) estimates that the GSEs' purchased 40 percent of newly-
originated conventional mortgages in 2001. Total GSE purchases, 
including loans originated in prior years, amounted to 46 percent of 
conventional originations in 2001.
    The dominant position of the GSEs in the mortgage market is 
reinforced by their relationships with other market institutions. 
Commercial banks, mutual savings banks, and savings and loans are their 
competitors as well as their customers--they compete to the extent they 
hold mortgages in portfolio, but at the same time they sell mortgages 
to the GSEs. They also buy mortgage-backed securities, as well as the 
debt securities used to finance the GSEs' portfolios. Mortgage bankers 
sell virtually all of their prime conventional conforming loans to the 
GSEs. Private mortgage insurers are closely linked to the GSEs, because 
mortgages purchased by the enterprises that have loan-to-value ratios 
in excess of 80 percent are normally required to be covered by private 
mortgage insurance, in accordance with the GSEs' charter acts.
b. Underwriting Standards for the Primary Mortgage Market
    The GSEs' underwriting guidelines are followed by virtually all 
originators of prime mortgages, including lenders who do not sell many 
of their mortgages to Fannie Mae or Freddie Mac. The guidelines are 
also commonly followed in underwriting ``jumbo'' mortgages, which 
exceed the maximum principal amount which can be purchased by the GSEs 
(the conforming loan limit)--such mortgages eventually might be sold to 
the GSEs, as the principal balance is amortized or when the conforming 
loan limit is otherwise increased. Changes that the GSEs have made to 
their underwriting standards in order to address the unique needs of 
low-income families were discussed in Section C.4 of this Appendix. The 
GSEs' market influence is one reason these new, more flexible 
underwriting standards have spread throughout the market. Because the 
GSEs' guidelines set the credit standards against which the mortgage 
applications of lower-income families are judged, the enterprises have 
a profound influence on the rate at which mortgage funds flow to low- 
and moderate-income borrowers and underserved neighborhoods.
    As discussed below, the GSEs' new automated underwriting systems 
are widely used to originate mortgages in today's market. As discussed 
in Sections C.7 and C.8, the GSEs have started adapting their 
underwriting systems for subprime loans and other loans that have not 
met their traditional underwriting standards.
c. State-of-the-Art Technology
    Both GSEs are in the forefront of new developments in mortgage 
industry technology. Automated underwriting and online mortgage 
processing are a couple of the new technologies that have impacted the 
mortgage market, expanding homeownership opportunities. This section 
provides an overview of these new technologies and the extent of their 
use.
    Each enterprise released an automated underwriting system in 1995--
Freddie Mac's ``Loan Prospector'' (LP) and Fannie Mae's ``Desktop 
Underwriter'' (DU). During 2001 and 2002, roughly 60 percent of all 
newly-originated mortgages that Freddie Mac purchased were processed 
through LP. Lenders and brokers used LP to evaluate 7.3 million loan 
applications in 2001 (almost double the amount in 2000) and 8.2 million 
loans in 2002.\286\ As of the end of 2002, LP had processed 25 million 
loans since its inception. Fannie Mae also reports that roughly 60 
percent of the loans it purchased during 2001 and 2002 were processed 
through DU. DU evaluated more than 10 million loans in 2002, compared 
with 8 million in 2001. As of the end of 2002, DU had processed over 26 
million loans since its inception. The GSEs' systems have also been 
adapted for FHA and jumbo loans. Automated underwriting systems are 
being further adapted to facilitate risk-based pricing, which enables 
mortgage lenders to offer each borrow an individual rate based on his 
or her risk. As discussed earlier, concerns about the use of automated 
underwriting and risk-based pricing include the disparate impact on 
minorities and low-income borrowers and the ``black box'' nature of the 
score algorithm.
---------------------------------------------------------------------------

    \286\ This section is based heavily on ``DU and LP Usage 
Continues to Rise,'' in Inside Mortgage Technology published by 
Inside Mortgage Finance, January 27, 2003, page 1-2.
---------------------------------------------------------------------------

    The GSEs are using their state-of-the-art technology in certain 
ways to help expand homeownership opportunities. For example, Fannie 
Mae has developed Fannie Mae Property GeoCoder a computerized mapping 
service offered to lenders, nonprofit organizations, and state and 
local governments to help them determine whether a property is located 
in an area that qualifies for Fannie Mae's community lending products 
designed to increase homeownership and revitalization in traditionally 
underserved areas. In addition, eFannieMae.com is Fannie Mae's 
business-to-business web site where lenders can access product 
information and important technology tools, view upcoming events, and 
receive news about training opportunities. This site receives on 
average 80,000 visitors per week.\287\ Freddie Mac has introduced in 
recent years internet-based debt auctions, debt repurchase operations, 
and debt exchanges. These mechanisms benefit investors by providing 
more uniform pricing, greater transparency and faster price discovery--
all of which makes Freddie Mac debt more attractive to investors and 
reduces the cost of funding mortgages.\288\ In addition, Freddie Mac 
has provided automated tools for lenders to identify and work with 
borrowers most likely to encounter problems making their mortgage 
payments. EarlyIndicator has become the industry standard for default 
management technology. It can reduce the consequences of mortgage 
delinquency for borrowers, servicers and investors.\289\
---------------------------------------------------------------------------

    \287\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
pp. 10-11.
    \288\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 14.
    \289\ Freddie Mac, 2002 Annual Housing Activities Report, 2003, 
p. 52.
---------------------------------------------------------------------------

    The GSEs are also expanding homeownership opportunities through the 
use of the Internet in processing

[[Page 24363]]

mortgage originations. New online mortgage originations reached $267.6 
billion in the first half of 2002, compared with $97 billion for the 
first six months of 2001. The 2002 six-month volume comprised 26.5 
percent of the estimated $1.01 trillion in total mortgage originations 
for the same time period.\290\ Freddie Mac made Loan Prospector on the 
Internet service available to lenders for their retail operations. 
Freddie Mac also adopted the mortgage industry's XML (extensible markup 
language) data standard, which is integral to streamlining and 
simplifying Internet-based transactions. In addition, Congress enacted 
legislation that allows the use of electronic signature in contracts in 
2001, making a completely electronic mortgage transaction possible. 
With the use of electronic signatures, electronic mortgages are 
expected to improve the mortgage process, further reducing origination 
and servicing costs. In October 2000, Freddie Mac purchased its first 
electronic mortgage under the new law.
---------------------------------------------------------------------------

    \290\ Inside Mortgage Finance, ``Online Volume Comprises One-
Fourth of Total Originations in First Half `02,'' September 20, 
2002, p. 8.
---------------------------------------------------------------------------

    Fannie Mae also offers a variety of other online tools and 
applications that have the potential to make the mortgage loan process 
more cost effective and efficient for lenders. For example, ``HomeBuyer 
Funds Finder,'' a one-stop online resource designed for lenders and 
other housing professionals, enables users to access a database of 
local housing subsidy programs available for low- and moderate-income 
borrowers. In 2002, the HomeBuyer Funds Finder web site received over 
24,500 hits.\291\ ``Home Counselor Online'' provides homeownership 
counselors with the necessary tools to help consumers financially 
prepare to purchase a home. As of February 2002, over 1,200 counselors 
representing 542 organizations were using Home Counselor Online.\292\ A 
more complete list of Fannie Mae's online tool and applications can be 
found in its Annual Housing Activities Report. In 2002, Fannie Mae's 
total eBusiness volume was $1.1 trillion, up from $800 billion in 
2000.\293\
---------------------------------------------------------------------------

    \291\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 12.
    \292\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 11.
    \293\ Fannie Mae, 2002 Annual Housing Activities Report, 2003, 
p. 10.
---------------------------------------------------------------------------

d. Staff Resources
    Both Fannie Mae and Freddie Mac are well-known throughout the 
mortgage industry for the expertise of their staffs in carrying out 
their current programs, conducting basic and applied research regarding 
mortgage markets, developing innovative new programs, and undertaking 
sophisticated analyses that may lead to new programs in the future. The 
role that the GSEs have played in spreading the use of technology 
throughout the mortgage market reflects the enormous expertise of their 
staff. 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.
e. Financial Strength
    Fannie Mae. The benefits that accrue to the GSEs because of their 
GSE status, as well as their solid management, have made them two of 
the nation's most profitable businesses. Fannie Mae's net income was 
$3.9 billion in 1999, $4.4 billion in 2000, $5.9 billion in 2001, and 
$4.6 billion in 2002.\294\ Fannie Mae's return on equity averaged 24.0 
percent over the 1995-99 period--far above the rates achieved by most 
financial corporations. Fannie Mae's return on equity reached 26.1 
percent in 2002, an increase of 3 percent over the previous year.\295\ 
In 2002, Fannie Mae's core business earnings grew by 19 percent, credit 
losses fell to their lowest level since 1983 and taxable equivalent 
revenues grew by 17 percent.\296\
---------------------------------------------------------------------------

    \294\ The 22% decrease in Fannie Mae's 2002 net income resulted 
primarily from a $4.508 billion increase in purchased options 
expense, which occurred due to an increase in the notional amount of 
purchased options outstanding and the declining interest rate 
environment. Recorded purchased options expense for 2001 was only 
$37 million by comparison. Fannie Mae 2002 Annual Report, 2003, p. 
23.
    \295\ Fannie Mae, 2002 Annual Report to Shareholders, 
``Financial Highlights.''
    \296\ Fannie Mae, 2002 Annual Report to Shareholders, Financial 
Highlights and Letter to Shareholders.
---------------------------------------------------------------------------

    Fannie Mae's core business earnings have increased from 39 cents a 
share in 1987 to $6.31 in 2002, and dividends per common share have 
increased from $.96 in 1998 to $1.32 in 2002, an 10 percent increase 
over 2001. Although operating earnings per diluted common share 
decreased from 2001 to 2002 by 21% to $4.53, Fannie Mae has still 
produced double-digit increases for the past 16 years in core business 
earnings per share, placing them among the best of the S&P 500 
companies.\297\
---------------------------------------------------------------------------

    \297\ Fannie Mae, 2002 Annual Report to Shareholders, Financial 
Highlights and Letter to Shareholders.
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    Freddie Mac. Freddie Mac has shown similar trends. Freddie Mac's 
net income was $3.7 billion in 2000 and rose to $10.1 billion in 2002, 
an increase of 320 percent from the previous year.\298\ 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. Freddie 
Mac's return on common equity exceeded 20 percent in 2001 for the 
twentieth consecutive year, reaching a high of 39.2 percent in 2001. 
Freddie Mac's total revenues grew to $7.4 billion in 2001, up from $4.5 
billion in 2000.\299\
---------------------------------------------------------------------------

    \298\ Freddie Mac, Consolidated Statements of Income, Restated 
November 21, 2003.
    \299\ Freddie Mac, 2001 Annual Report to Shareholders, pp. 21-
22.
---------------------------------------------------------------------------

    Investors in Freddie Mac's common stock have seen their annual 
dividends per share increase from $0.68 in 2000 to $0.88 in 2002.\300\ 
Earnings per diluted common share increased from $4.23 in 2001 to 
$14.18 in 2002.\301\
---------------------------------------------------------------------------

    \300\ Freddie Mac, Consolidated Statements of Income, Restated 
November 21, 2003.
    \301\ Freddie Mac, Consolidated Statements of Income, Restated 
November 21, 2003.
---------------------------------------------------------------------------

    Other Indicators. Additional indicators of the strength of the GSEs 
are provided by various rankings of American corporations. Business 
Week has reported that among Standard & Poor's 500 companies in 1999, 
Fannie Mae and Freddie Mac respectively ranked 49th and 88th in market 
value, and 24th and 43rd in total profits.\302\ Fannie Mae ranked 30th 
in market value and 13th in total profits in 2001, while Freddie Mac 
ranked 23rd in annual growth revenues from 1991-2001.\303\
---------------------------------------------------------------------------

    \302\ Business Week, March 27, 2000, p. 197.
    \303\ The ``2002 Fortune 500 Top Performing Companies and 
Industries.'' <http://www.fortune.com/fortune/fortune500/topperformers/0,14940,00.html .
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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 reviewed by the Office of Federal Housing 
Enterprise Oversight, HUD concludes that the goals raise minimal, if 
any, safety and soundness concerns.

[[Page 24364]]

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 proposed to be 
established at 52 percent of eligible units financed in each of 
calendar years 2005, 53 percent in 2006, 55 percent in 2007, and 57 
percent in 2008. This goal will remain in effect thereafter, unless 
changed by the Secretary prior to that time. In addition, a low- and 
moderate-income subgoal of 45 percent in 2005, 46 percent in 2006, and 
47 percent in both 2007 and is proposed for the GSEs' acquisitions of 
single-family-owner home purchase loans in metropolitan areas. This 
subgoal is designed to encourage the GSEs to lead the primary market in 
offering homeownership opportunities to low- and moderate-income 
families. The Secretary's consideration of the six statutory factors 
that led to the choice of these goals is summarized in this section.

1. Housing Needs and Demographic Conditions

    Affordability Problems. Data from the 2000 Census and the American 
Housing Surveys demonstrate that there are substantial housing needs 
among low- and moderate-income families. Many of these households are 
burdened by high homeownership costs or rent payments and will likely 
continue to face serious housing problems, given the dim prospects for 
earnings growth in entry-level occupations. There is evidence of deep 
and persistent housing problems for Americans with the lowest incomes. 
Recent HUD analysis reveals that in 1999, 4.9 million households had 
``worst case'' housing needs, defined as housing costs greater than 50 
percent of household income or severely inadequate housing among 
unassisted very-low-income renter households. Among the 34 million 
renters in all income categories, 6.3 million (19 percent) had a severe 
rent burden and over one million renters (3 percent) lived in housing 
that was severely inadequate.
    Demographic Trends. Changing population demographics will result in 
a need for the primary and secondary mortgage markets to meet 
nontraditional credit needs, respond to diverse housing preferences and 
overcome information and other barriers that many immigrants and 
minorities face. It is projected that there will be 1.2 million new 
households each year over the next decade. The aging of the baby-boom 
generation and the entry of the baby-bust generation into prime home 
buying age will have a dampening effect on housing demand. However, the 
continued influx of immigrants will increase the demand for rental 
housing, while those who immigrated during the 1980s and 1990s will be 
in the market for owner-occupied housing. Immigrants and other 
minorities--who accounted for nearly 40 percent of the growth in the 
nation's homeownership rate over the past five years--will be 
responsible for almost two-thirds of the growth in the number of new 
households over the next ten years. Non-traditional households have 
become more important, as overall household formation rates have 
slowed. With later marriages, divorce, and non-traditional living 
arrangements, the fastest growing household groups have been single-
parent and single-person households. As these demographic factors play 
out, the overall effect on housing demand will likely be sustained 
growth and an increasingly diverse household population from which to 
draw new renters and homeowners. According to the National Association 
of Homebuilders, annual housing demand will average 1.82 million units 
over the next decade.
    Growth in Single-Family Affordable Lending. Many younger, minority 
and lower-income families did not become homeowners during the 1980s 
due to the slow growth of earnings, high real interest rates, and 
continued house price increases. Over the past ten years, economic 
expansion, accompanied by low interest rates and increased outreach on 
the part of the mortgage industry, has improved affordability 
conditions for these families. As this appendix explains, there has 
been a ``revolution in affordable lending'' that has extended 
homeownership opportunities to historically underserved households. The 
mortgage industry has offered more customized mortgage products, more 
flexible underwriting, and expanded outreach to low-income and minority 
borrowers. Fannie Mae and Freddie Mac have been a big part of this 
``revolution in affordable lending.'' HMDA data suggest that the 
industry and GSE initiatives are increasing the flow of credit to 
underserved borrowers. Between 1993 and 2002, conventional loans to 
low-income and minority families increased at much faster rates than 
loans to upper-income and non-minority families. Thus, the 1990s and 
the early part of the current decade have seen the development of a 
strong affordable lending market.
    Disparities in Housing and Mortgage Markets. Despite this strong 
growth in affordable lending, serious disparities in the nation's 
housing and mortgage markets remain. The homeownership rate for 
African-American and Hispanic households is about 25 percentage points 
below that of white households. In addition to low income, barriers to 
homeownership that disproportionately affect minorities and immigrants 
include: lack of capital for down payment and closing costs; poor 
credit history; lack of access to mainstream lenders; little 
understanding of the homebuying process; and, continued discrimination 
in housing markets and mortgage lending. With respect to the latter, a 
recent HUD-sponsored study of discrimination in the rental and owner 
markets found that while differential treatment between minority and 
white home seekers had declined over the past ten years, it continued 
at an unacceptable level in the year 2000. In addition, disparities in 
mortgage lending continued across the nation in 2002, when the loan 
denial rate for African-American applicants was almost three times that 
for white applicants, even after controlling for income of the 
applicant. HUD studies also show that African Americans and Hispanics 
are subject to discriminatory treatment during the pre-qualification 
process of applying for a mortgage.
    Single-Family Mortgage Market. Heavy refinancing due to low 
interest rates increased single-family mortgage originations to record 
levels during 2001-2003. Demographic forces, industry outreach, and low 
interest rates also kept lending for home purchase at record levels as 
well. As noted above, the potential homeowner population over the next 
decade will be highly diverse, as growing demand from immigrants and 
minorities are expected to sustain the home purchase market, as our 
population ages. Single-family housing starts are expected to continue 
in the 1.65-1.70 million range over the next few years. Refinancing of 
existing mortgages, which accounted for about 65 percent of 
originations during 2000-2003 is expected to return to more normal 
levels. As this Appendix explains, the GSEs will continue to play a 
dominant role in the single-family market and will both impact and be 
affected by major market developments such as the growth in subprime 
lending and the increasing use automated underwriting.
    Multifamily Mortgage Market. The market for financing of 
multifamily apartments has grown to record volumes. The favorable long-
term prospects for apartments, combined with record low interest rates, 
have kept investor demand for apartments strong and supported property 
prices. As

[[Page 24365]]

explained below, Fannie Mae and Freddie Mac have been among those 
boosting volumes and introducing new programs to serve the multifamily 
market. The long run outlook for the multifamily rental market is 
sustained, moderate growth, based on favorable demographics. The 
minority population, especially Hispanics, provides a growing source of 
demand for affordable rental housing. ``Lifestyle renters'' (older, 
middle-income households) are also a fast growing segment of the rental 
population. However, provision of affordable housing will continue to 
challenge suppliers of multifamily rental housing and policy makers at 
all levels of governments. Low incomes combined with high housing costs 
define a difficult situation for millions of renter households. Housing 
cost reductions are constrained by high land prices and construction 
costs in many markets. Government action--through land use regulation, 
building codes, and occupancy standards--are major contributors to 
those high costs. In addition to fewer regulatory barriers and costs, 
multifamily housing would benefit from more favorable public attitudes. 
Higher density housing is a potentially powerful tool for preserving 
open space, reducing sprawl, and promoting transportation alternatives 
to the automobile. The recently heightened attention to these issues 
may increase the acceptance of multifamily rental construction to both 
potential customers and their prospective neighbors.

2. Past Performance of the GSEs

    This section reviews the low- and moderate-income performance of 
Fannie Mae and Freddie Mac. It first reviews the GSEs' performance on 
the Low- and Moderate-Income Goal, then reviews findings from Section 
E.2 regarding the GSEs' purchases of home loans for historically 
underserved families and their communities. Finally, it reviews 
findings from Section G concerning the GSEs' presence in owner and 
rental markets.
a. Housing Goals Performance
    In the October 2000 rule, the low- and moderate-income goal was set 
at 50 percent for 2001-03. Effective on January 1, 2001, several 
changes in counting requirements came into effect for the low- and 
moderate-income goal, as follows: (a) ``B.00000000onus points'' (double 
credit) for purchases of mortgages on small (5-50 unit) multifamily 
properties and, above a threshold level, mortgages on 2-4 unit owner-
occupied properties; (b) a ``temporary adjustment factor'' (1.35 unit 
credit) for Freddie Mac's purchases of mortgages on large (more than 50 
units) multifamily properties; (c) changes in the treatment of missing 
data; and (d) a procedure for the use of imputed or proxy rents for 
determining goal credit for multifamily mortgages. Fannie Mae's 
performance was 51.5 percent in 2001 and 51.8 percent in 2002, and 
Freddie Mac's performance was 53.2 percent in 2001 and 51.4 percent in 
2002; thus both GSEs surpassed this higher goal.
    Counting requirements (a) and (b) expired at the end of 2003, while 
(c) and (d) will remain in effect after that. If this counting 
approach--without the bonus points and the ``temporary adjustment 
factor'' had been in effect in 2000 and 2001, and the GSEs had 
purchased the same mortgages that they actually did purchase in both 
years, then Fannie Mae's performance would have been 51.3 percent in 
2000, 49.2 percent in 2001, and 49.0 percent in 2002. Freddie Mac's 
performance would have been 50.6 percent in 2000, 47.7 percent in 2001, 
and 46.5 percent in 2001. Thus, both Fannie Mae and Freddie Mac would 
have surpassed the low- and moderate-income goal of 50 percent in 2000 
and fallen short in 2001 and 2002. (See Figure A.1.)
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b. Single-Family Affordable Lending Market
    The GSEs have played a major role in the single-family mortgage 
market over the past ten years. Their purchases of single-family-owner 
mortgages accounted for 57 percent of all mortgages originated in the 
single-family conventional conforming market between 1999 and 2002. 
Their underwriting and purchase guidelines are market standards, used 
in all segments of the mortgage market. The GSEs have worked to improve 
their affordable lending record--they have introduced new low-
downpayment products targeted at lower-income families; they have 
customized their underwriting standards to recognize the unique needs 
of immigrant and minority families; and, they have entered into 
numerous partnerships with lenders and non-profit groups to reach out 
to underserved populations. The enterprises' role in the mortgage 
market is also reflected in their use of cutting edge technology, such 
as the development of Loan Prospector and Desktop Underwriter, the 
automated underwriting systems developed by Freddie Mac and Fannie Mae, 
respectively. Both GSEs are also entering new and challenging fields of 
mortgage finance, such as purchasing subprime mortgages.
    Despite these efforts and the overall gains in goal performance, 
the Department remains concerned about the GSEs' support of home 
lending for the lower-income end of the market and for first-time 
homebuyers. The lower-income shares of the GSEs' purchases are too low, 
particularly for underserved groups such as minority first-time 
homebuyers.
    This appendix included a comprehensive analysis of the GSEs' 
performance in funding home purchase mortgages for families and 
communities that historically have not been well served by the mortgage 
market. The following findings are offered with respect to the GSEs' 
acquisitions of home purchase loans that qualify for the three housing 
goals (special affordable and underserved areas as well as low- and 
moderate-income) and their acquisitions of first-time homebuyer loans:
     While Fannie Mae and Freddie Mac have both 
improved their support for the single-family affordable lending market 
over the past ten years, they have generally lagged the overall 
conventional conforming market in providing affordable loans to lower-
income borrowers and underserved areas. This finding is based on HUD's 
analysis of GSE and HMDA data and on numerous studies by academics and 
research organizations.
     The GSEs have shown different patterns of 
mortgage purchases. Except for two years (1999 and 2000), Fannie Mae 
has performed better than Freddie Mac since 1993 on all three goals-
qualifying categories--low-mod, special affordable, and underserved 
areas. As a result, the percentage of Freddie Mac's purchases 
benefiting historically underserved families and their neighborhoods 
has been less than the corresponding shares of total market 
originations, while Fannie Mae's purchases have been somewhat closer to 
the patterns of originations in the primary market.
     The above patterns can be seen by the following 
percentage shares of home purchase loans that qualified for the three 
housing goals between 1996 and 2002:

 
----------------------------------------------------------------------------------------------------------------
                                                                      Special                       Underserved
                                                                    affordable        Low-mod          areas
                                                                     (percent)       (percent)       (percent)
----------------------------------------------------------------------------------------------------------------
Freddie Mac.....................................................            12.8            39.8            21.7
Fannie Mae......................................................            13.5            41.2            23.5
Market (w/o B&C)................................................            16.0            43.6            25.4
----------------------------------------------------------------------------------------------------------------

     During 2001 and 2002, Fannie Mae improved its 
performance enough to reduce its gap in the special affordable and 
underserved areas markets and to match the low-mod market. During 2001 
and 2002, Freddie Mac lagged the conventional conforming market on all 
three goals-qualifying categories; see Figure A.2 for the low- and 
moderate-income shares for Fannie Mae, Freddie Mac and the market.
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     Both Fannie Mae and Freddie lag the conventional 
conforming market in funding first-time homebuyers, and by a rather 
wide margin. Between 1999 and 2001, first-time homebuyers accounted for 
27 percent of each GSE's purchases of home loans, compared with 38 
percent for home loans originated in the conventional conforming 
market.
     The GSEs also account for a very small share of 
the market for important groups such as minority first-time homebuyers. 
Considering the total mortgage market (both government and conventional 
loans), it is estimated that the GSEs purchased only 14 percent of 
loans originated between 1999 and 2001 for African-American and 
Hispanic first-time homebuyers, or one-third of their share (42 
percent) of all home purchase loans originated during that period. 
Considering the conventional conforming market and the same time 
period, it is estimated that the GSEs purchased only 31 percent of 
loans originated for African-American and Hispanic first-time 
homebuyers, or approximately one-half of their share (57 percent) of 
all home purchase loans in that market.
    To summarize, the Department's analysis suggests that the GSEs have 
not been leading the single-family-owner market in purchasing loans 
that qualify for the housing goals, although Fannie Mae improved its 
low-mod and underserved area performance during 2001 and 2002 to 
approach the market in funding special affordable and underserved areas 
loans and to match the market in funding low- and moderate-income 
loans. Still, there is room for both Fannie Mae and Freddie Mac to 
further improve their performance in purchasing affordable loans at the 
lower-income end of the market, particularly in the minority first-time 
homebuyer market. Evidence suggests that there is a significant 
population of potential homebuyers who might respond well to aggressive 
outreach by the GSEs--immigrants and minorities, in particular, are 
expected to be a major source of future homebuyers. Furthermore, 
studies indicate the existence of a large untapped pool of potential 
homeowners among the rental population. Indeed, the GSEs' recent 
experience with new outreach and affordable housing initiatives is 
important confirmation of this potential. To move the GSEs into a 
leadership position, the Department is establishing three subgoals for 
home purchase loans that qualify for the three housing goals. The low- 
and moderate-income subgoal is discussed in Section I.3 below.
c. Overall Market Shares
    This appendix also included an analysis of the GSEs' role in the 
overall (owner and rental) conventional conforming mortgage market. 
While GSE mortgage purchases represented 49 percent of total dwelling 
units financed between 1999 and 2002, they represented smaller shares 
of the three goals-qualifying markets: 42 percent of housing units 
financed for low- and moderate-income families; 41 percent of newly-
mortgaged units in underserved areas; and 35 percent of units financed 
for the very-low-income and other families that qualify as special 
affordable. (See Figure A.3.) In other words, the GSEs accounted for 
approximately 40 percent or less of the single-family and multifamily 
units financed in the goals-qualifying markets. This market share 
analysis suggests that there is room for the GSEs to increase their 
purchases in these goals-qualifying markets.
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    The market analysis also examined the GSEs' presence in the three 
major property sectors of the mortgage market: Single-family owner (a 
57 percent share for the GSEs between 1999 and 2002), single-family 
rental (a 27 percent share), and multifamily (a 30 percent share). The 
GSEs have historically played a minimal role in the market financing 
single-family rental properties, which is an important source of low-
income rental housing. Fannie Mae and Freddie Mac have increased their 
purchases of these mortgages, but their purchases totaled only 27 
percent of the single-family rental units that received financing 
between 1999 and 2002. A further increased presence by Fannie Mae and 
Freddie Mac would bring lower interest rates and liquidity to this 
market, as well as improve their housing goals performance.
d. The GSEs' Purchases of Multifamily Mortgages
    Fannie Mae and, especially, Freddie Mac have rapidly expanded their 
presence in the multifamily mortgage market in the period since the 
passage of FHEFSSA. The Senate report on this legislation in 1992 
referred to the GSEs' activities in the multifamily arena as 
``troubling,'' citing Freddie Mac's September 1990 suspension of its 
purchases of new multifamily mortgages and criticism of Fannie Mae for 
``creaming'' the market.\304\
---------------------------------------------------------------------------

    \304\ Senate Report 1023-282, May 15, 1992, p. 36.
---------------------------------------------------------------------------

    Freddie Mac has successfully rebuilt its multifamily acquisition 
program, as shown by the increase in its purchases of multifamily 
mortgages: From $27 million in 1992 to $3 billion in 1997 and then to 
approximately $7 billion during the next three years (1998 to 2000), 
before rising further to $11.9 billion in 2001 and $13.3 billion in 
2002. Multifamily properties accounted for over 9 percent of all 
dwelling units (both owner and rental) financed by Freddie Mac during 
2000 and 2001, and for 7 percent during the heavy refinancing year of 
2002. Concerns regarding Freddie Mac's multifamily capabilities no 
longer constrain their performance with regard to low- and moderate-
income families.
    Fannie Mae never withdrew from the multifamily market, but it has 
also stepped up its activities in this area substantially, with 
multifamily purchases rising from $3.0 billion in 1992 to $9.4 billion 
in 1999, $18.7 billion in 2001, and $18.3 billion in 2002. Multifamily 
units as a share of all dwelling units (both owner and rental) financed 
by Fannie Mae varied in the 10-13 percent range between 1999 and 2001, 
before falling to 7.3 percent during heavy refinancing year of 2002.
    The increased purchases of multifamily mortgages by Fannie Mae and 
Freddie Mac have major implications for the Low- and Moderate-Income 
Housing Goal, since a very high percentage of multifamily units have 
rents which are affordable to low- and moderate-income families. 
However, the potential of the GSEs to lead the multifamily mortgage 
industry has not been fully developed. As reported earlier in Table 
A.30, the GSEs' purchases between 1999 and 2002 accounted for only 30 
percent of the multifamily units that received financing during this 
period. Certainly there are ample opportunities and room for expansion 
of the GSEs' share of the multifamily mortgage market. The GSEs' size 
and market position between loan originators and mortgage investors 
makes them the logical institutions to identify and promote needed 
innovations and to establish standards that will improve market 
efficiency. As their role in the multifamily market continues to grow, 
the GSEs will have the knowledge and market presence to push 
simultaneously for standardization and for programmatic flexibility to 
meet special needs and circumstances, with the ultimate goal of 
increasing the availability and reducing the cost of financing for 
affordable and other multifamily rental properties.

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

    As discussed in Section E, the Department is proposing to establish 
a subgoal of 45 percent for each GSE's purchases of home purchase loans 
for low- and moderate-income families in the single-family-owner market 
of metropolitan areas for 2005, with the subgoal rising to 46 percent 
in 2006 and 47 percent in 2007 and 2008. The purpose of this subgoal is 
to encourage the GSEs to improve their acquisitions of home purchase 
loans for lower-income families and first-time homebuyers who are 
expected to enter the homeownership market over the next few years. If 
the GSEs meet this goal, they will be leading the primary market by 
approximately one percentage point in 2005 and by three percentage 
points in 2007 and 2008, based on the income characteristics of home 
purchase loans reported in HMDA. Between 1999 and 2002 (2000 and 2002), 
HMDA data show that low- and moderate-income families accounted for an 
average of 44.3 (44.2) percent of single-family-owner loans originated 
in the conventional conforming market of metropolitan areas. Loans in 
the B&C portion of the subprime market are not included in these 
averages. To reach the 45-percent (47 percent) subgoal for 2005 (for 
2007-08), both GSEs would have to improve their historical 
performance'Fannie Mae by 0.8 percentage points (2.8 percentage points) 
over its average performance of 44.2 percent in 2001 and 2002, and 
Freddie by 2.4 percentage points (4.4 percentage points) over its 
average performance of 42.6 percent during the same period.
    As explained in Section E.9.f, HUD will be re-benchmarking its 
median incomes for metropolitan areas and non-metropolitan counties 
based on 2000 Census median incomes, and will be incorporating the 
effects of the new OMB metropolitan area definitions. HUD projected the 
effects of these two changes on the low- and moderate-income shares of 
the single-family-owner market for the years 1999-2002. These estimates 
will be referred to as ``projected data'' while the 1990-based data 
reported above will be referred to as ``historical data.'' The average 
low-mod share of the home purchase market (without B&C loans) was 43.1 
percent based on projected data, as compared with 44.3 percent based on 
historical data. Thus, based on projected data, the 45-percent (47-
percent) subgoal is approximately two (four) percentage points above 
the 1999-2002 market average. Fannie Mae's average low-mod performance 
between 1999 and 2002 based on the projected data was 41.4 percent, 
compared with 42.5 percent based on historical data. To reach the 45-
percent subgoal for 2005 based on projected data, Fannie Mae would have 
to improve its performance by 2.3 percentage points over its projected 
average performance of 42.7 percent in 2001 and 2002, or by 1.4 
percentage points over its projected 2002 low-mod performance of 43.6 
percent. Freddie Mac's average low-mod performance between 1999 and 
2002 based on the projected data was 40.9 percent, compared with 42.3 
percent based on historical data. To reach the 45-percent subgoal for 
2005 based on projected data, Freddie Mac would have to improve its 
performance by 4.0 percentage points over its projected average 
performance of 41.0 percent in 2001 and 2002, or by 2.9 percentage 
points over its projected 2002 low-mod performance of 42.1 percent.
    The approach taken is for the GSEs to obtain their leadership 
position by staged increases in the low-mod subgoal; this will enable 
the GSEs to take new initiatives in a correspondingly staged manner to

[[Page 24372]]

achieve the new subgoal each year. Thus, the increases in the low-mod 
subgoal are sequenced so that the GSEs can gain experience as they 
improve and move toward the new higher subgoal targets.
    As explained in Section E.9, the subgoal applies only to the GSEs' 
purchases in metropolitan areas because the HMDA-based market benchmark 
is only available for metropolitan areas. The Department is also 
setting subgoals for the other two goals-qualifying categories, as 
follows: 17 percent for special affordable loans and 33 percent for 
loans in underserved areas.
    The Department considered the following factors when setting the 
subgoal for low- and moderate-income loans.
    (a) The GSEs have the ability to lead the market. The GSEs have the 
ability to lead the primary market for single-family-owner loans, which 
is the ``bread-and-butter'' of their business. They both have 
substantial experience in this market, which means there are no issues 
as whether or not the GSEs have yet penetrated the market, as there are 
with the single-family rental and multifamily markets. Both GSEs have 
not only been operating in the owner market for years, they have been 
the dominant players in that market, funding 57 percent of the single-
family-owner mortgages financed between 1999 and 2002. As discussed in 
Section G, their underwriting guidelines are industry standards and 
their automated mortgage systems are widely used throughout the 
mortgage industry. Through their new downpayment and subprime products, 
and their various partnership initiatives, the GSEs have shown that 
they have the capacity to reach out to lower-income families seeking to 
buy a home. Both Fannie Mae and Freddie Mac have the staff expertise 
and financial resources to make the extra effort to lead the primary 
market in funding single-family-owner mortgages for low- and moderate-
income mortgages, as well for special affordable and undeserved area 
mortgages.
    (b) The GSEs have lagged the market. Even though the GSEs have the 
ability to lead the market, they have lagged the market under the 
housing goals. 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 funding loans that qualify 
for the three housing goals. While the GSEs, and particularly Fannie 
Mae, have significantly improved their performance over the past two 
years, they have lagged the primary market in funding goals-qualifying 
loans during the period that they have operated under the current 
definitions of HUD's housing goals. Between 1996 and 2002 (1999 and 
2002), low- and moderate-income mortgages accounted for 39.8 (42.3) 
percent of Freddie Mac's purchases, 41.2 (42.5) percent of Fannie Mae's 
purchases, and 43.6 (44.3) percent of primary market originations 
(without B&C loans). The type of improvement needed to meet this new 
low-mod subgoal was demonstrated by Fannie Mae during 2001 and 2002, as 
Fannie Mae increased its low-mod purchases from 40.8 percent of its 
single-family-owner business in 2000 to 45.3 percent in 2002 (or from 
40.1 percent in 2000 to 43.6 percent in 2002 based on projected data).
    (c) Disparities in Homeownership and Credit Access Remain. There 
remain troublesome disparities in our housing and mortgage markets, 
even after the ``revolution in affordable lending'' and the growth in 
homeownership that has taken place since the mid-1990s. The 
homeownership rate for African-American and Hispanic households remains 
25 percentage points below that of white households. Minority families 
face many barriers in the mortgage market, such as lack of capital for 
down payment and lack of access to mainstream lenders (see above). 
Immigrants and minorities are projected to account for almost two-
thirds of the growth in the number of new households over the next ten 
years. As emphasized throughout this Appendix, changing population 
demographics will result in a need for the primary and secondary 
mortgage markets to meet nontraditional credit needs, respond to 
diverse housing preferences and overcome information and other barriers 
that many immigrants and minorities face. The GSEs have to increase 
their efforts in helping these families because so far they have played 
a surprisingly small role in serving minority first-time homebuyers. It 
is estimated that the GSEs accounted for 46.5 percent of all (both 
government and conventional) home loans originated between 1999 and 
2001; however, they accounted for only 14.3 percent of home loans 
originated for African-American and Hispanic first-time homebuyers. 
Within the conventional conforming market, it is estimated that the 
GSEs purchased only 20 percent of loans originated for African-American 
and Hispanic first-time homebuyers, even though they accounted for 57 
percent of all home purchase loans in that market. A subgoal for home 
purchase loans should increase the GSEs' efforts in important sub-
markets such as the one for minority first-time homebuyers.
    (d) There are ample opportunities for the GSEs to improve their 
performance. Low- and moderate-income loans are available for the GSEs 
to purchase, which means they can improve their performance and lead 
the primary market in purchasing loans for borrowers with less-than-
median income. Three indicators of this have already been discussed. 
First, Sections B and C of this appendix and Appendix D explain that 
the affordable lending market has shown an underlying strength over the 
past few years that is unlikely to vanish (without a significant 
increase in interest rates or a decline in the economy). The low-mod 
share of the home purchase market has averaged 43.6 percent since 1996 
and annually has ranged from 42.2 percent to 45.2 percent. Second, the 
market share data reported in Table A.30 of Section G demonstrate that 
there are newly-originated loans available each year for the GSEs to 
purchase. The GSEs' purchases of single-family owner loans represented 
57 percent of all single-family-owner loans originated between 1999 and 
2002, compared with 53 percent of the low-mod loans that were 
originated during this period. Thus, almost one-half of the low-mod 
conforming market is not touched by the GSEs. As noted above, the 
situation is even more extreme for special sub-markets such the 
minority first-time homebuyer market where the GSEs have only a minimal 
presence. Finally, the GSEs' purchases under the subgoal are not 
limited to new mortgages that are originated in the current calendar 
year. The GSEs can purchase loans from the substantial, existing stock 
of affordable loans held in lenders' portfolios, after these loans have 
seasoned and the GSEs have had the opportunity to observe their payment 
performance. In fact, based on Fannie Mae's recent experience, the 
purchase of seasoned loans appears to be one useful strategy for 
purchasing goals-qualifying loans.
    To summarize, although single-family-owner mortgages 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 lag the corresponding shares for the primary market. 
For the reasons given above, the Secretary believes that the GSEs can 
do more to raise the low- and moderate-income shares of their mortgages 
on these properties. This can be accomplished by building on various 
programs that the enterprises have already started, including (1) their 
partnership and outreach efforts, (2)

[[Page 24373]]

their incorporation of greater flexibility into their underwriting 
guidelines, (3) their purchases of CRA loans, and (4) their targeting 
of important markets where they have had only a limited presence in the 
past, such as the market for minority first-time homebuyers. A wide 
variety of quantitative and qualitative indicators indicate that the 
GSEs' have the resources and financial strength to improve their 
affordable lending performance enough to lead the market for low- and 
moderate-income families.

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

    As detailed in Appendix D, the low- and moderate-income mortgage 
market accounts for 51 to 57 percent of dwelling units financed by 
conventional conforming mortgages. In estimating the size of the 
market, HUD excluded the effects of the B&C market. HUD also used 
alternative assumptions about future economic and market affordability 
conditions that were less favorable than those that existed over the 
last five years. HUD is well aware of the volatility of mortgage 
markets and the possible impacts of changes in economic conditions on 
the GSEs' ability to meet the housing goals. Should conditions change 
such that the goals are no longer reasonable or feasible, the 
Department has the authority to revise the goals.

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

    The proposed Low- and Moderate-Income Housing Goal is 52 percent of 
eligible units for 2005, 53 percent for 2006, 55 percent for 2007, and 
57 percent for 2008. It is recognized that neither GSE met these 
proposed goals in 2001 and 2002. However, the market for the Low- and 
Moderate-Income Goal is estimated to be 51-57 percent. Under the new 
counting rules (i.e., 2000-Census income re-benchmarking and the new 
OMB metropolitan area definitions), Fannie Mae's low- and moderate-
income performance is estimated to have been 46.3 percent in 1999, 51.2 
percent in 2000, 48.7 percent in 2001, and 47.9 percent in 2002--for 
2005, Fannie Mae would have to increase its performance by 3.5 
percentage points over its average (unweighted) performance of 48.5 
percent over these last four years, or by 0.8 percentage point over its 
previous peak performance (51.2 percent in 2000). By 2008, Fannie Mae's 
performance would have to increase by 8.5 percentage points over 
average 1999-2002 performance, and by 5.8 percentage points over its 
previous peak performance in 2000. Freddie Mac's performance is 
estimated to have been 46.0 percent in 1999, 50.2 percent in 2000, 47.0 
percent in 2001, and 45.0 percent in 2002--for 2005, Freddie Mac would 
have to increase its performance by 4.9 percentage points over its 
average (unweighted) performance of 47.1 percent over these last four 
years, or by 1.8 percentage points over its previous peak performance 
(50.2 percent in 2000). By 2008, Freddie Mac's performance would have 
to increase by 9.9 percentage points over average 1999-2002 
performance, and by 6.8 percentage points over its previous peak 
performance. However, the low- and moderate-income market is estimated 
to be 51-57 percent. Thus, the GSEs should be able to improve their 
performance enough to meet these proposed goals of 52-57 percent.
    The objective of HUD's proposed Low- and Moderate-Income Goal is to 
bring the GSEs' performance to the upper end of HUD's market range 
estimate for this goal (51-57 percent), consistent with the statutory 
criterion that HUD should consider the GSEs' ability to lead the market 
for each Goal. To enable the GSEs to achieve this leadership, the 
Department is proposing modest increases in the Low- and Moderate-
Income Goal for 2005 which will increase further, year-by-year through 
2008, to achieve the ultimate objective for the GSEs to lead the market 
under a range of foreseeable economic circumstances by 2008. Such a 
program of staged increases is consistent with the statutory 
requirement that HUD consider the past performance of the GSEs in 
setting the Goals. Staged annual increases in the Low- and Moderate-
Income Goal will provide the enterprises with opportunity to adjust 
their business models and prudently try out business strategies, so as 
to meet the required 2008 level without compromising other business 
objectives and requirements.
    Figure A.3 summarizes many of the points made in this section 
regarding opportunities for Fannie Mae and Freddie Mac to improve their 
overall performance on the Low- and Moderate-Income Goal. The GSEs' 
purchases provided financing for 23,580,594 (or 49 percent) of the 
48,270,415 single-family and multifamily units that were financed in 
the conventional conforming market between 1999 and 2002. However, in 
the low- and moderate-income part of the market, the 11,408,692 units 
that were financed by GSE purchases represented only 42 percent of the 
27,158,020 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.

6. Conclusions

    Having considered the projected mortgage market serving low- and 
moderate-income families, economic, housing and demographic conditions 
for 2005-08, and the GSEs' recent performance in purchasing mortgages 
for low- and moderate-income families, the Secretary has determined 
that the proposed goals of 52 percent of eligible units financed in 
2005, 53 percent in 2006, 55 percent in 2007, and 57 percent in 2008 
are feasible. The Secretary is also proposing a subgoal of 45 percent 
for the GSEs' purchases of single-family-owner home purchase mortgages 
in metropolitan areas in 2005, increasing to 46 percent in 2006 and 47 
percent in 2007 and 2008. The Secretary has considered the GSEs' 
ability to lead the industry as well as the GSEs' financial condition. 
The Secretary has determined that the proposed goals and the proposed 
subgoals are necessary and appropriate.

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

A. Introduction

1. Establishment of Goal

    The Federal Housing Enterprises Financial Safety and Soundness 
Act of 1992 (FHEFSSA) requires the Secretary to establish an annual 
goal for the purchase of mortgages on housing located in central 
cities, rural areas, and other underserved areas (the ``Underserved 
Areas Housing Goal'').
    In establishing this annual housing goal, Section 1334 of 
FHEFSSA requires the Secretary to consider:
    1. Urban and rural housing needs and the housing needs of 
underserved areas;
    2. Economic, housing, and demographic conditions;
    3. The performance and effort of the enterprises toward 
achieving the Underserved Areas Housing Goal in previous years;
    4. The size of the conventional mortgage market for central 
cities, rural areas, and other underserved areas relative to the 
size of the overall conventional mortgage market;
    5. The ability of the enterprises to lead the industry in making 
mortgage credit available throughout the United States, including 
central cities, rural areas, and other underserved areas; and
    6. The need to maintain the sound financial condition of the 
enterprises.
    Organization of Appendix. The remainder of Section A first 
defines the Underserved

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Areas Housing Goal for both metropolitan areas and nonmetropolitan 
areas. Sections B and C address the first two factors listed above, 
focusing on findings from the literature on access to mortgage 
credit in metropolitan areas (Section B) and in nonmetropolitan 
areas (Section C). Separate discussions are provided for 
metropolitan and nonmetropolitan (rural) areas because of 
differences in the underlying markets and the data available to 
measure them. Section D discusses the past performance of the GSEs 
on the Underserved Areas Housing Goal (the third factor) and 
Sections E-G report the Secretary's findings for the remaining 
factors. Section H presents the Department's proposals relating to 
the definition of underserved areas in nonmetropolitan areas. 
Section I summarizes the Secretary's rationale for establishing a 
subgoal for single-family-owner home purchase mortgages and for 
setting the level for the Underserved Areas Housing Goal.

2. HUD's Underserved Areas Housing Goal

    HUD's definition of the geographic areas targeted by this goal 
is basically the same as that used during 1996-2003. It is divided 
into a metropolitan component and a nonmetropolitan component. 
However, as explained below, switching to 2000 Census geography 
increases the number of census tracts defined as underserved, and 
this necessitates an adjustment of the goal level.
    Metropolitan Areas. This rule provides that within metropolitan 
areas, mortgage purchases will count toward the goal when those 
mortgages finance properties that are located in census tracts where 
(1) median income of families in the tract does not exceed 90 
percent of area (MSA) median income or (2) minorities comprise 30 
percent or more of the residents and median income of families in 
the tract does not exceed 120 percent of area median income.
    In this Rule, the underserved census tracts are defined in terms 
of the 2000 Census rather than the 1990 Census. As shown in Table 
B.1a, switching to 2000 Census data and re-specified MSA boundaries 
as of June 2003, increases the proportions of underserved census 
tracts, population, owner-occupied housing units, and population 
below the poverty line in metropolitan areas. The definition now 
covers 26,959 (51.3 percent) of the 52,585 census tracts in 
metropolitan areas, which include 48.7 percent of the population and 
38.0 percent of the owner-occupied housing units in metropolitan 
areas.\1\ The 1990-based definition covered 21,587 (47.5 percent) of 
the 45,406 census tracts in metropolitan areas, which included 44.3 
percent of the population and 33.7 percent of the owner-occupied 
units in metropolitan areas.
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    \1\ This analysis excludes Puerto Rico. In addition, tracts are 
excluded if median income is suppressed in the underlying census 
data. There are 379 such tracts. When reporting analysis of mortgage 
loan denial, origination, and application rates later in this 
appendix, tracts are excluded if there are no purchase or refinance 
applications. Tracts are also excluded if: (1) group quarters 
constitute more than 50 percent of housing units or (2) there are 
less than 15 home purchase applications in the tract and the tract 
denial rates equal 0 or 100 percent. Excluded tracts account for a 
small percentage of mortgage loan applications (1.4 percent). These 
tracts are not excluded from HUD's underserved areas if they meet 
the income and minority thresholds. Rather, the tracts are excluded 
to remove the effects of outliers from the analysis.
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    The census tracts included in HUD's definition of underserved 
areas exhibit low rates of mortgage access and distressed 
socioeconomic conditions. Between 1999 and 2002, the unweighted 
average mortgage denial rate in these tracts was 17.5 percent, 
almost double the average denial rate (9.3 percent) in excluded 
tracts. The underserved tracts include 75.3 percent of the number of 
persons below the poverty line in metropolitan areas.
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    HUD's establishment of this definition is based on a substantial 
number of studies of mortgage lending and mortgage credit flows 
conducted by academic researchers, community groups, the GSEs, HUD 
and other government agencies. As explained in the 2000 Rule, one 
finding stands out from the existing research literature on mortgage 
access for different types of neighborhoods: High-minority and low-
income neighborhoods continue to have higher mortgage denial rates 
and lower mortgage origination rates than other neighborhoods. A 
neighborhood's minority composition and its level of income are 
highly correlated with access to mortgage credit.
    Nonmetropolitan Areas. In nonmetropolitan areas, mortgage 
purchases count toward the Underserved Areas Housing Goal for 
properties which are located in counties where (1) median income of 
families in the county does not exceed 95 percent of the greater of 
(a) state nonmetropolitan median income or (b) nationwide 
nonmetropolitan median income, or (2) minorities comprise 30 percent 
or more of the residents and median income of families in the county 
does not exceed 120 percent of the greater of (a) state 
nonmetropolitan median income or (b) nationwide nonmetropolitan 
median income.
    In 1995, two important factors influenced HUD's definition of 
nonmetropolitan underserved areas--lack of available data for 
measuring mortgage availability in rural areas and lenders' 
difficulty in operating mortgage programs at the census tract level 
in rural areas. Because of these factors, the 1995 Rule (as well as 
the 2000 Rule) used a more inclusive, county-based approach to 
designating underserved portions of rural areas. As discussed in a 
later section, HUD is now proposing to replace the county-based 
definition with a tract-based definition.
    As shown in Table B.1b, switching from 1990 to 2000 Census data 
and incorporating the June, 2003 specification of metropolitan areas 
causes a slight decrease in underserved proportions of counties, 
population, owner-occupied housing units, and poverty population in 
non-metropolitan areas. In terms of the 2000 Census geography and 
June 2003 metropolitan area specification, the definition covers 
1,260 (61.4 percent) of the 2,052 counties in nonmetropolitan areas, 
which include 51.0 percent of the population, 50.7 percent of the 
owner-occupied housing units, and 64.3 percent of the population 
below the poverty level in non-metropolitan areas. The 1990-based 
definition covered 1,514 (65.5 percent) of the 2,311 counties in 
non-metropolitan areas, which included 54.6 percent of the 
population, 53.4 percent of the owner-occupied units, and 67.9 
percent of the poor in non-metropolitan areas.\2\
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    \2\ Kalawao County, Hawaii, which has a very small population, 
is excluded from the analysis for 1990 but included for 2000.

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    Data comparable to that in Table B.1b is presented in Table B.1c 
based on census tracts, rather than counties, in nonmetropolitan 
areas. As indicated, the tract-based definition includes 6,782 (54.9 
percent) of the 12,359 nonmetropolitan census tracts in the country. 
These tracts contain 52.5 percent of the nonmetropolitan population 
(comparable to the 51.0 percent using a county-based definition) and 
50.4 percent of owner-occupied housing units (close to the 
corresponding figure of 50.7 percent under the county-based 
approach). But the tract-based approach better targets families most 
in need, as shown, for example, by the fact that it includes 68.9 
percent of the population in poverty, exceeding the corresponding 
figure of 64.3 percent under the county-based definition of 
nonmetropolitan underserved areas.
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    GSE Performance. Table B.1d shows the increases in the GSEs' 
overall goals performance under the more expansive geography of the 
2000 Census. During 2000, Fannie Mae's performance would have been 
an estimated 37.5 percent if underserved areas were defined in terms 
of 2000 Census geography, compared with 31.0 percent under 1990 
Census geography. Corresponding 2001 figures (adjusted to be 
comparable with the 2000 figures) are 35.7 percent and 30.4 percent. 
The figures for Freddie Mac are 34.1 percent and 29.2 percent for 
2000 performance, and 32.5 percent and 28.2 percent for 2001 
performance. (The 2001 housing goals percentages in the table are 
adjusted to exclude the effects of the bonus points and Freddie 
Mac's Temporary Adjustment Factor, which became applicable in 2001 
for scoring of loans toward the housing goals.)
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    Goal and Subgoal Levels. The Department proposes to establish 
the Underserved Areas Housing Goal as 38 percent of eligible units 
financed for 2005, 39 percent for 2006 and 2007, and 40 percent for 
2008.
    HUD is proposing to establish a subgoal of 33 percent for the 
share of each GSE's total single-family-owner mortgage purchases 
that finance single-family-owner properties located in underserved 
census tracts of metropolitan areas for 2005, with this subgoal 
rising to 34 percent for 2006 and 35 percent for 2007 and 2008. In 
this case, subgoal performance for a particular calendar year would 
be calculated for each GSE by dividing (a) the number of mortgages 
purchased by the GSE that finance single-family-owner properties 
located in underserved areas (i.e., census tracts) of metropolitan 
areas by (b) the number of mortgages purchased by the GSE that 
finance single-family-owner properties located in metropolitan 
areas. As explained in Section H, the purpose of this subgoal is to 
encourage the GSEs to lead the primary market in funding mortgages 
in underserved census tracts.

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

    This section discusses differential access to mortgage funding 
in urban areas and summarizes available evidence on identifying 
those neighborhoods that have historically experienced problems 
gaining access to credit. Section B.1 provides an overview of the 
problem of unequal access to mortgage funding, focusing on 
discrimination and other housing problems faced by minority families 
and the communities where they live. Section B.2 examines mortgage 
access at the neighborhood level and discusses in some detail the 
rationale for the Underserved Areas Housing Goal in metropolitan 
areas. The most thorough studies available provide strong evidence 
that low-income and high-minority census tracts are underserved by 
the mortgage market. Section B.3 presents recent statistics on the 
credit characteristics and socioeconomic characteristics of 
underserved areas under HUD's definition. Readers are referred to 
the expansive literature on this issue, which is reviewed some 
detail in Appendix B of HUD's 2000 Rule. This section focuses on 
some of the main studies and their findings.
    Three main points are made in this section:
     Both borrowers and neighborhoods can be 
identified as currently being underserved by the nation's housing 
and mortgage markets. Appendix A provided evidence of racial 
disparities in the sale and rental of housing and in the provision 
of mortgage credit. Partly as a result of this, the homeownership 
rate for minorities is substantially below that for whites.
     The existence of substantial neighborhood 
disparities in mortgage credit is well documented for metropolitan 
areas. Research has demonstrated that census tracts with lower 
incomes and higher shares of minority population consistently have 
poorer access to mortgage credit, with higher mortgage denial rates 
and lower origination rates for mortgages. Thus, the income and 
minority composition of an area is a good measure of whether that 
area is being underserved by the mortgage market.
     Research supports a targeted neighborhood-
based definition of underservice. Studies conclude that 
characteristics of mortgage loan applicants and the neighborhood 
where the property is located are the major determinants of mortgage 
denial rates and origination rates. Once these characteristics are 
accounted for, other influences, such as location in a central city, 
play only a minor role in explaining disparities in mortgage 
lending.\3\
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    \3\ In this appendix, the term ``central city'' is used to mean 
``OMB-designated central city.''
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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. This section briefly 
reviews evidence on lending discrimination as well as a recent HUD-
sponsored study of discrimination in the housing market.
    Mortgage Denial Rates. A quick look at mortgage denial rates 
reported by Home Mortgage Disclosure Act (HMDA) data reveals that in 
2002 minority denial rates were higher than those for white loan 
applicants. For lower-income borrowers, the denial rate for African 
Americans applying for conventional loans was 2.1 times the denial 
rate for white borrowers, while for higher-income borrowers, the 
denial rate for African Americans was 2.7 times the rate for white 
borrowers.\4\
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    \4\ The actual denial rates were as follows: 23.6 percent for 
low-income (80% AMI or less) African Americans, 15.5 percent for 
upper-income (120% AMI or more) African Americans, 11.4 percent for 
low-income Whites, and 5.6 percent for upper-income Whites. The 
overall denial rate in the conventional conforming home purchase 
market was 9.7 percent in 2002. The data exclude applications to 
lenders that specialize in manufactured home lending.
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    Differentials in denial rates, such as those reported above, are 
frequently used to demonstrate the problems that minorities face 
obtaining access to mortgage credit. However, an important question 
is the degree to which variations in denial rates reflect lender 
bias against certain kinds of borrowers relative to the degree to 
which they reflect the credit quality of potential borrowers (as 
indicated by applicants' available assets, credit rating, employment 
history, etc.). Without fully accounting for the creditworthiness of 
the borrower, racial differences in denial rates cannot be 
attributed to lender bias. Some studies of credit disparities have 
attempted to control for credit risk factors that might influence a 
lender's decision to approve a loan.
    Boston Fed Study. The best example of accounting for credit risk 
is the study of mortgage denial rates by researchers at the Federal 
Reserve Bank of Boston.\5\ This landmark study found that racial 
differentials in mortgage denial rates cannot be fully explained by 
differences in credit risk. To control for credit risk, the Boston 
Fed researchers included 38 borrower and loan variables indicated by 
lenders to be critical to loan decisions. For example, the Boston 
Fed study included a measure of the borrower's credit history, which 
is a variable not included in other studies. The Boston Fed study 
found that minorities' higher denial rates could not be explained 
fully by income and credit risk factors. The denial rate for African 
Americans and Hispanics was 17 percent, compared with 11 percent for 
Whites with similar characteristics. That is, African Americans and 
Hispanics were about 60 percent more likely to be denied credit than 
Whites, even after controlling for credit risk characteristics such 
as credit history, employment stability, liquid assets, self-
employment, age, and family status and composition. Although almost 
all highly-qualified applicants were approved, differential 
treatment was observed among borrowers with more marginal 
qualifications. That is, highly-qualified borrowers of all races 
seemed to be treated equally, but in cases where there was some flaw 
in the application, white applicants seemed to be given the benefit 
of the doubt more frequently than minority applicants. A subsequent 
refinement of the data used by the Federal Reserve Bank of Boston 
confirmed the findings of that study.\6\
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    \5\ Alicia H. Munnell, Lynn E. Browne, James McEneaney, and 
Geoffrey M.B. Tootell, ``Mortgage Lending in Boston: Interpreting 
HMDA Data,'' American Economic Review, March 1996.
    \6\ William C. Hunter, ``The Cultural Affinity Hypothesis and 
Mortgage Lending Decisions,'' WP-95-8, Federal Reserve Bank of 
Chicago, 1995. Hunter confirmed that race was a factor in denial 
rates of marginal applicants. While denial rates were comparable for 
borrowers of all races with ``good'' credit ratings, among those 
with ``bad'' credit ratings or high debt ratios, minorities were 
significantly more likely to be denied than similarly-situated 
whites. The study concluded that the racial differences in denial 
rates were consistent with a cultural gap between white loan 
officers and minority applicants, and conversely, a cultural 
affinity with white applicants.
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    The Boston Fed study, as well as reassessments of that study by 
other researchers, concluded that the effect of borrower race on 
mortgage rejections persists even after controlling for legitimate 
determinants of lenders' credit decisions.\7\

[[Page 24383]]

Thus, these studies imply that variations in mortgage denial rates, 
such as those reported above, are not determined entirely by 
borrower risk, but reflect discrimination in the housing finance 
system. However, the independent race effect identified in these 
studies is still difficult to interpret. In addition to lender bias, 
access to credit can be limited by loan characteristics that reduce 
profitability \8\ and by underwriting standards that have disparate 
effects on minority and lower-income borrowers and their 
neighborhoods.\9\
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    \7\ For a reassessment of the Boston Fed study, see Stephen Ross 
and John Yinger, The Color of Credit, MIT Press 2002, and other 
studies cited there.
    \8\ Since upfront loan fees are frequently determined as a 
percentage of the loan amount, lenders are discouraged from making 
smaller loans in older neighborhoods, because such loans generate 
lower revenue and are less profitable to lenders.
    \9\ Traditional underwriting practices may have excluded some 
lower income families that are, in fact, creditworthy. Such families 
tend to pay cash, leaving them without a credit history. In 
addition, the usual front-end and back-end ratios applied to 
applicants' housing expenditures and other on-going costs may be too 
stringent for lower income households, who typically pay larger 
shares of their income for housing (including rent and utilities) 
than higher income households.
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    Paired-Testing Studies. As discussed in Appendix A, paired 
testing studies of the pre-qualification process have supported the 
findings of the Boston Fed study. Based on a review of paired tests 
conducted by the National Fair Housing Alliance, The Urban Institute 
concluded that differential treatment discrimination at the pre-
application level occurred at significant levels in at least some 
cities. Minorities were less likely to receive information about 
loan products, received less time and information from loan 
officers, and were quoted higher interest rates in most of the 
cities where tests were conducted.\10\ Another Urban Institute study 
used the paired testing methodology to examine the pre-application 
process in Los Angeles and Chicago. African Americans and Hispanics 
faced a significant risk of unequal treatment when they visited 
mainstream mortgage lending institutions to make pre-application 
inquiries.\11\
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    \10\ Margery A. Turner and Felicity Skidmore, eds., Mortgage 
Lending Discrimination: A Review of Existing Evidence, The Urban 
Institute: Washington, DC, June 1999.
    \11\ Margery Austin Turner, All Other Things Being Equal: A 
Paired Testing Study of Mortgage Lending Institutions, The Urban 
Institute Press, April 2002.
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    Sales and Rental Markets. In 2002, HUD released its third 
Housing iscrimination Study (HDS) in the sale and rental of housing. 
The study, entitled Discrimination in Metropolitan Housing Markets: 
National Results from Phase I of the Housing Discrimination Study 
(HDS), was conducted by the Urban Institute.\12\ The results of this 
HDS were based on 4,600 paired tests of minority and non-minority 
home seekers conducted during 2000 in 23 metropolitan areas 
nationwide. The report showed large decreases between 1989 and 2000 
in the level of discrimination experienced by Hispanics and African 
Americans seeking to buy a home. There has also been a modest 
decrease in discrimination toward African Americans seeking to rent 
a unit. This downward trend, however, has not been seen for Hispanic 
renters, who now are more likely to experience discrimination in 
their housing search than are African American renters. But while 
generally down since 1989, the report found that housing 
discrimination still exists at unacceptable levels. The greatest 
share of discrimination for Hispanic and African American home 
seekers can still be attributed to being told units are unavailable 
when they are available to non-Hispanic whites and being shown and 
told about fewer units than a comparable non-minority. Although 
discrimination is down on most areas for African American and 
Hispanic homebuyers, there remain worrisome upward trends of 
discrimination in the areas of geographic steering for African 
Americans and, relative to non-Hispanic whites, the amount of help 
agents provide to Hispanics with obtaining financing. On the rental 
side, Hispanics are more likely in 2000 than in 1989 to be quoted a 
higher rent than their white counterpart for the same unit.
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    \12\ Margery Austin Turner, Stephen L. Ross, George Galster, and 
John Yinger, Discrimination in Metropolitan Housing Markets, The 
Urban Institute Press, November 2002.
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    Another HUD-sponsored study asked respondents to a nationwide 
survey if they ``thought'' they had ever been discriminated against 
when trying to buy or rent a house or an apartment.\13\ While the 
responses were subjective, they are consistent with the findings of 
the HDS. African Americans and Hispanics were considerably more 
likely than whites to say they have suffered discrimination--24 
percent of African Americans and 22 percent of Hispanics perceived 
discrimination, compared to only 13 percent of whites.
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    \13\ How Much Do We Know? Public Awareness of the Nation's Fair 
Housing Laws, prepared for HUD by Martin D. Abravanel and Mary K. 
Cunningham of the Urban Institute, April 2002.
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    Segregation in Urban Areas. Discrimination, while not the only 
cause, contributes to the pervasive level of segregation that 
persists between African Americans and Whites in our urban areas. 
The Census Bureau recently released one of the most exhaustive 
studies of residential segregation ever undertaken, entitled Racial 
and Ethnic Residential Segregation in the United States: 1980-
2000.\14\ The Census Bureau found that the United States was still 
very much racially divided. While African Americans have made modest 
strides, they remain the most highly segregated racial group. The 
authors said that residential segregation likely results from a 
variety of factors, including choices people make about where they 
want to live, restrictions on their choices, or lack of information. 
The fact that many mainstream lenders do not operate in segregated 
areas makes it even more difficult for minorities to obtain access 
to reasonable-priced mortgage credit.\15\ Section C.8 of Appendix A 
cited several studies showing that these inner city neighborhoods 
are often served mainly by subprime lenders. In addition, there is 
evidence that denial rates are higher in minority neighborhoods 
regardless of the race of the applicant. The next section explores 
the issue of credit availability in neighborhoods in more detail.
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    \14\ U.S. Bureau of the Census, August 2002. The co-authors of 
the study were John Iceland and Daniel H. Weinberg. For a summary of 
the study, see ``Residential Segregation Still Prevalent,'' National 
Mortgage News, January 6, 2003, page 1.
    \15\ See Randall M. Scheessele, Black and White Disparities in 
Subprime Mortgage Refinance Lending, Housing Finance Working Paper 
No. HF-114, Office of Policy Development and Research, U.S. 
Department of Housing and Urban Development, April 2002.
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2. Evidence About Access to Credit in Urban Neighborhoods--An 
Overview

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

[[Page 24384]]

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

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

    In its deliberations leading up to FHEFSSA, Congress was 
concerned about geographic redlining--the refusal of lenders to make 
loans in certain neighborhoods regardless of the creditworthiness of 
individual applicants. During the 1980s and early 1990s, a number of 
studies using HMDA data (such as that reported in Tables B.2 and 
B.3, below) attempted to test for the existence of mortgage 
redlining. Consistent with the redlining hypothesis, these studies 
found lower volumes of loans going to low-income and high-minority 
neighborhoods.\16\ However, such analyses were criticized because 
they did not distinguish between demand, risk, and supply effects 
\17\--that is, they did not determine whether loan volume was low 
because families in high-minority and low-income areas were unable 
to afford homeownership and therefore were not applying for mortgage 
loans, or because borrowers in these areas were more likely to 
default on their mortgage obligations, or because lenders refused to 
make loans to creditworthy borrowers in these areas.18 19
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    \16\ These studies, which were conducted at the census tract 
level, typically involved regressing the number of mortgage 
originations (relative to the number of properties in the census 
tract) on characteristics of the census tract including its minority 
composition. A negative coefficient estimate for the minority 
composition variable was often interpreted as suggesting redlining. 
For a discussion of these models, see Eugene Perle, Kathryn Lynch, 
and Jeffrey Horner, ``Model Specification and Local Mortgage Market 
Behavior,'' Journal of Housing Research, Volume 4, Issue 2, 1993, 
pp. 225-243.
    \17\ For critiques of the early HMDA studies, see Andrew Holmes 
and Paul Horvitz, ``Mortgage Redlining: Race, Risk, and Demand,'' 
The Journal of Finance, Volume 49, No. 1, March 1994, pp. 81-99; and 
Michael H. Schill and Susan M. Wachter, ``A Tale of Two Cities: 
Racial and Ethnic Geographic Disparities in Home Mortgage Lending in 
Boston and Philadelphia,'' Journal of Housing Research, Volume 4, 
Issue 2, 1993, pp. 245-276.
    \18\ Like early HMDA studies, an analysis of deed transfer data 
in Boston found lower rates of mortgage activity in minority 
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.
    \19\ Using an analytical approach similar to that of Bradbury, 
Case, and Dunham, Anne Shlay found evidence of fewer mortgage loans 
originated in black census tracts in Chicago and Baltimore. See Anne 
Shlay, ``Not in That Neighborhood: The Effects of Population and 
Housing on the Distribution of Mortgage Finance within the Chicago 
SMSA,'' Social 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.
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    More Comprehensive Tests of the Redlining Hypothesis. Recent 
statistical studies have sought to test the redlining hypothesis by 
more completely controlling for differences in neighborhood risk and 
demand. In these studies, the explanatory power of neighborhood race 
is reduced to the extent that the effects of neighborhood risk and 
demand are accounted for; thus, they do not support claims of 
racially induced mortgage redlining. Many of these studies find that 
the race of the individual borrower is more important than the 
racial composition of the neighborhood. However, these studies 
cannot reach definitive conclusions about redlining because 
segregation in inner cities makes it difficult to distinguish the 
impacts of geographic redlining from the effects of individual 
discrimination. The following are two good examples of these 
studies.
    Holmes and Horvitz examined variations in conventional mortgage 
originations across census tracts in Houston.\20\ Their model 
explaining census-tract variations in mortgage originations included 
the following types of explanatory variables: (a) The economic 
viability of the loan, (b) characteristics of properties in and 
residents of the tract (e.g., house value, income, age distribution 
and education level), (c) measures of demand (e.g., recent movers 
into the tract and change in owner-occupied units between 1980 and 
1990), (d) measures of credit risk (defaults on government-insured 
loans and change in tract house values between 1980 and 1990), and 
(e) the racial composition of the tract, as a test for the existence 
of racial redlining. Most of the neighborhood risk and demand 
variables were significant determinants of the flow of conventional 
loans in Houston. The coefficients of the racial composition 
variables were insignificant, which led Holmes and Horvitz to 
conclude that allegations of redlining in the Houston market could 
not be supported.
---------------------------------------------------------------------------

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

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

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

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

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

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

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

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[[Page 24385]]

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

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

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

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

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

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

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

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

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

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

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

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

[[Page 24386]]

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

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

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

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

c. Conclusions From the Economics Literature About Urban Underserved 
Areas

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

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

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

3. Characteristics of HUD's Underserved Areas

a. Credit Characteristics

    HMDA data provide information on the disposition of mortgage 
loan applications (originated, approved but not accepted by the 
borrower, denied, withdrawn, or not completed) in metropolitan 
areas. HMDA data include the census tract location of the property 
being financed and the race and income of the loan applicant(s). 
Therefore, this is a rich data base for analyzing mortgage activity 
in urban neighborhoods. HUD's analysis using HMDA data for 2002 
shows that high-minority and low-income census tracts have both 
relatively high loan application denial rates and relatively low 
loan origination rates.
    Table B.2 presents mortgage denial and origination rates by the 
minority composition and median income of census tracts in 
metropolitan areas. Two patterns are clear:
     Census tracts with higher percentages of 
minority residents have higher mortgage denial rates and lower 
mortgage origination rates than all-white or substantially-white 
tracts. For example, in 2002 the denial rate for census tracts that 
are over 90 percent minority (20.2 percent) was 2.4 times that for 
census tracts with less than 10 percent minority (8.4 percent).
     Census tracts with lower incomes have higher 
denial rates and lower origination rates than higher income tracts. 
For example, in 2002 mortgage denial rates declined from 22.7 
percent to 6.6 percent as tract income increased from less than 40 
percent of area median income to more than 150 percent of area 
median income.
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    Table B.3 illustrates the interaction between tract minority 
composition and tract income by aggregating the data in Table B.2 
into nine minority and income combinations. The low-minority (less 
than 30 percent minority), high-income (over 120 percent of area 
median) group had a denial rate of 6.5 percent and an origination 
rate of 22.7 loans per 100 owner occupants in 2002. The high-
minority (over 50 percent), low-income (under 90 percent of area 
median) group had a denial rate of 18.3 percent and an origination 
rate of only 13.1 loans per 100 owner occupants. The other groupings 
fall between these two extremes.
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    The advantages of HUD's underserved area definition can be seen 
by examining the minority-income combinations highlighted in Table 
B.3. The sharp differences in denial rates and origination rates 
between the underserved and remaining served categories illustrate 
that HUD's definition delineates areas that have significantly less 
success in receiving mortgage credit. In 2002 underserved areas had 
over one and a half times the average denial rate of served areas 
(14.0 percent versus 8.9 percent) and three-fourths the average 
origination rate per 100 owner occupants (16.0 versus 21.4). HUD's 
definition does not include high-income (over 120 percent of area 
median) census tracts even if they meet the minority threshold. The 
average denial rate (9.9 percent) for high-income tracts with a 
minority share of population over 30 percent is much less than the 
denial rate (14.0 percent) in underserved areas as defined by HUD.
    Figure B.1 compares underserved and served areas within central 
cities and suburbs. First, Figure B.1 shows that HUD's definition 
targets central city neighborhoods that are experiencing problems 
obtaining mortgage credit. The 15.8 percent denial rate in these 
neighborhoods in 2002 was almost twice the 8.0 percent denial rate 
in the remaining areas of central cities. A broad, inclusive 
definition of ``central city'' that includes all areas of all 
central cities would include these ``remaining'' portions of cities. 
Figure B.1 shows that these areas, which account for approximately 
36 percent of the population in central cities, appear to be well 
served by the mortgage market. As a whole, they are not experiencing 
problems obtaining mortgage credit.
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    Second, Figure B.1 shows that HUD's definition also targets 
underserved census tracts in the suburbs as well as in central 
cities. The average denial rate in underserved suburban areas (13.7 
percent) is 1.7 times that in the remaining served areas of the 
suburbs (8.0 percent), and is almost as large as the average denial 
rate (15.8 percent) in underserved central city tracts. Low-income 
and high-minority suburban tracts appear to have credit problems 
similar to their central city counterparts. These suburban tracts, 
which account for 34 percent of the suburban population, are 
included in HUD's definition of other underserved areas.

b. Socioeconomic Characteristics

    The targeted nature of HUD's definition can be seen from the 
data presented in Table B.4, which show that families living in 
tracts within metropolitan areas that are underserved based on HUD's 
definition experience much more economic and social distress than 
families living in served areas. For example, the poverty rate in 
underserved census tracts is 18.5 percent, or over three times the 
poverty rate (5.7 percent) in served census tracts. The unemployment 
rate and the high-school dropout rate are also higher in underserved 
areas. In addition, there are nearly three times more female-headed 
households with children in underserved areas (30.0 percent) than in 
served areas (13.2 percent). Three-fourths of units in served areas 
are owner-occupied, while only one-half of units in underserved 
areas are owner-occupied.
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C. Consideration of Factors 1 and 2 in Nonmetropolitan Areas: The 
Housing Needs of Underserved Rural Areas and the Housing, Economic, and 
Demographic Conditions in Underserved Rural Areas

    Based on discussions with rural lenders in 1995, the definition 
of underserved rural areas was established at the county level, 
since such lenders usually do not make distinctions on a census 
tract basis. A nonmetropolitan county is classified as an 
underserved area if median income of families in the county does not 
exceed 95 percent of the greater of state nonmetropolitan or 
national nonmetropolitan median income, or minorities comprise 30 
percent or more of the residents and the median income of families 
in the county does not exceed 120 percent of the greater of state 
nonmetropolitan or national nonmetropolitan median income. For 
nonmetropolitan areas the median income component of the underserved 
definition is broader than that used for metropolitan areas. While 
tract income is compared with area income for metropolitan areas, in 
rural counties income is compared with the greater of state 
nonmetropolitan income and national nonmetropolitan income. This is 
based on HUD's analysis of 1990 census data, which indicated that 
comparing county nonmetropolitan income only to state 
nonmetropolitan income would lead to the exclusion of many lower-
income low-minority counties from the definition, especially in 
Appalachia. Based on 1990 census geography, underserved counties 
account for 57 percent (8,091 of 14,419) of the census tracts and 54 
percent of the population in rural areas. By comparison, the 
definition of metropolitan underserved areas encompassed 47 percent 
of metropolitan census tracts and 44 percent of metropolitan 
residents.
    The purchasing of loans from underserved areas by the GSEs is 
intended to induce greater homeownership among moderate, low, very 
low income, and poor families and minorities. For various reasons, 
including creditworthiness and lending discrimination, these groups 
experience greater difficulty in securing loans under fair and 
reasonable terms and in buying decent and affordable housing, and it 
is for them that the geographic goals were designed. The geographic 
goals, then, are meant to target places where these ``underserved'' 
populations live in order to stimulate local mortgage lending and, 
it is hoped, the availability of credit to those families who reside 
there who, otherwise, will have difficulty securing credit. This 
section addresses the basic question of whether and the extent to 
which HUD's definition of underservice in nonmetropolitan areas 
effectively targets areas that encompass large populations of 
socially and economically disadvantaged families.
    Table B.5 shows data on demographic and socioeconomic conditions 
of underserved and served nonmetropolitan areas based on HUD's 
definition applied at the county level using Census 2000 data. (A 
later section considers the effects of applying the definition of 
the census tract level.) Several variables are used to describe area 
demographic and socioeconomic conditions.
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    On the national level, a few key results show that the 1995 
definition of underservice captures a potentially disadvantaged 
segment of the population. In examining the minority composition, 
one can see that the percentage of African Americans, Hispanics/
Latinos, and total minority population is higher in underserved 
nonmetropolitan areas as compared to served nonmetropolitan areas. 
Overall, the minority population of underserved areas is 25.8 
percent as compared with 9.3 percent in served areas. Other 
supporting results include median family income, poverty rate, 
unemployment rate, school dropout rate, and in-migration rate. 
Specifically we find:
     Median income is approximately $10,000 less 
in underserved areas than in served areas. This represents an 
average gap of 25 percent.
     Poverty in underserved areas is twice the 
rate in served areas (14.5 vs. 7.5 percent).
     Unemployment is 7.3 percent in underserved 
areas and 5.2 percent in served areas.
     The school dropout rate is 28.1 percent in 
underserved areas and 18.7 percent in served areas.
     Migration into underserved areas is somewhat 
lower than in served areas: 7.4 vs. 8.0 percent.
    Table B.5 also includes data on homeownership rates, housing 
affordability, housing quality, and overcrowding. On several of 
these dimensions, housing conditions and needs in underserved areas 
are not substantially worse than in served areas. Although housing 
quality and crowding appear to be marginally worse in underserved 
areas, homeownership in the two areas is about the same and owning a 
home actually appears to be more affordable in underserved areas 
than in served areas. Specific findings include the following:
     Homeownership is slightly higher in 
underserved than in served nonmetropolitan counties: 74.3 percent 
vs. 73.7 percent. Removing manufactured homes lowers ownership rates 
slightly, because ownership of such homes is relatively high, but 
this does not affect the basic result.
     Owner-occupied and rental vacancy rates are 
both somewhat higher in underserved areas.
     Median housing unit values are significantly 
lower in underserved areas: $67,358 vs. $88,099.
     The value of a housing affordability index 
for owner-occupied housing is slightly higher in underserved 
areas.\36\ On average, median income is 1.83 times higher than 
income required to qualify to buy a home of median value in 
underserved areas. The comparable factor for served areas is 1.78.
---------------------------------------------------------------------------

    \36\ The purchase affordability index assesses the extent to 
which a family with the median income of a given area would be able 
to afford a housing unit that carries the median purchase price of 
that area. For example, a purchase affordability index number less 
than 100 means that a family with the median income would not 
qualify for a mortgage on a unit with the median value; a purchase 
affordability index equal to 100 means that a family with the median 
income has exactly the level of income needed to qualify for a 
mortgage on a unit with the median value; and an index number 
greater than 100 means that a family with the median income has 20 
percent more than the level of income needed to qualify for a 
mortgage on a unit with the median value. The rental affordability 
index is similarly constructed.
---------------------------------------------------------------------------

     Rental affordability is approximately the 
same in underserved and served areas.
     While nearly all housing in served and 
underserved areas have complete plumbing and kitchens, the 
percentage of units with incomplete facilities in underserved is 
twice the percentage in served areas.
     Crowded units are a small share of all 
housing in nonmetropolitan areas, but the rate is higher for 
underserved areas: 4.3 vs. 2.3 percent.
    Mikesell \37\ found using the 1995 American Housing Survey that 
while the rate of homeownership in nonmetropolitan areas is higher 
than metropolitan areas, the quality of housing is lower as compared 
to metropolitan areas. Results based on the 2000 Census show that 
the homeownership rate for nonmetropolitan areas was 74 percent (73 
percent without manufactured homes), and for metropolitan areas it 
was 64 percent, but both metropolitan and nonmetropolitan areas had 
approximately 97.5 percent of units with complete plumbing and 99 
percent with complete kitchens.
---------------------------------------------------------------------------

    \37\ J.J. Mikesell, ``Housing Problems across Types of rural 
Households'', Rural Conditions and Trends, Volume 9, Number 2, pp. 
97-101, 1999.
---------------------------------------------------------------------------

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

    Section D.1 reports the past performance of each GSE with regard 
to the Underserved Areas Housing Goal. Section D.2 then examines the 
role that the GSEs are playing in funding single-family mortgages in 
underserved urban neighborhoods based on HUD's analysis of GSE and 
HMDA data. That section also discusses an underserved area subgoal 
for home purchase loans. Section D.3 concludes this section with an 
analysis of the GSEs' purchases in rural (nonmetropolitan) areas.
    The increased coverage of the Underserved Areas Housing goal due 
to switching to 2000 census geography is discussed throughout this 
section.

1. Past Performance of the GSEs

    This section discusses each GSE's performance under the 
Underserved Areas Housing Goal over the 1996-2002 period.\38\ As 
explained in Appendix A, the data presented are 'official HUD 
results' which, in some cases, differ from goal performance reported 
by the GSEs in the Annual Housing Activities Reports (AHARs) that 
they submit to the Department.
---------------------------------------------------------------------------

    \38\ Performance for the 1993-95 period was discussed in the 
October 2000 rule.
---------------------------------------------------------------------------

    The main finding of this section is that both Fannie Mae and 
Freddie Mac surpassed the Department's Underserved Areas Housing 
Goals for each of the seven years during this period. Specifically:
     The goal was set at 21 percent for 1996; 
Fannie Mae's performance was 28.1 percent and Freddie Mac's 
performance was 25.0 percent.
     The goal was set at 24 percent for 1997-2000. 
Fannie Mae's performance was 28.8 percent in 1997, 27.0 percent in 
1998, 26.8 percent in 1999, and 31.0 percent in 2000; and Freddie 
Mac's performance was 26.3 percent in 1997, 26.1 percent in 1998, 
27.5 percent in 1999, and 29.2 percent in 2000.
     In the October 2000 rule, the underserved 
areas goal was set at 31 percent for 2001-03. As of January 1, 2001, 
several changes in counting requirements came into effect for the 
undeserved areas goal, as follows: ``bonus points'' (double credit) 
for purchases of goal-qualifying mortgages on small (5-50 unit) 
multifamily properties and, above a threshold level, mortgages on 2-
4 unit owner-occupied properties; a ``temporary adjustment factor'' 
(1.20 units credit, subsequently increased by Congress to 1.35 units 
credit) for Freddie Mac's purchases of goal-qualifying mortgages on 
large (more than 50-unit) multifamily properties; and eligibility 
for purchases of certain qualifying government-backed loans to 
receive goal credit. These changes are explained below. Fannie Mae's 
performance was 32.6 percent in 2001 and 32.8 percent in 2002, and 
Freddie Mac's performance was 31.7 percent in 2001 and 31.9 percent 
in 2002, thus both GSEs surpassed this higher goal in both years. 
This section discusses the October 2000 counting rule changes in 
detail below, and provides data on what goal performance would have 
been in 2001-02 without these changes.\39\
---------------------------------------------------------------------------

    \39\ To separate out the effects of changes in counting rules 
that took effect in 2001, this section also compares performance in 
2001 to estimated performance in 2000 if the 2001 counting rules had 
been in effect in that year.
---------------------------------------------------------------------------

a. Performance on the Underserved Areas Housing Goal in 1996-2002

    HUD's December 1995 rule specified that in 1996 at least 21 
percent of the number of units financed by each of the GSEs that 
were eligible to count toward the Underserved Areas Goal should 
qualify as units in properties located in underserved areas, and at 
least 24 percent should qualify in 1997-2000. HUD's October 2000 
rule made various changes in the goal counting rules, as discussed 
below, and increased the Underserved Areas Goal to 31 percent for 
2001-03.
    Table B.6 shows performance on the underserved areas goal over 
the 1996-2002 period, based on HUD's analysis. The table shows that 
Fannie Mae surpassed the goals by 7.1 percentage points and 4.8 
percentage points in 1996 and 1997, respectively, while Freddie Mac 
surpassed the goals by narrower margins, 4.0 and 2.3 percentage 
points. In 1998 Fannie Mae's performance fell by 1.8 percentage 
points, while Freddie Mac's performance fell only slightly, by 0.2 
percentage point. Freddie Mac showed a gain in performance to 27.5 
percent in 1999, exceeding its previous high by 1.2 percentage 
points. Fannie Mae's performance in 1999 was 26.8 percent, which, 
for the first time, slightly lagged Freddie Mac's performance in 
that year.
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    Both GSEs exhibited sharp gains in goal performance in 2000--
Fannie Mae's performance increased by 4.2 percentage points, to a 
record level of 31.0 percent, while Freddie Mac's performance 
increased somewhat less, by 1.7 percentage points, which also led to 
a record level of 29.2 percent. Fannie Mae's performance was 32.6 
percent in 2001 and 32.8 percent in 2002; Freddie Mac's performance 
was 31.7 percent in 2001 and 31.9 percent in 2002. However, as 
discussed below, using consistent accounting rules for 2000-02, 
under one method each GSE's performance in 2001-02 was below its 
performance in 2000.
    The official figures for underserved areas goal performance 
presented above for 1996-2002 are the same as the corresponding 
figures presented by Freddie Mac in its Annual Housing Activity 
Reports to HUD for every year except 1999 and 2002, when there was a 
difference of 0.1 percentage point. The official figures are the 
same as those presented by Fannie Mae in most years, and differ by 
0.1-0.2 percentage point in the other years, reflecting minor 
differences in the application of counting rules.
    Fannie Mae's performance on the underserved areas goal surpassed 
Freddie Mac's in every year through 1998. This pattern was reversed 
in 1999, as Freddie Mac surpassed Fannie Mae in goal performance for 
the first time, though by only 0.7 percentage point. This improved 
relative performance of Freddie Mac was due to its increased 
purchases of multifamily loans, as it re-entered that market, and to 
increases in the goal-qualifying shares of its single-family 
mortgage purchases. However, Fannie Mae's performance once again 
exceeded Freddie Mac's performance in 2000, 31.0 percent to 29.2 
percent. Fannie Mae's official performance also exceeded Freddie 
Mac's official performance in 2001-02, despite the fact that Freddie 
Mac benefited from a difference in the counting rules applicable to 
the two GSEs that was enacted by Congress; if the same counting 
rules were applied to both GSEs, Fannie Mae's performance would have 
exceeded Freddie Mac's performance by an even greater margin, and in 
fact Freddie Mac would have just attained the goal, at 31.0 percent, 
in 2002, and fallen short of the goal in 2001.

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

    Several changes in the counting rules underlying the calculation 
of underserved areas goal performance took effect beginning in 2001. 
These also applied to the low- and moderate-income goal and are 
discussed in Appendix A; only brief summaries of those changes are 
given here:\40\
---------------------------------------------------------------------------

    \40\ Unlike the low- and moderate-income and special affordable 
goals, there is no exclusion of units from the denominator for units 
with missing information about the area in which a property is 
located. That is, such units are counted in the denominator, but not 
in the numerator, in determining undeserved area goal performance.
---------------------------------------------------------------------------

    Bonus points for multifamily and single-family rental 
properties. Each qualifying unit in a small multifamily property 
counted as two units in the numerator in calculating performance on 
all of the goals for 2001-03. And, above a threshold equal to 60 
percent of the average number of qualifying rental units financed in 
owner-occupied properties over the preceding five years, each unit 
in a 2-4 unit owner-occupied property also counted as two units in 
the numerator in calculating goal performance.
    Freddie Mac's Temporary Adjustment Factor. Freddie Mac received 
a ``Temporary Adjustment Factor'' of 1.35 units of credit for each 
qualifying unit financed in ``large'' multifamily properties (i.e., 
those with 51 or more units) in the numerator in calculating its 
performance on the housing goals for 2001-03.\41\ This factor did 
not apply to units in large multifamily properties in underserved 
areas whose mortgages were financed by Fannie Mae during this 
period.
---------------------------------------------------------------------------

    \41\ See Congressional Record, December 15, 2000, pp. H12295-96.
---------------------------------------------------------------------------

    Purchases of certain government-backed loans. Prior to 2001, 
purchases of government-backed loans were not taken into account in 
determining performance on the GSEs' low- and moderate-income and 
underserved area housing goals. As discussed in Appendix A, the 2000 
rule established eligibility for FHA-insured home equity conversion 
mortgages (HECMs) for mortgagors in underserved areas, purchases of 
mortgages on properties on tribal lands insured under FHA's Section 
248 program or HUD's Section 184 program, and purchases of mortgages 
under the Rural Housing Service's Single Family Housing Guaranteed 
Loan Program to count toward the underserved area goal.

c. Effects of Changes in the Counting Rules on Goal Performance

    Because of the changes in the underserved areas goal counting 
rules that took effect in 2001, direct comparisons between official 
goal performance in 2000 and 2001-02 are somewhat of an ``apples-to-
oranges comparison.'' For this reason, the Department has calculated 
what performance would have been in 2000 under the 2001-03 rules; 
this may compared with official performance in 2001-02--an ``apples-
to-apples comparison.'' HUD has also calculated what performance 
would have been in 2001-02 under the 1996-2000 rules; this may be 
compared with official performance in 2000--an ``oranges-to-oranges 
comparison.'' These comparisons are presented in Table B.7a.
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    Specifically, Table B.7a shows performance under the underserved 
areas goal in three ways. Baseline A represents the counting rules 
in effect in 1996-2000. Baseline B incorporates the one minor 
technical change in counting rules pertaining to the underserved 
areas goal'' eligibility of certain government-backed loans for 
goals credit. Baseline C incorporates in addition to that technical 
change the bonus points and, for Freddie Mac, the temporary 
adjustment factor. Baseline B corresponds to the counting approach 
proposed in this rule to take effect in 2005. Boldface figures under 
Baseline A for 1999-2000 and under Baseline C for 2001-02 indicate 
official goal percentages based on the counting rules in effect in 
those years'e.g., for Freddie Mac, 27.5 percent in 1999, 29.2 
percent in 2000, 31.7 percent in 2001, and 31.8 percent in 2002.
    Performance on the Underserved Areas Goal under 1996-2000 
Counting Rules Plus Technical Changes. If the ``Baseline B'' 
counting approach had been in effect in 2000-02 and the GSEs' had 
purchased the same mortgages that they actually did purchase in 
those years, Fannie Mae would have just matched the underserved 
areas goal in 2000 and fallen short in 2001-02, while Freddie Mac 
would have fallen short of the goal in all three years, 2000-02. 
Specifically, Fannie Mae's performance would have been 31.0 percent 
in 2000, 30.4 percent in 2001, and 30.1 percent in 2002. Freddie 
Mac's performance would have been 29.2 percent in 2000, 28.2 percent 
in 2001, and 28.4 percent in 2002.
     Performance on the Underserved Areas Goal under 2001-2003 
Counting Rules. If the 2001-03 counting rules had been in effect in 
2000-02 and the GSEs had purchased the same mortgages that they 
actually did purchase in those years (i.e., abstracting from any 
behavioral effects of ``bonus points,'' for example), both GSEs 
would have surpassed the underserved areas goal in all three years, 
and both GSEs' performance figures would have increased from 2000 to 
2002. Specifically, Fannie Mae's ``Baseline C'' performance would 
have been 32.3 percent in 2000, 32.6 percent in 2001, and 32.8 
percent in 2002. Freddie Mac's performance would have been 31.4 
percent in 2000, 31.7 percent in 2001, and 31.8 percent in 2002. 
Measured on this consistent basis, then, Fannie Mae's performance 
increased by 0.3 percentage point in 2001 and 0.2 percentage point 
in 2002, and Freddie Mac's performance increased by 0.4 percentage 
point in 2001 and 0.2 percentage point in 2002. These increases were 
the effect of increased activity in mortgages eligible to receive 
bonus points between 2000 and 2001-02.
    Details of Effects of Changes in Counting Rules on Goal 
Performance in 2001. As discussed above, counting rule changes that 
took effect in 2001 had significant impacts on the performance of 
both GSEs on the underserved areas goal in that year--2.4 percentage 
points for Fannie Mae, and 3.5 percentage points for Freddie Mac. 
This section breaks down the effects of these changes on goal 
performance for both GSEs; results are shown in Table B.7a along 
with figures for other years.
    Freddie Mac. The largest impact of the counting rule changes on 
Freddie Mac's goal performance was due to bonus points for purchases 
of mortgages on small multifamily properties; this added 1.3 
percentage points to goal performance in 2001 and 1.0 percentage 
points in 2002, as shown in Table B.7. The application of the 
temporary adjustment factor for purchases of mortgages on large 
multifamily properties enacted by Congress added 0.9 percentage 
points to goal performance in 2002. Bonus points for purchase of 
mortgages on owner-occupied 2-4 unit rental properties also added 
1.1 percentage points to performance. Credit for purchases of 
qualifying government-backed loans played a minor role in 
determining Freddie Mac's goal performance.
    Fannie Mae. The temporary adjustment factor which applied to 
Freddie Mac's goal performance did not apply to Fannie Mae, thus 
counting rule changes had less impact on its performance than on 
Freddie Mac's performance in 2002. The largest impact of the 
counting rule changes on Fannie Mae's goal performance was due to 
the application of bonus points for purchases of mortgages on owner-
occupied 2-4 unit rental properties, which added 1.8 percentage 
points to performance, and for purchases of mortgages on small 
multifamily properties, which added 0.8 percentage point to 
performance. Credit for purchases of qualifying government-backed 
loans played a minor role in determining Fannie Mae's goal 
performance.

d. Bonus Point Incentives for the GSEs' Purchases in Underserved Areas

    The Department established ``bonus points'' for 2001-03 to 
encourage the GSEs to step up their activity in two segments of the 
mortgage market'the small (5-50 unit) multifamily mortgage market, 
and the market for mortgages on 2-4 unit properties where 1 unit is 
owner-occupied and 1-3 units are occupied by renters.
    Bonus points for small multifamily properties. Each unit 
financed in a small multifamily property that qualified for any of 
the housing goals was counted as two units in the denominator (and 
one unit in the numerator) in calculating goal performance for that 
goal.
    Fannie Mae financed 37,389 units in small multifamily properties 
in 2001 that were eligible for the underserved areas goal, an 
increase of more than 400 percent from the 7,196 units financed in 
2000. As explained in Appendix A, small multifamily properties also 
accounted for a greater share of Fannie Mae's multifamily business 
in 2001--7.4 percent of total multifamily units financed, up from 
2.5 percent in 2000. However, HUD's Housing Goals 2000 Final Rule 
cited a Residential Finance Survey finding that small multifamily 
properties account for 37 percent of total units in multifamily 
mortgaged properties, thus Fannie Mae is still less active in this 
market than in the market for large multifamily properties.\42\
---------------------------------------------------------------------------

    \42\ 65 FR 65141 & n. 145 (2000).
---------------------------------------------------------------------------

    Within the small multifamily market, there was some evidence 
that Fannie Mae targeted properties in underserved areas to a 
greater extent in 2001 than in 2000. That is, 56 percent of Fannie 
Mae's small multifamily units qualified for the underserved areas 
goal in 2000, but this rose to 64 percent in 2001.
    Freddie Mac financed 50,211 units in small multifamily 
properties in 2001 that were eligible for the underserved areas 
goal, an increase of more than 1500 percent from the a small base of 
2,985 units financed in 2000. Small multifamily properties also 
accounted for a significantly greater share of Freddie Mac's 
multifamily business in 2001--16.1 percent of total multifamily 
units financed, up from 1.8 percent in 2000.
    Within the small multifamily market, there was some evidence 
that Freddie Mac targeted properties in underserved areas to a 
greater extent in 2001 than in 2000. That is, 61 percent of Freddie 
Mac's small multifamily units qualified for the underserved areas 
goal in 2000; this rose to 86 percent in 2001.
    Bonus points for single-family rental properties. Above a 
threshold, each unit financed in a 2-4 unit property with at least 
one owner-occupied unit (referred to as ``OO24s'' below) that 
qualified for any of the housing goals was counted as two units in 
the denominator (and one unit in the numerator) in calculating goal 
performance for that goal in 2001-03. The threshold was equal to 60 
percent of the average number of such qualifying units over the 
previous five years. For example, Fannie Mae financed an average of 
47,100 underserved area units in these types of properties between 
1996 and 2000, and 105,946 such units in 2001. Thus in 2001 Fannie 
Mae received 77,688 bonus points in this area in 2001--that is, 
105,946 minus 60 percent of 47,100. So 183,629 units were entered in 
the numerator for these properties in calculating underserved area 
goal performance.
    Single-family rental bonus points thus encouraged the GSEs to 
play a larger role in this market, and also to purchase mortgages on 
such properties in which large shares of the units qualify for the 
housing goals. As for small multifamily bonus points, some evidence 
on the effects of such bonus points on the GSEs' operations may be 
gleaned from the data provided to HUD by the GSEs for 2001.
    Fannie Mae financed 177,872 units in OO24s in 2001 that were 
eligible for the underserved areas goal, an increase of 116 percent 
from the 82,464 units financed in 2000. However, Fannie Mae's total 
single-family business increased at approximately the same rate as 
its OO24 business in 2001, thus the share of its business accounted 
for by OO24s was the same in 2001 as in 2000--4 percent.
    Within the OO24 market, there was no evidence that Fannie Mae 
targeted affordable properties to a greater extent in 2001 than in 
2000. That is, approximately 60 percent of Fannie Mae's OO24 units 
qualified for the underserved area goal in both 2000 and 2001.
    Freddie Mac financed 96,983 units in OO24s in 2001 that were 
eligible for the underserved areas goal, an increase of 91 percent 
from the 50,868 units financed in 2000. However, Freddie Mac's total 
single-family business increased at approximately the same rate as 
its OO24 business in 2001, thus the share of its business accounted 
for

[[Page 24401]]

by OO24s was the same in 2001 as in 2000--3 percent.
    As for Fannie Mae, within the OO24 market there was no evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001 than in 2000. That is, 60 percent of Fannie Mae's OO24 units 
qualified for the underserved areas goal in both 2000 and 2001.

e. Effects of 2000 Census on Scoring of Loans Toward the Underserved 
Areas Housing Goal

    Background. Scoring of housing units under the Underserved Areas 
Housing Goal is based on decennial census data used to identify 
underserved areas, as follows: For properties in MSAs scoring is 
based on the median income of the census tract where the property is 
located, the median income of the MSA, and the percentage minority 
population in the census tract where the property is located. For 
properties located outside of MSAs scoring is based on the median 
income of the county, the median income of the non-metropolitan 
portion of the State in which the property is located or of the non-
metropolitan portion of the United States, whichever has the larger 
median income, and the percentage minority population in the county 
where the property is located. Thus, scoring loans under the 
Underserved Areas Housing Goal requires decennial census data on 
median incomes for metropolitan census tracts, MSAs, non-
metropolitan counties, the non-metropolitan portions of States, and 
the non-metropolitan portion of the United States. The determination 
has been based on 1990 census data through 2004, and beginning in 
2005 will be based on 2000 census data.43 44 Under HUD's 
proposal, the basis for the determination outside of MSAs will 
change from counties to census tracts beginning in 2005.
---------------------------------------------------------------------------

    \43\ In New England, MSAs were defined through mid-2003 in terms 
of Towns rather than Counties, and the portion of a New England 
county outside of any MSA is regarded as equivalent to a county in 
establishing the metropolitan or non-metropolitan location of a 
property. The MSA definitions established by the Office of 
Management and Budget (OMB) in June, 2003 defined MSAs in New 
England in terms of counties.
    \44\ The procedure used to generate estimated rents in 
connection with Low- and Moderate Income and Special Affordable 
Housing Goals, as mentioned in Appendixes A and C, uses similar data 
series.
---------------------------------------------------------------------------

    2005 Procedure. Relative to the above procedure, Underserved 
Areas Housing Goals performance percentages for loans purchased by 
the GSEs in and after 2005 will be affected by three factors. First, 
2000 census data on median incomes and minority populations replace 
1990 census data. Second, the Office of Management and Budget in 
June, 2003, respecified MSA boundaries based on analysis of 2000 
census data. Third, the Department's proposed re-specification of 
the Underserved Areas goal in terms of census tracts rather than 
counties in non-metropolitan areas will come into effect.\45\ Thus, 
for properties located outside of MSAs the basis of determination 
for non-metropolitan areas will be changed for properties located 
outside of MSAs to: The median income of the census tract where the 
property is located; the median income of the non-metropolitan 
portion of the State in which the property is located or of the non-
metropolitan portion of the United States, whichever is larger; and 
the percentage minority population in the census tract where the 
property is located.
---------------------------------------------------------------------------

    \45\ HUD has deferred application of the 2000 census data and 
2003 MSA designations to 2005, pending completion of the present 
rulemaking process.
---------------------------------------------------------------------------

    Analysis. HUD used 2000 census data to generate underserved area 
designations for census tracts as defined for the 2000 census with 
2003 MSA designations. Because Fannie Mae and Freddie Mac geocoded 
the mortgages they purchased prior to 2003 based on census tract 
boundaries as established for the 1990 census, GSE mortgages 
purchased prior to 2003 can be directly identified as being from a 
served or underserved area only where the property is located in a 
1990-defined census tract whose area consists entirely of whole 
2000-defined census tracts, or portions of such tracts, which are 
all designated either as served or as underserved. In the situation 
where the area of a 1990-defined census tract includes whole 2000-
defined census tracts, or portions of such tracts, some of which are 
served and some underserved, HUD calculated an ``underservice 
factor'' defined as the underserved percentage of the 1990-defined 
tract's population, based on population data from the 2000 
census.\46\ These factors were used in estimating underservice 
percentages for aggregated GSE purchases in and before 2002 based on 
the 2000 census.
---------------------------------------------------------------------------

    \46\ 8,717 tracts included both served and underserved area, out 
of a total of 61,493 tracts that could be classified as served or 
underserved or assigned an underservice factor.
---------------------------------------------------------------------------

    The resulting underserved areas file was used to re-score loans 
purchased by the GSEs between 1999 and 2002, and was used further in 
estimating the share of loans originated in metropolitan areas that 
would be eligible to score toward the Underserved Areas Housing 
Goal, from HMDA data. The results of the retrospective GSE analysis 
are provided in Table B.7b. The results of the GSE-HMDA comparative 
analysis are presented in the next section.
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    Table B.7b shows four sets of estimates for each GSE, based 
respectively on the counting rules in place in 2001-2002 (but 
disregarding the bonus points and Temporary Adjustment Factor), on 
shifting from 1990 to 2000 census data on median incomes and 
minority concentrations, on the further addition 2003 MSA 
specification, and finally on shifting from counties to tracts as 
the basis for scoring loans in non-metropolitan areas.

2. GSEs' Mortgage Purchases in Metropolitan Neighborhoods

    Metropolitan areas accounted for about 85 percent of total GSE 
purchases under the Underserved Areas Housing Goal in 2001 and 2002. 
This section uses HMDA and GSE data for metropolitan areas to 
examine the neighborhood characteristics of the GSEs' mortgage 
purchases. In subsection 2.a, the GSEs' performance in underserved 
neighborhoods is compared with the overall market. This section 
therefore expands on the discussion in Appendix A, which compared 
the GSEs' funding of affordable loans with the overall conventional 
conforming market. A subgoal that the Department is establishing for 
each GSE's acquisitions of home purchase loans financing properties 
in the underserved census tracts of metropolitan areas is also 
discussed subsection 2.a. In subsection 2.b., the characteristics of 
the GSEs' purchases within underserved areas are compared with those 
for their purchases in served areas.

a. Comparisons With the Primary Market

    Market Comparisons Based on 1990 Census Geography. Section E.8-
10 in Appendix A provided detailed information on the GSEs' funding 
of mortgages for properties located in underserved neighborhoods for 
the years 1993 to 2002. To take advantage of historical data going 
back to 1993, these comparisons were first made using 1990 Census 
tract geography. The findings with respect to the GSEs' funding of 
underserved neighborhoods are similar to those reported in Appendix 
A regarding the GSEs' overall affordable lending performance in the 
single-family-owner market. While both GSEs improved their 
performance, they historically lagged the conventional conforming 
market in providing affordable loans to underserved neighborhoods. 
The two GSEs themselves engaged in very different patterns of 
funding--Freddie Mac was less likely than Fannie Mae to fund home 
loans in underserved neighborhoods, as the following percentage 
shares for home purchase loans indicate:

----------------------------------------------------------------------------------------------------------------
                                                     Freddie Mac           Fannie Mae         Market  (w/o B&C)
                     Year                       (percent)  (percent)  (percent)
----------------------------------------------------------------------------------------------------------------
1996-2002.....................................              21.7                  23.5                  25.4
1999-2002.....................................              22.9                  24.0                  25.8
2001-2002.....................................              24.1                  25.6                  25.9
----------------------------------------------------------------------------------------------------------------

Between 1996 and 2002, 21.7 percent of Freddie Mac's purchases 
financed properties in underserved neighborhoods, compared with 23.5 
percent of Fannie Mae's purchases and 25.4 percent of home purchase 
loans originated in the conventional conforming market (excluding 
B&C loans). Thus, Freddie Mac performed at only 85 percent of the 
market (21.7 divided by 25.4), while Fannie Mae performed at 93 
percent of the market. Freddie Mac's recent performance has been 
slightly closer to the market. Over the past four years (1999 to 
2002), Freddie Mac performed at 89 percent of the market (22.9 
percent for Freddie Mac compared with 25.8 percent for the market), 
and in 2001 and 2002, the first two years under HUD's higher housing 
goal targets, at 93 percent of the market (24.1 percent compared 
with 25.9 percent). (See Tables A.13 to A.16 in Appendix A for 
complete data going back to 1993.)
    Fannie Mae has funded underserved areas at a higher level than 
Freddie Mac, as indicated above. And during 2001 and 2002, Fannie 
Mae average performance was only slightly below the market. The 
share of Fannie Mae's purchases going to underserved areas was 24.4 
percent in 2001 to 26.7 percent in 2002, compared with market levels 
of 25.2 percent and 26.4 percent, respectively. However, like 
Freddie Mac, Fannie Mae's longer-term performance (since 1993 or 
1996) as well as its recent average performance (1999 to 2002) has 
consistently been below market levels. Over the past four years, 
Fannie Mae performed at 93 percent of the market (24.0 percent for 
Fannie Mae compared with 25.8 percent for the market). Still, it is 
encouraging that Fannie Mae significantly improved its performance 
and closed its gap with the market during the first two years of 
HUD's higher housing goal levels.
    Market Comparisons Based on 2000 Census Geography. As explained 
in Section A.2 of this appendix, HUD will be defining underserved 
areas based on 2000 Census data and re-specified metropolitan area 
boundaries beginning in 2005, the first year covered by the proposed 
rule. The number of census tracts in metropolitan areas covered by 
HUD's definition will increase from 21,587 tracts (based on 1990 
Census) to 26,959 tracts (based on 2000 Census and new OMB 
metropolitan area specifications). The increase in the number of 
tracts defined as underserved means that both GSE performance and 
the market estimates will be higher than reported above. This 
section provides an analysis of the performance of the GSEs in the 
single-family-owner market based on 2000 census tract geography. For 
the years 1999, 2000, 2001, and 2002, HUD used the apportionment 
technique described above involving ``underservice factors'' to re-
allocate 1990-based GSE and HMDA data into census tracts as defined 
by the 2000 Census.
    The main results are provided in Table B.8, which compares the 
GSEs to the market using both the 1990 Census geography and the 2000 
Census geography. Switching to the 2000-based tracts increases the 
underserved area share of market originations by nearly six 
percentage points. Between 1999 and 2002, 31.5 percent of home 
purchase mortgages (without B&C loans) were originated in 
underserved tracts based on 2000 geography, compared with 25.8 
percent based on 1990 geography--a differential of 5.7 percentage 
points. As also shown in Table B.8, the underserved areas share of 
Fannie Mae's purchases rises by 5.5 percentage points, and the 
underserved areas share of Freddie Mac's purchases rises by 5.4 
percentage points. Thus, the conclusions reported above and in 
Appendix A about the GSEs' performance relative to the market about 
remain the same when the analysis is conducted based on 2000 Census 
geography.
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    It is interesting to repeat the earlier 1990-based analysis of 
home purchase loans but this time based on the 2000 Census 
geography. The following results are obtained for home purchase 
loans from Table B.8:

------------------------------------------------------------------------
                                                             Market  (w/
               Year                Freddie Mac   Fannie Mae     o B&C)
                                     (percent)   (percent)    (percent)
------------------------------------------------------------------------
1999.............................         26.1         27.0         31.4
2000.............................         27.4         29.9         32.9
2001.............................         27.4         30.8         31.6
2002.............................         31.7         32.3         32.3
1999-2002 (average)..............         28.3         29.5         31.5
1996-2002 (estimate).............         27.1         29.0         31.1
------------------------------------------------------------------------

Between 1999 and 2002, 28.3 percent of Freddie Mac's purchases and 
29.5 percent of Fannie Mae's purchases financed properties in 
underserved neighborhoods, compared with 31.5 percent home purchase 
loans originated in the conventional conforming market (excluding 
B&C loans). Thus, Freddie Mac performed at 90 percent of the market 
level, while Fannie Mae performed at 94 percent of the market 
level--both results similar to those reported above for underserved 
areas based on 1990 Census geography. The 2000-based results also 
show that Fannie Mae has improved its performance and matched the 
primary market in funding underserved areas during 2002. The share 
of Fannie Mae's purchases going to underserved areas increased from 
25.7 in 1999 to 32.3 percent in 2002, which placed it at the market 
level of 32.3 percent. However, the 2000-based results show that, 
like Freddie Mac, Fannie Mae's longer-term performance (since 1996) 
as well as its recent average performance (1999 to 2001) have 
consistently been below market levels. (Note that the 1996-2002 
averages reported above are estimated by adding the following 2000-
Census versus 1990-Census differentials calculated for 1999-2002: 
5.4 percentage points for Freddie Mac, 5.5 for Fannie Mae, and 5.7 
for the market.)
    Underserved Area Subgoal for Home Purchase Loans. The Department 
is proposing to establish a subgoal of 33 percent for each GSE's 
acquisitions of home purchase loans financing single-family-owner 
properties located in the underserved census tracts of metropolitan 
areas for 2005, with this proposed subgoal rising to 34 percent for 
2006 and 35 percent for 2007-2008. If the GSEs meet this 2005 (2007-
2008) subgoal, they will be leading the primary market by about 1.5 
(3.5) percentage points, based on historical data. This home 
purchase subgoal will encourage the GSEs to provide additional 
credit and capital to urban neighborhoods that historically have not 
been adequately served by the mortgage industry--but in the future 
may be the very neighborhoods where the growing population of 
immigrants and minorities choose to live. As detailed in Section I.5 
of this appendix, there are four specific reasons for establishing 
this subgoal: (1) The GSEs have the expertise, resources, and 
ability to lead the single-family-owner market, which is their 
``bread and butter'' business; (2) the GSEs have been lagging the 
primary market in underserved areas, not leading it; (3) the GSEs 
can help reduce troublesome neighborhood disparities in access to 
mortgage credit; and (4) there are ample opportunities for the GSEs 
to expand their purchases in low-income and high-minority 
neighborhoods. Sections E.9 and G of Appendix A provide additional 
information on the opportunities for an enhanced GSE role in 
underserved area segments of the home purchase market and on the 
ability of the GSEs to lead that market.
    As discussed above, underserved areas accounted for an average 
of 31.5 percent of home purchase loans originated in the 
conventional conforming market of metropolitan areas (computed over 
1999-2002 or over 2001-2002). To reach the proposed 33-percent (35-
percent) subgoal for 2005 (2007-2008), both GSEs will have to 
improve their performance--Fannie Mae by 1.9 (3.9) percentage points 
over its average performance of 31.1 percent during 2001 and 2002, 
and by 0.7 (2.7) percentage points over its performance of 32.3 
percent in 2002; and Freddie Mac by 3.4 (5.4) percentage points over 
its average performance of 29.6 percent in 2001 and 2002, and by 1.3 
(3.3) percentage points over its performance of 31.7 percent in 
2002. Loans in the B&C portion of the subprime market are excluded 
from the market average of 31.5 percent for 1999-2001.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for non-metropolitan counties are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices A and C.

b. Characteristics of GSEs' Purchases of Mortgages on Properties in 
Metropolitan Underserved Areas

    Several characteristics of loans purchased in 2002 by the GSEs 
in metropolitan underserved areas are presented in Table B.9. As 
shown, borrowers in underserved areas are more likely than borrowers 
in served areas to be first-time homebuyers, all female, all male 
and younger than 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 8.7 percent of the GSEs' 
mortgage purchases in underserved areas and 6.1 percent of their 
business in served areas. In underserved areas, 55.1 percent of 
borrowers had incomes below the area median, compared with 36.7 
percent of borrowers in served areas.
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    Minorities' share of the GSEs' mortgage purchases in underserved 
areas (33.3 percent) was greater than two times their share in 
served areas (14.3 percent). And the pattern was even more 
pronounced for African Americans and Hispanics, who accounted for 
22.7 percent of the GSEs' business in underserved areas, but only 
6.6 percent of their purchases in served areas.
    Fannie Mae and Freddie Mac have different purchasing behavior 
for home purchases and refinance loans in served and underserved. 
While Fannie Mae is less likely to purchase refinance mortgages in 
underserved area than served areas and more like to purchase home 
purchase loans in served areas than underserved areas, Freddie Mac 
purchase the same proportion of both home purchase and refinance 
loans in served areas as in underserved areas.

3. GSE Mortgage Purchases in Nonmetropolitan Areas

    There are numerous studies that have evaluated the impact of the 
GSEs' purchases on metropolitan areas, but few address the impact on 
nonmetropolitan areas; therefore, our understanding of the GSEs and 
the nonmetropolitan markets is very limited.
    A study of the GSE market share in underserved counties \47\ 
found that location has a role in the accessibility of credit for 
some people in nonmetropolitan areas (low income, minority, and 
first-time homebuyers). West North Central counties (Minnesota, 
Missouri, South Dakota, Iowa, Kansas, Nebraska, and North Dakota) 
have much lower GSE activity than all other geographic regions, 
suggesting that the 1995 definition of underservice does not capture 
the specific characteristics of this region, leading to limited GSE 
activity.
---------------------------------------------------------------------------

    \47\ Heather MacDonald, ``Fannie Mae and Freddie Mac in 
Nonmetropolitan Housing Markets: Does Space Matter? '' Cityscape: A 
Journal of Policy Development and Research, Volume 5, 2001, pp. 219-
264.
---------------------------------------------------------------------------

    Additionally, The Urban Institute prepared a report for HUD that 
investigated the factors influencing GSE activity in nonmetropolitan 
areas.\48\ The authors found that Fannie Mae and Freddie Mac have 
increased their lending to nonmetropolitan areas since 1993; 
however, there are still weak areas in terms of the percentage of 
affordable loans being offered.\49\ They also established that GSE 
underwriting criteria was not a major barrier in nonmetropolitan 
areas.
---------------------------------------------------------------------------

    \48\ Jeanette Bradley, Noah Sawyer and Kenneth Temkin, Factors 
Influencing GSE Service to Rural Areas. the Urban Institute, 
prepared for U.S. Department of Housing and Urban Development, 2002.
    \49\ Affordable loans are defined as borrowers earning less than 
80 percent the Area Median Income.
---------------------------------------------------------------------------

    In nonmetropolitan areas, the financial market is often made up 
of locally owned community banks, manufactured home lenders, and 
subprime lenders. Industry representatives contacted by the Urban 
Institute researchers assessed that the barriers nonmetropolitan 
lenders faced were in the areas of availability of sales 
comparables, technology, and the type and number of lenders in the 
area. They also believed that for the GSEs' market share to improve 
in underserved nonmetropolitan areas, the GSEs would have to begin 
to build relationships with the community lenders and provide 
education/training on how to sell loans directly to the GSEs rather 
than using intermediaries.

a. Effects of 2000 Census Geography

    In order to compare served and underserved areas, either in 
terms of GSE performance or socioeconomic characteristics, it is 
first necessary to update current geographic (county) designations, 
which reflect 1990 census median income and minority population 
data, to reflect newly available 2000 census data. Table B.10 shows 
the impact on 2000, 2001, and 2002 GSE purchases. These are reported 
for total GSE purchases and separately for Fannie Mae and Freddie 
Mac. As above, the results also are shown separately for counties 
that change classification and those that do not. This analysis is 
limited to nonmetropolitan areas based on both the pre- and post-
June, 2003 OMB metropolitan area designations.
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    Applying 2000 census median income and minority population data 
results in a slight drop in the proportion of counties that are 
classified as underserved. Out of a total of 2,493 counties, 1,514 
(65.5 percent) are underserved based on 1990 data, and 1,260 (61.4 
percent) based on 2000 data. This small net change disguises a 
somewhat larger shift of counties, as about 11.2 percent of 
currently underserved counties are reclassified as served counties 
and 4.6 percent of currently served counties are reclassified as 
underserved.
    Comparing underserved and served nonmetropolitan areas in Table 
B.10, it is apparent that underserved nonmetropolitan areas make up 
a larger percentage of nonmetropolitan areas as a whole than do 
served nonmetropolitan areas, as shown by the number of counties 
(1,260 for underserved (61.4%); 792 for served (38.6%)). These 
relationships hold true also for the number of households (9.5 
million for underserved (50.5%); 9.3 million for served (49.5%)), 
and the population (24.9 million for underserved (51%); 23.9 million 
for served (49%)) as shown in Table B.5.
    Table B.10 shows that Fannie Mae's performance in 2002 (40.2 
percent) was somewhat higher than Freddie Mac's (36.3 percent). This 
gap widens slightly (1.8 percent) in applying 2000 census income and 
minority data and 2003 metropolitan area definitions.

b. Characteristics of GSEs' Purchases of Mortgages on Properties in 
Non-metropolitan Underserved Areas

    Nonmetropolitan mortgage purchases made up 11.9 percent of the 
GSEs' total mortgage purchases in 2002. Mortgages in underserved 
counties made up 39.0 percent of the GSEs' business in 
nonmetropolitan areas.\50\
---------------------------------------------------------------------------

    \50\ Underserved areas make up about 56 percent of the census 
tracts in nonmetropolitan areas and 47 percent of the census tracts 
in metropolitan areas. This is one reason why underserved areas 
comprise a larger portion of the GSEs' single-family mortgages in 
nonmetropolitan areas (39 percent) than in metropolitan areas (23 
percent).
---------------------------------------------------------------------------

    Unlike the underserved areas definition for metropolitan areas, 
which is based on census tracts, the rural underserved areas 
definition is based on counties. Rural lenders argued that they 
identified mortgages by the counties in which they were located 
rather than the census tracts; and therefore, census tracts were not 
an operational concept in rural areas. Market data on trends in 
mortgage lending for metropolitan areas are provided by HMDA; 
however, no comparable data source exists for rural mortgage 
markets. The absence of rural market data is a constraint for 
evaluating credit gaps in rural mortgage lending and for defining 
underserved areas.
    One concern is whether the broad definition overlooks 
differences in borrower characteristics in served and underserved 
counties that should be included. Table B.11 compares borrower and 
loan characteristics for the GSEs' mortgage purchases in served and 
underserved areas.
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    Fannie Mae is slightly more likely and Freddie Mac is less 
likely to purchase loans for first-time homebuyers in underserved 
areas than in served areas. Mortgages to first-time homebuyers 
accounted for 5.6 percent of Fannie Mae's mortgage purchases in 
served counties, compared with 5.8 percent of its purchases in 
underserved counties. For Freddie Mac the corresponding figures are 
4.7 percent in served counties and 5.1 percent in underserved 
counties.
    The GSEs are more likely to purchases mortgages for high-income 
borrowers in underserved than in served counties. Surprisingly, 
borrowers in served counties were more likely to have incomes below 
the median than in underserved counties (37.8 percent compared to 
34.5 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.
    There are similarities and one difference 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 slightly 
more likely to purchase refinance loans in underserved counties than 
in served counties; mortgage purchases with loan-to-value ratios 
above 80 percent are more likely to be in underserved counties than 
in served counties; and seasoned mortgage purchases are more likely 
to be in underserved than in served counties. The GSEs differ in 
that Fannie Mae is slightly more likely and Freddie Mac is less 
likely to purchase loans for first-time homebuyers in underserved 
areas than served areas.

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

    HUD estimates that underserved areas account for 35-40 percent 
of the conventional conforming mortgage market. The analysis 
underlying this estimate is detailed in Appendix D.

F. Factor 5: Ability To Lead the Industry

    This factor is the same as the fifth factor considered under the 
goal for mortgage purchases on housing for low- and moderate-income 
families. Accordingly, see Section G of Appendix A for a discussion 
of this factor, as well as Section I.5 of this Appendix, which 
describes the home purchase subgoal which is designed to place the 
GSEs in a leadership role in the underserved market.

G. Factor 6: Need To Maintain the Sound Financial Condition of the 
Enterprises

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

H. Defining Nonmetropolitan Underserved Areas

1. Whether To Adopt a Tract-Based Definition of Underserved Areas

    The current county-based definition for targeting GSE purchases 
to underserved nonmetropolitan areas was adopted in 1995 over 
alternative narrower definitions, such as census tracts, despite the 
use of census tracts in metropolitan areas. In the 1995 Final Rule, 
HUD found the merits of a county-based system of targeting 
outweighed a tract-based system. Now, with seven years of experience 
under a county-based system, the release of Census 2000 data, and 
improvements in information technology and systems, HUD can 
reexamine whether to switch to census tracts for defining 
underserved nonmetropolitan areas. This section compares impacts of 
the potential shift in definition for both served and underserved 
populations as determined by tract-based and county-based 
definitions using a number of common industry variables as focal 
points for analysis.
    The rationale for choosing counties in 1995 rested primarily on 
perceived shortcomings of census tracts.\51\ In particular, rural 
lenders did not perceive their market areas in terms of census 
tracts, but rather, in terms of counties. Another concern was a 
perceived lack of reliability in geocoding 1990 census tracts. At 
the same time, HUD found merit in using a tract-based geography for 
nonmetropolitan areas. Because tracts encompass more homogeneous 
populations than counties, they permit more precise targeting of 
underserved populations. In other words, more homogeneous geographic 
areas increase the potential for targeting the GSE mortgage 
purchases into areas where borrowers are more likely to face 
obstacles and other challenges in securing mortgage credit.
---------------------------------------------------------------------------

    \51\ 60 FR 61925-61958 (1995) (Appendix B).
---------------------------------------------------------------------------

    The criteria used for this analysis include the following:
     Do tracts provide a sharper delineation of 
served and underserved areas? Specifically, are underserved 
nonmetropolitan populations more clearly differentiated by adopting 
tracts vs. counties? Could service to the underserved 
nonmetropolitan populations be more comprehensive under tract-based 
definitions?
     What is the impact on GSE purchasing patterns 
if underserved areas are defined by tract?
     Applying the current criteria for identifying 
underserved areas to tracts would result in reclassifying 
approximately 23 percent of all tracts, with 28 percent of tracts in 
served counties being redesignated as underserved and 19 percent of 
tracts in underserved counties being redesignated as served. 
Overall, roughly the same percentage of families (and population) 
would be reclassified. However, because underserved tracts are 
somewhat less densely populated than served tracts, the 
corresponding proportions of families that shift from served and 
underserved counties are closer: 25 vs. 21 percent.

a. Do Census Tracts Allow a Sharper Delineation of Served and 
Underserved Areas?

    This section compares the differences in housing need and 
economic, demographic, and housing conditions in served and 
underserved nonmetropolitan areas classified on, respectively, 
counties and tracts. Additionally, the ``efficiency'' with which 
counties and tracts cover the target populations is compared. That 
is, does tract-based targeting do a better job of capturing lower 
income households and excluding higher income households than 
county-based targeting?
    Table B.12 presents several indicators of socioeconomic and 
housing condition in served and underserved areas under both a 
tract-based and a county-based definition. In addition, served and 
underserved counties are subdivided into their served and 
underserved tract components. This allows a closer examination of 
the population and housing characteristics of the tracts that are 
reclassified (i.e., served to underserved or visa versa) under 
tract-based targeting. Thus, area characteristics of housing need 
and housing, economic, and demographic conditions can be compared, 
for the following four groups of tracts: (1) Tracts in served 
counties that would remain ``served'' classified as tracts; (2) 
tracts that remain ``underserved''; (3) tracts that shift from 
served to underserved; and (4) tracts that shift from underserved to 
served. In addition, we provide counts of tracts falling into each 
of these groups. If a tract-based classification of underserved 
areas improves geographic targeting, the regrouping of tracts would 
be more similar to one another than to the other tracts in their 
respective counties: e.g., formerly underserved areas that become 
served should be more similar to tracts that were and remain served 
than to underserved (unchanged).
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    Socioeconomic and Demographic Conditions. Table B.12 shows that 
in important socioeconomic and demographic characteristics, tract-
based targeting would more effectively distinguish underserved 
populations. Median family income, poverty, unemployment, school 
dropout rates, and minority population all exhibit greater 
differences between served and underserved areas using tracts. For 
example, the difference in median income between served and 
underserved counties is $9,579, or alternatively, between served and 
underserved tracts, the difference is $12,744. Similarly, there is a 
7-percentage point gap in poverty rates (7.5 vs. 14.5 percent 
poverty) using counties, which widens to 8.6 percentage points (6.6 
vs. 15.3 percent) using tracts. Minority population also is captured 
somewhat better with tracts, with the served/underserved gap 
increasing from 16.5 to 17.3 percentage points. In all cases, the 
levels of the indicators for underserved areas move in a direction 
consistent with targeting lower income households and areas with 
higher minority populations.
    The 4-way breakdown of served and underserved counties reveals 
some significant differences between the two component groups. In 
most respects, ``underserved tracts'' (i.e., those meeting the 
underserved criteria), whether located in an underserved or served 
county, are more alike than they are like served tracts. Using 
median income again to illustrate, the effect of reclassifying areas 
by tract characteristics is to put together two groups of 
underserved tracts: tracts that were in previously underserved 
counties and are not reclassified and tracts that were in served 
counties but meet the underserved criteria. A new group of served 
tracts is similarly formed. In both cases, the difference in median 
incomes of the constituent groups is about $3,500. In contrast, the 
served and underserved counties now encompass ``served'' and 
``underserved'' groups of tracts whose respective median incomes 
differ by almost $11,000. Combined with the fact that a fairly large 
number of tracts are affected overall (i.e., switch), these results 
support an assessment that counties are relatively crude for 
targeting underserved populations.
    Housing Needs and Conditions. Table B.12 shows that tract-based 
targeting would produce modest gains in focusing GSE purchases on 
areas with relatively greater housing needs and conditions as 
measured by low owner-occupancy, higher vacancy rates, and crowding. 
For each of these indicators, measured need increases in underserved 
areas and the gap between served and underserved areas widens when 
tracts are used to classify areas. Most notably, the percent of 
owner-occupied housing units switches from being higher in 
underserved than served counties to being significantly lower among 
underserved tracts. With a shift to tracts overall ownership drops 
in underserved areas, from 74 to 72 percent, and increases in served 
areas from 74 to 77 percent. In contrast, the homeownership rate for 
tracts located in served counties that would be deemed underserved 
if judged separately is only 65 percent. In fact, this rate is much 
lower even than underserved tracts in underserved counties. Shifting 
these tracts from served to underserved largely accounts for the 
switching of homeownership rates.
    Results for other indicators of housing need and conditions are 
less clear-cut. No definitive patterns are apparent for two, 
admittedly weak, measures of housing quality--units with complete 
plumbing and units with complete kitchen facilities, as well as for 
crowding. Purchase affordability, as measured by the ratio of median 
housing value to the income necessary to qualify for a loan for the 
median valued unit, is higher in underserved areas than in served 
areas. However, the measure of purchase affordability presented here 
is influenced by many market and other economic factors, some of 
which do not relate to housing need. For example, a low 
affordability ratio may reflect abundant supply, but it may also 
reflect low demand stemming from, e.g., limited availability of 
credit or high interest rates.
    Coverage Efficiency. The coverage efficiency index measures the 
effect of adopting tract-based targeting. This index can be used to 
indicate how well underserved areas encompass populations deemed to 
be underserved (``sensitivity'') and to exclude populations that are 
deemed to be served (``specificity''). The index is computed for 
median income as the difference in two percentages: (1) the 
proportion of all families in nonmetropolitan areas that meet the 
applicable income threshold who live in underserved tracts minus (2) 
the proportion of all families in nonmetropolitan areas that do not 
meet the applicable underserved income threshold who live in 
underserved areas. This difference can range from 1 (perfect) to--1 
(bad; perverse). For example, a coverage efficiency index equal to 1 
implies that every family in need is living in an underserved area 
while there are no families who are not in need living in an 
underserved area; a coverage efficiency index equal to--1 implies 
that none of the families in need live in an underserved area, or 
equivalently, all families in underserved areas are not in need.
    Comparing coverage efficiency for counties and tracts indicates 
that tracts do a better job; capturing a higher percentage of 
nonmetropolitan families whose income falls below the applicable 
income threshold and excluding more families whose income exceeds 
the threshold.\52\ Overall, the efficiency index rises from 22.0 to 
27.4 percent.
---------------------------------------------------------------------------

    \52\ In areas with 30 percent or greater minority population, 
all families with income in excess of 120 percent of the greater of 
State or national median income are counted as qualifying as ``in 
need'' for these computations. Similarly, in areas with less than 30 
percent minority, those minority (headed) families with income 
between 95 and 120 percent of the applicable median income are not 
classified as ``in need.''
---------------------------------------------------------------------------

    Given income thresholds that are not far away from median income 
in most places and the degree of income variation even with census 
tract boundaries, it should not come as a great surprise that 
neither the levels of coverage efficiency (22-27 percent) nor 
improvement produced in applying tracts (5 percent) are not more 
dramatic. Nevertheless, tracts do produce better tracking of lower 
income, very low income, and minority families.

b. Does GSE Performance Vary between Served and Underserved Tracts 
Within Underserved Counties?

    A similar analytical approach is used to examine how a shift to 
tracts would impact GSE purchases. Having applied income and 
minority thresholds from the 2000 census and updating census tract 
geography, Table B.13 compares, respectively, 2000, 2001, and 2002 
GSE purchases for served and underserved counties and tracts and 
also for the served and underserved tracts within county boundaries. 
On net there would be somewhat more tracts classified as underserved 
under a tract-based system than currently: 6,782 vs. 6,414. As noted 
above, however, 23.1 percent of all tracts are reclassified. Moving 
to tracts also would have a significant effect on the relative 
performance of the GSEs. In 2002, Fannie Mae's performance would 
drop 2.1 percentage points to 35.4 percent, while Freddie Mac's 
performance would increase by 0.9 percent to 32.7 percent.
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    Differences between qualifying purchases of single-family and 
multifamily loans are further increased when assessed at the tract 
level. Performance for single-family loans drops 0.7 percentage 
points to 35.2, but for multifamily increases by 2.5 percentage 
points to 46.8. These changes dramatically compound the results 
observed in updating to 2000 census data, resulting in a widening of 
the single- and multifamily performance difference from the current 
level of 7.0 percentage points to 11.6 percentage points.

2. Alternative Definitions of Underservice

    The current definition of underservice in nonmetropolitan areas 
was established in 1995 to be relatively broad, encompassing nearly 
twice as many underserved as served counties and somewhat more than 
half of the total nonmetropolitan population. This was done 
primarily to ensure that certain areas with low incomes and/or high 
minority populations, which might not be considered underserved in 
comparison to the rest of their State, would nevertheless be 
identified as underserved from a national perspective. This section 
summarizes a new analysis, based on 2000 census data, to evaluate 
the extent to which the current definition focuses GSE purchasing 
activity toward stimulating mortgage lending in areas with 
populations having greatest housing need. Alternative definitions of 
underservice are considered as follows: (1) Variations of the 
current thresholds; (2) applying only the State median income level 
for qualifying underserved counties and tracts; and (3) establishing 
different thresholds in micropolitan and ``outside of core'' 
nonmetropolitan areas. In each case the objective is to assess how 
redesignating served and underserved areas would affect relative 
conditions and needs and GSE purchasing performance. In 
distinguishing micropolitan and ``outside of core'' areas, it is of 
interest to determine whether it would be appropriate to establish 
different thresholds for underservice. The overarching criterion for 
evaluating and comparing definitions is their ability to serve very 
low-income, low-income and moderate-income households, households in 
poverty, first-time homebuyers, minorities, and households in remote 
locations.\53\
---------------------------------------------------------------------------

    \53\ A more comprehensive presentation of this analysis may be 
found in Economic Systems, Inc., Indicators of Mortgage Market 
Underservice in Non-Metropolitan Areas, Interim Report to HUD, March 
2003, Chapter 6.
---------------------------------------------------------------------------

    In the current definition, areas are classified as underserved 
if either the minority population share is greater than 30 percent 
and median income is less than 120 percent of the greater of State 
nonmetropolitan or national nonmetropolitan median income; or area 
median income is less than or equal to 95 percent of the greater of 
State nonmetropolitan or national nonmetropolitan median income. The 
greater of State nonmetropolitan or national median income is termed 
the ``reference income.'' Denoting the current thresholds as ``30/
120/95,'' the following set of alternative thresholds are evaluated:
     30/120/95 vs. 30/120/90 vs. 30/120/80--to 
examine the effect of lowering the general income threshold from 95 
percent to 90 percent to 80 percent.
     30/120/95 vs. 30/110/95 vs. 30/110/80--to 
examine the effect of lowering both the minority (from 120% to 110%) 
and general income (from 95% to 80%) thresholds; and
     30/120/95 vs. 50/120/95--to examine the 
effect of increasing the minority population threshold that must be 
attained before applying the minority income threshold.
    For each alternative, indicators of socioeconomic and housing 
conditions are calculated for served and underserved areas for each 
alternative and compare the results to the current definition. Of 
particular interest is whether certain thresholds of minority 
population and median income capture the differences in housing 
needs and conditions between served and underserved areas better 
than others. The ``coverage efficiency'' of each alternative 
relative to households below the poverty line, below 50, 70, and 95 
percent of area reference income, and below the alternative income 
level(s) used to define underservice, is also presented. GSE 
purchasing activity is also examined for each alternative 
definition, specifically, the percentage of eligible loans that 
qualify towards the goal for underserved areas defined by different 
thresholds. Each analysis is conducted both with counties and tracts 
as the geographic unit.
    County Results. The main effect of lowering the general income 
threshold from 95 to 90 to 80 percent of the reference income is to 
roughly halve the number of counties and population residing in 
underserved areas. Under the current definition, 11.6 million people 
reside in underserved areas as opposed to fewer than 10 million in 
served areas. With a general income threshold of 80 percent, 5.7 
million would be left in underserved areas. A 90 percent threshold 
would produce a shift of approximately half this amount.
    In terms of social, economic, demographic, and housing 
characteristics, lowering the income threshold from 95 to 80 percent 
would have the following notable consequences:
     Minority population in underserved areas 
would increase from 12.4 to 20.8 percent with no significant change 
in served areas.
     Median income would fall in both served and 
underserved areas with the difference remaining nearly constant at 
$10,000.
     Poverty, unemployment, school drop out rates 
all would be higher in both served and underserved areas. The gap 
would increase for each of these characteristics.
     Migration into underserved areas (from other 
States) would be relatively lower than into served areas with an 80 
percent income threshold.
     Indicators of homeownership would decline 
somewhat in underserved areas relative to served areas. For all 
units, for example, ownership would decline from 74.3 to 72.9 
percent in underserved areas and increase from 73.5 to 74.3 percent 
in served areas.
     Median housing values would fall in both 
served and underserved areas with a significant narrowing in the gap 
from approximately $25,000 to $19,000 at an 80 percent median income 
threshold.
     Housing affordability would decline in 
underserved areas, becoming nearly equal with affordability in 
served areas at 80 percent.
     Crowding would be higher in underserved 
areas, absolutely and relative to served areas. Thus, more narrowly 
defined underserved areas would more strongly manifest conditions 
and needs associated with underservice: lower income, higher 
poverty, higher minority populations, lower homeownership, lower 
affordability, more crowding, etc. However, served areas would 
expand to encompass significant numbers of these same underserved 
and target populations.
    Use of the coverage efficiency index highlights one of the 
tradeoffs between using a low median income threshold versus a high 
median income threshold in redefining underservice. Coverage 
efficiency based on all variables examined, including 
``underserved,'' poor, very low income, low income and even moderate 
income families, declines sharply as the income threshold is lowered 
from 95 to 80 percent, becoming negative for most groups. Coverage 
for the ``underserved'' cohort declines from 22.0 to -1.0 percent, 
and for families with up to 95 percent of reference income, it 
declines from 17.2 to -10.0 percent. These changes result from 
losing almost half of the families in target income ranges without 
any appreciable gain in specificity, i.e., shrinking the proportion 
of people living in underserved counties with incomes above the 
respective target levels. Similar patterns are observed for families 
with below 70 percent of reference income, below 50 percent of 
reference income, and families in poverty.
    The second set of comparisons builds on the first set by 
lowering the income threshold applicable to areas with a relatively 
high minority populations (30 percent) from 120 to 110 percent in 
addition to the general threshold. This change further shrinks, 
albeit, only marginally, the size and population of underserved 
areas. Minority underserved populations would be smaller and 
socioeconomic and housing conditions would be worse. Not 
surprisingly, coverage efficiencies and GSE purchase performance 
levels also would decline across the board, although the marginal 
effects of reducing the minority income threshold are quite small. 
The 30/110/80 alternative is the narrowest definition examined and 
produces the biggest loses in efficiency and GSE performance.
    The third variation of the current definition is an increase in 
the minority population threshold from 30 to 50 percent. Thus, if an 
area does not qualify as underserved against the general income 
threshold of 95 percent it could still qualify if its population is 
50 percent minority and median income is less than or equal to 120 
percent of the reference income level.
    Relatively few counties qualify solely under the current 
minority thresholds. Raising the population threshold would trim 
this number by an additional 73 counties (457 tracts). Not 
surprisingly, the percent minority in underserved areas would 
decrease. However, the areas being redesignated as served are 
apparently somewhat above average in terms of

[[Page 24416]]

socioeconomic and housing conditions in underserved areas and below-
average in terms of conditions in served areas. Coverage 
efficiencies for all cohorts would be lower than for the current 
definition of underservice and GSE performance overall would be 
approximately 90 percent of the current level.
    Using the State median income, alone, as the general reference 
income would reduce the number underserved counties relative to the 
current definition, and, although there would still be more 
underserved counties (1,274 vs. 1,064), the underserved population 
actually would become smaller than the served population. The effect 
of this alternative on differences in housing conditions and needs 
between served and underserved areas is generally small and 
ambiguous, but overall, results in less contrast. Consistent with 
the results for other alternatives, applying a State median income 
standard, alone, would result in lower coverage efficiency across 
all target groups.
    Census Tract Results. As discussed above, the adoption of a 
tract-based system would result in greater coverage efficiency of 
underserved populations and sharper distinctions in the 
socioeconomic, demographic and housing characteristics of served and 
underserved areas. That is, tracts more effectively carve out areas 
that exhibit characteristics that are associated with underservice, 
such as low income, large minority populations and low 
homeownership. The converse is true for served areas. In analysis at 
the tract level, these patterns tend to be maintained quite 
consistently. A tract-based system would improve the power to 
differentiate underserved and served populations. According to 
virtually every indicator of socioeconomic, demographic, and housing 
conditions, applying State median income, alone, with a tract-based 
geography would produce superior differentiation to the current 
county-based definition. In terms of coverage efficiency, we again 
see improvement with tracts, but not enough to offset the loss of 
eliminating the national median income threshold. For the 
underserved population, for example, coverage efficiency would be 
16.9 percent with tracts, still below 22 percent under the current 
definition.\54\
---------------------------------------------------------------------------

    \54\ Note that, unlike the other panels in tables 6.3 and 6.8, 
``underserved population'' is defined according to the applicable 
definition. Thus, eliminating the national median income test, 
narrows the defined cohort of underserved families. Despite this, 
coverage falls.
---------------------------------------------------------------------------

I. Determination of the Underserved Areas Housing Goal

    The proposed 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 
38 percent of eligible units financed in 2005, 39 percent in 2006 
and 2007, and 40 percent in 2008. The 2008 goal will remain in 
effect in subsequent years, unless changed by the Secretary prior to 
that time. The goal of 38 percent for 2005 is larger than the goal 
of 31 percent for 2001-03 mainly because, compared with the 1990 
Census, the 2000 Census includes a larger number of census tracts 
that meet HUD's definition of underserved area. The proposed new 38 
percent-40 percent goals are commensurate with recent market share 
estimates of 37-40 percent for 1999-2002, presented in Appendix D.
    In addition, an Underserved Areas Housing Subgoal of 33 percent 
is proposed for the GSEs' acquisitions of single-family-owner home 
purchase loans in metropolitan areas in 2005, with the proposed 
subgoal rising to 34 percent in 2006 and 35 percent in both 2007 and 
2008. The subgoal is designed to encourage the GSEs to lead the 
primary market in providing mortgage credit in underserved areas.
    This section summarizes the Secretary's consideration of the six 
statutory factors that led to the Underserved Area Housing Goal and 
the subgoal for home purchase loans in metropolitan areas. This 
section discusses the Secretary's rationale for defining underserved 
areas and it compares the characteristics of such areas and 
untargeted areas. The section draws heavily from earlier sections 
which have reported findings from HUD's analyses of mortgage credit 
needs as well as findings from other research studies investigating 
access to mortgage credit.

1. Housing and Credit Disparities in Metropolitan Areas

    There are families who are not being adequately served by the 
nation's housing and mortgage markets. A major HUD-funded study of 
discrimination in the sales and rental markets found that while 
discrimination against minorities was generally down since 1989, it 
remained at unacceptable levels in 2000. The greatest share of 
discrimination against Hispanic and African American home seekers 
can still be attributed to being told that units are unavailable 
when they are available to whites and being shown and told about 
fewer units than a comparable white home seeker. There has also been 
an upward trend of discrimination in the area of geographic steering 
for African Americans.
    Racial disparities in mortgage lending are also well documented. 
HUD-sponsored studies of the pre-qualification process conclude that 
African Americans and Hispanics faced a significant risk of unequal 
treatment when they visit mainstream mortgage lenders. Numerous 
studies of HMDA data have shown that mortgage denial rates are 
substantially higher for African Americans and Hispanics, even after 
controlling for applicant income. And the now-famous Boston Fed 
study found that the higher denial rates for minorities remained 
after controlling for a host of underwriting characteristics, such 
as the credit record of the applicant. Partly as a result of these 
racial disparities in the housing and mortgage markets, the 
homeownership rate for minorities is 25 percentage points below that 
for whites.
    There are also neighborhoods that are not being adequately 
served by the nation's housing and mortgage industries. The 
existence of substantial neighborhood disparities in homeownership 
and mortgage credit is well documented for metropolitan areas. HUD's 
analysis of HMDA data shows that mortgage credit is substantially 
lower in high-minority and low-income neighborhoods and mortgage 
denial rates are much higher for residents of these neighborhoods. 
The economics literature discusses the underlying causes of these 
disparities in access to mortgage credit, particularly as related to 
the roles of discrimination, segregation, ``redlining'' of specific 
neighborhoods, and the barriers posed by underwriting guidelines 
that disadvantage applicants from inner city neighborhoods. 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. The income and minority 
composition of an area is a good measure of whether that area is 
being underserved by the mortgage market.

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: application denial rates and mortgage 
origination rates per 100 owner-occupied units. Tables B.2 and B.3 
in Section B of this Appendix presented detailed data on denial and 
origination rates by the racial composition and median income of 
census tracts for metropolitan areas. Aggregating this data is 
useful in order to examine denial and origination rates for broader 
groupings of census tracts:\55\
---------------------------------------------------------------------------

    \55\ Denial rates are computed for mortgage applications without 
manufactured housing loans. Origination rates equal home purchase 
and refinance mortgages (without subprime loans) per 100 owner 
occupants in a census tract.

------------------------------------------------------------------------
                                                    Denial
         Minority composition  (percent)             rate     Orig. rate
                                                   (percent)
------------------------------------------------------------------------
0-30............................................         8.7        19.3
30-50...........................................        11.2        19.3
50-100..........................................        16.3        14.7
------------------------------------------------------------------------


------------------------------------------------------------------------
                                                    Denial
                  Tract income                       rate     Orig. rate
                                                   (percent)
------------------------------------------------------------------------
Less than 90% of AMI............................        15.6        13.9
90-120%.........................................        10.1        18.6
Greater than 120%...............................         7.1        22.7
------------------------------------------------------------------------

    Two points stand out. First, high-minority census tracts have 
higher denial rates and lower origination rates than low-minority 
tracts. Specifically, tracts that are over 50 percent minority have 
nearly twice the denial rate and three-fourths the origination rate 
of tracts that are under 30 percent minority.\56\

[[Page 24417]]

Second, census tracts with lower incomes have higher denial rates 
and lower origination rates than higher income tracts. Tracts with 
income less than 90 percent of area median income have over twice 
the denial rate and three-fifths the origination rate of tracts with 
income over 120 percent of area median income.
---------------------------------------------------------------------------

    \56\ The differentials in denial rates are due, in part, to 
differing risk characteristics of the prospective borrowers in 
different areas. However, use of denial rates is supported by the 
findings in the Boston Fed study which found that denial rate 
differentials persist, even after controlling for risk of the 
borrower. See Section B for a review of that study.
---------------------------------------------------------------------------

    In both the 1995 and the 2000 GSE Rules, HUD's research 
determined that ``underserved areas'' could best be characterized in 
metropolitan areas as census tracts where: (1) median income of 
families in the tract does not exceed 90 percent of area (MSA) 
median income or (2) minorities comprise 30 percent or more of the 
residents and median income of families in the tract does not exceed 
120 percent of area median income. The earlier analysis was based on 
1990 Census data. HUD has now conducted the same analysis using 2000 
Census data and has determined that the above definition continues 
to be a good proxy for underserved areas in metropolitan areas. The 
income and minority cutoffs produce sharp differentials in denial 
and origination rates between underserved areas and adequately 
served areas. For example, in 2002 the mortgage denial rate in 
underserved areas (14.0 percent) was over one-and-a-half times that 
in adequately served areas (8.9 percent).
    These minority population and income thresholds apply in the 
suburbs as well as in central cities. The average denial rate in 
underserved suburban areas (13.7 percent) is 1.7 times that in the 
remaining served areas of the suburbs (8.0 percent), and is almost 
as large as the average denial rate (15.8 percent) in underserved 
central city tracts. Low-income and high-minority suburban tracts 
appear to have credit problems similar to their central city 
counterparts. Thus HUD uses the same definition of underserved areas 
throughout metropolitan areas--there is no need to define such areas 
differently in central cities and in the suburbs.
    This definition of metropolitan underserved areas based on 2000 
Census geography includes 26,316 of the 51,040 census tracts in 
metropolitan areas, covering 49.2 percent of the metropolitan 
population in 2000. (By contrast, the 1990-based definition included 
21,587 of the 45,406 census tracts in metropolitan areas, covering 
44.3 percent of the metropolitan population in 1990.) The 2000-based 
definition includes 75.7 percent of the population living in poverty 
in metropolitan areas. The unemployment rate in underserved areas is 
more than twice that in served areas, and owner units comprise only 
51.6 percent of total dwelling units in underserved tracts, versus 
75.9 percent of total units in served tracts. As shown in Table 
B.14, this definition covers most of the population in several 
distressed central cities including Bridgeport (100 percent), Newark 
(99 percent), and Detroit (93 percent). The nation's five largest 
cities also contain large concentrations of their population in 
underserved areas: New York (68 percent), Los Angeles (72 percent), 
Chicago (75 percent), Houston (73 percent), and Phoenix (50 
percent).
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[[Page 24419]]

3. Identifying Underserved Portions of Nonmetropolitan Areas

    Based on an exploration of alternative numerical criteria for 
identifying underserved nonmetropolitan areas using 2000 census 
data, HUD has concluded that the current definition of underservice 
is broad but efficacious and that any narrower definition of 
underservice would not serve congressional intent under FHEFSSA. 
Narrowing the definition of underservice potentially could promote 
more intense purchasing in needier communities, but this seems 
unlikely. On the contrary, the greatest marginal impact on GSE 
purchasing could be in the very areas that would be excluded under 
the alternatives.
    Research comparing a tract-based system for defining underserved 
areas with the current county-based system, using 2000 census data, 
indicates that a tract-based system would result in more effective 
geographic targeting of GSE purchases. Although the total number of 
tracts designated as served and underserved areas would change very 
little, 23 percent of all tracts would be reclassified, reassigning 
approximately equal numbers of families from served to underserved 
and from underserved to served.
    The main effect of the reclassification is to align tracts into 
more homogeneous and distinct groups as measured by differences in 
key socioeconomic and demographic characteristics such as median 
family income, poverty, unemployment, school dropouts, and minority 
population. As a result of reclassification, underserved areas stand 
out more as areas of lower income and economic activity and somewhat 
larger minority populations.
    Tract-based targeting would potentially focus GSE purchases in 
areas with relatively greater housing needs and conditions as 
measured by owner-occupancy, vacancy rates, and crowding. For each 
of these indicators, measured need increases in underserved areas 
and the gap between served and underserved areas widens when tracts 
are used to classify areas. Most notably, homeownership would be 
significantly lower in underserved areas relative to served areas 
under a tract-based system. Currently, and contrary to expectations, 
homeownership actually is slightly greater in underserved areas. 
Driving this reversal is the fact that tracts in served counties 
that would be reclassified as underserved tracts have an ownership 
rate of just 65 percent, which is much lower even than in the 
underserved tracts in underserved counties, where ownership is 73 
percent. Meanwhile, the served tracts in served and underserved 
counties have the same ownership rate of 77 percent, which is 
significantly higher than in underserved areas.
    Two groups of measures of housing conditions--housing quality 
and affordability--exhibit less clear-cut results from applying 
tracts. However, we conclude that these results are consistent with 
the ambiguous patterns discussed in chapter 4 above and do not 
undermine the overall conclusion that basing geographic targeting on 
tracts would more sharply define areas with greater housing need and 
adverse housing conditions.
    Not surprisingly, the results from analyzing housing, 
socioeconomic, and demographic characteristics are further 
reinforced in finding that a tract-based system would better capture 
underserved populations and exclude served populations from 
geographic targeting. Defining underserved families as those in any 
area whose income was less than 95 percent of the reference income 
(or in areas with a minority population of 30 percent or more, 
families with incomes below 120 percent of the reference income) the 
use of more refined tract geography results in a 5 percentage point 
increase in the coverage efficiency index, from 22 to 27 percent. 
This reflects two improvements under a tract system: underserved 
areas would capture more of the nonmetropolitan ``underserved'' 
families (62 vs. 65 percent) and fewer ``served'' families 
(decreasing from 40 to 37 percent of families in underserved areas).

4. Past Performance of the GSEs

    Goals Performance. In the October 2000 rule, the underserved 
areas goal was set at 31 percent for 2001-03. Effective on January 
1, 2001, several changes in counting requirements came into effect 
for the undeserved areas goal, as follows: (a) ``bonus points'' 
(double credit) for purchases of mortgages on small (5-50 unit) 
multifamily properties and, above a threshold level, mortgages on 2-
4 unit owner-occupied properties; (b) a ``temporary adjustment 
factor'' (1.35 units credit) for Freddie Mac's purchases of 
mortgages on large (more than 50 unit) multifamily properties; and 
(c) eligibility for purchases of certain qualifying government-
backed loans to receive goal credit. Under these counting rules, as 
shown in Figure B.2, Fannie Mae's performance in 2001 was 32.6 
percent and Freddie Mac's performance was 31.7 percent; thus both 
GSEs surpassed the goal of 31 percent.
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[[Page 24421]]

    Counting requirements (a) and (b) expired at the end of 2003, 
while (c) will remain in effect after that. If this counting 
approach--without the bonus points and the ``temporary adjustment 
factor''--had been in effect in 2000 and 2001, and the GSEs' had 
purchased the same mortgages that they actually did purchase in both 
years, then Fannie Mae's performance would have been 31.0 percent in 
2000, 30.4 percent in 2001, and 30.2 percent in 2002. Freddie Mac's 
performance would have been 29.2 percent in 2000, 28.2 percent in 
2001, and 29.4 percent in 2002. Therefore, Fannie Mae would have 
just matched the underserved areas goal of 30 percent in 2000 and 
fallen short in 2001 and 2002, while Freddie Mac would have fallen 
short of the goal in 2000-2002.
    The above performance figures are for underserved areas (census 
tracts in metropolitan areas and counties in non-metropolitan areas) 
defined in terms of 1990 Census geography. Switching to 2000 Census 
data increases the coverage of underserved areas, which increases 
the share of the GSEs' purchases in underserved areas by 
approximately 5 percentage points. Based on 2000 Census geography, 
and excluding counting requirements (a) and (b) then Fannie Mae 's 
performance would have been 38.1 percent in 2000, 36.6 percent in 
2001, and 35.9 percent in 2002. Freddie Mac's performance would have 
been 35.1 percent in 2000, 33.5 percent in 2001, and 33.6 percent in 
2002.
    Single-Family-Owner Home Purchase Mortgages. Sections E.9 of 
Appendix A and D.2 of this appendix compared the GSEs' funding of 
home purchase loans in underserved areas with originations by 
lenders in primary market. To take advantage of HMDA and GSE data 
going back to 1993, the analysis was conducted using 1990 Census 
tract geography. While both GSEs have improved their performance 
since 1993, they have both lagged the conventional conforming market 
in providing affordable loans to underserved areas. The 1990-based 
analysis shows that the two GSEs have engaged in very different 
patterns of funding--Freddie Mac has been much less likely than 
Fannie Mae to fund home loans in underserved neighborhoods. HUD will 
begin defining underserved areas based on 2000 Census geography and 
new OMB definitions of metropolitan areas in 2005, the first year of 
the proposed rule. As noted above, the 2000-based definition of 
underserved areas includes 5,372 more census tracts in metropolitan 
areas than the 1990-based definition, which means the GSE-market 
comparisons need to be updated to incorporate tract designations 
from the 2000 Census. Therefore, for the years 1999, 2000, 2001, and 
2002, HUD used various apportionment techniques to re-allocate 1990-
based GSE and HMDA data into census tracts as defined by the 2000 
Census. Switching to the 2000-based tracts increases the underserved 
area share of market originations by 5.7 percentage points. Between 
1999 and 2002, 31.5 percent of mortgage originations (without B&C 
loans) were originated in underserved tracts based on 2000 
geography, compared with 25.8 percent based on 1990 geography. As 
shown in Table B.8 of Section D.2, the underserved areas share of 
each GSE's purchases also rises by approximately 5.5 percentage 
points. Thus, conclusions about the GSEs' performance relative to 
the market are similar whether the analysis is conducted in terms of 
2000 Census geography or 1990 Census geography.
    The analysis for home purchase loans based on 2000 Census 
geography will be summarized here (see Section D.2 of this appendix 
for a similar analysis using 1990-based geography):

----------------------------------------------------------------------------------------------------------------
                                                                                                    Market (w/o
                              Year                                  Freddie Mac     Fannie Mae         B&C)
                                                                     (percent)       (percent)       (percent)
----------------------------------------------------------------------------------------------------------------
1999............................................................            26.1            27.0            31.4
2000............................................................            27.4            29.9            32.9
2001............................................................            27.4            30.8            31.6
2002............................................................            31.7            32.3            32.3
1999-2002 (average).............................................            28.3            29.5            31.5
1996-2001 (estimate)............................................            27.1            29.0            31.1
----------------------------------------------------------------------------------------------------------------

Between 1999 and 2002, 28.3 percent of Freddie Mac's purchases and 
29.5 percent of Fannie Mae's purchases financed properties in 
underserved neighborhoods, compared with 31.5 percent home purchase 
loans originated in the conventional conforming market (excluding 
B&C loans). Thus, Freddie Mac performed at 90 percent of the market 
level, while Fannie Mae performed at 94 percent of the market 
level--both results similar to those reported above for underserved 
areas based on 1990 Census geography. The 2000-based results also 
show that Fannie Mae has improved its performance and matched the 
primary market in funding underserved areas during 2002. The share 
of Fannie Mae's purchases going to underserved areas increased from 
27.0 in 1999 to 32.3 percent in 2002, which placed it at the market 
level. However, the 2000-based results show that, like Freddie Mac, 
Fannie Mae's longer-term performance (since 1996) as well as its 
recent average performance (1999 to 2001) has consistently been 
below market levels. But, it is encouraging that Fannie Mae 
significantly improved its performance relative to the market during 
the first two years of HUD's higher housing goal levels. (See 
Section D.2 for the method of estimating the 1996-2002 average 
results.)

5. Ability To Lead the Single-Family-Owner Market: A Subgoal for 
Underserved Areas

    The Secretary believes the GSEs can play a leadership role in 
underserved markets. Thus, as discussed in Section D.2, the 
Department is proposing to establish a subgoal of 33 percent for 
each GSE's acquisitions of home purchase loans for single-family-
owner properties located in the underserved census tracts of 
metropolitan areas in 2005, rising to 34 percent in 2006 and 35 
percent in both 2007 and 2008. If the GSEs meet this subgoal, they 
will be leading the primary market by about 1.5 percentage points in 
2005 and 3.5 percentage points in 2007-2008, based on historical 
data. As discussed above, underserved areas accounted for an average 
of 31.5 percent of home purchase loans originated in the 
conventional conforming market of metropolitan areas (computed over 
1999-2002 or over 2001-2002). To reach the 33-percent (35-percent) 
subgoal for 2005 (2007-2008), both GSEs would have to improve their 
performance--Fannie Mae by 1.9 (3.9) percentage points over its 
average performance of 31.1 percent during 2001 and 2002, and by 0.7 
(2.7) percentage points over its performance of 32.3 percent in 
2002; and Freddie Mac by 3.4 (5.4) percentage points over its 
average performance of 29.6 percent in 2001 and 2002, and by 1.3 
(2.3) percentage points over its performance of 31.7 percent in 
2002. Loans in the B&C portion of the subprime market are excluded 
from the market average of 31.5 percent for 1999-2001.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for non-metropolitan counties are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices A and C.
    The approach taken is for the GSEs to obtain their leadership 
position by staged increases in the underserved areas subgoal; this 
will enable the GSEs to take new initiatives in a correspondingly 
staged manner to achieve the new subgoal each year. Thus, the 
increases in the underserved areas subgoal are sequenced so that the 
GSEs can gain experience as they improve and move toward the new 
higher subgoal targets.
    Appendix A discusses in some detail the factors that the 
Department considered when setting the subgoal for low- and 
moderate-income loans. Several of the considerations were general in 
nature--for example, related to the GSEs' overall ability to lead 
the single-family-owner market--while others were specific to the 
low-mod subgoal. Because the reader can refer to Appendix A, this

[[Page 24422]]

appendix provides a briefer discussion of the more general factors. 
The specific considerations that led to the subgoal for underserved 
areas can be organized around the following four topics:
    (1) The GSEs have the ability to lead the market. As discussed 
in Appendix A, the GSEs have the ability to lead the primary market 
for single-family-owner loans, which is their ``bread-and-butter'' 
business. Both GSEs have been dominant players in the home purchase 
market for years, funding 57 percent of the single-family-owner 
mortgages financed between 1999 and 2002. Through their many new 
product offerings and their various partnership initiatives, the 
GSEs have shown that they have the capacity to operate in 
underserved neighborhoods. They also have the staff expertise and 
financial resources to make the extra effort to lead the primary 
market in funding single-family-owner mortgages in undeserved areas.
    (2) The GSEs have lagged the market. Even though they have the 
ability to lead the market, they have not done so, as discussed 
above. The type of improvement needed to meet this new underserved 
area subgoal was demonstrated by Fannie Mae during 2001 and 2002. 
During 2001, underserved area loans declined as a percentage of 
primary market originations (from 32.2 to 30.9 percent), but they 
increased as a percentage of Fannie Mae's purchases (from 29.1 to 
29.8 percent); and during 2002, they increased further as a 
percentage of Fannie Mae's purchases (from 29.8 to 32.3 percent), 
placing Fannie Mae at the market level.
    (3) There are disparities among neighborhoods in access to 
mortgage credit. There remain troublesome neighborhood disparities 
in our mortgage markets, even after the substantial growth in 
conventional lending to low-income and minority neighborhoods that 
accompanied the so-called ``revolution in affordable lending''. 
There is growing evidence that inner city neighborhoods are not 
being adequately served by mainstream lenders. Some have concluded 
that a dual mortgage market has developed in our nation's financing 
system, with conventional mainstream lenders serving white families 
living in the suburbs and FHA and subprime lenders serving minority 
families concentrated in inner city neighborhoods.\57\ In addition 
to the unavailability of mainstream lenders, families living in 
these often highly-segregated neighborhoods face many additional 
hurdles, such as lack of cash for a down payment, credit problems, 
and discrimination. Immigrants and minorities, who 
disproportionately live in underserved areas, are projected to 
account for almost two-thirds of the growth in the number of new 
households over the next ten years. To meet the diverse and unique 
needs of these families, the GSEs must continue adjusting their 
underwriting guidelines and offering new products so that they can 
better serve these areas and hopefully attract more mainstream 
lenders into our inner city neighborhoods.
---------------------------------------------------------------------------

    \57\ See Dan Immergluck, Stark Differences: The Explosion of the 
Subprime Industry and Racial Hypersegmentation in Home Equity 
Lending, Woodstock Institute, October 2000; and Daniel Immergluck 
and Marti Wiles, Two Steps Back: The Dual Mortgage Market, Predatory 
Lending, and the Undoing of Community Development, Woodstock 
Institute, Chicago, IL, November 1999. For a nationl analyses, see 
the HUD report Unequal Burden: Income and Racial Disparities in 
Subprime Lending in America, April 2000; and Randall M. Scheesele, 
Black and White Disparities in Subprime Mortgage Refinance Lending, 
Housing Finance Working Paper No. HF-114, Office of Policy 
Development and Research, U.S. Department of Housing and Urban 
Development, April 2002.
---------------------------------------------------------------------------

    (4) There are ample opportunities for the GSEs to improve their 
performance. Mortgages are available for the GSEs to purchase in 
underserved areas. They can improve their performance and lead the 
primary market in purchasing loans in these low-income and high-
minority neighborhoods. The underserved areas share of the home 
purchase market has consistently been around 31 percent since 1995, 
which suggests a degree of underlying strength in the market. 
According to the market share data reported in Table A.30 of 
Appendix A, the GSEs have been purchasing about half of new 
originations in underserved areas, which means there are plenty of 
purchase opportunities left for them in the non-GSE portion of that 
market. In addition, the GSEs' purchases under the subgoal are not 
limited to new mortgages that are originated in the current calendar 
year. The GSEs can purchase loans from the substantial, existing 
stock of affordable loans held in lenders' portfolios, after these 
loans have seasoned and the GSEs have had the opportunity to observe 
their track record. In fact, both GSEs have often purchased seasoned 
loans that were used to finance properties in underserved areas (see 
Table A.11 in Appendix A).
    To summarize, although single-family-owner mortgages comprise 
the ``bread-and-butter'' of their business, the GSEs have lagged 
behind the primary market in financing properties in underserved 
areas. For the reasons given above, the Secretary believes that the 
GSEs can do more to raise the share of their home loan purchases in 
underserved areas. This can be accomplished by building on efforts 
that the enterprises have already started, including their new 
affordable lending products, their many partnership efforts, their 
outreach to inner city neighborhoods, their incorporation of greater 
flexibility into their underwriting guidelines, and their purchases 
of CRA loans. A wide variety of quantitative and qualitative 
indicators indicate that the GSEs' have the resources and financial 
strength to improve their affordable lending performance enough to 
lead the market in underserved areas.

6. Size of the Mortgage Market for Underserved Areas

    As detailed in Appendix D, the market for mortgages in 
underserved areas is projected to account for 35-40 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. Between 1999 and 
2002, the underserved areas market averaged 39 percent. 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.

7. The Underserved Areas Housing Goal for 2005-2008

    The proposed Underserved Areas Housing Goal for 2005 is 38 
percent of eligible purchases, rising to 39 percent in 2006 and 40 
percent in 2007 and 2008. Five percent of the seven percentage point 
increase in 2005 simply reflects the expanded coverage of HUD's 
definition in the 2000 Census tract data. The bonus points for small 
multifamily properties and owner-occupied 2-4 units, as well as 
Freddie Mac's Temporary Adjustment Factor, will no longer be in 
effect for goal counting purposes. It is recognized that neither GSE 
would have met the 38-percent target for 2005 in the past three 
years. Fannie Mae's performance is projected to have been 37.5 
percent in 2000, 35.7 percent in 2001, and 35.0 percent in 2002, 
under a 2000-based underserved area goal. Freddie Mac's performance 
is projected to have been 34.1 percent in 2000, 32.5 percent in 
2001, and 32.8 percent in 2002. However, the market for the 
Underserved Areas Housing Goal averaged 39 percent between 1999 and 
2002. Thus, the GSEs should be able to improve their performance 
enough to meet these targets of 38 percent-40 percent.
    The objective of HUD's proposed Underserved Areas Housing Goal 
is to bring the GSEs' performance to the upper end of HUD's market 
range estimate for this goal (35-40 percent), consistent with the 
statutory criterion that HUD should consider the GSEs' ability to 
lead the market for each Goal. To enable the GSEs to achieve this 
leadership, the Department is proposing modest increases in the 
Underserved Areas Housing Goal for 2005 which will increase further 
through 2008, to achieve the ultimate objective for the GSEs to lead 
the market under a range of foreseeable economic circumstances by 
2008. Such a program of staged increases is consistent with the 
statutory requirement that HUD consider the past performance of the 
GSEs in setting the Goals. Staged increases in the Underserved Areas 
Housing Goal will provide the enterprises with opportunity to adjust 
their business models and prudently try out business strategies, so 
as to meet the required 2008 level without compromising other 
business objectives and requirements.
    The analysis of this section implies that there are many 
opportunities for Fannie Mae and Freddie Mac to improve their 
overall performance on the Underserved Areas Housing Goal. The GSEs 
provided financing for 49 percent of the single-family and 
multifamily units that were financed in the conventional conforming 
market between 1999 and 2002. However, in the underserved areas 
portion of the market, the GSE's purchases represented only 41 
percent of the dwelling units that were financed in the market. 
Thus, there appears to be ample room for the GSEs to increase their 
purchases of loans that qualify for the Underserved Areas Housing 
Goal. In addition, there are

[[Page 24423]]

several market segments that would benefit from a greater secondary 
market role by the GSEs, and many of these market segments are 
concentrated in underserved areas.

8. Conclusions

    Having considered the projected mortgage market serving low- and 
moderate-income families, economic, housing and demographic 
conditions for 2005-08, and the GSEs' recent performance in 
purchasing mortgages in underserved areas the Secretary has 
determined that the proposed annual goal of 38 percent of eligible 
units financed in, 2005, 39 percent in 2006 and 2007, and 40 percent 
in 2008 is feasible. The Secretary has also proposed a subgoal of 33 
percent for the GSEs' purchases of single-family-owner mortgages in 
metropolitan areas, for 2005, rising to 34 percent in 2006 and 35 
percent in 2007 and 2008. The Secretary has considered the GSEs' 
ability to lead the industry as well as the GSEs' financial 
condition. The Secretary has determined that the proposed goals and 
subgoals are necessary and appropriate.

Appendix C--Departmental Considerations To Establish the Special 
Affordable Housing Goal

A. Introduction

1. Establishment of the Goal

    The Federal Housing Enterprises Financial Safety and Soundness 
Act of 1992 (FHEFSSA) requires the Secretary to establish a special 
annual goal designed to adjust the purchase by each GSE of mortgages 
on rental and owner-occupied housing to meet the unaddressed needs 
of, and affordable to, low-income families in low-income areas and 
very-low-income families (the Special Affordable Housing Goal).
    In establishing the Special Affordable Housing Goal, FHEFSSA 
requires the Secretary to consider:
    1. Data submitted to the Secretary in connection with the 
Special Affordable Housing Goal for previous years;
    2. The performance and efforts of the GSEs toward achieving the 
Special Affordable Housing Goal in previous years;
    3. National housing needs of targeted families;
    4. The ability of the GSEs to lead the industry in making 
mortgage credit available for low-income and very-low-income 
families; and
    5. The need to maintain the sound financial condition of the 
enterprises.

2. The Goal and Subgoals

    Special Affordable Housing Goal. The proposed rule provides that 
the Special Affordable Housing Goal will be 22 percent in 2005, 24 
percent in 2006, 26 percent in 2007, and 28 percent in 2008.
    Units That Count Toward the Goal. Units that count toward the 
Special Affordable Housing Goal include units occupied by low-income 
owners and renters in low-income areas, and very low-income owners 
and renters. Other low-income rental units in multifamily properties 
count toward the goal where at least 20 percent of the units in the 
property are affordable to families whose incomes are 50 percent of 
area median income or less, or where at least 40 percent of the 
units are affordable to families whose incomes are 60 percent of 
area median income or less.
    Multifamily Subgoal. HUD has established a special affordable 
subgoal for GSE purchases of multifamily mortgages. This subgoal is 
expressed in terms of a minimum annual dollar volume of multifamily 
mortgage purchases for units qualifying for the goal, rather than as 
a percentage of total units financed, as for the three housing 
goals. Both GSEs have consistently surpassed the multifamily subgoal 
since its establishment in 1996. The proposed rule increases the 
subgoal such that, of the total Special Affordable mortgage 
purchases each year, each GSE must purchase special affordable 
multifamily mortgages in dollar amount equal to at least 1 percent 
of its combined (i.e., single-family and multifamily) annual average 
mortgage purchases over the 2000-2002 period. The proposed level of 
this subgoal is $5.49 billion per year for Fannie Mae and $3.92 
billion per year for Freddie Mac.
    Single-Family-Owner Home Purchase Subgoal. The Department 
proposes to establish a subgoal of 17 percent for the share of each 
GSE's purchases of single-family-owner home purchase mortgages that 
qualify as special affordable and are originated in metropolitan 
areas in 2005, with the proposed subgoal rising to 18 percent in 
2006, and 19 percent in 2007 and 2008.

B. Consideration of the Factors

    In considering the factors under FHEFSSA to establish the 
Special Affordable Housing Goal, HUD relied upon data gathered from 
the American Housing Survey through 2000, the Census Bureau's 1991 
Residential Finance Survey, the 1990 and 2000 Censuses of Population 
and Housing, Home Mortgage Disclosure Act (HMDA) data for 1992 
through 2002, and annual loan-level data from the GSEs on their 
mortgage purchases through 2002. Appendix D discusses in detail how 
these data resources were used and how the size of the conventional 
conforming market for this goal was estimated.
    The remainder of Section C discusses the factors listed above, 
and Section D provides the Secretary's rationale for establishing 
the Special Affordable Housing Goal.

Factors 1 and 2. Data submitted to the Secretary in Connection With 
the Special Affordable Housing Goal for Previous Years, and the 
Performance and Efforts of the Enterprises Toward Achieving the 
Special Affordable Housing Goal in Previous Years

    The discussions of these two factors have been combined because 
they overlap to a significant degree.
    This section discusses each GSE's performance under the Special 
Affordable Housing Goal over the 1996-2002 period.\1\ As explained 
in Appendix A, the data presented are ``official HUD results'' 
which, in some cases, differ from goal performance reported by the 
GSEs in the Annual Housing Activities Reports (AHARs) that they 
submit to the Department.
---------------------------------------------------------------------------

    \1\ Performance for the 1993-95 period was discussed in HUD's 
Housing Goals 2000 Final Rule.
---------------------------------------------------------------------------

    The main finding of this section is that both Fannie Mae and 
Freddie Mac surpassed the Department's Special Affordable Housing 
Goals for each of the seven years during this period. Specifically:
     The goal was set at 12 percent for 1996; 
Fannie Mae's performance was 15.4 percent and Freddie Mac's 
performance was 14.0 percent.
     The goal was set at 14 percent for 1997-2000. 
Freddie Mac's performance was 15.2 percent in 1997, 15.9 percent in 
1998, 17.2 percent in 1999, and 20.7 percent in 2000; and Fannie 
Mae's performance was 17.0 percent in 1997, 14.3 percent in 1998, 
17.6 percent in 1999, and 19.2 percent in 2000.
     In HUD's Housing Goals 2000 Final Rule, the 
special affordable goal was set at 20 percent for 2001-03. As of 
January 1, 2001, several changes in counting requirements took 
effect for the special affordable goal, as follows: ``bonus points'' 
(double credit) for purchases of goal-qualifying mortgages on small 
(5-50 unit) multifamily properties and, above a threshold level, 
mortgages on 2-4 unit owner-occupied properties; a ``temporary 
adjustment factor'' (1.20 units credit, subsequently increased by 
Congress to 1.35 units credit) for Freddie Mac's purchases of goal-
qualifying mortgages on large (more than 50-unit) multifamily 
properties; changes in the treatment of missing data; a procedure 
for the use of imputed or proxy rents for determining goal credit 
for multifamily mortgages; and changes regarding the ``recycling'' 
of funds by loan originators. These changes are explained below. 
Fannie Mae's performance was 21.6 percent in 2001 and 21.4 percent 
in 2002, and Freddie Mac's performance was 22.6 percent in 2001 and 
21.4 percent in 2002, thus both GSEs surpassed this higher goal in 
both years. This section discusses the October 2000 counting rule 
changes in detail and provides data on what goal performance would 
have been in 2001-02 without these changes.\2\
---------------------------------------------------------------------------

    \2\ To separate out the effects of changes in counting rules 
that took effect in 2001, this section also compares performance in 
2001 to estimated performance in 2000 if the 2001 counting rules had 
been in effect in that year.
---------------------------------------------------------------------------

    In addition, HUD has established a special affordable subgoal 
for GSE purchases of multifamily mortgages. This subgoal is 
expressed in terms of a minimum annual dollar volume of multifamily 
mortgage purchases for units qualifying for the goal, rather than as 
a percentage of total units financed, as for the three housing 
goals. As discussed below, both GSEs surpassed the multifamily 
subgoal in each of these years.

a. Performance on the Special Affordable Housing Goal in 1996-2002

    HUD's Housing Goals 1995 Final Rule specified that in 1996 at 
least 12 percent of the number of units financed by each of the GSEs 
that were eligible to count toward the Special Affordable Housing 
Goal should qualify for the goal (that is, be for very low-income 
families or low-income families in low-income areas), and at least 
14 percent should qualify in 1997-2000. HUD's October

[[Page 24424]]

2000 rule made various changes in the goal counting rules, as 
discussed below, and increased the Special Affordable Housing Goal 
to 20 percent for 2001-03.
    In the December 1995 rule, the minimum special affordable 
multifamily subgoals for 1996-2000 were set at 0.8 percent of the 
total dollar volume of each GSE's mortgage purchases in 1994, or 
$1.29 billion annually for Fannie Mae and $0.99 billion annually for 
Freddie Mac. These subgoals were increased for 2001-03 in the 
October 2000 rule, to $2.85 billion annually for Fannie Mae and 
$2.11 billion annually for Freddie Mac, or 1.0 percent of the 
average dollar volume of each GSE's mortgage purchases over the 
1997-99 period.
    Table C.1 and Figure C.1 show performance on the special 
affordable goal and the special affordable multifamily subgoal over 
the 1996-2002 period, based on HUD's analysis. The table shows that 
Fannie Mae surpassed the goals by 3.4 percentage points and 3.0 
percentage points in 1996 and 1997, respectively, while Freddie Mac 
surpassed the goals by narrower margins, 2.0 and 1.2 percentage 
points. In 1998 Fannie Mae's performance fell by 2.7 percentage 
points, while Freddie Mac's performance continued to rise, by 0.7 
percentage point, thus for the first time Freddie Mac outperformed 
Fannie Mae on this goal. Freddie Mac showed a gain in performance to 
17.2 percent in 1999, while Fannie Mae exhibited an even greater 
gain, to 17.6 percent.
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[[Page 24427]]

    Both GSEs exhibited sharp gains in goal performance in 2000--
Fannie Mae's performance increased by 1.6 percentage points, to a 
record level of 19.2 percent, while Freddie Mac's performance 
increased even more, by 3.5 percentage points, which also led to a 
record level of 20.7 percent. Fannie Mae's performance was 21.6 
percent in 2001 and 21.4 percent in 2002; Freddie Mac's performance 
was 22.6 percent in 2001 and 21.4 percent in 2002. However, as 
discussed below, using consistent accounting rules for 2000-02, each 
GSE's Special Affordable Housing Goal performance in 2001 was below 
its performance in 2000, and in 2002 each enterprise's performance 
was below its 2001 performance level.
    With regard to the special affordable multifamily subgoal, 
Fannie Mae's purchases have exceeded the subgoal by wide margins in 
all years, with performance ranging from 184 percent of the goal in 
1996 to 315 percent of the goal in 1999. Fannie Mae's subgoal was 
more than doubled in the October 2000 rule, to a minimum of $2.85 
billion in each year from 2001 through 2003, but its qualifying 
purchases amounted to $7.36 billion, or 258 percent of the goal, in 
2001, and $7.57 billion, or 260 percent of the goal, in 2002.
    Freddie Mac has also exceeded its special affordable multifamily 
subgoals in every year, albeit by smaller margins than Fannie Mae. 
In 1996 Freddie Mac's special affordable multifamily mortgage 
purchases amounted to $1.06 billion, or 107 percent of the goal. 
This ratio rose to 122 percent in 1997, and exceeded 200 percent for 
each year from 1998 through 2000. Freddie Mac's subgoal was more 
than doubled in the October 2000 rule, to a minimum of $2.11 in each 
year from 2001 through 2003, but its qualifying purchases amounted 
to $4.65 billion, or 220 percent of the goal, in 2001, and $5.22 
billion, or 247 percent of the goal, in 2002.
    The official figures for Freddie Mac's special affordable goal 
performance presented above differ from the corresponding figures 
presented by Freddie Mac in its Annual Housing Activity Reports to 
HUD by 0.1-0.2 percentage point for 1996-2000, reflecting minor 
differences in the application of counting rules. The official 
figures for special affordable goal performance by both GSEs are the 
same as those submitted by the enterprises for both GSEs for 2001, 
and for Fannie Mae for 2002. However, for 1996-2000, HUD's official 
special affordable goal performance figures for Fannie Mae were 
approximately 1-3 percentage points lower than the corresponding 
figures reported by the enterprise. This was due to differences 
between HUD and Fannie Mae in the application of counting 
requirements applicable to purchases of portfolios of seasoned 
loans, based on a statutory requirement that the proceeds of such 
GSE purchases by the loan sellers should be ``recycled'' in order 
for the GSE to receive Special Affordable goal credit.\3\ This 
discrepancy did not persist in 2001-02 because of a change in 
counting requirements, described below. And for 2002, HUD's official 
goal performance figure was 21.4 percent, somewhat above the figure 
of 20.6 percent submitted to the Department by Freddie Mac.
---------------------------------------------------------------------------

    \3\ During 1996-2000 Freddie Mac took steps to acquire 
representations and warranties from lenders to attest that they were 
``recycling'' the proceeds from the sales of qualifying loans. 
Fannie Mae did not take such steps; rather, Fannie Mae excluded such 
loans from the denominator in making its own calculations of its 
special affordable goal performance. In 1996-2000 HUD counted all 
eligible loans in the denominator, and, in the absence of measures 
to verify ``recycling'' by Fannie Mae, did not award credit in the 
numerator of the special affordable goal for most of Fannie Mae's 
seasoned mortgage purchases.
---------------------------------------------------------------------------

    Fannie Mae's performance on the Special Affordable Housing Goal 
surpassed Freddie Mac's in 1996-97. This pattern was reversed in 
1998, as Freddie Mac surpassed Fannie Mae in goal performance for 
the first time, though by only 0.2 percentage point. This improved 
relative performance of Freddie Mac was due to its increased 
purchases of multifamily loans, as it re-entered that market, and to 
increases in the goal-qualifying shares of its single-family 
mortgage purchases. However, Fannie Mae again surpassed Freddie Mac 
in special affordable goal performance in 1999, 17.6 percent to 17.2 
percent; Freddie Mac regained the lead in 2000, 20.7 percent to 19.2 
percent. Freddie Mac's official performance also exceeded Fannie 
Mae's official performance in 2001, but this reflected a difference 
in the counting rules applicable to the two GSEs that was enacted by 
Congress; if the same counting rules were applied to both GSEs, 
Fannie Mae's performance would have exceeded Freddie Mac's 
performance, by 21.6 percent to 21.1 percent.
    In 2002, Freddie Mac's performance on the special affordable 
goal was the same as Fannie Mae's performance (21.4 percent), even 
though Freddie Mac had the advantage of the Temporary Adjustment 
Factor, which did not apply to performance by Fannie Mae. Freddie 
Mac's performance would have trailed Fannie Mae's without this 
factor, and in fact Freddie Mac would have only slightly exceeded 
the goal, at 20.2 percent.

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

    Several changes in the counting rules underlying the calculation 
of special affordable goal performance took effect beginning in 
2001. Most of these also applied to the low- and moderate-income 
goal and are discussed in Appendix A; only brief summaries of those 
changes are given here:
     Bonus points for multifamily and single-
family rental properties. Each qualifying unit in a small 
multifamily property counted as two units in the numerator in 
calculating special affordable goal performance on all of the goals 
for 2001-03. And, above a threshold equal to 60 percent of the 
average number of qualifying rental units financed in owner-occupied 
properties over the preceding five years, each qualifying unit in a 
2-4 unit owner-occupied property also counted as two units in the 
numerator in calculating goal performance.
     Freddie Mac's Temporary Adjustment Factor. 
Freddie Mac received a ``Temporary Adjustment Factor'' of 1.35 units 
of credit for each qualifying unit financed in ``large'' multifamily 
properties (i.e., those with 51 or more units) in the numerator in 
calculating special affordable goal performance for 2001-03.\4\ This 
factor did not apply to special affordable units in large 
multifamily properties whose mortgages were financed by Fannie Mae 
during this period.
---------------------------------------------------------------------------

    \4\ See Congressional Record, December 15, 2000, pp. H12295-96.
---------------------------------------------------------------------------

     Missing data for single-family properties. 
The GSEs may exclude loans with missing borrower income from the 
denominator if the property is located in a below-median income 
census tract, subject to a ceiling of 1 percent of total owner-
occupied units financed. The enterprises are also allowed to exclude 
single-family rental units with missing rental information from the 
denominator in calculating performance for the special affordable 
goal.
     Missing data and proxy rents for multifamily 
properties. If rent is missing for multifamily units, the GSEs may 
apply ``proxy rents,'' up to a ceiling of 5 percent of total 
multifamily units financed, in determining whether such units 
qualify for the special affordable goal. If such proxy rents cannot 
be estimated, these multifamily units are excluded from the 
denominator in calculating performance under these goals.
     Change in ``recycling'' requirements. Under 
Section 1333(b)(1)(B) of FHEFSSA, if a GSE acquires a portfolio of 
mortgages originated in a previous year (that is, seasoned 
mortgages) that qualify under the Special Affordable Housing goal, 
the seller must be ``engaged in a specific program to use the 
proceeds of such sales to originate additional loans that meet such 
goal'' and such purchases or refinancings must ``support additional 
lending for housing that otherwise qualifies under such goal'' in 
order to receive credit toward the goal. This has been referred to 
as the ``recycling requirement.'' The 2000 rule both clarified the 
conditions under which HUD would regard these statutory conditions 
to be satisfied and established certain categories of lenders that 
would be presumed to meet the recycling requirements. These included 
BIF-insured and SAIF-insured depository institutions that are 
regularly in the business of mortgage lending and which are subject 
to, and have received at least a satisfactory Community Reinvestment 
Act performance evaluation rating under specified conditions.\5\
---------------------------------------------------------------------------

    \5\ The revised requirements are codified at 24 CFR 81.14(e)(4). 
The changes are discussed in detail in the rule preamble, 68 FR 
65074-76 (October 31, 2000).
---------------------------------------------------------------------------

c. Effects of Changes in the Counting Rules on Goal Performance

    Because of the changes in special affordable goal counting rules 
that took effect in 2001, direct comparisons between official goal 
performance in 2000 and 2001-02 are somewhat of an ``apples-to-
oranges comparison.'' For this reason, the Department has calculated 
what performance would have been in 2000 under the 2001-03 rules; 
this may be compared with official performance in 2001-02--an 
``apples-to-apples

[[Page 24428]]

comparison.'' HUD has also calculated what performance would have 
been in 2001-02 under the 1996-2000 rules; this may be compared with 
official performance in 2000--an ``oranges-to-oranges comparison.'' 
These comparisons are presented in Table C.2.
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[[Page 24430]]

    Specifically, Table C.2 shows performance under the special 
affordable goal in three ways. Baseline A presents performance under 
the counting rules in effect for 1996-2000. Baseline B incorporates 
the technical changes in counting rules--changes in the treatment of 
missing data (including use of proxy rents), and changes in 
procedures related to the ``recycling'' requirement. Baseline C 
incorporates in addition to the technical changes the bonus points 
and, for Freddie Mac, the temporary adjustment factor. Baseline B 
corresponds to the counting approach proposed in this rule to take 
effect in 2005. Boldface figures under Baseline A for 1999-2000 and 
under Baseline C for 2001-02 indicate official goal performance 
based on the counting rules in effect in those years--e.g., for 
Freddie Mac, 17.2 percent in 1999, 20.7 percent in 2000, 22.6 
percent in 2001, and 21.4 percent in 2002.
     Performance on the Special Affordable Housing 
Goal under 1996-2000 Counting Rules Plus Technical Changes. If the 
``Baseline B'' counting approach had been in effect in 2000-02 and 
the GSEs' had purchased the same mortgages that they actually did 
purchase in those years, Fannie Mae would have surpassed the special 
affordable goal in both 2000 and 2001, but not in 2002, while 
Freddie Mac would have surpassed the goal in 2000 but fallen short 
in both 2001 and 2002. Specifically, Fannie Mae's performance would 
have been 21.4 percent in 2000, 20.2 percent in 2001, and 19.9 
percent in 2002. Freddie Mac's performance would have been 21.0 
percent in 2000, 19.3 percent in 2001, and 18.6 percent in 2002.
     Performance on the Special Affordable Housing 
Goal under 2001-2003 Counting Rules. If the 2001-03 counting rules 
had been in effect in 2000-02 and the GSEs' had purchased the same 
mortgages that they actually did purchase in that year (i.e., 
abstracting from any behavioral effects of ``bonus points,'' for 
example), both GSEs would have substantially surpassed the special 
affordable goal in all three years, but both GSEs' performance 
figures would have deteriorated somewhat from 2000 to 2001 and also 
from 2001 to 2002. Specifically, Fannie Mae's ``Baseline C'' 
performance would have been 22.2 percent in 2000, 21.6 percent in 
2001, and 21.4 percent in 2002. Freddie Mac's performance would have 
been 23.4 percent in 2000, 22.6 percent in 2001, and 21.4 percent in 
2002. Measured on this consistent basis, then, Fannie Mae's 
performance fell by 0.6 percentage point in 2001 and 0.2 percentage 
point in 2002. Freddie Mac's ``Baseline C'' performance fell by 0.8 
percentage point in 2001 and 1.2 percent in 2002. These reductions 
were primarily due to 2001-02 being years of heavy refinance 
activity.
    Details of Effects of Changes in Counting Rules on Goal 
Performance in 2001-02. As discussed above, counting rule changes 
that took effect in 2001 had significant impacts on the performance 
of both GSEs on the special affordable goal in 2001--3.0 percentage 
points for Fannie Mae and 3.5 percentage points for Freddie Mac. 
This section breaks down the effects of these changes on goal 
performance for both GSEs; results are shown in Table C.2.
     Freddie Mac. The largest impact of the 
counting rule changes on Freddie Mac's goal performance was due to 
the application of the temporary adjustment factor for purchases of 
mortgages on large multifamily properties, as enacted by Congress; 
this added 1.4 percentage points to goal performance in 2001, as 
shown in Table C.2. Bonus points for purchases of mortgages on small 
multifamily properties added 1.1 percentage points to performance, 
and bonus points for purchase of mortgages on owner-occupied 2-4 
unit rental properties added 0.7 percentage point to performance. 
The remaining impact (0.2 percentage point) was due to technical 
changes in counting rules--primarily, the exclusion of single-family 
units with missing information from the denominator in calculating 
goal performance. Changes in the Department's counting rules related 
to ``recycling'' did not play a role in Freddie Mac's performance on 
the special affordable goal. These same patterns also generally 
appeared in 2002.
     Fannie Mae. The temporary adjustment factor 
applied to Freddie Mac's goal performance, but not to Fannie Mae's 
performance, thus counting rule changes had less impact on its 
performance than on Freddie Mac's performance in 2001. The largest 
impacts of the counting rule changes on Fannie Mae's goal 
performance were due to the application of bonus points for 
purchases of mortgages on owner-occupied 2-4 unit rental properties, 
which added 0.9 percentage point to performance; bonus points for 
purchases of mortgages on small multifamily properties, which added 
0.4 percentage point to performance; and technical changes, which 
added 1.6 percentage points to performance--this included the change 
in the Department's rules regarding ``recycling'' and the exclusion 
of single-family units with missing information from the denominator 
in calculating goal performance.\6\ The use of proxy rents for 
multifamily properties played a minor role in determining Fannie 
Mae's special affordable goal performance. These same patterns also 
appeared in 2002.
---------------------------------------------------------------------------

    \6\ Exclusion of loans with missing information had a greater 
impact on Fannie Mae's goal performance than on Freddie Mac's goal 
performance.
---------------------------------------------------------------------------

d. Bonus Points for the Special Affordable Housing Goal

    As discussed above and in Appendix A, the Department established 
``bonus points'' to encourage the GSEs to step up their activity in 
2001-03 in two segments of the mortgage market--the small (5-50 
unit) multifamily mortgage market, and the market for mortgages on 
2-4 unit properties where 1 unit is owner-occupied and 1-3 units are 
occupied by renters. Bonus points did not apply to purchases of 
mortgages for owner-occupied 1-unit properties, for investor-owned 
1-4 unit properties, and for large (< 50-unit) properties, although 
as also discussed above, a ``temporary adjustment factor'' applied 
to Freddie Mac's purchases of qualifying mortgages on large 
multifamily properties.
    Bonus points for small multifamily properties. Each unit 
financed in a small multifamily property that qualified for any of 
the housing goals was counted as two units in the numerator (and one 
unit in the denominator) in calculating goal performance for that 
goal. For example, if a GSE financed a mortgage on a 40-unit 
property in which 10 of the units qualified for the special 
affordable goal, 20 units would be entered in the numerator and 40 
units in the denominator for this property in calculating goal 
performance.
    Fannie Mae financed 37,449 units in small multifamily properties 
in 2001 that were eligible for the special affordable goal, and 
58,277 such units in 2002--a two-year increase of more than 700 
percent from the 7,196 such units financed in 2000. Small 
multifamily properties also accounted for a greater share of Fannie 
Mae's multifamily business in 2001-02--7.4 percent of total 
multifamily units financed in 2001 and 13.2 percent in 2002, up from 
2.5 percent in 2000. However, HUD's 2000 rule reported information 
from the 1991 Residential Finance Survey that small multifamily 
properties accounted for 37 percent of all multifamily units, thus 
Fannie Mae was still less active in this market than in the market 
for large multifamily properties.
    Within the small multifamily market, there was no evidence that 
Fannie Mae targeted affordable properties to a greater extent in 
2001-02 than in 2000. That is, 61 percent of Fannie Mae's small 
multifamily units qualified for the special affordable goal in 2000; 
this fell to 46 percent in 2001 and 52 percent in 2002.
    Freddie Mac financed 50,299 units in small multifamily 
properties in 2001 that were eligible for the special affordable 
goal and 43,979 such units in 2002, a two-year increase of more than 
1300 percent from the 2,996 such units financed in 2000. Small 
multifamily properties also accounted for a significantly greater 
share of Freddie Mac's multifamily business in 2001-02--16.0 percent 
of total multifamily units financed in 2001 and 13.2 percent in 
2002, up from 1.8 percent in 2000.
    Within the small multifamily market, there was some evidence 
that Freddie Mac targeted affordable properties to a greater extent 
in 2001 than in 2000. That is, 55 percent of Freddie Mac's small 
multifamily units qualified for the special affordable goal in 2000; 
this rose to 73 percent in 2001 and 64 percent in 2002.
    In summary, then, there is evidence that bonus points for small 
multifamily properties had an impact on Fannie Mae's role in this 
market in 2001-02 and an even larger impact on Freddie Mac's role in 
this market. In addition, Fannie Mae has announced a program to 
increase its role in this market further in future years.\7\
---------------------------------------------------------------------------

    \7\ ``Fannie Courting Multifamily Sellers; Small Banks 
Balking,'' American Banker, January 13, 2003, p. 1.
---------------------------------------------------------------------------

    Bonus points for single-family rental properties. Above a 
threshold, each unit financed in a 2-4 unit property with at least 
one owner-occupied unit (referred to as ``OO24s'' below) that 
qualified for any of the housing goals was counted as two units in 
the numerator (and one unit in the denominator) in calculating goal 
performance

[[Page 24431]]

for that goal in 2001-03. The threshold was equal to 60 percent of 
the average number of such qualifying units over the previous five 
years. For example, Fannie Mae financed an average of 24,780 special 
affordable units in these types of properties between 1996 and 2000, 
and 55,118 such units in 2001. Thus Fannie Mae received 40,250 bonus 
points in this area in 2001--that is, 55,118 minus 60 percent of 
24,780. So 95,368 units were entered in the numerator for these 
properties in calculating special affordable goal performance.
    Fannie Mae financed 176,369 units in OO24s that were eligible 
for the special affordable goal in 2001 and 229,827 such units in 
2002, a two-year increase of nearly 200 percent from the 77,985 such 
units financed in 2000. However, Fannie Mae's total single-family 
business increased at approximately the same rate as its OO24 
business in 2001 and 2002, thus the share of this business accounted 
for by OO24s was the same in 2001-02 as in 2000--4 percent.
    Within the OO24 market, there was no evidence that Fannie Mae 
targeted special affordable properties to a greater extent in 2001-
02 than in 2000. That is, approximately 30 percent of Fannie Mae's 
OO24 units qualified for the special affordable goal in each of 
these three years.
    Freddie Mac financed 96,204 units in OO24s that were eligible 
for the special affordable goal in 2001 and 146,242 such units in 
2002, a two-year increase of nearly 200 percent from the 49,993 such 
units financed in 2000. However, Freddie Mac's total single-family 
business increased at approximately the same rate as its OO24 
business between 2000 and 2002, thus the share of this business 
accounted for by OO24s was the same in 2002 as in 2000--4 percent.
    As for Fannie Mae, within the OO24 market there was no evidence 
that Freddie Mac targeted special affordable properties to a greater 
extent in 2001-02 than in 2000. That is, approximately 36 percent of 
Freddie Mac's OO24 units qualified for the special affordable goal 
in each of these three years.

e. Effects of 2000 Census on Scoring of Loans Toward the Special 
Affordable Housing Goal

    Background. Scoring of housing units under the Special 
Affordable Housing Goal is based on data for mortgagors' incomes for 
owner-occupied units, rents for rental units, area median incomes, 
and, for units that are in the low-income but not the very low-
income range, decennial census data used to determine whether the 
median income for the area where the property is located is in the 
low-income range. Specifically, for single-family owner-occupied 
units scoring is based on--
     The mortgagors' income at the time of 
mortgage origination
     The median income of an area specified in the 
same way as for the Low- and Moderate-Income Housing Goal, that is: 
(i) For properties located in Metropolitan Statistical Areas (MSAs) 
the area is the MSA; and (ii) for properties located outside of 
MSAs, the area is the county or the non-metropolitan portion of the 
State in which the property is located, whichever has the larger 
median income, as of the year of mortgage origination (which may be 
for the current year or a prior year).
     Also, if the property is located in a 
Metropolitan Statistical Area (MSA), the determination for purposes 
of the Special Affordable Housing Goal involves data on median 
income of the MSA; or if the property is located elsewhere, the 
median income of the county or the non-metropolitan portion of the 
State in which the property is located, whichever is larger, as of 
the most recent decennial census.

Analogous specifications to those detailed in Appendix A for the 
Low- and Moderate-Income Housing Goal are applied in the case of the 
Special Affordable Housing Goal for rental units in single-family 
properties with rent data available (assuming no income data 
available for actual or prospective tenants), for rental units in 
multifamily properties where rent data are available, and for rental 
units in multifamily properties where rent data are not available.
    Thus, scoring loans under the Special Affordable Housing Goal 
requires a data series showing annual median incomes for MSAs, non-
metropolitan counties, and the non-metropolitan portions of states; 
decennial census data on median incomes for census tracts; and 
decennial census data on median incomes for MSAs, non-metropolitan 
counties, and the non-metropolitan portions of States.\8\
---------------------------------------------------------------------------

    \8\ In New England, MSAs were defined through mid-2003 in terms 
of Towns rather than Counties, and the portion of a New England 
county outside of any MSA was regarded as equivalent to a county in 
establishing the metropolitan or non-metropolitan location of a 
property. The MSA definitions established by the Office of 
Management and Budget (OMB) in June, 2003 defined MSAs in New 
England in terms of counties.
---------------------------------------------------------------------------

    For scoring loans purchased by the GSEs year-by-year from 1993 
through 2002, area median income estimates produced by HUD's 
Economic and Market Analysis Division were used. The same median 
income data series described in Appendix A for the Low- and 
Moderate-Income Goal was used. The determination of low-income areas 
was based on 1990 census data.
    2005 Procedure. Relative to the above procedure, scoring of 
loans purchased by the GSEs in and after 2005 will be affected by 
two factors--first, re-benchmarking of area median incomes to the 
2000 census as described in Appendix A, with a shift from 1990 to 
2000 census data for identifying low-income areas, and second, the 
Office of Management and Budget's June, 2003, re-specification of 
MSA boundaries based on analysis of 2000 census data.\9\
---------------------------------------------------------------------------

    \9\ HUD has deferred application of the 2003 MSA specification 
to 2005, pending completion of the present rulemaking process.
---------------------------------------------------------------------------

    Analysis. For purposes of specifying the level of the Special 
Affordable Housing Goal, the HUD estimates of area median incomes 
for MSAs, non-metropolitan counties, and the non-metropolitan parts 
of States, as described in Appendix A, were used in conjunction with 
the data identifying low-income areas based on the 2000 census, to 
re-score loans purchased by the GSEs between 1999 and 2002. The same 
data series were used further in estimating the share of loans 
originated in metropolitan areas that would be eligible to score 
toward the Special Affordable Housing Goal, from HMDA data. The 
results of the retrospective GSE analysis are provided in Table C.3. 
The results of the GSE-HMDA comparative analysis are presented in 
the next section.
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[[Page 24433]]

    Table C.3 shows three sets of estimates for each GSE, based 
respectively on the counting rules in place in 2001-2002 (but 
disregarding the bonus points and Temporary Adjustment Factor), on 
the addition of 2000 census re-benchmarking and low-income areas, 
and finally on the further addition of 2003 MSA specification.

F. The GSEs' Multifamily Special Affordable Purchases

    Since 1996 each GSE has been subject to an annual dollar-based 
subgoal for Special Affordable multifamily mortgage purchases, as 
discussed above. This subgoal was established for 1996-2000 as 0.8 
percent of the total dollar volume of single-family and multifamily 
mortgages purchased by the respective GSE in 1994. Thus Fannie Mae's 
subgoal was $1.29 billion per year and Freddie Mac's subgoal was 
$988 million per year during that period. Fannie Mae surpassed the 
subgoal by $1.08 billion, $1.90 billion, $2.24 billion, $2.77 
billion, and $2.50 billion in 1996, 1997, 1998, 1999, and 2000 
respectively, while Freddie Mac exceeded the subgoal by $18 million, 
$220 million, $1.70 billion, $1.27 billion, and $1.41 billion.
    The subgoal was established for 2001-03 as 1.0 percent of the 
average annual volume of each GSE's total mortgage purchases over 
the 1997-99 period. Thus Fannie Mae's subgoal was established as 
$2.85 billion per year and Freddie Mac's as $2.11 billion per year. 
In 2001 Fannie Mae exceeded its subgoal by $4.51 billion and Freddie 
Mac exceeded its subgoal by $2.54 billion. In 2002, Fannie Mae 
exceeded its subgoal by $4.72 billion and Freddie Mac exceeded its 
subgoal by $3.11 billion. Those subgoals are also in effect for 
2004. Table C.1 includes figures on subgoal performance, and they 
are depicted graphically in Figure C.2.

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[[Page 24435]]



g. Characteristics of the GSEs' Special Affordable Purchases

    The following analysis presents information on the composition 
of the GSEs' Special Affordable purchases according to area income, 
unit affordability, tenure of unit and property type (single- or 
multifamily).
    Tables C.4 and C.5 show that each GSE's reliance on multifamily 
housing units to meet the special affordable goal has been variable 
from year to year since 1996. Fannie Mae's multifamily purchases 
were at 37.7 percent in 1996 and 28.8 percent in 2001 with a high of 
44.0 percent in 1997 and a low of 27.8 percent in 1998. Freddie 
Mac's multifamily purchases represented 29.4 percent of all 
purchases qualifying for the goal in 1996 and 27.0 percent in 2001, 
with a high of 31.5 percent in 1997 and a low of 21.6 percent in 
1999. The two GSEs' purchase percentages for single-family owner 
properties exhibited a similar variability through this entire 
period, as did their purchases of mortgages financing single-family 
rental units from 1996 through 2000. Both GSEs' high points for 
mortgages financing single-family rental units occurred in 2001: 
Fannie Mae's purchase percentage was 17.1 percent while Freddie 
Mac's was 17.2 percent.

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[[Page 24438]]

    Tables C.4 and C.5 also show the allocation of units qualifying 
for the goal as related to the family income and area median income 
criteria in the goal definition. Very-low-income families (shown in 
the two leftmost columns in the tables) accounted for 80.8 percent 
of Fannie Mae's units qualifying under the goal in 1996, rising to 
83.6 percent in 2001. For Freddie Mac, very-low-income families 
accounted for 82.1 percent of units qualifying under the goal in 
1996, rising to 84.4 percent in 2001. In contrast, mortgage 
purchases from low-income areas (shown in the first and third 
columns in the tables) accounted for 37.0 percent of Fannie Mae's 
units qualifying under the goal in 1996, compared to 35.5 percent in 
2001. The corresponding percentages for Freddie Mac were 35.6 
percent in 1996 and 35.5 percent in 2001. Thus given the definition 
of special affordable housing in terms of household and area income 
characteristics, both GSEs have consistently relied substantially 
more on low-income characteristics of households than low-income 
characteristics of census tracts to meet this goal.

h. The GSEs' Performance Relative to the Market

    Section E.9 in Appendix A uses HMDA data and GSE loan-level data 
for home purchase mortgages on single-family-owner properties in 
metropolitan areas to compare the GSEs' performance in special 
affordable lending to the performance of depositories and other 
lenders in the conventional conforming market. (See Tables A.13 to 
A.16 in Appendix A.). There were two main findings with respect to 
the special affordable category. First, Freddie Mac and Fannie Mae 
have historically lagged depositories and the overall market in 
providing mortgage funds for special affordable borrowers. Between 
1993 and 2002, 11.8 percent of Freddie Mac's mortgage purchases were 
for special affordable borrowers, 12.7 percent of Fannie Mae's 
purchases, 15.4 percent of loans originated by depositories, and 
15.4 percent of loans originated in the conventional conforming 
market (without estimated B&C loans). For the recent years, the GSE-
market comparisons are as follows:

----------------------------------------------------------------------------------------------------------------
                                                                                                    Market (w/o
                              Year                                  Feddie Mac      Fannie Mae         B&C)
                                                                     (percent)       (percent)       (percent)
----------------------------------------------------------------------------------------------------------------
1999............................................................            12.8            12.5            17.0
2000............................................................            14.7            13.3            16.8
2001............................................................            14.4            14.9            15.6
2002............................................................            15.8            16.3            16.3
1996-2002 (average).............................................            12.8            13.5            16.0
1999-2002 (average).............................................            14.5            14.4            16.4
2001-2002 (average).............................................            15.1            15.6            16.0
----------------------------------------------------------------------------------------------------------------

During the period between 1999 and 2002, both GSEs' performance was 
at approximately 88 percent of the market--special affordable loans 
accounted for 14.4 percent of Fannie Mae's purchases, 14.5 percent 
of Freddie Mac's purchases, and 16.4 percent of loans originated in 
the conforming market.
    Second, while both GSEs have improved their performance over the 
past few years, Fannie Mae has been made more progress than Freddie 
Mac in closing its gap with the market. During the first two years 
(2001 and 2002) of HUD's new housing goal targets, the average share 
of Fannie Mae's purchases going to special affordable loans was 15.6 
percent, which was close to the market average of 16.0 percent. The 
share of Freddie Mac's purchases going to special affordable loans 
was 15.1 percent during this period.
    Section G in Appendix A discusses the role of the GSEs both in 
the overall special affordable market and in the different segments 
(single-family owner, single-family rental, and multifamily rental) 
of the special affordable market. The GSEs' special affordable 
purchases accounted for 35 percent of all special affordable owner 
and rental units that were financed in the conventional conforming 
market between 1999 and 2002. The GSEs' 35-percent share of the 
special affordable market was two-thirds of their 49-percent share 
of the overall market. Even in the owner market, where the GSEs 
account for 57 percent of the market, their share of the special 
affordable market was only 49 percent during this period. While the 
GSEs improved their market shares during 2001 and 2002, this 
analysis shows that the GSEs have not been leading the single-family 
market in purchasing loans that qualify for the Special Affordable 
Goal. There is room and ample opportunities for the GSEs to improve 
their performance in purchasing affordable loans at the lower-income 
end of the market. Section C.3 of this appendix discusses a home 
purchase subgoal designed to place the GSEs in such a leadership 
position in the special affordable single-family-owner market.

Factor 3. National Housing Needs of Low-Income Families in Low-
Income Areas and Very-Low-Income Families

    This discussion concentrates on very-low-income families with 
the greatest needs. It complements Section C of Appendix A, which 
presents detailed analyses of housing problems and demographic 
trends for lower-income families which are relevant to the issue 
addressed in this part of Appendix C.
    Data from the American Housing Survey demonstrate that housing 
problems and needs for affordable housing continue to be more 
pressing in the lowest-income categories than among moderate-income 
families, as established in HUD's analysis for the 1995 and 2000 
Final Rules. Table C.6 displays figures on several types of housing 
problems--high housing costs relative to income, physical housing 
defects, and crowding--for both owners and renters. Figures are 
presented for households experiencing multiple (two or more) of 
these problems as well as households experiencing a severe degree of 
either cost burden or physical problems. Housing problems in 2001 
continued to be much more frequent for the lowest-income groups.\10\ 
Incidence of problems is shown for households in the income range 
covered by the special affordable goal, as well as for higher income 
households.
---------------------------------------------------------------------------

    \10\ Tabulations of the 2001 American Housing Survey by HUD's 
Office of Policy Development and Research. The results in the table 
categorize renters reporting housing assistance as having no housing 
problems.
---------------------------------------------------------------------------

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[[Page 24440]]

    This analysis shows that priority problems of severe cost burden 
or severely inadequate housing are noticeably concentrated among 
renters and owners with incomes below 60 percent of area median 
income: 30.5 percent of renter households and 34.9 percent of owner 
households had priority problems. In contrast, in the next higher 
income range, up to 80 percent of area median income, 2.5 percent of 
renter households and 7.3 percent of owner households had priority 
problems. The table demonstrates the significance of affordability 
problems: Sixty-five percent of very-low-income renter families had 
rent burden over 30 percent of income; 35 percent had rent burden 
over 50 percent of income. Thirteen percent had moderately or 
severely inadequate housing; 6 percent lived in crowded conditions, 
defined as more than one person per room.

Factor 4. The Ability of the Enterprises To Lead the Industry in 
Making Mortgage Credit Available for Low-Income and Very-Low-Income 
Families

    The discussion of the ability of Fannie Mae and Freddie Mac to 
lead the industry in Section G of Appendix A is relevant to this 
factor--the GSEs' roles in the owner and rental markets, their role 
in establishing widely-applied underwriting standards, their role in 
the development of new technology for mortgage origination, their 
strong staff resources, and their financial strength. Additional 
analyses of the potential ability of the enterprises to lead the 
industry in the low- and very-low-income market appears below in 
Section D, which explains the Department's rationale for the home 
purchase subgoal for Special Affordable loans.

Factor 5. The Need To Maintain the Sound Financial Condition of the 
GSEs

    HUD has undertaken a separate, detailed economic analysis of 
this final rule, which includes consideration of (a) the financial 
returns that the GSEs earn on special affordable loans and (b) the 
financial safety and soundness implications of the housing goals. 
Based on this economic analysis, HUD concludes that the housing 
goals in this final rule raise minimal, if any, safety and soundness 
concerns.

C. Determination of the Special Affordable Housing Goal

    Several considerations, many of which are reviewed in Appendixes 
A and B and in previous sections of this Appendix, led to the 
determination of the Special Affordable Housing Goal, the 
multifamily special affordable subgoal, and the special affordable 
subgoal for home purchase loans on single-family-owner properties in 
metropolitan areas.

1. Severe Housing Problems

    The data presented in Section C.3 demonstrate that housing 
problems and needs for affordable housing are much more pressing in 
the lowest-income categories than among moderate-income families. 
The high incidence of severe problems among the lowest-income 
renters reflects severe shortages of units affordable to those 
renters. At incomes below 60 percent of area median, 34.7 percent of 
renters and 21.6 percent of owners paid more than 50 percent of 
their income for housing. In this same income range, 65.6 percent of 
renters and 42.4 percent of owners paid more than 30 percent of 
their income for housing. In addition, 31.5 percent of renters and 
23.8 percent of owners exhibited ``priority problems'', meaning 
housing costs over 50 percent of income or severely inadequate 
housing. Homeownership gaps and other disparities in the housing and 
mortgage markets discussed in Section H of Appendix A also apply to 
Special Affordable housing and mortgages.

2. GSE Performance and the Market

a. The GSEs' Special Affordable Housing Goals Performance

    In the October 2000 rule, the special affordable goal was set at 
20 percent for 2001-03. Effective on January 1, 2001, several 
changes in counting requirements came into effect for the special 
affordable goal, as follows: (a) ``Bonus points'' (double credit) 
for purchases of mortgages on small (5-50 unit) multifamily 
properties and, above a threshold level, mortgages on 2-4 unit 
owner-occupied properties; (b) a ``temporary adjustment factor'' 
(1.35 unit credit) for Freddie Mac's purchases of mortgages on large 
(more than 50 unit) multifamily properties; (c) changes in the 
treatment of missing data; (d) a procedure for the use of imputed or 
proxy rents for determining goal credit for multifamily mortgages; 
and (e) changes regarding the ``recycling'' of funds by loan 
originators. Fannie Mae's performance in 2001 was 21.6 percent and 
Freddie Mac's performance was 22.6 percent, thus both GSEs surpassed 
this higher goal.
    Counting requirements (a) and (b) expired at the end of 2003 
while (c)-(e) will remain in effect after that. If this counting 
approach--without the bonus points and the ``temporary adjustment 
factor''--had been in effect in 2000-2002, and the GSEs' had 
purchased the same mortgages that they actually did purchase in both 
years, then Fannie Mae's performance would have been 21.4 percent in 
2000, 20.2 percent in 2001, and 19.9 percent in 2002. Freddie Mac's 
performance would have been 21.0 percent in 2000, 19.3 percent in 
2001, and 18.6 percent in 2002. Fannie Mae would have surpassed the 
special affordable goal in both 2000 and 2001 while Freddie Mac 
would have surpassed the goal in 2000 and fallen short in 2001.
    The above performance figures are for the special affordable 
goal defined in terms of 1990 Census geography. Switching to 2000 
Census data slightly increases the coverage of special affordable 
goal, which increases the special affordable share of the GSEs' 
purchases by up to one percentage point. Based on 2000 Census 
geography, and excluding counting requirements (a) and (b), then 
Fannie Mae 's performance would have been 21.7 percent in 2000, 20.1 
percent in 2001, and 19.4 percent in 2002. Freddie Mac's performance 
would have been 20.8 percent in 2000, 19.1 percent in 2001, and 17.8 
percent in 2002.

b. Single-Family Market Comparisons in Metropolitan Areas

    The Special Affordable Housing Goal is designed, in part, to 
ensure that the GSEs maintain a consistent focus on serving the very 
low-income portion of the housing market where housing needs are 
greatest. Section C compared the GSEs' performance in special 
affordable lending to the performance of depositories and other 
lenders in the conventional conforming market for single-family home 
loans. The analysis showed that while both GSEs have improved their 
performance, they have historically lagged depositories and the 
overall market in providing mortgage funds for very low-income and 
other special affordable borrowers. Between 1999 and 2002, special 
affordable borrowers accounted for 14.4 percent of the home loans 
purchased by Fannie Mae, 14.5 percent of Freddie Mac's purchases, 
16.4 percent of home loans originated by depositories, and 16.4 
percent of all home loans originated in the conventional conforming 
market (without B&C loans). Section C also noted that while both 
GSEs have improved their performance over the past few years, Fannie 
Mae has made more progress than Freddie Mac in closing its gap with 
the market. During the first two years (2001 and 2002) of HUD's new 
housing goal targets, the average share of Fannie Mae's purchases 
going to special affordable loans was 15.6 percent, which was close 
to the market average of 16.0 percent. The share of Freddie Mac's 
purchases going to special affordable loans was 15.1 percent during 
this period. (See Figure C.3.)
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3. Ability To Lead the Single-Family Owner Market: A Special 
Affordable Sub Goal

    The Secretary believes the GSEs can play a leadership role in 
the special affordable market. Thus, the Department is proposing to 
establish a subgoal of 17 percent for each GSE's purchases of home 
purchase loans for special affordable families in the single-family-
owner market of metropolitan areas for 2005, rising to 18 percent in 
2006, and 19 percent in both 2007 and 2008. The purpose of this 
subgoal is to encourage the GSEs to improve their purchases of 
mortgages for very-low-income and minority first-time homebuyers who 
are expected to enter the housing market over the next few years. If 
the GSEs meet this goal, they will be leading the primary market by 
approximately one-half percentage point in 2005 and 2.5 percentage 
points by 2007 and 2008, based on the income characteristics of home 
purchase loans reported in HMDA. HMDA data show that special 
affordable families accounted for an average of 16.4 percent of 
single-family-owner loans originated in the conventional conforming 
market of metropolitan areas between 1999 and 2002--the special 
affordable market share was 16.0 percent for both the longer 1996-
2002 period and the shorter 2001-2002 period. Loans in the B&C 
portion of the subprime market are not included in these averages. 
As explained in Appendix D, HUD also projected special affordable 
shares for the market for 1999 to 2002 using the new 2000 Census 
geography and the new OMB specifications. For special affordable 
loans, the 1999-2002 market average using these projected data was 
also 16.4 percent.
    To reach the proposed 17-percent subgoal for 2005, both GSEs 
will have to improve their performance--Fannie Mae by 2.6 percentage 
points over its average performance of 14.4 percent between 1999 and 
2002, by 1.4 percentage points over its average performance of 15.6 
percent during 2001 and 2002, and by 0.7 percentage point over its 
16.3 percent performance in 2002; and Freddie Mac by 2.5 percentage 
points over its average performance of 14.5 percent between 1999 and 
2002, by 1.9 percentage points over its average performance of 15.1 
percent during 2001 and 2002, and by 1.2 percentage point over its 
15.8 percent performance in 2002. By 2007-2008 the required 
increases in subgoal performance over past performance will be 2 
percentage points higher than the increases cited in the preceding 
sentence. For example, Fannie Mae would have to increase its 
performance by 2.7 percentage points over its 16.3 percent 
performance in 2002; and Freddie Mac would have to increase its 
performance by 3.2 percentage points over its 15.8 percent 
performance in 2002. The special affordable performances of Fannie 
Mae and Freddie Mac were also projected to take into account the new 
2000 Census geography and the new OMB specifications. On average, 
the results with the new data were similar to the old data, but the 
differential was higher during 2002. For home purchase loans, the 
1999-2002 average performance for Fannie Mae was 14.3 percent with 
the projected data, versus 14.4 percent with the historical data; 
the largest difference was in 2002, when Fannie Mae's performance 
was 15.8 percent with the projected data, compared with 16.3 percent 
with the historical data. The 1999-2002 average performance for 
Freddie Mac was 14.1 percent with the projected data, versus 14.5 
percent with the historical data; the largest difference was also in 
2002, when Freddie Mac's performance was 15.1 percent with the 
projected data, compared with 15.8 percent with the historical data. 
Thus, the increases in each GSE's performance needed to meet the 
proposed special affordable home purchase subgoal in 2005-08 will be 
slightly higher than those noted above.
    The approach taken is for the GSEs to obtain their leadership 
position by staged increases in the special affordable subgoal; this 
will enable the GSEs to take new initiatives in a correspondingly 
staged manner to achieve the new subgoal each year. Thus, the 
increases in the special affordable subgoal are sequenced so that 
the GSEs can gain experience as they improve and move toward the new 
higher subgoal targets.
    The subgoal applies only to the GSEs' purchases in metropolitan 
areas because the HMDA-based market benchmark is only available for 
metropolitan areas. HMDA data for non-metropolitan counties are not 
reliable enough to serve as a market benchmark. The Department is 
also setting home purchase subgoals for the other two goals-
qualifying categories, as explained in Appendices A and B. Sections 
E.9 and G of Appendix A provide additional information on the 
opportunities for an enhanced GSE role in the special affordable 
segment of the home purchase market and on the ability of the GSEs 
to lead that market.
    The preamble and Appendix A discuss in some detail the factors 
that the Department considered when setting the subgoal for low- and 
moderate-income loans. Several of the considerations were general in 
nature--for example, related to the GSEs' overall ability to lead 
the single-family-owner market--while others were specific to the 
low-mod subgoal. Because the reader can refer to Appendix A, this 
appendix provides a briefer discussion of the more general factors. 
The specific considerations that led to the subgoal for special 
affordable loans can be organized around the following four topics:
    (1) The GSEs have the ability to lead the market. As discussed 
in Appendix A, the GSEs have the ability to lead the primary market 
for single-family-owner loans, which is their ``bread-and-butter'' 
business. Both GSEs have been dominant players in the home purchase 
market for years, funding 57 percent of the single-family-owner 
mortgages financed between 1999 and 2002. Through their many new 
product offerings and their various partnership initiatives, the 
GSEs have shown that they have the capacity to reach out to very-
low-income and other special affordable borrowers. They also have 
the staff expertise and financial resources to make the extra effort 
to lead the primary market in funding single-family-owner mortgages 
for special affordable borrowers.
    (2) The GSEs have lagged the market. Even though they have the 
ability to lead the market, they have not done so. While the GSEs 
have significantly improved their performance, according to numerous 
studies by the Department and independent researchers, they have 
historically lagged the primary market in providing funds for 
special affordable borrowers (see above GSE-market comparisons). The 
type of improvement needed to meet this new special affordable 
subgoal was demonstrated by Fannie Mae during 2001 and 2002. Between 
2000 and 2001, special affordable loans declined as a percentage of 
Freddie Mac's purchases (from 14.7 to 14.4 percent) and as a 
percentage of primary market originations (from 16.8 to 15.6 
percent), but they increased as a percentage of Fannie Mae's 
purchases (from 13.3 to 14.9 percent). During 2002, Fannie Mae 
further increased its special affordable share (from 14.9 percent 
tin 2001 to 16.3 percent in 2002), placing it at the market level. 
This subgoal is designed to encourage Fannie Mae as well as Freddie 
Mac to lead the special affordable market.
    (3) Disparities in Homeownership and Credit Access Remain. There 
remain troublesome disparities in our housing and mortgage markets, 
even after the ``revolution in affordable lending'' and the growth 
in homeownership that has taken place since the mid-1990s. The 
homeownership rate for African-American and Hispanic households 
remains 25 percentage points below that of white households. 
Minority families face many barriers in the mortgage market, such as 
lack of capital for down payment and lack of access to mainstream 
lenders (see above). Immigrants and minorities--many of whose very-
low-income levels will qualify them as special affordable--are 
projected to account for almost two-thirds of the growth in the 
number of new households over the next ten years. As emphasized in 
Appendix A, changing population demographics will result in a need 
for the primary and secondary mortgage markets to meet 
nontraditional credit needs, respond to diverse housing preferences, 
and overcome information and other barriers that many immigrants and 
minorities face. The GSEs have to increase their efforts in helping 
special affordable families--but so far they have played a 
surprisingly small role in serving minority first-time homebuyers. 
It is estimated that the GSEs accounted for 46.5 percent of all 
(both government and conventional) home loans originated between 
1999 and 2001; however, they accounted for only 14.3 percent of home 
loans originated for African-American and Hispanic first-time 
homebuyers. A subgoal for special affordable home purchase loans 
should increase the GSEs' efforts in important sub-markets such as 
the one for minority first-time homebuyers.
    (4) There are ample opportunities for the GSEs to improve their 
performance. Special affordable mortgages are available for the GSEs 
to purchase, which means they can improve their performance and lead 
the primary market in purchasing loans for these very-low-income 
borrowers. Sections B, C, and I of Appendix A and Section H of 
Appendix D explain that the special affordable lending market has 
shown an underlying strength over the past few years that is 
unlikely to vanish (without a

[[Page 24443]]

significant increase in interest rates or a decline in the economy). 
The special affordable share of the home purchase market has 
averaged 16.0 percent since 1996 and annually has ranged from 15.0 
percent to 17.0 percent. Second, the market share data reported in 
Table A.30 of Appendix A demonstrate that there are newly-originated 
loans available each year for the GSEs to purchase. The GSEs' 
purchases of single-family owner loans represented 57 percent of all 
single-family-owner loans originated between 1999 and 2002, compared 
with 49 percent of the special affordable loans that were originated 
during this period. Thus, half of the special affordable conforming 
market is not touched by the GSEs. As noted above, the situation is 
even more extreme for special sub-markets such the minority first-
time homebuyer market where the GSEs have only a minimal presence. 
Between 1999 and 2001, the GSEs purchased only 33 percent of 
conventional conforming loans originated for minority first-time 
homebuyers, even though they purchased 57 percent of all home loans 
originated in the conventional conforming market during that period. 
But also important, the GSEs' purchases under the subgoal are not 
limited to new mortgages that are originated in the current calendar 
year. The GSEs can purchase loans from the substantial, existing 
stock of special affordable loans held in lenders' portfolios, after 
these loans have seasoned and the GSEs have had the opportunity to 
observe their payment performance. In fact, based on Fannie Mae's 
recent experience, the purchase of seasoned loans appears to be one 
useful strategy for purchasing goals-qualifying loans.
    To summarize, although single-family-owner mortgages comprise 
the ``bread-and-butter'' of their business, the GSEs have lagged 
behind the primary market in financing special affordable loans. For 
the reasons given above, the Secretary believes that the GSEs can do 
more to raise the special affordable shares of the home loans they 
purchase on single-family-owner properties. This can be accomplished 
by building on efforts that the enterprises have already started, 
including their new affordable lending products aimed at special 
groups such as first-time homebuyers, their many partnership 
efforts, their outreach to inner city neighborhoods, their 
incorporation of greater flexibility into their underwriting 
guidelines, and their purchases of seasoned CRA loans. A wide 
variety of quantitative and qualitative indicators indicate that the 
GSEs' have the resources and financial strength to improve their 
special affordable performance enough to lead the market.

4. Size of the Overall Special Affordable Mortgage Market

    As detailed in Appendix D, single-family and multifamily special 
affordable mortgages are estimated to account for 24-28 percent of 
the dwelling units financed by conventional conforming mortgages; in 
estimating the size of the market, HUD used alternative assumptions 
about future economic and market affordability conditions that were 
less favorable than those that existed over the past several years. 
Between 1999 and 2002, the special affordable market averaged 28 
percent. HUD is well aware of the volatility of mortgage markets and 
the possible impacts on the GSEs' ability to meet the housing goals. 
Should conditions change such that the goals are no longer 
reasonable or feasible, the Secretary has the authority to revise 
the goals.

5. The Special Affordable Housing Goal for 2005-2008

    The proposed Special Affordable Housing Goal for 2005 is 22 
percent of eligible purchases, a two percentage point increase over 
the current goal of 20 percent, with the proposed goal rising to 24 
percent in 2006, 26 percent in 2007, and 28 percent in 2008. The 
bonus points for small multifamily properties and owner-occupied 2-4 
units, as well as Freddie Mac's Temporary Adjustment Factor, will no 
longer be in effect for goal counting purposes. It is recognized 
that neither GSE would have met the 22-percent target in the past 
three years. Under the new counting rules, Fannie Mae's special 
affordable performance is estimated to have been 18.6 percent in 
1999, 21.7 percent in 2000, 20.1 percent in 2001, and 19.4 percent 
in 2002--Fannie Mae would have to increase its performance in 2005 
by 2.0 percentage points over its average (unweighted) performance 
of 20.0 percent over these last four years. By 2008 this increase 
relative to average 1999-2002 performance would be 8.0 percentage 
points. Freddie Mac's performance is projected to have been 17.4 
percent in 1999, 20.8 percent in 2000, 19.1 percent in 2001, and 
17.8 percent in 2002--Freddie Mac would have to increase its 
performance in 2005 by 3.2 percentage points over its average 
(unweighted) performance of 18.8 percent over these last four years. 
By 2008 this increase relative to average 1999-2002 performance 
would be 9.2 percentage points. As explained in Appendix D, the 
Special Affordable market averaged 28 percent between 1999 and 2002. 
Thus, the GSEs should be able to improve their performance enough to 
meet the proposed targets of 22 percent in 2005, 24 percent in 2006, 
26 percent in 2007, and 28 percent in 2008.
    The objective of HUD's proposed Special Affordable Goal is to 
bring the GSEs' performance to the upper end of HUD's market range 
estimate for this goal (24-28 percent), consistent with the 
statutory criterion that HUD should consider the GSEs' ability to 
lead the market for each Goal. To enable the GSEs to achieve this 
leadership, the Department is proposing modest increases in the 
Special Affordable Goal for 2005 which will increase further, year-
by-year through 2008, to achieve the ultimate objective for the GSEs 
to lead the market under a range of foreseeable economic 
circumstances by 2008. Such a program of staged increases is 
consistent with the statutory requirement that HUD consider the past 
performance of the GSEs in setting the Goals. Staged annual 
increases in the Special Affordable Goal will provide the 
enterprises with opportunity to adjust their business models and 
prudently try out business strategies, so as to meet the required 
2008 level without compromising other business objectives and 
requirements.
    Section C compared the GSEs' role in the overall market with 
their role in the special affordable market. The GSEs' purchases 
provided financing for 23,580,594 dwelling units, which represented 
49 percent of the 48,270,415 single-family and multifamily units 
that were financed in the conventional conforming market between 
1999 and 2002. However, in the special affordable part of the 
market, the 4,595,201 units that were financed by GSE purchases 
represented only 35 percent of the 13,232,549 dwelling units that 
were financed in the market. Thus, there appears to ample room for 
the GSEs to improve their performance in the special affordable 
market. In addition, there are several market segments (e.g., first-
time homebuyers) that would benefit from a greater secondary market 
role by the GSEs, and special affordable borrowers are concentrated 
these markets.

6. Multifamily Special Affordable Subgoals

    Based on the GSEs' past performance on the special affordable 
multifamily subgoals, and on the outlook for the multifamily 
mortgage market, HUD is proposing that these subgoals be retained 
and increased for the 2005-2008 period. Unlike the overall goals, 
which are expressed in terms of minimum goal-qualifying percentages 
of total units financed, these subgoals for 2001-03 and in prior 
years have been expressed in terms of minimum dollar volumes of 
goal-qualifying multifamily mortgage purchases. Specifically, each 
GSE's special affordable multifamily subgoal is currently equal to 
1.0 percent of its average total (single-family plus multifamily) 
mortgage volume over the 1997-99 period. Under this formulation, in 
October 2000 the subgoals were set at $2.85 billion per year for 
Fannie Mae and $2.11 billion per year for Freddie Mac, in each of 
calendar years 2001 through 2003. These represented increases from 
the goals for 1996-2000, which were $1.29 billion annually for 
Fannie Mae and $0.99 billion annually for Freddie Mac. These 
subgoals are also in effect for 2004.
    HUD's Determination. The multifamily mortgage market and both 
GSEs' multifamily transactions volume grew significantly over the 
1993-2001 period, indicating that both enterprises have provided 
increasing support for the multifamily market, and that they have 
the ability to continue to provide further support for the market.
    Specifically, Fannie Mae's total eligible multifamily mortgage 
purchase volume increased from $4.6 billion in 1993 to $12.5 billion 
in 1998, and then jumped sharply to $18.7 billion in 2001 and $18.3 
billion in 2002. Its special affordable multifamily mortgage 
purchases followed a similar path, rising from $1.7 billion in 1993 
to $3.5 billion in 1998 and $4.1 billion in 1999, and also jumping 
sharply to $7.4 billion in 2001 and $7.6 billion in 2002. As a 
result of its strong performance, Fannie Mae's purchases have been 
at least twice its minimum subgoal in every year since 1997--247 
percent of the subgoal in that year, 274 percent in 1998, 315 
percent in 1999, 294 percent in 2000, and, under the new higher 
subgoal level, 258 percent in 2001, and 266 percent in 2002.
    Freddie Mac's total eligible multifamily mortgage purchase 
volume increased even

[[Page 24444]]

more sharply, from $0.2 billion in 1993 to $6.6 billion in 1998, and 
then jumped sharply in 2001 to $11.8 billion and $13.3 billion in 
2002. Its special affordable multifamily mortgage purchases followed 
a similar path, rising from $0.1 billion in 1993 to $2.7 billion in 
1998, and also jumping sharply to $4.6 billion in 2001 and $5.2 
billion in 2002. As a result of its strong performance, Freddie 
Mac's purchases have also been at least twice its minimum subgoal in 
every year since 1998--272 percent of the subgoal in that year, 229 
percent in 1999, 243 percent in 2000, and, under the new higher 
subgoal level, 220 percent in 2001, and 247 percent in 2002.
    The Special Affordable Housing Multifamily Subgoals set forth in 
this proposed rule are reasonable and appropriate based on the 
Department's analysis of this market. The Department's decision to 
retain the multifamily subgoal is based on the fact that HUD's 
analysis indicates that multifamily housing still serves the housing 
needs of lower-income families and families in low-income areas to a 
greater extent than single-family housing. By retaining the 
multifamily subgoal, the Department ensures that the GSEs continue 
their activity in this market, and that they achieve at least a 
minimum level of special affordable multifamily mortgage purchases 
that are affordable to lower-income families. The Department 
proposes to establish each GSE's special affordable multifamily 
subgoal as 1.0 percent of its average annual dollar volume of total 
(single-family and multifamily) mortgage purchases over the 2000-
2002 period. In dollar terms, the Department's proposal is $5.49 
billion per year in special affordable multifamily mortgage 
purchases for Fannie Mae, and $3.92 billion per year in special 
affordable multifamily mortgage purchases for Freddie Mac. These 
subgoals would be less than actual special affordable multifamily 
mortgage purchase volume in 2001 and 2002 for both GSEs; thus the 
Department believes that they would be feasible for the 2005-2008 
period.

7. Conclusion

    HUD has determined that the Special Affordable Housing Goal in 
this proposed rule addresses national housing needs within the 
income categories specified for this goal, while accounting for the 
GSEs' past performance in purchasing mortgages meeting the needs of 
very-low-income families and low-income families in low-income 
areas. HUD has also considered the size of the conventional mortgage 
market serving very-low-income families and low-income families in 
low-income areas. Moreover, HUD has considered the GSEs' ability to 
lead the industry as well as their financial condition. HUD has 
determined that a Special Affordable Housing Goal of 22 percent in 
2005, 24 percent in 2006, 26 percent in-2007, and 28 percent in 2008 
is both necessary and achievable. HUD has also determined that a 
multifamily special affordable subgoal for 2005-2008 set at 1.0 
percent of the average of each GSE's respective dollar volume of 
combined (single-family and multifamily) 1999-2001 mortgage 
purchases in is both necessary and achievable. Finally, HUD is 
proposing to establish a subgoal of 17 percent for the GSEs' 
purchases of single-family-owner mortgages that qualify for the 
special affordable goal and are originated in metropolitan areas, 
for 2005, with this subgoal rising to 18 percent in 2006, and 19 
percent in both 2007 and 2008. The Secretary has considered the 
GSEs' ability to lead the industry as well as the GSEs' financial 
condition. The Secretary has determined that the proposed goals, the 
proposed multifamily subgoals, and the proposed single-family-owner 
subgoals are necessary and appropriate.

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

A. Introduction

    In establishing the three housing goals, the Secretary is 
required to assess, among a number of factors, the size of the 
conventional market for each goal. This appendix explains HUD's 
methodology for estimating the size of the conventional market for 
each of the three housing goals. Following this overview, Section B 
summarizes the main components of HUD's market-share model and 
identifies those parameters that have a large effect on the relative 
market shares. Sections C and D discuss two particularly important 
market parameters, the size of the multifamily market and the share 
of the single-family mortgage market accounted for by single-family 
rental properties. Section E provides a more systematic presentation 
of the model's equations and main assumptions. Sections F, G, and H 
report HUD's estimates for the Low- and Moderate-Income Goal, the 
Underserved Areas Goal, and the Special Affordable Housing Goal, 
respectively.
    In developing this rule, HUD has followed the same basic 
approach that it followed in the last two GSE rules. HUD has 
carefully reviewed existing information on mortgage activity in 
order to understand the weakness of various data sources and has 
conducted sensitivity analyses to show the effects of alternative 
parameter assumptions. HUD is well aware of uncertainties with some 
of the data and much of this appendix is spent discussing the 
effects of alternative assumptions about data parameters and 
presenting the results of an extensive set of sensitivity analyses.
    In an earlier critique of HUD's market share model, Blackley and 
Follain (1995, 1996) concluded that conceptually HUD had chosen a 
reasonable approach to determining the size of the mortgage market 
that qualifies for each of the three housing goals.\1\ Blackley and 
Follain correctly note that the challenge lies in getting accurate 
estimates of the model's parameters. In their comments on the 2000 
Proposed GSE Rule, both Fannie Mae and Freddie Mac stated that HUD's 
market share model (outlined in Section B below) was a reasonable 
approach for estimating the goals-qualifying (low-mod, special 
affordable, and underserved areas) shares of the mortgage market. 
Freddie Mac stated:
---------------------------------------------------------------------------

    \1\ Dixie M. Blackley and James R. Follain, ``A Critique of the 
Methodology Used to Determine Affordable Housing Goals for the 
Government Sponsored Housing Enterprises,'' unpublished report 
prepared for Office of Policy Development and Research, Department 
of Housing and Urban Development, October 1995; and ``HUD's Market 
Share Methodology and its Housing Goals for the Government Sponsored 
Enterprises,'' unpublished paper, March 1996.

    We believe the Department takes the correct approach in the 
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.\2\
---------------------------------------------------------------------------

    \2\ See Freddie Mac, ``Comments on Estimating the Size of the 
Conventional Conforming Market for Each Housing Goal: Appendix III 
to the Comments of the Federal Home Loan Mortgage Corporation on 
HUD's Regulation of the Federal National Mortgage Association 
(Fannie Mae) and the Federal Home Loan Mortgage Corporation (Freddie 
Mac)'', May 8, 2000, page 1.
---------------------------------------------------------------------------

    Similarly, Fannie Mae stated that ``HUD has developed a 
reasonable model for assessing the size of the affordable housing 
market''.\3\
---------------------------------------------------------------------------

    \3\ See Fannie Mae, ``Fannie Mae's Comments on HUD's Regulation 
of the Federal National Mortgage Association (Fannie Mae) and the 
Federal Home Loan Mortgage Corporation (Freddie Mac)'', May 8, 2000, 
page 53.

    However, both GSEs have criticized HUD's implementation of its 
market methodology. Their major criticisms and HUD's responses to 
their criticisms can be found in Section B of Appendix D of the 2000 
Final Rule. HUD recognizes that there is no single, perfect data set 
for estimating the size of the affordable lending market and that 
available data bases on different sectors of the market must be 
combined in order to implement its market share model (as outlined 
in Section B below). As this appendix will show, HUD has carefully 
combined various mortgage market data bases in a manner which draws 
on the strength of each in order to implement its market methodology 
and to arrive at a reasonable range of estimates for the three 
goals-qualifying shares of the mortgage market. In this appendix, 
HUD demonstrates the robustness of its market estimates by reporting 
the results of numerous sensitivity analyses that examine a range of 
assumptions about the relative importance of the rental and owner 
markets and the goals-qualifying shares of the owner portion of the 
mortgage market.
    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. The next section 
provides an overview of HUD's market share model.

B. Overview of HUD's Market Share Methodology \4\
---------------------------------------------------------------------------

    \4\ Readers not interested in this overview may want to proceed 
to Section C, which begins the market analysis by examining the size 
of the multifamily market.
---------------------------------------------------------------------------

1. Definition of Market Share

    The size of the market for each housing goal is one of the 
factors that the Secretary is required to consider when setting the 
level

[[Page 24445]]

of each housing goal.\5\ Using the Low- and Moderate-Income Housing 
Goal as an example, the market share in a particular year is defined 
as follows:
---------------------------------------------------------------------------

    \5\ Sections 1332(b)(4), 1333(a)(2), and 1334(b)(4).

    Low- and Moderate-Income Share of Market: The number of dwelling 
units financed by the primary mortgage market in a particular 
calendar year that are occupied by (or affordable to, in the case of 
rental units) families with incomes equal to or less than the area 
median income divided by the total number of dwelling units financed 
---------------------------------------------------------------------------
in the conforming conventional primary mortgage market.

    There are three important aspects to this definition. First, the 
market is defined in terms of ``dwelling units'' rather than, for 
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.\6\ 
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).
---------------------------------------------------------------------------

    \6\ So-called ``jumbo'' mortgages, greater than $300,700 in 2002 
for 1-unit properties, are excluded in defining the conforming 
market. There is some overlap of loans eligible for purchase by the 
GSEs with loans insured by the FHA and guaranteed by the Veterans 
Administration.
---------------------------------------------------------------------------

2. Three-Step Procedure

    Ideally, computing the low- and moderate-income market share 
would be straightforward, consisting of three steps:
    Step 1: Projecting the market shares of the four major property 
types included in the conventional conforming mortgage market, 
i.e.--
    (a) Single-family owner-occupied dwelling units (SF-O units);
    (b) Rental units in 2-4 unit properties where the owner occupies 
one unit (SF 2-4 units); \7\
---------------------------------------------------------------------------

    \7\ The owner of the SF 2-4 property is counted in (a).
---------------------------------------------------------------------------

    (c) Rental units in one-to-four unit investor-owned properties 
(SF Investor units); and,
    (d) Rental units in multifamily (5 or more units) properties (MF 
units).\8\
---------------------------------------------------------------------------

    \8\ Property types (b), (c), and (d) consist of rental units. 
Property types (b) and (c) must sometimes be combined due to data 
limitations; in this case, they are referred to as ``single-family 
rental units'' (SF-R units).
---------------------------------------------------------------------------

    Step 2: Projecting the ``goal percentage'' for each of the above 
four property types (for example, the ``Low- and Moderate-Income 
Goal percentage for single-family owner-occupied properties'' is the 
percentage of those dwelling units financed by mortgages in a 
particular year that are occupied by households with incomes below 
the area median).
    Step 3: Multiplying the four percentages in (2) by their 
corresponding market shares in (1), and summing the results to 
arrive at an estimate of the overall share of dwelling units 
financed by mortgages that are occupied by low- and moderate-income 
families.
    The four property types are analyzed separately because of their 
differences in low- and moderate-income occupancy. Rental properties 
have substantially higher percentages of low- and moderate-income 
occupants than owner-occupied properties. This can be seen in the 
top portion of Table D.1, which illustrates Step 3's basic formula 
for calculating the size of the low- and moderate-income market.\9\ 
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.
---------------------------------------------------------------------------

    \9\ 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.
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BILLING CODE 4210-27-P

[[Page 24446]]

[GRAPHIC] [TIFF OMITTED] TP03MY04.069

BILLING CODE 4210-27-C

[[Page 24447]]

    To examine the other housing goals, the ``goal percentages'' in 
Step 2 would be changed and the new ``goal percentages'' would be 
multiplied by Step 1's property distribution, which remains 
constant. For example, the Underserved Areas Goal \10\ 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.\11\
---------------------------------------------------------------------------

    \10\ This goal will be referred to as the ``Underserved Areas 
Goal''.
    \11\ The example in Table D.1 is based on 1990 Census tract 
geography. As explained in Section G, switching to 2000 Census tract 
geography (scheduled for 2005) increases the underserved areas 
market share by approximately five percentage points.
---------------------------------------------------------------------------

3. Data Issues

    Unfortunately, complete and consistent mortgage data are not 
readily available for carrying out the above three steps. A single 
data set for calculating either the property shares or the housing 
goal percentages does not exist. However, there are several major 
data bases that provide a wealth of useful information on the 
mortgage market. HUD combined information from the following 
sources: the Home Mortgage Disclosure Act (HMDA) reports, the 
American Housing Survey (AHS), HUD's Survey of Mortgage Lending 
Activity (SMLA), 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 initial rule-making process during 1995; this was also an 
issue that the GSEs focused on in their comments on the 2000 
proposed rule. Because most renters qualify under the Low- and 
Moderate-Income Goal, the chosen market size for multifamily can 
have a substantial effect on the overall estimate of the low- and 
moderate-income market (as well as on the estimate of the special 
affordable market). Thus, it is important to consider estimates of 
the size of the multifamily market in some detail, as Section C 
does. In addition, given the uncertainty surrounding estimates of 
the multifamily mortgage market, it is important to consider a range 
of market estimates, as Sections F-H do.
    Goal Percentages. To derive the goal percentages for each 
property type, HUD relied heavily on HMDA, AHS, and POMS data. For 
single-family-owner originations, HMDA provides comprehensive 
information on borrower incomes and census tract locations for 
metropolitan areas. Unfortunately, it provides no information on the 
incomes of renters living in mortgaged properties (either single-
family or multifamily) or on the rents (and therefore the 
affordability) of rental units in mortgaged properties. The AHS, 
however, does provide a wealth of information on rents and the 
affordability of the outstanding stock of single-family and 
multifamily rental properties. An important issue here concerns 
whether rent data for the stock of rental properties can serve as a 
proxy for rents on newly-mortgaged rental properties. During the 
2000 rule-making process, POMS data were used to examine the rents 
of newly-mortgaged rental properties; thus, the POMS data 
supplements the AHS data. The data base issues as well as other 
technical issues related to the goal percentages (such as the need 
to consider a range of mortgage market environments) are discussed 
in Sections F, G, and H, which present the market share estimates 
for the Low- and Moderate-Income Goal, the Underserved Areas Goal, 
and the Special Affordable Goal, respectively.

4. Conclusions

    HUD is using the same basic methodology for estimating market 
shares that it used in 1995 and 2000. 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.
    In considering the levels of the goals, HUD carefully examined 
past comments by the GSEs and others on the methodology used to 
establish the market share for each of the goals. Based on that 
thorough evaluation, as well as HUD's additional analysis for this 
Proposed Rule, HUD concludes that its basic methodology is a 
reasonable and valid approach to estimating market shares. As in the 
past, HUD recognizes the uncertainty regarding some of these 
estimates, which has led the Department to undertake a number of 
sensitivity and other analyses to reduce this uncertainty and also 
to provide a range of market estimates (rather than precise point 
estimates) for each of the housing goals.

C. Size of the Conventional Multifamily Mortgage Market \12\
---------------------------------------------------------------------------

    \12\ This section is based on analysis by Jack Goodman under 
contract with the Urban Institute.
---------------------------------------------------------------------------

    This section provides estimates of (a) the annual dollar volume 
of conventional multifamily mortgage originations and (b) the annual 
average loan amount per unit financed. The estimates build on 
research reported in the Final Rule on HUD's Regulation of Fannie 
Mae and Freddie Mac as published in the Federal Register on October 
31, 2000, especially in Appendix D. That material from the 2000 Rule 
will not be repeated here but will be referenced or summarized where 
appropriate.
    The section uses the information on dollar volume of multifamily 
originations and average loan amounts to estimate the number of 
multifamily units financed each year as a percentage share of the 
total (both single-family and multifamily) number of dwelling units 
financed each year; the years covered include 1991 to 2002. This 
percentage share, called the ``multifamily mix'', is an important 
parameter in HUD's projection model of the mortgage market for 2005-
08.
    Estimating this ``multifamily mix'' is important because 
relative to its share of the overall housing market, the multifamily 
rental sector has disproportionate importance for the housing goals 
established for Fannie Mae and Freddie Mac. This is because most 
multifamily rental units are occupied by households with low or 
moderate incomes. In 2001, for example, Freddie Mac purchased 
mortgages on approximately 3.5 million housing units, of which only 
12 percent were multifamily rental units. However, of Freddie Mac's 
purchases qualifying as mortgages on low- and moderate-income 
housing, fully 25 percent of the units financed were multifamily 
rental units. Fannie Mae's experience is similar. Ten percent of all 
housing units on which mortgages were purchased in 2001 were 
multifamily rental units, but 21 percent of the units with 
qualifying mortgages were multifamily rentals.
    The methods used in the 2000 Rule for estimating the size of the 
multifamily mortgage market and related variables were the product 
of extensive research by HUD and review by interested parties. The 
approach here is first to extend those estimates through 2002 using 
the same methods as in the 2000 Rule, and then to present 
alternative methods, along with commentary.

1. Data Sources

    The data sources available for estimating the size of the 
multifamily mortgage market are more limited in scope and timeliness 
than was the case for the 2000 Rule. Among the key sources described 
in detail in the 2000 Rule, the following are now less useful:
    Survey of Mortgage Lending Activity. This survey has been 
discontinued; estimates are available only through 1997.
    Residential Finance Survey: The 1991 Residential Finance Survey 
(RFS) is now 13 years out of date.
    Urban Institute Statistical Model: This model, developed in 1995 
and calibrated

[[Page 24448]]

using data from 1975-1990, is now even further removed from its 
calibration period and probably captures current market conditions 
less well.
    Estimates from the GSEs: As part of their comments on the 
proposed 2000 Rule, Fannie Mae and Freddie Mac shared with HUD their 
own estimates of the size of the multifamily mortgage market.
    Fortunately, several key sources are available with the 
timeliness and quality comparable to the sources used during 
development of the 2000 Rule. These sources are: the Home Mortgage 
Disclosure Act (HMDA); activity reports submitted to HUD and the 
Office of Federal Enterprise Oversight (OFHEO) by Fannie Mae and 
Freddie Mac; non-GSE mortgage-backed security issuance from the 
Commercial Mortgage Alert database; and multifamily mortgage 
activity by life insurance companies, as estimated by the American 
Council of Life Insurers (ACLI). For background information on each 
of these sources, readers are referred to Appendix D of the 2000 
Rule.

2. Estimates Based on ``HUD New'' Methodology

    In the 2000 Rule, HUD developed a new methodology for estimating 
aggregate multifamily conventional loan originations. The method, 
here labeled ``HUD New'', was developed to make full use of the 
available data, and in particular the four sources listed above, 
which encompass most of the multifamily mortgage market.
    The advantages of HUD New are that it provides reasonably 
complete coverage of the market, produces those estimates within 
nine months of the end of the year, generally includes only current 
originations and avoids double counting. The main disadvantage of 
HUD New is that it produces a lower bound estimate. Some loan 
originators are missed, including pension funds, government entities 
at the federal, state, and local levels, real estate investment 
trusts, and some mortgage bankers. Also excluded are loans made by 
private individuals and partnerships. In addition to these 
exclusions, estimates from the covered lenders require some 
judgmental adjustments to conform to the definitions and time 
intervals of HUD New.
    Despite these limitations, HUD New is one sound way to estimate 
the size of the multifamily conventional mortgage market. The method 
requires unavoidable judgment calls on which analysts will differ. 
However, due to the reasonableness of the HUD New approach, the 
value of maintaining continuity in estimation methods, and the fact 
that no data has become available in the past few years that would 
argue for modifying HUD New, it is used here for the baseline 
estimate of the size of the conventional multifamily mortgage market 
in 2000, 2001 and 2002.
    The estimates from HUD New are presented in Table D.2. This 
table is the counterpart of Table D.5 in the 2000 Rule. The 
historical years have two columns each, one for the estimates 
presented in the 2000 Rule and one for estimates independently 
produced as part of this research. Footnotes to the table provide 
more complete descriptions of the components. Additional background 
on the calculations is provided in the 2000 Rule (Appendix D, 
Section C).
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    The revisions to the historical estimates result from both 
revisions to some of the input data and recalculations. For the 
years 1995 through 1998, the revisions are small for the estimates 
of total originations. The only one of note is a 5 percent upward 
revision to the estimate for 1995, prompted by a recalculation of 
the entry for life insurance companies. The revision to 1999 is 
larger, and results mostly from the substitution of the actual HMDA 
results for that year for the projected value used in the 2000 Rule. 
Surprisingly, the revised estimate for 2000 based on complete data 
for that year only varies slightly from the projection made at the 
time of the 2000 Rule.
    Most of the historical estimates produced in 2000 can be 
replicated or closely approximated, including those for Fannie and 
Freddie, CMBS, HMDA, and life insurance companies. The replicability 
of the CMBS figures is especially heartening, in light of all the 
selection criteria and hand calculations required to generate those 
estimates from the CMBS database. (In the 2000 Rule, the estimates 
for Freddie Mac and CMBS originations in 1997 appear to have been 
switched, and the revised estimates make this correction.)
    The revised figures for 1999 and 2000 indicate that total 
conventional originations dropped 8 percent in 1999 from 1998's very 
strong level and another 13 percent in 2000. However, the HUD New 
estimate indicates that total conventional originations then jumped 
40 percent in 2001 and further increased 15 percent in 2002. Judging 
from Survey of Mortgage Lending Activity estimates since 1970, the 
2002 number is a new record high. For 2002, most of the increased 
volume is due to increases by HMDA lenders and life insurance 
companies.
    One possible concern is that the significant increase in the 
HMDA number in 2002 was caused by the FFIEC relaxing its eligibility 
requirements between 2001 and 2002. This concern turns out to be 
unfounded. The FFIEC actually raised its eligibility requirements. 
The level of assets required by FFIEC to be reported to HMDA 
increased from $31 million in 2001 to $32 million in 2002. In 
addition, the number of HMDA reporters decreased from 7,771 in 2001 
to 7,638 in 2002.

3. An Alternative Method

    The HUD New method makes use of all the available sources of 
data on individual origination sources in attempting to estimate 
total conventional mortgage originations. However, as discussed in 
the 2000 Rule and summarized above, unavoidable gaps in coverage 
make the resulting HUD New figures lower-bound estimates of actual 
originations rather than best ``point'' estimates. In addition, even 
for those loans that are available, certain assumptions must be made 
to convert the available data into estimates corresponding to the 
desired definition and time periods.
    An alternative to the bottom-up approach of HUD New avoids some 
of the data problems. The Federal Reserve's Flow of Funds accounts 
provide the most complete and timely set of estimates of multifamily 
mortgage credit. The Flow of Funds statistics refer to net changes 
in credit outstanding rather than gross originations. Specifically, 
balance sheet estimates of mortgage assets of lenders are used to 
produce estimated changes in holdings of mortgages over time. An 
alternative label for the resulting time series is ``net change in 
mortgage debt outstanding.''
    The historical relationship between gross originations and net 
change can be used to estimate recent origination volume. Separate 
information on FHA multifamily activity can be used to convert the 
total originations to estimates of only conventional originations. 
The Flow of Funds method that is described in this section will be 
called ``FoF-based.''
    Flow of Funds estimates of mortgage debt outstanding are based 
on data from sources of varying accuracy and timeliness. Bank and 
thrift institution holdings, taken from regulatory filings, are by 
all accounts highly accurate, as are those from the government 
sponsored agencies and direct Federal government holdings. The 
private MBS data and the life insurance company figures, both taken 
from Wall Street sources, are also thought to be reasonably 
accurate. Less accurate are the estimates of loans made by private 
individuals and certain institutions, for which comprehensive data 
on loans outstanding is provided only once every ten years, through 
the Residential Finance Survey. Fortunately, the depository 
institutions, GSEs, and mortgage-backed securities account for the 
bulk of all holdings of mortgage debt (approximately 72 percent, 
according to the Flow of Funds estimates for year-end 2001).
    The net change in mortgage debt outstanding in any year is the 
lower bound on originations. This is because the net change is 
defined as originations less the sum of principal repayments and 
charge offs. Historically loan originations have exceeded the net 
change by a considerable margin in both the multifamily and single-
family markets. There are several reasons why the relationship of 
originations to net change differs between the multifamily and 
single-family sectors, but the basic principles apply to both 
sectors.
    Table D.3 presents the annual estimates from the Flow of Funds. 
Also shown are the estimates of multifamily conventional 
originations as published in Table D.10 from the 2000 rule, and FHA 
originations from HUD administrative records.
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[[Page 24452]]

    The ratio of mortgage originations to net change should be 
positively correlated with the proportion of total originations that 
are refinancings, for which the net change in mortgage debt would be 
expected to be low relative to that on loans taken out in connection 
with a property acquisition. (This is the pattern observed in the 
single-family mortgage market.) Refinancings, in turn, would be 
expected to be prevalent relative to purchase loans at times when 
interest rates are low relative to their recent past.
    The historical evidence generally supports this expectation 
regarding the relationship of originations to net lending. As shown 
in Table D.3, total originations have been highest relative to net 
change when interest rates have been low relative to their recent 
past. The ten-year Treasury yield, a common benchmark for pricing 
multifamily mortgages, has generally trended down since 1990. The 
early 1990s were all marked by high originations relative to net 
change, and these were also years in which interest rates were 
particularly low relative to their trailing five-year averages. In 
1996 and 1997, by contrast, originations were less high relative to 
net change, and these were years in which interest rates were only 
slightly lower than their five-year trailing averages.
    In estimating conventional originations for 1999-2002, the 1998 
experience is a useful benchmark. That year, total originations 
exceeded the net change by about 80 percent, as shown in Table D.3. 
There was also a big drop in interest rates in 1998 relative to the 
recent past, providing an incentive for refinancings. As shown in 
the table, interest rates rose slightly in 1999 and again in 2000, 
presumably diminishing the incentive to refinance. Nonetheless, the 
net change in mortgage debt was higher in 1999 and 2000 than it had 
been in 1998.
    Putting all this together, it seems that the appropriate ratio 
of total originations to net change to apply to 1999 and 2000 would 
be below that of 1998 and of most other years of the 1990s. Applying 
a ratio of 1.5 to the net change estimates in 1999 and 2000 results 
in a total originations estimate of approximately $56 billion. 
Subtracting the $4 billion in FHA originations results in estimates 
of $52 billion for conventional originations in each year. A 
subjective confidence band around this point estimate is at least +/
-$2 billion.
    Turning to the estimate for 2001, the first thing to note is 
that net change in mortgage debt jumped to $48 billion from $37 
billion of the previous two years. The second thing to note is that 
interest rates fell by nearly a percentage point in 2001 relative to 
their past average. For both of these reasons, total originations in 
2001 would be expected to have been higher than in 1999 or 2000. How 
much higher is a subjective judgment, but 1.5 would seem an 
appropriate multiple to apply to the net change number in 2001. This 
is the same multiple as in 1999 and 2000, despite the added 
refinancing incentive in 2001. By the beginning of 2001, there were 
relatively few properties ``at risk'' of refinancing. Many 
presumably had refinanced in one of the preceding years, and lock-
out provisions, yield maintenance agreements, and other loan 
conditions may have kept these properties from coming in for 
refinancings. Also, there may have been some short-run capacity 
problems in the multifamily loan origination industry in 2001 that 
further curtailed volume.
    Applying the 1.5 multiple to 2001's net change of $48 billion 
yields a total originations estimate of $72 billion. Subtracting the 
$5 billion of FHA business results in a conventional originations 
estimate of $67 billion, to which a subjective confidence band of at 
least +/-$2 billion appears warranted.
    As seen in Table D.3, the Flow of Funds methodology indicates 
that total conventional originations decreased 7.5% between 2001 and 
2002. In 2002, the net change in mortgage debt decreased slightly to 
$44 billion. Using the 1.5 multiple for 2002's net change of $44.2 
billion yields a total originations estimate of $66 billion. 
Subtracting $4.5 billion of FHA business results in a conventional 
originations estimate of $62 billion.
    This Flow of Funds estimate is over $5 billion less than the 
estimate from HUD New. This is surprising given that the HUD New 
method is supposed to serve as a lower boundary on the size of the 
multifamily market, while the Flow of Funds method is designed to 
produce a higher ``point'' estimate of the actual size of the 
market.

4. Most Likely Range

    In the 2000 Rule, estimates of conventional multifamily loan 
originations from various sources and methods were evaluated in 
determining the most likely range of annual originations. Those 
estimates were summarized in Table D.10 in the 2000 Rule. Some of 
the estimates from that table are reproduced below, in Table D.4, 
along with updates and estimates from the Flow of Funds method.
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[[Page 24454]]

    Both HUD New (column 4 in Table D.4) and FoF-based 
(column 9) indicate a surge in lending activity in 2001. 
Some corroboration of this jump is provided by other indicators, 
flawed though they may be. HMDA has well-documented coverage 
problems with multifamily loans, but it is noteworthy that HMDA-
estimated conventional originations stayed in the same general range 
($26 to $31 billion) in 1998-2000 before jumping to $36 billion in 
2001. The composite of 1.25 times HMDA originations plus life 
insurance commitments, described in the 2000 Rule and updated here 
in column 5, also follows this basic path. Similarly, 
aggregate GSE multifamily purchases and securitizations stayed in 
the same general level in 1998-2000, before jumping in 2001, 
although this trend reflects changes in both market size and GSE 
market share. FHA originations (not shown) also rose substantially 
in 2001, but this too may indicate more than just market size 
trends.
    Column 11 of Table D.4 gives the likely ranges of 
originations for each of the years. These are based on the estimates 
from all sources and interpretations of their strengths and 
weaknesses. In 1999, the $4 billion upward revision to the HUD New 
estimate from the preliminary figure reported in the 2000 Rule, 
together with the higher estimate produced by the FoF-based method, 
justify an upward revision to the $45-$48 range estimated in the 
2000 Rule. The revised range is set at $50-54 billion. In 2000, HUD 
New (revised and extended version) suggests that originations were 
somewhat lower than in 1999, but FoF-based has originations holding 
at $52 billion. Balancing these conflicting indicators, a range of 
$48-$52 billion is selected for 2000. Finally, all indicators point 
to a substantial pickup in 2001, and the range that seems to fit 
best with those indicators is $65-$69 billion.
    In 2002, the various methods of estimation give a mixed picture. 
HUD New indicates a surge in lending activity in 2002, while the 
flow of funds method shows a decrease in lending activity. Other 
methods also show divergent trends. The composite of 1.25 times HMDA 
originations plus life insurance commitments also shows a 
significant increase between 2001 and 2002. On the other hand, 
aggregate GSE multifamily purchases and securitizations showed a 
slight decrease between 2001 and 2002. FHA originations (not shown) 
also decreased slightly in 2002.
    While this is a subjective judgment, 1.5 may not be the 
appropriate multiple to apply to net mortgage debt outstanding in 
the flow of funds model in 2002. The difference between the flow of 
funds estimate and the HUD estimate cannot be reconciled without 
adjusting the FOF multiple. Given the low interest rates in 2002, 
and a refinancing boom in the single-family mortgage market, it 
could be that the multifamily market also had a significant amount 
of refinancing activity. In such a case, there could be an increase 
in the size of the multifamily market without a corresponding 
increase in net mortgage debt outstanding. A higher multiple would 
need to be applied to the Flow of Funds model to compensate for the 
increase in multifamily refinancings.
    Due to data limitations, the above remains a speculation. The 
largest increase in multifamily volume came from HMDA reporting 
lenders. The HMDA data do not allow for the separation of 
multifamily purchase originations from refinancings. Other data 
sources need to be explored to determine if an adjustment to the 
FoF-based model is appropriate.

5. Loan Amount per Unit

    In determining the size of the conventional multifamily mortgage 
market for purposes of the GSE rules, the measure of market size is 
the annual number of conventionally financed multifamily rental 
housing units. The number of units is derived by dividing the 
aggregate annual originations by an estimate of the average loan 
amount per housing unit financed. For this reason, accuracy in the 
estimate of loan amount per unit is as important as accuracy in the 
dollar estimate of aggregate conventional originations. A 10 percent 
error in either will result in a 10 percent error in the estimate of 
market size.
    The 2000 Rule used estimates of loan amount per unit drawn from 
various sources. As summarized in Table D.9 of the 2000 Rule and the 
accompanying text, the estimates for 1993-1998 were taken from the 
GSEs and for 1999 from CMBS data. ``Unpaid Principal Balance'' or 
UPB--a balance sheet measure which for current year loan 
originations will differ little from the initial loan amount--is 
used to calculate aggregate originations of loans bought or 
securitized by the GSEs or pooled into non-GSE mortgage-backed 
securities. The figures from Table D.9 of the 2000 Rule are 
reproduced below in Table D.5, along with updated estimates from all 
three sources for 2000, 2001 and 2002. The estimates that are new 
since the 2000 Rule appear in italics.
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[[Page 24456]]

    Several options are available for developing estimates for 2000, 
2001 and 2002. The first is to use the UPB (unpaid principal 
balance) per unit estimates from the GSEs. These estimates, taken 
from the Fannie Mae and Freddie Mac annual activity reports to HUD, 
are as follows, computed as in the 2000 Rule as a unit-weighted 
average of the unpaid principal balance (UPB) per multifamily unit 
in Fannie Mae's and Freddie Mac's portfolios:

1997..........................................................   $27,266
1998..........................................................    31,041
1999..........................................................    35,038
2000..........................................................    37,208
2001..........................................................    37,258
2002..........................................................    39,787
 

The figure for 2002 is approximately 46 percent higher than in 1997. 
Both Fannie Mae and Freddie Mac's portfolios generate estimates of 
between $39,000 and $40,000 for 2002.
    Several alternative approaches to estimating loan amount per 
unit are available. The first is to base the estimate on CMBS data, 
as was done for 1999 in the 2000 Rulemaking. As shown in the last 
column of Table D.5, the estimates of UPB/unit from this source are 
somewhat below those of the GSEs and indicate less increase since 
the late1990s.
    In the first 10 months of 2002, CMBS properties showed a UPB/
unit of $37,038, a nearly 14 percent jump over the previous year. 
Although slightly below the UPB/unit for the GSEs, the CMBS numbers 
are closer to the GSE calculations than in previous years.
    Another approach is to move the 1999 estimate of UPB/unit 
forward by some justifiable index. The 2001 estimates use the change 
in average rent on multifamily rental units from the American 
Housing Survey. Because AHS data are not available for 2002, the 
2002 estimate uses the consumer price index for rent of primary 
residence. Both AHS and CPI rent estimates are listed below:

------------------------------------------------------------------------
                     Year                       Median    Mean     CPI
------------------------------------------------------------------------
1999.........................................     $550     $592    177.5
2001.........................................      590      647    192.1
2002.........................................      N/A      N/A    199.7
------------------------------------------------------------------------

    There is some variation between the two measures. In the AHS, 
median rent rose 7.3 percent over this two-year period, and mean 
rent increased 9.3 percent. Meanwhile, the CPI showed an increase of 
8.2 percent. In 2001, using the AHS produces an estimate of $34,000. 
The CPI yields a smaller estimate for 2001; applying the 8.2 percent 
increase from the CPI results in a 2001 estimate of $33,200. Since 
the AHS data are unavailable in 2002, the CPI provides a 2002 
estimate of approximately $35,000.
    In 2001, the rent-adjusted 1999 estimate was in between the 
estimates from the CMBS and GSE data, and was a fair estimate of the 
actual size of the market. In 2002, however, the rent-adjusted 
number is below both the CMBS and GSE calculations. The rent-
adjusted number could be underestimating the 2002 UPB/unit. Either 
the CMBS or GSE calculations, or an average of the various methods 
could be used. Section F will report the results of several 
sensitivity analyses showing the effects of the different 
multifamily mortgage estimates (HUD New versus Flow-of-Funds) and 
different per unit amounts ($35,000 or $37,275 which is an average 
of the various estimates) on the goals-qualifying shares for the 
year 2002. Under the various estimates, the multifamily mix (defined 
below) for 2002 ends up around 11 percent.

6. Multifamily Mix During the 1990s

    The section uses the information on dollar volume of multifamily 
originations (Table D.4) and average loan amounts (Table D.5) to 
estimate the number of multifamily units financed each year as a 
percentage share of the total (both single-family and multifamily) 
number of dwelling units financed each year; the years covered 
include 1991 to 2001. This percentage share, called the 
``multifamily mix'', is reported in the last two columns of Table 
D.4.\13\ The ``minimum'' (``maximum'') multifamily mix figure 
reflects the low (upper) end of the ``likely range'' of multifamily 
dollar originations, also reported in Table D.4. Because of the high 
goals-qualifying shares of multifamily housing, the multifamily mix 
is an important parameter in HUD's projection model for the overall 
market; other things equal, a higher multifamily mix (or conversely, 
a lower share of single-family loans) leads to a higher estimate of 
goals-qualifying loans in the overall mortgage market.
---------------------------------------------------------------------------

    \13\ 1990 is excluded from this calculation because of the 
unusually high multifamily mix that year. Also, the estimated 
multifamily mix from the HUD New Method is also provided for 2002 
since it was greater than the estimate from the Flow of Funds 
method.
---------------------------------------------------------------------------

    Based on the ``likely range'' of annual conventional multifamily 
origination volume, multifamily units have represented 15.1 percent 
(the average of the ``minimum'' figures) to 16.3 percent (the 
average of the ``maximum'' figures) of units financed each year 
between 1991 and 2002. Considering the mid-points of the ``likely 
range'', the multifamily mix averaged 15.7 percent during this 
period. Notice that multifamily mix is lower during years of heavy 
refinancing when single-family originations dominate the mortgage 
market; the multifamily mix was only 13-14 percent during 1993, 
1998, and 2001, and approximately 11 percent during 2002.\14\ As 
discussed in Sections F-H, the record single-family originations 
($3.3 trillion) during 2003 likely resulted in a lower multifamily 
mix than any of the years between 1991 and 2002. Sensitivity 
analyses are conducted to show the effects of multifamily mixes less 
than the previous lows of 11 percent in 1992 and 2002.
---------------------------------------------------------------------------

    \14\ The projection model for 2002 showed the following 
multifamily mixes for 2002: 11.5 percent for the HUD New multifamily 
estimate ($67.7 billion) if the average loan amount is $35,000 and 
10.9 percent if the average loan amount is $37,275; 11.0 percent for 
the top end ($64 billion) of the Flow of Funds multifamily range 
($60-64 billion) if the average loan amount is $35,000 and 10.4 
percent if the average loan amount is $37,275; 10.7 percent for the 
mid-point ($62 billion) of the Flow of Funds multifamily range if 
the average loan amount is $35,000 and 10.1 percent if the average 
loan amount is $37,275; and 10.4 percent for the low end ($60 
billion) of the Flow of Funds multifamily range if the average loan 
amount is $35,000 and 9.8 percent if the average loan amount is 
$37,275.
---------------------------------------------------------------------------

    The multifamily share of the conforming conventional market (or 
``multifamily mix'') is utilized below as part of HUD's analysis of 
the share of units financed each year meeting each of the housing 
goals. Following the 2000 Rule, the analysis will focus on 
multifamily mixes of 15 percent and 16.5 percent, which seems 
reasonable given the 1991-2002 estimates reported in Table D.4. 
While at the low end of the 1992-2002 averages for the ``likely 
range'', a 15 percent mix more readily accommodates any uncertainty 
about the data and the estimation process. An alternative 
multifamily mix assumption of 13.5 percent is also considered, as 
well as even lower ones in order to fully consider the effects of 
heavy refinancing environments such as 2001-03.

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 Residential Finance Survey (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. (An updated 
version of the RFS based on the 2000 Census will not be available 
until the spring of 2004). HMDA divides newly-originated single-
family mortgages into two property types: \15\
---------------------------------------------------------------------------

    \15\ The data in Table D.6a ignore HMDA loans with ``non-
applicable'' for owner type.

    (1) Owner-occupied originations, which include both SF-O and SF 
2-4.
    (2) Non-owner-occupied mortgage originations, which include SF 
Investor.

The percentage distributions of mortgages from these data sources 
are provided in Table D.6a. (Table D.6b 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 2000 (2001) HMDA data, investors 
account for 9.4 (9.9 percent) percent of home purchase loans and 7.6 
percent (5.9 percent) of refinance loans.\16\

[[Page 24457]]

Assuming a 35 percent refinance rate per HUD's projection model, the 
2000 (2001) HMDA data are consistent with an investor share of 8.8 
(8.5) percent.\17\ The RFS estimate of 17.3 percent is approximately 
twice the HMDA estimates. In their past comments, the GSEs have 
argued that the HMDA-reported SF investor share should be used by 
HUD. In its 1995 and 2000 rules, HUD's baseline model assumed a 10 
percent share for the SF investor group--only slightly higher than 
the HMDA-based estimates; alternative models assuming 8 percent and 
12 percent were also considered. 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. The 
release this spring of the updated RFS should clarify this issue.
---------------------------------------------------------------------------

    \16\ Due to the higher share of refinance mortgages during 2001, 
the overall single-family-owner percentage reported by HMDA for 2001 
(92.7 percent) is larger than that reported for 2000 (91.3 percent).
    \17\ HMDA data for 2002 would yield a slightly higher investor 
share; the derived investor share assuming a 35 percent refinance 
rate would be 9.6 percent if 2002 HMDA data were used.
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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.\18\ Blackley and Follain provide 
reasons why HMDA should be adjusted upward as well as reasons why 
the RFS should be adjusted downward. They find that HMDA may 
understate the investor share of single-family mortgages because of 
``hidden investors'' who falsely claim that a property is owner-
occupied in order to more easily obtain mortgage financing. RFS may 
overstate the investor share of the market because units that are 
temporarily rented while the owner seeks another buyer may be 
counted as rental units in the RFS, even though rental status of 
such units may only be temporary. The RFS's investor share should be 
adjusted downward in part because the RFS assigns all vacant 
properties to the rental group, but some of these are likely 
intended for the owner market, especially among one-unit properties. 
Blackley and Follain's analysis of this issue suggests lowering the 
investor share from 17.3 percent to about 14-15 percent.
---------------------------------------------------------------------------

    \18\ Dixie M. Blackley and James R. Follain, ``A Critique of the 
Methodology Used to Determine Affordable Housing Goals for the 
Government Sponsored Housing Enterprises,'' report prepared for 
Office of Policy Development and Research, Department of Housing and 
Urban Development, October 1995; and ``HUD's Market Share 
Methodology and its Housing Goals for the Government Sponsored 
Enterprises,'' unpublished paper, March 1996.
---------------------------------------------------------------------------

    Finally, Blackley and Follain note that a conservative estimate 
of the SF investor share is advisable because of the difficulty of 
measuring the magnitudes of the various effects that they analyzed. 
In their 1996 paper, they conclude that 12 percent is a reasonable 
estimate of the investor share of single-family mortgage 
originations.\19\ Blackley and Follain caution that uncertainty 
exists around this estimate because of inadequate data.
---------------------------------------------------------------------------

    \19\ Blackley and Follain (1996), p. 20.
---------------------------------------------------------------------------

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.6a 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.\20\
---------------------------------------------------------------------------

    \20\ The unit-per-mortgage data from the 1991 RFS match closely 
the GSE purchase data for 2001. 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.
---------------------------------------------------------------------------

    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.6a). The 
results are presented in Table D.6b. 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.
    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 and 2000 Rules 
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 HUD's estimate. Rental units account for 15.1 percent 
of all newly financed single-family units under HUD's baseline 
model, compared with 13.7 (13.1) percent under a model based on 2000 
(2001) 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:
     While there is uncertainty concerning the 
relative size of this market, the projections made by HUD in 1995 
and 2000 appear reasonable and, therefore, will serve as the 
baseline assumption in the HUD's market share model for this year's 
Proposed Rule.
     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 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.\21\ 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.
---------------------------------------------------------------------------

    \21\ The property distribution reported in Table D.1 is an 
example of the output of the market share model. Thus, this section 
completes Step 1 of the three-step procedure outlined above in 
Section B.
---------------------------------------------------------------------------

1. Basic Equations for Determining Units Financed in the Mortgage 
Market

    The model first estimates the number of dwelling units financed 
by conventional conforming mortgage originations for each of the 
four property types. It then determines each property type's share 
of the total number of dwelling units financed.

a. Single-Family Units

    This section estimates the number of single-family units that 
will be financed in the conventional conforming market, where 
single-family units (SF-UNITS) are defined as:

SF-UNITS = SF-O + SF 2-4 + SF-INVESTOR

    First, the dollar volume of conventional conforming single-
family mortgages (CCSFM$) is derived as follows:

(1) CCSFM$ = CONV% * CONF% * SFORIG$

Where:

CONV% = conventional mortgage originations as a percent of total 
mortgage originations; estimated to be 88%.\22\
---------------------------------------------------------------------------

    \22\ According to estimates by the Mortgage Bankers Association 
of America (MBAA), the conventional share of the 1-4 family market 
was between 86 and 88 percent of the market from 1993 to 1999, with 
a one-time low of 81 percent in 1994. Calculated from ``1-4 Family 
Mortgage Originations'' tables (Table 1--Industry and Table 2--
Conventional Loans) from ``MBAA Mortgage and Market Data,'' at 
www.MBAAa.org/marketkdata/ as of July 13, 2000. More recent 
unpublished estimates by MBAA are slightly higher.
---------------------------------------------------------------------------

CONF% = conforming mortgage originations (measured in dollars) as a 
percent of conventional single-family originations; forecasted to be 
80% by industry.
SFORIG$ = dollar volume of single-family one-to-four unit mortgages; 
$1,700 billion is used here as a starting assumption to reflect 
market conditions during the years 2005-2008.\23\ While

[[Page 24460]]

alternative assumptions will be examined, it must be emphasized that 
the important concept for deriving the goal-qualifying market shares 
is the relative importance of single-family versus multifamily 
mortgage originations (the ``multifamily mix'' discussed in Section 
C) rather than the total dollar volume of single-family originations 
considered in isolation.
---------------------------------------------------------------------------

    \23\ Single-family mortgage originations of $1,700 billion are 
similar to Freddie Mac's projection of $1,748 billion for 2005 and 
Fannie Mae's projection of $1,675 billion for 2005. As discussed 
later, single-family originations could differ from $1,700 billion 
during the 2005-2008 period that the goals will be in effect. As 
recent experience shows, market projections often change. For 
example, the MBAA projected $1,246 billion for 2003, while their 
projection for 2003 rose to $1,774 billion in January 2003; of 
course, actual 2003 mortgage originations were almost double the 
latter amount. (See http://www.MBAAa.org/marketdata/forecasts for 
January 2003 Mortgage Finance Forecasts.) In its January 22, 2004 
forecast, the MBAA projected mortgage originations of $1.9 trillion 
in 2004 and approximately $1.7 trillion in 2005 and 2006. Section F 
will report the effects on the market estimates of alternative 
estimates of single-family mortgage originations.

Substituting these values into (1) yields an estimate for the 
conventional conforming market (CCSFM$) of $1,197 billion.
    Second, the number of conventional conforming single-family 
mortgages (CCSFM) is derived as follows:

(2) CCSFM = (CCSFM$ * (1-REFI)/PSFLOAN$) + (CCSFM$ * REFI)/
RSFLOAN$)

Where:

REFI = the refinance rate, assumed to be 35 percent for the 
baseline.\24\
---------------------------------------------------------------------------

    \24\ The model requires an estimated refinance rate because 
purchase and refinance loans can have different shares of goals-
qualifying units. In 2003, the refinance rate was over 60 percent. 
In its January 22, 2004 forecast, the MBAA projects 34 percent for 
2004 and 22 percent for 2005. Freddie Mac projects a 36 percent 
refinance rate for 2004 and a 29 percent rate for 2005, and Fannie 
Mae projects a 48 percent refinance rate for 2004 and 24 percent for 
2005. The baseline model uses a higher refinance rate of 35 percent 
because conforming conventional loans tend to refinance at a higher 
rate than the overall market. Sensitivity analyses for alternative 
refinance rates are presented in Sections F-H.
---------------------------------------------------------------------------

PSFLOAN$ = the average conventional conforming purchase mortgage 
amount for single-family properties; estimated to be $146,000.\25\
---------------------------------------------------------------------------

    \25\ The average 2002 purchase loan amount is estimated at 
$135,060 for owner occupied units using 2002 HMDA average loan 
amounts for single-family home purchase loans in metropolitan areas. 
A small adjustment is made to this figure to account for a small 
number of two-to-four and investor properties (see Section D above). 
This produces an average purchase loan size of $133,458 for 2002 
which is then inflated 3 percent a year for three years and then 
rounded to arrive at an estimated $146,000 average loan size for 
home purchase loans in 2005.
---------------------------------------------------------------------------

RSFLOAN$ = the average conventional conforming refinance mortgage 
amount for single-family properties; estimated to be $131,000.\26\
---------------------------------------------------------------------------

    \26\ The average refinance loan amount is estimated by averaging 
the relationship between HMDA average purchase and refinance loan 
amounts for 1999 and 2000, which were non-refinance environments. 
Applying this average of 90 percent (refinance loan amount/purchase 
loan amount) to the $146,000 average loan amount for purchase loans 
gives a rounded estimate of $131,000 for average refinance loan 
amounts. When refinance environments are used, $146,000 average loan 
amounts are used for both purchase and refinance loans. This 
relationship is consistent with the observed relationship in past 
refinance years such as 1998, 2001, and 2002.

Substituting these values into (2) yields an estimate of 8.5 million 
mortgages.
    Third, the total number of single-family mortgages is divided 
among the three single-family property types. Using the 88/2/10 
percentage distribution for single-family mortgages (see Section D), 
the following results are obtained:

(3a) SF-OM = 0.88 * CCSFM = number of owner-
occupied, one-unit mortgages = 7.5 million.
(3b) SF-2-4M = 0.02 * CCSFM = number of owner-
occupied, two-to-four unit mortgages = 0.17 million.
(3c) SF-INVM = 0.10 * CCSFM = number of one-to-
four unit investor mortgages = 0.85 million.

    Fourth, the number of dwelling units financed for the three 
single-family property types is derived as follows:

(4a) SF-O = SF-OM + SF-2-4M = number of owner-
occupied dwelling units financed = 7.7 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 = 0.2 
million.\27\
---------------------------------------------------------------------------

    \27\ 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).
---------------------------------------------------------------------------

(4c) SF-INVESTOR = 1.35 * SF-INVM = number of single-family 
investor dwelling units financed = 1.1 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 = 9.0 million

b. Multifamily Units

    The number of multifamily dwelling units (MF-UNITS) financed by 
conventional conforming multifamily originations is calculated by 
the following series of equations:

(5a) TOTAL = SF-UNITS + MF-UNITS
(5b) MF-UNITS = MF-MIX * TOTAL = MF-MIX * (SF-UNITS + MF-UNITS) = 
[MF-MIX/(1--MF-MIX)] * SF-UNITS
Where:

MF-MIX = the ``multifamily mix'', or the percentage of all newly-
mortgaged dwelling units that are multifamily; as discussed in 
Section C, alternative estimates of the multifamily market will be 
included in the analysis. As explained in Section C above, the 
baseline model assumes a multifamily mix of 15 percent; results are 
also presented in the basic market tables of Sections F-H for a 
higher (16.5 percent) and a lower (13.5 percent) multifamily mix. In 
addition, further sensitivity analyses are reported in those 
sections for even lower multifamily mixes that could occur during 
periods of heavy single-family refinancing activity.

    Assuming a multifamily mix of 15 percent and solving (5b) yields 
the following:

(5c) MF-UNITS = [0.15/0.85] * SF-UNITS = 0.176 * SF-UNITS = 1.6 
million.

c. Total Units Financed

    The total number of dwelling units financed by the conventional 
conforming mortgage market (TOTAL) can be expressed in three useful 
ways:

(6a) TOTAL = SF-UNITS + MF-UNITS = 10.6 million (or more precisely, 
10,632,145 units)
(6b) TOTAL = SF-O + SF 2-4 + SF-INVESTOR + MF-UNITS
(6c) TOTAL = SF-O + SF-RENTAL + MF-UNITS
Where:
SF-RENTAL equals SF-2-4 plus SF-INVESTOR

2. Dwelling Unit Distributions by Property Type

    The next step is to express the number of dwelling units 
financed for each property type as a percentage of the total number 
of units financed by conventional conforming mortgage 
originations.\28\
---------------------------------------------------------------------------

    \28\ The share of the mortgage market accounted for by owner 
occupants is (SF-O)/TOTAL; the share of the market accounted for by 
all single-family rental units is SF-RENTAL/TOTAL; and so on.
---------------------------------------------------------------------------

    The projections used above in equations (1)-(6) produce the 
following distributions of financed units by property type:

------------------------------------------------------------------------
                                                                 % Share
------------------------------------------------------------------------
SF-O..........................................................      72.2
SF 2-4........................................................       2.0
SF INVESTOR...................................................      10.8
MF-UNITS......................................................      15.0
                                                               ---------
    Total.....................................................     100.0
 
        or
 
SF-O..........................................................      72.2
SF-RENTER.....................................................      12.8
MF-UNITS......................................................      15.0
                                                               ---------
    Total.....................................................     100.0
------------------------------------------------------------------------

    Sections C and D discussed alternative projections for the mix 
of multifamily originations and the investor share of single-family 
mortgages. Following the 2000 Rule, 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 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. 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.
    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

[[Page 24461]]

``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 F-H will also consider market assumptions other 
than the baseline assumptions.
    Table D.7 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 
projection (15 percent mix and 10 percent investor) is 72.2 percent.
BILLING CODE 4210-27-P

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[[Page 24463]]

    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.7. 
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 multifamily rental units. 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. As noted earlier, the 
RFS based on the year 2000 Census should clarify issues related to 
the rental segment of the mortgage market when it becomes available 
in the spring of this year (2004).

F. Size of the Conventional Conforming Mortgage Market Serving Low- and 
Moderate-Income Families

    This section estimates the size of the low- and moderate-income 
market by applying low- and moderate-income percentages to the 
property shares given in Table D.7. This section essentially 
accomplishes Steps 2 and 3 of the three-step procedure discussed in 
Section B.2.
    Technical issues and data adjustments related to the low- and 
moderate-income percentages for owners and renters are discussed in 
the first two subsections. Then, estimates of the size of the low- 
and moderate-income market are presented along with several 
sensitivity analyses. Based on these analyses, HUD concludes that 
51-57 percent is a reasonable estimate of the mortgage market's low- 
and moderate-income share for the four years (2005-2008) when the 
new goals will be in effect.

1. Low- and Moderate-Income Percentage for Single-Family-Owner 
Mortgages

a. HMDA Data

    The most important determinant of the low- and moderate-income 
share of the mortgage market is the income distribution of single-
family borrowers. HMDA reports annual income data for families who 
live in metropolitan areas and purchase a home or refinance their 
existing mortgage.\29\ The data cover conventional mortgages below 
the conforming loan limit, which was $300,700 in 2002. Table D.8 
gives the percentage of mortgages originated for low- and moderate-
income families for the years 1992-2002. Data are presented for home 
purchase, refinance, and all single-family-owner loans. The 
discussion below will often focus on home purchase loans because 
they typically account for the majority of all single-family-owner 
mortgages.\30\ For each year, a low- and moderate-income percentage 
is also reported for the conforming market without B&C loans.
---------------------------------------------------------------------------

    \29\ 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.
    \30\ Sensitivity analyses will focus on how the results change 
during a heavy refinancing environment.
---------------------------------------------------------------------------

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[[Page 24465]]

    Table D.8 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 growth in the market's funding of low- and moderate-income 
families during the 1990s (and particularly the growth since 1998 
which was the last year analyzed in HUD's 2000 GSE Rule); and the 
other related to changes in the borrower income distributions for 
refinance and home purchase mortgages. Throughout this appendix, 
``low- and moderate-income'' will often be referred to as ``low-
mod''.
    Recent Trends in the Market Share for Lower Income Borrowers. 
First, focus on the percentages in Table D.8 for the total (both 
home purchase and refinance) conforming market. After averaging 
about 30 percent during 1992-93, the percentage of borrowers with 
less than area median income jumped to 41.0 percent in 1994, and 
remained above 40 percent through 2002. Over the eight year period, 
1994 to 2001, the low-mod share of the total market averaged 43.2 
percent (or 42.4 percent if B&C loans are excluded from the market 
totals).\31\ The share of the market accounted for by very-low-
income borrowers followed a similar trend, increasing from 6-7 
percent in 1992-93 to about 12 percent in 1994 and averaging 13.3 
percent during the 1994-to-2002 period (or 12.8 percent if B&C loans 
are excluded).
---------------------------------------------------------------------------

    \31\ The annual averages of the goals-qualifying mortgages 
reported in this appendix are unweighted averages; for analyses 
using weighted average see Appendix A.
---------------------------------------------------------------------------

    Next, consider the percentages for home purchase loans. The 
share of the home loan market accounted for by less-than-median-
income borrowers increased from 34.4 percent in 1992 to 45.3 percent 
in 2002. Within the 1994-to-2002 period, the low-mod share of the 
home purchase market averaged 44.6 percent between 1999 and 2002, 
compared with 42.2 percent between 1994 and 1998. Similarly, the 
very-low-income share of the home purchase market was also higher 
during the 1999-to-2002 period than during the 1994-to-1998 period 
(14.4 percent versus 12.6 percent). Note that within the more recent 
period, the low-mod share for home purchase loans was particularly 
high during 1999 (45.2 percent) and 2000 (44.8 percent) before 
falling slightly in 2001 (43.2 percent), only to rebound again in 
2002 (45.3 percent). As shown in Table D.8, the low-mod shares do 
not change much when B&C home loans are excluded from the market 
definition; this is because B&C loans are mainly refinance loans.
    It appears that the affordable lending market is even stronger 
today than when HUD wrote the 2000 Rule, which covered market data 
through 1998. The very-low-income and low-mod percentages were 
higher during 1999 to 2002 than they were during the earlier period. 
In addition, when HUD wrote the 2000 Rule, there had been five years 
(1994-98) of solid affordable lending for lower-income borrowers. 
Now, with four additional years of data for 1999-2002, there have 
been nine years of strong affordable lending.
    Of course, it is recognized that lending patterns could change 
with sharp changes in interest rates and the economy. However, the 
fact that lending to low-income families has remained at a high 
level for nine years demonstrates that the market has changed in 
fundamental ways from the mortgage market of the early 1990s. The 
numerous innovative products and outreach programs that the industry 
has developed to attract lower-income families into the 
homeownership and mortgage markets appear to be working and there is 
no reason to believe that they will not continue to assist in 
closing troubling homeownership gaps that exist today. As explained 
in Appendix A, the demand for homeownership on the part of 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. There is also evidence that the 
affordable lending market increased slightly since 1998, although it 
is recognized that this could be due to the recent period of 
historically low interest rates.
    Refinance Mortgages. In the 2000 Rule, HUD's market projection 
model assumed that low-mod borrowers represented a smaller share of 
refinance mortgages than they do of home purchase mortgages. 
However, as shown in Table D.8, the income characteristics of 
borrowers refinancing mortgages seem to depend on the overall level 
of refinancing in the market. During the refinancing wave of 1992 
and 1993, refinancing borrowers had much higher incomes than 
borrowers purchasing homes. For example, during 1993 low- and 
moderate-income borrowers accounted for 29.3 percent of refinance 
mortgages, compared to 38.9 percent of home purchase borrowers. 
While this same pattern was exhibited during the two recent 
refinancing periods (1998 and 2001-2002), the differentials were 
much smaller--during 2001-2002 (1998), low-mod borrowers accounted 
for 42.1 (39.7) percent of refinance loans, compared with 44.3 
(43.0) percent of home purchase loans. However, the refinance effect 
was still evident, as can be seen by the almost seven percentage 
drop in the low-mod percentage for refinance loans between 2000 (a 
low refinance year) and 2001 (a high refinance year).
    On the other hand, for recent years characterized by a low level 
of refinancing, the low-mod share of refinance mortgages has been 
about the same or even greater than that of home purchase mortgages. 
As shown in Table D.8, there was little difference in the very-low-
income and low-mod shares of refinance and home purchase loans 
during 1995 and 1996. In 1997, 1999, and 2000, the two lower-income 
shares (i.e., very-low-income and low-mod shares) of refinance 
mortgages were significantly higher than the lower-income shares of 
home purchase loans. To a certain extent, this pattern was 
influenced by the growth of subprime loans, which are mainly 
refinance loans. If B&C loans are excluded from the market 
definition, the home purchase and refinance percentages are 
approximately the same in 1997 and 1999, as well as in 1995 and 
1996. (See Table D.8.) Even after excluding all subprime loans from 
the market definition in 1997 and 1999, the very-low-income and low-
mod shares for refinance loans are only slightly less (about one 
percentage point) than those for home purchase loans.
    The year 2000 stands out because of the extremely high lower-
income shares for refinance loans. In that year, the low-mod (very-
low-income) share of refinance loans was 6.8 (4.3) percentage points 
higher than the low-mod (very-low-income) share of home purchase 
loans; this differential is reduced to 5.2 (3.2) percent if B&C 
loans are excluded from the market definition (see Table D.8). The 
differential for 2000 is reduced further to 2.8 (1.5) percent if all 
subprime loans (both A-minus and B&C) are excluded from the market 
definition (not reported). While the projection model (explained 
below) for years 2005-08 will input low-mod percentages for the 
entire conforming market, the model will exclude the effects of B&C 
loans. Sensitivity analyses will also be conducted showing the 
effects on the overall market estimates of excluding all subprime 
loans as well as other loan categories such as manufactured housing 
loans.
    The projection model will initially assume that refinancing is 
35 percent of the single-family mortgage market; this will be 
followed by projection models that reflect heavy refinance 
environments. Given the volatility of refinance rates from year to 
year, it is important to conduct sensitivity tests using different 
refinance rates.

b. Manufactured Housing Loans

    Because manufactured housing loans are such an important source 
of affordable housing, they are included in the mortgage market 
definition in this appendix--or at least that portion of the 
manufactured housing market located in metropolitan areas is 
included, as HMDA doesn't adequately cover non-metropolitan areas. 
The GSEs have questioned HUD's including these loans in its market 
estimates; therefore, following the same procedure used in the 2000 
Rule, this Appendix will report the effects of excluding 
manufactured home loans from the market estimates. As explained 
later, the effect of manufactured housing on HUD's metropolitan area 
market estimate for each of the three housing goals is approximately 
one percentage point or less.
    As discussed in Appendix A, the manufactured housing market 
increased rapidly during the 1990s, as units placed in service 
increased from 174,000 in 1991 to 374,000 in 1999. However, due to 
various problems in the industry such as lax underwriting and 
repossessions, volume has declined in recent years, falling to 
192,000 in 2001 and to 172,000 in 2002. Still, the affordability of 
manufactured homes for lower-income families is demonstrated by 
their average price of $48,800 in 2001, a fraction of the median 
price for new ($175,000) and existing ($147,800) homes.

[[Page 24466]]

Many households live in manufactured housing because they simply 
cannot afford site-built homes, for which the construction costs per 
square foot are much higher.
    Although manufactured home loans cannot be identified in the 
HMDA data, Randy Scheessele at HUD identified 21 lenders that 
primarily originated manufactured home loans during 2001 and likely 
account for most of these loans in the HMDA data for metropolitan 
areas.\32\ HMDA data on home loans originated by these lenders 
indicate that:\33\
---------------------------------------------------------------------------

    \32\ See Randall M. Scheesele, 1998 HMDA Highlights, op. cit. 
and ``HUD Subprime and Manufactured Home Lender List'' at http://huduseer.org/datasets/manu.html.
    \33\ Since most HMDA data are for loans in metropolitan areas 
and a substantial share of manufactured homes are located outside 
metropolitan areas, HMDA data may not accurately state the goals-
qualifying shares for loans on manufactured homes in all areas.
---------------------------------------------------------------------------

     A very high percentage of these loans--75 
percent in 2001--would qualify for the Low- and Moderate-Income 
Goal,
     A substantial percentage of these loans--42 
percent in 2001--would qualify for the Special Affordable Goal, and
     Almost half of these loans--47 percent in 
2001--would qualify for the Underserved Areas Goal.\34\
---------------------------------------------------------------------------

    \34\ While many fewer manufactured homes loans were identified 
in the 2002 HMDA data, the loans showed similar goals-qualifying 
shares: low-mod (78.3 percent), special affordable (45.6 percent), 
and underserved areas (47.5 percent).
---------------------------------------------------------------------------

Thus an enhanced presence in this market by the GSEs would benefit 
many lower-income families. It would also contribute to their 
presence in underserved rural areas, especially in the South.

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

    Following the 2000 Rule, measures of the rent affordability of 
the single-family rental and the multifamily rental markets are 
obtained from the American Housing Survey (AHS) and the Property 
Owners and Managers Survey (POMS). As explained below, the AHS 
provides rent information for the stock of rental properties while 
the POMS provides rent information for flow of mortgages financing 
that stock. As discussed below, the AHS and POMS data provide very 
similar estimates of the low- and moderate-income share of the 
rental market.

a. American Housing Survey Data

    The American Housing Survey does not include data on mortgages 
for rental properties; rather, it includes data on the 
characteristics of the existing rental housing stock and recently 
completed rental properties. Current data on the income of 
prospective or actual tenants has also not been readily available 
for rental properties. Where such income information is not 
available, the 1992 GSE Act provides that the rent of a unit can be 
used to determine the affordability of that unit and whether it 
qualifies for the Low- and Moderate-Income Goal. A unit qualifies 
for the Low- and Moderate-Income Goal if the rent does not exceed 30 
percent of the local area median income (with appropriate 
adjustments for family size as measured by the number of bedrooms). 
Thus, the GSEs' performance under the housing goals is measured in 
terms of the affordability of the rental dwelling units that are 
financed by mortgages that the GSEs purchase; the income of the 
occupants of these rental units is not considered in the calculation 
of goal performance. For this reason, it is appropriate to base 
estimates of market size on rent affordability data rather than on 
renter income data.
    A rental unit is considered to be ``affordable'' to low- and 
moderate-income families, and thus qualifies for the Low- and 
Moderate-Income Goal, if that unit's rent is equal to or less than 
30 percent of area median income. Table D.14 of Appendix D in HUD's 
2000 Rule reported AHS data on the affordability of the rental 
housing stock for the survey years between 1985 and 1997. The 1997 
AHS showed that for 1-4 unit unsubsidized single-family rental 
properties, 94 percent of all units and of units constructed in the 
preceding three years had gross rent (contract rent plus the cost of 
all utilities) less than or equal to 30 percent of area median 
income. For multifamily unsubsidized rental properties, the 
corresponding figure was 92 percent. The AHS data for the other 
survey years were similar to the 1997 data.

b. Property Owners and Managers Survey (POMS)

    As discussed in the 2000 GSE Rule, there were concerns about 
using AHS data on rents from the outstanding rental stock to proxy 
rents for newly mortgaged rental units. HUD investigated that issue 
further using the POMS.
    POMS Methodology. The affordability of multifamily and single-
family rental housing backing mortgages originated in 1993-1995 was 
calculated using internal Census Bureau files from the American 
Housing Survey-National Sample (AHS) from 1995 and the Property 
Owners and Managers Survey from 1995-1996. The POMS survey was 
conducted on the same units included in the AHS survey, and provides 
supplemental information such as the origination year of the 
mortgage loan, if any, recorded against the property included in the 
AHS survey. Monthly housing cost data (including rent and 
utilities), number of bedrooms, and metropolitan area (MSA) location 
data were obtained from the AHS file.
    In cases where units in the AHS were not occupied, the AHS 
typically provides rents, either by obtaining this information from 
property owners or through the use of imputation techniques. 
Estimated monthly housing costs on vacant units were therefore 
calculated as the sum of AHS rent and utility costs estimated using 
utility allowances published by HUD as part of its regulation of the 
GSEs. Observations where neither monthly housing cost nor monthly 
rent was available were omitted, as were observations where MSA 
could not be determined. Units with no cash rent and subsidized 
housing units were also omitted. Because of the shortage of 
observations with 1995 originations, POMS data on year of mortgage 
origination were utilized to restrict the sample to properties 
mortgaged during 1993-1995. POMS weights were then applied to 
estimate population statistics. Affordability calculations were made 
using 1993-95 area median incomes calculated by HUD.
    POMS Results. The rent affordability estimates from POMS of the 
affordability of newly-mortgaged rental properties are quite 
consistent with the AHS data on the affordability of the rental 
stock (discussed above). Ninety-six (96) percent of single-family 
rental properties with new mortgages between 1993 and 1995 were 
affordable to low- and moderate-income families, 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.\35\
---------------------------------------------------------------------------

    \35\ In 2002, 75 percent of GSE purchases of single-family 
rental units and 89 percent of their purchases of multifamily units 
qualified under the Low- and Moderate-Income Goal, excluding the 
effects of missing data.
---------------------------------------------------------------------------

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 
2000 rule-making process with actual experience between 1999 and 
2001. 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. Actual Market Performance Between 1995 and 2002

    Before reporting market projections for the new goals-setting 
period (2005-08), this section discusses actual market experience 
for 1995 to 2002, as shown in Table D.9.\36\ The 1995 to 1998 market 
estimates in Table D.9 were reported by HUD in its 2000 Rule while 
the 1999-2002 estimates are new. The 1999-2002 estimates allow a 
comparison between HUD's projections and actual market experience. 
This discussion of the 1995-to-2002 market considers all three 
housing goals, since the explanations for the differences between 
the projected and actual market shares are common across the three 
goals. B&C loans are not included in the market estimates reported 
in Table D.9. The discussion of Table D.9 will first focus on the 
market estimates for 1995-1997 and 1999-2000, which, because of 
their relatively low levels of refinancing, will be referred to as 
``home purchase environments''. The discussion will then examine the 
market

[[Page 24467]]

estimates for the heavy refinance years of 1998, 2001, and 2002. 
After that, HUD's methods for adjusting the 1995-2001 market data to 
exclude B&C loans and to incorporate the more expansive definition 
of Underserved Areas in non-metropolitan areas will be explained.
---------------------------------------------------------------------------

    \36\ The goals-qualifying shares reported in Table D.9 for 1995-
2002 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.
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[[Page 24469]]

    HUD's market projections in the 2000 Rule were 50-55 percent for 
the Low- and Moderate-Income Goal, 23-26 percent for the Special 
Affordable Goal, and 29-32 percent for the Underserved Areas Goal. 
Thus, the upper bound figures for the market share ranges in the 
2000 Rule were lower than actual experience during 1999 and 2000, as 
well as for the earlier 1995-97 period--for the low-mod estimate, 55 
percent versus 57-59 percent; for the special affordable estimate, 
26 versus 28-30 percent, and for the underserved areas estimate, 32 
percent versus 33-35 percent.
    There are three main reasons for the differential between HUD's 
earlier estimates (made during 2000 based on HMDA data through 1998) 
and the higher goals-qualifying market shares of recent years. 
First, historically low interest rates and strong economic expansion 
allowed lower-income families to enter the homeownership and 
mortgage market during the mid-to-late 1990s. Affordable home 
purchase lending continued during the past four years, at an even 
higher rate than earlier, particularly for the two borrower-income 
goals (low-mod and special affordable). The average low-mod 
percentage for home purchase loans during 1999-2002 was 44.6 
percent, compared with 42.2 percent during 1995-98. Similarly, the 
average special affordable percentage for home purchase loans during 
1999-2002 was 16.7 percent, compared with 15.1 percent during 1995-
98. Thus, the home lending market for lower-income borrowers 
continued to grow. HUD's earlier estimates anticipated smaller 
shares of new mortgages being originated for lower-income families.
    Second, HUD's projection model in the 2000 Rule assumed that 
refinance loans would have lower goals-qualifying percentages than 
home purchase loans; this assumption was based on the average home-
purchase-refinance differential between 1992 and 1998. As discussed 
above, this has not been the case during ``home purchase'' years 
such as 1995-97 and 1999-2000. Thus, the projection model 
underestimates actual market experience when the goals-qualifying 
shares of refinance loans turn out to be equal or greater than the 
goals-qualifying shares of home purchase loans.\37\ This issue will 
be addressed further in the sections that present the new market 
estimates.
---------------------------------------------------------------------------

    \37\ The 1995-2002 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.
---------------------------------------------------------------------------

    Third, the financing of multifamily properties continued at 
strong levels during 1999 and 2000. HUD's baseline model in the 2000 
Rule assumed a multifamily share of 15 percent, which was lower than 
the approximately 16-17 percent multifamily share during 1999 and 
2000.\38\ As discussed throughout this appendix, the multifamily mix 
fell during the heavy refinance years.
---------------------------------------------------------------------------

    \38\ The accuracy of a single-family portion of HUD's model can 
be tested using HMDA data. The number of single-family-owner loans 
reported to HMDA for the years 1999-2002 can be compared with the 
corresponding number predicted by HUD's model. Single-family-owner 
loans reported to HMDA during 1999 were 87 percent of the number of 
loans predicted by HUD's model; comparable percentages for 2000, 
2001, and 2002 were 84 percent, 89 percent, and 80 percent, 
respectively. Studies of the coverage of HMDA data through 1996 
conclude that HMDA covers approximately 85 percent of the 
conventional conforming market, which suggests that HUD's model 
produces reasonable estimates of single-family-owner loans. For 
analysis of HMDA coverage, see Randall M. Scheesele, HMDA Coverage 
of the Mortgage Market, op. cit.
---------------------------------------------------------------------------

    Refinance Years. The goals-qualifying percentages for the heavy 
refinance years (1998, 2001 and 2002) are lower than those for the 
other years. For example, the low-mod market share was 54 percent in 
1998 and 2002 and 55 percent in 2001--both estimates within HUD's 
earlier market share range of 50-55 percent.\39\ The special 
affordable market share during 1998, 2001, and 2002 was 26 percent--
which places it at the top end of HUD's earlier market range of 23-
26 percent. The goals-qualifying percentages during 1998, 2001, and 
2002 are, of course, lower than those for the ``home purchase'' 
years of 1995-97 and 1999-2000. For example, the special affordable 
market share of approximately 26 percent in 2001 and 2002 was 3-4 
percentage points lower than the corresponding share in 1999 and 
2000. There are three main reasons for this. First, the goals-
qualifying shares for single-family refinance loans fall during 
heavy refinance years, as middle and upper income borrowers dominate 
that market. On the other hand, in low refinancing years, the goals-
qualifying shares of refinance loans can equal or be greater than 
the goals-qualifying shares of home purchase loans. Second, and 
related, is the fact that subprime lending, which is characterized 
by relatively high goals-qualifying shares, accounts for a smaller 
portion of the single-family mortgage market during heavy refinance 
years. Although they were at a record dollar level ($213 billion) 
during 2002, subprime originations accounted for only 8.6 percent of 
all single-family mortgages originated that year, compared with 
about 13 percent during 1999 and 2000. Finally, the high volume of 
single-family mortgages in a heavy refinance year reduces the share 
of multifamily rental units. For example, the multifamily share of 
all financed units was less than 14 percent in 1998, 2001, and 
2002,\40\ compared to multifamily shares of 19 percent during 1995-
97 and 16-17 percent during 1999-2000. Of course, this shift toward 
single-family loans reduces the goals-qualifying shares of the 
overall market.
---------------------------------------------------------------------------

    \39\ As discussed in Section C.6 of this appendix, there is some 
uncertainty about the multifamily mix for the year 2002. The goals-
qualifying shares reported in Table D.9 assume $67.7 billion (the 
HUD New estimate) and an average loan amount of $37,275; this 
produces a multifamily mix of 10.9 percent. Section C.6 discussed 
several other multifamily market and average loan amount estimates 
sfor 2002, each with a specific multifamily mixes. The low-mod, 
special affordable, and underserved areas shares for the other 
multifamily mixes discussed in Section C.6 are as follows: 11.5 
percent (54.4, 26.0, 32.25), 11.3 percent (54.3, 25.9, 32.1), 11.0 
percent (54.2, 25.8, 32.0), 10.7 percent (54.0, 25.7, 31.9), 10.4 
percent (53.9, 25.6, 31.8), and 10.1 percent (53.8, 25.5, 31.8).
    \40\ Although data are not available yet, the multifamily share 
for 2003 will be lower than the approximately 11 percent in 2002. 
Senstivity analyses with lower multifamily mixes are provided below.
---------------------------------------------------------------------------

    B&C Mortgages. As discussed in Appendix A, the market for 
subprime mortgages has experienced rapid growth over the past 5-6 
years, rising from an estimated $65 billion in 1995 to $174 billion 
in 2001 and $213 billion in 2002. Table 9 provides goals-qualifying 
market shares that exclude the B&C portion of the subprime market; 
or conversely, that include the A-minus portion of the subprime 
market. This section explains how these ``adjusted'' market shares 
are calculated from ``unadjusted'' market shares that include B&C 
loans, using the year 1999 as an example.
    Industry sources estimate that the subprime market totaled $160 
billion in 1999, or 12.5 percent of all mortgages ($1,285 billion) 
originated that year.\41\ In terms of credit risk, this $160 billion 
includes a wide range of mortgage types. ``A-minus'' loans, which 
represent at least half of the subprime market, make up the least 
risky category.\42\ As discussed in Appendix A, the GSEs are 
involved in this market both through specific program offerings and 
through purchases of securities backed by subprime loans (including 
B&C loans as well as A-minus loans). The B&C loans experience much 
higher delinquency rates than A-minus loans.\43\
---------------------------------------------------------------------------

    \41\ Estimates of the subprime market for other recent years are 
as follows (dollar and market share): 1995 ($65 billion, 10 
percent); 1996 ($96.5 billion, 12.3 percent); 1997 ($125 billion, 15 
percent); 1998 ($150 billion, 10 percent; 1999 ($160 billion, 12.5 
percent); 2001 ($173 billion, 8.5 percent); 2002 ($213 billion, 8.6 
percent). The uncertainty about what these various estimates include 
should be emphasized; for example, they may include second mortgages 
and home equity loans as well as first mortgages, which are the 
focus of this analysis. The source for these estimates is Inside 
Mortgage Finance (various years).
    \42\ The one-half assumption for A-minus loans is conservative 
because it probably underestimates (overestimates) the share of A-
minus (B&C) loans. According to data obtained by the Mortgage 
Information Corporation (see next footnote), 57 percent of all 
subprime loans were labeled A-minus (as of September 30, 2000). 
According to Inside B&C Lending, which is published by Inside 
Mortgage Finance, the A-minus share of the subprime market was 61.6 
percent in 2000, 70.7 percent in 2001 (see March 11, 2002 issue), 75 
percent in 2002 (see the September 15, 2003 issue), and 82 percent 
during the first nine months of 2003 (see the December 8, 2003 
issue).
    \43\ The Mortgage Information Corporation (MIC) reports the 
following serious delinquency rates (either 90 days past due or in 
foreclosure) by type of subprime loan: 3.36 percent for A-minus; 
6.67 percent for B; 9.22 percent for C; and 21.03 percent for D. The 
D category accounted for only 2 percent of subprime loans and of 
course, is included in the ``B&C'' category referred to in this 
appendix. By comparison, MIC reports a seriously delinquent rate of 
3.63 percent for FHA loans. See MIC, The Market Pulse, Winter 2001, 
page 6. 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.
---------------------------------------------------------------------------

    The procedure for excluding B&C mortgages from estimated 
``unadjusted'' market shares for goals-qualifying loans in

[[Page 24470]]

1999 combined information from several sources. First, the $160 
billion estimate for the subprime market was multiplied by 79.4 
percent to arrive at an estimate of $127 billion for subprime loans 
less than the year 1999 conforming loan limit of $240,000; the 79.4 
percent estimate for the conforming market was based on HMDA data 
for mortgages originated by subprime lenders. The $127 billion was 
reduced by one-half to arrive at an estimate of $63.5 billion for 
the conforming B&C market; with an average loan amount of 
$78,801(obtained from HMDA data, as discussed below), the $63.5 
billion represented approximately 806,081 B&C loans originated 
during 1999 under the conforming loan limit.
    HMDA data was used to provide an estimate of the portion of 
these 806,081 B&C loans that would qualify for each of the housing 
goals. HMDA data does not identify subprime loans, much less divide 
them into their A-minus and B&C components. As explained in Appendix 
A, Randall Scheessele in HUD's Office of Policy Development and 
Research has identified almost 200 HMDA reporters that primarily 
originate subprime loans. The goals-qualifying percentages of the 
loans originated by these subprime lenders in 1999 were as follows: 
63.0 percent qualified for the Low- and Moderate-Income Goal, 32.5 
percent for the Special Affordable Goal, and 47.0 percent for the 
Underserved Areas Goal.\44\ Applying the goals-qualifying 
percentages to the estimated B&C market total of 806,081 gives the 
following estimates of B&C loans that qualified for each of the 
housing goals in 1999: Low- and Moderate Income (507,831), Special 
Affordable (261,976), and Underserved Areas (378,858).
---------------------------------------------------------------------------

    \44\ The goals-qualifying percentages for subprime lenders are 
much higher than the percentages (46.3 percent, 18.3 percent, and 
28.2 percent, respectively) for the overall single-family 
conventional conforming market in 1999. For further analysis of 
subprime lenders, see Randall M. Scheessele, 1998 HMDA Highlights, 
op. cit.
---------------------------------------------------------------------------

    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 10,638,797 single-family and multifamily 
units were financed during 1999; of these, 6,229,569 (58.6 percent) 
qualified for the Low- and Moderate-Income Goal, 3,133,701 (29.5 
percent) for the Special Affordable Goal, and 3,711,271 (34.9 
percent) for the Underserved Areas Goal. Deducting the B&C market 
estimates produces the following adjusted market estimates: a total 
market of 9,983.276, of which 5,721,738 (58.2 percent) qualified for 
the Low- and Moderate-Income Goal, 2,871,725 (29.2 percent) for the 
Special Affordable Goal, and 3,332,413 (33.9 percent) for the 
Underserved Areas Goal.
    As seen, the low-mod market share estimate exclusive of B&C 
loans (58.2 percent) is practically the same as the original market 
estimate (58.6 percent), as is also the special affordable market 
estimate (29.5 percent versus 29.2 percent). 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 63.0 percent and HUD's market model 
projected the overall low-mod share to be 58.6 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 47.0 percent of the B&C loans, which 
is a higher percentage than the underserved area share of the 
overall market (34.9 percent). Thus, dropping the B&C loans leads to 
a reduction in the underserved areas market share of 1.0 percentage 
points, from 34.9 percent to 33.9 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 1999, 
HUD's model calculates that single-family-owner units accounted for 
71.4 percent of total units financed during 1999. Dropping the B&C 
owner loans, as described above, reduces the owner percentage of the 
market by 2.3 percentage points to 69.1 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.
    Dropping all subprime loans (both A-minus and B&C) from the 
market definition would lead to similar results for the Low-Mod and 
Special Affordable Goals '' little change in the market estimates 
for the reasons given above (the low-mod estimate falls to 57.8 
percent and the special affordable share falls to 28.9 percent). The 
market estimate for the Underserved Areas Goal would fall an 
additional 1.2 percentage points to 32.7 percent (or 2.2 percentage 
points lower than the overall estimate of 34.9 percent).
    As discussed in the 2000 Rule, there are caveats that should be 
mentioned concerning the above adjustments for the B&C market for 
1999. The adjustment for B&C loans depends on several estimates 
relating to the 1999 mortgage market, derived from various sources. 
Different estimates of the size of the B&C market in 1999 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.\45\ 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.
---------------------------------------------------------------------------

    \45\ 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.9 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.
---------------------------------------------------------------------------

    Adjustment for Non-Metropolitan Areas. HUD first estimated the 
underserved area percentage for 1999-2002 based on single-family-
owner parameters for metropolitan areas. It was necessary to adjust 
these metropolitan-based market shares upward to reflect the fact 
that underserved counties account for a much larger portion of non-
metropolitan areas than underserved census tracts do of metropolitan 
areas. The adjustment averaged about 1.5 percentage points; the 
method for deriving the upward adjustment is explained in Section 
G.3 below.
    Manufactured Housing Loans. HUD includes the effects of 
manufactured housing loans (at least those financing properties in 
metropolitan areas) in its market estimates. However, sensitivity 
analyses are conducted to determine the effects of excluding these 
loans. Excluding these loans from the market definition would reduce 
the 1995-2001 estimates of the three goals-qualifying market shares 
by approximately one percentage point. Assuming a home purchase 
environment (1995-97 and 1999-2000) and a constant mix of owner and 
rental properties, excluding manufactured housing loans (as well as 
loans less than $15,000) would reduce the goals-qualifying shares 
reported in Table D.9 roughly as follows: Low- and Moderate-Income 
Goal by 1.2 percentage points, Special Affordable Goal by 1.0 
percentage points, and Underserved Areas Goal by 0.8 percentage 
point. (The method for calculating these reductions is explained in 
Section F.3b below.) Dropping manufactured housing from the market 
totals would increase the rental share of the

[[Page 24471]]

mortgage market, which would tend to increase the goals-qualifying 
shares and thus partially offset the reductions reported above. In 
addition, the estimated reductions in goals-qualifying shares due to 
excluding manufactured housing are even lower during the heavy 
refinance years such as 1998 and 2001. It should also be mentioned 
that manufactured housing in non-metropolitan areas is not included 
in HUD's analysis due to lack of data; including that segment of the 
market would increase the goals-qualifying shares of the overall 
market. Thus, the analyses of manufactured housing reported above 
and throughout this proposed Rule pertain only to manufactured 
housing loans in metropolitan areas, as measured by loans originated 
by the 21 manufactured housing lenders identified by HUD.

b. Estimates of the Low- and Moderate-Income Market

    This section provides HUD's estimates for the size of the low- 
and moderate-income mortgage market that will serve as a proxy for 
the four-year period (2005-2008) when the new housing goals will be 
in effect. Three alternative sets of projections about property 
shares and rental property low- and moderate-income percentages are 
given in Table D.10. 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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[[Page 24473]]

    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. Thus, Table D.11 provides market estimates for 
different low-mod percentages for the owner market as well as for 
different multifamily mix percentages--15.0 percent bracketed by 
13.5 percent and 16.5 percent, which are the same multifamily mixes 
assumed in the 2000 Rule. The low-mod market estimates in Table D.11 
exclude B&C loans, in the same manner as discussed earlier for the 
1995-2001 market estimates. This is explained further below.

[[Page 24474]]

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    Table D.11 assumes a refinance rate of 35 percent, which means 
that the table reflects home purchase or low-refinancing 
environments. After presenting these results, market estimates 
reflecting heavy refinance environments will be presented. Because 
of

[[Page 24475]]

the increase in single-family mortgages, the multifamily share of 
the mortgage market typically falls during a heavy refinance 
environment; therefore, several sensitivity analyses using lower 
multifamily mixes are examined below.
    In the 2000 Rule, HUD assumed that the low-mod share of 
refinance loans was three percentage points lower than the low-mod 
share of borrowers purchasing a home. However, as discussed earlier, 
the low-mod share of refinance loans has equaled or been greater 
than the low-mod share of home purchase loans during recent home 
purchase environments such as 1995-97 or 1999-2000; thus, the 
assumption of a lower low-mod shares for refinance loans is 
initially dropped for this analysis but will be reintroduced during 
the sensitivity analysis and during the discussion of heavy 
refinance environments.
    There are two ways to view the single-family-owner low-mod 
percentages reported in the first column of Table D.11. A first 
approach would be to view them as representing low-mod percentages 
of only the home purchase market. For example, a low-mod percentage 
for home purchase loans of 43 percent (as it was say in 1997)--
combined with the assumption of an equal low-mod share for refinance 
loans (i.e., also 43 percent) and with the other model assumptions 
(such as a multifamily mix of 15 percent)--produces an estimate of 
55.9 percent for the low-mod share of the overall (owner and rental) 
market, excluding B&C loans. Thus, the reader can view Table D.11 as 
showing the overall low-mod market estimate once the reader 
specifies his or her views about the low-mod share of the single-
family home purchase market (given the other model assumptions). In 
this case, if the reader believes that the low-mod share of 
refinance loans should be lower than that for home purchase loans, 
the reader simply has to multiply the differential amount by 0.35 
(which is the refinance share of single-family-owner loans) and 
0.722 (which is the single-family-owner share of all dwelling units 
in the baseline model that assumes a 15 percent multifamily mix). 
For example, applying the assumption in the 2000 Rule that the low-
mod share is three percentage points lower for refinance loans would 
reduce the overall low-mod share of the market by 0.8 percentage 
points (3.0 times 0.35 times 0.722). In this manner, the reader can 
easily adjust the market estimates reported in Table D.11 to 
incorporate his or her own views about differences in the low-mod 
share of home purchase and refinance loans.
    A second approach would be to view the low-mod percentages (in 
the first column of Table D.11) as representing low-mod shares for 
the overall single-family-owner market, including both home purchase 
and refinance loans. This approach does not specify separate low-mod 
percentages for home purchase and refinance loans, but rather 
focuses on the overall single-family-owner environments. Thus, it 
allows for mortgage market environments where the low-mod share of 
refinance loans is greater than the low-mod share for home purchase 
loans. For example, a low-mod percentage for single-family-owner 
loans of 47 percent would reflect the year 2000 environment, which 
had a low-mod home purchase percentage of 45 percent combined with a 
higher low-mod refinance percentage of 52 percent. Of course, the 47 
percent low-mod share for the overall single-family-owner market 
could be consistent with other combinations of low-mod shares for 
home purchase and refinance loans. In this case, a 47 percent 
assumption for the overall single-family-owner market produces an 
estimate of 59.0 percent for the low-mod share of the overall (owner 
and rental) market, excluding B&C loans.
    While both approaches will be discussed below, most of the 
discussion will focus on the first approach. It should be noted that 
several low-mod percentages of the owner market are given in Table 
D.11 to account for different perceptions of that market. 
Essentially, HUD's approach throughout this appendix is to provide 
several sensitivity analyses to illustrate the effects of different 
views about the goals-qualifying share of the single-family-owner 
market. This approach recognizes that there is some uncertainty in 
the data and that there can be different viewpoints about the 
various market definitions and other model parameters.
    Market Estimates. As shown in Table D.11, the market estimate 
is: 57-58 percent if the owner percentage is 45 percent (home 
purchase share for 1999, 2000, and 2002); 55-57 percent if the owner 
percentage is 43 percent (home purchase share for 1998 and 2001); 
and 54-55 percent if the owner percentage is 42 percent (home 
purchase average from 1995-97). If the low- and moderate income 
percentage for home purchase loans fell to 38 percent--or five 
percentage points from its 1995-2001 average level of 43 percent--
then the overall market estimate would be about 52 percent. Thus, 52 
percent is consistent with a rather significant decline in the low-
mod share of the single-family home purchase market. If the low-mod 
percentage for home purchase loans fell further to 35 percent (or 8 
percentage points below its 1995-2002 average of 43 percent), the 
overall market estimate would still be approximately 50 percent. 
Under the baseline projection, the home purchase percentage can fall 
as low as 34 percent--about four-fifths of the 1995-2002 average--
and the low- and moderate-income market share would still be 49-50 
percent.
    The market estimates reported in Table D.11 for Case 2 and Case 
3 bracket those for Case 1 (the baseline). The smaller single-family 
rental market and lower low- and moderate-income percentages for 
rental properties result in the Case 2 estimates being about one and 
a half percentage points below the Case 1 estimates. Conversely, the 
higher percentages under Case 3 result in estimates of the low-mod 
market approximately two percentage points higher than the Case 1 
estimates. As discussed in Section D, the baseline Case 1 is a 
reasonable approach for estimating the market shares.
    Multifamily Mix. The volume of multifamily activity is also an 
important determinant of the size of the low- and moderate-income 
market. HUD is aware of the uncertainty surrounding projections of 
the multifamily market and consequently recognizes the need to 
conduct sensitivity analyses to determine the effects on the overall 
market estimate of different assumptions about the size of that 
market. As discussed in Section C of this appendix, the average 
multifamily share between 1991 and 2002 was approximately 16 
percent, so 15 percent represents a slightly more conservative 
baseline. In addition, in single-family home purchase (or low 
refinancing) environments, the multifamily mix has typically been 
above 16 percent. Therefore, when considering single-family home 
purchase environments, it is probably more appropriate to focus on 
the top two multifamily mixes (15 percent and 16.5 percent) in Table 
D.11. Still, given the uncertainty surrounding the size of the 
multifamily market, it is useful to consider the effects of lower 
multifamily mix assumptions, even in a home purchase environment. 
Assuming a 13.5 percent multifamily mix reduces the overall low-mod 
market estimates by 0.6-0.7 percentage points compared with a 15 
percent mix, and by 1.2-1.4 percentage points compared with a 16.5 
percent mix. For example, when the low-mod share of the home 
purchase market is at 43 percent, the low-mod share of the overall 
market is 55.3 percent assuming a 13.5 percent multifamily mix, 
compared with 55.9 (56.6) percent assuming a 15 (16.5) percent 
multifamily mix. The next section examines the effects of 
multifamily mixes lower than 13.5 percent.
    Heavy Refinancing Environments. As shown earlier in Table D.11, 
the low-mod share of the overall market declines when refinances 
dominate the market. Compared with low-mod market shares of 57-59 
percent during recent home purchase environments (1995-97 and 1999-
2000), the low-mod share declined to 54-55 percent during 1998, 
2001, and 2002--three years where refinancing dominated the single-
family-owner mortgage market. As explained earlier, this decline in 
the low-mod market share during heavy refinancing periods is due to 
(a) a decline in the low-mod share of single-family refinance 
mortgages as middle- and upper-income borrowers dominate the 
refinance market; (b) a decline in the relative importance of the 
subprime market; and (c) a decline in the share of multifamily 
mortgages. For example, during 2001, the refinance share of low-mod 
loans fell to 41.8 percentage points (from about 49 percent during 
1999 and 2000); the subprime share of the single-family market fell 
to 8.5 percent (from about 13 percent during 1999 and 2000); and the 
multifamily share of the market fell to 13.4 percent (from about 16 
percent during 1999 and 2000). Similarly during 2002, the low-mod 
share of refinance loans was 42.3 percent, the subprime share of the 
market was 8.6 percent, and the multifamily mix was approximately 11 
percent.
    Several assumptions were changed to incorporate a refinance 
environment into the projection model for 2005-08. The refinance 
share of single-family mortgages was increased to 65 percent, or 
almost double the 35 percent refinance rate assumed in the 
projection model for a ``home purchase'' environment. The market 
share for subprime loans was assumed to be 8.5 percent and the

[[Page 24476]]

multifamily mix, 13.5 percent. The low-mod share for refinance loans 
was assumed to be 39 percent, or four percentage points below the 
assumed low-mod share of home purchase loans (which was set at the 
1998 and 2002 level of 43 percent). Under these assumptions, the 
overall low-mod market share (excluding B&C loans) was projected to 
be 53.4 percent--or about 1-2 percentage points below the market 
shares estimated for 1998, 2001, and 2002. If the multifamily mix is 
reduced further to 12 (10) percent, the market projection falls to 
52.7 (51.8) percent. If the single-family low-mod percentages are 
reduced to 41 percent (home purchase) and 37 percent (refinance), 
and the multifamily mix is 12 (10) percent, the overall low-mod 
market share falls 51.1 (50.2) percent. Since refinance environments 
are characterized by low interest rates, it is unlikely that the 
low-mod share of the home purchase market would fall below 41 
percent, given that it has averaged 43 percent over the past eight 
years.
    To further examine this issue in the context of an actual 
refinance environment, the various parameters (e.g., low-mod share 
of home purchase and refinance loans for owner and rental 
properties, the subprime share of the market, etc.) for the year 
2002 were used except that the multifamily mix was lowered from the 
actual level in 2002. During 2002, there was a three percentage 
point differential between the low-mod share of home purchase loans 
(45.3 percent) and refinance loans (42.3 percent). As reported 
earlier, the low-mod share of the 2002 market was estimated to be 
54.4 percent assuming a multifamily mix of 11.5 percent, and 10.9 
percent assuming a multifamily mix of 10.9 percent. The multifamily 
mix for a year such as 2003, characterized by single-family 
originations of $3.3 trillion, will certainly be lower than the 11 
percent multifamily mix of 2002, characterized by $2.5 trillion in 
single-family originations. Thus, this sensitivity analysis reduces 
the multifamily mix for the 2002 refinance environment. The low-mod 
shares vary with the multifamily mix as follows: (53.8 percent low-
mod share, 10 percent multifamily mix); (53.3 percent, 9 percent); 
(52.9 percent, 8 percent); 52.5 percent, 7 percent); and (52.1 
percent, 6 percent). Thus, under the actual 2002 assumptions, the 
low-mod share drops by about one-half percentage point for each one 
percentage point reduction in the multifamily mix.\46\ The low-share 
remains above 52 percent even if the multifamily mix falls to 6 
percent.\47\
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    \46\ This analysis assumes the 2002 refinance rate of 62 
percent; if the refinance rate is increased to 65-68 percent 
(current predictions for 2003), then the overall low-mod market 
percentages in this sentence would decline by about 0.1 percentage 
point. If there were a four (five) percentage point difference 
between the low-mod shares of home purchase and refinance loans, 
rather than a three percentage point difference as in 2002, then the 
overall low-mod market percentages in this sentence would decline by 
about 0.5 (1.0) percentage point.
    \47\ For a given multifamily mix, the low-mod shares of the 
market are higher under the simulations based on the 2002 
environment, as compared with the simulations reported in the above 
paragraph based on the projection model. The reason for this is that 
the low-mod shares for the various property types were higher during 
2002 than those assumed in the projection model.
---------------------------------------------------------------------------

    The various market estimates presented in Table D.11 for a home 
purchase environment and reported above for a refinance environment 
are not all equally likely. Most of them equal or exceed 52 percent. 
In the home purchase environment, estimates below 52 percent would 
require the low-mod share of the single-family-owner market for home 
purchase loans to drop to 36-37 percent, which would be 6-7 
percentage points below the average. Dropping below 52 percent would 
be more likely in a heavy refinance environment, as the actual 
estimated market shares during 1998, 2001, and 2002 were in the 54-
55 percent range. However, sensitivity analyses of a refinance 
environment showed that a 52 percent low-mod market share was 
consistent with market assumptions more adverse than the heavy 
refinance years of 1998, 2001, and 2002.
    B&C Loans. There are two possible approaches for adjusting for 
the effects of B&C loans in the projection model. First, readers 
could choose a single-family low-mod percentage (that is, one of the 
percentages in the first column in Table D.11) that they believe is 
adjusted for B&C loans and then obtain a rough estimate of the 
overall market estimate from the second to fourth columns 
corresponding to different multifamily mixes. For instance, if one 
believes the appropriate single-family-owner percentage adjusted for 
B&C loans (or adjusted for any other market sectors that the reader 
thinks appropriate) is 39 percent, then the low-mod market estimate 
is 52.7 percent assuming a multifamily mix of 15 percent. While 
intuitively appealing, such an approach would provide inaccurate 
results, as explained next.
    Second, readers could choose a single-family-owner percentage 
directly from HMDA data that is unadjusted for B&C loans and then 
rely on HUD's methodology (described below) for excluding the 
effects of B&C loans. This is the approach taken in Table D.11. The 
advantage of the second approach is that HUD's methodology makes the 
appropriate adjustments to the various property shares (i.e., the 
owner versus rental percentages) that result from excluding single-
family B&C loans from the analysis. According to HUD's methodology, 
dropping B&C loans would reduce the various low-mod market estimates 
by less than half of a percentage point. This minor effect is due to 
(a) the fact that the low-mod share of B&C loans is similar to that 
of the overall market; and (b) the offsetting effects of the 
increase in the rental market share when single-family B&C loans are 
dropped from the market totals.
    As noted above, if one assumes the single-family-owner 
percentages in the first column of Table D.11 are unadjusted for B&C 
loans, then the overall low-mod market estimates must be adjusted to 
exclude these loans. B&C loans were deducted in HUD's projection 
model using the same procedure described earlier for the 1995-2002 
market estimation models. The effects of deducting the B&C loans 
from the projection model can be illustrated using an example of a 
low-mod percentage of 43 percent for single-family-owner loans. 
Again, as explained earlier, this 43 percent figure could reflect a 
mortgage market environment where home purchase and refinance loans 
had similar low-mod percentages (i.e., 43 percent) or a mortgage 
market environment where home purchase and refinance loans had 
different low-mod market percentages that together resulted in a 43 
percent average for the single-family-owner market.
    As Table D.11 shows, a 43 percent low-mod share for owner 
mortgages translates into an overall low-mod market share of 55.9 
percent. It is assumed that the subprime market accounts for 12 
percent of all mortgages originated, which would be $204 billion 
based on $1,700 billion for the mortgage market. This $204 billion 
estimate for the subprime market is reduced by 20 percent to arrive 
at $163.2 billion for subprime loans that will be less than the 
conforming loan limit. This figure is reduced by one-half to arrive 
at $81.6 billion for the conforming B&C market; with an average loan 
amount of $129,899; the $81.6 billion represents 628,180 B&C loans 
projected to be originated under the conforming loan limit.
    Following the procedure discussed in Section F.3a, the low-mod 
share of the market exclusive of B&C loans is estimated to be 55.9 
percent (see Table D.11), which is only slightly lower than the 
original (unadjusted) estimate of 56.1 percent.\48\ 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 (58.6 percent for excluded B&C 
loans versus 56.1 percent for the overall, unadjusted market 
estimate). The impact of dropping B&C loans is larger when the 
overall market share for low-mod loans is smaller. If the low-mod 
share for single-family owners is assumed to be 38 percent, dropping 
B&C loans would reduce the low-mod market share by 0.4 percentage 
points, from 52.5 percent to the 52.1 percent reported in Table 
D.11. Still, dropping B&C loans from the market totals does not 
change the overall low-mod share of the market appreciably.
---------------------------------------------------------------------------

    \48\ 1999-2002 HMDA data for subprime lenders were used to 
provide an estimate of 58.6 percent for the portion of the B&C 
market that would qualify as low- and moderate-income. Applying the 
58.6 percentage to the estimated B&C market total of 628,180 gives 
an estimate of 367,957 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 628,180 B&C loans and the 367,957 
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 10,632,145 single-
family and multifamily units will be financed and of these, 
5,962,527 (56.1 percent) 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 10,003,964 of 
which 5,594,570 (55.9 percent) will qualify for the Low- and 
Moderate-Income Goal.
---------------------------------------------------------------------------

    Dropping B&C loans from HUD's projection model changes the mix 
between rental and owner units in the final market estimate;

[[Page 24477]]

rental units accounted for 29.6 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.
    A similar analysis can be used to demonstrate the effects of 
deducting the remaining, A-minus portion of the subprime market from 
the market estimates. Of course, deducting A-minus loans as well as 
B&C loans is equivalent to deducting all subprime loans from the 
market. In the example given above (43 percent low-mod percentage 
for owners), deducting all subprime loans would further reduce the 
overall low-mod market estimate to 55.7 percent. Thus, the 
unadjusted low-mod market estimate is 56.1 percent, the estimate 
adjusted for B&C loans is 55.9 percent (reported in Table D.11), and 
the estimate adjusted for all subprime loans is 55.7 percent.
    Section F.3.a discussed several caveats concerning the analysis 
of subprime loans. It is not clear what types of loans (e.g., first 
versus second mortgages) are included in the subprime market 
estimates. There is only limited data on the borrower 
characteristics of subprime loans and the extent to which these 
loans are included in HMDA is not clear. Still, the above analysis 
demonstrates that the projection model can incorporate the effects 
of dropping B&C loans (or even all subprime loans) from the final 
market estimates.
    Manufactured Housing Loans. Excluding manufactured housing loans 
(as well as small loans less than $15,000) reduces the overall 
market estimates reported in Table D.11 by one-percentage point. 
This is estimated as follows. First, excluding these loans reduces 
the unadjusted low-mod percentage for single-family-owner mortgages 
in metropolitan areas by about 1.8 percentage points, based on 
analysis of recent home purchase environments (1995-97 and 1999 and 
2000). Multiplying this 1.8 percentage point differential by the 
property share (0.722) of single-family-owner units yields 1.3 
percentage points, which serves as a proxy for the reduction in the 
overall low-mod market share due to dropping manufactured home loans 
from the market analysis. The actual reduction will be somewhat less 
because dropping manufactured home loans will increase the share of 
rental units, which increases the overall low-mod market share, thus 
partially offsetting the 1.3 percent reduction. The net effect is 
probably a reduction of about one percentage point.
    The above analysis of the effects of dropping different 
categories of loans from the market suggest that 52-58 percent is a 
reasonable range of estimates for the low- and moderate-income 
market. This range covers markets without B&C and allows for market 
environments that would be much less affordable than recent market 
conditions. The next section presents additional analyses related to 
market volatility and affordability conditions. After that, a one-
percentage point downward adjustment is made to the 52-58 percent 
market range to reflect the anticipated effects of re-benchmarking 
metropolitan area incomes based on 2000 Census data and 
incorporating the new OMB definitions for metropolitan areas.

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

    During the 2000 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. 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 have existed during the 1993 to 
2002 period.
    Volatility of Market. Changing economic conditions can affect 
the validity of HUD's market estimates as well as the feasibility of 
the GSEs' accomplishing the housing goals. The volatile nature of 
the mortgage market in the past few years suggest a degree of 
uncertainty around projections of the origination market. Large 
swings in refinancing, consumers switching between adjustable-rate 
mortgages and fixed-rate mortgages, and increased first-time 
homebuyer activity due to record low interest rates, have all 
characterized the mortgage market during the nineties. These 
conditions are beyond the control of the GSEs but they would affect 
their performance on the housing goals. A mortgage market dominated 
by heavy refinancing on the part of middle-income homeowners would 
reduce the GSEs' ability to reach a specific target on the Low- and 
Moderate-Income Goal, for example. A jump in interest rates would 
reduce the availability of very-low-income mortgages for the GSEs to 
purchase. But on the other hand, the next few years may be favorable 
to achieving the goals because of the high refinancing activity in 
2001, 2002, and 2003. A period of low-to-moderate interest rates 
would sustain affordability levels without causing the rush to 
refinance seen earlier in 1998 and 2001-2003. A high percentage of 
potential refinancers have already done so, and are less likely to 
do so again. However, these same predictions were made after the 
1998 refinance wave, which indicates the uncertainty of making 
predictions about the mortgage market.
    HUD conducted numerous sensitivity analyses of the market 
shares, several of which were described in Section F.3b above. The 
starting point of HUD's estimates is the projected $1,700 billion in 
single-family originations. 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 $200 billion, from $1,700 
billion to $1,900 billion, would reduce the market share for the 
Low- and Moderate-Income Goal by approximately 0.6 percentage point, 
assuming the other baseline assumptions remain unchanged. A $400 
billion increase would reduce the low-mod projected market share by 
one percentage point. These reductions in the low-mod share of the 
mortgage market share occur because the multifamily mix is reduced 
from 15 percent to 13.6 percent to 12.5 percent. As explained in 
Section E, the absolute volume of single-family originations (such 
as the $1,700 billion) is not as important as the relative shares of 
single-family and multifamily rental units.
    Recent years have been characterized by record affordability 
conditions due to low interest rates and economic expansion. Thus, 
HUD also examined potential changes in the market shares under very 
different macroeconomic environments, including periods of 
recession, high interest rates, and heavy refinancing (accompanied 
by low interest rates). A recessionary environment would likely be 
characterized by a reduction in single-family activity (or an 
increase in the multifamily share of the market) and a reduction in 
the low-mod shares of the single-family-owner market. The low- and 
moderate-income share of the home purchase market was reduced to 34 
percent, or 10.6 percentage points lower than its 1999-2002 average 
share. Under these rather severe conditions, the overall market 
share for the Low- and Moderate-Income Goal would decline to 49.0 
(49.8) percent, assuming a multifamily mix of 15.0 (16.5) percent. 
If the low-mod share of the owner market were reduced more modestly 
to 37 percent, the low-mod share for the overall market would fall 
to 51.3 percent assuming a multifamily mix of 15.0 percent. (See 
Table D.11.)
    As explained above, several heavy refinance environments were 
simulated. As a way of examining more extreme refinance environments 
than 2002, the effects of reducing the multifamily mix for the 2002 
refinance environment were examined. The low-mod shares varied with 
the multifamily mix from 53.8 percent low-mod share with a 10 
percent multifamily mix to 52.1 percent with a 6 percent multifamily 
mix. Under the actual 2002 market assumptions, the low-mod share 
drops by about one-half percentage point for each one percentage 
point reduction in the multifamily mix.\49\
---------------------------------------------------------------------------

    \49\ This analysis assumes the 2002 refinance rate of 62 
percent; if the refinance rate is increased to 65-68 percent 
(current predictions for 2003), then the overall low-mod market 
percentages in this sentence would decline by about 0.1 percentage 
point. If there were a four (five) percentage point difference 
between the low-mod shares of home purchase and refinance loans, 
rather than a three percentage point difference as in 2002, then the 
overall low-mod market percentages in this sentence would decline by 
about 0.5 (1.0) perecentage point. In addition, due to the 
uncertainty surrounding estimates of the investor share of the 
single-family mortgage market (see Section D), the analysis assumes 
a constant 10 percent share for investors; if the investor share is 
reduced to 8 percent during a refinance environment, the estimated 
low-mod share of the market would fall about one percentage point. 
This figure is obtained by multiplying the low-mod percentage 
differential between owner and investor mortgages (about 47 percent) 
by the resulting decimal point increase in the share of owner units 
(.021 as shown in Table D.7).

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[[Page 24478]]

    Affordability Conditions and Market Estimates. As discussed in 
Appendix A, record low interest rates, a more diverse socioeconomic 
group of households seeking homeownership, and affordability 
initiatives of the private sector have encouraged first-time buyers 
and low-income borrowers to enter the market since the mid-1990s. 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 52-58 percent range for the low-mod 
market share covers economic and market affordability conditions 
much less favorable than recent conditions of low interest rates and 
economic expansion. The low-mod share of the single-family home 
purchase market could fall to 38 percent, which is 5.2 percentage 
points lower than its 1995-2002 average level of 43.2 percent, 
before the baseline market share for the Low- and Moderate-Income 
Goal would below 52 percent.
    Feasibility Determination. As stated in the 2000 Rule, HUD is 
well aware of the volatility of mortgage markets and the possible 
impacts on the GSEs' ability to meet the housing goals. FHEFSSA 
allows for changing market conditions.\50\ If HUD has set a goal for 
a given year and market conditions change dramatically during or 
prior to the year, making it infeasible for the GSE to attain the 
goal, HUD must determine ``whether (taking into consideration market 
and economic conditions and the financial condition of the 
enterprise) the achievement of the housing goal was or is 
feasible.'' This provision of FHEFSSA clearly allows for a finding 
by HUD that a goal was not feasible due to market conditions, and no 
subsequent actions would be taken. As HUD noted in both the 1995 and 
2000 GSE Rules, it does not set the housing goals so that they can 
be met even under the worst of circumstances. Rather, as explained 
above, HUD has conducted numerous sensitivity analyses for economic 
and market affordability environments much more adverse than has 
existed in recent years. If macroeconomic conditions change even 
more dramatically, the levels of the goals can be revised to reflect 
the changed conditions. FHEFSSA and HUD recognize that conditions 
could change in ways that require revised expectations.
---------------------------------------------------------------------------

    \50\ Section 1336(b)(3)(A).
---------------------------------------------------------------------------

d. New 2000 Census Data and New OMB Metropolitan Area Definitions

    Going forward, HUD will be re-benchmarking its median incomes 
for metropolitan areas and non-metropolitan counties based on 2000 
Census median incomes, and will be incorporating the effects of the 
new OMB metropolitan area definitions. HUD projected the effects of 
these two changes on the low- and moderate-income shares of the 
single-family-owner market for the years 1999-2002. Under the 
historical data, the average low-mod share of the conventional 
conforming market was 44.6 percent for home purchase loans 
(unweighted average of 1999-2002 percentages in Table D.8); the 
corresponding average with the projected data was 43.4 percent, 
yielding a differential of 1.2 percentage points. For home purchase 
loans in the conventional conforming market, the projected low-mod 
percentages for each year between 1999 and 2002 were as follows 
(with the historical data from Table D.8 in parentheses): 44.4 
(45.2) percent for 1999; 44.2 (44.8) percent for 2000; 41.8 (43.2) 
percent for 2001; and 43.3 (45.3) percent for 2002. The 
differentials between the projected and historical data are larger 
in 2001 (1.4 percentage points) and 2002 (2.0 percentage points) 
than in 1999 (0.8 percentage point) and 2000 (0.6 percentage point). 
For total (both home purchase and refinance) loans, the average low-
mod share of the conventional conforming market based on historical 
data was 44.8 percent (unweighted average of 1999-2002 percentages 
in Table D.8); the corresponding average with the projected data was 
43.6 percent, again yielding a differential of 1.2 percentage 
points, with the same pattern exhibited for the annual 
differentials.\51\ It appears that the low-mod share for single-
family-owners in the conventional conforming market will be at least 
one percentage point less due to the re-benchmarking of area median 
incomes and the new OMB definitions of metropolitan areas.
---------------------------------------------------------------------------

    \51\ Between 1999 and 2002, the average single-family-owner 
differential between the historical and projected low-mod 
percentages was 1.1 percentage point for Fannie Mae and 1.3 
percentage point for Freddie Mac.
---------------------------------------------------------------------------

    For the other two property types (single-family rental and 
multifamily), comparisons between projected and historical low-mod 
percentages were made using the GSEs' data. For single-family rental 
mortgages, the unweighted average of Fannie Mae's (Freddie Mac's) 
low-mod percentage for the years 1999 to 2002 was 87.8 (88.1) 
percent using the projected data, compared with 87.7 (88.1) percent 
using the historical data. For multifamily mortgages, the unweighted 
average of Fannie Mae's (Freddie Mac's) low-mod percentage for the 
years 1999 to 2002 was 92.1 (90.3) percent using the projected data, 
compared with 92.9 (92.6) percent using the historical data. These 
comparisons suggest little difference between the projected and 
historical low-mod shares for rental properties. HUD also projected 
the overall low-mod goal percentage for each GSE. For the overall 
low-mod goal (considering all three property types), the unweighted 
average of Fannie Mae's (Freddie Mac's) low-mod percentage for the 
years 1999 to 2002 was 48.5 (47.1) percent using the projected data, 
compared with 49.1 (47.9) percent using the historical data. 
Compared with the historical data, the projected data reduces Fannie 
Mae's average low-mod percentage by 0.6 percentage points, and 
Freddie Mac's by 0.8 percentage point.
    Based on the above analysis, it appears the low-mod share of the 
conventional conforming market is about one percentage point less 
when based on projected data, as compared with historical data. 
Thus, it seems appropriate to drop the 52-58 percent market range to 
51-57 percent.

e. Conclusions About the Size of Low- and Moderate-Income Market

    Based on the above findings as well as numerous sensitivity 
analyses, HUD concludes that 51-57 percent is a reasonable range of 
estimates of the mortgage market's low- and moderate-income share 
for the year 2005 and beyond. This range covers much more adverse 
economic and market affordability 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 and refinancing could increase or 
decrease the size of the low- and moderate-income market during that 
period.

G. Size of the Conventional Conforming Market Serving Central Cities, 
Rural Areas, and Other Underserved Areas

    The following discussion presents estimates of the size of the 
conventional conforming market for the Central City, Rural Areas, 
and other Underserved Areas Goal; this housing goal will also be 
referred to as the Underserved Areas Goal. The first three sections, 
which analyze historical data going back to the early 1990's, 
necessarily used 1990 Census geography to define underserved census 
tracts and underserved counties. The first two sections focus on 
underserved census tracts in metropolitan areas, as Section 1 
presents underserved area percentages for different property types 
while Section 2 presents market estimates for metropolitan areas. 
Section 3 discusses B&C loans and rural areas. But as explained in 
Appendix B, HUD will be defining underserved areas based on 2000 
Census geography beginning in 2005, the first year covered by this 
proposed rule. Therefore, Section 4 repeats much of the analyses in 
Sections 1-3 but in terms of 2000 Census geography, rather than 1990 
Census geography.

1. Underserved Areas Goal Shares by Property Type

    For purposes of the Underserved Areas Goal, underserved areas in 
metropolitan areas are defined as census tracts with:
    (a) Tract median income at or below 90 percent of the MSA median 
income; or
    (b) A minority composition equal to 30 percent or more and a 
tract median income no more than 120 percent of MSA median income.
    Owner Mortgages. The first set of numbers in Table D.12 are the 
percentages of single-family-owner mortgages that financed 
properties located in underserved census tracts of metropolitan 
areas between 1992 and 2002. There are several interesting patterns 
in these data. During 1999 and 2000, 28-30 percent of mortgages 
(both home purchase and refinance loans) financed properties located 
in these areas; this percentage fell to 25.7 percent in 2001 and 
25.2 percent in 2002, figures that were slightly below the average 
(26.8 percent) between 1994 and 1998. In 1992 and 1993,

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the underserved areas share of single-family-owner mortgages was 
only 20 percent.
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    In most years, refinance loans are more likely than home 
purchase loans to finance properties located in underserved census 
tracts. Between 1994 and 2002, 28.5 percent of refinance loans were 
for properties in underserved areas, compared to 25.6 percent of 
home purchase loans. This refinance-home-purchase differential is 
mostly due to the influence of subprime loans. Excluding B&C (all 
subprime) loans and considering the same time period, 27.2 (25.6) 
percent of refinance loans were for properties in underserved areas, 
compared to 25.2 (24.8) percent of home purchase loans. In the year 
(2000) with the largest differential, excluding B&C (all subprime) 
loans reduced the refinance-home-purchase differential from 8.1 
percent to 6.8 (4.9) percent; in this case, a significant 
differential remained after excluding B&C (subprime) loans. In the 
heavy refinance years of 1998, 2001, and 2002, underserved areas 
accounted for 25-27 percent of both home purchase and refinance 
loans.
    The underserved areas share for home purchase loans has been in 
the 25-26 range since 1995, except for 2000 and 2002 when it 
increased to slightly over 27 percent. Considering all (both home 
purchase and refinance) loans during recent ``home purchase'' 
environments, the underserved areas share was a high 28-30 percent 
during 1999-2000, compared with a 27.1 percent average between 1995 
and 1997; excluding B&C and other (i.e., A-minus) subprime loans 
places 1999 on par with the earlier years, with only the year 2000 
showing a higher level of underserved area lending than occurred 
during 1995-97. These data indicate that the single-family-owner 
market in underserved areas has remained strong since the 2000 Rule 
was written. While it is recognized that economic and housing 
affordability conditions could change and reduce the size of the 
underserved areas market, it appears that the underserved market has 
certainly maintained itself at a high level over the past four 
years.
    Renter Mortgages. The second and third sets of numbers in Table 
D.12 are the underserved area percentages for single-family rental 
mortgages and multifamily mortgages, respectively. Based on HMDA 
data for single-family, non-owner-occupied (investor) loans, the 
underserved area share of newly-mortgaged single-family rental units 
has been in the almost 45 percent range over the past nine 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 2000 GSE Rule, HUD estimated that the market share for 
underserved areas would be between 29 and 32 percent. This estimate 
turned out to be below market experience, as underserved areas 
accounted for approximately 32-35 percent of all mortgages 
originated in metropolitan areas between 1999 and 2002 (see Table 
D.9). One reason for the underestimation of 1999-2002 experience was 
that the underserved areas share of the single-family-owner market 
continued to increase during this period of low interest rates. 
Table D.13 reports HUD's new estimates of the market share for 
underserved areas based on the projection model discussed 
earlier.\52\ The estimates in Table D.13 exclude the effects of B&C 
loans.
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    \52\ Table D.13 presents estimates for the same combinations of 
projections used to analyze the Low- and Moderate-Income Goal. Table 
D.10 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.
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    The percentage of single-family-owner mortgages financing 
properties in underserved areas is the most important determinant of 
the overall market share for this goal. Therefore, Table D.13 
reports market shares for different single-family-owner percentages 
ranging from 30 percent (2000 level) to 20 percent (1993 level) to 
18 percent. If the single-family-owner percentage for underserved 
areas is at its 1994-2002 HMDA average of 27 percent, the market 
share estimate is 32-33 percent. The overall market share for 
underserved areas peaks at 35 percent when the single-family-owner 
percentage is at its 2000 level of 30 percent. Most of the estimated 
market shares for the owner percentages that are slightly below 
recent experience are in the 30 percent range.
    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 from 16.5 percent to 13.5 percent reduces 
the overall market projection for underserved areas by only about 
0.6 percentage points. This is because the underserved area 
differentials between owner and rental properties are not as large 
as the low- and moderate-income differentials reported earlier.
    Additional sensitivity analyses were conducted to reflect the 
volatility of the economy and mortgage market. Recession and high 
interest rate scenarios assumed a significant drop in the 
underserved area percentage for single-family-owner mortgages. The 
single-family-owner percentage can go as low as 24 percent--which is 
3 percentage points lower than the 1994-2002 average of 27 percent--
and the estimated market share for underserved areas remains over 30 
percent. In a more severe case, the overall underserved market share 
would be 28 percent if the single-family-owner share fell to 21 
percent (its 1992 level), which is 8-9 percentage points lower than 
its 1999-2000 levels. The heavy refinance scenarios discussed for 
the low-mod market were also projected for the underserved areas 
market. With a 65 percent refinance rate and an assumed 24 percent 
underserved area percentage for owner mortgages, the projection 
model produced overall market estimates that ranged from 32.6 
percent (multifamily mix of 13.5 percent) to 31.7 percent 
(multifamily mix of 9 percent). Lowering the multifamily mix in the 
heavy refinance model characterized by year 2002 assumptions 
produced the following range of estimates for the overall 
underserved areas market: 32.1 percent (multifamily mix of 11.0 
percent) to 31.2 percent (multifamily mix of 8 percent) to 30.7 
percent (multifamily mix of 6 percent).\53\ In the refinance 
scenarios, the underserved areas market share was typically at or 
slightly above 30 percent, which is similar to its market share 
during 1998 (31.0 percent) but somewhat less than its market share 
during 2001 (32.6 percent) and 2002 (32.0 percent).
---------------------------------------------------------------------------

    \53\ During 2002, the underserved areas share was 27.2 percent 
for home purchase loans and 24.4 percent for refinance loans, 
yielding a differential of 2.8 percentage points. Increasing the 
differential to 4 percentage points (by reducing the underserved 
area share of refinance loans to 23.2 percent) would reduce the 
overall underserved areas market percentages reported in the text by 
about 0.6 percentage point.
---------------------------------------------------------------------------

3. Adjustments: B&C Loans, the Rural Underserved Areas Market, and 
Manufactured Housing Loans

    B&C Loans. The procedure for dropping B&C loans from the 
projections is the same as described in Section F.3.b for the Low- 
and Moderate-Income Goal. The underserved area percentage for B&C 
loans is 44.5 percent, which is much higher than the projected 
percentage for the overall market (which peaks at 35 percent as 
indicated in Table D.13). Thus, dropping B&C loans will reduce the 
overall market estimates. Consider the case of a single-family-owner 
percentage of 27 percent, which yields an overall market estimate 
for underserved areas of 33.4 percent, including B&C loans. When B&C 
loans are excluded from the projection model, the underserved areas 
market share falls by 0.7 percentage points to 32.7 percent, which 
is the figure reported in Table D.13.
    Non-metropolitan Areas. Underserved rural areas are non-
metropolitan counties with:
    (a) County median income at or below 95 percent of the greater 
of statewide non-metropolitan median income or nationwide non-
metropolitan income; or
    (b) A minority composition equal to 30 percent or more and a 
county median income no more that 120 percent of statewide non-
metropolitan median income.
    HMDA's limited coverage of mortgage data in non-metropolitan 
counties makes it impossible to estimate the size of the mortgage 
market in rural areas. However, all indicators suggest that 
underserved counties in non-metropolitan areas comprise a larger 
share of the non-metropolitan mortgage market than the underserved 
census tracts in metropolitan areas comprise of the metropolitan 
mortgage market. For instance, underserved counties within rural 
areas include 54 percent of non-metropolitan homeowners; on the 
other hand, underserved census tracts in metropolitan areas account 
for only 34 percent of metropolitan homeowners.
    During 1999-2001, 36-39 percent of the GSEs' total purchases in 
non-metropolitan areas were in underserved counties while 25-30 
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. Between 1999 and 2001, the 
non-metropolitan portion of the Underserved Areas Goal has 
contributed 1.1 to 1.4 (0.7 to 1.3) percentage points to Freddie 
Mac's (Fannie Mae's) 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 41-
45 percent (or 42.7 percent) of all mortgages originated in non-
metropolitan areas between 1999 and 2002. By contrast, underserved 
census tracts accounted for approximately 24-33 percent (or 27.4 
percent) of all mortgages originated in metropolitan areas between 
1999 and 2002.\54\ Assuming that non-metropolitan areas account for 
13 percent of all single-family-owner mortgages and estimating that 
the single-family-owner market for accounts for 72 percent of newly-
mortgaged dwelling units, then the non-metropolitan underserved area 
differential of approximately 15 percent would raise the overall 
market estimate by 1.4 percentage point--15 percentage points times 
0.13 (non-metropolitan area mortgage market share) times 0.72 
(single-family owner mortgage market share). Based on this 
calculation, if the 15 point differential reflected actual market 
conditions, then the underserved areas market share estimated using 
metropolitan area data should be increased by 1.4 percentage points 
to account for the effects of underserved counties in non-
metropolitan areas.\55\ A more conservative adjustment of 1.25 
percentage points was made in Table D.13 for the projection 
model.\56\
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    \54\ These data do not include loans originated by lenders that 
specialize in manufactured housing loans, as well as estimated B&C 
loans. The averages in this and the preceding sentence are annual 
unweighted averages.
    \55\ Mortgage Interest Rate Survey (MIRS) data reported by the 
Federal Housing Finance Board separate conventional home purchase 
loans by their metropolitan and non-metropolitan location. The 
average non-metropolitan share between 1999 and 2002 was about 13 
percent.
    \56\ For the 1999-2002 data in Table D.9, the non-metropolitan 
adjustment was calculated by multiplying the actual single-family-
owner property share during a particular year by that year's 
underserved area share for non-metropolitan areas by the average 
metropolitan/non-metropolitan differential of 15 percent (see text). 
The average differential of 15 percent was used because the annual 
differentials exhibited rather wide variation, and given issues 
about HMDA's coverage of non-metropolitan areas, the average 
differential was used. An adjustment of 1.5 percentage points was 
used for the earlier years, 1995 to 1998.
---------------------------------------------------------------------------

    Manufactured Housing Loans. Excluding manufactured housing loans 
(as well as small loans less than $15,000) reduces the overall 
underserved area market estimates reported in Table D.13 by less 
than one percentage point. This is estimated as follows. First, 
excluding these loans reduces the unadjusted underserved areas 
percentage for single-family-owner mortgages in metropolitan areas 
by about 1.2 percentage points, based on analysis of recent home 
purchase environments (1995-97 and 1999 and 2000). Multiplying this 
1.2 percentage point differential by the property share of single-
family-owner units (72.2 percent) yields 0.8 percentage points, 
which serves as a proxy for the reduction in the overall underserved 
area market share due to dropping manufactured home loans from the 
market analysis. The actual reduction will be somewhat less because 
dropping

[[Page 24484]]

manufactured home loans will increase the share of rental units, 
which increases the overall underserved areas market share, thus 
partially offsetting the 0.8 percent reduction. The net effect is 
probably a reduction of about three-quarters of a percentage point.
    The estimates presented in Table D.13 suggest that 30-35 percent 
would be a reasonable range for the market estimate for underserved 
areas based on the projection model described earlier and assuming 
1990 Census geography. This range incorporates market affordability 
conditions that are more adverse than have existed recently and it 
excludes B&C loans from the market estimates. As discussed next, 
switching from 1990 to 2000 Census geography increases this market 
range by five percentage points to 35-40 percent.

4. 2000-Based Underserved Area Market Shares

    The above analysis has concluded that 30-35 percent would be a 
reasonable market range for the Geographically Targeted Goal based 
on past origination activity in underserved areas and on scenarios 
that cover a variety of economic and mortgage market conditions. 
That analysis, which included historical data going back to the 
early 1990s, necessarily used 1990 Census geography to define 
underserved census tracts. As explained in Appendix B, HUD will be 
defining underserved areas based on 2000 Census geography beginning 
in 2005, the first year covered by this proposed rule. Appendix B 
also explains that the number of census tracts in metropolitan areas 
covered by HUD's underserved area definition will increase from 
21,587 tracts (based on 1990 Census) to 26,959 tracts (based on 2000 
Census and OMB's respecification of metropolitan areas). This 
increase in the number of tracts defined as underserved means that 
the market estimate for the Geographically Targeted Goal will be 
higher than the 30-35 percent estimate presented above. Thus, this 
section provides a new range of market estimates for underserved 
areas defined in terms of 2000 Census data. The 1990-based analysis 
that produced the 30-35 percent range serves as the starting point 
for an upward adjustment in the market range.
    For the years 1999 to 2002, Table D.14 reports the underserved 
areas share of the mortgage market for single-family-owner, investor 
(non-owner), and multifamily properties, with comparisons between 
1990-based and 2000-based measures of underserved areas. HMDA data, 
which is the source of the mortgage data, were reported in terms of 
1990 census tracts. For the years 1999 to 2002, HUD used various 
apportionment techniques to re-allocate 1990-based HMDA mortgage 
data into census tracts as defined by the 2000 Census. The 1990-
based underserved area market shares reported in Table D.14 are the 
same data reported earlier in Table D.12, while the 2000-based 
underserved area market shares result from re-allocating 1999-2002 
HMDA data into 2000 Census geography. In addition, the data are 
defined in terms of the new OMB metropolitan area definitions.

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    First, consider the market shares for single-family-owner 
properties in the top portion of Table D.14. In 2002, the 
underserved area percentage for home purchase loans increases from 
27.2 percent (1990-based) to 33.3 percent (2000-based), an increase 
of 6.1 percentage points; the corresponding percentages for 
refinance loans were 24.4 percent (1990-based) and 29.8 percent 
(2000-based), or an increase of 5.4 percentage points. Considering 
total owner loans (i.e., both home purchase and refinance owner 
loans), the average of the ``Differences'' reported in Table D.14 is 
5.6 percentage points for the conforming market. Between 1999 and 
2001, 32.3 percent of mortgage originations were originated in 
underserved areas based on 2000 geography, compared with 26.7 
percent based on 1990 geography--yielding an overall differential of 
5.6 percentage points.
    Next, consider the underserved area market shares reported for 
single-family rental (or non-owner) and multifamily properties in 
the middle and bottom portions of Table D.14. In 2002, the 
underserved area percentage for home purchase non-owner loans 
increases from 42.1 percent (1990-based) to 48.1 percent (2000-
based), an increase of 6.0 percentage points; the corresponding 
percentages for refinance loans were 45.8 percent (1990-based) and 
51.2 percent (2000-based), or an increase of 5.4 percentage points. 
Considering total single-family rental loans (i.e., home purchase 
and refinance loans), the 1999-02 average of the ``Differences'' 
reported in Table D.14 is 5.3 percentage points for the single-
family rental market. The multifamily differentials are slightly 
higher at approximately 7-8 percentage points. Between 1999 and 
2002, 59.8 percent of multifamily originations (on a dollar basis) 
were originated in underserved areas based on 2000 geography, 
compared with 52.3 percent based on 1990 geography.
    The underserved areas shares based on 2000 Census geography were 
estimated for the last four years, 1999 to 2002; the following 
estimates were obtained: 39.0 percent (1999), 40.4 percent (2000), 
37.7 percent (2001), and 37.2 percent (2002). These 2000-based 
market estimates are slightly over five percentage points higher 
than the 1990-based market estimates for underserved areas reported 
in Table D.9: 5.1 percent (1999), 5.2 percent (2000), 5.1 percent 
(2001), 5.1 percent (2002), and 5.1 percent (2002).\57\ This 
analysis suggests that a reasonable range for the overall market 
share for underserved areas based on 2000 geography might be 35-40 
percent, which is obtained by simply adding five percentage points 
to the 30-35 percent range estimated earlier based on 1990-based 
geography. As discussed next, a 35-40 percent range is indeed an 
appropriate estimate of the underserved area market based on 2000 
geography.
---------------------------------------------------------------------------

    \57\ The differentials reported in Table D.14 for the three 
individual property types tend to be greater than 5.5 percentage 
points, which raises the question of why the overall differential is 
only 5.1 percentage points. As explained later, the upward 
adjustment to account for underserved areas in non-metropolitan 
areas is about 0.65 percentage point less using the 2000-based 
Census data than it was using the 1990-based Census data.
---------------------------------------------------------------------------

    Table D.15 reports the results of the projection model assuming 
2000 geography. Since Table D.15 has the same interpretation as 
Table D.13, there is no need to provide a detailed discussion of 
it.\58\ If the single-family-owner percentage for underserved areas 
is at its 1999-2002 HMDA average of 33 percent, the market share 
estimate is 39 percent. The overall market share for underserved 
areas peaks at approximately 41 percent when the single-family-owner 
percentage is at its 2000 level of 36 percent. Most of the estimated 
market shares for the owner percentages that are within four 
percentage points of recent experience (i.e., the 29-33 percent 
range) are in the 36-39 percent range.
---------------------------------------------------------------------------

    \58\ In addition to adjusting the various single-family-owner 
parameters upward, the following 2000-based assumptions were made 
with respect to the underserved areas shares of single-family rental 
properties: 52.0% for Case 1, 50.0% for Case 2, and 54.0% for Case 
3. If these percentages were based only on the HMDA data reported in 
Table D.14, they would have been 48.0% for Case 1, 46.0% for Case 2, 
and 50.0% for Case 3. However, in conducting this 2000-based 
analysis, HUD also computed the single-family rental shares for the 
GSEs in terms of both the number of mortgages (consistent with the 
HMDA data in Table D.14) and the number of single-family rental 
units financed (the concept used in the housing goals calculation). 
That analysis showed that the unit-based underserved area percentage 
was approximately six percentage points higher than the number-of-
mortgage-based underserved area percentage. To reflect this 
differential, HUD adjusted the percentages in Cases 1-3 by an 
additional four percentage points. With respect to multifamily 
properties, the following assumptions were made with respect to 
underserved areas shares: 58.0% for Case 1, 56.0% for Case 2, and 
59.0% for Case 3. If these percentages were based only on the HMDA 
data reported in Table D.14, they would have been 55.0% for Case 1, 
53.0% for Case 2, and 55.0% for Case 3. HUD computed the multifamily 
underserved area shares for the GSEs in terms of mortgage dollars 
(consistent with the HMDA data Table D.14) and the number of 
multifamily rental units financed (the concept used in the housing 
goals calculation). That analysis showed that the unit-based 
underserved area percentage was also approximately six percentage 
points higher than the mortgage-dollar-based underserved area 
percentage; thus HUD adjusted the percentages upward.
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    Following the 1990-based analysis in Section G.2, additional 
sensitivity analyses were conducted to reflect the volatility of the 
economy and mortgage market. Recession and high interest rate 
scenarios assumed a significant drop in the underserved area 
percentage for single-family-owner mortgages. The single-family-
owner percentage can go as low as 29 percent--which is 3 percentage 
points lower than the 1994-2002 average of 32 percent and 4 
percentage points lower than the 1999-2002 average of 33 percent--
and the estimated market share for underserved areas remains about 
36 percent. In a more severe case, the overall underserved market 
share would be 33-34 percent if the single-family-owner share fell 
to 26 percent (its 1992 level), which is 7 percentage points lower 
than its 1999-2002 average. In the heavy refinance scenarios (with 
their lower multifamily mixes), the underserved areas market share 
was typically around 36-37 percent.
    Non-metropolitan Areas. As explained in Section G.3, in order to 
account for the much larger coverage of underserved areas in non-
metropolitan areas, 1.25 percent was added to the market share based 
on metropolitan area data, in order to arrive at a nationwide 
estimate of the market share for underserved areas. According to 
HMDA, underserved counties accounted for 42.7 percent of single-
family-owner mortgages originated in non-metropolitan areas during 
the 1999-to-2002 period, based on 1990 geography. With 2000 
geography and the new tract-based definition of underserved areas in 
non-metropolitan areas, the market share falls by 2.3 percentage 
points to 39.6 percent. This 2000-based underserved areas percentage 
of 39.6 percent for non-metropolitan areas is about eight percentage 
points less than the comparable percentage for metropolitan 
areas.\59\ This eight-point differential is lower than the 15-point 
differential used in the earlier 1990-based Census analysis. 
Assuming that non-metropolitan areas account for 13 percent of all 
single-family-owner mortgages and estimating that the single-family-
owner market accounts for 72 percent of newly-mortgaged dwelling 
units, then the non-metropolitan underserved area differential of 8 
percent would raise the overall market estimate by 0.75 percentage 
point--8 percentage points times 0.13 (non-metropolitan area 
mortgage market share) times 0.72 (single-family owner mortgage 
market share). Based on this calculation, if the 8 point 
differential reflected actual market conditions, then the 
underserved areas market share estimated using metropolitan area 
data should be increased by 0.75 percentage point to account for the 
effects of underserved counties in non-metropolitan areas, based on 
2000 geography. A more conservative adjustment of 0.65 percentage 
points was made in Table D.15, which reports the results of the 
projection model.
---------------------------------------------------------------------------

    \59\ Between 1999 and 2002, 2000-based underserved census tracts 
accounted for 31.4 percent (unweighted annual average) of all 
mortgages in metropolitan areas. This 1999-02 average percentage for 
metropolitan areas is lower that the 33.0 percent reported in 
previous paragraphs. To be comparable with the non-metropolitan 
data, these metropolitan area data do not include loans originated 
by lenders that specialize in manufactured housing loans and B&C 
loans; excluding these loans lowers the underserved areas share.
---------------------------------------------------------------------------

    Section G.3 reported that excluding manufactured housing loans 
(as well as small loans less than $15,000) reduced the overall 
underserved area market estimates based on 1990 geography by less 
than one percentage point. Excluding manufactured housing loans 
leads to a similar reduction for the market estimates based on 2000 
geography.
    The estimates presented in Table D.15 suggest that 35-40 percent 
is a reasonable range for the market estimate for underserved areas 
based on the projection model described earlier. This range 
incorporates market affordability conditions that are more adverse 
than have existed recently and it excludes B&C loans from the market 
estimates.

5. Conclusions

    Based on the above findings as well as numerous sensitivity 
analyses, HUD concludes that 35-40 percent is a reasonable estimate 
of mortgage market originations that would qualify toward 
achievement of the Geographically Targeted Goal if purchased by a 
GSE. The 35-40 percent range is higher than the market range in the 
2000 Rule mainly because it is based on 2000 Census geography which 
includes more underserved census tracts than 1990 Census geography. 
HUD recognizes that shifts in economic and housing market conditions 
could affect the size of this market; however, the market estimate 
allows for the possibility that adverse economic conditions can make 
housing less affordable than it has been in the last few years. In 
addition, the market estimate incorporates a range of assumptions 
about the size of the multifamily market and excludes B&C loans.

H. Size of the Conventional Conforming Market for the Special 
Affordable Housing Goal

    This section presents estimates of the conventional conforming 
mortgage market for the Special Affordable Housing Goal. The special 
affordable market consists of owner and rental dwelling units which 
are occupied by, or affordable to: (a) Very-low-income families; or 
(b) low-income families in low-income census tracts; or (c) low-
income families in multifamily projects that meet minimum income 
thresholds patterned on the low-income housing tax credit 
(LIHTC).\60\ HUD estimates that the special affordable market is 24-
28 percent of the conventional conforming market.
---------------------------------------------------------------------------

    \60\ There are two LIHTC thresholds: at least 20 percent of the 
units are affordable at 50 percent of AMI or at least 40 percent of 
the units are affordable at 60 percent of AMI.
---------------------------------------------------------------------------

    HUD is proposing to establish each GSE's special affordable 
multifamily subgoal as 1.0 percent of its average annual dollar 
volume of total (single-family and multifamily) mortgage purchases 
over the 2000-2002 period. In dollar terms, the Department's 
proposal is $5.49 billion per year in special affordable multifamily 
purchases for Fannie Mae, and $3.92 billion for Freddie Mac. The 
multifamily special affordable goal, as well as the special 
affordable home purchase subgoal, are discussed further in Appendix 
C.
    Section F described HUD's methodology for estimating the size of 
the low- and moderate-income market. Essentially the same 
methodology is employed here except that the focus is on the very-
low-income market (0-60 percent of Area Median Income) and that 
portion of the low-income market (60-80 percent of Area Median 
Income) that is located in low-income census tracts. Data are not 
available to estimate the number of renters with incomes between 60 
and 80 percent of Area Median Income who live in projects that meet 
the tax credit thresholds. Thus, this part of the Special Affordable 
Housing Goal is not included in the market estimate.

1. Special Affordable Shares by Property Type

    The basic approach involves estimating for each property type 
the share of dwelling units financed by mortgages that are occupied 
by very-low-income families or by low-income families living in low-
income areas. HUD combined mortgage information from HMDA, the 
American Housing Survey, and the Property Owners and Managers Survey 
in order to estimate these special affordable shares.

a. Special Affordable Owner Percentages

    HMDA data for the percentage of single-family-owners that 
qualify for the Special Affordable Goal are reported in Table D.16. 
That table also reports data for the two components of the Special 
Affordable Goal--very-low-income borrowers and low-income borrowers 
living in low-income census tracts. Focusing first on home purchase 
loans, HMDA data show that the special affordable share of the 
market has followed a pattern similar to that discussed earlier for 
the low- and moderate-income loans. The percentage of special 
affordable borrowers increased significantly between 1992 and 1994, 
from 10.4 percent of the conforming market to 12.6 percent in 1993, 
and then to 14.1 percent in 1994. Between 1995 and 1998, the special 
affordable market was in the 14-16 percent range, averaging 15.1 
percent. Over the past four years (1999-2002), the special 
affordable share of the home purchase loans has averaged 16.7 
percent.
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    Considering all (home purchase and refinance) loans during 
recent ``home purchase'' environments, the special affordable share 
averaged 18.8 percent during 1999-2000, over three percentage points 
more than the 15.4 percent average between 1995 and 1997. Excluding 
B&C (all subprime) loans from the analysis reduces this differential 
only slightly to 2.7 (2.4) percentage points. As mentioned earlier, 
lending patterns could change with sharp changes in the economy, but 
the fact that there have been several years of strong affordable 
lending suggests that the special affordable market has changed in 
fundamental ways from the mortgage market of the early 1990s. In 
fact, there appears to have been a slight increase in this market 
recently, at least during 1999 and 2000.
    Except for the three years of heavy refinancing (1998, 2001, and 
2002), the special affordable share of the refinance market has 
recently been higher than the special affordable share of the home 
purchase market--a pattern discussed in Section F for low-mod and 
very-low-income loans. During 1999 (2000), for example, the special 
affordable share of the refinance market was 19.2 (22.7) percent, 
compared with 17.3 (17.1) percent for the home loan market. The 
higher special affordable percentages for refinance loans are 
reduced or even eliminated if subprime loans are excluded from the 
analysis. As shown in Table D.16, excluding B&C loans from the data 
practically eliminates the refinance-home-purchase differential for 
1999 and reduces the differential for 2000 to 4.1 percentage points 
(from 5.6 percentage points). Going further and excluding A-minus 
loans from the year 2000 data would reduce the differential to 2.1 
percentage points. HUD's projection model excludes B&C loans and 
sensitivity analyses will show the effects on the overall special 
affordable market of excluding all single-family subprime loans.

b. Very-Low-Income Rental Percentages

    Table D.14 in Appendix D of the 2000 Rule reported the 
percentages of the single-family rental and multifamily stock 
affordable to very-low-income families. According to the AHS, 59 
percent of single-family units and 53 percent of multifamily units 
were affordable to very-low-income families in 1997. The 
corresponding average values for the AHS's six surveys between 1985 
and 1997 were 58 percent and 47 percent, respectively. As discussed 
earlier in Section F, an important issue concerns whether rent data 
based on the existing rental stock from the AHS can be used to proxy 
rents of newly mortgaged rental units. HUD's analysis of POMS data 
during the 2000 rule-making process suggested that it could--
estimates from POMS of the rent affordability of newly-mortgaged 
rental properties are quite consistent with the AHS data on the 
affordability of the rental stock. Fifty-six (56) percent of single-
family rental properties with new mortgages between 1993 and 1995 
were affordable to very-low-income families, as 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. As explained in the 2000 GSE Rule, the share of single-family 
and multifamily rental units affordable to low-income renters at 60-
80 percent of area median income (AMI) and located in low-income 
tracts was calculated using the internal Census Bureau AHS and POMS 
data files.\61\ 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.\62\ 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.\63\
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    \61\ 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.
    \62\ 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.
    \63\ 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.10.
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2. Size of the Special Affordable Market

    During the 2000 rule making, HUD estimated a market share for 
the Special Affordable Goal of 23-26 percent. This estimate was 
below market experience, as the special affordable market accounted 
for 26-30 percent of all housing units financed between 1999 and 
2002, as well as 26-29 percent of units financed between 1995 and 
1998 (see Table D.9). This underestimation was mainly due to the 
assumption in the projection model that the special affordable share 
of refinance loans was lower than the special affordable share of 
home purchase loans; and the fact that the special affordable share 
of the single-family-owner market increased recently (see above 
discussion). This section produces new estimates of the special 
affordable market.
    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.10 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.
    Table D.17 assumes a refinance rate of 35 percent, which means 
that the table reflects home purchase or low-refinancing 
environments. After presenting these results, market estimates 
reflecting a heavy refinance environment will be presented. In the 
2000 GSE Rule, HUD assumed that the special affordable share of 
refinance loans was 1.4 percentage points lower than the special 
affordable share of borrowers purchasing a home. However, as 
discussed earlier, the special affordable share of refinance loans 
equaled or was greater than the special affordable share of home 
purchase loans during home purchase environments such as 1995-97 or 
1999-2000; thus, the assumption of a lower special affordable shares 
for refinance loans is initially dropped from the analysis but will 
be reintroduced during the sensitivity analysis and the discussion 
of heavy refinancing environments.
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    As shown in Table D.17, the market estimates are: 28-29 percent 
if the owner percentage is 17 percent (home purchase share for 1999 
and 2000); 27-28 percent if the owner percentage is 16 percent (home 
purchase share for 1998, 2001, and 2002); and 26-27 percent if the 
owner percentage is 15 percent (home purchase average from 1995-97). 
If the special affordable percentage for home purchase loans fell to 
12 percent '' or by four percentage points below its 1995-2002 
average level of 16 percent '' then the overall market estimate 
would be about 25 percent. Thus, 25 percent is consistent with a 
rather significant decline in the special affordable share of the 
single-family home purchase market. A 25 percent market estimate 
allows for the possibility that adverse economic and housing 
affordability conditions could keep special affordable families out 
of the housing market. On the other hand, if the special affordable 
home purchase percentage stays at its recent levels (15-17 percent), 
the market estimate is in the 27-29 percent range.
    Heavy Refinancing Environments. The special affordable share of 
the overall market declines when refinances dominate the market. 
Section F.3b, which presents the low-mod market estimates, explained 
the assumptions for incorporating a refinance environment into the 
basic projection model for 2005-08. Briefly, they are: (1) the 
refinance share of single-family mortgages was increased to 65 
percent (from 35 percent); the market share for subprime loans 
reduced to 8.5 percent (from 12 percent); and the multifamily mix 
was initially assumed to be 13.5 percent (instead of 15 percent or 
16.5 percent, which characterize a home purchase environment). The 
special affordable share for refinance loans was assumed to be 13 
percent, or two percentage points below the assumed special 
affordable share of home purchase loans (which was set at 15 
percent, slightly below the 1998, 2001, and 2002 level of 16 
percent). Under these assumptions, the special affordable market 
share (excluding B&C loans) was projected to be 25.4 percent. If the 
multifamily mix is reduced further to 11 (9) percent, the market 
projection falls to 24.4 (23.6) percent. If the single-family 
special affordable percentages are reduced to 14 percent (home 
purchase) and 12 percent (refinance), and the multifamily mix is 11 
(9) percent, the overall low-mod market share falls 23.6 (22.8) 
percent. As noted in the discussion of the low-mod market, refinance 
environments are characterized by low interest rates; therefore, it 
is unlikely that the special affordable share of the home purchase 
market would fall below 14 percent during heavy refinance 
environments, given that it has averaged almost 16 percent over the 
past seven years. In addition to these projections, a refinance 
environment characterized by the year 2002 market was used to 
examine how the special affordable market changed under heavy 
refinancing conditions. Lowering the multifamily mix in the heavy 
refinance model characterized by year 2002 assumptions produced the 
following range of estimates for the overall special affordable 
market: 25.8 percent (multifamily mix of 11.0 percent) to 24.7 
percent (multifamily mix of 8 percent) to 23.9 percent (multifamily 
mix of 6 percent).\64\
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    \64\ During 2002, the special affordable share was 15.8 percent 
for home purchase loans and 14.6 percent for refinance loans, 
yielding a differential of 1.2 percentage points. Increasing the 
differential to 2 percentage points (by reducing the special 
affordable share of refinance loans to 13.8 percent) would reduce 
the overall special affordable market percentages reported in the 
text by about 0.4 percentage point.
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    The various market estimates presented in Table D.17 for a home 
purchase environment and reported above for a refinance environment 
are not all equally likely. Most of them equal or exceed 25 percent. 
In the home purchase environment, estimates below 25 percent would 
require the special affordable share for home purchase loans to drop 
to 12-13 percent which would be 3-4 percentage points lower than the 
1995-2002 average for the special affordable share of the home 
purchase market. Dropping below 25 percent would be more likely in a 
heavy refinance environment, as the actual estimated market shares 
during 1998, 2001, and 2002 were approximately 26 percent. However, 
sensitivity analyses of a refinance environment showed that a 24 
percent special affordable market share was consistent with market 
assumptions significantly more adverse than the heavy refinance 
years of 1998, 2001, and 2002.
    Additional Sensitivity Analyses. Additional sensitivity analyses 
were conducted around the results reported in Table D.17, which 
reflects a home purchase environment. Assuming that the special 
affordable share of the home loan market is 16 percent, reducing the 
multifamily mix from its baseline of 15 percent to 13.5 (12) percent 
would reduce the overall special affordable market share from 27.7 
percent to 27.1 (26.4) percent. In this case, increasing the 
multifamily mix from 15 percent to 16.5 percent would increase the 
special affordable market share from 27.7 percent to 28.2 percent.
    As shown in Table D.17, the market estimates under the more 
conservative Case 2 projections are one to one-and-a-half 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).
    Recent years have been characterized by record low interest 
rates and strong housing affordability conditions. Therefore, it was 
important for HUD to examine potential changes in the market shares 
under more adverse market affordability environments than have 
existed recently, as well as under heavy refinance environments. A 
heavy refinance environment has already been discussed so this 
section focuses on recession and high-interest-rate scenarios. In 
the recession scenario defined earlier in the low-mod analysis (see 
Section F.3a), the special affordable share of the home purchase 
market was reduced to 12 (10) percent, or 4 (6) percentage points 
lower than its 1995-2002 average share of 16 percent. Under these 
rather severe conditions, the overall market share for the Special 
Affordable Goal would decline to 25.1 (23.6) percent, assuming a 
multifamily mix of 16.5 percent. A significant increase in interest 
rates would also make it more difficult for lower income families to 
afford homeownership and qualify for mortgages, thus reducing the 
special affordable share of the market. But as noted above, the 
special affordable share of the home purchase market could fall to 
10 percent '' almost forty percent below its seven-year average of 
16 percent '' before the market share for the Special Affordable 
Goal would fall below 24 percent.
    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 28.0 percent, which is similar to the projected percentages 
for the overall market given in Table D.17. Thus, dropping B&C loans 
(as well as all subprime loans) does not appreciably reduce the 
overall market estimates. Consider the case of a single-family-owner 
percentage of 15 percent, which yields an overall market estimate 
for Special Affordable Goal of 27.0 percent if B&C loans are 
included in the analysis. Dropping B&C loans from the projection 
model reduces the special affordable market share by 0.1 percentage 
points to 26.9, as reported in Table D.15. Dropping all subprime 
loans (A-minus as well as B&C) would reduce the special affordable 
market projection to 26.8 percent.
    Manufactured Housing Loans. Excluding manufactured housing loans 
(as well as small loans less than $15,000) reduces the overall 
market estimates reported in Table D.17 by about one percentage 
point or less. This is estimated as follows. First, excluding these 
loans reduces the unadjusted special affordable percentage for 
single-family-owner mortgages in metropolitan areas by about 1.5 
percentage points, based on analysis of recent home purchase 
environments (1995-97 and 1999 and 2000). Multiplying this 1.5 
percentage point differential by the property share of single-
family-owner units (72.2 percent) yields 1.1 percentage points, 
which serves as a proxy for the reduction in the overall special 
affordable market share due to dropping manufactured home loans from 
the market analysis. The actual reduction will be somewhat less 
because dropping manufactured home loans will increase the share of 
rental units, which increases the overall special affordable market 
share, thus partially offsetting the 1.1 percent reduction. The net 
effect is probably a reduction of slightly less than one percentage 
point.
    Tax Credit Definition. Data are not available to measure the 
increase in market share associated with including low-income units 
located in multifamily buildings that meet threshold standards for 
the low-income housing tax credit. Currently, the effect on GSE 
performance under the Special Affordable Housing Goal is rather 
small. For instance, adding the tax credit condition increased 
Fannie Mae's performance as follows: 0.42 percentage point in 1999 
(from 17.20 to 17.62 percent); 0.59 percentage point in 2000 (from 
18.64 to 19.23 percent); and

[[Page 24493]]

0.43 percent point in 2001 (from 19.29 to 19.72 percent). The 
increases for Freddie Mac have been lower (ranging from 0.24 to 0.38 
percentage point during the same period).
    New 2000-Based Census Geography and New OMB Metropolitan Area 
Definitions. Going forward, HUD will be re-benchmarking its median 
incomes for metropolitan areas and non-metropolitan counties based 
on 2000 Census incomes, will be defining low-income census tracts 
(which are included in the definition of special affordable) in 
terms of the 2000 Census geography, and will be incorporating the 
effects of the new OMB metropolitan area definitions. HUD projected 
the effects of these three changes on the special affordable shares 
of the market for the years 1999-2002. Under the historical data, 
the average special affordable share of the conventional conforming 
market was 16.7 (16.9) percent for home purchase (total) loans (see 
Table D.16); the corresponding average with the projected data was 
16.6 (16.9) percent. For home purchase loans in the conventional 
conforming market, the projected special affordable percentages for 
each year between 1999 and 2002 were as follows (with the historical 
data from Table D.16 in parentheses): 17.5 (17.3) percent for 1999; 
17.4 (17.1) percent for 2000; 15.6 (15.8) percent for 2001; and 15.8 
(16.4) percent for 2002. While the projected percentages are lower 
in 2001 (0.2 percentage point) and 2002 (0.6 percentage point), they 
are higher in 1999 (0.2 percentage point) and 2000 (0.3 percentage 
point). Given these small differences there is no need to changes 
the market estimates discussed above.\65\
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    \65\ For the other two property types (single-family rental and 
multifamily), comparisons between projected and historical special 
affordable percentages were made using the GSEs' data. For single-
family rental mortgages, the unweighted average of Fannie Mae's 
(Freddie Mac's) special affordable percentage for the years 1999 to 
2002 was 50.2 (51.4) percent using the projected data, compared with 
48.0 (49.4) percent using the historical data. For multifamily 
mortgages, the unweighted average of Fannie Mae's (Freddie Mac's) 
special affordable percentage for the years 1999 to 2002 was 50.4 
(45.1) percent using the projected data, compared with 53.6 (49.4) 
percent using the historical data. These comparisons suggest little 
difference between the projected and historical special affordable 
shares for rental properties. HUD also projected the overall special 
affordable percentage for each GSE. For the overall special 
affordable goal (considering all three property types), the 
unweighted average of Fannie Mae's (Freddie Mac's) special 
affordable percentage for the years 1999 to 2002 was 20.0 (18.9) 
percent using the projected data, compared with 20.0 (18.9) percent 
using the historical data. There is little difference in the GSEs' 
average special affordable performance between the projected and 
historical data.
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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 24-28 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.

[FR Doc. 04-9352 Filed 4-30-04; 8:45 am]
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