[Federal Register Volume 65, Number 47 (Thursday, March 9, 2000)]
[Proposed Rules]
[Pages 12632-12816]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 00-5122]



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Part II





Department of Housing and Urban Development





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24 CFR Part 81



Office of the Assistant Secretary for Housing-Federal Housing 
Commissioner; HUD's Regulation of the Federal National Mortgage 
Association (Fannie Mae) and the Federal Home Loan Mortgage Corporation 
(Freddie Mac); Proposed Rule

  Federal Register / Vol. 65, No. 47 / Thursday, March 9, 2000 / 
Proposed Rules  

[[Page 12632]]


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DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT

Office of the Assistant Secretary for Housing--Federal Housing 
Commissioner

24 CFR Part 81

[Docket No. FR-4494-P-01]
RIN 2501-AC60


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

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

ACTION: Proposed rule.

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SUMMARY: Through this proposed rule, the Department of Housing and 
Urban Development is soliciting comments on proposed 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 2000 
through 2003. In accordance with the Federal Housing Enterprises 
Financial Safety and Soundness Act of 1992, this rule proposes new goal 
levels for the purchase by Fannie Mae and Freddie Mac of mortgages 
financing low-and moderate-income housing, special affordable housing, 
and housing in central cities, rural areas, and other underserved 
areas. This rule also proposes to clarify HUD's guidelines for counting 
different types of mortgage purchases toward those goals, and to 
provide greater public access to certain types of mortgage data on the 
GSEs' mortgage purchases in HUD's public use database. This rule also 
solicits public comments on several other issues related to the housing 
goals.
    While Fannie Mae and Freddie Mac have been successful in providing 
stability and liquidity in the market for certain types of mortgages, 
their share of the affordable housing market is substantially smaller 
than their share of the total conventional conforming mortgage market. 
There are several reasons for these disparities, related both to the 
GSEs' purchase and underwriting guidelines and to their relatively low 
level of activity in specific markets that serve lower-income families, 
including small multifamily rental properties, manufactured housing, 
single family owner-occupied rental properties, and seasoned affordable 
housing mortgages. As the GSEs continue to grow their businesses, the 
proposed new goals will provide strong incentives for the two 
enterprises to more fully address the housing finance needs for very 
low-, low-and moderate-income families and residents of underserved 
areas and thus, more fully realize their public purposes.

DATES: Comments must be submitted on or before: May 8, 2000.

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. Written 
comments may also be provided electronically to the following e-mail 
address: [email protected] All communications should refer to the above 
docket number and title. Facsimile (FAX) comments are not acceptable. A 
copy of each communication submitted will be available for public 
inspection and copying between 7:30 a.m. and 5:30 p.m. weekdays at the 
above address.

FOR FURTHER INFORMATION CONTACT: Janet A. Tasker, Director, Office of 
Government Sponsored Enterprises Oversight, Room 6182, telephone (202) 
708-2224. For questions on data or methodology, contact John L. 
Gardner, Director, Financial Institutions Regulation Division, Office 
of Policy Development and Research, Room 8234, telephone (202) 708-
1464. For legal questions, contact Kenneth A. Markison, Assistant 
General Counsel for Government Sponsored Enterprises/RESPA, Office of 
the General Counsel, Room 9262, telephone (202) 708-3137. The address 
for all of these persons is: Department of Housing and Urban 
Development, 451 Seventh Street, SW, Washington, DC 20410.
    Persons with hearing and speech impairments may access the phone 
numbers via TTY by calling the Federal Information Relay Service at 
(800) 877-8399.

SUPPLEMENTARY INFORMATION:

I. General

A. Purpose

    Through this proposed rule, the Department of Housing and Urban 
Development (HUD or the Department) is soliciting comments on proposed 
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 2000 through 2003. The housing goals will be phased in 
beginning in calendar year 2000 and will be fully implemented by 
calendar year 2001. In accordance with the Federal Housing Enterprises 
Financial Safety and Soundness Act of 1992,\1\ which requires the GSEs 
to facilitate the financing of affordable housing for low-and moderate-
income families and underserved neighborhoods and requires the 
Department to establish housing goals; this rule proposes increased 
housing goal levels for the purchase by Fannie Mae and Freddie Mac of 
mortgages financing low- and moderate-income housing, special 
affordable housing, and housing in central cities, rural areas, and 
other underserved areas. This rule also proposes to clarify HUD's 
guidelines for counting different types of mortgage purchases toward 
those goals, and to provide greater public access to certain types of 
mortgage data on the GSEs' mortgage purchases in HUD's public use 
database. This rule also solicits public comments on several other 
issues related to the housing goals.
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    \1\ 12 U.S.C. 4501 et seq.; Pub. L. 102-550, approved Oct. 28, 
1992.
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    While Fannie Mae and Freddie Mac have been successful in providing 
stability and liquidity in the market for certain types of mortgages, 
their share of the affordable housing market is substantially smaller 
than their share of the total conventional conforming mortgage market. 
The GSEs' mortgage purchases accounted for 39 percent of all owner and 
rental housing units that were financed in the market during 1997, but 
their purchases that qualified for the Low- and Moderate-Income Housing 
Goal represented only 30 percent of the low- and moderate-income 
housing market and their Special Affordable Housing Goal (directed 
toward very low- and low-income families) qualifying mortgage purchases 
represented only 24 percent of that market. There are several reasons 
for these disparities, related both to the GSEs' purchase and 
underwriting guidelines and to their relatively low level of activity 
in specific markets that serve lower-income families, including small 
multifamily rental properties, manufactured housing, single family 
owner-occupied rental properties, and seasoned affordable housing 
mortgages. As the GSEs continue to grow their businesses, the proposed 
new goals will provide strong incentives for the two enterprises to 
more fully address the housing finance needs of very low-, low-and 
moderate-income families and the residents of underserved areas, and,

[[Page 12633]]

thus, more fully realize their public purposes.
    In determining the appropriate level of the housing goals, HUD must 
consider six statutory factors: national housing needs; economic, 
housing and demographic conditions; performance and effort of Fannie 
Mae and Freddie Mac toward achieving the housing goals in previous 
years; the size of the conventional mortgage market serving the 
targeted population or areas relative to the size of the overall 
conventional mortgage market; the ability of the GSEs to lead the 
industry in making mortgage credit available for the targeted 
population or areas; and the need to maintain the sound financial 
condition of the GSEs.
    Based on consideration of all the statutory factors, HUD is 
proposing increases to the housing goal levels. In summary, the shares 
of the mortgage markets that qualify for each of the housing goals are 
higher than the current goal levels. The proposed goal levels will 
close the gap between the GSEs' performance and the opportunities 
available in the primary mortgage market. The proposed goal levels, 
while consistent with the Department's estimate of the market share for 
each goal, are higher than the GSEs' current level of performance, yet 
they would be reasonable even under economic conditions more adverse 
than have existed recently. There are a number of relatively untapped 
segments of the multifamily, single family owner-occupied, and single 
family rental markets where the GSEs might play an enhanced role and 
thereby increase their shares of targeted loans and their performance 
on the housing goals. These areas include small multifamily mortgage 
loans, multifamily rehabilitation loans, single family rental property 
loans, manufactured housing loans, A-minus mortgage loans, and 
affordable seasoned loan purchases. The proposed goal levels will 
challenge both Fannie Mae and Freddie Mac to increase their purchases 
of mortgages for lower-income families and for properties in 
underserved areas, and to further their efforts to meet the affordable 
housing needs of lower-income families, minorities, and residents of 
underserved areas, who continue to face problems obtaining mortgage 
credit and who would benefit from a more active and focused secondary 
market. The Department's analyses indicate that there are substantial 
opportunities in the mortgage market where the GSEs may purchase 
additional mortgages that qualify for one or more of the housing goals. 
The GSEs have the financial and operational capacity to improve their 
affordable housing performance and lead the industry in supporting 
mortgage lending for families and neighborhoods targeted by the housing 
goals. Further, the GSEs themselves have indicated that they want to 
increase their market presence in many of the business areas identified 
above.
    The current housing goal levels are 42 percent for the Low- and 
Moderate-Income Housing Goal, 24 percent for the Geographically 
Targeted Goal, and 14 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 0.8 
percent of the dollar volume of mortgages purchased by the respective 
GSE in 1994--$1.29 billion annually for Fannie Mae and $988 million 
annually for Freddie Mac. The Department is proposing to increase the 
housing goal levels as follows: The proposed level of the Low- and 
Moderate-Income Housing Goal is 48 percent for calendar year 2000 and 
50 percent in calendar years 2001-2003; the proposed level of the 
Geographically Targeted Goal is 29 percent for calendar year 2000 and 
31 percent in calendar years 2001-2003; and the proposed level of the 
Special Affordable Housing Goal is 18 percent in calendar year 2000 and 
20 percent in calendar years 2001-2003. In addition, HUD is proposing 
to increase the special affordable multifamily subgoal to 0.9 percent 
of the dollar volume of total 1998 mortgage purchases in calendar year 
2000 and to 1.0 percent in calendar years 2001-2003.
    Further discussion of the statutory factors HUD is required to 
consider in setting the housing goals, and the rationale for HUD's 
establishment of these goals, are provided throughout the remainder of 
this preamble and in the Appendices to the Proposed Rule. In 
particular, because of the importance of the GSEs' ability to lead the 
industry in making mortgage credit available for targeted populations 
and areas, HUD is seeking comment on the following: Are the proposed 
housing goals appropriate given the statutory factors HUD must consider 
in setting the goals, and in light of the market estimates of the GSEs' 
shares of the affordable housing market? (See Section E.7, ``Closing 
the Gap Between the GSEs and The Market.'').

B. Background

    1. Fannie Mae and Freddie Mac. The GSEs engage in two principal 
businesses: investing in residential mortgages and guaranteeing 
securities backed by residential mortgages. Fannie Mae and Freddie Mac 
are Government Sponsored Enterprises, chartered by Congress in order 
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.\2\
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    \2\ See sec. 301 of the Federal National Mortgage Association 
Charter Act (Fannie Mae Charter Act) (12 U.S.C. 1716); sec. 301(b) 
of the Federal Home Loan Mortgage Corporation Act (Freddie Mac Act) 
(12 U.S.C. 1451 note).
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    Fannie Mae and Freddie Mac receive significant explicit benefits 
through their status as GSEs that are not enjoyed by any other 
shareholder-owned corporations in the mortgage market. These benefits 
include: (1) Conditional access to a $2.25 billion line of credit from 
the U.S. Treasury; \3\ (2) exemption from the securities registration 
requirements of the Securities and Exchange Commission and the States; 
\4\ and (3) exemption from all State and local taxes except property 
taxes.\5\
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    \3\ Secs. 306(c)(2) of the Freddie Mac Act and 304(c) of the 
Fannie Mae Charter Act.
    \4\ Secs. 306(g) of the Freddie Mac Act and 304(d) of the Fannie 
Mae Charter Act.
    \5\ Secs. 303(e) of the Freddie Mac Act and 309(c)(2) of the 
Fannie Mae Charter Act.
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    Additionally, although the securities the GSEs guarantee and the 
debt instruments they issue are not backed by the full faith and credit 
of the United States, and nothing in this proposed rule should be 
construed otherwise, the GSEs' securities trade at yields only a few 
basis points over those of U.S. Treasury securities and at yields lower 
than those received for securities issued by potentially higher-
capitalized, fully private, but otherwise comparable firms. The market 
prices for GSE debt and mortgage-backed securities, and the fact that 
the market does not require that those securities be rated by a 
national rating agency, suggest that investors perceive that the 
government implicitly backs the GSEs' debt and securities. This 
perception evidently arises from the GSEs' relationship to the Federal

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Government, including their public purposes, their Congressional 
charters, their potential direct access to U.S. Department of Treasury 
funds, and the statutory exemptions of their debt and mortgage-backed 
securities (MBS) from otherwise mandatory security laws. Consequently, 
each GSE's cost of doing business is significantly less than that of 
other firms in the mortgage market. According to the U.S. Department of 
Treasury, the benefits of federal sponsorship are worth almost $6 
billion annually to Fannie Mae and Freddie Mac. Of this amount, reduced 
operating costs (i.e., exemption from SEC filing fees and from state 
and local income taxes) represent approximately $500 million annually. 
These estimates are broadly consistent with the magnitudes estimated by 
the Congressional Budget Office and General Accounting Office. Fannie 
Mae and Freddie Mac appear to pass through part of these benefits to 
consumers through reduced mortgage costs and retain part for their own 
stockholders.\6\
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    \6\ U.S. Department of Treasury, Government Sponsorship of the 
Federal National Mortage Association and the Federal Home Loan 
Mortgage Corporation(1996), page 3.
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    2. Regulation of the GSEs--FHEFSSA. In 1968, Congress assigned HUD 
general regulatory authority over Fannie Mae \7\ and in 1989, Congress 
granted the Department essentially identical regulatory authority over 
Freddie Mac.\8\ Under the 1968 and 1989 legislation, HUD was authorized 
to require that a portion of Fannie Mae's mortgage purchases be related 
to the national goal of providing adequate housing for low-and 
moderate-income families. Accordingly, the Department established two 
housing goals--a goal for low-and moderate-income housing and a goal 
for housing located in central cities--by regulation, for Fannie Mae in 
1978.\9\ Each goal was established at the level of 30 percent of 
mortgage purchases. Similar housing goals for Freddie Mac were proposed 
by the Department in 1991 but were not finalized before October 1992, 
when Congress revised the Department's GSE regulatory authorities 
including requirements for new housing goals.
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    \7\ Section 802(ee) of the Housing and Urban Development Act of 
1968 (Pub. L. 90-448, approved August 1, 1968; 82 Stat. 476, 541).
    \8\ See sec. 731 of the Financial Institutions Reform, Recovery, 
and Enforcement Act of 1989 (FIRREA) (Pub. L. 101-73, approved 
August 9, 1989), which amended the Freddie Mac Act.
    \9\ See 24 CFR 81.16(d) and 81.17 (1992 codification).
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    In 1992, Congress enacted the Federal Housing Enterprises Financial 
Safety and Soundness Act (FHEFSSA),\10\ which revamped the statutory 
requirements and regulatory structure of the GSEs by separating the 
Government's financial regulation of the GSEs from its mission 
regulation. FHEFSSA created a new Office of Federal Housing Enterprise 
Oversight (OFHEO), within HUD, which was assigned new, independent, 
regulatory powers to ensure the GSEs' financial safety and 
soundness.\11\ At the same time, FHEFSSA affirmed the Secretary of 
Housing and Urban Development's responsibility for mission regulation 
and provided that, except for the specific authority of the Director of 
OFHEO relating to the safety and soundness of the GSEs, the Secretary 
retains general regulatory power over the GSEs.\12\ FHEFSSA also 
detailed and expanded the Department's specific powers and authorities, 
including the power to establish, monitor, and enforce housing goals 
for the GSEs' purchases of mortgages that finance housing for low-and 
moderate-income families, housing located in central cities, rural 
areas, and other underserved areas, and special affordable housing, 
affordable to very low-income families and low-income families in low-
income areas.\13\
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    \10\ Pub. L. 102-550; approved Oct. 28, 1992.
    \11\ Sec. 1311 of FHEFSSA; see also sec. 1313 of FHEFSSA. 
FHEFSSA charged OFHEO with designing and administering a stress test 
for capital adequacy and risk-based capital standards to ensure the 
financial safety and soundness of the GSEs. The proposed rule 
containing the risk-based capital requirements was published by 
OFHEO in the Federal Register (Vol. 64, No. 70) on April 13, 1999. 
Hereafter, unless otherwise specified, all section citations are 
citations to the Federal Housing Enterprises Financial Safety and 
Soundness Act of 1992.
    \12\ Sec. 1321.
    \13\ See generally secs. 1331-34.
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    FHEFSSA also required that the Department prohibit the GSEs from 
discriminating in their mortgage purchases and charged the Department 
with several fair lending authorities including the power to take 
remedial action against lenders found to have engaged in discriminatory 
lending practices and to periodically review and comment on the GSEs' 
underwriting and appraisal guidelines to ensure that such guidelines 
are consistent with the Fair Housing Act and the fair housing 
requirements in FHEFSSA.\14\
    FHEFSSA affirmed and detailed HUD's authority to review and approve 
new programs of the GSEs \15\ and to require reports from the GSEs \16\ 
including periodic data and information submissions.\17\ FHEFSSA also 
required that the Department establish a public use data base and 
implement requirements for the protection of proprietary information 
provided by the GSEs.\18\ FHEFSSA also contained detailed procedural 
requirements for the exercise of HUD's regulatory authorities.\19\
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    \14\ Sec. 1325(1)-(6).
    \15\ Sec. 1322.
    \16\ Sec 1327.
    \17\ See secs. 1381(o)-(p), 1382(r)-(s).
    \18\ Secs. 1323, 1326.
    \19\ Secs. 1322, 1336, and 1341-49.
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    FHEFSSA provided that performance under its income based housing 
goals--the low- and moderate-income and special affordable housing 
goals--would be counted based on the actual income of owners and 
renters. The earlier housing goal regulations governing Fannie Mae had 
counted performance under the then existing low- and moderate-income 
housing goal based on house prices and rent levels.\20\ The previous 
central cities goal counted Fannie Mae's mortgage purchases in areas 
designated by the Office of Management and Budget (OMB) as central 
cities. Following a two year transition, FHEFSSA expanded the central 
cities goal to include rural and other underserved areas (see 
discussion below). Under FHEFSSA, the Department is required to 
establish each of the goals after consideration of certain prescribed 
factors relevant to the particular goal.\21\
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    \20\ 24 CFR 81.2(1)(3) (1992 codification). Under the previous 
regulations, ``housing for low- and moderate-income families'' 
included ``any single family dwelling * * * purchased at a price not 
in excess of 2.5 times the median family income * * * for the 
Standard Metropolitan Statistical Area.''
    \21\ Secs. 1332(b), 1333(a)(2), 1334(b).
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    3. Transition Period. For a transition period of calendar years 
1993 and 1994, FHEFSSA established statutory targets for purchases by 
Fannie Mae and Freddie Mac of mortgages on housing for low- and 
moderate-income families and housing located in OMB-defined central 
cities; and mortgages on special affordable housing.\22\ FHEFSSA's 
targets for (a) low- and moderate-income mortgage purchases; and (b) 
central cities mortgage purchases were each established at the pre-
FHEFSSA goal level of at least 30 percent of the units financed by each 
GSEs' total mortgage purchases for those years.\23\ FHEFSSA's targets 
for the Special Affordable Housing Goal for the transition years,\24\ 
unlike the other targets, were set at no less than a minimum amount of 
mortgage purchases measured in dollars financed, rather than the 
percentage of units, with the Fannie Mae goal greater than the Freddie 
Mac goal. For the transition period, FHEFSSA also set subgoals under 
the Special Affordable

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Housing Goal for purchases of single family and multifamily mortgages.
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    \22\ Secs. 1332(d), 1333(d), and 1334(d).
    \23\ Secs. 1332(d)(1) and 1334(d)(1).
    \24\ Sec. 1333(d)(1) and (2).
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    FHEFSSA required HUD to establish interim goals for the transition 
period to improve the GSEs' performances relative to the statutory 
targets for low-and moderate-income and central cities mortgage 
purchases so that the GSEs would meet the targets by the end of the 
transition period.\25\ Following the transition, the Department would 
establish the goals under the statutory factors and FHEFSSA required 
the Department to establish a broader underserved areas goal inclusive 
of rural and other underserved areas as well as central cities to be 
defined by HUD.
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    \25\ Secs. 1332(d)(2)(A) and 1334(d)(2)(A).
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    On October 13, 1993, HUD published notices in the Federal Register 
establishing the interim goals and subgoals for the GSEs' mortgage 
purchases, and requirements for implementing those goals.\26\ For 
Fannie Mae, HUD set the interim goal for housing for low- and moderate-
income families at 30 percent of the units financed by mortgage 
purchases for 1993 and 1994; \27\ for housing located in central cities 
at 28 percent for 1993 and 30 percent for 1994;\28\ and for special 
affordable housing at $16.4 billion over the 1993-94 transition 
period.\29\ For Freddie Mac, HUD set the interim goal for housing for 
low- and moderate-income families at 28 percent of the units financed 
by mortgage purchases for 1993 and 30 percent for 1994; \30\ the 
interim goal for housing located in central cities at 26 percent for 
1993 and 30 percent for 1994; \31\ and for special affordable housing 
at $11.9 billion over the 1993-94 transition period.\32\ On November 
30, 1994,\33\ HUD extended the 1994 goals for both GSEs through 1995 
while the Department completed its development of post transition 
goals.
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    \26\ 58 FR 53048, 53072.
    \27\ 58 FR 53049.
    \28\ Id.
    \29\ HUD arrived at this amount of $16.4 billion by doubling 
Fannie Mae's good faith estimate of its mortgage purchases that 
would have qualified for the Special Affordable Housing Goal in 1992 
(i.e., $5.85 billion in single family mortgage purchases and $1.34 
billion in multifamily mortgage purchases), and adding the $2 
billion increment specified in section 1333(d)(1) of FHEFSSA. See 58 
FR 53049.
    \30\ 58 FR 53072.
    \31\ Id. at 53073.
    \32\ HUD arrived at this amount of $11.9 billion by doubling 
Freddie Mac's good faith estimate of its mortgage purchases that 
would have qualified for the Special Affordable Housing Goal in 1992 
(i.e., $5.19 billion in single family mortgage purchases and $0.02 
billion in multifamily mortgage purchases), and adding the $1.5 
billion increment specified in section 1333(d)(2) of FHEFSSA. See 58 
FR 53073.
    \33\ 59 FR 61504.
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    Both GSEs surpassed their goals for low- and moderate-income 
housing in 1993, 1994, and 1995. Neither GSE met its central cities 
goal in 1993; while Fannie Mae successfully met its central cities goal 
for 1994 and 1995, Freddie Mac never achieved its central cities goal 
during the transition period from 1993 through 1995. Both GSEs exceeded 
their respective special affordable housing goals and their respective 
single family subgoals. Fannie Mae also exceeded its multifamily 
subgoals for the transition period. Although Freddie Mac did not 
achieve the multifamily subgoal during the 1993 through 1994 period, 
Freddie Mac's multifamily purchases increased every year during the 
transition period such that Freddie Mac did achieve its multifamily 
subgoal in 1995.
    4. HUD's 1995 Rulemaking. The Department issued proposed and final 
rules in 1995 to establish and implement the housing goals for the 
years 1996 through 1999, and to implement the Department's other 
authorities in FHEFSSA.\34\ These regulations replaced HUD's previous 
regulations governing Fannie Mae, and for the first time established 
regulations governing Freddie Mac. HUD benefited from substantial 
comment during the rulemaking process from the public, the GSEs, and 
representatives of lenders, developers, nonprofit groups, public 
interest organizations, other Federal agencies and academic experts. 
Through the 1995 rulemaking, HUD established counting requirements for 
the goals, revised and streamlined the special affordable housing goal, 
and redefined the central cities goal to target those geographic areas 
of central cities, rural areas, and other areas that are underserved by 
mortgage credit, including those areas--metropolitan and non-
metropolitan--with low median incomes and/or high minority populations 
that typically experience the highest mortgage denial rates and the 
lowest mortgage origination rates. The new regulations also prohibit 
the GSEs from discriminating in their mortgage purchases, implement 
procedures by which HUD exercises its authority to review new programs 
of the GSEs, require reports from the GSEs, operate a public use data 
base on the GSEs' mortgage purchase activities while protecting 
confidential and proprietary information, and enforce HUD's authorities 
under FHEFSSA.
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    \34\ HUD issued the proposed rule on February 16, 1995 (60 FR 
9154) and the final rule on December 1, 1995 (60 FR 61846).
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    In setting the first, post-transitional period housing goals for 
the years 1996 through 1999, HUD sought to recognize the unique 
position the GSEs occupy in the nation's housing finance system and to 
ensure that, consistent with their Congressional mandates, the GSEs 
provide leadership in expanding housing opportunities and providing 
wider access to mortgage credit. In establishing each of the housing 
goals, HUD considered the factors presented in FHEFSSA, including 
national housing needs; economic, housing, and demographic conditions; 
the previous performance and effort of the GSEs in achieving the 
specific goal; the size of the primary mortgage market for that goal; 
the ability of the GSEs to lead the industry; and the need to maintain 
the sound financial condition of the GSEs.\35\ HUD established the 
goals under the factors, based on its estimates of the market share at 
that time, at levels that were reasonable and appropriate, reflecting a 
margin to compensate for the cyclical nature of mortgage markets and 
the unpredictability of other economic indicators, and allowing the 
GSEs flexibility in choosing how to achieve the goals.\36\ Recognizing 
the GSEs' and others concerns about need for predictability in order to 
manage their business operations, HUD established the levels of the 
goals for a four-year period. The rule provides that the housing goals 
for 1999 may continue beyond 1999 if the Department does not change the 
goals, and explained that HUD, under FHEFSSA may change the level of 
the goals for the years 2000 and beyond based upon HUD's experience and 
in accordance with HUD's statutory authority and responsibility.
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    \35\ Sec. 1332.
    \36\ 60 FR 61851.
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    In the 1995 rulemaking, HUD established the annual goals for each 
GSE's purchases of mortgages on housing for low-and moderate-income 
families as follows: for 1996, at 40 percent of the total number of 
dwelling units financed by each GSE's mortgage purchases; and for each 
of the years 1997 through 1999, at 42 percent of the total number of 
dwelling units financed by each GSE's mortgage purchases.\37\ HUD 
established the following annual goals for purchases of mortgages on 
housing located in central cities, rural areas, and other underserved 
areas: 21 percent of the total number of dwelling units financed by 
each GSE's mortgage purchases for 1996; and 24 percent of the total 
number of dwelling units financed by each GSE's mortgage purchases for 
each of the years 1997

[[Page 12636]]

through 1999.\38\ HUD established the annual goals for purchases of 
mortgages on special affordable housing as follows: for 1996, at 12 
percent of the total number of dwelling units financed by each GSE's 
mortgage purchases; and for each of the years 1997 through 1999, at 14 
percent of the total number of dwelling units financed by each GSE's 
mortgage purchases. The Special Affordable Housing Goal includes a 
subgoal for mortgage purchases financing dwelling units in multifamily 
housing set at 0.8 percent of the dollar volume of mortgages purchased 
by the respective GSE in 1994 \39\--$1.29 billion annually for Fannie 
Mae and $988 million annually for Freddie Mac. As described in more 
detail below, through 1998, the GSEs have met and in some cases 
exceeded the housing goals that HUD set for the 1996 to 1999 period.
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    \37\ 24 CFR 81.12.
    \38\ 24 CFR 81.13.
    \39\ 24 CFR 81.14.
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C. Secretary's Approach to Regulating the Enterprises

    As explained previously, the GSEs are Congressionally-chartered 
entities that enjoy substantial public benefits. Through these public 
benefits and successful corporate management strategies, the GSEs have 
continued to grow and to earn substantial profits for their 
shareholders.
    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. 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, and to promote access to 
mortgage credit throughout the nation, including central cities, rural 
areas, and other underserved areas. These requirements create an 
obligation for the GSEs to work to ensure that everyone throughout the 
country has a reasonable opportunity to enjoy access to the mortgage 
financing benefits resulting from the activities of these Federally-
sponsored entities.
    The GSEs have achieved an important part of their mission: 
providing stability and liquidity to large segments of the housing 
finance markets. As a result of the GSEs' activities, many home buyers 
have benefited from lower interest rates and increased access to 
capital, contributing, in part, to a record national homeownership rate 
of 66.3 percent in 1998. While the GSEs have been successful in 
providing stability and liquidity to certain portions of the mortgage 
market, the GSEs must further utilize their entrepreneurial talents and 
power in the marketplace and ``lead the mortgage finance industry'' to 
``ensure that citizens throughout the country enjoy access to the 
public benefits provided by these federally related entities.'' \40\
---------------------------------------------------------------------------

    \40\ S. Rep. No. 282, 102d Cong., 2d Sess. 34 (1992).
---------------------------------------------------------------------------

    Despite the record national homeownership rate in 1998, lower rates 
have prevailed for certain minorities, especially for African-American 
households (45.9 percent) and Hispanics (45.7 percent). These gaps are 
only partly explained by differences in income, age, and other 
socioeconomic factors. Disparities in mortgage lending are also 
reflected in loan denial rates of minority groups when compared to 
white applicants. Denial rates for conventional (non-government-backed) 
home purchase mortgage loans in 1997 were 53 percent for African 
Americans, 52 percent for Native American applicants, 38 percent for 
Hispanic applicants, 26 percent for White applicants, and 13 percent 
for Asian applicants.\41\ Despite strong economic growth, low 
unemployment, the lowest mortgage rates in more than 30 years, and 
relatively stable home prices, housing problems continue to persist for 
low-income families and certain minorities.
---------------------------------------------------------------------------

    \41\ FFIEC Press Release, August 6, 1998
---------------------------------------------------------------------------

    Certain segments of the population have not benefited to the same 
degree as have others from the advantages and efficiencies provided by 
Fannie Mae and Freddie Mac. The GSEs have been much less active in 
markets where there is a need for additional financing sources to 
address persistent housing needs including small multifamily rental 
properties, manufactured housing, single family owner-occupied rental 
properties, seasoned affordable housing mortgages, and older housing in 
need of rehabilitation.
    While HUD recognizes that the GSEs have played a significant role 
in the mortgage finance industry by providing a secondary market and 
liquidity for mortgage financing for certain segments of the mortgage 
market, it is this recognition of their ability, along with HUD's 
comprehensive analyses of the size of the mortgage market and the 
opportunities available, America's unmet housing needs, identified 
credit gaps, and its consideration of all the statutory factors that 
causes HUD to propose increased goals so that as the GSEs grow their 
businesses they will address new markets and persistent housing finance 
needs.

D. Statutory Considerations in Setting the Level of the Housing Goals

    In establishing the housing goals, FHEFSSA requires the Department 
to consider six factors--national housing needs; economic, housing and 
demographic conditions; performance and effort of the GSEs toward 
achieving the goal in previous years; size of the conventional mortgage 
market serving the targeted population or areas, relative to the size 
of the overall conventional mortgage market; ability of the GSEs to 
lead the industry in making mortgage credit available for the targeted 
population or areas; and the need to maintain the sound financial 
condition of the GSEs. These factors are discussed in more detail in 
the following sections of this preamble and in the Appendices to this 
proposed rule. A summary of HUD's findings relative to each factor 
follows:
    1. National Housing Needs. Analysis and research by HUD and others 
in the housing industry indicate that there are, and will continue to 
be in the foreseeable future, substantial housing needs among lower-
income and minority families. Data from the 1990 Census and the 
American Housing Surveys demonstrate that there are substantial unmet 
housing needs among lower-income families. Many households are burdened 
by high homeownership costs or rent payments and will likely continue 
to face serious housing problems, given the dim prospects for earnings 
growth in entry-level occupations. According to HUD's ``Worst Case 
Housing Needs'' report, 21 percent of owner households faced a moderate 
or severe cost burden in 1995. Affordability problems were even more 
common among renters, with 40 percent paying more than 30 percent of 
their income for rent in 1995.\42\
---------------------------------------------------------------------------

    \42\ Rental Housing Assistance--The Crisis Continues: The 1997 
Report to Congress on Worst Case Housing Needs, Department of 
Housing and Urban Development, Office of Policy Development and 
Research, (April 1998).
---------------------------------------------------------------------------

    Despite the growth during the 1990s in affordable housing lending, 
disparities in the mortgage market remain, with certain minorities, 
particularly African-American and Hispanic families, lagging the 
overall market in rate of homeownership. In addition, there is evidence 
that the aging stocks of single family rental properties and small 
multifamily properties with 5-50 units, which play a key role in lower-
income housing, have been affected by difficulties in obtaining credit. 
The ability of the

[[Page 12637]]

nation to maintain the quality and availability of the existing 
affordable housing stock and to stabilize neighborhoods depends on an 
adequate supply of affordable credit to rehabilitate and repair older 
units.
    a. Single Family Mortgage Market. Many younger, minority, and 
lower-income families did not become homeowners during the 1980s due to 
the slow growth of earnings, high real interest rates, and continued 
house price increases. Over the past six years, economic expansion, 
accompanied by low interest rates and increased outreach on the part of 
the mortgage industry, has improved affordability conditions for lower-
income families. Between 1994 and 1998, record numbers of lower-income 
and minority families purchased homes. First time homeowners have 
become a major driving force in the home purchase market over the past 
five years. Thus, the 1990s have seen the development of a strong 
affordable lending market. However, despite the growth of lending to 
minorities, disparities in the mortgage market remain. For example, 
African-American applicants are still twice as likely to be denied a 
loan as white applicants, even after controlling for income.
    b. Multifamily Mortgage Market. Since the early 1990s, the 
multifamily mortgage market has become more closely integrated with 
global capital markets, although not to the same degree as the single 
family mortgage market. Loans on multifamily properties are still 
viewed as riskier by some than mortgages on single family properties. 
Property values, vacancy rates, and market rents in multifamily 
properties appear to be highly correlated with local job market 
conditions, creating greater sensitivity of loan performance to 
economic conditions than may be experienced for single family 
mortgages.
    Recent volatility in the market for Commercial Mortgage Backed 
Securities (CMBS), an important source of financing for multifamily 
properties, underlines the need for an ongoing GSE presence in the 
multifamily secondary market. The potential for an increased GSE 
presence is enhanced by the fact that an increasing proportion of 
multifamily mortgages are now originated in accordance with secondary 
market standards.
    The GSEs can play a role in promoting liquidity for multifamily 
mortgages and increasing the availability of long-term, fixed rate 
financing for these properties. Increased GSE presence would provide 
greater liquidity to lenders, i.e., a viable ``exit strategy,'' that in 
turn would serve to increase their lending. It appears that financing 
of small multifamily rental properties with 5-50 units, where a 
substantial portion of the nation's affordable housing stock is 
concentrated, have been adversely affected by excessive borrowing 
costs. Multifamily properties with significant rehabilitation needs 
also appear to have experienced difficulty gaining access to mortgage 
financing. Moreover, the flow of capital into multifamily housing for 
seniors has been historically characterized by a great deal of 
volatility.
    2. Economic, Housing, and Demographic Conditions. Studies indicate 
that changing population demographics will result in a need for the 
mortgage market to meet nontraditional credit needs and to respond to 
diverse housing preferences. The U.S. population is expected to grow by 
an average of 2.4 million per year over the next 20 years, resulting in 
1.1 to 1.2 million new households per year. In particular, the 
continued influx of immigrants will increase the demand for rental 
housing while those who immigrated during the 1980s will be in the 
market to purchase owner-occupied housing. The aging of the baby-boom 
generation and the entry of the smaller baby-bust generation into prime 
home buying age is expected, however, to have a dampening effect on 
housing demand. Non-traditional households have, and will, become more 
important, as overall household formation rates slow down. With later 
marriages, divorce, and non-traditional living arrangements, the 
fastest growing household groups have been single-parent and single-
person households. With continued house price appreciation and 
favorable mortgage terms, ``trade-up buyers'' will also increase their 
role in the housing market. There will also be increased credit needs 
from new and expanding market sectors, such as manufactured housing and 
housing for senior citizens. These demographic trends will lead to 
greater diversity in the homebuying market, which, in turn, will 
require greater adaptation by the primary and secondary mortgage 
markets.
    As a result of the above demographic forces, housing starts are 
expected to average 1.5 million units between 1999 and 2003, 
essentially the same as in 1996-98.\43\ Refinancing of existing 
mortgages, which accounted for 50 percent of originations in 1998, has 
continued to play a major role in 1999, but is expected to return to 
more normal levels during 2000. Thus, the mortgage market remained 
strong with over one trillion dollars in expected originations in 1999, 
and a somewhat lower number of originations are expected in 2000.
---------------------------------------------------------------------------

    \43\ Standard & Poor's DRI Review of the U.S. Economy. 
(September 1999), p. 53-55.
---------------------------------------------------------------------------

    3. Performance and Effort of the GSEs Toward Achieving the Goal in 
Previous Years. Both Fannie Mae and Freddie Mac have improved their 
affordable housing loan performance over the past five years. However, 
the GSEs' mortgage purchases continue to lag the overall market in 
providing financing for affordable housing to underserved borrowers and 
their neighborhoods, indicating that there is more that the GSEs can do 
to improve their performance. In addition, a large percentage of the 
lower-income loans purchased by the GSEs have relatively high down 
payments, which raises questions about whether the GSEs are adequately 
meeting the needs of those lower-income families which have little cash 
for making large down payments but can fully meet their monthly 
obligations. The discussion of the performance and effort of the GSEs 
toward achieving the housing goals in previous years is specific to 
each of the three housing goals. This topic is discussed further in 
Section II., B., ``Subpart B--Housing Goals'' below and in the 
Appendices to this proposed rule.
    4. Size of the Conventional Mortgage Market Serving the Targeted 
Population or Areas, Relative to the Size of the Overall Conventional 
Mortgage Market. The Department's analyses indicate that the size of 
the conventional conforming market relative to each housing goal is 
greater than earlier estimates based mainly on HMDA data for 1992 
through 1994 used in establishing the 1995-1999 housing goals. Due to 
inherent uncertainty about future market conditions, HUD has developed 
a plausible range under each goal, rather than a point estimate, for 
the current market. The discussion of the size of the conventional 
mortgage market serving targeted populations or areas relative to the 
size of the overall conventional mortgage market is specific to each of 
the three housing goals. The Department's estimate of the size of the 
conventional mortgage market is discussed further below in Section I, 
``Setting the Level of the Housing Goals,'' Section II., B., ``Subpart 
B--Housing Goals'' and in the Appendices to this proposed rule.
    5. Ability of the GSEs to Lead the Industry in Making Mortgage 
Credit Available for the Targeted Population or Areas. Research 
concludes that the GSEs have generally not been leading the market, but 
have lagged behind the primary market in financing housing for

[[Page 12638]]

lower-income families and their communities. However, the GSEs' state-
of-the-art technology, staff resources, share of the total conventional 
conforming market, and their financial strength suggest that the GSEs 
have the ability to lead the industry in making mortgage credit 
available for lower-income families and underserved neighborhoods.
    The legislative history of FHEFSSA indicates Congress's strong 
concern that the GSEs need to do more to benefit low- and moderate-
income families and the residents of underserved areas that lack access 
to credit.\44\ 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.'' \45\ FHEFSSA, 
therefore, specifically required that HUD consider the ability of the 
GSEs to lead the industry in establishing the level of the housing 
goals. FHEFSSA also clarified the GSEs' responsibility to complement 
the requirements of the Community Reinvestment Act \46\ and fair 
lending laws \47\ in order to expand access to capital to those 
historically underserved by the housing finance market.
---------------------------------------------------------------------------

    \44\ See, e.g., S. Rep. at 34.
    \45\ S. Rep. at 34.
    \46\ 12 U.S.C. 2901 et seq.
    \47\ See section 1335(3)(B).
---------------------------------------------------------------------------

    During the 1995 rulemaking, HUD received comments regarding what it 
means for the GSEs to ``lead the industry.'' The GSEs themselves and 
others pointed out that the GSEs are often ``leaders'' through their 
introduction of innovative products, technology, and processes. For 
example, both GSEs have introduced technological advances through their 
development of automated underwriting systems. Fannie Mae has also 
developed state-of-the-art mapping software for use by lenders, 
nonprofit organizations, and State and local governments to help 
implement community lending programs. In addition, Fannie Mae has 
established partnership offices in more than 30 cities, allowing it to 
reach out to local lenders and affordable housing groups regarding 
Fannie Mae's programs. While Freddie Mac has not established 
partnership offices, it has established alliances at the national and 
local level to expand affordable housing opportunities. Nonetheless, 
while the GSEs are ``leaders'' in these areas, leadership also involves 
increasing the availability of financing for homeownership and 
affordable rental housing. Thus, the GSEs' obligation to ``lead the 
industry'' also entails leadership in facilitating access to affordable 
credit in the primary market for borrowers at different income levels 
and housing needs, as well as for underserved urban and rural areas.
    While the GSEs cannot be expected to solve all of the nation's 
housing problems, the efforts of Fannie Mae and Freddie Mac have not 
matched the opportunities that are available in the primary mortgage 
market. Although the GSEs were directed by Congress to ``lead the 
mortgage finance industry in making mortgage credit available for low- 
and moderate-income families,'' depository institutions have been more 
successful than the GSEs in providing affordable loans to lower income 
borrowers and in historically underserved neighborhoods.
    For example, very low-income borrowers accounted for 9.9 percent of 
Freddie Mac's purchases of home loans in 1998, 11.4 percent of Fannie 
Mae's purchases, 15.2 percent of home loans originated and retained by 
depository institutions, and 13.3 percent of home purchase mortgages 
originated in the overall conventional conforming market. Similarly, 
mortgage purchases on properties located in underserved areas accounted 
for 20.0 percent and 23.5 percent of Freddie Mac's and Fannie Mae's 
purchases of home loans, respectively, 26.1 percent of home purchase 
mortgages originated and retained by depository institutions and 24.6 
percent of home purchase mortgages originated in the overall 
conventional conforming market. Since 1992, Fannie Mae has improved its 
affordable lending performance and has made progress toward closing the 
gap between its performance and that of the overall mortgage market. 
Freddie Mac has shown less improvement and, as a result, has not made 
as much progress in closing the gap between its performance and that of 
the overall market for home loans.
    The GSEs have been much less active in providing financing for the 
multifamily rental housing market. In 1997, Fannie Mae's multifamily 
purchases amounted to $6.9 billion and Freddie Mac's, $2.7 billion, for 
total multifamily purchases of $9.6 billion. The GSEs' purchases have 
accounted for approximately 22 percent of the multifamily dwelling 
units that were financed in 1997. By way of comparison, HUD estimates 
that 4.9 million units were financed by mortgages on single family 
owner-occupied properties in 1997, and the GSEs have financed 2.4 
million, or 49 percent of these units. Thus, the GSEs' presence in the 
multifamily mortgage market was less than one-half of their presence in 
the market for mortgages on single family owner-occupied properties.
    In addition, the GSEs continue to lag the overall conforming, 
conventional market in providing affordable home purchase loans to 
underserved neighborhoods. During 1998, mortgages financing housing in 
underserved census tracts (as defined by HUD) \48\ accounted for 20.0 
percent of Freddie Mac's single family mortgage purchases, compared 
with 22.9 percent of Fannie Mae's single family mortgage purchases, 
26.1 percent of mortgage loans originated and held in portfolio by 
depository institutions, and 24.6 percent of the overall conforming 
conventional mortgage market. Fannie Mae has improved its performance 
in underserved areas to almost reach market levels. However, Freddie 
Mac has made much less progress through 1998 in serving families living 
in underserved neighborhoods.
---------------------------------------------------------------------------

    \48\ 24 CFR 81.2(b).
---------------------------------------------------------------------------

    Additionally, a large percentage of the lower-income loans 
purchased by both GSEs have relatively high down payments, which raises 
questions about whether the GSEs are adequately meeting the needs of 
lower-income families, who find it difficult to raise enough cash for a 
large down payment. Also, while single family rental properties are an 
important source of low- and moderate-income rental housing, they 
represent only a small portion of the GSEs' business.
    The Appendices to this proposed rule provide more information on 
HUD's analysis of the extent to which the GSEs have not led the 
mortgage industry in funding loans to underserved borrowers and 
neighborhoods. From this analysis of the GSEs' performance in 
comparison with the primary mortgage market and with other participants 
in the mortgage markets, it is clear that the GSEs need to improve 
their performance relative to the primary market of conforming 
conventional mortgage lending. The need for improvements in the GSEs' 
performance is especially apparent with respect to the single family 
and multifamily rental markets.
    6. Need to Maintain the Sound Financial Condition of the GSEs. 
Based on HUD's economic analysis and discussions with the Office of 
Federal Housing Enterprise Oversight, HUD concludes that the proposed 
level of the goals will not adversely affect the sound financial 
condition of the GSEs.

E. Setting the Level of the Housing Goals

    There are several reasons the Department, having considered all the

[[Page 12639]]

statutory factors, is proposing increases in the housing goals.
    1. Market Needs and Opportunities. First, the GSEs appear to have 
substantial room for growth in serving the affordable housing mortgage 
market. For example, the Department calculated that the two GSEs' 
mortgage purchases accounted for 39 percent of the total conventional 
mortgage market during 1997 (as measured by the total number of units 
financed by the GSEs). In contrast, GSE purchases comprised only 30 
percent of the low- and moderate-income mortgage market in 1997, 33 
percent of the underserved areas market, and, a still smaller, 24 
percent of the special affordable market.
    The GSEs' role in the mortgage market varies somewhat from year to 
year in response to changes in interest rates, mortgage product types, 
and a variety of other factors. But underlying market trends show a 
clear and significant increase in the GSEs' role. Specifically, OFHEO 
estimates that the share (in dollars) of single-family mortgages 
outstanding accounted for by mortgage-backed securities issued by the 
GSEs and by mortgages held in the GSEs' portfolios has risen from 31 
percent in 1990 to 37 percent in 1992, 40 percent in 1994, 43 percent 
in 1996, and 45 percent in 1998. In absolute terms, the GSEs' presence 
has grown even more sharply, as the total volume of single-family 
mortgage debt outstanding has increased rapidly over this period.
    The GSEs have indicated that they expect their role in the mortgage 
market to continue to increase in the future, as they develop new 
products, refine existing products, and enter markets where they have 
not played a major role in the past. The Department's goals for the 
GSEs also anticipate that their involvement in the mortgage market will 
continue to increase.
    The Department estimates that 7.4 million owner-occupied and rental 
units were financed by conventional conforming mortgages in 1997, and 
that the GSEs provided financing for 39 percent, or 2.9 million, of 
these units. However, the GSEs' mortgage market presence varies 
significantly by property type--while they accounted for about 49 
percent of the owner-occupied units financed in the primary market in 
that year, their role was much less in the mortgage market for 
mortgages on rental properties.
    Specifically, HUD estimates that Fannie Mae and Freddie Mac 
accounted for only about 19 percent of rental units financed in 1997. 
And within the rental category, the GSEs have yet to play a major role 
in financing mortgages for single family rental properties--those with 
at least one rental unit and no more than four units in total.
    For the types of units covered by HUD's goals, the GSEs' role is 
significantly less than their overall market presence of 39 percent. 
Specifically, HUD estimates that Fannie Mae and Freddie Mac financed 33 
percent of the units that qualified for the Geographically Targeted 
Goal. The GSEs' role was even lower for HUD's other two goals--they 
financed just 31 percent of units qualifying for the Low- and Moderate-
Income Housing Goal, and only 24 percent of special affordable units, 
for very low-income families and low-income families in low-income 
areas.
    There are a number of relatively untapped segments of the 
multifamily, single-family owner, and single-family rental markets 
where the GSEs might play an enhanced role and thereby increase their 
shares of targeted loans and their performance on the housing goals. 
Six such areas are discussed below.
    a. Small Multifamily Properties. One sector of the multifamily 
mortgage market where the GSEs could play an enhanced role involves 
loans on small multifamily properties--those containing 5-50 units. The 
GSEs typically purchase relatively few of these loans, which account 
for 37 percent of the stock of all multifamily units in mortgaged 
properties, according to the 1991 Survey of Residential Finance.
    HUD estimates that the GSEs acquired loans financing only four 
percent of units in small multifamily properties originated during 1995 
through 1997. This is substantially less than the GSEs' presence in the 
overall multifamily mortgage market, which the Department estimates was 
22 percent in 1997.
    Increased purchases of small multifamily mortgages would make a 
significant contribution to performance on the goals, since the 
percentages of these units qualifying for the income-based housing 
goals are high--in 1998, 94 percent of units backing both GSEs' 
combined multifamily mortgage purchases qualified for the Low- and 
Moderate-Income Housing Goal and about 55 percent of units backing 
Freddie Mac's multifamily mortgage purchases met the Special Affordable 
Housing Goal.\49\
---------------------------------------------------------------------------

    \49\ Fannie Mae did not obtain some of the data necessary to 
qualify many of their multifamily loans for the Special Affordable 
Housing Goal.
---------------------------------------------------------------------------

    b. Multifamily Rehabilitation Loans. Another multifamily market 
segment holding potential for expanded GSE presence involves properties 
with significant rehabilitation needs.
    Properties that are more than 10 years old are typically classified 
as ``C'' or ``D'' properties, and are considered less attractive than 
newer properties by many lenders and investors. Fannie Mae's 
underwriting guidelines for negotiated transactions state that ``the 
Lender is required to use a more conservative underwriting approach'' 
for transactions involving properties 10 or more years old. Fannie Mae 
funding for rehabilitation projects is generally limited to $6,000 per 
unit. Multifamily rehabilitation loans accounted for only 0.5 percent 
of units backing Fannie Mae's 1998 purchases. Freddie Mac's purchases 
of multifamily rehabilitation loans in 1998 were 1.9 percent of its 
multifamily total.
    c. Single Family Rental Properties. Studies show that single family 
rental properties are a major source of affordable housing for lower-
income families. Yet, these properties are only a small portion of the 
GSEs' overall business.
    HUD estimates that approximately 127,000 mortgages were originated 
on owner-occupied single-family rental properties in 1997. These 
mortgages financed a total of 286,000 units--the owner units plus an 
additional 159,000 rental units. Data submitted to HUD by the GSEs 
indicates that the GSEs combined to finance 94,000 such units, only 33 
percent of the units financed in the primary market.
    There is ample room for an enhanced GSE role in this ``goal-rich'' 
market. For the GSEs combined, 64 percent of the units in these 
properties qualified for the low-mod goal in 1997, 33 percent qualified 
for the special affordable goal, and 56 percent qualified for the 
underserved areas goal. Thus significant gains could be made in 
performance on all of their goals if Fannie Mae and Freddie Mac played 
a larger role in the market for mortgages on single-family 2-4 unit 
owner-occupied properties.
    d. Manufactured Homes. The Manufactured Housing Institute, in its 
Annual Survey of Manufactured Home Financing, reported that 116 
reporting institutions originated $15.6 billion in consumer loans on 
manufactured homes in 1998, and that, with an average loan amount of 
about $30,000, approximately 520,000 loans were originated.
    While the GSEs have traditionally played a minimal role in 
financing manufactured housing, they have recently stepped up their 
activity. But, even with this stepped-up activity in this market, the 
GSEs' purchases probably accounted for less than 15 percent of total 
loans on manufactured

[[Page 12640]]

homes in 1998--a figure well below their overall market presence of 39 
percent.
    There is ample room for an enhanced GSE role in this market, with 
its high concentration of goals-qualifying mortgage loans. For loans 
reported in 1998 in accordance with HMDA by 21 manufactured housing 
lenders, 76 percent qualified for the low-mod goal in 1998, 42 percent 
qualified for the special affordable goal, and 47 percent qualified for 
the underserved areas goal. Thus manufactured housing has significantly 
higher shares of goal-qualifying loans than all single-family owner-
occupied properties, though they are not quite as ``goal-rich'' as 
loans on multifamily properties. In general, though, goal performance 
could be enhanced substantially if the GSEs were to play an increased 
role in the manufactured housing mortgage market.
    e. A-Minus Loans. Industry sources estimate that subprime mortgage 
originations amounted to about $125 billion in 1997, and that these 
loans are divided evenly between the more creditworthy (``A-minus'') 
subprime borrowers and less creditworthy (``B,'' ``C,'' and ``D'') 
borrowers. Based on HMDA data for 200 subprime lenders, the Department 
estimates that 58 percent of the units financed by subprime loans 
qualified for the low-mod goal in 1997, 29 percent qualified for the 
special affordable goal, and 45 percent qualified for the underserved 
areas goal.
    Freddie Mac has begun to purchase loans originated in the A-minus 
mortgage market, as long as the loans are processed through its Loan 
Prospector system. Freddie Mac has estimated that 10-30 percent of 
subprime borrowers would qualify for a prime conventional loan. Freddie 
Mac has also purchased subprime loans through structured transactions 
that limit Freddie Mac's risk to the ``A'' piece of a senior-
subordinated transaction. Fannie Mae recently introduced a program 
aimed at borrowers with past credit problems that would lower the 
interest rates for those borrowers that were timely on their mortgage 
payments.
    However, there is ample room for further enhancement of both GSEs' 
roles in the A-minus market. A larger role by the GSEs could help 
standardize mortgage terms in this market, which would lead to lower 
interest rates.
    f. Seasoned Mortgages. Over the past five years, depository 
institutions (banks and thrifts) have been expanding their affordable 
loan programs and, as a result, have originated substantial numbers of 
loans to low-income and minority borrowers and their neighborhoods. 
Much of this outreach to underserved communities is due to the 
Community Reinvestment Act (CRA), which requires depository 
institutions to help meet the credit needs of their communities. A 
large number of the ``CRA-type'' loans that have recently originated 
remain in thrift and bank portfolios; selling these loans on the 
secondary market would free up capital for depositories to originate 
new CRA loans. Given its enormous size, the CRA market segment provides 
an opportunity for Fannie Mae and Freddie Mac to expand their 
affordable lending programs. While some of these loans, when 
originated, may not have met the GSE's underwriting guidelines, it 
appears they are beginning to be purchased by GSEs after the loans have 
seasoning and through various structured transactions. As explained in 
Appendix A, Fannie Mae is beginning to purchase these seasoned loans, 
which has improved its performance on the housing goals. Freddie Mac, 
on the other hand, has not been as active as Fannie Mae in purchasing 
seasoned ``CRA-type'' loans. With billions of dollars worth of CRA 
loans in bank portfolios, the early experience of Fannie Mae suggests 
that this could not only be an important strategy for reaching the 
housing goals but could also provide needed liquidity for a market that 
is serving the needs of low-income and minority homeowners.
    2. Market Share Higher Than Goal Levels. The shares of the mortgage 
markets that qualify for each of the housing goals are higher than the 
current goals. Specifically, the current Low-and Moderate-Income 
Housing Goal for 1997 through 1999 is 42 percent, but the market share 
for low-and moderate-income mortgages is estimated at 50-55 percent. 
The Geographically Targeted Goal for 1997 through 1999 is 24 percent, 
but the estimated market share of geographically targeted mortgages is 
29-32 percent. The Special Affordable Housing Goal for 1997 through 
1999 is 14 percent, but the estimated special affordable market share 
is 23-26 percent.\50\ Thus, the proposed increases in the housing 
goals, described below, will significantly reduce the disparities that 
currently exist between the housing goals and HUD's market estimates. 
HUD's analysis indicates that the proposed goals are reasonable and 
feasible under more adverse economic environments than have recently 
existed. Reasons for the remaining disparity between the proposed GSE 
housing goals and the respective shares of the overall mortgage market 
qualifying for each of the housing goals are discussed below in Section 
E.7, ``Closing The Gap Between the GSEs and The Market.''
---------------------------------------------------------------------------

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

    3. Need for Increased Affordable Single Family Mortgage Purchases. 
Higher housing goals are needed to assure that both Fannie Mae and 
Freddie Mac increase their purchases of single family mortgages for 
lower-income families. The GSEs lag behind depository institutions and 
other lenders in the conventional conforming market in providing 
mortgage funds for these underserved families and their neighborhoods. 
Numerous studies have concluded that Fannie Mae and, especially, 
Freddie Mac have room to increase their purchases of affordable loans 
originated by primary lenders. The single family affordable market, 
which had only begun to grow when HUD set housing goals in 1995, has 
now established itself with six straight years (1993-1998) of solid 
performance. Current economic forecasts suggest that the strong housing 
affordability of the past several years will be maintained in the post-
1999 period, leading to additional opportunities for the GSEs to 
support mortgage lending benefiting families targeted by the housing 
goals. But, as explained in Appendix D, HUD's housing market estimates 
allow for more adverse economic conditions than have existed recently.
    4. Market Disparities. Despite the recent growth in affordable 
lending, there are many groups who continue to face problems obtaining 
mortgage credit and who would benefit from a more active and targeted 
secondary market. Homeownership rates for lower-income families, 
certain minorities, and central city residents are substantially below 
those of other families, and the disparities cannot simply be 
attributed to differences in income. Immigrants represent a ready 
supply of potential first-time home buyers and will need access to 
mortgage credit. Special needs in the market, such as rehabilitation of 
older 2-4 unit properties, could be helped by new mortgage products and 
more flexibility in underwriting and appraisal guidelines. The GSEs, 
along with primary lenders and private mortgage insurers, have been 
making efforts to reach out to these underserved portions of the 
markets. However, more needs to be done, and the proposed increases in 
the housing goals are

[[Page 12641]]

intended to encourage additional efforts by Fannie Mae and Freddie Mac.
    5. Impact of Multifamily Mortgage Purchases. When the 1996-99 goals 
were established in December 1995, Freddie Mac had only recently 
reentered the multifamily mortgage market, after an absence in the 
early 1990s. Freddie Mac has made progress in rebuilding its 
multifamily mortgage purchase program, with its purchases of these 
loans rising from $191 million in 1993 to $6.6 billion in 1998. Freddie 
Mac's limited role in the multifamily market was a significant 
constraint when HUD set the level of the housing goals for 1996 through 
1999. While Freddie Mac has made progress by establishing a solid 
foundation of multifamily mortgage purchases, they still lag the market 
in this area. Accordingly, the Department is proposing to provide 
Freddie Mac with a temporary adjustment factor for purchases of 
mortgages in multifamily properties with more than 50 units, as 
discussed in more detail, below.
    6. Financial Capacity to Support Affordable Housing Lending. A wide 
variety of quantitative and qualitative indicators demonstrate that the 
GSEs' have ample, indeed robust, financial strength to improve their 
affordable lending performance. For example, the combined net income of 
the GSEs has risen steadily over the last decade, from $677 million in 
1987 to $5.1 billion in 1998, an average annual growth rate of 20 
percent per year. 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.
    7. Closing the Gap Between the GSEs and the Market. This section 
discusses the relationship between the housing goals, HUD's market 
estimates, and key segments of the affordable market in which the GSEs 
have had only a weak presence. To lay the groundwork for this 
discussion, the following table summarizes the Department's findings 
regarding market estimates and GSE performance as well as the levels of 
the housing goals during 1997-1999 and the goals proposed here:
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    It is evident from this table that the proposed Low- and Moderate-
Income and Special Affordable Housing Goals are below HUD's projected 
market estimate for the years (2000-2003) covered by the proposed 
housing goals. One reason for this disparity involves disaggregating 
GSE purchases by property type, which shows that the GSEs have little 
presence in some important segments of the affordable housing market. 
For example, as shown in Figure 1, in 1997 the GSEs purchased loans 
representing only 13 percent of units in single-family rental 
properties, and only 2 percent of units in small multifamily properties 
mortgaged that year. (Figure 2 provides additional detail providing 
unit data comparing the GSEs' with the conventional conforming market). 
Typically, more than 90 percent of units in single-family rental and 
small multifamily properties qualify for the Low- and Moderate-Income 
Housing Goal. Thus, one reason why the GSEs' performance on the Low- 
and Moderate-Income Housing Goal falls short of HUD's market estimate, 
is that the GSEs have had only a weak and inconsistent presence in 
financing these important sources of affordable housing, but these 
market segments are important components in the market estimate.

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    The same disparities are seen in figures relating to GSE purchase 
shares and market shares in the relevant market segments, as utilized 
by HUD in preparing its market estimates for the Low- and Moderate-
Income Housing Goal. In the overall conventional mortgage market, units 
in single-family rental properties and small multifamily properties are 
expected to represent approximately 19 percent of the overall mortgage 
market, and 31 percent of units backing mortgages qualifying for the 
Low- and Moderate-Income Housing Goal. Yet in 1997, units in such 
properties accounted for 5.5 percent of the GSEs' overall purchases, 
and only 10.5 percent of GSE purchases meeting the Low- and Moderate-
Income Housing Goal. The continuing weakness in GSE purchases of 
mortgages on single-family rental and small multifamily properties is a 
major factor explaining the shortfall between GSE performance and that 
of the primary mortgage market.
    For a variety of reasons, the GSEs have historically viewed the 
single-family rental and small multifamily market segments as more 
difficult for them to penetrate than the single-family owner-occupied 
mortgage market. In order to provide the GSEs with an incentive to 
enter these markets and provide the benefits of more consistent 
exposure to secondary markets, HUD is proposing to award ``bonus 
points'' for their purchases of mortgages on owner-occupied single-
family rental properties and small multifamily properties in 
calculating credit toward the housing goals, as discussed below. The 
bonus points will make the Department's proposed housing goals easier 
for the GSEs to attain if they devote resources to affordable market 
segments where their past role has been limited. Further, awarding 
bonus points for these units would have resulted in some increases in 
the GSEs' performance for the three goals over the 1996-98 period. (See 
Subpart B, 5a.).
    Because of the importance of the GSEs' ability to lead the industry 
in making mortgage credit available for targeted populations and areas, 
HUD wishes to solicit comments on the following:
    Are the proposed housing goals appropriate given the statutory 
factors HUD must consider in setting the goals, and in light of the 
market estimates of the GSEs' share of the affordable housing market?

F. Principles Governing Regulation of the GSEs

    In proposing these regulations, the Department was guided by and 
affirmed the following principles established in the 1995 rulemaking:
    1. To fulfill the intent of FHEFSSA, the GSEs should lead the 
industry in ensuring that access to mortgage credit is made available 
for very low-, low- and moderate-income families and residents of 
underserved areas. HUD recognizes that, to lead the mortgage industry 
over time, the GSEs will have to stretch to reach certain goals and 
close the gap between the secondary mortgage market and the primary 
mortgage market. This approach is consistent with Congress' recognition 
that ``the enterprises will need to stretch their efforts to achieve'' 
the goals.\51\
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    \51\ See footnote 40.
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    2. The Department's role as a regulator is to set broad performance 
standards for the GSEs through the housing goals, but not to dictate 
the specific products or delivery mechanisms the GSEs will use to 
achieve a goal. Regulating two exceedingly large financial enterprises 
in a dynamic market requires that HUD provide the GSEs with sufficient 
latitude to use their innovative capacities to determine how best to 
develop products to carry out their respective missions. HUD's 
regulations should allow the GSEs to maintain their flexibility and 
their ability to respond quickly to market opportunities. At the same 
time, the Department must ensure that the GSEs' strategies serve all 
families and markets and address unmet credit needs. The addition of 
subgoals and/or bonus points to the regulatory structure may provide an 
additional means of encouraging the GSEs' affordable housing activities 
to address identified, persistent credit needs while leaving the 
specific approaches to meeting these needs to the GSEs.
    3. Discrimination in lending--albeit sometimes subtle and 
unintentional--has denied racial and ethnic minorities the same access 
to credit to purchase a home that has been available to similarly 
situated non-minorities. The GSEs have a central role and 
responsibility to promote access to capital for minorities and other 
identified groups and to thereby exhibit the feasibility of such 
lending.
    4. In addition to the GSEs' purchases of single family home loans, 
the GSEs also must continue to assist in the creation of an active 
secondary market for multifamily loans. Affordable rental housing is 
essential for those families who cannot afford to become homeowners. 
The GSEs must assist in making capital available to assure the 
continued development of rental housing.

II. Discussion of Proposed Regulatory Changes

    This proposed rule includes changes to definitions applicable to 
the housing goals, establishment of new housing goal levels, new 
requirements for counting mortgage purchases under the goals, 
discussion of possible regulatory incentives intended to spur greater 
GSE involvement in untapped segments of the affordable housing market, 
and an expansion of data available to the public on the GSEs' mortgage 
loan purchases. Much of the analysis referenced in this discussion is 
based on data through calendar year 1997. Information on the GSEs' 
mortgage purchases for 1998 is referenced where feasible.
    Many of the proposed rule changes, included in the final rule, will 
involve changes in data reporting requirements. The final rule will 
identify the specific changes to data reporting necessary to implement 
any new requirements for counting mortgage purchases under the housing 
goals.

A. Subpart A--General

    Since 1996, as a result of HUD's experience with the 1995 GSE rule, 
the Department has identified several definitions that require greater 
clarity to ensure consistent application of the housing goal 
requirements. Accordingly, some definitional changes are proposed for 
this purpose. Other definitional changes would be necessary as a result 
of the proposed changes to the housing goals. These types of 
definitional changes are discussed in the following Subpart B--Housing 
Goals.
    1. Definitions. The following definitions are proposed to be added 
or revised in order to provide greater clarity, consistency and 
guidance with regard to this regulation.
    a. Metropolitan Area. This rule proposes to revise the existing 
definition of ``Metropolitan Area'' to correct an ambiguity in the 
relevant area for defining median incomes. ``Metropolitan Area'' is 
defined in Sec. 81.2 of the current regulation as a ``metropolitan 
statistical area (MSA), a primary metropolitan statistical area (PMSA), 
or a consolidated metropolitan statistical area (CMSA), designated by 
the Office of Management and Budget of the Executive Office of the 
President.'' This definition gives rise to an ambiguity in the 
definitions of underserved area and the denominator of the 
affordability ratio used to compute the Low- and Moderate-Income 
Housing Goal and Special Affordable Housing Goal in whether to use the 
median income of the CMSA or the PMSA. For example, the underserved

[[Page 12647]]

area definition requires that the denominator be the metropolitan area 
median income. Should the median income of a census tract in 
Washington, D.C. be compared to median income of the Washington PMSA or 
the Baltimore-Washington CMSA? HUD has consistently defined underserved 
areas, as well as denominators for the other goals, using the median 
incomes of the PMSA. This rule would correct this ambiguity by revising 
the definition of ``Metropolitan Area'' in Sec. 81.2 to eliminate the 
reference to CMSAs.
    b. Median Income. Under Sec. 81.2 of HUD's current regulations, the 
definition of ``Median Income'' with respect to an area is the 
unadjusted median family income for the area, as most recently 
determined and published by the Department; ``area'' includes 
metropolitan areas. ``Metropolitan Area'' is defined in Sec. 81.2 in 
terms of areas designated as such by OMB. These definitions give rise 
to an inconsistency, in that HUD routinely publishes area median family 
income estimates but, in some cases, determines them not for MSAs, or 
PMSAs, but rather for portions of such areas. For example, OMB defines 
the Washington D.C. PMSA to include Berkeley and Jefferson counties in 
West Virginia and Culpeper, King George and Warren counties in 
Virginia. However, HUD's published area income estimates for these five 
counties are based on the incomes specific to these counties, not the 
PMSA. Moreover, HUD's published area income estimates for the other 
counties in the Washington MSA are based on data pertaining to the 
remaining counties and disregarding data for these five counties. As 
another example, OMB defines the New York City PMSA to include Rockland 
and Westchester Counties. HUD's published area income estimates for 
these two counties are based on incomes specific to the counties, not 
the PMSA. HUD's published area income estimates for the other counties 
in the New York City PMSA are based on data pertaining to the entire 
New York City PMSA including Rockland and Westchester Counties. Such 
differences between HUD's published area estimates and MSAs have led to 
ambiguity concerning the appropriate determination of area incomes by 
the GSEs. HUD proposes to change the definition of ``Median Income'' to 
require the GSEs to use HUD estimates of median family income. As part 
of this change to the definition of ``Median Income,'' HUD would 
provide the GSEs, on an annual basis, with information specifying how 
HUD's published median family income estimates are to be applied.
    c. Underserved Area. This rule proposes to revise the existing 
definition of ``Underserved Area'' to correct the parameters of rural 
underserved areas. The definition of rural underserved areas in 
Sec. 81.2 has an ``income-only'' portion (i.e., a median income at or 
below 95 percent of the state non-metropolitan median income or the 
nationwide non-metropolitan median income, whichever is greater) and 
``income/minority'' portion (i.e., a median income at or below 120 
percent of the state non-metropolitan median income and a minority 
population of at least 30 percent). In the preamble to the 1995 Final 
Rule, HUD explained that for the income only portion of the definition, 
the median income of a county would be compared to the greater of 
either the state or the nationwide non-metropolitan median income, in 
order to ensure that poor counties in poor states would be included in 
the definition. However, the 1995 Final Rule did not recognize this 
comparison in the ``income/minority'' portion. Therefore, this proposed 
rule would correct this oversight by proposing to revise the definition 
of ``Underserved Areas'' in Sec. 81.2. This rule also proposes a 
specific change to this definition related to tribal lands and 
discusses other possible changes to the definition related to 
metropolitan and non-metropolitan (rural) areas. The changes are 
proposed are discussed below in Section B., 3., e., ``Central Cities, 
Rural Areas and Other Underserved Areas Housing Goal.''

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 Goal, a Special Affordable Housing Goal, and a 
Central Cities, Rural Areas, and Other Underserved Areas Housing Goal 
(the Geographically Targeted 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 December 1995, HUD established housing goals for the GSEs for 
1996-1999, revising and restructuring the transition goals that had 
been in effect for 1993-1995. The current housing goal levels, which 
were in place for 1996-1999, 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),\52\ and which was set at 40 percent of total units 
financed by each of the GSEs' mortgage purchases in 1996 and 42 percent 
for each calendar year from 1997 though 1999;
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    \52\ 24 CFR 81.2.
---------------------------------------------------------------------------

    A Geographically Targeted 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 was set at 21 percent of total 
units financed by each of the GSEs' mortgage purchases in 1996 and at 
24 percent for each calendar year from 1997 through 1999;
    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 was set at 12 percent of total units 
financed by each of the GSEs' mortgage purchases in 1996 and at 14 
percent for calendar each year from 1997 through 1999; and
    A Special Affordable Multifamily Housing 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 was set at a fixed 
amount of 0.8 percent of the total dollar volume of mortgages purchased 
by each GSE in 1994. This formula results in a subgoal of special 
affordable multifamily mortgage purchases totaling $1.29 billion per 
year for Fannie Mae and $988 million per year for Freddie Mac for each 
calendar year from 1996 through 1999.
    These housing goals, excluding the special affordable multifamily 
housing subgoal, share common characteristics: (1) Annual 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 four-year period from 1996 through 1999 
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

[[Page 12648]]

size of the conventional market for each goal. In 1995, HUD estimated 
the low- and moderate-income share of the conventional market at 48-52 
percent; the underserved (geographically targeted) areas share at 25-28 
percent; and the special affordable share at 20-23 percent. These 
market estimates were based mainly on HMDA data for 1992 to 1994. Upon 
further analysis, however, these estimates are below what actual data 
shows for the period from 1995 to 1998. For example, HUD's 1995 market 
estimates underestimated the size of the rental market and did not 
anticipate the underlying strength and persistence of the affordable 
lending market. A large portion of new mortgages were originated for 
low-income families and first time homebuyers during the 1995 to 1998 
period. Therefore, HUD estimates that the low- and moderate-income 
market accounted for 57-58 percent of all mortgages originated during 
the 1995 to 1997 period, and for 54 percent during the heavy 
refinancing year of 1998. Appendix D, ``Estimating the Size of the 
Conventional Conforming Market for each Housing Goal,'' provides other 
reasons that the actual market shares were higher than anticipated in 
HUD's 1995 estimates.
    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 2000 through 
2003.\53\ HUD estimates that for the years 2000 through 2003 the low- 
and moderate-income share of the conventional market will be 50-55 
percent, the underserved (geographically targeted) areas share of the 
market will be 29-32 percent, and the special affordable share will be 
23-26 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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    \53\ The goal-qualifying market shares are estimated for the 
years 2000-2003 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.
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    The higher market estimates suggest that the gaps between the 
current goal levels and the market estimates of the opportunities 
available to the GSEs are wider than was anticipated in 1995. As with 
the 1995 estimates, these new market estimates also allow for more 
adverse economic conditions than recently experienced. For example, the 
lower end--50 percent--of the range for the low- and moderate-income 
market estimate is consistent with low- and moderate-income borrowers 
accounting for 35 percent of home purchase loans in the single-family 
owner market. (The remainder of the low- and moderate-income market 
share estimate includes multifamily and single family rental 
properties.) Since the 1992-98 average for the low- and moderate-income 
share of the home purchase market was 41 percent, and the more recent 
1995-1998 average was 42 percent, some leeway is allowed for more 
adverse income and interest rate conditions. Such leeway may be needed 
since it is possible that the affordable housing market may not 
continue at current rates, particularly if there is a slowdown in 
economic activity.
    While the single family affordable market has not changed 
substantially since 1995 when HUD developed its first market estimates, 
HUD has revised its new market estimates upward based upon its analyses 
of the underlying strength of the single family affordable market. That 
market has been consistently strong for the past six years (1993-1998). 
When HUD produced the market estimates in 1995, the data was limited to 
the early 1990s, during which 1993 and 1994 demonstrated the strongest 
affordable housing markets. Now, with four additional years (1995 to 
1998) of data indicating consistent trends in the affordable market, 
HUD is more confident about the underlying strength of this market.
    At the same time, HUD has used assumptions about future economic 
and market conditions that are more conservative than those that have 
actually prevailed over the last six years. HUD is well aware of the 
volatility of mortgage markets and their possible impacts on the GSEs' 
ability to meet the housing goals. HUD's market estimates have also 
changed to a small extent by including manufactured housing loans in 
the single family owner market, and slightly increasing the 
affordability and underserved area parameters for rental housing.
    Under HUD's current regulations, the current levels of the housing 
goals remain in effect in 2000 and thereafter until such time as the 
Department establishes new annual housing goals. In this rule, HUD is 
proposing to establish new levels for the three housing goals and for 
the special affordable multifamily housing subgoal for the years 2000 
through 2003. The housing goals as proposed would be phased in 
beginning in calendar year 2000 and would be fully in place in calendar 
years 2001, 2002 and 2003. In proposing the level of the housing goals 
for 2000 and thereafter, HUD has applied the statutory factors and also 
has concluded that the goals should be set far enough into the future 
to allow the GSEs to engage in long-term planning.
    2. Section 81.12 Low- and Moderate-Income Housing Goal. This 
section discusses the Department's consideration of all the statutory 
factors in arriving at its proposed new housing goal level for the Low- 
and Moderate-Income Housing Goal. Additional information analyzing each 
of the statutory factors is provided in Appendix A, ``Departmental 
Considerations to Establish the Low- and Moderate-Income Housing 
Goal,'' and Appendix D, ``Estimating the Size of the Conventional 
Conforming Market for each Housing Goal.''
    a. Definition. The Low- and Moderate-Income Housing Goal counts 
mortgages on housing for families with incomes not in excess of area 
median incomes.
    b. Market Estimate for the Low- and Moderate Income Housing Goal in 
2000. The Department estimates that dwelling units serving low- and 
moderate-income families will account for 50-55 percent of total units 
financed in the overall conventional conforming mortgage market during 
the period 2000 through 2003. Due to inherent uncertainty about future 
market conditions, HUD has developed a plausible range, rather than a 
point estimate, for the market. The detailed analyses underlying this 
estimate are presented in Appendix D, ``Estimating the Size of the 
Conventional Conforming Market for Each Housing Goal.''
    c. Past Performance of the GSEs Under the Low- and Moderate-Income 
Housing Goal. HUD's current goals specified that in 1996 at least 40 
percent of the number of units financed by mortgage purchases of the 
GSEs and eligible to count toward the Low- and Moderate-Income Goal 
should qualify as low- and moderate-income, and at least 42 percent 
should qualify in each year from 1997 through 1999. Fannie Mae 
surpassed these goal levels by 5.6 percentage points in 1996, 3.7 
percentage points in 1997, and 2.1 percentage points in 1998. Freddie 
Mac surpassed the goals by 1.1 percentage points, 0.6 percentage point 
and 0.9 percentage point in 1996, 1997 and 1998, respectively. The 
GSEs' performance under the Low- and Moderate-Income Housing Goal for 
the 1996 through 1998 period is summarized below:

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    During the transition period from 1993 through 1995, Fannie Mae's 
performance under the Low- and Moderate-Income Housing Goal jumped 
sharply in one year, from 34.2 percent in 1993 to 44.8 percent in 1994, 
before tailing off to 42.3 percent in 1995. It then stabilized at just 
over 45 percent in 1996 and 1997. Fannie Mae's performance in 1998 
declined to 44.1 percent due in large measure to the high volume of 
refinance loans that Fannie Mae funded in 1998.
    During the transition period, Freddie Mac demonstrated steadier 
gains in performance under the Low- and Moderate-Income Housing Goal, 
from 29.7 percent in 1993 to 37.4 percent in 1994 and 38.9 percent in 
1995. Freddie Mac then achieved 41.1 percent in 1996, and 42.6 percent 
and 42.9 percent in 1997 and 1998, respectively. Fannie Mae's 
performance on the Low- and Moderate-Income Housing Goal has surpassed 
Freddie Mac's in every year. Nonetheless, Freddie Mac's 1998 
performance represented a 44 percent increase over its 1993 level, 
exceeding the 29 percent increase for Fannie Mae. Freddie Mac's 
performance was 97 percent of Fannie Mae's low- and moderate-income 
share in 1998, the highest ratio since the goals took effect in 1993. 
Freddie Mac's improved performance is due mainly to its increased 
purchases of multifamily loans as it has become more active in this 
market. Some housing industry observers believe that the Low- and 
Moderate-Income Housing Goal has been an important factor explaining 
Freddie Mac's re-entry into the multifamily market.
    In fact, multifamily purchases represent a significant component of 
both GSEs' activities in meeting the Low- and Moderate-Income Housing 
Goal, even though multifamily loans comprise a relatively small portion 
of the GSEs' business activities. In 1997, while Fannie Mae's 
multifamily purchases represented only 13.4 percent of its total 
acquisition volume measured in terms of dwelling units, these purchases 
comprised 26.7 percent of units qualifying for the Low- and Moderate-
Income Housing Goal. Multifamily purchases were 8.2 percent of the 
units financed by Freddie Mac's 1997 mortgage purchases but were 19 
percent of Freddie Mac's low- and moderate-income mortgage purchases.
    The GSEs' 1998 performance took place in the context of a record 
level of mortgage originations, with unusually high refinance volume 
reaching 50 percent of single family mortgage originations. The GSEs 
relied upon a record volume of multifamily mortgage purchases in 1998--
$12.5 billion for Fannie Mae and $6.6 billion for Freddie Mac--to 
exceed the 42 percent goal.
    d. Proposed Goal Levels for 2000-2003. Having considered all 
statutory factors including housing needs, projected economic and 
demographic conditions for 2000 to 2003, the GSEs' past performance, 
the size of the market serving low- and moderate-income families, and 
the GSEs' ability to lead the market while maintaining a sound 
financial condition; HUD is proposing that the annual goal for mortgage 
purchases qualifying under the Low- and Moderate-Income Housing Goal be 
48 percent of eligible units financed in calendar year 2000, and 50 
percent of eligible units financed in each of calendar years 2001, 2002 
and 2003. This proposed goal level is intended to increase the GSEs' 
current level of performance to a level that is consistent with 
reasonable estimates of the low- and moderate-income housing market. 
HUD's detailed findings under the statutory factors for establishing 
the goal are described 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.''
    3. Section 81.13--Central Cities, Rural Areas, and Other 
Underserved Areas Housing Goal. This section discusses the Department's 
consideration of all the statutory factors in arriving at its proposed 
new housing goal level for the Central Cities, Rural Areas, and Other 
Underserved Areas Housing Goal (the Geographically Targeted Goal). 
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.'' This section also discusses possible changes 
being considered to the definition of underserved areas.
    a. Definition. The Geographically Targeted Goal focuses on areas 
currently underserved by the mortgage finance system. The 1995 Final 
Rule provides that for properties in metropolitan areas, mortgage 
purchases count toward the Geographically Targeted Goal if such 
purchases finance properties that are located in underserved census 
tracts. In Sec. 81.2, HUD defined ``underserved areas'' as areas where 
either: (1) The tract median income is at or below 90 percent of the 
area median income (AMI); or (2) the minority population is at least 30 
percent and the tract median income is at or below 120 percent of AMI. 
The AMI ratio is calculated by dividing the tract median income by the 
MSA median income. The minority percent of a tract's population is 
calculated by dividing the tract's minority population by its total 
population.
    For properties in non-metropolitan (rural) areas, mortgage 
purchases count toward the Geographically Targeted Goal where such 
purchases finance properties that are located in underserved counties. 
These are defined as counties where either (1) the median income in the 
county does not exceed 95 percent of the greater of the state or 
nationwide non-metropolitan median income; or (2) minorities comprise 
at least 30 percent of the residents and the median income in the 
county does not exceed 120 percent of the state non-metropolitan median 
income.
    b. Market Estimate for the Geographically Targeted Goal. The 
Department estimates that dwelling units in underserved areas will 
account for 29-32 percent of total units financed in the overall 
conventional conforming mortgage market during the period 2000 through 
2003. Due to inherent uncertainty about future market conditions, HUD 
has developed a plausible range, rather than a point estimate, for the 
market. The detailed analyses underlying this estimate are presented in 
Appendix D, ``Estimating the Size of the Conventional Conforming Market 
for Each Housing Goal.''
    c. Past Performance of the GSEs Under the Geographically Targeted 
Goal. HUD's goals specified that in 1996 at least 21 percent of the 
units financed by the GSEs' mortgage purchases should count toward the 
Geographically Targeted Goal, and at least 24 percent in 1997 through 
1999. Fannie Mae surpassed the goal by 7.1 percentage points in 1996, 
4.8 percentage points in 1997, and 3.0 percentage points in 1998. 
Freddie Mac surpassed the goal by 4.0, 2.3 and 2.1 percentage points in 
1996, 1997 and 1998, respectively. The GSEs' performance for the 1996-
98 period is summarized below:

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    Although both GSEs have improved their performance in underserved 
areas, on average, their mortgage purchases continue to lag the primary 
market in providing financing for affordable loans in underserved 
neighborhoods. During the 1996-1998 period, underserved areas accounted 
for 19.9 percent of Freddie Macs purchases of single family home 
mortgages compared with 22.9 percent of Fannie Mae's purchases, 25.8 
percent of mortgages retained by portfolio lenders, and 24.9 percent of 
all home purchase mortgages originated in the conventional conforming 
market. As these figures indicate, Freddie Mac has been less likely 
than Fannie Mae to purchase mortgages on properties in underserved 
neighborhoods. Freddie Mac has not made progress in reducing the gap 
between its performance and that of the overall market. In 1992, 
underserved areas accounted for 18.6 percent of Freddie Mac's purchases 
of home purchase mortgages and for 22.2 percent of home loans 
originated in the conforming market, which yields a ``Freddie Mac-to-
Market'' ratio \54\ of 0.84 percent. By 1998, the ``Freddie Mac-to-
Market'' ratio had actually fallen to 0.81 percent. During the same 
period, the ``Fannie Mae-to-Market'' ratio increased from 0.82 percent 
to 0.93 percent.
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    \54\ GSE to market ratio is calculated by dividing the 
performance of the respective GSE by the performance of the market.
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    Fannie Mae's performance under this goal improved due to its 
increased purchases during 1997 and 1998 of mortgages originated in 
prior years in underserved neighborhoods. For instance, Fannie Mae's 
purchases of single family home mortgage loans in underserved areas 
increased from 22.3 percent in 1996 to 23.5 percent in 1997. However, 
the percentage of Fannie Mae's purchases of newly originated mortgages 
on dwellings in underserved areas was lower in 1997 (20.8 percent) than 
in 1996 (21.9 percent). This decline was offset by the fact that a high 
percentage (30.1 percent) of Fannie Mae's purchases in 1997 of prior 
year mortgages were home mortgage loans on properties in underserved 
areas. This focus on prior year mortgages explains why Fannie Mae's 
performance increased across several affordable lending categories 
between 1996 and 1997. Fannie Mae's purchases of prior year affordable 
housing loans continued in 1998.
    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 purchase activity in underserved areas derives totally from lower 
income families. In 1997, above median-income households accounted for 
37 percent of the mortgages the GSEs purchased in underserved areas.
    d. Proposed Goal Levels for 2000-2003. Having considered all 
statutory factors including housing needs, projected economic and 
demographic conditions for 2000 to 2003, the GSEs' past performance, 
the size of the market for central cities, rural areas and other 
underserved areas, and the GSEs' ability to lead the market while 
maintaining a sound financial condition; HUD is proposing that the 
annual goal for mortgage purchases qualifying under the Geographically 
Targeted Goal be 29 percent of eligible units financed in calendar year 
2000, and 31 percent of eligible units financed in each of calendar 
years 2001, 2002 and 2003. This proposed goal level is intended to 
increase the GSEs' current level of performance to a level that is 
consistent with reasonable estimates of the housing market in 
underserved areas. The Department's detailed findings under the 
statutory factors for establishing the goal are described 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.''
    e. Proposed Definitional Changes for Underserved Areas. (1) 
Metropolitan Areas. The Department is seeking comments on possible 
changes to the current metropolitan underserved areas definition in an 
effort to more accurately target underserved areas with higher mortgage 
denial rates and thereby promote access to mortgage credit nationwide. 
Specifically, HUD is considering changing the current tract income 
ratio to an ``enhanced'' tract income ratio and requiring that for 
tracts to qualify they must have an enhanced tract income ratio at or 
below 80 percent of area median income. The enhanced tract income ratio 
described below would make the underserved areas definition used by the 
GSEs consistent with the requirements of Federally insured depository 
institutions under the Community Reinvestment Act (CRA).
    The ``enhanced'' option is two-fold. First, it would change the 
tract income ratio (described in the definition of ``central city'' or 
``other underserved area'' in paragraph (1) of the definition of 
``Underserved areas'' in Sec. 81.2) from one that is calculated using 
MSA median income to one that is based on the greater of either the 
national metropolitan median income or the MSA median income. This 
approach would ensure that low-income census tracts in low-income MSAs 
are classified as underserved. With this change, 994 tracts, with an 
average mortgage denial rate of 26.8 percent, would be added to the 
scope of the current definition.
    Second, the enhanced option would change the level of the income 
ratio required in paragraph (1)(ii) of the definition of ``Underserved 
areas.'' Tracts would qualify as underserved if their income ratio were 
80 percent as compared to a tract income ratio of 90 percent under the 
current definition. With this change, 2,500 tracts, with an average 
mortgage denial rate of 17.8 percent, would be dropped from the scope 
of the current definition. Of the tracts that would be dropped, the 
mortgage denial rate is not much higher than the average mortgage 
denial rate for all metropolitan areas, which is 15.3 percent. This 
suggests that these areas are not experiencing severe problems in 
obtaining mortgage credit and should not be targeted. The overall 
number of tracts that would qualify with both parts of the enhanced 
option is 20,093, with an average mortgage denial rate of 25.0 percent.
    Although the Department preliminarily favors adopting a 
definitional change based on the enhanced tract income option described 
above, another approach to targeting high mortgage denial areas is to 
increase the alternative requirement for an underserved area by 
increasing the minority concentration required from the current 30 
percent to 50 percent. Adopting this option would exclude many tracts 
with high mortgage denial rates. This option would drop 1,045 tracts 
with a relatively high mortgage denial rate of 20.2 percent. 
Nevertheless, this proposal should stimulate conventional lending in 
high minority neighborhoods that have been traditionally underserved.
    Either of the possible changes to the existing definition for 
underserved areas would likely affect the estimated market share for 
the Geographically Targeted Goal. If either of the possible changes 
were adopted, the Department would revise its market estimates of 
underserved areas accordingly and the level of the housing goal as 
needed to reflect the revised estimates.
    HUD seeks comment on the proposed options for revising the 
definition of underserved metropolitan areas, including the extent to 
which these definitional changes are likely to increase the 
availability of credit to areas with high mortgage denial rates.

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    (2) Tribal Lands. In reviewing the criteria for underserved areas, 
HUD believes that difficulties in obtaining mortgage loans on 
qualifying American Indian Reservations and trust lands deserve 
attention. A February 1998 report by the General Accounting Office 
(GAO) concerning lending on tribal lands found that, during a five year 
period from 1992 through 1996, only 91 conventional home purchase loans 
were made to Native Americans on trust lands.\55\ The eight lenders 
making these loans held all of them in portfolio. In addition, 
government-backed loans were insured by HUD under its Section 184 and 
Section 248 programs which promote affordable housing opportunities for 
Native American families, and through programs of the Department of 
Veterans Affairs, the U.S. Department of Agriculture, and the Federal 
Home Loan Banks. Fannie Mae has consistently purchased Section 184 
loans, and Freddie Mac has recently become involved in this program.
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    \55\ GAO/RCED-98-49.
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    A number of reservations cross county and census tract lines with a 
portion of the reservation in a county that is otherwise considered 
high-income and/or low-minority and a portion of the reservation in a 
county that is neither. Part of a reservation, therefore, may be 
considered an underserved area and part a served area. To remedy such 
anomalies, this rule proposes that reservations and trust lands would 
be considered separate geographic entities rather than parts of the 
counties in which they are located. Thus, in a non-metropolitan area, 
median income for the reservation would be compared with state (or 
national) non-metropolitan median income in determining whether the 
reservation is an ``underserved area;'' and in a metropolitan area, 
median income for the reservation would be compared with the median 
income of the respective metropolitan area.
    HUD has determined that currently 173 non-metropolitan counties 
that contain Indian reservations or trust lands are classified as 
underserved areas and 88 such counties are classified as served areas. 
In metropolitan areas, 131 census tracts that contain Indian 
reservations or trust lands are currently classified as underserved 
areas and 115 such tract are classified as served areas. Inclusion of 
qualifying Indian reservations and trust lands in these 88 counties and 
115 census tracts as underserved areas in calculating the 
Geographically Targeted Goal would not automatically be expected to 
have a major impact on lending in these areas, at least initially, but 
it could heighten awareness and encourage future growth in conventional 
mortgage lending to these areas.
    Based on this analysis, the Department proposes to revise Sec. 81.2 
to designate all qualifying Indian reservations and trust lands as 
underserved areas.
    (3) Rural Areas. The current definition of underserved non-
metropolitan or rural areas under the Geographically Targeted Goal 
accounts for 53 percent of the households, 57 percent of the census 
tracts, and 66 percent of the counties in rural areas. Unlike the 
underserved definition for metropolitan areas, which is based on the 
minority or low-income concentration of census tracts, the non-
metropolitan/rural underserved definition is based on these criteria 
for counties. During the 1995 rulemaking process, experts on rural 
lending informed HUD that lenders' business operations in rural areas 
are oriented toward counties, not census tracts. In addition, counties 
are easy to identify and geocode, which facilitates the reporting 
process for lenders who provide the GSEs with loan-level data on 
mortgages. However, HUD recognized then, and experience has borne out, 
that, under its county-based definition, the GSEs can achieve the goal 
by purchasing mortgages located in the parts of underserved counties 
that have higher incomes.
    The broad nature of the underserved definition for non-metropolitan 
areas raises at least two concerns. The first concern is that the broad 
definition appears to result in similar borrower characteristics in 
served and underserved counties. HUD's analysis indicates that the GSEs 
are less likely to purchase loans for first-time homebuyers and more 
likely to purchase mortgages for high-income borrowers in underserved 
than in served counties. Mortgages to first-time homebuyers account for 
13.9 percent of the GSEs' mortgage purchases in served counties 
compared with 12.3 percent in underserved counties. Interestingly, it 
is more likely for borrowers in underserved counties (71.2 percent) to 
have incomes above the county median than in served counties (65.5 
percent). These findings support the claim that, in rural underserved 
counties, the GSEs purchase mortgages of borrowers who probably 
encounter few obstacles to obtaining mortgage credit. Further, 
mortgages purchased by the GSEs in underserved areas do not have low 
down payments. In both served and underserved counties, only 27 percent 
of the GSEs' mortgage purchases have loan-to-value ratios above 80 
percent.
    Defining underserved areas in terms of an entire county also 
appears to encourage the GSEs to purchase mortgages in the more 
affluent tracts. HUD's analysis shows that even though the GSEs 
purchase a greater percentage of mortgages in high-minority and low-
income tracts in underserved than in served counties, they purchase 
nearly the same percentage of mortgages in both underserved and served 
counties in high-income tracts. In underserved counties, 12.3 percent 
of the GSEs' mortgage purchases are in tracts above 120 percent area 
median income compared with 14.6 percent in served counties.
    There are few conclusive studies on access to mortgage credit in 
rural areas, and the studies that do exist suggest only broad 
conclusions about credit flows in these areas. Moreover, evaluating 
which rural locations are underserved in terms of access to mortgage 
credit cannot be done with HMDA data on which HUD mainly relied in 
defining urban underserved areas. Other data bases available with 
mortgage market information have similar limitations with regard to 
coverage of mortgage activity in rural areas. Nonetheless, based on an 
analysis of the GSEs' mortgage purchases by tract median income, it 
does not appear that the current county definition is encouraging the 
GSEs to target their mortgage purchases to the most underserved 
portions of rural areas.
    For these reasons, the Department is seeking public comment on 
alternative methodologies and sources of rural market data that HUD 
might use to define underserved non-metropolitan/rural areas. 
Specifically, HUD seeks comment on whether the Department should follow 
a tract-based approach in defining underserved rural areas, which would 
be consistent with the tract-based definition used in metropolitan 
areas. As technology and computer mapping capabilities have evolved 
since 1995, it may be appropriate to revisit the issue of whether 
entire counties or census tracts within the counties should be used to 
define rural underserved areas.
    4. Section 81.14 Special Affordable Housing Goal. This section 
discusses the Department's consideration of all the statutory factors 
in arriving at its proposed new housing goal level for the Special 
Affordable Housing Goal. 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.'' This section also

[[Page 12654]]

discusses possible changes being considered to the structure of the 
multifamily subgoal.
    a. Definition. The Special Affordable Housing Goal targets 
mortgages on housing for very low-income families and low-income 
families living in low-income areas. 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. In addition, low-income rental units in multifamily properties 
in which at least 20 percent of the units 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 area median income, or less, count toward the 
goal.
    b. Market Estimate for the Special Affordable Housing Goal. The 
Department estimates that dwelling units serving very low-income 
families and low-income families living in low-income areas will 
account for 23-26 percent of total units financed in the overall 
conventional conforming mortgage market during the period 2000 through 
2003. Due to inherent uncertainty about future market conditions, HUD 
has developed a plausible range, rather than a point estimate, for this 
market. The detailed analyses underlying this estimate are presented in 
Appendix D, ``Estimating the Size of the Conventional Conforming Market 
for Each Housing Goal.''
    c. Past Performance of the GSEs' Under the Special Affordable 
Housing Goal. The Special Affordable Housing Goal is designed to ensure 
that the GSEs consistently focus on serving the very low-and low-income 
portion of the housing market. However, analysis of American Housing 
Survey and HMDA data show that the shares of mortgage loans for very 
low-income homebuyers are smaller for the GSEs' mortgage purchases than 
for depository institutions and others originating mortgage loans in 
the conforming conventional market. HUD's analysis suggests that the 
GSEs should improve their performance in providing financing for the 
very low-income housing market.
    HUD's goals specified that in 1996 at least 12 percent of the 
number of units eligible to count toward the Special Affordable Housing 
Goal should qualify as special affordable, and at least 14 percent in 
1997 through 1999. As indicated below, Fannie Mae surpassed the goal by 
3.4 percentage points in 1996, 3.0 percentage points in 1997 and 0.3 
percentage point in 1998. Freddie Mac surpassed the goal by 2.0, 1.2, 
and 1.9 percentage points in 1996, 1997 and 1998, respectively. The 
GSEs' performance for the 1996-95 period is summarized below:

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    HMDA and GSE data for metropolitan areas show that both GSEs lag 
depository institutions and other lenders in providing financing for 
home loans that qualify for the Special Affordable Housing Goal. 
Special affordable loans, which include loans for very low-income 
borrowers and low-income borrowers living in low-income areas, 
accounted for 9.8 percent of Freddie Mac's purchases of home purchase 
mortgages during 1996-98, 11.9 percent of Fannie Mae's purchases, 16.7 
percent of newly originated loans retained by depository institutions, 
and 15.3 percent of all new originations in the conventional conforming 
market. While Freddie Mac has improved its special affordable lending 
over the past few years, it has not made as much progress as Fannie Mae 
in closing the gap with depository institutions and other lenders in 
the home loan market. In 1998, Freddie Mac's special affordable 
performance was 73 percent of the primary market proportion of home 
loans that would qualify under the Special Affordable Housing Goal, 
compared to Fannie Mae's performance of 85 percent during the same 
period.
    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. In 1997, 57 percent of units 
financed by Freddie Mac's multifamily mortgage purchases met the 
Special Affordable Housing Goal, representing 31 percent of units 
counted toward its Special Affordable Housing Goal, at a time when 
multifamily units represented only eight percent of its total purchase 
volume. Corresponding percentages for Fannie Mae's multifamily 
purchases were: 54 percent of units financed by Fannie Mae's 
multifamily mortgage purchases met the Special Affordable Goal, 
multifamily units represented 44 percent of units meeting the Special 
Affordable Goal but only 13 percent of total purchase volume. In 
comparison, HUD estimates that multifamily mortgages accounted for 20 
percent of the total number of dwelling units financed in the 
conventional conforming market in 1997.
    d. Proposed Goal Levels for 2000-2003. Having considered all 
statutory factors including housing needs, projected economic and 
demographic conditions for 2000 to 2003, the GSEs' past performance, 
the size of the market serving very low-income families and low-income 
families living in low-income areas, and the GSEs' ability to lead the 
market while maintaining a sound financial condition; HUD is proposing 
that the annual goal for mortgage purchases qualifying under the 
Special Affordable Housing Goal be 18 percent of eligible units 
financed in calendar year 2000, and 20 percent of eligible units 
financed in each of calendar years 2001, 2002 and 2003. This proposed 
goal level is intended to increase the GSEs' current level of 
performance to a level that is consistent with reasonable estimates of 
the special affordable housing market. The Department's detailed 
findings under the statutory factors for establishing the goal are 
described 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.''
    e. The Multifamily Subgoal. Under the Special Affordable Housing 
Goal, HUD established a subgoal for purchases of multifamily mortgages. 
HUD established this subgoal at 0.8 percent of the dollar value of each 
GSE's respective 1994 dollar purchase volume, including both single 
family and multifamily mortgage purchases. This yielded subgoals of 
$988 million for Freddie Mac and $1.29 billion for Fannie Mae.\56\
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    \56\ Mortgages that are backed by properties that include both 
special affordable and other units are counted by multiplying the 
acquisition unpaid principal balance by the number of units 
qualifying for the Special Affordable Housing Goal, divided by the 
total number of units.
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    Freddie Mac narrowly exceeded the subgoal in 1996 and 1997, with 
multifamily special affordable acquisitions of $1.1 billion and $1.2 
billion, respectively. Freddie Mac exceeded the goal by a wider margin 
in 1998, when it purchased $2.7 billion in multifamily special 
affordable loans. Fannie Mae has consistently surpassed its multifamily 
subgoal, with multifamily mortgage purchases of $2.4 billion in 1996, 
$3.2 billion in 1997, and $3.5 billion in 1998.\57\
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    \57\ These figures are as determined by HUD based on its 
analysis of GSE loan-level data. They differ somewhat from figures 
reported by the GSE in their Annual Housing Activities Reports 
submitted annually to HUD due to differences in application of 
counting rules, and for other reasons.
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    Approximately half of the GSEs' annual multifamily purchase volume 
usually qualifies toward the Special Affordable Housing Goal. Moreover, 
multifamily acquisitions typically represent a significant proportion 
of all GSE purchases qualifying toward the Special Affordable Housing 
Goal. As noted earlier, multifamily acquisitions contributed 44.0 
percent of units qualifying toward Fannie Mae's Special Affordable 
Housing Goal, with a corresponding figure of 31.4 percent for Freddie 
Mac.
    One of the Department's principal objectives in establishing the 
subgoal was to ensure Freddie Mac's re-entry into the multifamily 
market. In 1991-1993, following losses on multifamily mortgage loans, 
Freddie Mac had virtually no multifamily mortgage purchase capacity. 
Over the past five years, however, Freddie Mac has built new capacity 
to support its multifamily mortgage purchase activity and has expanded 
its presence in the multifamily financing market to the point that it 
purchased $6.6 billion of multifamily mortgages in 1998. Industry 
observers believe that the special affordable multifamily subgoal has 
contributed toward a significantly increased presence by Freddie Mac in 
the multifamily market.
    Fannie Mae was well established in the multifamily mortgage market 
prior to the establishment of the multifamily special affordable 
subgoal. Fannie Mae's performance has consistently surpassed the 
subgoal by a wide margin, as noted above.
    f. Proposed Multifamily Subgoal Level. The Secretary proposes to 
retain the special affordable multifamily subgoal for each of the 
calendar years for the period 2000 through 2003, and to increase the 
fixed minimum level to 0.9 percent of the dollar volume of combined 
(single family and multifamily) 1998 mortgage purchases in calendar 
year 2000, and 1.0 percent of the dollar volume of combined (single 
family and multifamily) 1998 mortgage purchases in each of calendar 
years 2001, 2002 and 2003. This approach is consistent with the 
approach taken under the current regulations.
    The proposed subgoal would establish the following new annual 
thresholds for the two GSEs.\58\
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    \58\ HUD has determined that the total dollar volume of the 
GSEs' combined (single and multifamily) mortgage purchases in 1998, 
measured in unpaid principal balance at acquisition, was as follows: 
Fannie Mae $367.589 million: Freddie Mac $273, 231 million.

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                                                         2000                              2001-2003
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Proposed Goal Levels...................  0.9 percent........................  1.0 percent.

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Fannie Mae.............................  $3.31 billion......................  $3.68 billion.
Freddie Mac............................  $2.46 billion......................  $2.73 billion.
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    The proposed subgoal levels can be compared with Fannie Mae's 1998 
performance of $3.5 billion, and Freddie Mac's 1998 multifamily special 
affordable multifamily acquisition volume of $2.7 billion. A 1.0 
percent dollar-based multifamily subgoal for 2001-2003 would sustain 
and likely increase the efforts of both GSEs in the multifamily 
mortgage market, with particular emphasis upon the special affordable 
segment.
    g. Alternative Approaches to Setting the Subgoal Level. A possible 
consequence of the subgoal as proposed, however, is that, to the extent 
that the GSEs experience certain fixed transactions costs in each 
multifamily acquisition, they can attain the special affordable 
multifamily subgoal with the smallest possible transactions costs by 
purchasing multifamily mortgages with large unpaid principal balances 
that have a high proportion of units that qualify for the Special 
Affordable Housing Goal. This approach, therefore, could foster the 
GSEs' purchases of loans on large properties with more than 50 units, 
the market for which is already relatively liquid, at the expense of 
loans on smaller properties, a sector which has not benefited from same 
degree of exposure to secondary markets, as discussed in Appendix A. In 
order to provide incentives for a greater commitment by the GSEs in the 
market for mortgages on small multifamily properties with 5-50 units, 
the Department is proposing to award ``bonus points'' for purchases of 
such loans, as described below.
    A further consequence of a dollar-based goal is that the number of 
mortgages the GSEs would be required to purchase under the subgoal, and 
the number of units in the associated properties, would both be 
expected to decrease over the goals period, due to the effects of 
inflation and an expected rise in property values over the period of 
years during which the subgoal is in effect. For example, the rise in 
multifamily property values over 1996-1998 contributed to an increase 
in per-unit loan amounts in the GSEs' multifamily special affordable 
purchases of approximately 15 percent, with a commensurate decrease in 
the number of units corresponding to the minimum dollar-based purchase 
volume required under the multifamily special affordable subgoal.
    While this proposed rule specifically proposes a dollar-based 
subgoal, the Department is considering three alternative approaches to 
structuring the special affordable multifamily subgoal--a unit-based 
subgoal, a subgoal based on a percentage of multifamily acquisitions, 
and a mortgage-based subgoal. These approaches may be structured as 
outlined in the following options. Additional discussion of these 
subgoal options in relation to GSE past performance is contained in 
Appendix C.
    (1) Option One--Subgoal Based on Number of Units. In this approach, 
the multifamily special affordable subgoal would be expressed as a 
minimum number of units meeting the Special Affordable Housing Goal. A 
multifamily subgoal for 2001-2003 established at the level of the 
dollar-based subgoal defined above, divided by $22,953, which is the 
average of Fannie Mae's and Freddie Mac's ratios of unpaid principal 
balance to the number of units in multifamily properties counted toward 
the Special Affordable Housing Goal in 1997 (as determined by HUD), 
would generate annual multifamily special affordable subgoals of 
160,328 units per year for Fannie Mae and 118,939 units per year for 
Freddie Mac. Such a multifamily subgoal for 2001-2003 would sustain and 
likely increase the efforts of both GSEs in the multifamily mortgage 
market, with particular emphasis upon the special affordable 
segment.\59\
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    \59\ If this option were selected, appropriate subgoal 
thresholds for the one-year transition period (2000) could be 
developed along the lines of those proposed under the multifamily 
special affordable subgoal above.
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    A unit-based subgoal would result in a greater level of 
affordability among the GSEs' special affordable purchases than does a 
dollar-based subgoal. This conclusion is based on GSE loan-level data 
which shows that the more affordable the unit, the smaller is the 
associated unpaid principal balance per unit. Therefore, a subgoal 
based on number of units provides the GSEs with an incentive to 
purchase mortgages on properties with relatively low loan amounts per 
unit and, as a result, relatively high affordability, as the least 
costly method of attaining the subgoal. This unit-based approach also 
avoids the problem associated with the effects of inflation discussed 
above in regard to the proposed dollar based subgoal.
    However, this approach also has one of the same consequences as the 
proposed subgoal based on dollar volume of acquisitions, in that a GSE 
can attain such a subgoal with the smallest possible transactions costs 
by purchasing a few multifamily mortgage loans with large unpaid 
principal balances which have a high proportion of units qualifying for 
the Special Affordable Housing Goal. This approach, therefore, may 
foster the GSEs' purchase of loans on large multifamily properties, 
which are already relatively well served by the mortgage market, at the 
expense of loans on smaller properties.
    (2) Option Two--Subgoal As A Percent of GSEs' Current Multifamily 
Mortgage Purchases. Another possible approach is to establish the 
special affordable multifamily subgoal as a minimum percentage of each 
GSE's current total dollar volume of multifamily mortgage purchases. 
For example, the subgoal level for 2001-2003 could be expressed as 58 
percent of a GSE's multifamily dollar volume in 2001, 2002 and 2003, 
respectively.\60\
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    \60\ If this option were selected, appropriate subgoal 
thresholds for the one-year transition period (2000) could be 
developed.
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    An advantage of expressing the subgoal in this manner is that it 
would be flexible, increasing and decreasing in a manner commensurate 
with the overall presence of the GSEs in the current-year multifamily 
market. It would not require a fixed quantity of units, or fluctuate 
based on the GSEs' involvement with the single-family market.
    An operational disadvantage is that such a subgoal could undermine 
the GSEs' incentive to expand multifamily volume that has existed since 
1994. For example, one of the GSEs, having met its special affordable 
multifamily subgoal by the end of the third quarter in a calendar year, 
could decide to withdraw from the multifamily market in the fourth 
quarter in order to avoid the possibility of not attaining the subgoal 
at the end of the year due to the uncertainty regarding the 
affordability characteristics of multifamily mortgages offered for sale 
during the remainder of the year. In order to mitigate any such 
disincentive effects, HUD could establish an ``alternative minimum'' 
subgoal floor based on dollar volume, units, or mortgages. However, 
this

[[Page 12658]]

would open the possibility that a GSE might choose to simply orient its 
multifamily business toward the required alternative minimum amount of 
multifamily mortgage purchases.
    (3) Option Three--Subgoal Based on Number of Mortgages Acquired. 
Because the GSEs incur relatively large fixed costs in purchasing 
multifamily mortgage loans, another alternative to the Special 
Affordable Multifamily Housing Subgoal would be to establish a subgoal 
based on the number of mortgages acquired. In this approach, the 
Special Affordable multifamily subgoal would be expressed as a minimum 
number of each GSEs' total mortgage purchases. If all the units in the 
property securing the mortgage are not eligible for the Special 
Affordable Housing Goal, then subgoal performance would be pro-rated 
based on the number of qualifying units. In other words, if one 
mortgage secured a 100-unit property and 50 of the units qualified for 
the Special Affordable Housing Goal, then subgoal credit would be 
counted as one-half of a mortgage.\61\
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    \61\ A similar pro-rating technique is specified for the special 
affordable multifamily subgoal in the 1995 Final Rule. See footnote 
62.
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    A multifamily subgoal for 2001-2003 established at 0.035 percent of 
the number of mortgages acquired by each of the GSEs in 1998 (as 
determined by HUD) would generate annual subgoals of 1,129 multifamily 
special affordable mortgages for Fannie Mae and 854 for Freddie 
Mac.\62\ A 0.035 percent mortgage-based multifamily subgoal for 2001-
2003 would sustain and likely increase the efforts of both GSEs in the 
multifamily mortgage market, with particular emphasis upon the special 
affordable segment.\63\
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    \62\ HUD has determined that the number of mortgage loans 
purchased by the GSEs in 1998 was as follows:
    Fannie Mae: 3,226,786.
    Freddie Mac: 2,439,194.
    \63\ If this option were selected, appropriate subgoal 
thresholds for the one-year transition period (2000) could be 
developed.
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    As noted previously, the GSEs incur relatively large fixed costs 
when underwriting and purchasing multifamily mortgage loans. As a 
result, there could be an incentive to purchase large multifamily 
mortgage loans to reduce the cost of the transactions per unit. Under 
this approach to the special affordable multifamily subgoal utilizing 
the number of mortgages acquired as the benchmark, the GSEs would have 
additional incentive to choose a large pool of small loans over a pool 
consisting of a few large loans.\64\ This could facilitate liquidity in 
the market for mortgages on small multifamily properties where there 
continues to be unmet credit needs. Because multifamily mortgage 
purchases are an important source of affordable housing and contribute 
significantly to meeting the unit based housing goals, the GSEs also 
would be expected to continue to purchase mortgages secured by larger 
properties.
---------------------------------------------------------------------------

    \64\ For example, under this subgoal option, the purchase of a 
mortgage backed by a 10-unit property with $300,000 mortgage would 
receive the same subgoal credit as a 100-unit property with a $2.5 
million mortgage (provided all units were eligible for the Special 
Affordable Housing Goal). If all the units in the property securing 
the mortgage are not eligible for the Special Affordable Housing 
Goal, then subgoal performance would be pro-rated based on the 
number of qualifying units, as discussed above.
---------------------------------------------------------------------------

    This approach also avoids the problem associated with the effects 
of inflation, discussed above, in regard to the proposed dollar-based 
subgoal. The magnitude of the goal is independent of the loan amount 
per unit.
    However, while a mortgage-based approach to the subgoal may address 
the small multifamily rental property issue, it may not have the same 
impact in financing as many units overall as other approaches.
    (4) Comments Sought. The Department seeks comment on whether the 
special affordable multifamily subgoal proposed that is based on a 
percentage of total dollar volume of mortgages purchased, or the 
possible alternative structures presented that base the subgoal on (a) 
the number of units financed, (b) a percent of current multifamily 
mortgage purchases, or (c) the number of mortgages acquired, are 
reasonable and desirable approaches to closing market gaps in the very 
low-and low-income rental market. HUD also solicits comment on the 
appropriate level for the subgoal as proposed, or under the various 
possible structures presented, and how the possible levels illustrated 
herein would likely impact multifamily acquisitions, especially for 
very low-and low-income multifamily units.
    5. Bonus Points and Subgoals. Although the GSEs have been 
successful in meeting their housing goals, analyses of their housing 
goal performance and market needs indicate that certain credit gaps 
remain. For example, HUD's analysis reveals that the need for mortgage 
credit persists in specific markets that focus on lower-income families 
including small multifamily rental properties; single family, owner-
occupied rental properties (2-4 units); manufactured housing; 
multifamily properties in need of rehabilitation; and properties in 
tribal areas. As a regulatory incentive to encourage the GSEs to 
increase their mortgage purchase activity in these underserved markets, 
the Department is proposing the use of bonus points in certain 
important segments of the housing market. HUD also seeks comments on 
the utility of applying similar regulatory incentives (bonus points 
and/or subgoals) to other underserved segments.
    a. Bonus Points. Section 1336(a)(2) of FHEFSSA directs the 
Department to ``establish guidelines to measure the extent of 
compliance with the housing goals, which may 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 Department deems 
appropriate.'' This provision confers broad authority upon HUD to 
assign varying levels of credit to differing types of mortgage 
purchases. Under this and other authorities, HUD may offer bonus points 
for particular categories of mortgage purchase transactions.
    The Department proposes to introduce a system of bonus points to 
encourage the GSEs to increase their activity in underserved markets 
that serve lower-income families. The intent of bonus points is to 
encourage increased involvement by the GSEs over the 2000-2003 period 
in financing mortgages on small multifamily properties and mortgages on 
2-4 unit owner-occupied properties that contain rental units, for which 
the GSEs' mortgage purchases have traditionally played a minor role.
    Bonus points would be used in calculating goal performance under 
each of the affordable housing goals but would not apply in determining 
performance under the special affordable housing multifamily subgoal. 
All units counting toward a specific housing goal and, thus, included 
in the numerator of the fraction used to calculate goal performance 
under that particular housing goal would be eligible for bonus points 
provided that the units met the specific criteria for allowable bonus 
points. This provision would apply to all units included in the 
numerator even if a unit were missing affordability data and the 
missing affordability data were treated consistent with the proposal 
included in the following section II,B,6,b, ``Data on Unit 
Affordability.''
    (1) Bonus Point Proposal for Small Multifamily Properties. HUD 
proposes to add Sec. 81.16(c)(10)(1) to provide for the assignment of 
double weight in the numerator for each of the three housing

[[Page 12659]]

goals for units in small multifamily properties (5 to 50 units) that 
qualify under the goals. The GSEs purchase relatively few of these 
loans. Over the 1996-98 period, only eight percent of the units 
represented in the combined multifamily purchases of Fannie Mae and 
Freddie Mac were in properties in the 5-50 unit size range, compared to 
37 percent of units which are in 5-50 unit properties among all 
mortgaged multifamily properties in 1991 (based on the Residential 
Finance Survey). Loans of this type which are not purchased by the GSEs 
are often structured with adjustable-rate mortgages, or with fixed-rate 
financing involving interest rates that are as much as 150 basis points 
above those on standard multifamily loans. Targeting the GSEs toward 
these purchases could make these properties and the units in them more 
available and affordable.
    Awarding bonus points for these units would have increased Fannie 
Mae's and Freddie Mac's performance on the Low-and Moderate-Income 
Housing Goal by an average of 0.89 and 0.33 percentage points, 
respectively, over the 1996-98 period. Corresponding percentage point 
effects for the Special Affordable Housing Goal are 0.55 and 0.21 
percentage points, and for the Geographically Targeted Goal, 0.66 and 
0.21 percentage points for Fannie Mae and Freddie Mac, respectively. 
The impacts could be significantly larger in future years if such a 
bonus point framework provided a significant incentive for the GSEs to 
step up their role in financing small multifamily properties.
    (2) Counting Units in Small Multifamily Properties. Implementing 
this provision would require clear specification of the concept of a 
multifamily property relative to which the 5-50 unit limit for bonus 
points would be applied. The Department proposes to award bonus points 
for small multifamily properties to address the significant needs for 
their financing, both for properties that are underwritten and financed 
individually and for properties that are aggregated into larger 
financing packages. However, the Department further intends that bonus 
points will not be awarded for properties that are aggregated or 
disaggregated into 5-50 unit financing packages solely for the purpose 
of earning bonus points. Normally, a property is the land and 
improvements associated with one mortgage as defined in HUD's 
regulations. Ambiguity may arise in connection with GSE financings 
which are not cash or swap transactions involving mortgages. In such 
cases, or in other cases where a GSE believes that it would be 
appropriate to award bonus points in connection with a transaction, the 
GSEs should seek guidance from the Department concerning the 
delineation of properties associated with the financing and the 
consequent allowability of bonus points.
    (3) Bonus Points for Small Rental Properties. HUD further proposes 
to add Sec. 81.16(c)(10)(ii) to assign double weight in the numerator 
for each of the three housing goals for all units in 2- to 4-unit 
owner-occupied properties that qualify under the goals. Under this 
proposal, such units would receive bonus-point treatment to the extent 
that the number of such units financed by mortgage purchases are in 
excess of 60 percent of the average number of units qualifying for the 
respective housing goal during the immediately preceding five years. 
These loans represent a small portion of the GSEs' overall mortgage 
purchases although these units comprise a large percentage of the low-
income housing stock. Use of bonus points in this category could 
provide incentives for the GSEs to increase their purchases in 
underserved areas.
    The 60 percent threshold, if it were in effect for 1999 GSE 
mortgage purchases, would be set at the following levels:

------------------------------------------------------------------------
                                                       Fannie    Freddie
                                                      Mae (No.  Mac (No.
                                                         of        of
                                                       units)    units)
------------------------------------------------------------------------
Low- and Moderate-Income Housing Goal...............    26,294    16,971
Geographically Targeted Goal........................    25,193    14,889
Special Affordable Housing Goal.....................    12,720     8,564
------------------------------------------------------------------------

    The Department estimates that, if bonus points for small rental 
properties had been in effect during 1996-1998, Freddie Mac's goal 
percentages would have increased by 0.89 percentage point on the Low-
and Moderate-Income Housing Goal, 0.67 percentage point on the 
Geographically Targeted Goal, and 0.47 percentage point on the Special 
Affordable Housing Goal, based on average purchase volumes over this 
three-year period. Fannie Mae's goal percentages would have increased 
by 0.91 percentage point on the Low and Moderate Income Housing Goal, 
0.76 percentage point on the Geographically Targeted Goal, and 0.43 
percentage point on the Special Affordable Housing Goal.
    The purpose of bonus points is to encourage the GSEs to establish a 
larger and more consistent presence for the GSEs in targeted segments 
of the mortgage market. During the period that the goals under this 
proposal are effective, the Department will carefully monitor the 
effects of the bonus points approach in the housing categories in which 
they are being applied, to determine whether they are effective in 
incorporating the financing of properties targeted by the bonus points 
into the GSEs' mainstream activities. The Department does not plan to 
award bonus points to the GSEs after December 31, 2003, unless the 
Department specifically chooses to extend their availability in 
accordance with provisions of the rule.
    b. Subgoals. Alternatively, HUD is considering using subgoals to 
encourage the GSEs to undertake activities to address the unmet credit 
needs of groups or areas and/or to support public policy initiatives 
that are consistent with the GSEs' public purposes. HUD may establish 
subgoals under any of the three housing goals although HUD may only 
enforce subgoals under the Special Affordable Housing Goal.\65\ While 
FHEFSSA prohibits the enforcement of subgoals under the Low- and 
Moderate-Income Housing Goal or the Geographically Targeted Goal, the 
use of subgoals, whether or not they are enforceable, could encourage 
the GSEs to address unmet credit needs by directing the GSEs' and the 
public's attention on particular needs. For example, the special 
affordable housing multifamily subgoal has focused the GSEs' attention 
on special affordable multifamily activities.
---------------------------------------------------------------------------

    \65\ Section 1332(a) of the FHEFSSA grants HUD authority to 
``establish separate specific subgoals within the [Low- and 
Moderate-Income Housing] goal. * * *'' Section 1334(a) contains a 
similar provision for the Geographically Targeted Goal. Section 1333 
allows HUD to establish subgoals under the Special Affordable 
Housing Goal that are enforceable.
---------------------------------------------------------------------------

    In the 1995 rulemaking, HUD chose not to establish subgoals under 
either the Low- and Moderate-Income Housing Goal or the Geographically 
Targeted Goal, despite a number of comments urging the use of such 
tools. At that time, HUD expressed concern that the establishment of 
subgoals might be construed as micromanagement of the GSEs' business 
decisions at that relatively early post-FHEFSSA stage.\66\ However, 
since issuance of the 1996 to 1999 housing goals, HUD has conducted 
extensive analyses of the GSEs' operations under the housing goals, as 
well as the size and components of the primary mortgage market. Based 
on this analysis, HUD can better identify areas of unmet credit needs. 
Inasmuch as Congress, in FHEFSSA, explicitly authorized HUD to create 
subgoals--although they would be largely

[[Page 12660]]

unenforceable--and in light of increased experience under the goals, 
HUD requests comments on the extent to which HUD should utilize 
subgoals.
    c. Areas Under Consideration for Bonus Points and/or Subgoals. In 
addition to those areas described above, for which HUD proposes to 
award bonus points, HUD has identified several areas of unmet credit 
needs that could be addressed through the use of bonus points or 
subgoals, as appropriate. These areas are listed below, along with the 
possible rationale for taking such approach(es).
---------------------------------------------------------------------------

    \66\ See id.

BILLING CODE 4210-27-P

[[Page 12661]]

[GRAPHIC] [TIFF OMITTED] TP09MR00.006

BILLING CODE 4210-27-C

[[Page 12662]]

    In addition to the specific rule changes proposed above, the 
Department invites comment on the following:
    (1) Should HUD use either bonus points or subgoals to target 
mortgage purchases for one or more of the areas of concern identified 
above?
    (2) Would one or more of these areas benefit more from bonus points 
or the establishment of subgoals and why? If bonus points are 
suggested, what amount of bonus points should be assigned, and why?
    (3) Are there other areas not identified where bonus points and/or 
subgoals should be considered?
    6. Calculating Performance Under the Housing Goals. In the current 
regulation, HUD set forth general requirements for counting the GSEs' 
performance under the housing goals in Sec. 81.15, special counting 
requirements in Sec. 81.16 (including specific exclusions from 
eligibility in Sec. 81.16(b)), additional special requirements 
pertaining to counting under the Special Affordable Housing Goal in 
Sec. 81.14, and rules for classifying families and units into income 
ranges in Secs. 81.17-81.19. HUD's experience since the 1995 issuance 
of the current regulations indicates that several of these counting 
rules require clarification to ensure that they are understood and 
applied in a consistent manner and that the GSEs are achieving 
FHEFSSA's objectives. HUD invites comment on these clarifications and 
revisions described below.
    a. Temporary Adjustment Factor for Freddie Mac. In response to 
widespread default losses, Freddie Mac ceased purchasing multifamily 
mortgages for a period of time in the early 1990s. However, Freddie Mac 
significantly expanded its presence in the multifamily mortgage market 
in the period since HUD's Interim Housing Goals took effect at the 
beginning of 1993, with purchases totaling $191 million that year. 
Freddie Mac's purchases reached $6.6 billion in 1998 and $3.4 billion 
in the first six months of 1999.
    Despite this progress, Freddie Mac's presence in the multifamily 
market lags far behind that in single-family. Multifamily mortgages 
held in portfolio or guaranteed by Freddie Mac represented only 3 
percent of the outstanding stock of such mortgages as of the end of the 
third quarter of 1998, compared with 16 percent of single-family 
mortgages. Corresponding figures for Fannie Mae are 11 percent in 
multifamily and 21 percent in single-family.\67\
---------------------------------------------------------------------------

    \67\ Source: Federal Reserve Bulletin, March 1999, p. A35. HUD 
estimates that, in 1997, Freddie Mac acquired mortgages representing 
approximately 7 percent of the conventional multifamily market, 
compared with 17 percent of the conventional, conforming single 
family market. Corresponding estimates for Fannie Mae are 21 percent 
of multifamily and 31 percent of single family.
---------------------------------------------------------------------------

    Because of the importance of multifamily acquisitions to the GSE 
housing goals, the limited scope of Freddie Mac's multifamily 
acquisition volume has impaired its performance on HUD's housing goals. 
For example, while multifamily units accounted for only 8 percent of 
Freddie Mac's overall 1997 business, they accounted for 31 percent of 
units qualifying toward the Special Affordable Housing Goal, and 19 
percent of the units qualifying for the Low- and Moderate-Income Goal. 
Thus, improved performance by Freddie Mac on the housing goals will 
require strengthening its efforts in the multifamily mortgage market.
    To overcome any lingering effects of Freddie Mac's decision to 
leave the multifamily market in the early 1990s, it is reasonable for 
the Department to provide an incentive for Freddie Mac to further 
expand its scope of multifamily operations. The Department is proposing 
a ``Temporary Adjustment Factor'' for Freddie Mac's multifamily 
mortgage purchases for purposes of calculating performance on the Low- 
and Moderate-Income Housing Goal and the Special Affordable Housing 
Goal. In determining Freddie Mac's performance for each of these two 
goals, each unit in a property with more than 50 units meeting one or 
both of these two housing goals would be counted as 1.2 units in 
calculating the numerator of the respective housing goal percentage. 
The Temporary Adjustment Factor would be limited to properties with 
more than 50 units because of separate provisions regarding multifamily 
properties with 5-50 units, discussed separately in Section 
II,B,5,a,(1).
    The Temporary Adjustment Factor would terminate December 31, 2003. 
The Adjustment Factor would not be applied to the Geographically 
Targeted Goal. The Adjustment Factor would not apply to Fannie Mae.
    The Department estimates that, if the Temporary Adjustment Factor 
were in effect during 1996-1998, it would have raised Freddie Mac's 
performance on the Low- and Moderate-Income Housing Goal by 1.52 
percentage points and the Special Affordable Housing Goal by 0.86 
percentage points.
    HUD specifically requests comments on whether the proposed 
temporary adjustment factor for Freddie Mac is set at an appropriate 
level, and if such an adjustment factor should be phased out prior to 
2003 or apply for the entire four year cycle.
    b. Data on Unit Affordability. As indicated in Sec. 81.15(a), each 
GSE must obtain all required information to determine whether units 
financed by the GSE purchased mortgages that qualify for one or more of 
the goals. If any of the information is missing, the GSEs must exclude 
the mortgage purchase from the numerator as not qualifying but they 
must include the mortgage in the denominator as a mortgage purchase in 
calculating performance under a housing goal.\68\ The Senate Report on 
FHEFSSA noted the presence of an ``information vacuum'' with regard to 
the GSEs' mortgage purchases, indicating Congress' intention that the 
Department require accurate and comprehensive data regarding the GSEs' 
mortgage purchases for purpose of measuring compliance with the housing 
goals.\69\ Therefore, the Department is committed to maintaining a 
complete and fully reliable loan level data base of the GSEs' mortgage 
purchases.
---------------------------------------------------------------------------

    \68\ Purchases of mortgages originated prior to 1993 with 
missing data may be excluded from the denominator.
    \69\ See Sen. Rep. at 33.
---------------------------------------------------------------------------

    The GSEs have indicated that, for certain single family and 
multifamily mortgage purchases, it is difficult, and therefore costly, 
to obtain the necessary data on incomes and rents for all units 
associated with their mortgage purchases, especially for seasoned loan 
transactions and some negotiated transactions. The GSEs have requested 
the authority to use estimation techniques to approximate the unit 
rents in multifamily properties where current rental information is 
unavailable and to exclude units from the goal calculations where it is 
impossible to obtain full data or estimate values.
    While providing the GSEs relief from the requirement to obtain 
rental data would remove an incentive to collect such information, the 
Department recognizes that the lack of such data in the mortgage market 
poses potentially insurmountable difficulties for the GSEs for a 
portion of their mortgage purchases. The Department, therefore, 
proposes the following measures for treatment of cases where a GSE does 
not obtain full data. The Department seeks comments on these proposals 
and welcomes suggestions for alternative ways of addressing the issue.
    (1) Multifamily Rental Units. For purposes of counting rental units

[[Page 12663]]

toward achievement of the Low- and Moderate-Income Housing Goal and the 
Special Affordable Housing Goal, the current regulation requires that 
mortgage purchases financing eligible units be evaluated based on 
either the income of the tenant, or where this information is unknown, 
on the actual or average rent relative to area median income, as of the 
time the mortgage was acquired.\70\ The GSEs generally use rental data 
in calculating goal achievement.
---------------------------------------------------------------------------

    \70\ 24 CFR 81.15(e). Rental information may be presented for 
type-of-unit categories identified by number of bedrooms and average 
rent level.
---------------------------------------------------------------------------

    For units in multifamily properties (five or more units), the 
Department proposes to allow the use by a GSE of estimated rents based 
on market rental data. The Department will review and approve the GSEs' 
data sources and methodologies for estimating rents on multifamily 
units prior to their use, to assure reliability. Rental data submitted 
to the Department based on an estimation shall be so identified by the 
GSE. HUD requests comments on whether it should establish a percentage 
ceiling for the GSEs' use of estimated data for multifamily mortgage 
purchases.
    The Department further proposes to exclude units in multifamily 
properties from the denominator as well as the numerator in calculating 
performance under the Low- and Moderate-Income Housing Goal and the 
Special Affordable Housing Goal when sufficient information is not 
available to determine whether the purchase of a mortgage originated 
after 1992 counts toward achievement of the goal, and when the 
application of estimated rents based on an approved market rental data 
source and methodology is not possible. HUD requests comments on 
whether it should establish a percentage ceiling for the exclusion of 
multifamily units with missing data from the denominator for goal 
calculation purposes when estimated rents are not available. Because a 
relatively large portion of multifamily units count toward the Low- and 
Moderate-Income Housing Goal and the Special Affordable Housing Goal, 
an incentive for the GSEs to provide affordability data would remain in 
place even if such data were excluded from the denominator without 
limitation.
    (2) Single Family Rental Units. For purposes of counting rental 
units in 1-4 unit single family properties toward achievement of the 
Low- and Moderate-Income Housing Goal and the Special Affordable 
Housing Goal, the Department proposes to exclude the rental units in 1-
4 unit properties from the denominator as well as the numerator in 
calculating performance under the Low- and Moderate-Income Housing Goal 
and the Special Affordable Housing Goal when sufficient information is 
not available to determine whether the purchase of a mortgage 
originated after 1992 counts toward achievement of the Low- and 
Moderate Income Housing Goal or the Special Affordable Housing Goal. 
HUD requests comments on whether it should establish a percentage 
ceiling for the exclusion of single family rental units with missing 
data from the denominator for goal calculation purposes when estimated 
rents are not available. Because a relatively large proportion of 
rental units in 1-4 unit single family properties count toward the Low- 
and Moderate-Income Housing Goal and the Special Affordable Housing 
Goal, an incentive for the GSEs to provide affordability data would 
remain in place even if such data were excluded from the denominator 
without limitation.
    (3) Single Family Owner-Occupied Units. For purposes of counting 
single family owner-occupied units toward achievement of the Low- and 
Moderate-Income Housing Goal and the Special Affordable Housing Goal, 
the current regulation requires that mortgage purchases financing 
eligible owner units be evaluated based on the income of the owner 
relative to area median income, as of the time the mortgage was 
originated.\71\
---------------------------------------------------------------------------

    \71\ 24 CFR 81.15(d).
---------------------------------------------------------------------------

    The Department proposes to allow a GSE to exclude certain single 
family owner-occupied units from the denominator as well as the 
numerator in calculating performance under the Low- and Moderate-Income 
Housing Goal when the GSE lacks sufficient information on borrower 
income to determine whether the purchase of a mortgage originated after 
1992 counts toward achievement of the goal, provided the mortgaged 
property is located in a census tract with median income less than or 
equal to area median income according to the most recent census. Such 
exclusion from the denominator and numerator will be permitted up to a 
ceiling of one percent (1%) of the total number of single family, 
owner-occupied dwelling units eligible to be counted toward the 
respective housing goal in the current year. Mortgage purchases in 
excess of the ceiling will be included in the denominator and excluded 
from the numerator.
    HUD's analysis of GSE loan-level data indicates that the share of 
single-family owner-occupied units qualifying for the Low- and Moderate 
Income Housing Goal and the Special Affordable Housing Goal is 
significantly higher in tracts with median income less than or equal to 
area median income (``low-mod tracts'') than in other tracts, and is in 
fact higher than the GSEs'' overall goals performance across all 
property types. Consequently, excluding such units from the numerator 
and denominator in cases where income data are missing is unlikely to 
result in measured goals performance exceeding actual goals 
performance.
    c. Seasoned Mortgage Loan Purchases ``Recycling'' Requirement. 
Under section 1333(b)(1)(B) of FHEFSSA, special rules apply for 
counting purchases of portfolios of seasoned mortgages under the 
Special Affordable Housing Goal. Specifically, the statute requires 
that purchases of seasoned mortgage portfolios receive full credit 
toward the achievement of the Special Affordable Housing Goal if ``(i) 
the seller is engaged in a specific program to use the proceeds of such 
sales to originate additional loans that meet such goal; and (ii) such 
purchases or refinancings support additional lending for housing that 
otherwise qualifies under such goal to be considered for purposes of 
such goal.'' \72\ HUD refers to this provision as the ``recycling 
requirement.''
---------------------------------------------------------------------------

    \72\ 12 U.S.C. 4563(b)(1)(B).
---------------------------------------------------------------------------

    Section 81.14(e)(4)(i) of HUD's regulations clarify the meaning of 
the phrase ``engaged in a specific program to use the proceeds of such 
sales to originate additional loans that meet'' the Special Affordable 
Housing Goal by providing that:

    [A] seller must currently operate on its own or actively 
participate in an ongoing program that will result in originating 
additional loans that meet the goal. Actively participating in such 
a program includes actively participating with a qualified housing 
group that operates a program resulting in the origination of loans 
that meet the requirements of the goal.

    Section 81.14(e)(4)(ii) provides that the GSEs must verify and 
monitor that the seller is engaging in a specific program to use the 
proceeds of such sales to originate additional loans that meet the 
Special Affordable Housing Goal.
    Based on a review of the GSEs' performance under the Special 
Affordable Housing Goal, the Department believes further guidance is 
needed with regard to the recycling requirements described above to 
ensure that mortgage purchases granted full credit under this provision 
satisfy the purposes of FHEFSSA and, at the same

[[Page 12664]]

time, to ensure that the rules are applied so as to avoid any 
unnecessary regulatory burden. The Department, therefore, proposes to 
amend its regulations to further explain the requirements for the GSEs 
to receive full credit under these provisions and to establish new, 
simpler rules when it is evident based on the characteristics of a 
mortgage seller, including the seller's legal responsibilities, that 
the recycling requirements are met. The new rules would provide that 
for a mortgage purchase to meet the recycling requirements:
    (1) The seller must currently operate on its own or actively 
participate in an on-going, discernible, active, and verifiable program 
directly targeted at the origination of new mortgage loans that qualify 
under the Special Affordable Housing Goal.
    (2) The seller's activities must evidence a current intention or 
plan to reinvest the proceeds of the sale into mortgages qualifying 
under the Special Affordable Housing Goal, with a current commitment of 
resources on the part of the seller to this purpose.
    (3) The seller's actions must evidence willingness to buy 
qualifying loans when these loans become available in the market as 
part of active, on-going, sustainable efforts to ensure that additional 
loans that meet the goal are originated. Actively participating in such 
a program includes purchasing qualifying loans from a correspondent 
originator, including a lender or qualified housing group, that 
operates an on-going program resulting in the origination of loans that 
meet the requirements of the goal, has a history of delivering, and 
currently delivers, qualifying loans to the seller.
    Under this proposed rule, as under the current requirements, the 
GSEs must ordinarily verify and monitor that sellers meet the foregoing 
requirements and develop any necessary mechanisms to ensure compliance 
with these requirements. However, HUD does not believe that the efforts 
of the GSEs are well spent on monitoring compliance when, because of 
the nature and responsibilities of particular sellers, it is clear that 
the seller meets the recycling requirements. For this reason, the rule 
proposes that an institution that is (1) regularly in the business of 
mortgage lending; (2) a BIF-insured or SAIF-insured depository 
institution; and (3) subject to, and has received at least a 
satisfactory performance evaluation rating for at least the two most 
recent consecutive examinations under, the Community Reinvestment 
Act,\73\ (which requires affordable lending), would meet the recycling 
requirements. The nature of such an institution's business and 
regulatory responsibilities require it to engage in a program that 
satisfies the recycling provisions. This rule, therefore, proposes that 
HUD and the GSEs may presume that such institutions, classified by the 
appropriate ``Type of Seller Institution'' data element, meet the 
recycling requirements.
---------------------------------------------------------------------------

    \73\ 12 U.S.C. 2901 et seq.
---------------------------------------------------------------------------

    Moreover, in the interest of further reducing unnecessary 
regulatory burden, HUD believes that there are certain additional 
classes of institutions or organizations that should be recognized as 
meeting the recycling requirements. For example, classes of 
institutions whose primary businesses are financing affordable housing 
mortgages, including possibly State Housing Finance Agencies or Special 
Affordable Housing Loan Consortia. For such classes of institutions or 
organizations, HUD is proposing that the GSEs may presume that they 
meet the recycling requirements. Classes of institutions or 
organizations must be approved by the Department and be appropriately 
identified in the GSEs' data submissions. Commenters are invited to 
provide their views on how to identify and define such classes of 
organizations or institutions.
    In addition to specific changes proposed, commenters are invited to 
share their views as to whether any additional exemptions or changes to 
this provision should be established under the recycling provisions 
that would further its purpose. Comments are also specifically invited 
on (1) what, if any, provisions should be included in the proposed rule 
to address the various affiliate structures of depository institutions; 
and (2) the treatment under the recycling provisions of structured 
transactions where the mortgage loans included in the transaction were 
originated by a depository institution or mortgage banker engaged in 
mortgage lending on special affordable housing but acquired, packaged 
and re-sold by a third party, e.g., an investment banking firm, that is 
not in the business of affordable housing lending.
    An additional matter concerns the appropriate interpretation of 
Sec. 81.16(c)(6) for counting seasoned mortgages. During the last four 
years, both GSEs have asserted that HUD's regulations permit the 
exclusion of purchases of seasoned mortgages from the denominator as 
well as from the numerator when the recycling requirements have not 
been met or when the status of loans with respect to this provision is 
unknown.
    The GSEs believe that the regulation should be interpreted to mean 
that purchases of seasoned loans should not count in the denominator in 
calculating Special Affordable Housing Goal performance if the 
recycling requirements of section 1333(b)(1)(B) are not satisfied. The 
GSEs maintain that this provision defines whether such loans are 
``mortgage purchases'' and thus, whether they are to be included in the 
denominator. As a result of this interpretation, Fannie Mae chooses not 
to undertake the verification and monitoring required to track 
compliance with the recycling provision and excludes the purchases from 
the denominator based on its lack of information. Freddie Mac chooses a 
similar treatment for those seasoned loans it does not count toward its 
Special Affordable Housing Goal performance.
    In calculating its 1996 and 1997 performance under the Special 
Affordable Housing Goal, Fannie Mae excluded all seasoned loan 
purchases from both the numerator and the denominator for purposes of 
reporting its goals performance to HUD. The effect of this action was 
to reduce the denominator by 212,290 units in 1996 and 197,074 units in 
1997, with the result that Fannie Mae considered its goal figures to be 
two percentage points higher than HUD's determination in 1996 and 2.15 
percentage points higher in 1997. Freddie Mac counted most of its 
seasoned loan purchases towards the Special Affordable Housing Goal 
and, thus, there was only a marginal impact on its goal performance.
    The Department has consistently maintained that the GSEs are 
required to count all mortgage purchases in the denominator. HUD's 
rules only permit the GSEs to exclude mortgages from the denominator 
under explicit circumstances. See Secs. 81.15(a) and 81.16(b). As we 
have stated, the legislative history of FHEFSSA emphasizes the 
importance of accurate and comprehensive data.\74\ On the other hand, 
experience indicates that incentives for the GSEs to gather accurate 
and comprehensive data may encourage the GSEs, in some instances, to 
avoid certain purchases altogether in order to keep such purchases out 
of their denominator, notwithstanding that such purchases may meet the 
other goals. Accordingly, while HUD has in the past disagreed with the 
GSEs' interpretation of its current rules, the Department is now 
proposing to consider the possibility of limited exceptions to the 
general rule where it

[[Page 12665]]

would be beneficial for the GSEs to purchase certain mortgages that 
simply will not meet recycling requirements, without having their goals 
performance effectively reduced by including the purchases in the 
denominator. An example would be a GSE's purchase of low- or moderate-
income loans from a mortgage seller that enters and then leaves the 
affordable lending business. Such an entity may not meet the recycling 
requirements as a statutory matter because the seller would no longer 
be ``engaged in a specific program to use the proceeds of such sales to 
originate additional loans that meet the goal.'' \75\ However, a GSE's 
willingness to purchase such mortgages may cause other originators to 
embark on affordable lending secure that the GSE will provide a 
secondary market for these loans.
---------------------------------------------------------------------------

    \74\ See Sen. Rep. at 33.
    \75\ 12 U.S.C. 4563(b)(1)(B).
---------------------------------------------------------------------------

    To encourage affordable lending, this rule proposes to permit the 
Department in certain cases or classes of cases to allow the GSEs to 
exclude mortgages from the numerator and the denominator under the 
Special Affordable Housing Goal when the Department determines that 
such treatment serves to encourage the GSEs' mortgage purchases to 
further the purposes of the goal. To implement this change, HUD 
proposes to revise the language in Sec. 81.16(c)(6) so that the 
Department may permit the exclusion of cases or classes of cases of 
purchases of seasoned mortgage loans from the numerator and the 
denominator in a GSE's calculations of performance under the Special 
Affordable Housing Goal when the Department determines such purchases 
further the purposes of the goal. The rule proposes that the GSE may 
request such treatment in writing and that the Department will respond 
to such request following the Department's determination. Commenters 
are specifically asked for their views regarding whether the Department 
should adopt this exclusion and, if so, what, if any, limits should be 
placed on it. To implement this change, HUD proposes to revise the 
language in Sec. 81.16(c)(6) so that the Department may permit the 
exclusion of cases or classes of cases of purchases of seasoned loans 
from the numerator and the denominator in a GSE's calculations of 
performance under the Special Affordable Housing Goal when the 
Department determines such purchases further the purposes of the goal. 
The rule proposes that the GSE may request such treatment in writing 
and the Department will respond to such request following the 
Department's determination. Commenters are specifically asked for their 
views regarding whether the Department should adopt this exclusion and, 
if so, what, if any, limits should be placed on it.
    d. Counting Federally Insured Mortgages Including HECMs, Mortgages 
on Housing in Tribal Areas and Mortgages Guaranteed by the Rural 
Housing Service Under the Housing Goals. Under HUD's current rules, 
non-conventional mortgages--mortgages that are guaranteed, insured or 
otherwise obligations of the United States--do not generally count 
under the three housing goals. (Sec. 81.16(b)(3)) Certain of these 
mortgages--including under the Home Equity Conversion Mortgage (HECM) 
Program, 12 U.S.C. 1715z-20, and the Farmers Home Administration's (now 
the Rural Housing Service's [RHS's]) Housing Loan Program--do, however, 
count under the Special Affordable Housing Goal. FHEFSSA specifically 
provides that mortgages that cannot be readily securitized through GNMA 
or another Federal agency and where a GSE's participation substantially 
enhances the affordability by statute receive full credit under the 
Special Affordable Housing Goal. On this basis, these two categories of 
mortgages count under that goal if they are for very low-income 
families or low-income families in low-income areas.
    HECMs provide an important source of funds for senior citizens, 
especially those with lower incomes, who have paid off most or all of 
the mortgages on their homes and who wish to draw on the equity in 
their home to pay unanticipated expenses or to maintain a higher 
standard of living than they could support from their current income 
alone. Under HUD's HECM program they can do this without selling or 
risking the loss of their home. Fannie Mae has played a major role in 
the secondary market for HECMs, purchasing 5800 such loans in 1997 and 
6700 such loans in 1998. Freddie Mac has not been involved in this 
program to date; inclusion of these loans for possible credit under all 
three of the housing goals will provide an incentive for them to play a 
role in the HECM market.
    RHS loans are especially important to cash-strapped families in 
rural areas, since loan-to-value ratios can be as high as 100 percent. 
And the RHS's new Section 502 Direct Loan program is targeted to low-
income and especially low-income families. Both GSEs have been involved 
in this market, with Fannie Mae purchasing 1600 such loans in 1997 and 
2100 such loans in 1998, and Freddie Mac sharply stepping up its 
presence from 1400 such loans in 1997 to 3300 such loans in 1998. The 
GSEs also assist the RHS in outreach through the development of 
promotional and advertising materials.
    One other area the Department is considering counting for goal 
credit are loans made to Native Americans under FHA's Section 248 
program and HUD's Section 184 program. The paucity of home mortgage 
lending on American Indian reservations and trust lands has been well 
documented. Secretary Cuomo, in his remarks accompanying President 
Clinton to the Pine Ridge Indian Reservation in South Dakota, recently 
commented that ``The descendants of the first Americans shouldn't be 
locked out of the American Dream of homeownership.'' Allowing goal 
credit for FHA's Section 248 loans and HUD's Section 184 loans on 
reservations and trust lands will provide some support for these 
programs, though much greater efforts will be needed to make this dream 
of homeownership a reality.
    Nonetheless, based upon its review of data on the GSEs mortgage 
purchases, HUD has concluded that HECMs, RHS mortgages and loans made 
to Native Americans under FHA's Section 248 program and HUD's Section 
184 program comprise very small shares of the GSEs' business. At the 
same time, the properties secured by these mortgages present 
substantial and growing financing needs. Accordingly, while HUD 
maintains that non-conventional mortgages should be excluded under the 
goals where financing needs are already met by government programs, the 
Department also believes that non-conventional loans may count where 
financing needs are not well served. In such cases the goals will serve 
to direct the GSEs toward these needs. Accordingly, HUD proposes to 
amend its rules at Sec. 81.16(b)(3) to except mortgages under the HECM 
program, mortgages guaranteed by RHS, and loans made under FHA's 
Section 248 program and HUD's Section 184 program on properties in 
tribal lands from the general exclusion under the rules for non-
conventional loans. In addition, the rule allows the Department to 
count mortgage purchases under other non-conventional mortgage 
program(s) to count under the goals where the Department determines, in 
writing, that the financing needs addressed by such program are not 
well served and that mortgage purchases under such program should 
count. The proposed rule provides that where non-conventional mortgage 
purchases will now count toward the goal, they no longer will be

[[Page 12666]]

excluded from the denominator of the GSEs' mortgage purchases as are 
other non-conventional loans.
    e. Counting Title I Loans. During the transition period, from 1993 
to 1995, HUD explicitly provided that home improvement and manufactured 
home loans for which lenders are insured under HUD's Title I program 
received half credit toward all three housing goals for which they 
qualified. \76\ Following the transition period, HUD's 1995 final rule 
provided that, in accordance with section 1333(b)(1)(A) FHEFSSA, GSE 
purchases of non-conventional mortgages do not count toward the housing 
goals.\77\ The exception to the rule is that Federally-related 
mortgages may receive full credit toward the Special Affordable Housing 
Goal if the mortgages would otherwise qualify for the goal, the 
Government National Mortgage Association (Ginnie Mae) cannot readily 
securitize them, and participation by the GSE substantially enhances 
their affordability.\78\
---------------------------------------------------------------------------

    \76\ Fannie Mae continued to count half credit for Title 1 
purchases during 1996 through 1998.
    \77\ Section 81.16(b)(3).
    \78\ Section 81.14(e)(2).
---------------------------------------------------------------------------

    In a pilot program initiated between July 1996 and July 1997, 
Ginnie Mae was not successful in securitizing Title I loans. Moreover, 
while HUD has not analyzed whether GSE participation in these loans 
enhances their affordability, the pricing efficiencies that result from 
the securitization of mortgages suggest that an affordability analysis 
would be favorable.
    Under the circumstances, HUD is proposing to amend Sec. 81.14 to 
explicitly allow the GSEs to receive half credit for Title I loans 
under the Special Affordable Housing Goal. Units financed with Title I 
loans would be included at 100 percent (each unit counts as such) in 
the Special Affordable Housing Goal denominator, and included at 50 
percent (each unit counts as such) in the Special Affordable Housing 
Goal numerator when they otherwise qualify for that goal. However, 
units financed with Title I loans would be excluded from the numerator 
and denominator in both the Low- and Moderate-Income Housing Goal and 
the Geographically Targeted Goal.\79\
---------------------------------------------------------------------------

    \79\ 12 U.S.C. 4563(b)(1)(A)(ii).
---------------------------------------------------------------------------

    f. Defining the Denominator. Section 81.15(a) of the 1995 final 
rule defines the denominator as ``the number of dwelling units that 
could count toward achievement of the goal under appropriate 
circumstances.'' HUD proposes to clarify this provision further by 
adding language to Sec. 81.15 that specifically provides that the 
denominator shall not include GSE transactions or activities that are 
not mortgages or that are mortgage purchases or transactions which are 
specifically excluded as ineligible under Sec. 81.16(b) of the 
regulations.
    g. Balloon Mortgages. Single family mortgage refinances that result 
from the conversion of balloon notes to fully amortizing notes shall 
not count as mortgage purchases where the GSE already owns or has an 
interest in the balloon note at the time the conversion occurs and the 
GSE owns or has an interest in the fully amortizing note. Such 
conversions shall not be treated as a refinancing and shall not be 
counted in the numerator or denominator in calculating goal 
performance. Refinancings of balloon mortgages not owned by the GSE 
will be included in the denominator and numerator as appropriate. To 
implement this change to the special counting requirements, HUD 
proposes to revise the definition of ``Refinancing'' in Sec. 81.2 to 
specifically exclude the conversion of balloon mortgages on single 
family properties and to add this provision to the special counting 
requirements in Sec. 81.16.
    h. Expiring Assistance Contracts. Section 517(c) of the Multifamily 
Assisted Housing Reform and Affordability Act of 1997 \80\ (the 1997 
Act) provides that actions taken to assist in maintaining the 
affordability of assisted units in eligible multifamily housing 
projects with expiring Section 8 contracts ``shall constitute part of 
the contribution of each [GSE] in meeting its affordable housing goals 
* * *, as determined by the Secretary.'' The Department is proposing to 
add a provision to Sec. 81.16 that provides partial or full credit for 
such actions. ``Actions'' under the 1997 Act relevant to the GSEs would 
include the restructuring or refinancing of mortgages, and credit 
enhancements or risk-sharing arrangements to modified or refinanced 
mortgages. Comments are invited on how and to what extent the GSEs 
should receive credit for such actions.
---------------------------------------------------------------------------

    \80\ Title V of HUD's 1998 Appropriations Act, Pub. L. 105-65, 
approved October 27, 1997.
---------------------------------------------------------------------------

     i. Especially Low Income. In accordance with section 1333 of 
FHEFSSA, Sec. 81.14(d)(1)(i) currently provides that dwelling units in 
a multifamily property will count toward the Special Affordable Housing 
Goal if 20 percent of the units are affordable to families whose 
incomes do not exceed 50 percent of the area median income. Sections 
81.17 through 81.19 provide that the income requirements are to be 
adjusted based on family size, and provide such adjustments for 
moderate-income families (income not in excess of 100 percent of area 
median income), low-income families (income not in excess of 80 percent 
of area median income), and very low-income families (income not in 
excess of 60 percent of area median income); but there is no similar 
adjustment table provided for families whose incomes do not exceed 50 
percent of area median income. While such adjustments could be 
extrapolated from the adjustment tables provided in Secs. 81.17 through 
81.19, in order to assist the public, this rule proposes to amend these 
sections to provide additional adjustment tables for such families. In 
the interests of consistency, this rule also proposes to designate such 
families as ``especially low-income families'' for purposes of the 
Department''s GSE regulations. Section 81.14 of the proposed rule is 
amended to make such a designation.
     j. Provision for HUD to Review New Activities to Determine 
Appropriate Counting Under the Housing Goals. While the GSEs 
participate in transactions and activities that support community and 
housing development in general, FHEFSSA is clear that only ``mortgage 
purchases'' count toward performance on the housing goals.\81\ HUD's 
regulations provide that HUD will determine whether a transaction or 
activity is a ``mortgage purchase'' and will therefore count toward one 
or more of the goals for which it qualifies. Section 81.16 of the 
current regulations provides that in determining whether a GSE will 
receive full credit toward one or more of the goals for a transaction 
or activity, the Department will consider whether the transaction or 
activity ``is substantially equivalent to a mortgage purchase and 
either creates a new market or adds liquidity to an existing market.''
---------------------------------------------------------------------------

    \81\ See Sen. Rep. at 38.
---------------------------------------------------------------------------

    As provided in Sec. 81.16(b), HUD has determined that certain 
transactions do not meet those criteria and therefore will not count 
toward a GSE's performance toward the housing goals (e.g., equity 
investments in housing development projects; commitments, options, or 
rights of first refusal to acquire mortgages; state and local 
government housing bonds; and non-conventional mortgages, except under 
certain circumstances); such purchases are not included in the 
numerator or the denominator. HUD has also provided guidelines in the 
regulations for the treatment of other types of transactions, such as 
credit enhancements, real estate mortgage investment conduits

[[Page 12667]]

(REMICs), risk-sharing arrangements, participations, cooperative 
housing and condominiums, seasoned mortgages, refinanced mortgages, and 
mortgage revenue bonds.
    In meeting the goal levels proposed here the GSEs will need to 
continue to develop products and approaches to close the gap between 
their performance and that of the primary mortgage market. In doing so, 
however, HUD and the GSEs must be mindful of FHEFSSA's requirements. 
Since only mortgage purchases count under the goals, this rule proposes 
new requirements to ensure timely guidance to the GSEs regarding new 
approaches or new types of transactions. Under the proposed revisions, 
in order to eliminate confusion about whether a given transaction will 
receive credit under the housing goals, the GSEs may provide 
information about specific transactions to the Department for 
evaluation and a determination of whether the transaction will receive 
full, partial, or no credit. The Department may also continue to 
independently request information of the GSEs about certain types of 
mortgage transactions. The Department will review the transactions to 
ensure that the counting of such transactions under the housing goals 
is consistent with FHEFSSA and advise the GSEs of the Department's 
determination with regard to credit for purposes of counting such 
transactions under the housing goals. This proposed rule amends 
Sec. 81.16 to further clarify this point.
    k. Credit Enhancements. The GSEs utilize a large variety of credit 
enhancements, for both single family and multifamily mortgage 
purchases, to reduce the credit risk to which they might otherwise be 
exposed. For example, the GSEs generally require the use of mortgage 
insurance on single-family loans with loan-to-value ratios exceeding 80 
percent. While more common in the multifamily mortgage market, seller-
provided credit enhancements may also be required for GSE purchases of 
single family mortgage loans when mortgage insurance is not carried on 
individual mortgage loans. Other types of credit enhancements include:
    (1) Credit enhancements in structured transactions where a GSE may 
acquire a pool of loans, mortgage-backed securities (MBS), or real 
estate mortgage investment conduits (REMICs), and then create separate 
senior and subordinated securities, structured so that the subordinated 
securities absorb credit losses. The senior securities are guaranteed 
by the GSE; the subordinated securities are not.
    (2) Spread accounts, in which a GSE may create a special class of 
unguaranteed securities where pass-through payments will cease in the 
event of default of the underlying mortgage collateral. Proceeds from 
the sale of such securities provide a degree of protection against 
credit losses. Such transactions differ from structured transactions in 
that no senior securities are explicitly created. Freddie Mac's 1998 
``MODERNs'' transactions are an example.\82\
---------------------------------------------------------------------------

    \82\ ``MODERN'' is an acronym for Mortgage Default Recourse 
Notes. See ``Freddie Mac Trying Hand at One of Fastest Growing 
Practices in Mortgage Business: Captive Reinsurance,'' Inside 
Mortgage Finance, June 26, 1998, pp. 3; ``New Details on Freddie 
Mac's Novel MODERNS Transactions Emerge: 27% Coverage on All 
Defaults,'' Inside MBS & ABS, June 19, 1998.
---------------------------------------------------------------------------

    (3) Acquisition of senior tranches of REMIC securities. In these 
transactions, the GSEs acquire senior tranches of REMICs which are 
enhanced by the presence of subordinate tranches. These senior tranches 
typically receive an investment-grade rating from one of the major 
rating agencies. A difference between this type of transaction and the 
structured transactions described above is that when the GSEs purchase 
a senior tranche, the collateral is already credit-enhanced prior to 
purchase.
    (4) Agency pool insurance. A GSE reduces its exposure if insurance 
is provided by a mortgage seller on a pool of single family mortgage 
loans which may also individually carry mortgage insurance.
    In its recent report titled ``HUD's Implementation of Its Mission 
Oversight Needs to Be Strengthened,'' dated July 28, 1998, GAO reviewed 
the effectiveness of HUD's regulation of the GSEs. As part of that 
report, GAO commented on the Department's treatment of credit 
enhancements under the current rule. GAO noted that by allocating full 
credit toward the housing goals on multifamily mortgages with seller 
provided credit enhancements, through which the seller of mortgages 
retains some of the credit risk on mortgages, HUD may be providing a 
``regulatory incentive'' for the GSEs to utilize such enhancements.\83\ 
These credit enhancements typically take the form of recourse to the 
seller or loss-sharing agreements between the seller and the GSE 
purchasing the mortgage.
---------------------------------------------------------------------------

    \83\ HUD's Implementation of Its Mission Oversight Needs to Be 
Strengthened, page 29 (GAO/GGD-98-173, July 28, 1998).
---------------------------------------------------------------------------

    The GAO commented further that HUD's treatment of mortgage 
purchases involving credit enhancements under the housing goals appears 
inconsistent with HUD's treatment of mortgages acquired by the GSEs 
under a risk-sharing program with FHA. Under Sec. 81.16(c)(3) of the 
regulation, the GSEs receive housing goal credit for mortgage purchases 
under a risk-sharing arrangement only where the GSEs bear at least 50 
percent of the credit risk. GAO noted that no similar requirement 
pertains to mortgages for which sellers provide credit enhancements, 
even, hypothetically, where a seller would bear 100 percent of the 
credit risk.
    HUD responded that GSE credit enhancement transactions provide 
liquidity. Moreover, seller provided credit enhancements differ from 
the FHA risk-sharing program in that seller provided credit 
enhancements include an element of counterparty risk; in the sense 
that, in the event of default, some sellers lack the financial 
resources to fulfill their commitment to repurchase a loan or otherwise 
share in default losses.
    In considering the treatment of credit enhancements, HUD invites 
comments on the following questions:
    (i) Given the wide range of institutional arrangements pertaining 
to credit enhancements and the interrelationships between credit 
enhancements and other considerations such as loan-to-value ratio and 
guarantee fee, how might the credit risk to which the GSEs are exposed 
be measured under various types of credit enhancement scenarios?
    (ii) Assuming credit risk can be adequately measured, should HUD 
give partial credit under the housing goals when credit enhancements 
result in a substantial portion of the credit risk of the transaction 
being borne by the seller or a third party? For example, if the GSE 
bears less than 50 percent of the credit risk of a transaction should 
the GSE receive no credit toward housing goal performance? If the GSEs 
assume between 50 percent and 75 percent of the credit risk of a 
transaction, should the GSE receive 50 percent credit for housing goal 
purposes?
    (iii) What would be the advantages and disadvantages of linking the 
amount of goals credit on a GSE mortgage purchase to the degree of 
associated credit risk? What are the possible effects on low-and 
moderate-income families and on underserved areas of the GSEs' use of 
various credit enhancements and how might they be affected if goals 
credit were linked to the degree of associated credit risk? Would there 
be potential effects on liquidity or other mortgage market factors?
    (iv) Assuming credit risk can be adequately measured, should HUD 
establish a minimum percentage in the range of 0 to 100 percent for the 
amount of credit risk borne by the GSEs on their

[[Page 12668]]

mortgage purchases in order for such purchases to count toward the 
housing goals?
    (v) If HUD establishes a minimum threshold for credit risk, should 
it be the same for multifamily and single family purchases, or should 
it be different for each? At what level should the threshold(s) be 
established? Should HUD establish the same threshold for all types of 
credit enhancements, or should this differ between types of credit 
enhancements? At what level should the threshold(s) be established?
    (vi) Should HUD measure counterparty risk on seller-provided credit 
enhancements? If so, how?
    (vii) Should HUD evaluate GSE performance in relation to the use of 
credit enhancements by calculating and comparing the risk-adjusted rate 
of return under the use of various credit enhancement alternatives?
    1. High Cost Mortgage Loans. There is ample evidence that high cost 
mortgage lending and abusive lending practices increase defaults, have 
destabilizing effects on neighborhoods, and adversely affect 
homeownership. High cost mortgage loans characterized by high interest 
rates and front-end fees are often coupled with requirements for 
balloon payments, negative amortization, prepayment penalties, and lump 
sum credit life insurance. Loans with these features sometimes are 
characterized as ``predatory; while they may prove profitable to some 
originators, they quickly erode home equity for unwary borrowers. 
Evidence suggests that high cost loans are often the product of 
``reverse redlining;'' these loans tend to target low-income 
communities and elderly, minority, and immigrant borrowers who have 
traditionally been denied access to mainstream sources of credit.
    In 1994, Congress addressed many abuses in the primary market with 
the Home Ownership and Equity Protection Act (HOEPA), which provides 
special disclosures and protections for borrowers of certain high cost 
refinance mortgages. (15 U.S.C. 1639) To be subject to HOEPA's 
requirements, mortgage loans covered under the law must have: (1) An 
annual percentage rate at least 10 points higher than the yield on 
Treasury securities with comparable maturity to the transaction; or (2) 
total points and fees payable by the consumer in excess of the greater 
of either $451 (an amount established annually under the law by the 
Federal Reserve) or eight percent of the amount loaned. (15 U.S.C. 
1602(aa)) Purchasers of these loans, including the GSEs, assume certain 
legal responsibilities under the Truth in Lending Act (``assignee 
liability'').
    Given the concerns about the adverse effects of high cost loans and 
abusive lending practices on neighborhoods and homeownership, the 
Department invites comments on whether this rule should disallow goals 
credit for high cost mortgage loans. The Department also seeks comments 
on the following: (1) If goals credit is restricted for such loans 
should the HOEPA definition be used, or should an alternative 
definition be established for purposes of this rule? (2) What are the 
potential benefits, if any, associated with the GSEs' presence in 
various higher cost mortgage markets including mortgages with annual 
percentage rates between those of the prime market and the market for 
high cost mortgage loans (for example, standardization of underwriting 
guidelines and reductions in interest rates)? (3) What are the 
potential dangers, if any associated with the GSEs' presence in various 
higher cost mortgage markets?
    The presence of the GSEs in the higher cost mortgage markets would 
seem to warrant increased monitoring and additional reporting by the 
GSEs to HUD. The Department seeks comments on what additional data 
would be useful and whether certain of these elements should be 
included in the public use data base. Possible data elements that could 
be collected for Department monitoring purposes include loan level data 
on the annual percentage rate, debt-to-income ratio, points and fees, 
and prepayment penalties.

C. Subpart F--Access to Information

    This subpart discusses proposed modifications to the Department's 
Final Order of October 1, 1996,\84\ ``Proprietary Data Submitted by the 
Federal National Mortgage Association (Fannie Mae) and the Federal Home 
Loan Mortgage Corporation (Freddie Mac)'' (the Final Order), under 
sections 1323 and 1326 of FHEFSSA. In the Final Order, HUD determined 
that certain mortgage data that HUD requires the GSEs to submit is 
proprietary and not to be included in the public use data base. Upon 
reviewing the previous order published as Appendix F of the 1995 Final 
Rule,\85\ the Final Order finalized existing and identified additional 
GSE loan-level data elements for single family and multifamily 
mortgages that HUD determined were proprietary and, therefore, withheld 
from the public. The Final Order also identified certain data elements 
that HUD would recode, adjust, or categorize in ranges to protect 
against the release of proprietary information, as necessary. After 
careful review of the previous proprietary orders, the Department is 
proposing a number of changes to the classification of certain GSE 
single family and multifamily mortgage data elements. The list of data 
elements that HUD proposes to make available to the public is described 
in the following sections. Appendix E of this proposed rule also 
contains full matrices, similar to those found in proprietary orders, 
that incorporate the changes proposed in this rule. Release of these 
data elements to public access is consistent with Congress's intent 
that ``every effort should be made to provide public disclosure of the 
information required to be collected and/or reported to the regulator, 
consistent with the exemption for proprietary data.'' \86\
---------------------------------------------------------------------------

    \84\ Notice of the Order was published in the Federal Register 
on October 17, 1996 (61 FR 54322).
    \85\ 60 FR 62001.
    \86\ Senate Report 102-282, 102d Cong., 2d Sess. 40 (19992).
---------------------------------------------------------------------------

    1. Background on Public Use Data Base and Public Information. 
Section 1323 of FHEFSSA requires that HUD make available to the public, 
data relating to the GSEs' mortgage purchases. In the legislative 
history of FHEFSSA, Congress indicated its intent that the GSE public 
use data base supplement the HMDA data.\87\ The purpose of the data 
base is to assist mortgage lenders, planners, researchers, and housing 
industry groups, as well as HUD and other government agencies, in 
studying the flow of mortgage credit and capital into the nation's 
communities. At the same time, Section 1326 protects from public access 
and disclosure, proprietary data and information that the GSEs submit 
to the Department and requires HUD to protect such data or information 
by Order or regulation.
---------------------------------------------------------------------------

    \87\ See, e.g., Rep. at 39.
---------------------------------------------------------------------------

    To comply with FHEFSSA, HUD established a public use data base to 
collect and make available to the public, loan-level data on the GSEs' 
single family and multifamily mortgage purchases. In Appendix F to the 
December 1, 1995 final rule, the Department specified the structure of 
the GSE public use data base and identified the data to be withheld 
from public use. The single family data was to be disclosed in three 
separate files--a Census Tract File (with geographic identifiers down 
to the census tract level), a National File A (with mortgage-level data 
on owner-occupied 1-unit properties), and a National File B (with unit-
level data on all single-family properties). The national files do not

[[Page 12669]]

have geographic indicators. The multifamily data was to be disclosed in 
two separate files--a Census Tract File and a National File consisting 
of two parts--one part containing mortgage loan level data and the 
other containing unit level data for all multifamily properties. For 
each file, the appendix identified data elements that were considered 
proprietary and those that were not proprietary and available to the 
public, and specified further that certain proprietary elements would 
be recoded or categorized into ranges to protect the proprietary 
information and to permit the release of non-proprietary information to 
the public. This multi-file structure was designed at that time to 
allow the greatest dissemination of loan-level data, without revealing 
information that would allow competitors to determine the GSEs' 
marketing and pricing strategies at the local level.
    On October 17, 1996, the Final Order describing each data element 
submitted by the GSEs and the proprietary nature of each element was 
published in the Federal Register. The Final Order also recoded, 
adjusted, or categorized in ranges certain proprietary loan-level data 
elements to protect the proprietary nature of the GSE information. HUD 
released the recoded data elements and the data elements that were 
identified as non-proprietary information to the public.
    In the fall of 1996, the Department released the first GSE public-
use data base that contained non-proprietary information on every 
mortgage purchased by the GSEs from 1993 to 1995. Subsequently, HUD 
made the 1996 and 1997 databases available to the public.
    2. Changes Proposed in This Rule. After consideration of the 
current structure of the public use data base, the Department is 
proposing several changes to its classifications of the GSEs' mortgage 
data. These changes are either technical in nature or would make 
available to the public the same data from the GSEs that is made 
available by primary lenders under HMDA. These changes, therefore, 
would not appear to release proprietary information and would, at the 
same time, affirm Congress's intent that the HMDA data base and the GSE 
data base complement each other.
a. GSE Single Family Mortgage Data
    (1) The Department proposes to change the MSA Code (Field #4) from 
YES (proprietary) to YES but Recode and to make the recoded data 
publicly available in National File A and National File B. The 
Department proposes to recode this data as:

1=Metropolitan
2=Non-Metropolitan
9=Missing

This change will make possible analyses at the national level by 
researchers beyond HUD of a variety of issues relating to metropolitan 
and non-metropolitan mortgage lending and GSE activities and will 
facilitate comparison between the GSE and HMDA data bases. Individual 
MSAs will not be identified.
    (2) The Department proposes to code the Borrower's Annual Income 
(Field #15) to ``99999999'' when missing. This change will permit the 
coding of larger borrower incomes.
    (3) The Department proposes to change the Purpose of Loan (Field 
#22) from YES (proprietary) to NO (non-proprietary) and to make such 
data publicly available in the Census Tract File and National File A. 
The Department also proposes to add the following values:

4=Rehabilitation
9=Not Applicable/Not Available

These changes will make possible separate analyses by researchers 
beyond HUD of home purchase, refinance, second, and rehabilitation 
mortgages and will facilitate comparisons between the GSE and HMDA data 
bases.
    (4) The Department proposes to change the Federal Guarantee (Field 
#27) from YES (proprietary) to NO (non-proprietary) and to make such 
data publicly available in the Census Tract File. These changes will 
make possible analyses by researchers beyond HUD of conventional and 
Federally guaranteed mortgages at the local level and will facilitate 
comparisons between the GSE and HMDA data bases.
    (5) The Department proposes to change the Borrower Race/National 
Origin (Field #41) from YES (proprietary) to NO (non-proprietary) and 
to make such data publicly available in National File A and National 
File B. The Department also proposes not to combine Field #41 and Field 
#42 in National File A and National File B and to delete subgroup #7 
indicating that Borrower and Co-Borrower are in different race/national 
origin categories. The Department also proposes to distinguish in the 
public use data base causes of missing data coded by the GSEs as ``7'' 
(information not provided in mail or telephone application), ``8'' (not 
applicable), and ``9'' (not available). These changes will make 
possible more precise analyses at the national level by researchers 
beyond HUD relating to household minority status and will facilitate 
comparisons between the GSE and HMDA data bases.
    (6) The Department proposes to change Co-Borrower Race/National 
Origin (Field #42) from YES (proprietary) to NO (non-proprietary) and 
to make such data publicly available in National File A and National 
File B, as discussed above in paragraph (5) with respect to Field #42. 
(7) The Department proposes to change the Occupancy Code (Field #47) 
from YES (proprietary) to (a) ``NO'' (non-proprietary) and make the 
data publicly available in National File A; and (b) ``YES but Recode'' 
and to make the recoded data publicly available in the Census Tract 
File. The Department proposes to recode this data as:

1=Owner-Occupied Property (1-4 units)
2=Investment Property (1-4 units)
9=Not Available

This change will make possible separate analyses by researchers beyond 
HUD for owner-occupied properties and rental properties and will 
facilitate comparisons between the GSE and HMDA data bases.
b. GSE Multifamily Mortgage Data
    (1) The Department proposes to make Date of Mortgage Note (Field 
#19) available in the National File, subject to recoding as follows:

1=Originated Same Calendar Year as Acquired
2=Originated Prior to Calendar Year of Acquisition
9=Missing

The change will permit analysis of multifamily loans originated in 
prior years by researchers beyond HUD and will facilitate comparisons 
between the GSE and HMDA data bases.
    (2) The Department proposes to change the Purpose of Loan (Field 
#21) to revise the definition of value ``9'' as follows: 9=Not 
Applicable/Not Available.
    This is a clarifying change.
    (3) The Department proposes to change Type of Seller Institution 
(Field #33) from YES (proprietary) to NO (non-proprietary) in the 
National File. This change, in connection with others being proposed, 
will facilitate comparisons between the GSE and HMDA data bases and 
will also facilitate analyses by researchers beyond HUD of 
affordability, property, size, and other key characteristics by type of 
seller at the national level.
    3. Comments Sought. HUD's specification of the data elements to be 
included in the public use data base involves complex issues and 
requires sensitivity to both Congress's concern that there be complete 
and accurate data

[[Page 12670]]

on the GSEs' activities and that there be protection of legitimately 
proprietary information submitted by the GSEs to the Department. In 
addition to public comments on these issues along with specific 
examples of data where disclosure furthers the public interest, 
comments are requested on the specific changes proposed above. HUD is 
considering two other changes to the multifamily mortgage data base and 
invites comments on the nature of these changes--(a) making available 
information on the term of the mortgage at origination recoded to group 
the data into buckets (e.g., less than seven years, seven years to less 
than ten years, ten years to less than 20 years, and more than 20 
years); and (b) making available information on the type of acquisition 
(e.g., cash, swap, credit enhancement, bond/debt purchased, missing and 
other). Both of these changes would enhance the type of multifamily 
analyses that could be conducted using the public use data base. 
Comment is also sought about whether certain data elements that are 
classified as proprietary when submitted to the Department might no 
longer be so classified after several years, because they would be 
unlikely to provide proprietary information about the GSEs' current 
business activities.
    Finally, the Department requests comments on what additional loan 
level information regarding the GSEs' mortgage purchases--on either a 
census tract or national level--would be useful to release to expand 
the public's understanding of the role the GSEs play in the mortgage 
market. The Department must protect the GSEs' proprietary interests 
with regard to the loan level data. However, when initially 
establishing the loan level data base, HUD took a conservative approach 
in making determinations about the proprietary nature of the loan level 
data elements. With the benefit of several years of experience with the 
public use data base, HUD believes it is appropriate to review the 
initial determinations with regard to the proprietary nature of 
individual loan level elements and welcomes public comment on what 
additional data should be made available, why it is needed and how the 
GSEs might be impacted through the release of this information. 
Possible examples of data that might be of interest to the public is 
the availability of data on loan-to-value ratios, special loan program 
characteristics, and how individual loans are scored for housing goal 
purposes at the census tract level.

III. Specific Areas for Public Comment

    Comment is invited on all aspects of the proposed regulation. In 
addition, the Department requests comments on several specific issues. 
These questions are discussed in context in Section II of the preamble 
and are repeated below for the convenience of commenters:
    This proposed rule solicits comments on specific changes to 
definitions applicable to the housing goal levels, establishment of new 
housing goals, new requirements for counting mortgage purchases under 
the goals, and an expansion of loan level data available to the public 
on the GSEs' mortgage loan purchases.

A. Definitions

    Comments are requested to the proposed definitional changes of the 
terms ``Median Income,'' ``Metropolitan Areas,'' ``Refinancing'' and 
``Underserved Areas'' in Sec. 81.2.

B. Housing Goal Levels

    Comments are requested on the proposed level of the housing goals 
described below and on whether the level of the proposed housing goals 
is appropriate given the statutory factors HUD must consider in setting 
the goals, and in light of the market estimates of the GSEs' shares of 
the affordable housing market.
    1. Low- and Moderate-Income Housing Goal. The rule proposes to 
amend Sec. 81.2 to change the level of the annual housing goal for 
mortgage purchases qualifying under the Low- and Moderate-Income 
Housing Goal to be 48 percent of eligible units financed in calendar 
year 2000, and 50 percent of eligible units financed in each of 
calendar years 2001, 2002 and 2003.
    2. Central Cities, Rural Areas, and Other Underserved Areas Housing 
Goal (Geographically Targeted Goal). The rule proposes to amend 
Sec. 81.13 to change the level of the annual housing goal for mortgage 
purchases qualifying under the Geographically Targeted Goal to be 29 
percent of eligible units financed in calendar year 2000, and 31 
percent of eligible units financed in each of calendar years 2001, 2002 
and 2003.
    3. Special Affordable Housing Goal. The rule proposes to amend 
Sec. 81.14 to change the level of the annual housing goal for mortgage 
purchases qualifying under the Special Affordable Housing Goal to be 18 
percent of eligible units financed in calendar year 2000, and 20 
percent of eligible units financed in each of calendar years 2001, 2002 
and 2003.
    4. Special Affordable Housing Multifamily Subgoal. For the calendar 
years 2000 through 2003, the rule proposes to amend Sec. 81.14 to 
change the level of the annual housing subgoal for mortgage purchases 
qualifying under the Special Affordable Housing Multifamily Subgoal to 
be 0.9 percent of the dollar volume of combined (single family and 
multifamily) 1998 mortgage purchases in calendar year 2000, and 1.0 
percent of the dollar volume of combined (single family and 
multifamily) 1998 mortgage purchases in each of calendar years 2001, 
2002 and 2003.

C. Possible Changes to Underserved Areas in Geographically Targeted 
Goal

    The Department is considering several possible changes to what is 
considered an underserved area for purposes of counting mortgage 
purchases under the Geographically Targeted Goal.
    1. Metropolitan Area. HUD seeks comment on the proposed options for 
revising the definition of underserved metropolitan areas in an effort 
to more accurately target underserved areas with higher mortgage denial 
rates. Specifically, HUD is considering two possible changes to the 
definition. The first option being considered is to change the current 
tract income ratio to an ``enhanced'' tract income ratio and to require 
that for tracts to qualify they must (1) calculate the tract income 
ratio based on the ratio of tract median income to the greater of the 
national metropolitan median income or the MSA median income; and (2) 
have a tract income ratio at or below 80 percent. The second option 
being considered is to increase the requirement for a tract's minority 
population from the current 30 percent to 50 percent. The Department is 
also requesting comments on the extent to which these definitional 
changes are likely to increase the availability of credit to areas with 
high denial rates.
    2. Tribal Lands. The Department seeks comment on the amended 
definition of underserved areas in Sec. 81.2 that includes low-income 
and/or high minority American Indian Reservations and trust lands in 
the definition of underserved areas for both metropolitan and non-
metropolitan areas.
    3. Rural Areas. HUD also seeks public comment on alternative 
methodologies and sources of rural market data that HUD might use to 
define underserved non-metropolitan/rural areas. Specifically, HUD 
seeks comment on whether the Department should follow a tract-based 
approach in defining underserved rural areas, which would be consistent 
with the tract-based definition used in metropolitan areas. As 
technology and computer mapping

[[Page 12671]]

capabilities have evolved since 1995, it may be appropriate to revisit 
the issue of whether entire counties or census tracts within the 
counties should be used to define rural underserved areas.

D. Possible Changes to the Structure of the Special Affordable Housing 
Multifamily Subgoal

    The Department seeks comment on whether the special affordable 
multifamily subgoal proposed that is based on a percentage of total 
dollar volume of mortgages purchased, or the possible alternative 
structures presented that base the subgoal on (a) the number of units 
financed, (b) a percent of current multifamily mortgage purchases, or 
(c) the number of mortgages acquired, are reasonable and desirable 
approaches to closing market gaps in the very low- and low-income 
rental market. HUD also solicits comment on the appropriate level for 
the subgoal as proposed, or under the various possible structures 
presented, and how the possible levels illustrated herein would likely 
impact multifamily acquisitions, especially for very low- and low-
income multifamily units.

E. Bonus Points and Subgoals

    Specifically, the Department invites comments on (a) whether, for 
the four year period ending December 31, 2003, Sec. 81.16(c)(10) should 
be added to allow small multifamily properties (5-50 units) and all the 
units in owner-occupied 2-4 unit properties to receive double weight in 
the numerator for each of the three housing goals that otherwise 
qualify for the housing goals; and (b) how to count small multifamily 
properties for purposes of receiving bonus points that may be 
aggregated into larger financing packages. The Department also seeks 
comments on the utility of applying similar regulatory incentives 
(bonus points and/or subgoals) to other underserved segments of the 
market. In addition, HUD requests comments on the following questions 
that relate to bonus points and subgoals in general:
    1. Whether HUD should use either bonus points or subgoals to target 
mortgage purchases for one or more of the areas of concern identified 
earlier?
    2. Whether one or more of these areas would benefit more from bonus 
points or establishment of subgoals and why? If bonus points are 
suggested, the amount of bonus points which should be assigned and why?
    3. Whether there are other areas not identified where bonus points 
and/or subgoals should be considered?

F. Calculating Performance Under the Housing Goals

    The Department invites comments on clarifications and revisions to 
certain requirements for calculating performance under the housing 
goals.
    1. Temporary Adjustment Factor for Freddie Mac. HUD requests 
comments on the proposal to provide Freddie Mac with an incentive to 
further expand the scope of its multifamily operations by providing 
them with a Temporary Adjustment Factor. The proposed rule calculates 
Freddie Mac's performance under the Low- and Moderate-Income Housing 
Goal and the Special Affordable Housing Goal by counting each unit in a 
multifamily property with more than 50 units meeting the definition of 
one or both housing goals as 1.2 units (the Temporary Adjustment 
Factor) in the numerator in determining the respective housing goal 
percentage. HUD specifically requests comments on whether the proposed 
temporary adjustment factor for Freddie Mac is set at an appropriate 
level, and if such an adjustment factor should be phased out prior to 
2003 or apply for the entire four year goal cycle.
    2. Data on Unit Affordability. The Department seeks comments on the 
proposed revisions to Sec. 81.15(d) and (e)(6) that identify the 
treatment for purposes of counting under the housing goals of those 
cases where a GSE does not obtain rental data on units, and welcomes 
suggestions for alternative ways of addressing the issue.
    a. Multifamily Rental Units. For units in multifamily properties, 
the Department proposes to allow the use by a GSE of estimated rents 
based on market rental data. The Department will review and approve the 
GSEs' data sources and methodologies for estimating rents on 
multifamily units prior to their use, to assure reliability. Estimated 
rental data submitted to the Department shall be so identified by the 
GSE. HUD requests comments on whether it should establish a percentage 
ceiling for the GSEs' use of estimated data for multifamily mortgage 
purchases. The Department further proposes to allow a GSE to exclude 
units in multifamily properties from the denominator as well as the 
numerator in calculating performance under the Low- and Moderate-Income 
Housing Goal and the Special Affordable Housing Goal when the GSE lacks 
sufficient information to determine whether the purchase of a mortgage 
originated after 1992 counts toward achievement of the goal, and when 
the application of estimated rents based on an approved market rental 
data source and methodology is not possible.
    b. Single Family Rental Units. For purposes of counting rental 
units in 1-4 unit single family properties toward achievement of the 
Low- and Moderate-Income Housing Goal and the Special Affordable 
Housing Goal, the Department proposes to allow a GSE to exclude the 
rental units in 1-4 unit single family properties from the denominator 
as well as the numerator in calculating performance under the Low- and 
Moderate-Income Housing Goal and the Special Affordable Housing Goal 
when the GSE lacks rent sufficient information to determine whether the 
purchase of a mortgage originated after 1992 counts toward achievement 
of the Low- and Moderate Income Housing Goal or the Special Affordable 
Housing Goal.
    c. Single Family Owner-Occupied Units. Comments are requested on 
the Department's proposal to allow a GSE to exclude certain single 
family owner-occupied units from the denominator as well as the 
numerator in calculating performance under the Low- and Moderate-Income 
Housing Goal when the GSE lacks sufficient information on borrower 
income to determine whether the purchase of a mortgage originated after 
1992 counts toward achievement of the goal, provided the mortgaged 
property is located in a census tract with median income less than or 
equal to area median income according to the most recent census. Such 
exclusion from the denominator and numerator will be permitted up to a 
ceiling of one percent (1%) of the total number of single family, 
owner-occupied dwelling units eligible to be counted toward the 
respective housing goal in the current year. Mortgage purchases in 
excess of the ceiling will be included in the denominator and excluded 
from the numerator.
    3. Seasoned Mortgage Loan Purchases. Comments are requested on 
specific changes that are proposed in Sec. 81.14 that address how 
purchases of seasoned mortgage portfolios receive full credit under the 
Special Affordable Housing Goal. Changes to Sec. 81.16 are proposed to 
clarify the treatment of seasoned mortgages in calculating goal 
performance. The suggested changes specifically provide direction and 
guidance to the GSEs for the purpose of determining whether a seller of 
special affordable seasoned mortgage portfolios is adequately engaged 
in a specific program to reinvest the proceeds of the loan sale into 
additional special affordable lending. In addition, commenters are 
invited to provide their views on how to identify and define

[[Page 12672]]

those classes of organizations or institutions who are primarily 
engaged in financing affordable housing mortgages, including possibly 
State Housing Finance Agencies or Special Affordable Housing Loan 
Consortia, or other types of businesses that further the purpose of the 
Special Affordable Housing Goal. In addition to specific proposed 
changes to the regulation, commenters are invited to share their views 
as to whether any additional exemptions or changes should be 
established under the recycling provisions that further its purpose. 
Comments are also specifically invited on (1) what, if any, provisions 
should be included in the proposed rule to address the various 
affiliate structures of depository institutions; and (2) the treatment 
under the recycling provisions of structured transactions where the 
mortgage loans acquired were originated by a depository institution or 
mortgage banker engaged in mortgage lending on special affordable 
housing but acquired and sold by a third party, e.g., an investment 
banking firm that is not in the business of affordable housing lending.
    4. Certain Federally Insured or Guaranteed Mortgages. Comments are 
requested on the proposed change to Sec. 81.16(b)(3) to except 
mortgages under the HECM program, mortgages guaranteed by RHS and loans 
made under FHA's Section 248 program and HUD's Section 184 program on 
properties in tribal lands from the general exclusion under the rules 
for non-conventional mortgage loans, and to allow the Department to 
count non-conventional mortgage purchases under the goals where the 
Department determines, in writing, that the financing needs addressed 
by such program are not well served and that mortgage purchases under 
such program should count. In addition, the proposed rule provides that 
where non-conventional mortgage purchases will now count toward the 
housing goals, they no longer will be excluded from the denominator of 
the GSEs' mortgage purchases as are other non-conventional mortgage 
loans.
    5. Other Counting Changes. Comments are welcome on the following 
specific changes to counting requirements contained in the proposed 
rule: (a) Allowing half-credit for purchases of HUD Title I loans under 
the Special Affordable Housing Goal (Sec. 81.14); (b) amending the 
calculation of ``Denominator'' to clarify that the denominator does not 
include GSE transactions or activities that are not mortgages or that 
are specifically excluded mortgage purchase transactions (Sec. 81.16); 
(c) excluding certain single family balloon mortgages from treatment as 
a refinancing at the time of conversion to a fully amortizing note 
(Secs. 81.2 and 81.16); (d) providing partial or full credit for 
actions that assist in maintaining the affordability of multifamily 
properties with expiring assistance contracts including how and to what 
extent the GSEs should receive credit for such actions; and (e) adding 
the designation of ``especially low-income'' in relationship to the 
Special Affordable Housing Goal (Secs. 81.14, 18.17, 81.18, and 81.19). 
In addition, while no specific change has been proposed, comments are 
requested on whether the final rule should disallow goals credit for 
high cost mortgage loans. The Department also seeks comments on the 
following: (i) If goals credit is restricted for such loans, should the 
HOEPA definition be used, or should an alternative definition be 
established for purposes of this rule? (ii) What are the potential 
benefits, if any, associated with the GSEs' presence in the various 
higher cost mortgage markets including mortgages with annual percentage 
rates between those of the prime market and the market for high cost 
mortgage loans (for example, standardization of underwriting guidelines 
and reductions in interest rates)? (iii) What are the potential 
dangers, if any, associated with the GSEs' presence in various higher 
cost mortgage markets? Finally, the Department requests comments on 
what additional reporting data would be useful for the purposes of 
monitoring the GSEs' activities in this area and on whether certain of 
these data elements should be included in the public use data base. 
Possible data elements that could be collected for Department 
monitoring purposes include loan level data on the annual percentage 
rate, debt-to-income ratio, points and fees, and prepayment penalties.
    6. Provision for HUD to Review New Activities to Determine 
Appropriate Counting Under the Housing Goals. The Department is 
requesting comments on the proposal to add a provision (Sec. 81.16(d)) 
for HUD to review activities of the GSEs to ensure that the counting of 
transactions towards the housing goals is consistent with FHEFSSA and 
advise the GSEs of the Department's determination with regard to credit 
for purposes of counting such transactions under the housing goals.
    7. Credit Enhancements. In relation to credit enhancements, HUD 
invites comments on the following questions:
    a. Given the wide range of institutional arrangements pertaining to 
credit enhancements and the inter-relationships between credit 
enhancements and other considerations such as loan-to-value ratio and 
guarantee fee, how should the credit risk to which the GSEs are exposed 
be measured under various types of credit enhancement scenarios?
    b. Assuming credit risk can be adequately measured, should HUD give 
partial credit under the housing goals when credit enhancements result 
in a substantial portion of the credit risk of the transaction being 
borne by the seller or a third party? For example, if the GSE bears 
less than 50 percent of the credit risk of a transaction should the GSE 
receive no credit toward housing goal performance? If the GSE assumes 
between 50 percent and 75 percent of the credit risk of a transaction, 
should the GSE receive 50 percent credit for housing goal purposes?
    c. What would be the advantages and disadvantages of linking the 
amount of goals credit on a GSE mortgage purchase to the degree of 
associated credit risk? What are the possible effects on low- and 
moderate-income families and on underserved areas of the GSEs' use of 
various credit enhancements and how might they be affected if goals 
credit were linked to the degree of associated credit risk? Would there 
be potential effects on liquidity or other mortgage market factors?
    d. Assuming credit risk can be adequately measured, should HUD 
establish a minimum percentage in the range of 0 to 100 percent for the 
amount of credit risk borne by the GSEs on their mortgage purchases in 
order for such purchases to count toward the housing goals?
    e. If HUD establishes a minimum threshold for credit risk, should 
it be the same for multifamily and single family purchases, or should 
it be different for each? Should HUD establish the same threshold for 
all types of credit enhancements, or should this differ between types 
of credit enhancements? At what level should the threshold(s) be 
established?
    f. Should HUD measure counterparty risk on seller-provided credit 
enhancements? If so, how?
    g. Should HUD evaluate GSE performance in relation to the use of 
credit enhancements by calculating and comparing the risk-adjusted rate 
of return under the use of various credit enhancement alternatives?

G. Access to Information

    HUD's specification of the data elements to be included in the 
public use data base involves complex issues and requires sensitivity 
to both Congress's concern that there be

[[Page 12673]]

complete and accurate data on the GSEs' activities and that there be 
protection of legitimately proprietary information submitted by the 
GSEs to the Department. In addition to public comments on these issues 
along with specific examples of data where disclosure furthers the 
public interest, comments are requested on the specific changes 
proposed to the rule. HUD is considering two other changes to the 
multifamily mortgage data base and invites comments on the feasibility 
of these changes--(a) making available information on the term of the 
mortgage at origination recoded to group the data into buckets; and (b) 
making available information on the type of acquisition. Both of these 
changes would enhance the type of multifamily analyses that could be 
conducted using the public use data base. Comment is also sought about 
whether certain data elements that are classified as proprietary when 
submitted to the Department might no longer be so classified after 
several years, because they would be unlikely to provide proprietary 
information about the GSEs' current business activities. Finally, the 
Department requests comments on what additional loan level information 
regarding the GSEs' mortgage purchases--on either a census tract or 
national level--would be useful to release to expand the public's 
understanding of the role the GSEs play in the mortgage markets.

IV. Findings and Certifications

A. 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 
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 7:30 a.m. 
and 5:30 p.m. weekdays in the Office of the Rules Docket Clerk, Office 
of General Counsel, Room 10276, Department of Housing and Urban 
Development, 451 Seventh Street, S.W., Washington, DC. The initial 
Economic Analysis prepared for this rule is also available for public 
inspection in the Office of the Rules Docket Clerk.

B. Congressional Review of Major Final Rules

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

C. Paperwork Reduction Act

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

D. Environmental Impact

    In accordance with 24 CFR 50.19(c)(1) of HUD's regulations, 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. Therefore, this proposed rule is 
categorically excluded from the requirements of the National 
Environmental Policy Act.

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

F. Executive Order 13132, Federalism

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

G. Unfunded Mandates Reform Act

    Title II of the Unfunded Mandates Reform Act of 1995 \88\ (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 governments, or on the private 
sector, within the meaning of the UMRA.
---------------------------------------------------------------------------

    \88\ Pub. L. 104-4, approved March 22, 1995.
---------------------------------------------------------------------------

List of Subjects in 24 CFR Part 81

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

    Accordingly, 24 CFR part 81 is proposed to be amended as follows:

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

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

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

    2. Section 81.2, is amended by revising the definitions of ``Median 
Income'' ``Metropolitan Area'', and ``Underserved Area,'' and by adding 
a new paragraph (7) to the definition of ``Refinancing,'' to read as 
follows:


Sec. 81.2  Definitions.

* * * * *
    Median Income means, with respect to an area, the unadjusted median 
family income for the area and most recently determined and published 
by HUD. HUD will provide the GSEs, on an annual basis, with information 
specifying how HUD's published median family income estimates for 
metropolitan areas are to be applied for the purposes of determining 
median family income in such areas.
    Metropolitan Area means a metropolitan statistical area (``MSA''), 
or primary metropolitan statistical area (``PMSA''), or a portion of 
such an area for which median family income estimates are published 
annually by HUD.
* * * * *
    Refinancing means: * * *
* * * * *
    (7) A conversion of a balloon mortgage note on a single family 
property to a fully amortizing mortgage note provided the GSE already 
owns or

[[Page 12674]]

has an interest in the balloon note at the time of the conversion.
* * * * *
    Underserved Area means:
    (1) For purposes of the definitions of ``Central City'' and ``Other 
Underserved Area'', a census tract, a Federal or State American Indian 
reservation or tribal or individual trust land, or the balance of a 
census tract excluding the area within any Federal or State American 
Indian reservation or tribal or individual trust land, having:
    (i) A median income at or below 120 percent of the median income of 
the metropolitan area and a minority population of 30 percent or 
greater; or
    (ii) A median income at or below 90 percent of median income of the 
metropolitan area.
    (2) For purposes of the definition of ``Rural Area'':
    (i) In areas other than New England, a whole county, a Federal or 
State American Indian reservation or tribal or individual trust land, 
or the balance of a county excluding the area within any Federal or 
State American Indian reservation or tribal or individual trust land, 
having:
    (A) A median income at or below 120 percent of the greater of the 
State non-metropolitan median income or the nationwide non-metropolitan 
median income and a minority population of 30 percent or greater; or
    (B) A median income at or below 95 percent of the greater of the 
State non-metropolitan median income or nationwide non-metropolitan 
median income.
    (ii) In New England, a whole county having the characteristics in 
paragraph (2)(i)(A) or (2)(i)(B) of this definition; a Federal or State 
American Indian reservation or tribal or individual trust land, having 
the characteristics in paragraph (2)(i)(A) or (2)(i)(B) of this 
definition; or the balance of a county, excluding any portion that is 
within any Federal or State American Indian reservation or tribal or 
individual trust land, or metropolitan area where the remainder has the 
characteristics in paragraph (2)(i)(A) or (2)(i)(B) of this definition.
    (3) Any Federal or State American Indian reservation or tribal or 
individual trust land that includes land that is both within and 
outside of a metropolitan area and that is designated as an underserved 
area by HUD. In such cases, HUD will notify the GSEs as to 
applicability of other definitions and counting conventions.
* * * * *
    3. Section 81.12 is amended as follows:
    a. Paragraph (b) is amended by revising the last sentence; and
    b. Paragraph (c) is revised, to read as follows:


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 will be inserted].
    (c) Goals. The annual goals for each GSE's purchases of mortgages 
on housing for low- and moderate-income families are:
    (1) For calendar year 2000, 48 percent of the total number of 
dwelling units financed by that GSE's mortgage purchases unless 
otherwise adjusted by HUD in accordance with FHEFSSA;
    (2) For each of the calendar years 2001-2003, 50 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years unless otherwise adjusted by HUD in 
accordance with FHEFSSA; and
    (3) For calendar year 2004 and thereafter HUD shall establish 
annual goals. Pending establishment of goals for calendar year 2004 and 
thereafter, the annual goal for each of those calendar years shall be 
50 percent of the total number of dwelling units financed by that GSE's 
mortgage purchases in each of those calendar years.
    4. Section 81.13 is amended as follows:
    a. Paragraph (b) is amended by revising the last sentence; and
    b. Paragraph (c) is revised, to read as follows:


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

* * * * *
    (b) Factors. * * * A statement documenting HUD's considerations and 
findings with respect to these factors, entitled ``Departmental 
Considerations to Establish the Central Cities, Rural Areas, and Other 
Underserved Areas Housing Goal,'' was published in the Federal Register 
on [date of publication of final rule will be inserted].
    (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 calendar year 2000, 29 percent of the total number of 
dwelling units financed by that GSE's mortgage purchases unless 
otherwise adjusted by HUD in accordance with FHEFSSA;
    (2) For each of the calendar years 2001-2003, 31 percent of the 
total number of dwelling units financed by that GSE's mortgage 
purchases in each of those years unless otherwise adjusted by HUD in 
accordance with FHEFSSA; and
    (3) For calendar year 2004 and thereafter HUD shall establish 
annual goals. Pending establishment of goals for calendar year 2004 and 
thereafter, the annual goal for each of those calendar years shall be 
31 percent of the total number of dwelling units financed by that GSE's 
mortgage purchases in each of those calendar years.
* * * * *
    5. Section 81.14 is amended as follows:
    a. Paragraph (b) is amended by revising the last sentence;
    b. Paragraph (c) is revised;
    c. Paragraph (d) is amended by revising paragraph (d)(1)(i);
    d. Paragraph (e) is amended by revising paragraphs (e)(2), (e)(3), 
and (e)(4);
    e. Paragraph (f) is redesignated as paragraph (g) and the last 
sentence of the newly redesignated paragraph (g) is revised; and
    f. A new paragraph (f) is added; to read as follows:


Sec. 81.14  Special Affordable Housing Goal.

* * * * *
    (b) * * * A statement documenting the 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 
will be inserted].
    (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 calendar year 2000, 18 percent of the total number of 
dwelling units financed by that GSE's mortgage purchases unless 
otherwise adjusted by HUD in accordance with FHEFSSA. The goal shall 
include mortgage purchases financing dwelling units in multifamily 
housing totaling not less than 0.9 percent of the dollar volume of 
combined (single family and multifamily) mortgages purchased by the 
respective GSE in 1998 unless otherwise adjusted by HUD in accordance 
with FHEFSSA;
    (2) For each of the calendar years 2001, 2002, and 2003, 20 percent 
of the total number of dwelling units financed by that GSE's mortgage 
purchases in

[[Page 12675]]

each of those years unless otherwise adjusted by HUD in accordance with 
FHEFSSA. The goal for each calendar year shall include mortgage 
purchases financing dwelling units in multifamily housing totaling not 
less than 1.0 percent of the dollar volume of combined (single family 
and multifamily) mortgages purchased by the respective GSE in 1998 
unless otherwise adjusted by HUD in accordance with FHEFSSA; and
    (3) For calendar year 2004 and thereafter HUD shall establish 
annual goals. Pending establishment of goals for calendar year 2004 and 
thereafter, the annual goal for each of those calendar years shall be 
20 percent of the total number of dwelling units financed by that GSE's 
mortgage purchases in each of those calendar years. The goal for each 
such calendar year shall include mortgage purchases financing dwelling 
units in multifamily housing totaling not less than 1.0 percent of the 
dollar volume of combined (single family and multifamily) mortgages 
purchased by the respective GSE in 1998.
* * * * *
    (d)(1) * * *
    (i) 20 percent of the dwelling units in the particular multifamily 
property are affordable to especially low-income families; or
* * * * *
    (e) * * *
* * * * *
    (2) Mortgages under HUD's Home Equity Conversion Mortgage 
(``HECM'') Insurance Program, 12 U.S.C. 1715 z-20; mortgages guaranteed 
by the Rural Housing Services' Guaranteed Rural Housing Loan Program, 7 
U.S.C. 1933; and mortgages on properties on tribal lands insured under 
FHA's Section 248 program, 12 U.S.C. 1715 z-13, or HUD's Section 184 
program, 12 U.S.C. 1515 z-13a; meet the requirements of 12 U.S.C. 
4563(b)(1)(A)(i) and (ii).
    (3) HUD will give full credit toward achievement of the Special 
Affordable Housing Goal for the activities in 12 U.S.C. 4563(b)(1)(A), 
provided the GSE submits documentation to HUD that supports eligibility 
under 12 U.S.C. 4563(b)(1)(A) for HUD's approval.
    (4)(i) For purposes of determining whether a seller meets the 
requirement in 12 U.S.C. 4563(b)(1)(B), a seller must currently operate 
on its own or actively participate in an on-going, discernible, active, 
and verifiable program directly targeted at the origination of new 
mortgage loans that qualify under the Special Affordable Housing Goal.
    (ii) A seller's activities must evidence a current intention or 
plan to reinvest the proceeds of the sale into mortgages qualifying 
under the Special Affordable Housing Goal, with a current commitment of 
resources on the part of the seller to this purpose.
    (iii) A seller's actions must evidence willingness to buy 
qualifying loans when these loans become available in the market as 
part of active, on-going, sustainable efforts to ensure that additional 
loans that meet the goal are originated.
    (iv) Actively participating in such a program includes purchasing 
qualifying loans from a correspondent originator, including a lender or 
qualified housing group, that operates an on-going program resulting in 
the origination of loans that meet the requirements of the goal, has a 
history of delivering, and currently delivers, qualifying loans to the 
seller.
    (v) The GSE must verify and monitor that the seller meets the 
requirements in paragraphs (e)(4)(i) through (e)(4)(iv) of this section 
and develop any necessary mechanisms to ensure compliance with the 
requirements, except as provided in paragraph (e)(4)(vi) of this 
section.
    (vi) Where a seller's primary business is originating mortgages on 
housing that qualifies under this Special Affordable Housing Goal 
(e.g., when such seller is an institution that is regularly in the 
business of mortgage lending; a BIF-insured or SAIF-insured depository 
institution; and subject to, and has received at least a satisfactory 
performance evaluation rating for at least the two most recent 
consecutive examinations under, the Community Reinvestment Act), such 
seller is presumed to meet the requirements in paragraphs (e)(4)(i) 
through (e)(4)(iv) of this section.
    (vii) For a class or classes of institutions or organizations whose 
primary business is financing affordable housing mortgages, e.g., State 
Housing Finance Agencies or Special Affordable Housing Loan Consortia, 
such classes of organizations or institutions are presumed to meet the 
requirements of paragraphs (e)(4)(i) through (e)(4)(iv) of this 
section. A determination that specific classes of institutions or 
organizations are primarily engaged in the business of financing 
affordable housing mortgages must be made in advance by HUD.
* * * * *
    (f) Partial credit activities. Mortgages insured under HUD's Title 
I program, which includes property improvement and manufactured home 
loans, shall receive one-half credit toward the Special Affordable 
Housing Goal until such time as the Government National Mortgage 
Association fully implements a program to purchase and securitize Title 
I loans.
    (g) No credit activities. * * * For purposes of this paragraph (g), 
``mortgages or mortgage-backed securities portfolios'' includes 
mortgages retained by Fannie Mae or Freddie Mac and mortgages utilized 
to back mortgage-backed securities.
* * * * *
    6. In Sec. 81.15, paragraph (a) is revised, paragraph (d) is 
amended by adding a new sentence at the end, and paragraph (e) is 
amended by redesignating paragraph (e)(6) as (e)(7), and by adding a 
new paragraph (e)(6), to read as follows:


Sec. 81.15  General requirements.

    (a) Calculating the numerator and denominator. Performance under 
each of the housing goals shall be measured using a fraction that is 
converted into a percentage.
    (1) The numerator. The numerator of each fraction is the number of 
dwelling units financed by a GSE's mortgage purchases in a particular 
year that count toward achievement of the housing goal.
    (2) The denominator. The denominator of each fraction is, for all 
mortgages purchased, the number of dwelling units that could count 
toward achievement of the goal under appropriate circumstances. The 
denominator shall not include GSE transactions or activities that are 
not mortgages or mortgage purchases as defined by HUD or transactions 
that are specifically excluded as ineligible under Sec. 81.16(b).
    (3) Missing data or information. When a GSE lacks sufficient data 
or information to determine whether the purchase of a mortgage 
originated after 1992 counts toward achievement of a particular housing 
goal, that mortgage purchase shall be included in the denominator for 
that housing goal, except under the circumstances described in 
paragraphs (d) and (e)(6) of this section.
* * * * *
    (d) Counting owner-occupied units. * * * When the income of the 
mortgagors is not available to determine whether the purchase of a 
mortgage originated after 1992 counts toward achievement of the Low- 
and Moderate-Income Housing Goal or the Special Affordable Housing 
Goal, a GSE may exclude single- family owner-occupied units located in 
census tracts with median income less than or equal to area median 
income according to the most recent census from the denominator as well 
as the numerator, up to a ceiling of one percent of the total number of 
single-family owner-occupied dwelling units eligible to be counted 
toward the respective housing goal in the current year. Mortgage

[[Page 12676]]

purchases in excess of the ceiling will be included in the denominator 
and excluded from the numerator.
    (e) * * *
* * * * *
    (6) Income or Rent Data Unavailable. (i) Multifamily. When neither 
the income of prospective or actual tenants of a dwelling unit nor 
actual or average rent data is available, a GSEs' performance with 
respect to such a unit may be evaluated with estimated rents based on 
market rental data, so long as the Department has reviewed and approved 
the data source and methodology for such estimated data. The GSE must 
identify such data as estimated data. When the application of estimated 
rents based on an approved market rental data source and methodology is 
not possible, and therefore the GSE lacks sufficient information to 
determine whether the purchase of a mortgage originated after 1992 
counts toward the achievement of the Low- and Moderate-Income Housing 
Goal or the Special Affordable Housing Goal, a GSE may exclude units in 
multifamily properties from the denominator as well as the numerator in 
calculating performance under those goals.
    (ii) Rental units in 1-4 unit single family properties. When 
neither the income of prospective or actual tenants of a rental unit in 
a 1-4 unit single family property nor actual or average rent data is 
available, and, therefore, the GSE lacks sufficient information to 
determine whether the purchase of a mortgage originated after 1992 
counts toward achievement of the Low- and Moderate-Income Housing Goal 
or the Special Affordable Housing Goal, a GSE may exclude rental units 
in 1-4 unit single family properties from the denominator as well as 
the numerator in calculating performance under those goals.
* * * * *
    7. Section 81.16 is amended as follows:
    a. Paragraph (a) is revised;
    b. Paragraph (b) is amended by revising paragraphs (b)(3) and 
(b)(9) and by adding a new paragraph (b)(10);
    c. Paragraph (c) is amended by revising the heading, by adding 
introductory text, by revising paragraph (c)(6), and by adding new 
paragraphs (c)(9), (c)(10) and (c)(11); and
    d. A new paragraph (d) is added; to read as follows:


Sec. 81.16  Special counting requirements.

    (a) General. HUD shall determine whether a GSE shall receive full, 
partial, or no credit for a transaction toward achievement of any of 
the housing goals. In this determination, HUD will consider whether a 
transaction or activity of the GSE is substantially equivalent to a 
mortgage purchase and either creates a new market or adds liquidity to 
an existing market, provided however that such mortgage purchase 
actually fulfills the GSE's purposes and is in accordance with its 
Charter Act.
    (b) * * *
* * * * *
    (3) Purchases of non-conventional mortgages except:
    (i) Where such mortgages are acquired under a risk-sharing 
arrangement with a Federal agency;
    (ii) Mortgages under HUD's Home Equity Conversion Mortgage 
(``HECM'') Insurance Program, 12 U.S.C. 1715 z-20; mortgages guaranteed 
by the Rural Housing Services' Guaranteed Rural Housing Loan Program, 7 
U.S.C. 1933; and mortgages on properties on tribal lands insured under 
FHA's Section 248 program, 12 U.S.C. 1715 z-13, or HUD's Section 184 
program, 12 U.S.C. 1515 z-13a; or
    (iii) Mortgages under other mortgage programs involving Federal 
guarantees, insurance or other Federal obligation where the Department 
determines in writing that the financing needs addressed by the 
particular mortgage program are not well served and that the mortgage 
purchases under such program should count under the housing goals, 
provided the GSE submits documentation to HUD that supports eligibility 
for HUD's approval.
* * * * *
    (9) Single family mortgage refinancings that result from conversion 
of balloon notes to fully amortizing notes, if the GSE already owns or 
has an interest in the balloon note at the time conversion occurs. New 
purchases of balloon mortgages or mortgages for which the borrower has 
exercised a conversion option prior to purchase and/or guarantee by the 
GSE will be included in the numerator and denominator as appropriate in 
accordance with Sec. 81.15.
    (10) Any combination of (1) through (9) above.
    (c) Supplemental rules. Subject to HUD's primary determination of 
whether a GSE shall receive full, partial, or no credit for a 
transaction toward achievement of any of the housing goals as provided 
in paragraph (a) of this section, the following supplemental rules 
apply:
* * * * *
    (6) Seasoned mortgages. A GSE's purchase of a seasoned mortgage 
shall be treated as a mortgage purchase for purposes of these goals and 
shall be included in the numerator, as appropriate, and the denominator 
in calculating the GSE's performance under the housing goals, except 
where the GSE has already counted the mortgage under a housing goal 
applicable to 1993 or any subsequent year, or where the Department 
determines, based upon a written request by a GSE, that a seasoned 
mortgage or class of such mortgages should be excluded from the 
numerator and the denominator in order to further the purposes of the 
Special Affordable Housing Goal.
* * * * *
    (9) Expiring assistance contracts. In accordance with 12 U.S.C. 
4565(a)(5), actions that assist in maintaining the affordability of 
assisted units in eligible multifamily housing projects with expiring 
Section 8 contracts shall receive partial to full credit under the 
housing goals as determined by HUD. For purposes of the paragraph, 
``actions'' include the restructuring or refinancing of mortgages, and 
credit enhancements or risk-sharing arrangements to modified or 
refinanced mortgages.
    (10) Bonus points. The following transactions or activities, to the 
extent the units otherwise qualify for one or more of the housing 
goals, will receive bonus points toward the particular goal or goals, 
by receiving double weight in the numerator under a housing goal or 
goals and receiving single weight in the denominator for the housing 
goal or goals. Bonus points will not be awarded for the purposes of 
calculating performance under the special affordable housing 
multifamily subgoal included in Sec. 81.14(c). All transactions or 
activities meeting the following criteria will qualify for bonus points 
even if a unit is missing affordability data and the missing 
affordability data is treated consistent with Sec. 81.15(a)(3). Bonus 
points are available to the GSEs for purposes of determining housing 
goal performance through December 31, 2003. Beginning in calendar year 
2004, bonus points are not available for goal performance counting 
purposes unless the Department extends their availability beyond 
December 31, 2003, for one or more types of activities and notifies the 
GSEs by letter of that determination.
    (i) Small multifamily properties. HUD will assign double weight in 
the numerator under a housing goal or goals for each unit in small 
multifamily properties (5 to 50 units), provided, however, that bonus 
points will not be awarded for properties that are aggregated or 
disaggregated into 5-50

[[Page 12677]]

unit financing packages for the purpose of earning bonus points.
    (ii) Rental units in 2-4 unit owner-occupied properties. HUD will 
assign double weight in the numerator under the housing goals for each 
unit in 2- to 4-unit owner-occupied properties, to the extent that the 
number of such units financed by mortgage purchases are in excess of 60 
percent of the average number of units qualifying for the respective 
housing goal during the immediately preceding five years.
    (11) Temporary adjustment factor for Freddie Mac. In determining 
Freddie Mac's performance on the Low- and Moderate-Income Housing Goal 
and the Special Affordable Housing Goal, HUD will count each qualifying 
unit in a property with more than 50 units as 1.2 units in calculating 
the numerator and as one unit in calculating the denominator, for the 
respective housing goal. HUD will apply this temporary adjustment 
factor for each calendar year from 2000 through 2003; for calendar 
years 2004 and thereafter, this temporary adjustment factor will no 
longer apply.
    (d) HUD review of transactions. HUD will determine whether a class 
of transactions counts as a mortgage purchase under the housing goals. 
If a GSE is considering a class of transactions for purposes of 
counting under the housing goals, the GSE may provide HUD detailed 
information regarding the transactions for evaluation and determination 
in accordance with this section. In making its determination, HUD may 
also request and evaluate information from a GSE with regard to how the 
GSE believes the transactions should be counted. HUD will notify the 
GSE of its determination regarding the extent to which the class of 
transactions should count under the goals.
    8. Section 81.17 is amended by adding a new paragraph (d), to read 
as follows:


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

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

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

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


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

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

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

    10. In Sec. 81.19, paragraph (d) is redesignated as paragraph (e), 
and a new paragraph (d) is added, to read as follows:


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

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

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

* * * * *

    Dated: January 20, 2000.
William C. Apgar,
Assistant Secretary for Housing.

    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

1. Establishment of Goal

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

2. Underlying Data

    In considering the statutory factors in establishing these 
goals, HUD relied on data from the 1995 American Housing Survey 
(AHS), the 1990 Census of Population and Housing, the 1991 
Residential Finance Survey (RFS), the 1995 Property Owners and 
Managers Survey (POMS), other government reports, reports submitted 
in accordance with the Home Mortgage Disclosure Act (HMDA), and the 
GSEs. In order to measure performance toward achieving the Low- and 
Moderate-Income Housing Goal in previous years, HUD analyzed the 
loan-level data on all mortgages purchased by the GSEs for 1993-98 
in accordance with the goal counting provisions established by the 
Department in the December 1995 rule (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 information on trends in refinancing 
activity) and is useful for gauging the reasonableness of specific 
levels of the Low- and Moderate-Income Housing Goal. In addition, 
the severe housing problems faced by lower-income families are 
discussed.
    The third factor (past performance) and the fifth factor 
(ability of the GSEs to lead the industry) are also discussed in 
some detail in this Appendix. The fourth factor (size of the market) 
and the sixth factor (need to maintain the GSEs' sound financial 
condition) are mentioned only briefly in this

[[Page 12678]]

Appendix. Detailed analyses of the fourth factor and the sixth 
factor are contained in Appendix D and in the economic analysis of 
this proposed rule, respectively.
    The factors are discussed in sections B through H of this 
appendix. Section I summarizes the findings and presents the 
Department's conclusions concerning the Low- and Moderate-Income 
Housing Goal. The consideration of the factors in this Appendix has 
led the Secretary to the following conclusions:
    (i) Despite the record national homeownership rate of 66.3 
percent in 1998, much lower rates prevailed for minorities, 
especially for African-American households (46.1 percent) and 
Hispanics (44.7 percent), and these lower rates are only partly 
accounted for by differences in income, age, and other socioeconomic 
factors.
    (ii) Pervasive and widespread disparities in mortgage lending 
continued across the nation in 1997, when the loan denial rate was 
10.2 percent for white mortgage applicants, but 23.3 percent for 
African Americans and 18.8 percent for Hispanics.\1\
---------------------------------------------------------------------------

    \1\ Mortgage denial rates are based on 1997 HMDA data; data for 
selected manufactured housing lenders and subprime lenders are 
excluded from these comparisons.
---------------------------------------------------------------------------

    (iii) Despite strong economic growth, low unemployment, the 
lowest mortgage rates in more than 30 years, and relatively stable 
home prices, there is clear and compelling evidence of deep and 
persistent housing problems for Americans with the lowest incomes. 
The number of very-low-income American households with ``worst 
case'' housing needs remains at an all-time high--5.3 million.\2\
---------------------------------------------------------------------------

    \2\ U.S. Department of Housing and Urban Development. Waiting in 
Vain: Update on America's Rental Housing Crisis. (March, 1999).
---------------------------------------------------------------------------

    (iv) Changing population demographics will result in a need for 
the primary and secondary mortgage markets to meet nontraditional 
credit needs, respond to diverse housing preferences and overcome 
information barriers that many immigrants face. In addition, market 
segments such as single-family rental properties, small multifamily 
properties, manufactured housing, and older inner city properties 
would benefit from the additional financing and pricing efficiencies 
of a more active secondary mortgage market.
    (v) The Low- and Moderate-Income Housing Goals for both GSEs 
were 40 percent in 1996 and 42 percent in 1997. Fannie Mae surpassed 
these goals, with a performance of 45.6 percent in 1996, 45.7 
percent in 1997 and 44.1 percent in 1998. Freddie Mac's performance 
of 41.1 percent in 1996, 42.6 percent in 1997 and 42.9 percent in 
1998 narrowly exceeded these goals.
    (vi) Several studies have shown that both Fannie Mae and Freddie 
Mac lag behind depository institutions and the overall conventional 
conforming market in providing affordable home loans to lower-income 
borrowers and underserved neighborhoods. Fannie Mae has made efforts 
to improve its performance. Freddie Mac, however, has made much less 
improvement, and therefore continues to fall behind Fannie Mae, 
depositories, and the overall market in serving lower-income and 
minority families and their neighborhoods. Thus, there is room for 
both GSEs (but particularly Freddie Mac) to improve their funding of 
single-family home mortgages for lower-income families and 
underserved communities.
    (vii) The GSEs' presence in the goal-qualifying market is 
significantly less than their presence in the overall mortgage 
market. Specifically, HUD estimates that they accounted for 39 
percent of all owner-occupied and rental units financed in the 
primary market in 1997, but only 30 percent of low- and moderate-
income units financed. Their role was even lower for low- and 
moderate-income rental properties, where they accounted for 24 
percent of low- and moderate-income multifamily units financed and 
only 13 percent of low- and moderate-income single-family rental 
units financed.
    (viii) Other issues have also been raised about the GSEs' 
affordable lending performance. A large percentage of the lower-
income loans purchased by the enterprises have relatively high down 
payments, which raises questions about whether the GSEs are 
adequately meeting the mortgage credit needs of lower-income 
families who do not have the cash to make a high down payment. Also, 
while single-family rental properties are an important source of 
low- and moderate-income rental housing, they represent only a small 
portion of the GSEs' business.
    (ix) Freddie Mac has re-entered the multifamily market after 
withdrawing for a time in the early 1990s. Thus, concerns regarding 
Freddie Mac's multifamily capabilities no longer constrain their 
performance with regard to the Low- and Moderate-Income Housing Goal 
and for the Special Affordable Housing Goal to the same degree that 
prevailed at the time the Department issued its 1995 GSE 
regulations. However, Freddie Mac's multifamily presence remains 
proportionately lower than that of Fannie Mae. For example, units in 
multifamily properties accounted for 7.9 percent of Freddie Mac's 
mortgage purchases during 1996-1998, compared with 12.2 percent for 
Fannie Mae. Because a relatively large proportion of multifamily 
units qualify for the Low- and Moderate-Income Housing Goal and for 
the Special Affordable Housing Goal, Freddie Mac's weaker 
multifamily presence is a major factor contributing to its weaker 
overall performance on these two housing goals relative to Fannie 
Mae.
    (x) The overall presence of both GSEs in the multifamily 
mortgage market falls short of their involvement in the single-
family market. Specifically, the GSEs' purchases of 1997 
originations have accounted for 49 percent of the owner market, but 
only 22 percent of the multifamily market. Further expansion of the 
presence of both GSEs in the multifamily market is needed in order 
for them to make significant progress in closing the gaps between 
the affordability of their mortgage purchases and that of the 
overall conventional market.
    (xi) The GSEs have proceeded cautiously in expanding their 
multifamily purchases during the 1990s. Fannie Mae's multifamily 
lending has been described by Standard & Poor's as ``extremely 
conservative,'' and Freddie Mac has not experienced a single default 
on the multifamily mortgages it has purchased since 1993.\3\ By the 
end of the 1998 calendar year, both GSEs' multifamily performance 
had improved to the point where multifamily delinquency rates were 
less than those in single-family.\4\
---------------------------------------------------------------------------

    \3\ ``Final Report of Standard & Poor's to the Office of Federal 
Housing Enterprise Oversight,'' February 3, 1997; Freddie Mac, 1998 
Annual Report to Shareholders, p. 6.
    \4\ Freddie Mac reported delinquency rates of 0.37 for 
multifamily and 0.50 percent for single-family in its 1998 Annual 
Report to Shareholders, p. 30. Corresponding figures for Fannie Mae 
were 0.29 percent for multifamily and 0.58 percent for single-family 
(1998 Annual Report to Shareholders, p. 28).
---------------------------------------------------------------------------

    (xii) Because of the advantages conferred by Government 
sponsorship, the GSEs are in a unique position to provide leadership 
in addressing the excessive cost and difficulty in obtaining 
mortgage financing for underserved segments of the multifamily 
market, including small properties with 5-50 units and properties in 
need of rehabilitation.

B. Factor 1: National Housing Needs

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

1. Homeownership Gaps

    Despite a record national homeownership rate, many Americans, 
including disproportionate numbers of racial and ethnic minorities, 
are shut out of homeownership opportunities. Although the national 
homeownership rate for all Americans was at an all-time high of 66.3 
percent in 1998, the rate for minority households was less. The 
homeownership rate for African-American households was 46.1 percent. 
Similarly, just 44.7 percent of Hispanic households owned a home.
    Importance of Homeownership. Homeownership is one of the most 
common forms of property ownership as well as savings.\5\ In fact, 
home equity is the largest source of wealth for most Americans. 
Median net wealth for renters was less than five percent of the 
median net wealth for homeowners in 1995. Half of all homeowners in 
1995 held more than half of their net wealth in the form of home 
equity. Even among low-income homeowners (household income less than 
$20,000), half held more than 70 percent of their wealth in home 
equity in 1995.\6\ Thus a homeownership gap translates directly into 
a wealth gap.
---------------------------------------------------------------------------

    \5\ According to the National Association of Realtors, Housing 
Market Will Change in New Millennium as Population Shifts, (November 
7, 1998), 45 percent of U.S. household wealth is in the form of home 
equity. Since 1968, home prices have increased each year, on 
average, at the rate of inflation plus up to two percentage points.
    \6\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 1997 (1997).
---------------------------------------------------------------------------

    Homeownership promotes social and community stability by 
increasing the

[[Page 12679]]

number of stakeholders and reducing disparities in the distributions 
of wealth and income. There is growing evidence that planning for 
and meeting the demands of homeownership may reinforce the qualities 
of responsibility and self-reliance. White and Green \7\ provide 
empirical support for the association of homeownership with a more 
responsible, self-reliant citizenry. Both private and public 
benefits are increased to the extent that developing and reinforcing 
these qualities improve prospects for individual economic 
opportunities.
---------------------------------------------------------------------------

    \7\ Michelle J. White, and Richard K. Green. ``Measuring the 
Benefits of Homeowning: Effects on Children,'' Journal of Urban 
Economics. 41 (May 1997), pp. 441-61.
---------------------------------------------------------------------------

    Barriers to Homeownership. Insufficient income, high debt 
burdens, and limited savings are obstacles to homeownership for 
younger families. As home prices skyrocketed during the late 1970s 
and early 1980s, real incomes also stagnated, with earnings growth 
particularly slow for blue collar and less educated workers. Through 
most of the 1980s, the combination of slow income growth and 
increasing rents made saving for home purchase more difficult, and 
relatively high interest rates required large fractions of family 
income for home mortgage payments. Thus, during that period, fewer 
households had the financial resources to meet down payment 
requirements, closing costs, and monthly mortgage payments.
    Economic expansion and lower mortgage rates have substantially 
improved homeownership affordability during the 1990s. Many young, 
lower-income, and minority families who were closed out of the 
housing market during the 1980s have re-entered the housing market. 
However, many of these households still lack the financial resources 
and earning power to take advantage of today's homebuying 
opportunities. Several trends have contributed to the reduction in 
the real earnings of young adults without college education over the 
last 15 years, including technological changes that favor white-
collar employment, losses of unionized manufacturing jobs, and wage 
pressures exerted by globalization. Fully 45 percent of the nation's 
population between the ages of 25 and 34 have no advanced education 
and are therefore at risk of being unable to afford 
homeownership.\8\ 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.
---------------------------------------------------------------------------

    \8\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 1998 (1998).
---------------------------------------------------------------------------

    In addition to low income, high debts are a primary reason 
households cannot afford to purchase a home. According to a 1993 
Census Bureau report, nearly 53 percent of renter families have both 
insufficient income and excessive debt problems that may cause 
difficulty in financing a home purchase.\9\ High debt-to-income 
ratios frequently make potential borrowers ineligible for mortgages 
based on the underwriting criteria established in the conventional 
mortgage market.
---------------------------------------------------------------------------

    \9\ Howard Savage and Peter Fronczek, Who Can Afford to Buy A 
House in 1991?, U.S. Bureau of the Census, Current Housing Reports 
H121/93-3, (July 1993), p. ix.
---------------------------------------------------------------------------

    An additional barrier to homeownership is the fear and 
uncertainty about the buying process and the risks of ownership. A 
study using focus groups with renters found that even among those 
whose financial status would make them capable of homeownership, 
many feel that the buying process was insurmountable because they 
feared rejection by the lender or being taken advantage of.\10\ 
Also, many fear the obligations of ownership, because of the 
concerns about the risk of future deterioration of the house or the 
neighborhood.
---------------------------------------------------------------------------

    \10\ Donald S. Bradley and Peter Zorn. ``Fear of Homebuying: Why 
Financially Able Households May Avoid Ownership,'' Secondary 
Mortgage Markets (1996).
---------------------------------------------------------------------------

    Finally, discrimination in mortgage lending continues to be a 
barrier to homeownership. Disparities in treatment between borrowers 
of different races and neighborhoods of different racial makeup have 
been well documented. These disparities are discussed in the next 
section.

2. Disparities in Mortgage Financing

    Disparities Between Borrowers of Different Races. Research based 
on Home Mortgage Disclosure Act (HMDA) data suggests pervasive and 
widespread disparities in mortgage lending across the Nation. For 
1997, the denial rate for white mortgage applicants was 10.2 
percent, while 23.3 percent of African-American and 18.8 percent of 
Hispanic applicants were denied. Even after controlling for income, 
the African-American denial rate was approximately twice that of 
white applicants. A major study by researchers at the Federal 
Reserve Bank of Boston found that mortgage denial rates remained 
substantially higher for minorities in 1991-93, even after 
controlling for indicators of credit risk.\11\ African-American and 
Hispanic applicants in Boston with the same borrower and property 
characteristics as white applicants had a 17 percent denial rate, 
compared with the 11 percent denial rate experienced by whites. A 
subsequent study conducted at the Federal Reserve Bank of Chicago 
reports similar findings.\12\
---------------------------------------------------------------------------

    \11\ Munnell, Alicia H., Geoffrey M. B. Tootell, Lynn E. Browne, 
and James McEneaney, ``Mortgage Lending in Boston: Interpreting HMDA 
Data,'' American Economic Review. 86 (March 1996).
    \12\ William C. Hunter. ``The Cultural Affinity Hypothesis and 
Mortgage Lending Decisions,'' WP-95-8, Federal Reserve Bank of 
Chicago, (1995). In addition, a study undertaken for HUD also found 
higher denial rates among FHA borrowers for minorities after 
controlling for credit risk. See Ann B. Schnare and Stuart A. 
Gabriel. ``The Role of FHA in the Provision of Credit to 
Minorities,'' ICF Incorporated, Prepared for the U.S. Department of 
Housing and Urban Development, (April 25, 1994).
---------------------------------------------------------------------------

    Several possible explanations for these lending disparities have 
been suggested. The studies by the Boston and Chicago Federal 
Reserve Banks found that racial disparities cannot be explained by 
reported differences in creditworthiness. In other words, minorities 
are more likely to be denied than whites with similar credit 
characteristics, which suggests lender discrimination. In addition, 
loan officers, who may believe that race is correlated with credit 
risk, may use race as a screening device to save time, rather than 
devote effort to distinguishing the creditworthiness of the 
individual applicant.\13\ This violates the Fair Housing Act.
---------------------------------------------------------------------------

    \13\ 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. Underwriting rigidities may fail to 
accommodate creditworthy low-income or minority applicants. For 
example, under traditional underwriting procedures, applicants who 
have conscientiously paid rent and utility bills on time but have 
never used consumer credit would be penalized for having no credit 
record. Applicants who have remained steadily employed, but have 
changed jobs frequently, would also be penalized. Over the past few 
years, lenders, private mortgage insurers, and the GSEs have 
adjusted their underwriting guidelines to take into account these 
special circumstances of lower-income families. Many of the changes 
recently undertaken by the industry to expand homeownership have 
focused on finding alternative underwriting guidelines to establish 
creditworthiness that do not disadvantage creditworthy minority or 
low-income applicants.
    However, because of the enhanced roles of credit scoring and 
automated underwriting in the mortgage origination process, it is 
unclear to what degree the reduced rigidity in industry standards 
will benefit borrowers who have been adversely impacted by the 
traditional guidelines. Some industry observers have expressed a 
concern that the greater flexibility in the industry's written 
underwriting guidelines may not be reflected in the numerical credit 
and mortgage scores which play a major role in the automated 
underwriting systems that the GSEs and others have developed. Thus 
lower-income and particularly minority loan applicants, who often 
have lower credit scores than other applicants, may be dependent on 
the willingness of lenders to take the time to look beyond such 
credit scores and consider any appropriate ``mitigating factors,'' 
such as the timely payment of their bills, in the underwriting 
process. For example, there is a concern in the industry that a 
``FICO'' score less than 620 means an automatic rejection of a loan 
application without further consideration of any such factors.\14\ 
This could disproportionately affect minority applicants. More 
information on the distribution of credit scores and on the

[[Page 12680]]

effects of implementing automated underwriting systems is 
needed.\15\
---------------------------------------------------------------------------

    \14\ The FICO score, developed by Fair, Isaac and Company, is 
summary index of an individual's credit history. The FICO score is 
based on elements from the applicant's credit report, such as number 
of delinquencies in the past year, number of trade lines, and the 
amount owed on trade lines as compared to the available maximum 
credit limits. The FICO score is said to reflect the credit risk of 
the applicant and a score of 620 is often cited as a threshold 
between being an acceptable and an unacceptable credit risk.
    \15\ Section 3.b of this appendix provides a further discussion 
of automated underwriting.
---------------------------------------------------------------------------

    Disparities Between Neighborhoods. Mortgage credit also appears 
to be less accessible in low-income and high-minority neighborhoods. 
As discussed in Appendix B, 1997 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 (23 percent versus 
12 percent). Numerous studies have found that mortgage denial rates 
are higher in low-income census tracts, even accounting for other 
loan and borrower characteristics.\16\ These geographic disparities 
can be the result of cost factors, such as the difficulty of 
appraising houses in these areas because of the paucity of previous 
sales of comparable homes. Sales of comparable homes may also be 
difficult to find due to the diversity of central city 
neighborhoods. The small loans prevalent in low-income areas are 
less profitable to lenders because up-front fees to loan originators 
are frequently based on a percentage of the loan amount, although 
the costs incurred are relatively fixed. Geographic disparities in 
mortgage lending and the issue of mortgage redlining are discussed 
further in Appendix B.
---------------------------------------------------------------------------

    \16\ 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 problems faced by low-income homeowners and renters 
are documented in HUD's ``Worst Case Housing Needs'' report. This 
report, which is prepared biennially for Congress, is based on the 
American Housing Survey (AHS), conducted every two years by the 
Census Bureau for HUD. The latest report analyzes data from the 1995 
AHS and focuses on the housing problems faced by low-income renters, 
but some data is also presented on families living in owner-occupied 
housing. In introducing a recent HUD report, Secretary Cuomo noted 
that it found ``clear and compelling evidence of deep and persistent 
housing problems for Americans with the lowest incomes.''\17\
---------------------------------------------------------------------------

    \17\ Rental Housing Assistance--The Crisis Continues: The 1997 
Report to Congress on Worst Case Housing Needs, Department of 
Housing and Urban Development, Office of Policy Development and 
Research, (April 1998), p. i. All statistics in this subsection are 
taken from this report, except as noted.
---------------------------------------------------------------------------

    The ``Worst Cases'' report measures three types of problems 
faced by homeowners and renters:
    (i) 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'');
    (ii) 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
    (iii) Crowded housing, where there is more than one person per 
room in a residence.
    The study reveals that in 1995, 5.3 million households had 
``worst case'' housing needs, defined as housing costs greater than 
50 percent of household income or severely inadequate housing among 
unassisted households. A preliminary HUD analysis of 1997 AHS data 
indicates that worst case needs have remained at or near this 
level.\18\
---------------------------------------------------------------------------

    \18\ U.S. Department of Housing and Urban Development. Waiting 
in Vain: Update on America's Rental Housing Crisis. (March, 1999), 
section I.
---------------------------------------------------------------------------

a. Problems Faced by Owners

    Of the 63.5 million owner households in 1995, 4.9 million (8 
percent) confronted a severe cost burden and another 8.1 million (13 
percent) faced a moderate cost burden. There were 1.2 million 
households with severe physical problems and 0.9 million which 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.\19\ Nearly a third of these households faced a severe 
cost burden, and an additional 22 percent faced a moderate cost 
burden. And nearly 10 percent of these families lived in severely or 
moderately inadequate housing, while 3 percent faced overcrowding. 
Only 40 percent of very low-income owners reported no problems.
---------------------------------------------------------------------------

    \19\ Very low-income households are defined in the report as 
those whose income, adjusted for family size, is less than 50 
percent of area median income. This differs from the definition 
adopted by Congress in the GSE Act of 1992, which uses a cutoff of 
60 percent and which does not adjust income for family size for 
owner-occupied dwelling units.
---------------------------------------------------------------------------

    Over time the percentage of owners faced with severe or moderate 
physical problems has decreased, as has the portion living in 
overcrowded conditions. However, affordability problems have grown--
the shares facing severe (moderate) cost burdens were only 3 percent 
(5 percent) in 1978, but rose to 5 percent (11 percent) in 1989 and 
8 percent (13 percent) in 1995. 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.\20\ 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 1995.
---------------------------------------------------------------------------

    \20\ Edward N. Wolff, ``Recent Trends in the Size Distribution 
of Household Wealth,'' The Journal of Economic Perspectives, 12(3), 
(Summer 1998), p. 137.
---------------------------------------------------------------------------

b. Problems Faced by Renters

    Problems of all three types listed above are more common among 
renters than among homeowners. In 1995 there were 6.2 million renter 
households (18 percent of all renters) who paid more than 50 percent 
of their income for rent.\21\ Another 8 million faced a moderate 
rent burden, thus in total 40 percent of renters paid more than 30 
percent of their income for rent.
---------------------------------------------------------------------------

    \21\ Rent is measured in this report as gross rent, defined as 
contract rent plus the cost of any utilities which are not included 
in contract rent.
---------------------------------------------------------------------------

    Among very low-income renters, 70 percent faced an affordability 
problem, including 41 percent who paid more than half of their 
income in rent. More than one-third of renters with incomes between 
51 percent and 80 percent of area median family income also paid 
more than 30 percent of their income for rent.
    Affordability problems have increased over time among renters. 
The shares of renters with severe (moderate) rent burdens rose from 
14 percent (18 percent) in 1978 to 15 percent (21 percent) in 1989 
and 18 percent (22 percent) in 1995.
    The share of families living in inadequate housing in 1995 was 
higher for renters (9 percent) than for owners (5 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 has diminished over time, 
while affordability problems have grown.
    Other problems faced by renters discussed in the ``Worst Cases'' 
report include the loss between 1993 and 1995 of 900,000 rental 
units affordable to very low-income families, the increase in 
``worst case needs'' among working families between 1991 and 1995, 
and the shortage of units affordable to very low-income households 
(especially in the West).
    The ``Worst Cases'' report presented analysis of 20-year trends 
in affordable housing units up through 1995, showing a steady 
decline in the number of such units. A recently-released HUD 
analysis of housing vacancy survey data reveals that this trend has 
continued since 1995, and that in the two years from 1996 to 1998 
the number of units that rent for less than $300 (inflation-
adjusted) declined by 19 percent.\22\ The same study reports the 
median asking rent for new rental units as $726, or beyond the 
affordable range.
---------------------------------------------------------------------------

    \22\ ``Waiting in Vain'' (cited above), section III.2.
---------------------------------------------------------------------------

    HUD's recent study on market trends includes also an analysis of 
trends in the Consumer Price Index from 1996 to 1998.\23\ During 
this two-year period the price index for all items grew by 3.9 
percent, but the price index for residential rent rose 6.2 percent. 
The same report also cites Bureau of Labor Statistics data showing 
that rents slightly outpaced income between 1995 and 1997 for the 20 
percent of U.S. households with the lowest incomes. The report 
concludes that low-income renters are continuing to face an 
affordability crisis.
---------------------------------------------------------------------------

    \23\ Ibid., section III.1.
---------------------------------------------------------------------------

4. Other National Housing Needs

    In addition to the broad housing needs discussed above, there 
are additional needs confronting specific sectors of the housing and 
mortgage markets. This section presents a brief discussion of three 
such areas and the roles that the GSEs play or might play in 
addressing the needs in these areas. Other

[[Page 12681]]

needs are discussed throughout these appendices.

a. Single-family Rental Housing

    The 1995 American Housing Survey (AHS) reported that 43 percent 
of all rental housing units are located in ``multifamily'' 
properties--i.e., properties that contain 5 or more rental units. 
The bulk (57 percent) of rental units are found in the ``mom and pop 
shops'' of the rental market--``single-family'' rental properties, 
containing 1-4 units. These small properties are largely 
individually-owned and managed, and in many cases the owner-managers 
live in one of the units in the property. They include many 
properties in older cities, such as the duplexes in Baltimore and 
the triple-deckers in Boston. A number of these single-family rental 
properties are in need of financing for rehabilitation, discussed in 
the next subsection.
    Single-family rental units play an especially important role in 
lower-income housing. The 1995 AHS found that 57 percent of such 
units were affordable to very low-income families--exceeding the 
corresponding share of 49 percent for multifamily units. These units 
also play a significant role in the GSEs' performance on the housing 
goals, since 34 percent of the single-family rental units financed 
by the GSEs in 1997 were affordable to very low-income families.
    There is not, however, a strong secondary market for single-
family rental mortgages. While single-family rental properties 
comprise a large segment of the rental stock for lower-income 
families, they make up a small portion of the GSEs' business. In 
1997 the GSEs purchased $11.6 billion in mortgages for such 
properties, but this represented only 4 percent of the total dollar 
volume of each enterprise's 1997 business and only 7 percent of 
total single-family units financed by each GSE. With regard to their 
credit market share, HUD estimates that the GSEs have financed only 
about 13 percent of all single-family rental units that received 
financing in 1997, well below the GSEs' estimated market share of 49 
percent for single-family owner properties.
    Given the large size of this market, the high percentage of 
these units which qualify for the GSEs' housing goals, and the 
weakness of the secondary market for mortgages on these properties, 
an enhanced presence by Fannie Mae and Freddie Mac in the single-
family rental mortgage market would seem warranted.\24\
---------------------------------------------------------------------------

    \24\ A detailed discussion of the GSE's activities in this area 
is contained in Theresa R. Diventi, The GSE's 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).
---------------------------------------------------------------------------

b. Rehabilitation Problems of Older Areas

    A major problem facing lower-income households is that low-cost 
housing units continue to disappear from the existing housing stock. 
Older properties are in need of upgrading and rehabilitation. These 
aging properties are concentrated in central cities and older inner 
suburbs, and they include not only detached single-family homes, but 
also small multifamily properties that have begun to deteriorate.
    The ability of the nation to maintain the quality and 
availability of the existing affordable housing stock and to 
stabilize the neighborhoods where it is found depends on an adequate 
supply of credit to rehabilitate and repair older units. But 
obtaining the funds to fix up older properties can be difficult. The 
owners of small rental properties in need of rehabilitation may be 
unsophisticated in obtaining financing. The properties are often 
occupied, and this can complicate the rehabilitation process. 
Lenders may be reluctant to extend credit because of a sometimes-
inaccurate perception of high credit risk involved in such loans.
    The GSEs and other market participants have recently begun to 
pay more attention to these needs for financing of affordable rental 
housing rehabilitation.\25\ However, extra effort is required, due 
to the complexities of rehabilitation financing, as there is still a 
need to do more.
---------------------------------------------------------------------------

    \25\ One program that shows promise is Fannie Mae's HomeStyle 
Home IMprovement Mortgage Loan Product. Under this program, Fannie 
Mae will purchase mortgages that finance the purchase and 
rehabilitation of 1- to 4-unit properties in ``as-is'' condition. 
The mortgage amount is limited to 90 percent of the appraised ``as 
completed'' value, with the rehab amount not to exceed 50 percent of 
this value.
---------------------------------------------------------------------------

c. Small Multifamily Properties

    There is evidence that small multifamily properties with 5-50 
units have been adversely affected by differentials in the cost of 
mortgage financing relative to larger properties.\26\ While mortgage 
loans can generally be obtained for most properties, the financing 
that is available is relatively expensive, with interest rates as 
much as 150 basis points higher than those on standard multifamily 
loans. Loan products are characterized by shorter terms and 
adjustable interest rates. Borrowers typically incur costs for 
origination and placement fees, environmental reviews, architectural 
certifications (on new construction or substantial rehabilitation 
projects), inspections, attorney opinions and certifications, credit 
reviews, appraisals, and market surveys.\27\ Because of a large 
fixed element, these costs are usually not scaled according to the 
mortgage loan amount or number of dwelling units in a property and 
consequently are often prohibitively high on smaller projects.
---------------------------------------------------------------------------

    \26\ See Drew Schneider and James Follain, ``A New Initiative in 
the Federal Housing Administration's Office of Multifamily Housing 
Programs: An Assessment of Small Projects Processing,'' Cityscape: A 
Journal of Policy Development and Research 4(1), (1998), pp. 43-58; 
and William Segal and Christopher Herbert, Segmentation of the 
Multifamily Mortgage Market: The Case of Small Properties, paper 
presented to annual meetings of the American Real Estate and Urban 
Economics Association, (January 2000).
    \27\ These costs have been estimated at $30,000 for a typical 
transaction. Presentation by Jeff Stern, Vice President, Enterprise 
Mortgage Investments, HUD GSE Working Group, July 23, 1998. The most 
comprehensive account of the multifamily housing finance system as 
it relates to small properties is contained in Schneider and Follain 
(see above reference).
---------------------------------------------------------------------------

d. Other Needs

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

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

    This section discusses economic, housing, and demographic 
conditions that affect the single-family mortgage market. After a 
review of housing trends and underlying demographic conditions that 
influence homeownership, the discussion focuses on specific issues 
related to the single-family owner mortgage market. This subsection 
includes descriptions of recent market interest rate trends, 
homebuyer characteristics, and the state of affordable lending. 
Section D follows with a discussion of the economic, housing, and 
demographic conditions affecting the multifamily mortgage market.

1. Recent Trends in the Housing Market

    Solid economic growth, low interest rates, price stability, and 
the lowest unemployment rate since 1969 combined to make 1998 a very 
strong year for the housing market. The employment-population ratio 
reached a record 64.1 percent last year, and a broad measure of 
labor market distress, combining the number of unemployed and the 
duration of unemployment, was down by 47 percent from its 1992 
peak.\28\ Rising real wages, a strong stock market, and higher home 
prices all contributed to a continuation of the rise in net 
household worth, following an estimated $4 trillion gain in 1997, 
contributing to the strong demand for housing.\29\
---------------------------------------------------------------------------

    \28\ This measure is discussed in Paul B. Manchester, ``A New 
Measure of Labor Market Distress,'' Challenge, (November/December 
1982).
    \29\ Office of Federal Housing Enterprise Oversight, 1998 Report 
to Congress, (June 1998), p. 28.
---------------------------------------------------------------------------

    Homeownership Rate. In 1980, 65.6 percent of Americans owned 
their own home, but due to the unsettled economic conditions of the 
1980s, this share fell to 63.8 percent by 1989. Major gains in 
ownership have occurred over the last few years, with the 
homeownership rate reaching a record level of 66.3 percent in 1998, 
when the number of households owning their own home was 9 million 
greater than in 1989.

[[Page 12682]]

    Gains in homeownership have been widespread over the last four 
years.\30\ As a result, the homeownership rate rose from:
---------------------------------------------------------------------------

    \30\ 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.
---------------------------------------------------------------------------

    (i) 42.0 percent in 1993 to 46.1 percent in 1998 for African 
American households,
    (ii) 39.4 percent in 1993 to 44.7 percent in 1998 for Hispanic 
households,
    (iii) 73.7 percent in 1993 to 77.3 percent in 1998 for married 
couples with children,
    (iv) 65.1 percent in 1993 to 66.9 percent in 1998 for household 
heads aged 35-44, and
    (v) 48.9 percent in 1993 to 50.0 percent in 1998 for central 
city residents.
    However, as these figures demonstrate, sizable gaps in 
homeownership remain--gaps which must be reduced if President 
Clinton's National Housing Strategy's goal of a homeownership rate 
of 67.5 percent by the year 2000 is to be met.
    Sales of New and Existing Homes.\31\ New home sales rose at a 
rate of 10 percent per year between 1991 and 1998 and exceeded the 
previous record level (set in 1977) by eight percent in 1998. The 
market for new homes has been strong throughout the nation, with 
record sales in the South and Midwest during 1998. New home sales in 
the Northeast and West, while strong, are running below the peak 
levels attained during their strong job markets of the mid-1980s and 
late-1970s, respectively.
---------------------------------------------------------------------------

    \31\ All of the home sales data in this section are obtained 
from U.S. Housing Market Conditions, 2nd Quarter 1999, U.S. 
Department of Housing and Urban Development, (August 1999).
---------------------------------------------------------------------------

    The National Association of Realtors reported that 4.8 million 
existing homes were sold in 1998, overturning the old record set in 
1997 by nearly 14 percent. The combined new and existing home sales 
also set a record of 5.7 million last year. Since existing homes 
account for more than 80 percent of the total market and sales of 
existing homes are strong throughout the country, combined sales 
reach record levels in three of the four major regions of the nation 
and came within 99 percent of the record in the Northeast.
    One of the strongest sectors of the housing market in recent 
years has been shipments of manufactured homes, which more than 
doubled between 1991 and 1996, and leveled off at the 1996 record 
level during 1997 before rising slightly to 373,000 in 1998. Over 
two-thirds of manufactured home placements were in the South, where 
they comprised more than one-third of total new homes sold in 1998.
    Economy/Housing Market Prospects. As noted above, the U.S. 
economy is coming off several years of economic expansion 
accompanied by low interest rates and high housing affordability. In 
fact, 1998 was a record year for the housing market. This leads to 
an important issue, what are the future prospects for the housing 
market?
    While the housing market is expected to slow down over the next 
four years, the sales of existing homes during 1999 are on a record 
breaking pace of over five million single-family units.\32\ Between 
2000 and 2003, existing single-family home sales are expected to 
average 4.4 million units. In addition to existing home sales, 
housing starts are expected to average 1.5 million units over the 
same period. Housing should remain affordable, as indicated by out-
of-pocket costs as a share of disposable income, which is expected 
to continue its downward trend through 2003, dipping below 25 
percent. According to Standard & Poor's/DRI, mortgage interest rates 
are expected to average 7.1 percent over the next four years for a 
30-year fixed rate mortgage.
---------------------------------------------------------------------------

    \32\ Existing home sales, housing starts, housing affordability 
and 30-year fixed rate mortgage rate forecasts are obtained from 
Standard & Poor's DRI, The U.S. Economy. (September 1999), pp. 53-5.
---------------------------------------------------------------------------

    The Congressional Budget Office (CBO) \33\ projects that real 
Gross Domestic Product will grow at an average rate of 2.4 percent 
through 2003, down somewhat from the expected 4.0 percent growth 
rate during 1999. The ten-year Treasury rate is projected to average 
5.6 percent between 2000 and 2003. 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 remain low over the next four years, ranging between 4.6 
and 5.1 percent. CBO expects housing starts to average 1.6 million 
units between 2000 and 2003, slightly off the 1999 level.
---------------------------------------------------------------------------

    \33\ Real GDP, unemployment, inflation, and treasury note 
interest rate projects are obtained for fiscal years 2000-2009 from 
The Economic and Budget Outlook: An Update, Washington DC: 
Congressional Budget Office, (July 1, 1999).
---------------------------------------------------------------------------

    Certain risks exist, however, which could undermine the well-
being of the economy. The probability of a recession still exists 
for the next couple of years. Under a pessimistic scenario (10 
percent probability), Standard & Poor's DRI predicts that housing 
starts could fall during 2000, but by the end of the year, the 
economy would be well on its way to recovery with housing starts 
increasing steadily.\34\ An alternate scenario has a recession 
arriving in 2002 (which DRI predicts with a probability of 30 
percent). Under this scenario, housing starts would fall, but 
rebound strongly, along with the economy, in 2003.\35\
---------------------------------------------------------------------------

    \34\ Standard & Poor's DRI, The U.S. Economy. (September 1999), 
p. 54.
    \35\ Standard & Poor's DRI, The U.S. Economy. (September 1999), 
p. 54.
---------------------------------------------------------------------------

2. Underlying Demographic Conditions

    Over the next 20 years, the U.S. population is expected to grow 
by an average of 2.4 million per year. This will likely result in 
1.1 to 1.2 million new households per year, creating a continuing 
need for additional housing.\36\ This section discusses important 
demographic trends behind these overall numbers that will likely 
affect housing demand in the future. These demographic forces 
include the baby-boom, baby-bust and echo baby-boom cycles; 
immigration trends; ``trade-up buyers;'' non-traditional and single 
households; and the growing income inequality between people with 
different levels of education.
    As explained below, the role of traditional first-time 
homebuyers, 25-to-34 year-old married couples, in the housing market 
will be smaller in the next decade due to the aging of the baby-boom 
population. However, growing demand from immigrants and non-
traditional homebuyers will likely fill in the void. The echo baby-
boom (that is, children of the baby-boomers) will also add to 
housing demand later in the next decade. Finally, the growing income 
inequality between people with and without a post-secondary 
education will continue to affect the housing market.
---------------------------------------------------------------------------

    \36\ National Association of Realtors. Housing Market Will 
Change in New Millennium as Population Shifts. (November 7, 1998).
---------------------------------------------------------------------------

    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.\37\
---------------------------------------------------------------------------

    \37\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 1998. (1998), p. 14.
---------------------------------------------------------------------------

    As the youngest of the baby-boomers, those born in the 1960s, 
reached their peak homebuying years in the 1990s, housing became 
more affordable. While this cohort has achieved a homeownership rate 
equal to the middle baby-boomers, they live in larger, more 
expensive homes. As the baby-boom generation ages, demand for 
housing from this group is expected to wind down.\38\
---------------------------------------------------------------------------

    \38\ Joint Center for Housing Studies of Harvard University. 
(1998), 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 is expected to 
lead to reduced housing demand during the next decade, though, as 
discussed below, other factors have kept the housing market very 
strong in the 1990s. However, the echo baby-boom generation (the 
children of the baby-boomers, who were born after 1977), while 
smaller than the baby-boom generation, will reach peak homebuying 
age later in the first decade of the new millennium, softening the 
blow somewhat.\39\
---------------------------------------------------------------------------

    \39\ National Association of Realtors. Housing Market Will 
Change in New Millennium As Population Shifts. (November 7, 1998).
---------------------------------------------------------------------------

    Immigrant Homebuyers. Past, present, and future immigration will 
also help keep homeownership growth at a respectable level. During 
the 1980s, 6 million legal immigrants entered the United States, 
compared with 4.2 million during the 1970s and 3.2 million during 
the 1960s.\40\ As a result, the foreign-born population of the 
United States doubled from 9.6 million in 1970 to 19.8 million in 
1990, and is expected

[[Page 12683]]

to reach 31 million by 2010.\41\ While immigrants tend to rent their 
first homes upon arriving in the United States, homeownership rates 
are substantially higher among those that have lived here for at 
least 6 years. In 1996, the homeownership rate for recent immigrants 
was 14.7 percent while it was 67.4 percent for native-born 
households. For foreign-born naturalized citizens, the homeownership 
rate after six years was a remarkable 66.9 percent.\42\
---------------------------------------------------------------------------

    \40\ Joint Center for Housing Studies of Harvard University. 
(1998).
    \41\ John R. Pitkin and Patrick A. Simmons. ``The Foreign-Born 
Population to 2010: A Prospective Analysis by Country of Birth, Age, 
and Duration of U.S. Residence,'' Journal of Housing Research. 7(1) 
(1996), pp. 1-31.
    \42\ Fred Flick and Kate Anderson. ``Future of Housing Demand: 
Special Markets,'' Real Estate Outlook. (1998), p. 6.
---------------------------------------------------------------------------

    Immigration is projected to add even more new Americans in the 
1990s, which will help offset declines in the demand for housing 
caused by the aging of the baby-boom generation. While it is 
projected that immigrants will account for less than four percent of 
all households in 2010, without the increase in the number of 
immigrants, household growth would be 25 percent lower over the next 
15 years. As a result of the continued influx of immigrants and the 
aging of the domestic population, household growth over the next 
decade should remain at or near its current pace of 1.1-1.2 million 
new households per year, even though population growth is slowing. 
If this high rate of foreign immigration continues, it is possible 
that first-time homebuyers will make up as much as half of the home 
purchasing market over the next several years.\43\
---------------------------------------------------------------------------

    \43\ Mark A. Calabria. ``The Changing Picture of Homebuyers,'' 
Real Estate Outlook. (May 1999), p. 10.
---------------------------------------------------------------------------

    Past and future immigration will lead to increasing racial and 
ethnic diversity, especially among the young adult population. As 
immigrant minorities account for a growing share of first-time 
homebuyers in many markets, HUD and others will have to intensify 
their focus on removing discrimination from the housing and mortgage 
finance systems. The need to meet nontraditional credit needs, 
respond to diverse housing preferences, and overcome the information 
barriers that many immigrants face will take on added importance.
    Trade-up Buyers. The fastest growing demographic group in the 
early part of the next millennium will be 45- to 65-year olds. This 
will translate into a strong demand for upscale housing and second 
homes. The greater equity resulting from recent increases in home 
prices should also lead to a larger role for ``trade-up buyers'' in 
the housing market during the next 10 to 15 years.
    Nontraditional and Single Homebuyers. While overall growth in 
new households has slowed down, nontraditional households have 
become more important in the homebuyer market. With later marriages 
and more divorces, single-person and single-parent households have 
increased rapidly. First-time buyers include a record number of 
never-married single households, although their ownership rates 
still lag those of married couple households. According to the 
Chicago Title and Trust's Home Buyers Surveys, the share of first-
time homebuyers who were never-married singles rose from 21 percent 
in 1991 to 37 percent in 1996, and to a record 43 percent in 1997. 
The shares for divorced/separated and widowed first-time homebuyers 
have stayed constant over the period, at eight percent and one 
percent, respectively.\44\ The National Association of Realtors 
reports that ``single individuals, unmarried couples and minorities 
are entering the market as first-time buyers in record numbers.'' 
\45\ With the increase in single person households, it is expected 
that there will be a greater need for apartments, condominiums and 
townhomes.
---------------------------------------------------------------------------

    \44\ Chicago Title and Trust Family of Insurers, Who's Buying 
Homes in America. (1998).
    \45\ Calabria. (May 1999), p. 11.
---------------------------------------------------------------------------

    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. Single-parent 
households are also expected to decline as the baby-boom generation 
ages out of the childbearing years. For these reasons, 
nontraditional homebuyers may account for a smaller share of the 
housing market in the future.
    Growing Income Inequality. The Census Bureau recently reported 
that the top 5 percent of American households received 21.7 percent 
of aggregate household income in 1997, up sharply from 16.1 percent 
in 1977. The share accruing to the lowest 80 percent of households 
fell accordingly, from 56.5 percent in 1977 to 50.7 percent in 1997. 
The share of aggregate income accruing to households between the 
80th and 95th percentiles of the income distribution was virtually 
unchanged over this period.\46\
---------------------------------------------------------------------------

    \46\ Bureau of the Census, ``Money Income in the United States: 
1997,'' Current Population Report P60-200, (September 1998).
---------------------------------------------------------------------------

    The increase in income inequality over the past two decades has 
been especially significant between those with and those without 
post-secondary education. The Census Bureau reports that by 1997, 
the mean income of householders with a high school education (or 
less) was less than half that for householders with a bachelor's 
degree (or more). According to the Joint Center for Housing Studies, 
inflation-adjusted median earnings of men aged 25 to 34 with only a 
high-school education decreased by 14 percent between 1989 and 
1995.\47\ So, while homeownership is highly affordable, this cohort 
lacks the financial resources to take advantage of the opportunity. 
As discussed earlier, the days of the well-paying unionized factory 
job have passed. They have given way to technological change that 
favors white-collar jobs requiring college degrees, and wages in the 
manufacturing jobs that remain are experiencing downward pressures 
from economic globalization. The effect of this is that workers 
without the benefit of a post-secondary education find their demand 
for housing constrained.
---------------------------------------------------------------------------

    \47\ Joint Center for Housing Studies of Harvard University. 
State of the Nation's Housing 1998. (1998).
---------------------------------------------------------------------------

3. Single-Family Owner Mortgage Market

    The mortgage market has undergone a great deal of growth and 
change over the past few years. Low interest rates, modest increases 
in home prices, and growth in real household income have increased 
the affordability of housing and resulted in a mortgage market boom. 
Total originations of single-family loans increased from $458 
billion in 1990 to $859 billion in 1997 and then jumped to $1.507 
trillion during the heavy refinancing year of 1998.\48\ There has 
also been many changes in the structure and operation of the 
mortgage market. Innovations in lending products, added flexibility 
in underwriting guidelines, the development of automated 
underwriting systems and the rise of the subprime market, have had 
impacts on both the overall market and affordable lending during the 
1990s.
---------------------------------------------------------------------------

    \48\ Data for 1990-97 from U.S. Housing Market Conditions, 1st 
Quarter 1999, U.S. Department of Housing and Urban Development, (May 
1999), Table 17; 1998 from the Mortgage Bankers Association.
---------------------------------------------------------------------------

    The section starts with a review of trends in the market for 
mortgages on single-family owner-occupied housing. Next, trends in 
affordable lending, including new initiatives and changes to 
underwriting guidelines and the prospects for potential homebuyers 
are discussed. The section concludes with a summary of the activity 
of the GSEs relative to originations in the primary mortgage market.

a. Basic Trends in the Mortgage Market

    Interest Rate Trends. The high and volatile mortgage rates of 
the 1980s and early 1990s have given way to a period with much lower 
and more stable rates in the last six years. Interest rates on 
mortgages for new homes were above 12 percent as the 1980s began and 
quickly rose to more than 15 percent.\49\ After 1982, they drifted 
downward slowly to the 9 percent range in 1987-88, before rising 
back into double-digits in 1989-90. Rates then dropped by about one 
percentage point a year for three years, reaching a low of 6.8 
percent in October-November 1993 and averaging 7.2 percent for the 
year as a whole.
---------------------------------------------------------------------------

    \49\ Interest rates in this section are effective rates paid on 
conventional home purchase mortgages on new homes, based on the 
Monthly Interest Rate Survey (MIRS) conducted by the Federal Housing 
Finance Board and published by the Council of Economic Advisers 
annually in the Economic Report of the President and monthly in 
Economic Indicators. These are average rates for all loan types, 
encompassing 30-year and 15-year fixed-rate mortgages and adjustable 
rate mortgages.
---------------------------------------------------------------------------

    Mortgage rates turned upward in 1994, peaking at 8.3 percent in 
early 1995, but fell to the 7.5 percent-7.9 percent range for most 
of 1996 and 1997. However, rates began another descent in late-1997 
and averaged 6.95 percent for 30-year fixed rate conventional 
mortgages during 1998, the lowest level since 1968.\50\
---------------------------------------------------------------------------

    \50\ U.S. Housing Market Conditions, 2nd Quarter 1999, (August 
1999), Table 12.
---------------------------------------------------------------------------

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

[[Page 12684]]

mortgages (ARMs) are more attractive when rates are high, because 
they carry lower rates than FRMs and because buyers may hope to 
refinance to a FRM when mortgage rates decline. Thus the Federal 
Housing Finance Board (FHFB) reports that the ARM share of the 
market jumped from 20 percent in the low-rate market of 1993 to 39 
percent when rates rose in 1994.\51\ The ARM share has since trended 
downward, falling to 22 percent in 1997 and a record low of 12 
percent in 1998.
---------------------------------------------------------------------------

    \51\ All statistics in this section are taken from the Federal 
Housing Finance Board's MIRS.
---------------------------------------------------------------------------

    In 1997 the term-to-maturity was 30 years for 83 percent of 
conventional home purchase mortgages. Other maturities included 15 
years (11 percent of mortgages), 20 years (2 percent), and 25 years 
(1 percent). The average term was 27.5 years, up slightly from 26.9 
years in 1996, but within the narrow range of 25-28 years which has 
prevailed since 1975.
    One dimension of the mortgage market which has changed in recent 
years is the increased popularity of low- or no-point mortgages. 
FHFB reports that average initial fees and charges (``points'') have 
decreased from 2.5 percent of loan balance in the mid-1980s to 2 
percent in the late-1980s, 1.5 percent in the early 1990s, and less 
than 1.0 percent in 1995-97. Last year 21 percent of all loans were 
no-point mortgages. These lower transactions costs have increased 
the propensity of homeowners to refinance their mortgages.\52\
---------------------------------------------------------------------------

    \52\ 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 recent major change in the conventional mortgage market 
has been the proliferation of high loan-to-value ratio (LTV) 
mortgages. Loans with LTVs greater than 90 percent (that is, down 
payments of less than 10 percent) made up less than 10 percent of 
the market in 1989-91, but 25 percent of the market in 1994-97. 
Loans with LTVs less than or equal to 80 percent fell from three-
quarters of the market in 1989-91 to an average of 56 percent of 
mortgages originated in 1994-97. As a result, the average LTV rose 
from 75 percent in 1989-91 to nearly 80 percent in 1994-97.\53\
---------------------------------------------------------------------------

    \53\ Other sources of data on loan-to-value ratios such as the 
American Housing Survey and the Chicago Title and Trust Company 
indicated 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.
---------------------------------------------------------------------------

    The statistics cited above pertain only to home purchase 
mortgages. Refinance mortgages generally have shorter terms and 
lower loan-to-value ratios than home purchase mortgages.
    Mortgage Originations: Refinance Mortgages. Mortgage rates 
affect the volume of both home purchase mortgages and mortgages used 
to refinance an existing mortgage. The effects of mortgage rates on 
the volume of home purchase mortgages are felt through their role in 
determining housing affordability, discussed in the next subsection. 
However, the largest impact of rate swings on single-family mortgage 
originations is reflected in the volume of refinancings.
    During 1992-93, homeowners responded to the lowest rates in 25 
years by refinancing existing mortgages. In 1989-90 interest rates 
exceeded 10 percent, and refinancings accounted for less than 25 
percent of total mortgage originations.\54\ 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.
---------------------------------------------------------------------------

    \54\ 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.\55\ Total single-family mortgage 
originations bottomed out at $639 billion in 1995, when the 
refinance share was only 15 percent. This meant that refinance 
volume declined by more than 80 percent in just two years.
---------------------------------------------------------------------------

    \55\ 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.
---------------------------------------------------------------------------

    A second surge in refinancings began in late-1997, abated 
somewhat in early 1998, but regained momentum in June 1998. The 
refinance share rose above 30 percent in mid-1997, exceeded 40 
percent in late-1997, and peaked at 64 percent in January, before 
falling to 40 percent by May 1998. This share increased steadily 
over the June-September 1998 period, and averaged 50 percent for 
1998. Total originations, driven by the volume of refinancings, 
amounted to $859 billion in 1997 and were $1.507 trillion in 1998, 
nearly 50 percent higher than the previous record level of $1.02 
trillion attained in 1993. Total refinance mortgage volume in 1998 
was estimated to be nearly 10 times the level attained in 1995. The 
1997-98 refinance wave reflects other factors besides interest 
rates, including greater borrower awareness of the benefits of 
refinancing, a highly competitive mortgage market, and the enhanced 
ability of the mortgage industry (including the GSEs), utilizing 
automated underwriting and mortgage origination systems, to handle 
this unprecedented volume expeditiously.
    Mortgage Originations: Home Purchase Mortgages. In 1972 the 
median price of existing homes in the United States was $27,000 and 
mortgage rates averaged 7.52 percent; thus with a 20 percent down 
payment, a family needed an income of $7,200 to qualify for a loan 
on a median-priced home. Actual median family income was $11,100, 
exceeding qualifying income by 55 percent. The National Association 
of Realtors (NAR) has developed a housing affordability index, 
calculated as the ratio of median income to qualifying income, which 
was 155 in 1972.
    By 1982 NAR's affordability index had plummeted to 70, 
reflecting a 154 percent increase in home prices and a doubling of 
mortgage rates over the decade. That is, qualifying income rose by 
nearly 400 percent, to $33,700, while median family income barely 
doubled, to $23,400. With so many families priced out of the market, 
single-family mortgage originations amounted to only $97 billion in 
1982.
    Declining interest rates and the moderation of inflation in home 
prices have led to a dramatic turnaround in housing affordability in 
the last decade and a half. Remarkably, qualifying income in 1993 
was $27,700 in 1993--$6,000 less than it had been in 1982. Median 
family income reached $37,000 in 1993, thus the NAR's housing 
affordability index reached 133, reflecting the most affordable 
housing in 20 years. Housing affordability has remained at about 130 
since 1993, with home price increases and somewhat higher mortgage 
rates in 1994-97 being offset by gains in median family income.\56\
---------------------------------------------------------------------------

    \56\ Housing affordability varies markedly between regions, 
ranging in May 1998 from 164 in the Midwest to 100 in the West, with 
the South and Northeast falling in between.
---------------------------------------------------------------------------

    The high affordability of housing, low unemployment, and high 
consumer confidence meant that home purchase mortgages reached a 
record level in 1997. However, this record was surpassed in 1998, as 
a July 1998 survey by Fannie Mae found that ``every single 
previously cited barrier to homeownership--from not having enough 
money for a down payment, to not having sufficient information about 
how to buy a home, to the confidence one has in his job, to 
discrimination or social barriers--has collapsed to the lowest level 
recorded in the seven years Fannie Mae has sponsored its annual 
National Housing Survey.'' \57\ Specifically, the Mortgage Bankers 
Association estimates that home purchase mortgages rose to about 
$750 billion in 1998, well above the previous record of $576 billion 
established in 1997.
---------------------------------------------------------------------------

    \57\ Fannie Mae, http://www.fanniemae.com/news/housingsurvey/
1998, (July 16, 1998).
---------------------------------------------------------------------------

    First-time Homebuyers. First-time homebuyers have been the 
driving force in the recovery of the nation's housing market over 
the past several years. First-time homebuyers are typically people 
in the 25-34 year-old age group that purchase modestly priced 
houses. As the post-World War II baby boom generation ages, the 
percentage of Americans in this age group decreased from 28.3 
percent in 1980 to 25.4 percent in 1992.\58\ Even though this cohort 
is smaller, first-time homebuyers increased their share of home 
sales. First-time buyers accounted for about 47 percent of home 
sales in 1997. Participation rates for first-time homebuyers so far 
this decade are all in excess of 45 percent. This follows 
participation rates that averaged 40 percent in the 1980s, including 
a low of 36 percent in 1985. The highest first-

[[Page 12685]]

time homebuyer participation rate was achieved in 1977 when it was 
48 percent.\59\
---------------------------------------------------------------------------

    \58\ 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).
    \59\ Chicago Title and Trust Family of Insurers, Who's Buying 
Homes in America, (1998).
---------------------------------------------------------------------------

    The Chicago Title and Trust Company reports that the average 
first time-buyer in 1997 was 32 years old and spent 5 months looking 
at 14 homes before making a purchase decision. Most such buyers are 
married couples, but in 1997 21 percent were never-married males and 
13 percent were never-married females.
    First time buyers paid an average of 35 percent of after-tax 
income, or $1,020 per month, on their mortgage payments in 1997, and 
saved for 2.2 years to accumulate a down payment. The National 
Association of Realtors reports that first-time buyers took out an 
average mortgage of $102,000 in 1997, corresponding to an LTV of 90 
percent, compared with a mortgage of $132,000 and an average LTV of 
84 percent for repeat buyers.
    GSEs' Acquisitions as a Share of the Primary Single-Family 
Mortgage Market. The GSEs' single-family mortgage acquisitions have 
generally followed the volume of originations in the primary market 
for conventional mortgages, falling from 5.3 million mortgages in 
the record year of 1993 to 2.2 million mortgages in 1995, but 
rebounding to 2.9 million mortgages in 1996. In 1997, however, 
single-family originations were essentially unchanged, but the GSEs' 
acquisitions declined to 2.7 million mortgages.\60\ This pattern was 
reversed in 1998, when originations rose by 73 percent, but the 
GSEs' purchases jumped to 5.8 million mortgages.
---------------------------------------------------------------------------

    \60\ Single-family originations rose by 10 percent in dollar 
terms in 1997, but the Mortgage Bankers Association estimates that 
they fell by 0.6 percent in terms of the number of loans.
---------------------------------------------------------------------------

    Reflecting these divergent trends, the Office of Federal Housing 
Enterprise Oversight (OFHEO) estimates that the GSEs' share of the 
conventional single-family mortgage market, measured in dollars, 
declined from 42 percent in 1996 to 37 percent in 1997--well below 
the peak of 58 percent attained in 1993.\61\ OFHEO attributes the 
1997 downturn in the GSEs' role to increased holdings of mortgages 
in portfolio by depository institutions and to increased competition 
with Fannie Mae and Freddie Mac by private label issuers. However, 
OFHEO estimates that the GSEs' share of the market rebounded sharply 
in 1998, to 48 percent.
---------------------------------------------------------------------------

    \61\ Office of Federal Housing Enterprise Oversight, 1998 Report 
to Congress, Figure 9, p. 32. The GSEs' market shares in terms of 
units financed in 1997 are shown below in Table A.7.
---------------------------------------------------------------------------

    Mortgage Market Prospects. The Mortgage Bankers Association 
(MBA) reports that 1998 was a record-breaking year, with $1.507 
trillion in mortgage originations. Refinancing of existing mortgages 
was also up in 1998, accounting for 50 percent share of the total 
mortgage originations. Meanwhile, ARMs accounted for a smaller 
share, 12 percent, of originations than usual. The mortgage market 
should remain strong in 1999, but should settle down a bit in the 
year 2000. The MBA predicts that originations will amount to $1.29 
trillion, with refinancings representing 35 percent of originations, 
during 1999. The MBA expects originations and refinancing activity 
to return to a more normal pace in 2000. ARMs are expected to 
account for a larger share, 23 percent in 1999 and 32 percent in 
2000, of total mortgage originations.\62\
---------------------------------------------------------------------------

    \62\ Mortgage market projections obtained from the MBA's MBA 
Mortgage Finance Forecast, October 1999.
---------------------------------------------------------------------------

b. Affordable Lending in the Mortgage Market

    In the past few years, conventional lenders, private mortgage 
insurers and the GSEs have begun implementing changes to extend 
homeownership opportunities to lower-income and historically 
underserved households. The industry has started offering more 
customized products, more flexible underwriting, and expanded 
outreach so that the benefits of the mortgage market can be extended 
to those who have not been adequately served through traditional 
products, underwriting, and marketing. This section summarizes 
recent initiatives undertaken by the industry to expand affordable 
housing. The section also discusses the significant role FHA plays 
in making affordable housing available to historically underserved 
groups.
    Down Payments. GE Capital's 1989 Community Homebuyer Program 
first allowed homebuyers who completed a program of homeownership 
counseling to have higher than normal payment-to-income qualifying 
ratios, while providing less than the full 5-percent down payment 
from their own funds. Thus the program allowed borrowers to qualify 
for larger loans than would have been permitted under standard 
underwriting rules. Fannie Mae made this Community Homebuyer Program 
a part of its own offerings in 1990. Affordable Gold is a similar 
program introduced by Freddie Mac in 1992. Many of these programs 
allowed 2 percentage points of the 5-percent down payment to come 
from gifts from relatives or grants and unsecured loans from local 
governments or nonprofit organizations.
    In 1994, the industry (including lenders, private mortgage 
insurers and the GSEs) began offering mortgage products that 
required down payments of only 3 percent, plus points and closing 
costs. Other industry efforts to reduce borrowers' up front costs 
have included zero-point-interest-rate mortgages and monthly 
insurance premiums with no up front component. These new plans 
eliminated large up front points and premiums normally required at 
closing.
    During 1998, Fannie Mae introduced its ``Flexible 97'' and 
Freddie Mac introduced its ``Alt 97'' low down payment lending 
programs. Under these programs borrowers are required to put down 
only 3 percent of the purchase price. The down payment, as well as 
closing costs, can be obtained from a variety of sources, including 
gifts, grants or loans from a family member, the government, a non-
profit agency and loans secured by life insurance policies, 
retirement accounts or other assets. While these programs started 
out slowly, by November 1998 both GSEs' programs reached volumes of 
$200 million per month. However, the GSEs are expected to purchase 
less than $4 billion in their 97 percent LTV programs by the end of 
1998, well below the $75 billion of 97 percent LTV loans that FHA is 
expected to insure in 1998.\63\
---------------------------------------------------------------------------

    \63\ ``After Slow Start, Fannie and Freddie Report Growing 
Interest in 97 Percent LTV Products,'' Inside Mortgage Finance. 
(November 20, 1998), pp. 10-11.
---------------------------------------------------------------------------

    In early 1999, Fannie Mae announced that it would introduce 
several changes to their mortgage insurance requirements. The 
planned result is to provide options for low downpayment borrowers 
to reduce their mortgage insurance costs. Franklin D. Raines, Fannie 
Mae chairman and chief executive officer stated, ``Now, thanks to 
our underwriting technology, our success in reducing credit losses, 
and innovative new arrangements with mortgage insurance companies, 
we can increase mortgage insurance options and pass the savings 
directly on to consumers.'' \64\
---------------------------------------------------------------------------

    \64\ Speech before the annual convention of the National 
Association of Home Builders in Dallas TX, (January 1999).
---------------------------------------------------------------------------

    Partnerships. In addition to developing new affordable products, 
lenders and the GSEs have been entering into partnerships with local 
governments and nonprofit organizations to increase mortgage access 
to underserved borrowers. Fannie Mae's partnership offices in 33 
central cities, serving to coordinate Fannie Mae's programs with 
local lenders and affordable housing groups, are an example of this 
initiative. Another example is the partnership Fannie Mae and the 
National Association for the Advancement of Colored People (NAACP) 
announced in January 1999.\65\ Under this partnership, Fannie Mae 
will provide funding for technical assistance to expand the NAACP's 
capacity to provide homeownership information and counseling. It 
will also invest in NAACP-affiliated affordable housing development 
efforts and explore structures to assist the organization in 
leveraging its assets to secure downpayment funds for eligible 
borrowers. Furthermore, Fannie Mae will provide up to $110 million 
in special financing products, including a new $50 million 
underwriting experiment specifically tailored to NAACP clientele.
---------------------------------------------------------------------------

    \65\ Fannie Mae News Release (January 1999).
---------------------------------------------------------------------------

    Freddie Mac does not have a partnership office structure similar 
to Fannie Mae's, but it has undertaken a number of initiatives in 
specific metropolitan areas. Freddie Mac also announced on January 
15, 1999 that it entered into a broad initiative with the NAACP to 
increase minority homeownership. Through this alliance, Freddie Mac 
and the NAACP seek to expand community-based outreach, credit 
counseling and marketing efforts, and the availability of low-
downpayment mortgage products with flexible underwriting guidelines. 
As part of the initiative, Freddie Mac has committed to purchase 
$500 million in mortgage loans.\66\
---------------------------------------------------------------------------

    \66\ Freddie Mac News Release (January 15, 1999).
---------------------------------------------------------------------------

    The above are only examples of the partnership efforts 
undertaken by the GSEs. There are more partnership programs than can 
be adequately described here. For full descriptions of Fannie Mae's 
and Freddie

[[Page 12686]]

Mac's partnership programs, see their respective Annual Reports.
    Underwriting Flexibility. Lenders, mortgage insurers, and the 
GSEs have also been modifying their underwriting standards to 
attempt to address the needs of families who find qualifying under 
traditional guidelines difficult. The goal of these underwriting 
changes is not to loosen underwriting standards, but rather to 
identify creditworthiness by alternative means that more 
appropriately measure the circumstances of lower-income households. 
The changes to underwriting standards include, for example:
    (i) Using a stable income standard rather than a stable job 
standard. This particularly benefits low-skilled applicants who have 
successfully remained employed, even with frequent job changes.
    (ii) 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.
    (iii) Allowing pooling of funds for qualification purposes. This 
change benefits applicants with extended family members.
    (iv) Making exceptions to the ``declining market'' rule and 
clarifying the treatment of mixed-use properties.\67\ These changes 
benefit applicants from inner-city underserved neighborhoods.
---------------------------------------------------------------------------

    \67\ Standard underwriting procedures characterize a property in 
a declining neighborhood as one at high risk of losing value. 
Implicitly, these underwriting standards presume that the real 
estate market is inefficient in economic terms, that is, prices do 
not reflect all available information.
---------------------------------------------------------------------------

    These underwriting changes have been accompanied by 
homeownership counseling to ensure homeowners are ready for the 
responsibilities of homeownership. In addition, the industry has 
engaged in intensive loss mitigation to control risks.
    Increase in Affordable Lending, 1993-1997.\68\ Home Mortgage 
Disclosure Act (HMDA) data suggest that the new industry initiatives 
may be increasing the flow of credit to underserved borrowers. 
Between 1993 and 1997, conventional loans to low-income and minority 
families increased at much faster rates than loans to higher income 
and non-minority families. As shown below, over this period home 
purchase originations to African Americans and Hispanics grew by 
almost 60 percent, and purchase loans to low-income borrowers (those 
with incomes less than 80 percent of area median income) increased 
by 45 percent.
---------------------------------------------------------------------------

    \68\ For an update of this analysis to include 1998, see Randall 
M. Scheessele, 1998 HMDA Highlights, Housing Finance Working Paper 
HF-009, Office of Policy Development and Research, U.S. Department 
of Housing and Urban Development, (October 1999).

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

However, as also shown, in the latter part of this period 
conventional lending for some groups slowed significantly. Between 
1995 and 1997, the slowing of the growth of home purchase 
originations was much greater for low-income borrowers than for 
higher-income borrowers. Moreover , even though remaining at near-
peak levels in 1997, conventional home purchase originations to 
African Americans and Hispanics actually decreased by two-tenths of 
a percent over the past three years. It should be noted, however, 
that total loans (conventional plus government) originated to 
African-American and Hispanic borrowers increased between 1995 and 
1997, but this was mainly the result of a 40.0 percent increase in 
FHA-insured loans originated for African-American and Hispanic 
borrowers.
    Affordable Lending Shares by Major Market Sector. The focus of 
the different sectors of the mortgage market on affordable lending 
can be seen by examining Tables A.1a, A.1b, and A.2. Tables A.1a and 
A.1b present affordable lending percentages for FHA, the GSEs, 
depositories (banks and thrift institutions), the conventional 
conforming sector, and the overall market.\69\ The discussion below 
will center on Table A.1a, which provides information on home 
purchase loans and thus, homeownership opportunities. Table A.1b, 
which provides information on total (both home purchase and 
refinance) loans, is included to give a complete picture of mortgage 
activity. Both 1997 and 1998 data are included in these tables; the 
year 1997 represents a more typical year of mortgage activity than 
1998, which was characterized by heavy refinance activity.
---------------------------------------------------------------------------

    \69\ The ``overall'' market is defined as all loans (including 
both government and conventional) below the 1997 conforming loan 
limit of $214,600 and the 1998 conforming loan limit of $227,150.
---------------------------------------------------------------------------

    The interpretation of the ``distribution of business'' 
percentages, reported in Table A.1a for several borrower and 
neighborhood characteristics, can be illustrated using the FHA 
percentage for low-income borrowers: during 1997, 47.5 percent of 
all FHA-insured home purchase loans in metropolitan areas were 
originated for borrowers with an income less than 80 percent of the 
local area median income. Table A.2, on the other hand, presents 
``market share'' percentages that measure the portion of all home 
purchase loans for a specific affordable lending category (such as 
low-income borrowers) accounted for by a particular sector of the 
mortgage market (FHA or the GSEs). In this case, the FHA market 
share of 33 percent for low-income borrowers is interpreted as 
follows: of all home purchase loans originated in metropolitan areas 
during 1997, 33 percent were FHA-insured loans. Thus, this ``market 
share'' percentage measures the importance of FHA to the market's 
overall funding of loans for low-income borrowers.

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    Four main conclusions may be drawn from the data presented in 
Tables A.1a and A.2. First, FHA places much more emphasis on 
affordable lending than the other market sectors. Low-income 
borrowers accounted for 47.5 percent of FHA-insured loans during 
1997, compared with 21.6 percent of the home loans purchased by the 
GSEs, 29.4 percent of home loans retained by depositories, and 27.3 
percent of conventional conforming loans.\70\ Likewise, 41.3 percent 
of FHA-insured loans were originated in underserved census tracts, 
while only 22.3 percent of the GSE-purchased loans and 25.2 percent 
of conventional conforming loans were originated in these 
tracts.\71\ As shown in Table A.2, while FHA insured only 23 percent 
of all home purchase mortgages originated in metropolitan areas 
during 1997, it insured 33 percent of all mortgages originated in 
underserved areas.\72\
---------------------------------------------------------------------------

    \70\ The percentages reported in Table A.1a for the year 1998 
are similar; in that year, low-income borrowers accounted for 49.1 
percent of FHA-insured loans, 24.3 percent of GSE purchases, and 
27.8 percent of mortgages originated in the conventional conforming 
market.
    \71\ FHA, which focuses on first-time homebuyers and low down 
payment loans, experiences higher mortgage defaults than 
conventional lenders and the GSEs. Still, the FHA system is 
actuarially sound because it charges an insurance premium that 
covers the higher default costs.
    \72\ FHA's role in the market is particularly important for 
African-American and Hispanic borrowers. As shown in Table A.2, FHA 
insured 44 percent of all 1997 home loan originations for these 
borrowers.
---------------------------------------------------------------------------

    Second, the affordable lending shares for the conventional 
conforming sector are particularly low for minority borrowers and 
their neighborhoods. For example, African-American and Hispanic 
borrowers accounted for only 11.0 percent of all conventional 
conforming loans originated during 1997, compared with 32.2 percent 
of FHA-insured loans and 16.5 percent of all loans originated in the 
market. Within the conventional conforming sector, about 10 percent 
of both GSE-purchased loans and loans retained by depositories were 
originated for African Americans and Hispanics. Only 8.3 percent of 
Freddie Mac's purchases were loans for these borrowers, compared 
with 10.9 percent of Fannie Mae's purchases. As shown in Table A.1a, 
Fannie Mae purchased mortgages for minority borrowers and their 
neighborhoods at higher rates than these loans were originated by 
primary lenders in the conventional conforming market. During 1997, 
17.8 percent of Fannie Mae's purchases were mortgages for minority 
borrowers, compared with 16.5 percent of conventional conforming 
loans. During 1998, 14.5 percent of Fannie Mae's purchases financed 
homes in high-minority census tracts, compared with 14.1 percent of 
conventional conforming loans. However, the minority lending 
performance of conventional lenders has been subject to much 
criticism in recent studies. These studies contend that primary 
lenders in the conventional market are not doing their fair share of 
minority lending which forces minorities, particularly African-
American and Hispanic borrowers, to the more costly FHA and subprime 
markets.\73\
---------------------------------------------------------------------------

    \73\ 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).
---------------------------------------------------------------------------

    Third, the GSEs, but particularly Freddie Mac, tend to lag the 
conventional conforming market in funding affordable loans for low-
income families and their neighborhoods. During 1997 and 1998, low-
income census tracts accounted for 8.0 percent of Freddie Mac's 
purchases, 9.7 percent of Fannie Mae's purchases, 12.1 percent of 
loans retained by depositories, and 10.8 percent of all home loans 
originated by conventional conforming lenders. This pattern of 
Freddie Mac lagging all market participants holds up for all of the 
borrower and neighborhood categories examined in Table A.1a. One 
encouraging trend is the significant increase in both GSEs' 
purchases of low-income-borrower loans between 1997 and 1998; on the 
other hand, the GSE percentages for the other borrower and 
neighborhood categories examined in Table A.1a declined between 1997 
and 1998. A more complete analysis of the GSEs' purchases of 
mortgages qualifying for the housing goals will be provided below in 
Section E.
    Finally, within the conventional conforming market, depository 
institutions stand out as important providers of affordable lending 
for lower-income families and their neighborhoods (see Table 
A.1a).\74\ Depository lenders have extensive knowledge of their 
communities and direct interactions with their borrowers, which may 
enable them to introduce flexibility into their underwriting 
standards without unduly increasing their credit risk. Another 
important factor influencing the types of loans held by depository 
lenders is the Community Reinvestment Act, which is discussed next.
---------------------------------------------------------------------------

    \74\ However, as shown in Table A.1a, depository institutions 
resemble other conventional lenders in their relatively low level of 
originating loans for African-American, Hispanic and minority 
borrowers.
---------------------------------------------------------------------------

    Seasoned CRA Loans. The Community Reinvestment Act (CRA) 
requires depository institutions to help meet the credit needs of 
their communities. CRA provides an incentive for lenders to initiate 
affordable lending programs with underwriting flexibility.\75\ CRA 
loans are typically made to low- and moderate-income borrowers 
earning less than 80 percent of median income for their area, and in 
moderate-income neighborhoods. They are usually smaller than typical 
conventional mortgages and also are likely to have a high LTV, high 
debt-to-income ratios, no payment reserves, and may not be carrying 
private mortgage insurance (PMI). Generally, at the time CRA loans 
are originated, many do not meet the underwriting guidelines 
required in order for them to be purchased by one of the GSEs. 
Therefore, many of the CRA loans are held in portfolio by lenders, 
rather than sold to Fannie Mae or Freddie Mac. On average, CRA loans 
in a pool have three to four years seasoning.\76\
---------------------------------------------------------------------------

    \75\ For an analysis of the impact of CRA agreements signed by 
lending institutions, see Alex Schwartz, ``From Confrontation to 
Collaboration? Banks, Community Groups, and the Implementation of 
Community Reinvestment Agreements'', Housing Policy Debate, 9(3), 
(1998), pp. 631-662.
    \76\ ``With Securities Market Back on Track, Analysts Expect 
Surge in CRA Loan Securitization in 1999,'' Inside MBS & ABS. 
(February 19, 1999), pp. 11-12.
---------------------------------------------------------------------------

    However, because of the size, LTV and PMI characteristics of CRA 
loans, they have slower prepayment rates than traditional mortgages, 
making them attractive for securitization. CRA loan delinquencies 
also have very high cure rates.\77\ For banks, selling CRA pools 
will free up capital to make new CRA loans. As a result, the CRA 
market segment may provide an opportunity for Fannie Mae and Freddie 
Mac to expand their affordable lending programs. In mid-1997, Fannie 
Mae launched its Community Reinvestment Act Portfolio Initiative. 
Under this pilot program Fannie Mae purchases seasoned CRA loans in 
bulk transactions taking into account track record as opposed to 
relying just on underwriting guidelines. By the end of 1997, Fannie 
Mae had financed $1 billion in CRA loans through this pilot.\78\ 
With billions of dollars worth of CRA loans in bank portfolios the 
market for securitization should improve. Section D, below, presents 
data showing that Fannie Mae's purchases of CRA-type seasoned 
mortgages have increased recently. Fannie Mae also started another 
pilot program in 1998 where they purchase CRA loans on a flow basis, 
as they are originated. Results from this four-year $2 billion 
nationwide pilot should begin to be reflected in the 1999 production 
data.
---------------------------------------------------------------------------

    \77\ Inside MBS & ABS. (February 19, 1999), p. 12.
    \78\ Fannie Mae. 1997 Annual Housing Activities Report, (1998), 
p. 28.
---------------------------------------------------------------------------

c. Potential Homebuyers

    While the growth in affordable lending and homeownership has 
been strong in recent years, attaining this Nation's housing goals 
will not be possible without tapping into the vast pool of potential 
homebuyers. The National Homeownership Strategy has set a goal of 
achieving a homeownership rate of 67.5 percent by the end of the 
year 2000. Due to the aging of the baby boomers, this rate reached 
an annual record of 66.3 percent in 1998, and should rise to 67 
percent by 2000. Thus the Strategy's target will require an increase 
in homeownership above and beyond that resulting from current 
demographic trends.
    The Urban Institute estimated in 1995 that there was a large 
group of potential homebuyers among the renter population who were 
creditworthy enough to qualify for homeownership.\79\ Of 20.3 
million renter households having low-or moderate-incomes, roughly 16 
percent were better qualified for homeownership than half of the 
renter households who actually did become homeowners over the sample 
period. When one also considered their likelihood of

[[Page 12691]]

defaulting relative to the average expected for those who actually 
moved into homeownership, 10.6 percent, or 2.15 million, low- and 
moderate-income renters were better qualified for homeownership, 
assuming the purchase of a home priced at or below median area home 
price. These results indicate the existence of a significant lower-
income population of low-risk potential homebuyer households that 
might become homeowners with continuing outreach efforts by the 
mortgage industry.
---------------------------------------------------------------------------

    \79\ George Galster, Laudan Y. Aron, Peter Tatain and Keith 
Watson. Estimating the Size, Characteristics, and Risk Profile of 
Potential Homebuyers. Washington: The Urban Institute, (1995). 
Report Prepared for the Department of Housing and Urban Development.
---------------------------------------------------------------------------

    Other surveys conducted by Fannie Mae indicate that renters 
desire to become homeowners, with 60 percent of all renters 
indicating in the July 1998 National Housing Survey that buying a 
home ranks from being a ``very important priority'' to their 
``number-one priority,'' the highest level found in any of the seven 
National Housing Surveys dating back to 1992. Immigration is 
expected to be a major source of future homebuyers--Fannie Mae's 
1995 National Housing Survey reported that immigrant renter 
household were 3 times as likely as renter households in general to 
list home purchase as their ``number-one priority.''
    The achievement of the National Homeownership Strategy goal for 
homeownership in 2000 also depends on whether or not recent gains in 
the homeowning share of specific groups are maintained. The Joint 
Center for Housing Studies has pointed out that minorities account 
for only 17 percent of all homeowners, but were responsible for 42 
percent of the 4 million increase in the number of homeowners 
between 1994 and 1997. Minority demand for homeownership continues 
to be high, as reported by the Fannie Mae Foundation's April 1998 
Survey of African Americans and Hispanics. For example, 38 percent 
of African Americans surveyed said it is fairly to very likely that 
they will buy a home in the next 3 years, compared with 25 percent 
in 1997.\80\ The survey also reports that 67 percent of African 
Americans and 65 percent of Hispanics cite homeownership as being a 
``very important priority'' or ``number-one priority.'' \81\
---------------------------------------------------------------------------

    \80\ Fannie Mae Foundation. African American and Hispanic 
Attitudes on Homeownership: A Guide for Mortgage Industry Leaders, 
(1998), p. 3.
    \81\ Fannie Mae Foundation. (1998), p. 14.
---------------------------------------------------------------------------

    The Joint Center for Housing Studies has stated that if 
favorable economic and housing market trends continue, and if 
additional efforts to target mortgage lending to low-income and 
minority households are made, the homeownership rate could reach 70 
percent by 2010.

d. Automated Mortgage Scoring

    This, and the following two sections, discuss special topics 
that have, in recent years, impacted the primary and secondary 
mortgage markets. They are automated mortgage scoring, subprime 
loans and manufactured housing.
    Automated mortgage scoring was developed as a high-tech tool 
with the purpose of identifying credit risks in a more efficient 
manner. As time and cost are reduced by the automated system, more 
time can be devoted by underwriters to qualifying marginal loan 
applicants that are referred by the automated system for more 
intensive review. Fannie Mae and Freddie Mac are in the forefront of 
new developments in automated mortgage scoring technology. Both 
enterprises released automated underwriting systems in 1995-Freddie 
Mac's Loan Prospector and Fannie Mae's Desktop Underwriter. Each 
system uses numerical credit scores, such as those developed by 
Fair, Isaac, and Company, and additional data submitted by the 
borrower, such as loan-to-value ratios and available assets, to 
calculate a mortgage score that evaluates the likelihood of a 
borrower defaulting on the loan. The mortgage score is in essence a 
recommendation to the lender to accept the application, or to refer 
it for further review through manual underwriting. Accepted loans 
benefit from reduced document requirements and expedited processing.
    Along with the promise of benefits, however, automated mortgage 
scoring has raised concerns. These concerns are related to the 
possibility of disparate impact and the proprietary nature of the 
mortgage score inputs. The first concern is that low-income and 
minority homebuyers will not score well enough to be accepted by the 
automated underwriting system resulting in fewer getting loans. The 
second concern relates to the ``black box'' nature of the scoring 
algorithm. The scoring algorithm is proprietary and therefore it is 
difficult, if not impossible, for applicants to know the reasons for 
their scores.
    Federal Reserve Study. Four economists at the Board of Governors 
of the Federal Reserve System have recently released a conceptual 
and empirical study on the use of credit scoring systems in mortgage 
lending.\82\ Their broad assessment of the models is that

    \82\ Robert B. Avery, Raphael W. Bostic, Paul S. Calem, and 
Glenn B. Canner, Credit Scoring: Issues and Evidence from Credit 
Bureau Files, mimeo., (1998).
---------------------------------------------------------------------------

[C]redit scoring is a technological innovation which has increased 
the speed and consistency of risk assessment while reducing costs. 
Research has uniformly found that credit history scores are powerful 
predictors of future loan performance. All of these features suggest 
that credit scoring is likely to benefit both lenders and 
consumers.'' \83\

    \83\ Avery et al. (1998), p. 24.
---------------------------------------------------------------------------

    The authors evaluate the current state-of-the-art of development 
of credit scoring models, focusing particularly on the 
comprehensiveness of statistical information used to develop the 
scoring equations. They present a conceptual framework in which 
statistical predictors of default include regional and local market 
conditions, individual credit history, and applicants' 
characteristics other than credit history. The authors observe that 
the developers of credit scoring models have tended to disregard 
regional and local market conditions in model construction, and such 
neglect may tend to reduce the predictive accuracy of scoring 
equations. To determine the extent of the problem, they analyzed 
Equifax credit scores together with mortgage payment history data 
for households living in each of 994 randomly selected counties from 
across the country. The authors use these data to assess the 
variability of credit scores relative to county demographic and 
economic characteristics.
    The authors find a variety of pieces of evidence which confirm 
their suspicions: Credit scores tended to be relatively lower in 
areas with relatively high county unemployment rates, areas that 
have experienced recent rises in unemployment rates, areas with high 
minority population, areas with lower median educational attainment, 
areas with high percentages of individuals living in poverty, areas 
with low median incomes and low house values, and areas with 
relatively high proportions of younger populations and lower 
proportions of older residents.
    This analysis suggests the need for a two-step process of 
improvement of the equations and their application, in which (a) new 
statistical analyses would be performed to incorporate the omitted 
environmental variables, and (b) additional variables bearing on 
individuals' prospective and prior circumstances will be taken into 
account in determining their credit scores.
    These authors also discuss the relationship between credit 
scoring and discrimination. They find a significant statistical 
relationship between credit history scores and minority composition 
of an area, after controlling for other locational characteristics. 
From this, they conclude that concerns about potential disparate 
impact merit future study. However, a disparate impact study must 
include a business justification analysis to demonstrate the ability 
of the score card to predict defaults and an analysis of whether any 
alternative, but equally-predictive, score card has a less 
disproportionate effect.
    Urban Institute Study. The Urban Institute recently submitted a 
report to HUD on a four-city reconnaissance study of issues related 
to the single-family underwriting guidelines and practices of Fannie 
Mae and Freddie Mac.\84\ The study included interviews with 
informants knowledgeable about mortgage markets and GSE business 
practices on the national level and in the four cities.
---------------------------------------------------------------------------

    \84\ 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). This study involves an analysis of the 
GSEs' underwriting guidelines in general. This section reviews only 
the aspects of the study related to mortgage scoring. A broader 
review of this paper is provided below in section E.4.
---------------------------------------------------------------------------

    The study observes, as did the Fed study summarized above, that 
minorities are more likely than whites to fail underwriting 
guidelines. Therefore, as a general matter the GSEs' underwriting 
guidelines--as well as the underwriting guidelines of others in the 
industry--do have disproportionate adverse effects on minority loan 
applicants.\85\
---------------------------------------------------------------------------

    \85\ Temkin, et al. (1999), p.2.
---------------------------------------------------------------------------

    Based on the field reconnaissance in four metropolitan housing 
markets, the study makes several observations about the operation of 
credit scoring systems in practice, as follows: \86\
---------------------------------------------------------------------------

    \86\ Temkin, et al. (1999), p. 5; pp. 26-27.
---------------------------------------------------------------------------

    (i) Credit scores are used in mortgage underwriting to separate 
loans that must be

[[Page 12692]]

referred to loan underwriters from loans that may be forwarded 
directly to loan officers; for example, a 620 score was mentioned by 
some respondents as the line below which the loan officer must refer 
the loan for manual underwriting. It is very difficult for 
applicants with low credit scores to be approved for a mortgage, 
according to the lenders interviewed by the Urban Institute.
    (ii) Some respondents believe the GSEs are applying cutoffs 
inflexibly, while others believe that lenders are not taking 
advantage of flexibility allowed by the GSEs.
    (iii) Some respondents believe that credit scores may not be 
accurate predictors of loan performance, despite the claims of users 
of these scores. Respondents who voiced this opinion tended to base 
these observations on their personal knowledge of low-income 
borrowers who are able to keep current on payments, rather than on 
an understanding of statistical validation studies of the models.
    (iv) Respondents indicate that the ``black box'' nature of the 
credit scoring process creates uncertainty among loan applicants and 
enhances the intimidating nature of the process for them.
    Based on these findings, the authors conclude that ``the use of 
automated underwriting systems and credit scores may place lower-
income borrowers at a disadvantage when applying for a loan, even 
though they are acceptable credit risks.''
    The report includes several recommendations for ongoing HUD 
monitoring of the GSEs' underwriting including their use of credit 
scoring models. One suggestion is to develop a data base on the 
GSEs' lending activities relevant for analysis of fair lending 
issues. The data would include credit scores to reveal the GSEs' 
patterns of loan purchase by credit score. A second suggestion is to 
conduct analyses of the effects of credit scoring systems using a 
set of ``fictitious borrower profiles'' that would reveal how the 
systems reflect borrower differences in income, work history, credit 
history, and other relevant factors. HUD has begun following up on 
the Urban Institute's recommendations. For instance, in February 
1999, HUD requested the information and data needed to analyze the 
GSEs' automated underwriting systems.
    Concluding Observation. It is important to note that both of the 
studies reviewed above comment on the problem of correlation of 
valid predictors of default (income, etc.) with protected factors 
(race, etc.). Both studies suggest that, ultimately, the question 
whether mortgage credit scoring models raise any problems of legal 
discrimination based on disparate effects would hinge on a business 
necessity analysis and analysis of whether any alternative 
underwriting procedures with less adverse disproportionate effect 
exist.

e. Subprime Loans

    Another major development in housing finance has been the recent 
growth in subprime loans. In the past borrowers traditionally 
obtained an ``A'' quality (or ``investment grade'') mortgage or no 
mortgage. However, an increasing share of recent borrowers have 
obtained ``subprime'' mortgages, with their quality denoted as ``A-
minus,'' ``B,'' ``C,'' or even ``D.'' The subprime borrower 
typically is someone who has experienced credit problems in the past 
or has a high debt-to-income ratio.\87\ Through the first nine 
months of 1998, ``A-minus'' loans accounted for 63 percent of the 
subprime market, with ``B'' loans representing 24 percent and ``C'' 
and ``D'' loans making up the remaining 13 percent.\88\
---------------------------------------------------------------------------

    \87\ Standard & Poor's B and C mortgage guidelines can be used 
to illustrate that underwriting criteria in the subprime market 
becomes more flexible as the grade of borrower moves from the most 
creditworthy A-borrowers to the riskier D borrowers. For example, 
the A-grade borrower is allowed to be delinquent 30 days on his 
mortgage twice in the last year whereas the D grade borrower is 
allowed to be delinquent 30 days on his mortgage credit five times 
in the last year. Moreover, the A-borrower is permitted to have a 45 
percent debt-to-income ratio compared to the D grade borrower's 60 
percent.
    \88\ ``Subprime Product Mix, Strategies Changed During a 
Turbulent 1998,'' Inside B&C Lending. (December 21, 1998), p. 2.
---------------------------------------------------------------------------

    Because of the perceived higher risk of default, subprime loans 
typically carry mortgage rates that in some cases are substantially 
higher than the rates on prime mortgages. While in many cases these 
perceptions about risk are accurate, some housing advocates have 
expressed concern that there are a number of cases in which the 
perceptions are actually not accurate. The Community Reinvestment 
Association of North Carolina (CRA*NC), conducted a study based on 
HMDA data, records of deeds, and personal contacts with effected 
borrowers in Durham County, NC. They found that subprime lenders 
make proportionally more loans to minority borrowers and in minority 
neighborhoods than to whites and white neighborhoods at the same 
income level. African-American borrowers represent 20 percent of 
subprime mortgages in Durham County, but only 10 percent of prime 
market.\89\ As a result, these borrowers can end up paying very high 
mortgage rates that more than compensate for their additional risks 
to lenders. High subprime mortgage rates make homeownership more 
expensive or force subprime borrowers to buy less desirable homes 
than they would be able to purchase if they paid lower prime rates 
on their mortgages.
---------------------------------------------------------------------------

    \89\ ``Renewed Attack on `Predatory' Subprime Lenders.'' Fair 
Lending/CRA Compass, (June 1999) and http://cra-
cn.home.mindspring.com.
---------------------------------------------------------------------------

    The HMDA database does not provide information on interest 
rates, points, or other loan terms that would enable researchers to 
separate more expensive subprime loans from other loans. However, 
the Department has identified 200 lenders that specialize in such 
loans, providing some information on the growth of this market.\90\ 
This data shows that mortgages originated by subprime lenders, and 
reported to HMDA, has increased from 104,000 subprime loans in 1993 
to 210,000 in 1995 and 997,000 in 1998. Most of the subprime loans 
reported to HMDA are refinance loans; for example, refinance loans 
accounted for 80 percent of the subprime loans reported by the 
specialized subprime lenders in 1997.
---------------------------------------------------------------------------

    \90\ See Randall M. Scheessele. 1998 HMDA Highlights, Housing 
Finance Working Paper HF-009, Office of Policy Development and 
Research, U.S. Department of Housing and Urban Development, (October 
1999). Nonspecialized lenders such as banks and thrifts also make 
subprime loans, but no data is available to estimate the number of 
these loans.
---------------------------------------------------------------------------

    An important question is whether borrowers in the subprime 
market are sufficiently creditworthy to qualify for more traditional 
loans. Freddie Mac has said that one of the promises of automated 
underwriting is that it might be better able to identify borrowers 
who are unnecessarily assigned to the high-cost subprime market. It 
has estimated that 10-30 percent of borrowers who obtain mortgages 
in the subprime market could qualify for a conventional prime loan 
through Loan Prospector, its automated underwriting system.\91\
---------------------------------------------------------------------------

    \91\ Freddie Mac, We Open Doors for America's Families, Freddie 
Mac's Annual Housing Activities Report for 1997, (March 16, 1998), 
p. 23.
---------------------------------------------------------------------------

    Most of the subprime loans that were purchased by the GSEs in 
past years were purchased through structured transactions. Under 
this form of transaction, whole groups of loans are purchased, and 
not all loans necessarily meet the GSEs' traditional underwriting 
guidelines. The GSEs typically guarantee the so-called ``A'' 
tranche, which is supported by a ``B'' tranche that covers default 
costs.
    An expanded GSE presence in the subprime market could be of 
significant benefit to lower-income families, minorities, and 
families living in underserved areas. HUD's research shows that in 
1998: African-Americans comprised 5.0 percent of market borrowers, 
but 19.4 percent of subprime borrowers; Hispanics made up 5.2 
percent of market borrowers, but 7.8 percent of subprime borrowers; 
very low-income borrowers accounted for 12.1 percent of market 
borrowers, but 23.3 percent of subprime borrowers; and borrowers in 
underserved areas amounted to 24.8 percent of market borrowers, but 
44.7 percent of subprime borrowers.\92\
---------------------------------------------------------------------------

    \92\ The statistics cited for the ``market'' refer to all 
conforming conventional mortgages (both home purchase and 
refinance). The data for the subprime market are for 200 lenders 
that specialize in such loans; see Scheessele, op. cit.
---------------------------------------------------------------------------

    Most subprime borrowers are classified as ``A-minus,'' which 
means that they are slightly below investment grade due to the 
borrower's past credit problems. Freddie Mac has developed 
initiatives to allow its Seller/Servicers using Loan Prospector to 
sell them ``A-minus'' loans. In April 1999 Freddie Mac began a 
purchasing ``A-minus'' loans with prepayment penalties on a flow 
basis and has provided guarantees for the senior portions of 
mortgage securitizations backed in part by B and C loans.\93\ 
Freddie Mac hopes that the information gleaned from these 
initiatives will enable it to study the performance of subprime 
loans and enhance its ability to provide financing in this market. 
One concern Freddie Mac has is that as the GSEs get deeply involved 
in the subprime market,

[[Page 12693]]

and if they take on a first-loss position, servicing quality might 
erode.\94\
---------------------------------------------------------------------------

    \93\ ``Freddie Mac Begins Buying A-Loans With Prepay 
Penalties,'' Inside Mortgage Finance. (May 21, 1999), p. 9; and 
``Democratic Senator Suggests Fannie and Freddie Could Improve 
Subprime Mortgage Market,'' Inside Mortgage Finance. (June 25, 
1999), pp. 5-6.
    \94\ ``Subprime Mortgage Market Nervously Makes Room for 
Government-Sponsored Enterprises,'' Inside Mortgage Finance. 
(February 19, 1999), p. 5-6.
---------------------------------------------------------------------------

    Fannie Mae has not been as involved in the subprime market as 
Freddie Mac to date, but it has expressed its intent to fully enter 
the ``A-minus'' market over the next several years.\95\ During 1998, 
Fannie Mae approximates that it purchased $10 billion in ``Alt-A'' 
loans, about a quarter of that market. In September 1999, Fannie Mae 
announced the availability of the ``Timely Payment Rewards'' 
mortgage. Under this product, borrowers who qualify but have 
slightly impaired credit are eligible for a mortgage with a higher 
rate than the standard conventional mortgage. After 24 months of 
paying the mortgage on time, the borrower is guaranteed a one 
percent interest rate reduction.\96\ Fannie Mae sees its Desktop 
Underwriter automated underwriting system and other technology 
initiatives as the keys which will enable it to manage credit risk 
of such loans in a manner that allows a greatly expanded presence in 
the subprime market.
---------------------------------------------------------------------------

    \95\ Fannie Mae's plans regarding its entry into the A-minus and 
``Alternative-A'' (Alt-A) markets are discussed in ``Fannie Mae to 
Fully Enter Alt-A Market in Two Years,'' Origination News, November 
1998, p. 33. The Alt-A market generally involves conforming size 
mortgages made to A quality borrowers that fall outside Fannie Mae's 
or Freddie Mac's purchase requirements due to lack of documentation, 
the property type, loan-to-value ratio, or a combination of the 
three.
    \96\ Fannie Mae press release, (September 30, 1999).
---------------------------------------------------------------------------

    Increased involvement by the GSEs in the subprime market will 
result in more standardized underwriting guidelines. 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.

f. Loans on Manufactured Housing

    Manufactured housing provides low-cost, basic-quality housing 
for millions of American households, especially younger, lower-
income families in the South, West, and rural areas of the nation. 
Many households living in manufactured housing because they simply 
cannot afford site-built homes, for which the construction cost per 
square foot is much higher. Because of its affordability to lower-
income families, manufactured housing is one of the fastest-growing 
parts of the American housing market.\97\
---------------------------------------------------------------------------

    \97\ A detailed discussion of manufactured housing is contained 
in Kimberly Vermeer and Josephine Louie, The Future of Manufactured 
Housing, Joint Center for Housing Studies, Harvard University, 
(January 1997).
---------------------------------------------------------------------------

    The American Housing Survey found that 15.5 million people lived 
in 7 million manufactured homes in the United States in 1995, and 
that such units accounted for 6.3 percent of the housing stock, an 
increase from 5.4 percent in 1985. Shipments of manufactured homes 
rose steadily from 171,000 units in 1991 to 373,000 units in 1998. 
The industry grew much faster over this period in sales volume, from 
$4.7 billion in 1991 to $16.4 billion in 1998, reflecting both 
higher sales prices and a major shift from single-section homes to 
multisection homes, which contain two or three units which are 
joined together on site.\98\
---------------------------------------------------------------------------

    \98\ Data on industry shipments and sales has been obtained from 
``U.S. Housing Market Conditions,'' U.S. Department of Housing and 
Urban Development (May, 1999), p. 51.
---------------------------------------------------------------------------

    Despite their eligibility for mortgage financing, only about 10-
20 percent of manufactured homes \99\ are financed with mortgages 
secured by the property, even though half of owners hold title to 
the land on which the home is sited. Most purchasers of manufactured 
homes take out a personal property loan on the home and, if they buy 
the land, a separate loan to finance the purchase of the land.
---------------------------------------------------------------------------

    \99\ Although the terms are sometimes used interchangeably, 
manufactured housing and mobile homes differ in significant ways 
relative to construction standards, mobility, permanence, and 
financing (These distinctions are spelled out in detail in Donald S. 
Bradley, ``Will Manufactured Housing Become Home of First Choice?'' 
Secondary Mortgage Markets, (July 1997)). Mobile homes are not 
covered by national construction standards, though they may be 
subject to State or local siting requirements. Manufactured homes 
must be built according to the National Manufactured Housing 
Construction Safety and Standards Act of 1974. In accordance with 
this act, HUD developed minimum building standards in 1976 and 
upgraded them in 1994. Manufactured homes, like mobile homes, are 
constructed on a permanent chassis and include both axles and 
wheels. However, with manufactured housing, the axles and wheels are 
intended to be removed at the time the unit is permanently affixed 
to a foundation. Manufactured homes, unlike mobile homes, are 
seldom, if ever, moved. Mobile homes are financed with personal 
property loans, but manufactured homes are eligible for 
conventional-mortgage financing if they are located on land owned by 
or under long-term lease to the borrower. Other types of factory-
built housing, such as modular and panelized homes, are not included 
in this definition of ``manufactured housing.'' These housing types 
are often treated as ``site built'' for purposes of eligibility for 
mortgage financing.
---------------------------------------------------------------------------

    In 1995 the average loan size for a manufactured home was 
$24,500, with a 15 percent down payment and term of 13 years. Rates 
averaged about 3 percentage points higher than those paid on 15-year 
fixed rate mortgages, but borrowers benefit from very rapid loan-
processing and underwriting standards that allow high debt payment-
to-income (``back-end'') ratios.
    Traditionally loans on manufactured homes have been held in 
portfolio, but a secondary market has emerged since trading of 
asset-backed securities collateralized by manufactured home loans 
was initiated in 1987. Investor interest has been reported as strong 
due to reduced loan losses, low prepayments, and eligibility for 
packaging of such loans into real estate mortgage investment 
conduits (REMICs). The GSEs' underwriting standards allow them to 
buy loans on manufactured homes that meet the HUD construction code, 
if they are owned, titled, and taxed as real estate.
    The GSEs are beginning to expand their roles in the manufactured 
home loan market.\100\ A representative of the Manufactured Housing 
Institute has stated that ``Clearly, manufactured housing loans 
would fit nicely into Fannie Mae's and Freddie Mac's affordable 
housing goals.'' \101\ Given that manufactured housing loans often 
carry relatively high interest rates, an enhanced GSE role could 
also improve the affordability of such loans to lower-income 
families.
---------------------------------------------------------------------------

    \100\ Freddie Mac, the Manufactured Housing Institute and the 
Low Income Housing Fund have formed an alliance to utilize 
manufactured housing along with permanent financing and secondary 
market involvement to bring affordable, attractive housing to 
underserved, low- and moderate-income urban neighborhoods. 
Origination News. (December 1998), p.18.
    \101\ Mortgage-Backed Securities Letter. (September 7, 1998), p. 
3.
---------------------------------------------------------------------------

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

    Since the early 1990s, the multifamily mortgage market has 
become more closely integrated with global capital markets, although 
not to the same degree as the single-family mortgage market. In 
1997, 34 percent of multifamily mortgage originations were 
securitized, compared with 50 percent of single-family 
originations.\102\
---------------------------------------------------------------------------

    \102\ The Mortgage Market Statistical Annual for 1998 
(Washington, DC: Inside Mortgage Finance Publications), 203, 425; 
U.S. Housing Market Conditions (November 1998), Table 17.
---------------------------------------------------------------------------

    Loans on multifamily properties are typically viewed as riskier 
than their single-family counterparts. Property values, vacancy 
rates, and market rents in multifamily properties appear to be 
highly correlated with local job market conditions, creating greater 
sensitivity of loan performance to economic conditions than may be 
experienced in the single-family market.
    Within much of the single-family mortgage market, the GSEs 
occupy an undisputed position of industrywide dominance, holding 
loans or guarantees with an unpaid principal balance (UPB) of $1.5 
trillion, comprising 36 percent of $4.0 trillion in outstanding 
single-family mortgage debt as of the end of 1997. In multifamily, 
the overall market presence of the GSEs is more modest. At the end 
of 1997, the GSEs direct holdings and guarantees were $41.4 billion, 
representing 13.8 percent of $301 billion in outstanding multifamily 
mortgage debt.\103\ Based on market origination volume estimated at 
$40.7 billion, GSE acquisitions during 1997 represented 24 percent 
of the conventional multifamily market.\104\
---------------------------------------------------------------------------

    \103\ Federal Reserve Bulletin, June 1998, A 35. The comparable 
figure for year-end 1992, before the interim housing goals took 
effect, was 10.5 percent. (Federal Reserve Bulletin, (December 
1993), A 38.)
    \104\ Mortgages acquired by the GSEs during 1997 include some 
seasoned loans originated before 1997, but, recognizing that it is 
likely that the GSE will purchase some 1997 acquisitions in later 
years, the 24 percent figure provides a fairly good indicator of the 
magnitude of the GSEs' multifamily presence that year . GSE 
multifamily market share appears to have risen significantly, to 
approximately 38 percent, in 1998. The size of the conventional 
multifamily market is discussed in Appendix D.
---------------------------------------------------------------------------

1. Special Issues and Unmet Needs

    Recent studies have documented a pressing unmet need for 
affordable housing. For

[[Page 12694]]

example, the Harvard University Joint Center for Housing Studies, in 
its report State of the Nation's Housing 1997, points out that:
    (i) Despite the recent growth in homeownership rates, the 
absolute number of households without access to affordable housing 
is growing because the rental stock is not keeping up with the 
growth in household formation. ``Homeownership is more affordable 
today than during much of the 1980s and early 1990s,'' but renter 
households ``have received no comparable relief from high housing 
costs.''
    (ii) The affordable stock continues to shrink as losses due to 
abandonment and demolition have outpaced the rate at which units 
filter down into the low cost stock. Reductions in federal subsidies 
may contribute to further losses in the affordable stock.
    (iii) The problems of extremely low-income households remains 
the largest and most urgent priority. The number of families 
receiving rental subsidies has actually decreased.\105\
---------------------------------------------------------------------------

    \105\ See also Rental Housing Assistance--The Crisis Continues: 
The 1997 Report to Congress on Worst Case Housing Needs, U.S. 
Department of Housing and Urban Development, Office of Policy 
Development and Research (April 1998).
---------------------------------------------------------------------------

    The affordable housing issues go beyond the need for greater 
efficiency in delivering capital to the rental housing market. In 
many cases, subsidies are needed in order for low-income families to 
afford housing that meets adequate occupancy and quality standards. 
Nevertheless, greater access to reasonably priced capital can reduce 
the rate of losses to the stock, and can help finance the 
development of new or rehabilitated affordable housing when combined 
with locally funded subsidies. Development of a secondary market for 
affordable housing is one of many tools needed to address these 
issues.
    Recent scholarly research suggests that more needs to be done to 
develop the secondary market for affordable multifamily 
housing.\106\ Cummings and DiPasquale (1998) point to the numerous 
underwriting, pricing, and capacity building issues that impede the 
development of this market. They suggest the impediments can be 
addressed through the establishment of affordable lending standards, 
better information, and industry leadership.
---------------------------------------------------------------------------

    \106\ Jean L. Cummings and Denise DiPasquale, ``Developing a 
Secondary Market for Affordable Rental Housing: Lessons From the 
LIMAC/Freddie Mac and EMI/Fannie Mae Programs,'' Cityscape: A 
Journal of Policy Development and Research, 4(1), (1998), pp. 19-41.
---------------------------------------------------------------------------

    (i) More consistent standards are especially needed for 
properties with multiple layers of subordinated financing (as is 
often the case with affordable properties allocated Low Income 
Housing Tax Credits and/or local subsidies).
    (ii) More comprehensive and accurate information, particularly 
with regard to the determinants of default, can help in setting 
standards for affordable lending.
    (iii) Leadership from the government or from a GSE is needed to 
develop consensus standards; it would be unprofitable for any single 
purely private lender to provide because costs would be borne 
privately but competitors would benefit.

2. Underserved Market Segments

    There is evidence that segments of the multifamily housing stock 
have been affected by costly, difficult, or inconsistent 
availability of mortgage financing. Small properties with 5-50 units 
represent an example. The fixed-rate financing that is available is 
typically structured with a 5-10 year term, with interest rates as 
much as 150 basis points higher than those on standard multifamily 
loans, which may have adverse implications for affordability.\107\ 
This market segment appears to be dominated by thrifts and other 
depositories who keep these loans in portfolio. In part to hedge 
interest rate risk, loans on small properties are often structured 
as adjustable-rate mortgages.
---------------------------------------------------------------------------

    \107\ Drew Schneider and James Follain assert that interest 
rates on small property mortgages are as high as 300 basis points 
over comparable maturity Treasuries in ``A New Initiative in the 
Federal Housing Administration's Office of Multifamily Housing 
Programs: An Assessment of Small Projects Processing,'' Cityscape: A 
Journal of Policy Development and Research 4(1): 43-58, 1998. 
Berkshire Realty, a Fannie Mae Delegated Underwriting and Servicing 
(DUS) lender based in Boston, was quoting spreads of 135 to 150 
basis points in ``Loans Smorgasbord,'' Multi-Housing News, August-
September 1996. Additional information on the interest rate 
differential between large and small multifamily properties is 
contained in William Segal and Christopher Herbert, Segmentation of 
the Multifamily Mortgage Market: The Case of Small Properties, paper 
presented to annual meetings of the American Real Estate and Urban 
Economics Association, (January 2000).
---------------------------------------------------------------------------

    Multifamily properties with significant rehabilitation needs 
have experienced difficulty in obtaining mortgage financing. 
Properties that are more than 10 years old are typically classified 
as ``C'' or ``D'' properties, and are considered less attractive 
than newer properties by many lenders and investors.\108\ Fannie 
Mae's underwriting guidelines for negotiated transactions state that 
``the Lender is required to use a more conservative underwriting 
approach'' for transactions involving properties 10 or more years 
old.\109\ Fannie Mae funding for rehabilitation projects is 
generally limited to $6,000 per unit.\110\ Multifamily 
rehabilitation loans account for 1.9 percent of units backing 
Freddie Mac 1998 purchases. Rehabilitation loans accounted for only 
0.5 percent of units backing Fannie Mae's purchases that year.
---------------------------------------------------------------------------

    \108\ On the relation between age of property and quality 
classification see Jack Goodman and Brook Scott, ``Rating the 
Quality of Multifamily Housing,'' Real Estate Finance, (Summer, 
1997).
    \109\ Fannie Mae Multifamily Negotiated Transactions Guide, 
Section 305.03, ``Properties More than Ten Years Old.''
    \110\ Fannie Mae Multifamily Delegated Underwriting and 
Servicing Guide, Section 306.01, ``Definition--Moderate 
Rehabilitation Property.'' Loans involving rehabilitation costs 
exceeding $6,000 per unit may be approved on an exception basis, but 
in no event may rehabilitation costs exceeds $10,000 per unit or 25 
percent of the loan amount, whichever is lower. In October, 1998 
Fannie Mae announced a rehabilitation lending initiative providing 
up to $15,000 per on the condition that all units financed are 
affordable to low- and moderate income tenants.
---------------------------------------------------------------------------

    Historically, the flow of capital into housing for seniors has 
been characterized by a great deal of volatility. A continuing lack 
of long-term, fixed-rate financing jeopardizes the viability of a 
number of some properties. There is evidence that financing for new 
construction remains scarce.\111\ Both Fannie Mae and Freddie Mac 
offer Senior Housing pilot programs.
---------------------------------------------------------------------------

    \111\ W. Donald Campbell. Seniors Housing Finance, prepared for 
American Association of Retired Persons White House Conference on 
Aging Mini-Conference on Expanding Housing Choices for Older People, 
(January 26-27, 1995).
---------------------------------------------------------------------------

    Under circumstances where mortgage financing is difficult, 
costly, or inconsistent, GSE intervention may be desirable. Follain 
and Szymanoski (1995) say that ``a [market] failure occurs when the 
market does not provide the quantity of a particular good or service 
at which the marginal social benefits of another unit equal the 
marginal social costs of producing that unit. In such a situation, 
the benefits to society of having one more unit exceeds the costs of 
producing one more unit; thus, a rationale exists for some level of 
government to intervene in the market and expand the output of this 
good.'' \112\ It can be argued that the GSEs have the potential to 
contribute to the mitigation of difficult, costly, or inconsistent 
availability of mortgage financing to segments of the multifamily 
market because of their funding cost advantage, and even a 
responsibility to do so as a consequence of their public missions, 
especially in light of the limitations on direct government 
resources available to multifamily housing in today's budgetary 
environment.
---------------------------------------------------------------------------

    \112\ James R. Follain and Edward J. Szymanoski. ``A Framework 
for Evaluating Government's Evolving Role in Multifamily Mortgage 
Markets,'' Cityscape: A Journal of Policy Development and Research 
1(2), (1995), p. 154.
---------------------------------------------------------------------------

3. Recent History and Future Prospects in Multifamily

    The expansion phase of the real estate cycle been well underway 
for several years now, at least insofar as it pertains to 
multifamily. Rental rates have been rising, and vacancy rates have 
been relatively stable, contributing to a favorable environment for 
multifamily construction and lending activity.\113\ Delinquencies on 
commercial mortgages reached an 18-year low in 1997.\114\ Some 
analysts have warned that recent prosperity may have contributed to 
overbuilding in some markets and deterioration in underwriting 
standards.\115\ A

[[Page 12695]]

September, 1998 report by the Office of the Comptroller of the 
Currency anticipates continued decline in credit standards at the 77 
largest national banks as a consequence of heightened competition 
between lenders, and the Federal Deposit Insurance Corporation has 
expressed similar concerns regarding 1,212 banks it examined.\116\
---------------------------------------------------------------------------

    \113\ Despite sustained economic expansion, however, the rise in 
homeownership, has not fallen below 9 percent in recent years. 
(Regis J. Sheehan, ``Steady Growth,'' Units, (November/December 
1998), pp. 40-43). Regarding rents and vacancy rates see also Ted 
Cornwell. ``Multifamily Lending Approaches Record Level,'' National 
Mortgage News, (September 23, 1996); and David Berson, Monthly 
Economic and Mortgage Market Report, Fannie Mae, (November 1998).
    \114\ American Council of Life Insurance data reported in Inside 
MBS & ABS, (March 20, 1998).
    \115\ A November, 1998 ``Review of the Short-Term Supply/Demand 
Conditions for Apartments'' by Peter P. Kozel of Standard and Poor's 
concludes that ``in some markets, the supply of units exceeds the 
likely level of demand, and in only a few MSAs should the pace of 
development accelerate.'' See also ``Apartment Projects Find Lenders 
Are Ready with Financing,'' Lew Sichelman, National Mortgage News, 
(April 14, 1997); Commercial Lenders Warned That They Could Spur 
Overbuilding, National Mortgage News, (March 30, 1998); 
``Multifamily, Commercial Markets Grow Up,'' Neil Morse, Secondary 
Marketing Executive, (February 1998);'' ``Recipe for Disaster,'' 
National Mortgage News editorial, (July 6, 1998).
    \116\ 1998 Survey of Credit Underwriting Practices, Comptroller 
of the Currency, National Credit Committee. ``For the fourth 
consecutive year, underwriting standards for commercial loans have 
eased,'' states the OCC report. ``Examiners again cite competitive 
pressure as the primary reason for easing underwriting standards.'' 
The weakening of underwriting practices is especially concentrated 
in commercial real estate lending according to a the Federal Deposit 
Insurance Corporation's Report on Underwriting Practices, (October 
1997-March 1998). See also Donna Tanoue, ``Underwriting Concerns 
Grow,'' National Mortgage News, (September 21, 1998), and ``Making 
the Risk-Takers Pay,'' National Mortgage News, (October 12, 1998).
---------------------------------------------------------------------------

    Growth in the multifamily mortgage market has been fueled by 
investor appetites for Commercial Mortgage Backed Securities (CMBS). 
Nonagency securitization of multifamily and commercial mortgages 
received an initial impetus from the sale of nearly $20 billion in 
mortgages acquired by the Resolution Trust Corporation (RTC) from 
insolvent depositories in 1992-1993. Nonagency issuers typically 
enhance the credit-worthiness of their offerings through the use of 
senior-subordinated structures, combining investment-grade senior 
tranches with high-yield, below investment-grade junior tranches 
designed to absorb any credit losses.\117\
---------------------------------------------------------------------------

    \117\ On the effects of multifamily mortgage securitization see 
``Financing Multifamily Properties: A Play With new Actors and New 
Lines,'' Donald S. Bradley, Frank E. Nothaft, and James L. Freund, 
Cityscape, A Journal of Policy Development and Research, vol. 4, No. 
1 (1998); and ``Financing Multifamily Properties,'' Donald S. 
Bradley, Frank E. Nothaft, and James L. Freund, Urban Land (November 
1998).
---------------------------------------------------------------------------

    Because of their relatively low default risk in comparison with 
loans on other types of income property, multifamily mortgages are 
often included in mixed-collateral financing structures including 
other commercial property such as office buildings, shopping 
centers, and storage warehouses. CMBS volume reached $30 billion in 
1996, $44 billion in 1997, and $78 billion in the 1998, 
approximately 25 percent of which was multifamily.\118\
---------------------------------------------------------------------------

    \118\ ``New-Issue CMBS Volume,'' Commercial Mortgage Alert, ( 
October 5, 1998); Inside MBS & ABS, (February 12, 1999).
---------------------------------------------------------------------------

    During the financial markets turmoil in the fall of 1998, 
investors expressed reluctance to purchase the subordinated tranches 
in CMBS transactions, jeopardizing the ability of issuers to provide 
a cost-effective means of credit-enhancing the senior tranches as 
well.\119\ When investor perceptions regarding credit risk on 
subordinated debt escalated rapidly in August and September, the 
GSEs, which do not typically use subordination as a credit 
enhancement, benefited from a ``flight to quality.'' \120\ As 
spreads on AAA-rated CMBS widened from 85 basis points to 200 basis 
points over to comparable-maturity Treasury securities, some 
conduits found it advantageous to sell whole loans to the life 
insurance companies, the GSEs, and other traditional investors 
rather than securitize them directly as they had originally 
planned.\121\ The withdrawal from the market of a number of the 
three largest CMBS originators, Nomura/Capital America, Conti-Trade 
Services and Daiwa Securities will contribute to higher levels of 
GSE multifamily market share on a continuing basis.\122\ Ultimately, 
the relation between GSE and CMBS yield spreads will be a major 
determinant of GSE multifamily market share.\123\ Continuing 
uncertainty in the CMBS sector adds a note of uncertainty to 
projections regarding GSE multifamily acquisition volume in Appendix 
D.
---------------------------------------------------------------------------

    \119\ ``New CMBS Headache: B-Piece Market Softens,'' Commercial 
Mortgage Alert, (September 21, 1998); ``Criimi Bankruptcy 
Accelerates CMBS Freefall,'' Commercial Mortgage Alert, (October 12, 
1998); ``Capital America Halts Lending Amid Woes,'' Commercial 
Mortgage Alert, (October 12, 1998).
    \120\ On CMBS spreads see ``Turmoil Hikes Loan Rates'' in Wall 
Street Mortgage Report, (September 14, 1998). Regarding implications 
for the GSEs of the conduit pullback see ``No Credit Crunch for 
First Mortgages'' in Commercial Mortgage Alert, (October 12, 1998).
    \121\ Sally Gordon, ``A Lesson From the Capital Markets,'' 
Mortgage Banking Special Issue--Commercial, (February 1999), pp. 12-
18.
    \122\ See ``'99 CMBS Outlook: Fast Start, Then Lull,'' 
Commercial Mortgage Alert, (December 7, 1998); ``Chastened Conduits 
Get Back to Business,'' Commercial Mortgage Alert, (February 15, 
1999). Nomura/Capital America's monthly CMBS volume had been at a 
level of approximately $1 billion. See also ``ContiFinancial Halts 
Originations, Plans Portfolio Selloff,'' Real Estate Finance & 
Investment, (November 9, 1998); and ``Nomura in US Quits CRE 
Lending,'' National Mortgage News, (December 21, 1998).
    \123\ CMBS yield spreads in early 1999 were approximately 75-100 
basis points wider than those in the summer of 1998, but 
approximately 75-100 basis points narrower than the peak reached in 
the fall of 1998. ``Chastened Conduits Get Back to Business,'' 
Commercial Mortgage Alert, (February 15, 1999).
---------------------------------------------------------------------------

    Depository institutions and life insurance companies, formerly 
among the largest holders of multifamily debt, have experienced a 
decline in their share of the market at the expense of CMBS 
conduits.\124\ Increasingly, depositories and life insurance 
companies are participating in multifamily markets by holding CMBS 
rather than whole loans, which are often less liquid, more 
expensive, and subject to more stringent risk-based capital 
standards.\125\ In recent years a rising proportion of multifamily 
mortgages have been originated to secondary market standards, a 
consequence of a combination of factors including the establishment 
of a smoothly functioning securitization ``infrastructure;'' the 
greater liquidity of mortgage-related securities as compared with 
whole loans; and the desire for an ``exit strategy'' on the part of 
investors.\126\
---------------------------------------------------------------------------

    \124\ ``Financing Multifamily Properties: A Play With New Actors 
and New Lines,'' Donald S. Bradley, Frank E. Nothaft, and James L. 
Freund, Cityscape: A Journal of Policy Development and Research, 
4(1), (1998).
    \125\ The Impact of Public Capital Markets on Urban Real Estate, 
Clement Dinsmore, discussion paper, Brookings Institution Center on 
Urban and Metropolitan Policy, July 1998; ``Capital Availability 
Fuels Commercial Market Growth,'' Marshall Taylor, Real Estate 
Finance Today, (February 17, 1997).
    \126\ Board of Governors of the Federal Reserve System and U.S. 
Securities and Exchange Commission, Report to the Congress on 
Markets for Small-Business- and Commercial-Mortgage-Backed 
Securities, (September 1998).
---------------------------------------------------------------------------

    Because of their limited use of mortgage debt, increased equity 
ownership of multifamily properties by REITs may have contributed to 
increased competition among mortgage originators, servicers and 
investors for a smaller mortgage market than would otherwise exist. 
During the first quarter of 1997, REITs accounted for 45 percent of 
all commercial real estate transactions, and the market 
capitalization of REITs at the end of January 1998 exceeded that of 
outstanding CMBS.\127\
---------------------------------------------------------------------------

    \127\ ``REITs Tally Nearly Half of All Big CRE Deals in First 
Quarter,'' National Mortgage News, (July 7, 1997); ``Will REITs, 
Mortgage-Backeds Make Difference in Downturn,'' Jennifer Goldblatt, 
American Banker, (February 18, 1998).
---------------------------------------------------------------------------

    Demographic factors will contribute to continued steady growth 
in the new construction segment of the multifamily mortgage market. 
The number of apartment households is expected to grow approximately 
1.1 percent per year over 2000-2005. Taking into consideration 
losses from the housing stock, it has been projected that 
approximately 250,000-275,000 additional multifamily units will be 
needed in order to meet anticipated demand.\128\ This flow is 
approximately half that of the mid-1980s, but twice that of the 
depressed early 1990s. In 1998, 273,900 apartment units were 
completed.\129\
---------------------------------------------------------------------------

    \128\ ``Apartment Demographics: Good for the Long Haul?'' Jack 
Goodman, Real Estate Finance, (Winter 1997); ``The Multifamily 
Outlook,'' Jack Goodman, Urban Land, (November 1998).
    \129\ U.S. Housing Market Conditions 2nd Quarter 1999, U.S. 
Department of Housing and Urban Development (August 1999), Table 4.
---------------------------------------------------------------------------

    The high degree of volatility of multifamily new construction 
experienced historically is consistent with a view that this sector 
of the housing market is driven more by fluctuations in the 
availability of financing than by demographic fundamentals. The 
stability and liquidity of the housing finance system is therefore a 
significant determinant of whether the volume of new construction 
remains consistent with demand.
    Past experience suggests that the availability of financing for 
all forms of commercial real estate is highly sensitive to the state 
of the economy. In periods of economic uncertainty, lenders and 
investors sometimes raise underwriting and credit standards to a 
degree that properties that would be deemed creditworthy under 
normal circumstances are suddenly unable to obtain financing. 
Ironically, difficulty in obtaining financing may contribute to a 
fall in property values that can exacerbate a credit crunch.\130\

[[Page 12696]]

The consensus viewpoint among most economists is that an economic 
recession in 2000 is unlikely.\131\ However, the possibility of a 
global economic downturn cannot be dismissed.\132\ The sensitivity 
of commercial real estate markets to investor perceptions regarding 
global volatility was demonstrated by the rise in CMBS spreads in 
September, 1998.\133\ Thus, market disruptions could have adverse 
implications on U.S. commercial and residential mortgage markets.
---------------------------------------------------------------------------

    \130\ Howard Esaki, a principal in CMBS Research at Morgan 
Stanley Dean Witter stated recently that volatility in global 
markets contributed to a 10-20 percent decline in commercial real 
estate values in late 1998. John Hackett, ``CRE Seen Down 10% to 
20%,'' National Mortgage News, (November 23, 1998), p. 1.
    \131\ The Congressional Budget Office, The Economic and Budget 
Outlook: An Update, (July 1999) predicts that GDP growth will slow 
from an annual rate exceeding 3.5 percent in recent years to 2.4 
percent over 2000-2003 (p. 11). Standard & Poor's DRI, The U.S. 
Economy, (September 1999), estimates the probability of a recession 
in 2000, triggered by a collapse of the stock market, at 10 percent. 
Under this scenario, GDP growth would drop to 0.2 percent in 2000, 
but rebound to over 3 percent during the 2001-2003period.
    \132\ The World Bank Group, Global Economic Prospects and the 
Developing Countries 1998/99: Beyond Financial Crisis, 1998. 
Implications of the economic crisis in developing countries for 
lenders in developed countries is discussed in Martin Wolf, 
``Borrowing: Let Lenders Beware,'' Financial Times, (December 9, 
1998). DRI/McGraw Hill's U.S. Financial Notes says there is about a 
30 percent chance of a ``hard landing'' in 1999 because of Brazil's 
decision to float the real and Japan's ongoing severe financial 
problems. Alternatively, if there is no recession in 1999, the 
result could be a later, but more severe, recession (February 18, 
1999, p. 3).
    \133\ John Holusha, ``As Financing Pool Dries Up, Some See 
Opportunity,'' New York Times, November 1, 1998.
---------------------------------------------------------------------------

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

    The GSEs have rapidly expanded their presence in the multifamily 
mortgage market in the period since the housing goals were 
established in 1993. Fannie Mae has played a much larger role in the 
multifamily market, with purchases of $6.9 billion in 1997 compared 
with $2.7 billion by Freddie Mac. If Fannie Mae multifamily 
acquisitions maintain their recent growth rate, it appears likely 
that they will be successful in reaching its publicly announced goal 
of conducting $50 billion in multifamily transactions between 1994 
and the end of the decade.\134\ Fannie Mae's multifamily 
underwriting standards are highly influential and have been widely 
emulated throughout the industry. Freddie Mac has successfully 
rebuilt its multifamily program after a three-year hiatus during 
1991-1993 precipitated by widespread defaults.
---------------------------------------------------------------------------

    \134\ See Fannie Mae's World Wide Web site at http://
www.fanniemae.com.
---------------------------------------------------------------------------

    Multifamily loans represent a relatively small portion of the 
GSEs' business activities. For example, multifamily loans held in 
portfolio or guaranteed by the GSEs at the end of 1997 totaled $41.4 
billion, less than 3 percent of their single-family combined 
portfolio and guaranteed holdings. In comparison, multifamily 
mortgages held or guaranteed by the GSEs represent approximately 8 
percent of the overall stock of mortgage debt.\135\
---------------------------------------------------------------------------

    \1\ Federal Reserve Bulletin, (June 1998), A 35.
---------------------------------------------------------------------------

    However, the multifamily market contributes disproportionately 
to GSE purchases meeting both the Low- and Moderate-Income and 
Special Affordable Housing goals. In 1997, Fannie Mae's multifamily 
purchases represented 13.4 percent of their total acquisition 
volume, measured in terms of dwelling units. Yet these multifamily 
purchases comprised 26.7 percent of units qualifying for the Low- 
and Moderate Income Housing Goal, and 44.4 percent of units meeting 
the Special Affordable goal. Multifamily purchases were 8.2 percent 
of units backing Freddie Mac's 1997 acquisitions, 18.8 percent of 
units meeting the Low-and Moderate Income Housing Goal, and 31.4 
percent of units qualifying for the Special Affordable Housing 
Goal.\136\ The multifamily market therefore comprises a significant 
share of units meeting the Low- and Moderate-Income and Special 
Affordable Housing Goals for both GSEs, and the goals may have 
contributed to increased emphasis by both GSEs on multifamily in the 
period since the Final Rule took effect in 1995.\137\
---------------------------------------------------------------------------

    \136\ 1997 Annual Housing Activity Reports, Table 1.
    \137\ William Segal and Edward J. Szymanoski. The Multifamily 
Secondary Mortgage Market: The Role of Government-Sponsored 
Enterprises. Housing Finance Working Paper No. HF-002, Office of 
Policy Development and Research, Department of Housing and Urban 
Development, (March 1997).
---------------------------------------------------------------------------

    The majority of units backing GSE multifamily transactions meet 
the Low- and Moderate Income Housing Goal because the great majority 
of rental units are affordable to families at 100 percent of median 
income, the standard upon which the Low- and Moderate Income Housing 
Goal is defined. For example, 33.3 percent of units securing Freddie 
Mac's 1997 one-family owner-occupied mortgage purchases met the Low- 
and Moderate Income Housing Goal, compared with 95.9 percent of its 
multifamily transactions. Corresponding figures for Fannie Mae were 
33.8 percent and 85.2 percent.\138\ For this reason, multifamily 
purchases represent a crucial component of the GSEs' efforts in 
meeting the Low- and Moderate Income Housing Goal.
---------------------------------------------------------------------------

    \138\ HUD analysis of GSE loan-level data. Affordability data 
are missing on 11.1 percent of units backing Fannie Mae's 1997 
multifamily acquisitions, which may contribute to the disparity 
between Fannie Mae and Freddie Mac regarding percentage of 
multifamily acquisitions contributing to the low-mod goal.
---------------------------------------------------------------------------

    Because such a large proportion of multifamily units qualify for 
the Low- and Moderate-Income Housing Goal and for the Special 
Affordable Housing Goal, Freddie Mac's weaker multifamily 
performance adversely affects its overall performance on these two 
housing goals relative to Fannie Mae. Units in multifamily 
properties accounted for 7.9 percent of Freddie Mac's mortgage 
purchases during 1996-1998, compared with 12.2 percent for Fannie 
Mae. Fannie Mae's greater emphasis on multifamily is a major factor 
contributing to the strength of its housing goals performance 
relative to Freddie Mac.

5. A Role for the GSEs in Multifamily Housing

    By sustaining a secondary market for multifamily mortgages, the 
GSEs can extend the benefits that come from increased mortgage 
liquidity to many more lower-income families while helping private 
owners to maintain the quality of the existing affordable housing 
stock. In addition, standardization of underwriting terms and loan 
documents by the GSEs has the potential to reduce transactions 
costs. As the GSEs gain experience in areas of the multifamily 
mortgage market affected by costly, difficult, or inconsistent 
access to secondary markets, they gain experience that enables them 
to better measure and price default risk, yielding greater 
efficiency and further cost savings.
    Ultimately, greater liquidity, stability, and efficiency in the 
secondary market due to a significant presence by the GSEs will 
benefit lower-income renters by enhancing the availability of 
mortgage financing for affordable rental units--in a manner 
analogous to the benefits the GSEs provide homebuyers. Providing 
liquidity and stability is the main role for the GSEs in the 
multifamily market, just as in the single-family market.
    Current volatility in the CMBS market underlines the need for an 
ongoing GSE presence in the multifamily secondary market. The 
potential for an increased GSE presence is enhanced by virtue of the 
fact that an increasing proportion of multifamily mortgages are 
originated to secondary market standards, as noted previously. While 
the GSEs have also been affected by the widening of yield spreads 
affecting CMBS, historical experience suggests that agency spreads 
will converge to historical magnitudes as a consequence of the 
perceived benefits of federal sponsorship.\139\ When this occurs, 
the capability of the GSEs to serve and compete in the multifamily 
secondary market will be enhanced.\140\
---------------------------------------------------------------------------

    \139\ Fundingnotes, Vol. 3, Issue 9; (September 1998), Eric 
Avidon, ``PaineWebber Lauds Fannie DUS Paper,'' National Mortgage 
News, (September 14, 1998), p. 21.
    \140\ There is evidence that the GSEs have benefited from recent 
widening in CMBS spreads because of their funding cost advantage. 
See ``No Credit Crunch for First Mortgages,'' Commercial Mortgage 
Alert, (October 12, 1998); and ``Turmoil a Bonanza for Freddie,'' 
Commercial Mortgage Alert, (November 2, 1998).
---------------------------------------------------------------------------

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

    Holding 9.8 percent of the outstanding stock of multifamily 
mortgage debt and guarantees as of the end of 1997, Fannie Mae is 
regarded as an influential force within the multifamily market. Its 
Delegated Underwriting and Servicing (DUS) program, in which Fannie 
Mae delegates underwriting responsibilities to originators in return 
for a commitment to share in any default risk, now accounts for more 
than half its multifamily acquisitions, and has been regarded as 
highly successful.

[[Page 12697]]

    Freddie Mac's presence in the multifamily market is not as large 
as that of Fannie Mae, with year-end 1997 holdings of multifamily 
debt and guarantees representing 2.5 percent of the total. However, 
Freddie Mac is credited with rapidly rebuilding its multifamily 
operations since 1993. The GSEs' ability to lead the multifamily 
industry is discussed further below.

7. GSEs' Performance in the Multifamily Mortgage Market

    GSE activity in the multifamily mortgage market has expanded 
rapidly since 1993, as noted previously. However, it is not clear 
that the potential of the GSEs to lead the multifamily mortgage 
industry has been fully exploited. In particular, the GSEs' 
multifamily purchases do not appear to be consistently contributing 
to mitigation of excessive cost of mortgage financing facing small 
properties with 5-50 units. GSE purchases of small loans with unpaid 
principal balance (UPB) less than or equal to $1 million have 
exhibited considerable volatility over 1993-1997, ranging from as 
little as 15 percent of the number of mortgage loans purchased 
(1996) to as high as 64 percent (1995).\141\
---------------------------------------------------------------------------

    \141\ HUD analysis of GSE loan-level data.
---------------------------------------------------------------------------

    Based on data from the Survey of Residential Finance showing 
that 37 percent of units in mortgaged multifamily properties were in 
properties with 5-49 units, it appears reasonable to assume that 
loans backed by small properties account for 37 percent of 
multifamily units financed each year. Applying estimates of the 
dollar-size of the conventional multifamily market derived in 
Appendix D, and combining these with figures on loan amount per unit 
from GSE data in conjunction with data on loans securitized by 
private conduits to derive estimates of the annual volume of 
multifamily lending as measured in number of units financed, is 
appears that, during 1996-1998, the GSEs acquired loans representing 
only 5 percent of units in small multifamily properties with 5-50 
units.
    GSE multifamily acquisitions tend to involve larger properties 
than are typical for the market as a whole.\142\ For example, the 
average number of units in Fannie Mae's 1997 multifamily 
transactions was 163, with a corresponding figure of 158 for Freddie 
Mac. Both of these averages are significantly higher than the 
overall market average of 33.4 units per property on 1995 
originations estimated from the HUD Property Owners and Managers 
(POMS) survey.\143\ A factor possibly contributing to the GSEs' 
emphasis on larger properties is the relatively high fixed 
multifamily origination costs, including appraisal, environmental 
review, and legal fees typically required under GSE underwriting 
guidelines.\144\
---------------------------------------------------------------------------

    \142\ Larger properties may be perceived as less subject to 
income volatility caused by vacancy losses. Scale economies in 
securitization may also favor purchase of larger multifamily 
mortgages by the GSEs. Scale economies refer to the fixed costs in 
creating a mortgage backed security, and the smaller reduction in 
yield (higher security price) if these costs can be spread over 
larger unpaid principal balances.
    \143\ 1995 POMS data are used because 1995 represents the year 
with the most complete mortgage origination information in the 
Survey. 1996 GSE data are used because of number of units or 
property exhibited atypical behavior during 1995.
    \144\ These costs have been estimated at $30,000 for a typical 
transaction. Presentation by Jeff Stern, Vice President, Enterprise 
Mortgage Investments, HUD GSE Working Group, (July 23, 1998).
---------------------------------------------------------------------------

    After evaluating the results of a $500 million Small Loan 
Experiment, Fannie Mae announced in October, 1998 that it had 
established a permanent Small Loan product through selected DUS 
lenders. Features include streamlined underwriting and due diligence 
procedures and documentation requirements. Unlike the standard DUS 
product, which has a $1 million minimum loan amount, there is no 
minimum loan amount for the Small Loan product.\145\
---------------------------------------------------------------------------

    \145\ ``Fannie Mae Offers Mortgage Financing for the 
Rehabilitation of Affordable Apartments; Also Expands Availability, 
Streamlines Procedures for Financing of Small Apartment 
Properties,'' Fannie Mae News Release, October 20, 1998. Freddie 
Mac's Conventional Cash Multifamily Mortgage Purchase Program 
includes a Small Loan Program for mortgages of $300,000--$1 million.
---------------------------------------------------------------------------

    Another area affected by credit gaps, in which the GSEs have not 
demonstrated market leadership is rehabilitation loans. Fannie Mae 
applies more conservative underwriting standards to such properties, 
as discussed above. Both GSEs' relatively weak performance in the 
multifamily rehabilitation market segment is related to the fact 
that, since the inception of the interim housing goals in 1993, the 
great majority of units backing GSE multifamily mortgage purchases 
have been in properties securing refinance loans with an established 
payment history, in a proportion exceeding 80 percent in some 
years.\146\
---------------------------------------------------------------------------

    \146\ Data from the HUD Property Owners and Managers Survey 
(POMS) suggests that, in and of itself, the GSEs' emphasis on 
refinance loans may roughly track that of the overall market.
---------------------------------------------------------------------------

    In October, 1998 Fannie Mae announced a rehabilitation lending 
initiative providing up to $15,000 per unit on the condition that 
all units financed are affordable to low-and moderate income 
tenants. This product is intended to assist property owners in 
enhancing property quality and retaining tenants, strengthening 
competitiveness in relation to other similar properties.\147\
---------------------------------------------------------------------------

    \147\ ``Fannie Mae Offers Mortgage Financing for the 
Rehabilitation of Affordable Apartments; Also Expands Availability, 
Streamlines Procedures for Financing of Small Apartment 
Properties,'' Fannie Mae News Release, October 20, 1998.
---------------------------------------------------------------------------

    The GSEs have been conservative in their approach to multifamily 
credit risk.\148\ HUD's analysis of prospectus data indicates that 
the average loan-to-value (LTV) ratio on pools of seasoned 
multifamily mortgages securitized by Freddie Mac during 1995 through 
1996 was 55 percent. In comparison, the average LTV on private-label 
multifamily conduit transactions over 1995-1996 was 73 percent. 
Fannie Mae utilizes a variety of credit enhancements to further 
mitigate default risk on multifamily acquisitions, including loss 
sharing, recourse agreements, and the use of senior/subordinated 
debt structures.\149\ Freddie Mac is less reliant on credit 
enhancements than is Fannie Mae, possibly because of a more 
conservative underwriting approach.\150\
---------------------------------------------------------------------------

    \148\ Standard & Poor's described Fannie Mae's multifamily 
lending as ``extremely conservative'' in ``Final Report of Standard 
& Poor's to the Office of Federal Housing Enterprise Oversight 
(OFHEO),'' (February 3, 1997), p. 10.
    \149\ See William Segal and Edward J. Szymanoski. ``Fannie Mae, 
Freddie Mac, and the Multifamily Mortgage Market,'' Cityscape: A 
Journal of Policy Development and Research, vol. 4, no. 1 (1998), 
pp. 59-91.
    \150\ Freddie Mac's policy of re-underwriting each multifamily 
acquisition is a response to widespread defaults affecting its 
multifamily portfolio during the late 1980s according to Follain and 
Szymanoski (1995).
---------------------------------------------------------------------------

    GSE ambivalence regarding the perception of credit risk in 
lending on affordable multifamily properties is evident with regard 
to pilot programs established in 1991 between Freddie Mac and the 
Local Initiatives Managed Assets Corporation (LIMAC), a subsidiary 
of the Local Initiatives Support Corporation (LISC), and in 1994 
between Fannie Mae and Enterprise Mortgage Investments (EMI), a 
subsidiary of the Enterprise Foundation. Cummings and DiPasquale 
(1998) conclude that both initiatives had mixed results, although 
the Fannie Mae/EMI pilot was more successful in a number of regards. 
The Freddie Mac/LIMAC initiative was suspended after two years with 
only one completed transaction, involving eight loans with an 
aggregate loan amount of $4.6 million. As of June, 1997, 15 
transactions comprising $20.5 million had been completed under the 
Fannie Mae/EMI pilot, which is ongoing.
    Both programs suffered initially from documentation requirements 
that borrowers perceived as burdensome. Cummings and DiPasquale 
observe that ``The smaller, nonprofit, and CDC developers that these 
programs intended to bring to the market were unprepared, and 
perhaps unwilling or unable, to meet the high costs of Freddie Mac's 
and Fannie Mae's due diligence requirements.''

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

    This section first discusses each GSE's performance under the 
Low- and Moderate-Income Housing Goal over the 1993-98 period. The 
data presented are ``official results''--i.e., they are based on 
HUD's in-depth analysis of the loan-level data submitted to the 
Department and the counting provisions contained in HUD's 
regulations in 24 CFR part 81, subpart B. As explained below, in 
some cases these ``official results'' differ from goal performance 
reported to the Department by the GSEs in their Annual Housing 
Activities Reports.
    Following this analysis, the GSEs' past performance in funding 
low- and moderate-income borrowers in the single-family mortgage 
market is provided. Performance indicators for the Geographically-
Targeted and Special Affordable Housing Goals are also included in 
order to present a complete picture in Appendix A of the GSEs' 
funding of single-family mortgages that qualify for the

[[Page 12698]]

three housing goals. In addition, the findings from a wide range of 
studies--employing both quantitative and qualitative techniques to 
analyze several performance indicators and conducted by HUD, 
academics, and major research organizations--are summarized below.
    Organization and Main Findings. Section E.1 reports the 
performance of Fannie Mae and Freddie Mac on the Low- and Moderate-
Income Housing Goal. Section E.2 uses HMDA data and the loan-level 
data that the GSEs provide to HUD on their mortgage purchases to 
compare the characteristics of GSE purchases of single-family loans 
with the characteristics of all loans in the primary mortgage market 
and of newly-originated loans held in portfolio by depositories. 
Section E.3 summarizes the findings from several studies that have 
examined the role of the GSEs in supporting affordable lending. 
Section E.4 discusses the findings from a recent HUD-sponsored study 
of the GSEs' underwriting guidelines.\151\ Finally, Section E.5 
reviews the GSEs' support of the single-family rental market.
---------------------------------------------------------------------------

    \151\ A more detailed discussion of underwriting guidelines is 
contained in the analysis below regarding Factor 5, ``The GSEs' 
Ability to Lead the Industry.''
---------------------------------------------------------------------------

    The Section's main findings with respect to the GSEs' single-
family mortgage purchases are as follows:
    (i) Both Fannie Mae and Freddie Mac surpassed the Low- and 
Moderate-Income Housing Goals of 40 percent in 1996 and 42 percent 
in 1997 and 1998.
    (ii) Both Fannie Mae and Freddie Mac have improved their 
affordable lending \152\ performance over the past six years but, on 
average, they have lagged the primary market in providing mortgage 
funds for lower-income borrowers and underserved neighborhoods. This 
finding is based both on HUD's analysis of GSE and HMDA data as well 
as on numerous studies by academics and research organizations.
---------------------------------------------------------------------------

    \152\ The term ``affordable lending'' is used generically here 
to refer to lending for lower-income families and neighborhoods that 
have historically been underserved by the mortgage market.
---------------------------------------------------------------------------

    (iii) The GSEs show very different patterns of home loan 
lending.\153\ Through 1998, Freddie Mac has been less likely than 
Fannie Mae to fund single-family home mortgages for low-income 
families and their communities. The percentages of Freddie Mac's 
purchases benefiting historically underserved families and their 
neighborhoods have also been substantially less than the 
corresponding shares of total market originations. Freddie Mac has 
not made much progress closing the gap between its performance and 
that of the overall home loan market.
---------------------------------------------------------------------------

    \153\ Throughout these appendices, the terms ``home loan'' or 
``home mortgage'' will refer to a ``home purchase loan,'' as opposed 
to a ``refinance loan.''
---------------------------------------------------------------------------

    (iv) Fannie Mae's purchases more nearly match the patterns of 
originations in the primary market than do Freddie Mac's. However, 
during the 1993-98 period as a whole and the 1996-98 period during 
which the new goals were in effect, Fannie Mae has lagged 
depositories and others in the conforming market in providing 
funding for the lower-income borrowers and neighborhoods covered by 
the three housing goals.
    (v) A large percentage of the lower-income loans purchased by 
the GSEs have relatively high down payments, which raises questions 
about whether the GSEs are adequately meeting the needs of lower-
income families who have little cash for making large down payments.
    (vi) A study by The Urban Institute of lender experience with 
the GSEs' underwriting standards finds that the enterprises have 
stepped up their outreach efforts and have increased the flexibility 
in their underwriting standards, to better accommodate the special 
circumstances of lower-income borrowers. However, this study 
concludes that the GSEs' guidelines remain somewhat inflexible and 
that they are often hesitant to purchase affordable loans. Lenders 
also tell the Urban Institute that Fannie Mae has been more 
aggressive than Freddie Mac in market outreach to underserved 
groups, in offering new affordable products, and in adjusting their 
underwriting standards.
    (vii) While single-family rental properties are an important 
source of low-income rental housing, they represent only a small 
portion of the GSEs' business. In addition, many of the single-
family rental properties funded by the GSEs are one-unit detached 
units in suburban areas rather than the older, 2-4 units commonly 
located in urban areas.

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

    HUD's goals specified that in 1996 at least 40 percent of the 
number of units eligible to count toward the Low- and Moderate-
Income Goal should qualify as low-or moderate-income, and at least 
42 percent should qualify in 1997 and 1998. Actual performance, 
based on HUD's analysis, was as follows:

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

Thus, Fannie Mae surpassed the goals by 5.6 percentage points and 
3.7 percentage points in 1996 in 1997, respectively, while Freddie 
Mac surpassed the goals by 1.1 and 0.6 percentage points. In 1998 
Fannie Mae's performance fell by 1.6 percentage points, while 
Freddie Mac's reported performance continued to rise, by 0.3 
percentage point.
    The figures for goal performance presented above for 1993-97 
differ from the corresponding figures presented by Fannie Mae and 
Freddie Mac in their Annual Housing Activity Reports to HUD by 0.2-
0.3 percentage points in both 1996 and 1997, reflecting minor 
differences in application of counting rules.
    Fannie Mae's performance on the Low- and Moderate-Income Goal 
jumped sharply in just one year, from 34.1 percent in 1993 to 45.1 
percent in 1994, before tailing off to 42.8 percent in 1995. As 
indicated, it then stabilized at the 1994 level, just over 45 
percent, in 1996 and 1997, before tailing off to 44.1 percent last 
year. Freddie Mac has shown more steady gains in performance on the 
Low- and Moderate-Income Goal, from 30.0 percent in 1993 to 38.0 
percent in 1994 and 39.6 percent in 1995, before surpassing 41 
percent in 1996 and 42 percent 1997, and rising to nearly 43 percent 
last year.
    Fannie Mae's performance on the Low-and Moderate-Income Goal has 
surpassed Freddie Mac's in every year. However, Freddie Mac's 1998 
performance represented a 44 percent increase over the 1993 level, 
exceeding the 29 percent increase for Fannie Mae. And Freddie Mac's 
performance was 97 percent of Fannie Mae's low- and moderate-income 
share in 1998, the highest ratio since the goals took effect in 
1993. This improved performance of Freddie Mac is due mainly to its 
increased purchases of multifamily loans as it re-entered that 
market.

2. Comparisons With the Primary Mortgage Market

    This section summarizes several analyses conducted by HUD on the 
extent to which the GSEs' loan purchases through 1998 mirror or 
depart from the patterns found in the primary mortgage market. The 
GSEs' affordable lending performance is also compared with the 
performance of major portfolio lenders such as commercial banks and 
thrift institutions. Dimensions of lending considered include the 
borrower income and underserved area dimensions covered by the three 
housing goals. Subsection a defines the primary mortgage market, 
subsection b addresses some questions that have recently

[[Page 12699]]

arisen about HMDA's measurement of GSE activity, and subsections c-e 
present the findings.\154\
---------------------------------------------------------------------------

    \154\ Subsections b-d of this section focus on the single-family 
mortgage market for home purchase loans, which is the relevant 
market for analysis of homeownership opportunities. Subsection e 
extends the analysis to include single-family refinance loans. For a 
discussion of past performance in the multifamily mortgage market, 
see Section D of this Appendix.
---------------------------------------------------------------------------

    The market analysis in this section is based mainly on HMDA data 
for home purchase loans originated in metropolitan areas during the 
years 1992 to 1998. The HMDA data for 1998 was not released until 
August 1999 which gave HUD little time to incorporate that data 
fully into the analyses reported in these appendices; thus, the 
discussion below will often focus on the year 1997, with any 
differences from 1998 briefly noted. However, it should be 
emphasized that 1997 represents more typical mortgage market 
activity than the heavy refinancing year of 1998. Still, important 
shifts in mortgage funding that occurred during 1998 will be 
highlighted in order to offer as complete and updated analysis as 
possible.

a. Definition of Primary Market

    First it is necessary to define what is meant by ``primary 
market'' in making these comparisons. In this section this term 
includes all mortgages on single-family owner-occupied properties 
that are originated in the conventional conforming market.\155\ The 
source of this market information is the data provided by loan 
originators to the Federal Financial Institutions Examination 
Council (FFIEC) in accordance with the Home Mortgage Disclosure Act 
(HMDA).
---------------------------------------------------------------------------

    \155\ Thus, the market definition in this section is narrower 
than the data presented earlier in Section C and Tables A.1a and 
A.1b, which covered all loans (both government and conventional) 
less than or equal to the conforming loan limit. In this section, 
only the GSEs' purchases of conventional conforming loans are 
considered.
---------------------------------------------------------------------------

    There is a consensus that the following loans should be excluded 
from the HMDA data in defining the ``primary market'' for the sake 
of comparison with the GSEs'' purchases of goal-qualifying 
mortgages:
    (i) Loans with a principal balance in excess of the loan limit 
for purchases by the GSEs--$240,000 for a 1-unit property in most 
parts of the United States in 1999.\156\ Loans not in excess of this 
limit are referred to as ``conforming mortgages'' and larger loans 
are referred to as ``jumbo mortgages.'' \157\
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    \156\ Higher limits apply for loans on 2-, 3-, and 4-unit 
properties and for properties in Alaska, Hawaii, Guam, and the 
Virgin Islands.
    \157\ ``Jumbo mortgages'' in any given year might become 
eligible for purchase by the GSEs in later years as the loan limits 
rise and the outstanding principal balance is reduced.
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    (ii) Loans which are backed by the Federal government, including 
those insured by the Federal Housing Administration and those 
guaranteed by the Department of Veterans Affairs, which are 
generally securitized by the Government National Mortgage 
Association (``Ginnie Mae''), as well as Rural Housing Loans, 
guaranteed by the Farmers Home Administration.\158\ Generally, the 
GSEs do not receive credit on the housing goals for purchasing loans 
with Federal government backing. Loans without Federal government 
backing are referred to as ``conventional mortgages.''
---------------------------------------------------------------------------

    \158\ However, in analyzing the provision of mortgage finance 
more generally, it is often appropriate to include government loans; 
see Tables A.1a, A.1b and A.2 in Section C.3.b.
---------------------------------------------------------------------------

    Questions have arisen about whether loans on manufactured 
housing should be excluded when comparing the primary market with 
the GSEs. As discussed elsewhere in this Appendix, the GSEs have not 
played a significant role in the manufactured housing mortgage 
market in the past. However, the manufactured home mortgage market 
is changing in ways that make a higher percentage of such loans 
eligible for purchase by the GSEs, and the GSEs are looking for ways 
to increase their purchases of these loans. But more importantly, 
the manufactured housing sector is one of the most important 
providers of affordable housing, which makes it appropriate to 
include this sector in the market definition. For comparison 
purposes, data are presented for the primary market defined both to 
include and exclude mortgages originated by manufactured housing 
lenders. This issue is discussed further in Appendix D, which 
calculates the market shares for each housing goal.
    Questions have also arisen about whether subprime loans should 
be excluded when comparing the primary market with the GSEs. 
Appendix D, which examines this issue in some detail, reports the 
effects of excluding the B&C portion of the subprime market from 
HUD's estimates of the goal-qualifying shares of the overall 
(combined owner and rental) mortgage market. As explained Section 
C.3.e of this appendix, the low-income and minority borrowers in the 
A-minus portion of the subprime market could benefit from the 
standardization and lower interest rates that typically accompany an 
active secondary market effort by the GSEs. A-minus loans are not 
nearly as risky as B&C loans and Freddie Mac has already starting 
purchasing A-minus loans, both on a flow basis and through 
negotiated transactions. Fannie Mae recently introduced a new 
program targeted at A-minus borrowers. Thus, HUD does not believe 
that A-minus loans should be excluded from the market definition.
    Unfortunately, HMDA does not identify subprime loans, much less 
separating them into their A-minus and B&C components. There is 
evidence that many subprime loans are not reported to HMDA but there 
is no conclusive evidence on this issue.\159\ Thus, it is not 
possible to exclude B&C loans from the comparisons reported below. 
However, HUD staff has identified HMDA reporters that primarily 
originate subprime loans.\160\ The text below will report the 
effects of excluding data for these lenders from the primary market. 
The effects are minor mostly because the analysis below focuses on 
home purchase loans, which accounted for only twenty percent of the 
mortgages originated by the subprime lenders. During 1997 and 1998, 
the subprime market was primarily a refinance market.
---------------------------------------------------------------------------

    \159\ Fair Lending/CRA Compass, (June 1999), p. 3.
    \160\ Randall M. Scheessele developed a list of 42 subprime 
lenders that was used by HUD and others in analyzing HMDA data 
through 1997. In 1998, Scheessele updated the list to 200 subprime 
lenders. For analysis comparing various lists of subprime lenders, 
see Appendix D of Scheessele (1999), op. cit. That paper also 
discusses Scheessele's lists of manufactured housing lenders.
---------------------------------------------------------------------------

b. Methods and Data for Measuring GSE Performance

    Several issues have arisen about the methods and the data used 
to measure the GSEs' performance relative to the characteristics of 
the mortgages being originated in the primary market. While most of 
these issues will be discussed throughout the appendices, one issue, 
the reliability of HMDA data in measuring GSE performance, needs to 
addressed before presenting the market comparisons, which utilize 
the HMDA data. Fannie Mae has raised questions about HUD's reliance 
on HMDA data for measuring its performance.
    There are two sources of loan-level information on the 
characteristics of mortgages purchased by the GSEs--the GSEs 
themselves and HMDA data. The GSEs provide detailed data on their 
mortgage purchases to HUD on an annual basis. As part of their 
annual HMDA reporting responsibilities, lenders are required to 
indicate whether their new mortgage originations or purchased loans 
are sold to Fannie Mae, Freddie Mac or some other entity. As 
discussed later, there have been numerous studies by HUD staff and 
other researchers that use the HMDA data to compare the borrower and 
neighborhood characteristics of loans sold to the GSEs with the 
characteristics of all loans originated in the market. The question 
is whether the HMDA data, which is widely available to the public, 
provides an accurate measure of GSE performance, as compared with 
the GSEs' own data.\161\ Fannie Mae has argued that HMDA data have 
understated its past performance, where performance is defined as 
the percentage of Fannie Mae's mortgage purchases accounted for by 
one of the goal-qualifying categories such as underserved areas. As 
explained below, HMDA provided reliable national-level information 
through 1997 on the GSEs' purchases of newly-originated loans but 
not on their purchases of prior-year loans. In 1998, HMDA data 
differed from data that the GSEs reported to HUD on their purchases 
of newly-originated loans.
---------------------------------------------------------------------------

    \161\ 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 Jim 
Berkovec and Peter Zorn. ``Measuring the Market: Easier Said than 
Done,'' Secondary Mortgage Markets. McLean VA: Freddie Mac (Winter 
1996), pp. 18-21.
---------------------------------------------------------------------------

    In any given calendar year, the GSEs can purchase mortgages 
originated in that calendar year or mortgages originated in a

[[Page 12700]]

prior calendar year. In 1997, purchases of prior-year mortgages 
accounted for 30 percent of the single-family units financed by 
Fannie Mae's mortgage purchases and 20 percent of the single-family 
units financed by Freddie Mac's mortgage purchases.\162\ HMDA data 
provides information mainly on newly-originated mortgages that are 
sold to the GSEs--that is, HMDA data on loans sold to the GSEs will 
not include many of their purchases of prior-year loans.\163\ The 
implications of this for measuring GSE performance can be seen in 
Tables A.3 and A.4a.\164\
---------------------------------------------------------------------------

    \162\ Since 1993, the GSEs have increased their purchases of 
seasoned loans. See Paul B. Manchester, Characteristics of Mortgages 
Purchased by Fannie Mae and Freddie Mac: 1996-1997 Update, Housing 
Finance Working Paper HF-006, Office of Policy Development and 
Research, Department of Housing and Urban Development, (August 
1998), p.17.
    \163\ For a discussion of the impact of the GSEs' seasoned 
mortgage purchases on HMDA data coverage, see Scheessele (1998), op. 
cit.
    \164\ Table A.4b, which reports similar GSE information as Table 
A.4a, provides several alternative estimates of the conventional 
conforming market depending on the treatment of small loans, 
manufactured housing loans, and subprime loans. The data in Table 
A.4b will be referenced throughout the discussion.
---------------------------------------------------------------------------

    Table A.3 summarizes affordable lending by the GSEs, 
depositories and the conforming market for the six-year period 
between 1993 and 1998 and for the borrower and census tract 
characteristics covered by the housing goals. The GSE percentages 
presented in Table A.3 are derived from the GSEs' own data that they 
provide to HUD, while the depository and market percentages are 
taken from HMDA data. Annual data on the borrower and census tract 
characteristics of GSE purchases are provided in Table A.4a. 
According to Fannie Mae's own data, 9.9 percent of its purchases 
during 1997 were loans for very low-income borrowers (see Table 
A.4a). According to HMDA data (also reported in Table A.4a), only 
8.8 percent of Fannie Mae's purchases were loans for very low-income 
borrowers.\165\ Thus, in this case the HMDA data underestimate the 
share of Fannie Mae's mortgage purchases for very low-income 
borrowers.
---------------------------------------------------------------------------

    \165\ Any HMDA data reported in the appendices on borrower 
incomes excludes loans where the loan-to-borrower-income ratio is 
greater than six.

BILLING CODE 4210-27-P

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    The reason that HMDA data underestimate those purchases can be 
seen by disaggregating Fannie Mae's purchases during 1997 into their 
``Prior Year'' and ``Current Year'' components. Table A.4a shows 
that the overall figure of 9.9 percent for very low-income borrowers 
is a weighted average of 13.4 percent for Fannie Mae's purchases 
during 1997 of ``Prior Year'' mortgages and 8.7 percent for its 
purchases of ``Current Year'' purchases. HMDA data report that 8.8 
percent of Fannie Mae's 1997 purchases consisted of loans to very 
low-income borrowers is based mainly on newly-mortgaged (current-
year originations) loans that lenders report they sold to Fannie 
Mae. Therefore, the HMDA data figure is similar in concept to the 
``Current Year'' percentage from the GSEs' own data. As Table A.4a 
shows, HMDA data and ``Current Year'' figures are practically the 
same in this case (about nine percent). Thus, the relatively large 
share of very low-income mortgages in Fannie Mae's 1997 purchases of 
``Prior Year'' mortgages is the primary reason why Fannie Mae's own 
data show an overall (both prior-year and current-year) percentage 
of very low-income loans that is higher than that reported in HMDA 
data.
    A review of the data in Table A.4a yields the following insights 
about the reliability of HMDA data at the national level for 
metropolitan areas. First, comparing the HMDA data on GSE purchases 
with the GSE ``Current Year'' data suggests that HMDA data provided 
reasonable estimates of the GSEs' current year purchases through 
1997.\166\ Second, the HMDA data percentages through 1997 are 
actually rather close to Freddie Mac's overall percentages because 
Freddie Mac's prior-year purchases often resembled their current-
year originations. Fannie Mae, on the other hand, was more apt to 
purchase seasoned loans with a relatively high percentage of low-
income loans, which means that HMDA data was more likely to 
underestimate its overall performance. However, this underestimation 
of the share of Fannie Mae's goal-qualifying loans in the HMDA data 
first arose in 1997, when Fannie Mae's purchases of prior-year loans 
were particularly targeted to affordable lending groups. For the 
years 1993 to 1996, Fannie Mae's prior-year loan purchases more 
closely resembled their current-year originations.
---------------------------------------------------------------------------

    \166\ For example, in 1997 Fannie Mae reported that 20.8 percent 
of the loans they purchased, that were originated during 1997, were 
for properties in underserved area. HMDA reports that 21.0 percent 
of the loans sold to Fannie Mae during 1997 were for properties in 
underserved areas. The corresponding numbers for Freddie Mac, in 
1997, are 19.3 percent reported by them and 18.6 percent reported by 
HMDA. During 1997, both Fannie Mae and HMDA reported that 
approximately 37 percent of the ``current year'' loans purchased by 
Fannie Mae were for low- and moderate-income borrowers. Freddie Mac 
reported that 34.2 percent of the current year loans they purchased 
were for low- and moderate-income borrowers, compared to the 35.4 
low-mod percent that HMDA reported as sold to Freddie Mac.
---------------------------------------------------------------------------

    Third, the 1998 data show that even the GSEs' ``Current Year'' 
data differ from the HMDA-reported data on GSE purchases. For 
example, special affordable loans accounted for 12.1 percent of 
Fannie Mae's current-year purchases in 1998 compared with only 10.7 
percent of Fannie Mae's special affordable purchases as reported by 
HMDA. Similarly, underserved areas accounted for 21.0 percent of 
Fannie Mae's current-year purchases compared with only 19.6 percent 
of Fannie Mae's underserved area purchases as reported by HMDA. The 
same patterns exist for Freddie Mac's 1998 data for the special 
affordable and underserved area categories. Thus, 1998 HMDA data do 
not provide a reliable estimate at the national level of the GSEs' 
purchases of current-year (newly-mortgaged) loans. More research on 
this issue is needed.
    The next section compares the GSE performance with that of the 
overall market. The fact that the GSE data includes prior-year as 
well as current-year loans, while the market data includes only 
current-year originations, means that the GSE-versus-market 
comparisons are defined somewhat inconsistently for any particular 
calendar year. Each year, the GSEs have newly-originated affordable 
loans available for purchase, but they can also purchase loans from 
a large stock of seasoned loans currently being held in the 
portfolios of depository lenders. Depository lenders have originated 
a large number of CRA-type loans over the past six years and many of 
them remain on their books. In fact, HUD has encouraged the GSEs to 
purchase seasoned, CRA-type loans that have demonstrated their 
creditworthiness. One method for making the data more consistent is 
to aggregate the data over several years, instead of focusing on 
annual data. This provides a clearer picture of the types of loans 
that have been originated and are available for purchase by the 
GSEs. This approach is taken in Table A.3.

c. Affordable Lending by the GSEs and the Primary Market

    Table A.3 summarizes goal-qualifying lending by the GSEs, 
depositories and the conforming market for the six-year period 
between 1993 and 1998 and for the more recent 1996-98 period, which 
covers the period since the most recent housing goals have been in 
effect. As noted above, the data are aggregated over time to provide 
a clearer picture of how the GSEs' purchases of both current-year 
and prior-year loans compare with the types of mortgages that have 
been originated during the past few years. All of the data are for 
home purchase mortgages in metropolitan areas. Several points stand 
out concerning the affordable lending performance of Freddie Mac and 
Fannie Mae.
    Freddie Mac. The data in Table A.3 show that Freddie Mac has 
substantially lagged both Fannie Mae and the primary market in 
funding affordable home loans. Between 1993 and 1998, 7.6 percent of 
Freddie Mac's mortgage purchases were for very low-income borrowers, 
compared with 9.2 percent of Fannie Mae's purchases, 14.5 percent of 
loans originated and retained by depositories, and 12.4 percent of 
loans originated in the conforming market (or 10.7 percent if 
manufactured home loans are excluded from the conforming market 
definition).\167\ As shown by the annual data reported in Table 
A.4a, Freddie Mac did improve its funding of very low-income 
borrowers during this period, from 6.0 percent in 1993 to 7.6 
percent in 1997, and then to 9.9 percent in 1998. However, Freddie 
Mac has not made as much progress as Fannie Mae (discussed below) in 
closing the gap between its performance and that of the overall 
market. During the 1996-98 period in which the new goals have been 
in effect, the ratio of Freddie Mac's average performance (8.4 
percent) to that of the overall market (13.0 percent) was only 0.65; 
this ``Freddie-Mac-to-market'' ratio remains at only 0.76 even when 
manufactured homes are excluded from the market definition.
---------------------------------------------------------------------------

    \167\ The borrower income distributions in Tables A.3 and A.4a 
for the ``market without manufactured housing'' exclude loans less 
than $15,000 as well as all loans originated by lenders that 
primarily originate manufactured housing loans. See Table A.4b for 
market definitions that show the separate effects of excluding small 
loans and manufactured housing loans.
---------------------------------------------------------------------------

    A similar conclusion about Freddie Mac's performance can be 
drawn for the other goal-qualifying categories presented in Tables 
A.3 and A.4a: Freddie Mac's performance has remained well below the 
market since 1993. For example, during the 1996-98 period when the 
new housing goals have been in effect, mortgages financing 
properties in underserved areas accounted for only 19.9 percent of 
Freddie Mac's purchases, compared with 22.9 percent of the loans 
purchased by Fannie Mae and 24.9 percent of the mortgages originated 
in the conforming market. Similarly, mortgages originated for low- 
and moderate-income borrowers represented 34.9 percent of Freddie 
Mac's purchases during this period, compared with 42.6 percent of 
all mortgages originated in the conforming market.
    One encouraging sign for Freddie Mac is that the borrower-income 
categories showed a rather large increase between 1997 and 1998. 
Special affordable (low-mod) loans increased from 9.0 (34.1) percent 
in 1997 to 11.3 (36.9) percent in 1998. The reasons for this 
increase require further study, but certainly, an interesting 
question going forward is whether Freddie Mac can continue this 
1997-98 pattern and thus further close its performance gap relative 
to the overall market. It is somewhat surprising that Freddie Mac's 
purchases of home loans in underserved areas did not increase (in 
percentage terms) between 1997 and 1998; as shown in Table A.4a, the 
underserved areas share of Freddie Mac's home loan purchases has 
remained constant at approximately 20 percent since 1994.
    Fannie Mae. The data in Table A.3 show that Fannie Mae has also 
lagged depositories and the primary market in the funding of homes 
for lower-income borrowers and underserved neighborhoods. Between 
1993 and 1998, 37.4 percent of Fannie Mae's purchases were for low- 
and moderate-income borrowers, compared with 43.6 percent of loans 
originated and retained by depositories and with 41.8 percent of 
loans originated in the primary market. Over the more recent 1996-98 
period, 22.9 percent of Fannie Mae's purchases financed properties 
in underserved neighborhoods, compared with 25.8 percent of loans 
originated by depositories and 24.9 percent of loans

[[Page 12705]]

originated in the conventional conforming market.
    However, Fannie Mae's affordable lending performance can be 
distinguished from Freddie Mac's. First, Fannie Mae has performed 
much better than Freddie Mac on every goal-category examined here. 
For example, home loans for special affordable loans accounted for 
13.2 percent of Fannie Mae's purchases in 1998, compared with only 
11.3 percent of Freddie Mac's purchases (see Table A.4a). In that 
same year, 22.9 percent of Fannie Mae's purchases were in 
underserved census tracts, compared with only 20.0 percent of 
Freddie Mac's purchases.
    Second, Fannie Mae has improved its performance over the past 
six years and has made more progress than Freddie Mac in closing the 
gap between its performance and the market's performance on the 
goal-qualifying categories examined here. In fact, Fannie Mae's 
performance is now close to that of the primary market for some 
important components of affordable lending. For example, in 1992, 
very low-income loans accounted for 5.2 percent of Fannie Mae's 
purchases and 8.7 percent of all loans originated in the conforming 
market, giving a ``Fannie Mae-to-market'' ratio of 0.60. By 1998, 
this ratio had risen to 0.86, as very low-income loans had increased 
to 11.4 percent of Fannie Mae's purchases and to 13.3 percent of 
market originations.
    A similar trend in market ratios can be observed for Fannie Mae 
on the underserved areas category. Fannie Mae has been improving its 
performance relative to the market; for example, the ``Fannie-Mae-
to-market'' ratio for underserved areas increased from 0.82 in 1992 
to 0.93 in 1998. This improved performance relative to the overall 
market by Fannie Mae is in sharp contrast to Freddie Mac's record--
the ``Freddie-Mac-to-market'' ratio for underserved areas actually 
declined, from 0.84 in 1992 to 0.81 in 1998. As a result, Fannie Mae 
has been approaching the home loan market in underserved areas while 
Freddie Mac has been losing ground relative to overall primary 
market.
    B&C Home Purchase Loans. As explained earlier, HMDA does not 
identify subprime loans, much less separate them into their A-minus 
and B&C components. Randall Scheessele at HUD has identified 200 
HMDA reporters that primarily originate subprime loans and probably 
accounted for at least half of the subprime market during 1998.\168\ 
As shown in Table A.4b, excluding the home purchase loans originated 
by these lenders from the primary market data has only minor effects 
on the goal-qualifying shares of the market. The average market 
percentages for 1998 are reduced as follows: low- and moderate-
income (43.0 to 42.6 percent); special affordable (15.5 to 15.2 
percent); and underserved areas (24.6 to 23.7 percent). As explained 
earlier, the effects are minor mostly because this analysis focuses 
on home purchase loans, which accounted for only 20 percent of the 
mortgages originated by these 200 subprime lenders-- the subprime 
market has been mainly a refinance market.
---------------------------------------------------------------------------

    \168\ See Scheessele (1999), op. cit. As explained in Appendix D 
of Scheessele's paper, the number of subprime lenders varies by 
year; the 200 figure cited in the text applies to 1998. The number 
of loans identified as subprime in these appendices is the same as 
reported by Scheessele in Table D.2b of his paper.
---------------------------------------------------------------------------

d. Prior-Year Loans

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

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

    The above sections have examined the GSEs' acquisitions of home 
purchase loans, which is appropriate given the importance of the 
GSEs for expanding homeownership opportunities. To provide a 
complete picture of the GSEs' mortgage purchases in metropolitan 
areas, this section briefly considers the GSEs' purchases of all 
single-family-owner mortgages, including both home purchase loans 
and refinance loans.\169\ Shifting the analysis to consider all 
(home purchase and refinance) mortgages does not change the basic 
finding that both GSEs lag the primary market in serving low-income 
borrowers and underserved neighborhoods. For example, in 1998 
underserved areas accounted for 21.2 (20.9) percent of Fannie Mae's 
(Freddie Mac's) purchases, compared to approximately 25.0 percent 
for both depository institutions and the overall primary market. 
Similarly, special affordable loans accounted for 11.1 (10.9) 
percent of Fannie Mae's (Freddie Mac's) purchases of single-family-
owner loans, compared to 14.9 percent for depository institutions 
and 14.3 percent for the overall primary market.
---------------------------------------------------------------------------

    \169\ Table A.1b in Section C.3.b provides several comparisons 
of the GSE's total purchases with primary market originations. As 
shown there, many of the same patterns described above for home 
purchase loans can be seen in the data for the GSEs' total 
purchases.
---------------------------------------------------------------------------

    There are two changes when one shifts the analysis from only 
home purchase loans to include all mortgages--one concerning the 
relative performance of Fannie Mae and Freddie Mac and one 
concerning the impact of subprime mortgages on the goals-qualifying 
percentages. These are discussed next.
    Fannie Mae versus Freddie Mac Performance. As indicated by the 
above percentages, the borrower-income comparisons between Fannie 
Mae and Freddie Mac change when the analysis switches from their 
acquisitions of only home purchase loans to their acquisitions of 
both home purchase and refinance loans. Consider the special 
affordable income category for 1997 and 1998. As shown in Table 
A.4a, special affordable loans accounted for a much higher 
percentage of Fannie Mae's acquisitions of home purchase loans than 
of Freddie Mac's in each of these two years. Similarly, in 1997, 
special affordable loans accounted for 11.5 percent of Fannie Mae's 
total (both home purchase and refinance) purchases, compared with 
9.9 percent of Freddie Mac's total purchases. However, between 1997 
and 1998, the special affordable percentage of Freddie Mac's total 
purchases increased from 9.9 percent to 10.9 percent, while the 
corresponding percentage for Fannie Mae actually declined from 11.5 
percent to 11.1 percent. Thus, in 1998, Freddie Mac's overall 
special affordable percentage (10.9 percent) was approximately the 
same as Fannie Mae's (11.1 percent).
    Further analysis shows that this improvement of Freddie Mac 
relative to Fannie Mae was due to Freddie Mac's better performance 
on refinance loans during 1998. The special affordable percentage of 
Fannie Mae's refinance loans fell from 11.1 percent in 1997 to 9.7 
percent in 1998, which is not surprising given that middle- and 
upper-income borrowers typically dominate heavy refinance markets 
such as 1998. But the special affordable percentage of Freddie Mac's 
refinance loans did not drop very much, falling from 11.3 percent in 
1997 to 10.7 percent in 1998.\170\ Thus, Freddie Mac's

[[Page 12706]]

higher special affordable percentage (10.7 percent versus 9.7 
percent for Fannie Mae) on refinance loans in 1998 enabled Freddie 
Mac to close the gap between its overall single-family performance 
and that of Fannie Mae.
---------------------------------------------------------------------------

    \170\ In general, the HMDA-reported affordability percentages 
for GSE purchases of refinance loans have matched the corresponding 
GSE-reported percentages. For example, in 1997, both GSEs reported 
to HUD that special affordable loans accounted for about 11 percent 
of their purchases of refinance loans in metropolitan areas; HMDA 
reported the same percentage for each GSE. Similarly, in 1998, both 
HMDA and Fannie Mae reported that special affordable loans accounted 
for 9.7 percent of Fannie Mae's refinance purchases. However, in 
1998, the Freddie-Mac-reported special affordable percentage (10.7 
percent) for its refinance loans was significantly higher than the 
corresponding percentage (9.5 percent) reported in the HMDA data. 
The reasons for this discrepancy require further study.
---------------------------------------------------------------------------

    The GSEs' underserved areas percentages followed a somewhat 
similar pattern as their special affordable percentages between 1997 
and 1998. In 1997, Freddie Mac's underserved area percentage (21.6 
percent) for total purchases was significantly less than Fannie 
Mae's (23.6), but in 1998, Freddie Mac's underserved areas 
percentage (20.9) was about the same as Fannie Mae's (21.2 percent). 
This convergence was mainly due to a sharper decline in Fannie Mae's 
underserved area percentage for refinance loans between 1997 and 
1998.
    B&C Loans. Section E.2.c showed that the estimates for the home 
purchase market did not change much when loans for subprime lenders 
were excluded from the HMDA analysis; the reason was that these 
lenders operate primarily in the refinance market. 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. For the year 1997, excluding subprime lenders 
reduced the goal-qualifying shares of the total market as follows: 
special affordable (from 16.3 to 14.8 percent); low-mod (from 43.6 
to 41.9 percent); and underserved areas (from 27.8 to 25.5 percent). 
Similarly, for the year 1998, excluding 200 subprime lenders reduced 
the goal-qualifying shares of the total market as follows: special 
affordable (from 14.3 to 12.7 percent); low-mod (from 41.0 to 39.0 
percent); and underserved areas (from 24.8 to 22.6 percent). As 
discussed earlier, the GSEs have been entering the subprime market 
over the past two years, particularly the A-minus portion of that 
market. Industry observers estimate that A-minus loans account for 
at least half of all subprime loans while the more risky B&C loans 
account for the remaining half. Thus, one proxy for excluding B&C 
loans originated by the 200 specialized lenders from the overall 
market benchmark might be to reduce the goal-qualifying percentages 
from the HMDA data by half the above differentials; accounting for 
B&C loans in this manner would reduce the 1998 HMDA-reported goal-
qualifying shares of the total conforming market as follows: special 
affordable (from 14.3 to 13.5 percent); low-mod (from 41.0 to 40.0 
percent); and underserved areas (from 24.8 to 23.7 percent). 
However, as discussed in Appendix D, much uncertainty exists about 
the size of the subprime market and its different components. More 
data and research are obviously needed on this growing sector of the 
mortgage market.\171\

f. GSE Mortgage Purchases in Individual Metropolitan Areas
---------------------------------------------------------------------------

    \171\ The Mortgage Information Corporation (MIC) has recently 
started publishing origination and default performance data for the 
subprime market. For an explanation of their data and some early 
findings, see Dan Feshbach and Michael Simpson, ``Tools for Boosting 
Portfolio Performance'', Mortgage Banking: The Magazine of Real 
Estate Finance, (October 1999), pp. 137-150.
---------------------------------------------------------------------------

    While the above analyses, as well as earlier studies,\172\ 
concentrate on national-level data, it is also instructive to 
compare the GSEs' purchases of mortgages in individual metropolitan 
areas (e.g. MSAs). In this section, the GSEs' purchases of single-
family owner-occupied home purchase loans are compared to the market 
in individual MSAs.\173\ To do so, total primary market mortgage 
originations from two years, 1995 and 1996, are summed up by year, 
by MSA, and for GSE purchases of these loans. The GSEs' purchases of 
1995 originations include all 1995 originations purchased by each 
GSE between 1995 and 1998 from 324 MSAs. For their purchases of 1996 
originations, all 1996 originations purchased between 1996 and 1998 
from 326 MSAs are included. This should cover 90 to 95 percent of 
the 1995 and 1996 originated loans that will be purchased by the 
GSEs, thus making the GSE data comparable to HMDA market data. The 
loans are then grouped by the GSE housing goal categories for which 
they qualify and the ratio of the housing goal category originations 
to total originations in each MSA is calculated for each GSE and the 
market. The GSE-to-market ratio is then calculated by dividing each 
GSE ratio by the corresponding market ratio. For example, if it is 
calculated that one of the GSEs' purchases of Low- and Moderate-
Income loans in a particular MSA is 47 percent of their overall 
purchases in that MSA, while 49 percent of all originations in that 
MSA are Low-Mod, then that GSE-to-market ratio is 47/49 (or 0.96).
---------------------------------------------------------------------------

    \172\ For example, see Bunce and Scheessele (1996 and 1998), op. 
cit.
    \173\ This analysis is limited to the conventional conforming 
market.
---------------------------------------------------------------------------

    Table A.5 shows the performance of the GSEs by MSA for 1995 and 
1996 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.\174\ For the above 
example, that GSE is considered to be lagging the market. These 
results are then summarized in Table A.5, which reports the number 
of MSAs in which each GSE under-performs the market with respect to 
the housing goal categories.
---------------------------------------------------------------------------

    \174\ This analysis was also conducted where the ``lag'' 
determination is made at 95 percent. The results are consistent with 
those shown in Table A.5. For example, at the 95 percent cutoff, 
Fannie Mae lagged the market in 275 MSAs (85 percent) in the 
purchase of 1995 originated Special Affordable category loans. 
Likewise, Freddie Mac lagged the market in 320 MSAs (99 percent).

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    For 1995 originations, Fannie Mae:
    (i) Lagged the market in 239 (74 percent) of the MSAs in the 
purchase of Underserved Area loans,
    (ii) Lagged the market in 264 (82 percent) of the MSAs in the 
purchase of Low- and Moderate-Income loans, and
    (iii) Lagged the market in 287 (89 percent) of the MSAs in the 
purchase of Special Affordable loans.
    Freddie Mac lagged the market to an even greater extent in 1995. 
Specifically, the market outperformed Freddie Mac in:
    (i) 300 (93 percent) of the MSAs in the purchase of Underserved 
Area loans,
    (ii) 319 (99 percent) of the MSAs in the purchase of Low- and 
Moderate-Income loans, and
    (iii) 321 (99 percent) of the MSAs in the purchase of Special 
Affordable loans.
    Thus Freddie Mac was behind Fannie Mae in at least three-
quarters of the MSAs for all three goal categories. As shown in 
Table A.5, the results for loans originated in 1996 are similar.

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

    Recent studies have raised questions about whether the lower-
income loans purchased by the GSEs are adequately meeting the needs 
of some lower-income families. In particular, the lack of funds for 
down payments is one of the main impediments to homeownership, 
particularly for many lower-income families who find it difficult to 
accumulate enough cash for a down payment. As this section explains, 
a noticeable pattern among lower-income loans purchased by the GSEs 
is the predominance of loans with high down payments.
    HUD's 1996 report to Congress on the possible privatization of 
Fannie Mae and Freddie Mac \175\ found, rather surprisingly, that 
the mortgages taken out by lower-income borrowers and purchased by 
the GSEs were as likely to have high down payments as the mortgages 
taken out by higher-income borrowers and purchased by the GSEs. For 
example, considering the GSEs' purchases of home purchase loans in 
1995, 58 percent of very low-income borrowers made a down payment of 
at least 20 percent, compared with less than 50 percent of borrowers 
from other groups. In addition, a surprisingly large percentage of 
the GSEs' first-time homebuyer loans had high down payments. In 
1995, 35 percent of Fannie Mae's and 41 percent of Freddie Mac's 
first-time homebuyer loans had down payments of 20 percent or more.
---------------------------------------------------------------------------

    \175\ Privatization of Fannie Mae and Freddie Mac: Desirability 
and Feasibility. Office of Policy Development and Research, 
Department of Housing and Urban Development, (July 1996).
---------------------------------------------------------------------------

    Table A.6 presents similar data for the GSEs purchases total 
loans during 1997. Over three-fourths of the GSEs very low-income 
loans had a down payment more than 20 percent. Essentially, the GSEs 
have been purchasing lower-income loans with large down 
payments.\176\
---------------------------------------------------------------------------

    \176\ The Treasury Department reached similar conclusions in its 
1996 report on the privatization of the GSEs, Government Sponsorship 
of the Federal National Mortgage Association and the Federal Home 
Loan Mortgage Corporation, U.S. Department of the Treasury (July 11, 
1996). Based on data such as the above, the Treasury Department 
questioned whether the GSEs were influencing the availability of 
affordable mortgages and suggested that the lower-income loans 
purchased by the GSEs would have been funded by private market 
entities if the GSEs had not purchased them.

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[[Page 12710]]

    The evidence is similar when the data are examined for each GSE 
separately. Between 1993 and 1997, 71 percent of all one-family 
owner-occupied loans bought by Fannie Mae, had an LTV less than or 
equal to 80 percent. Only 13 percent had an LTV greater than 90 
percent (one percent with LTVs greater than 95 percent). For Freddie 
Mac, 75 percent of loans bought had an LTV less than or equal to 80 
percent, while 10 percent had LTVs greater than 90 percent. Only 
one-eighth of one percent of Freddie Mac's loans had an LTV greater 
than 95 percent. For very low-income loans purchased by Fannie Mae, 
during the same period, 75 percent had a down payment greater than 
20 percent. Large down payment loans accounted for 82 percent of 
Freddie Mac's purchases of very-low income borrower loans. Thus, 
these results are consistent with previous studies that show that 
the proportion of large down payment loans purchased by the GSEs 
from lower-income borrowers is greater than that for all loans 
purchases.\177\
---------------------------------------------------------------------------

    \177\ See Glenn B. Canner, and Wayne Passmore. ``Credit Risk and 
the Provision of Mortgages to Lower-Income and Minority 
Homebuyers,'' Federal Reserve Bulletin. 81 (November 1995), pp. 989-
1016; Glenn B. Canner, Wayne Passmore and Brian J. Surette. 
``Distribution of Credit Risk among Providers of Mortgages to Lower-
Income and Minority Homebuyers.'' Federal Reserve Bulletin. 82 
(December 1996), pp. 1077-1102; Harold L. Bunce, and Randall M. 
Scheessele, The GSEs' Funding of Affordable Loans: A 1996 Update, 
Housing Finance Working Paper HF-005, Office of Policy Development 
and Research, Department of Housing and Urban Development, (July 
1998); and Manchester, (1998), p. 24.
---------------------------------------------------------------------------

    As discussed in Section C, Both Fannie Mae and Freddie Mac have 
introduced high-LTV products: ``Flexible 97'' and ``Alt 97'' 
respectively. By lowering the required down payment to three percent 
and adding flexibility to the source of the down payment, these 
loans should be more affordable. The down payment, as well as 
closing costs, can come from, gifts, grants or loans from a family 
member, the government, a non-profit agency and loans secured by 
life insurance policies, retirement accounts or other assets. 
However, in order to control default risk, these loans also have 
stricter credit history requirements.
    Fed Study. An important study by three economists--Glenn Canner, 
Wayne Passmore and Brian Surette \178\-- at the Federal Reserve 
Board showed the implications of the GSEs' focus on high down 
payment loans. Canner, Passmore, and Surette examined the degree to 
which different mortgage market institutions--the GSEs, FHA, 
depositories and private mortgage insurers--are taking on the credit 
risk associated with funding affordable mortgages. The authors 
combined market share and down payment data with data on projected 
foreclosure losses to arrive at an estimate of the credit risk 
assumed by each institution for each borrower group. This study 
found that Fannie Mae and Freddie Mac together provided only 4 to 5 
percent of the credit support for lower-income and minority 
borrowers and their neighborhoods. The relatively small role of the 
GSEs providing credit support is due to their low level of funding 
for these groups and to the fact that they purchase mainly high down 
payment loans. FHA, on the other hand, provided about two-thirds of 
the credit support for lower-income and minority borrowers, 
reflecting FHA's large market shares for these groups and the fact 
that most FHA-insured loans have less-than-five-percent down 
payments.
---------------------------------------------------------------------------

    \178\ Canner, et al. (1996).
---------------------------------------------------------------------------

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

    This section summarizes briefly the main findings from other 
studies of the GSEs' affordable housing performance. These include 
studies by the HUD and the GSEs as well as studies by academics and 
research organizations.

a. Studies by Bunce and Scheessele

    Harold Bunce and Randall Scheessele of the Department have 
published two studies of affordable lending. In December 1996, they 
published a study titled The GSEs' Funding of Affordable Loans.\179\ 
This report analyzed HMDA data for 1992-95, including a detailed 
comparison of the GSEs' purchases with originations in the primary 
market. In July 1998, they updated their earlier study to analyze 
the mortgage market and the GSEs' activities in 1996.\180\ The 
findings were largely similar in both studies: \181\
---------------------------------------------------------------------------

    \179\ Harold L. Bunce and Randall M. Scheessele, The GSEs' 
Funding of Affordable Loans, Housing Finance Working Paper HF-001, 
Office of Policy Development and Research, U.S. Department of 
Housing and Urban Development, (December 1996).
    \180\ Harold L. Bunce and Randall M. Scheessele, The GSEs' 
Funding of Affordable Loans: A 1996 Update, Housing Finance Working 
Paper HF-005, Office of Policy Development and Research, U.S. 
Department of Housing and Urban Development, (July 1998), pp. 15-16.
    \181\ Statistics cited are from Table B.1 of Bunce and 
Scheessele, (1998) and are based on sales to the GSEs as reported by 
lenders in accordance with the HMDA. ``Lagging the market'' means, 
for example, that the percentage of the GSEs' loans for very low- 
and low-income borrowers is less than the corresponding percentage 
for the primary market, depositories, and the FHA.
---------------------------------------------------------------------------

    (i) Both GSEs lagged the primary conventional market, 
depositories, and (particularly) FHA in funding mortgages for lower-
income and historically underserved borrowers. FHA stands out as the 
major funder of affordable loans. In 1996, approximately 30 percent 
of FHA-insured loans were for African-American and Hispanic 
borrowers, compared with only 10 percent of the loans purchased by 
the GSEs or originated in the conventional market.
    (ii) The two GSEs show very different patterns of lending--
Fannie Mae is much more likely than Freddie Mac to serve underserved 
borrowers and their neighborhoods. Since 1992, Fannie Mae has 
narrowed the gap between its affordable lending performance and that 
of the other lenders in the conforming market. Freddie Mac's 
improvement has been more mixed--in some cases it has improved 
slightly relative to the market but in other cases it has actually 
declined relative to the market. The findings with respect to 
Freddie Mac are similar to those discussed earlier in Section E.2.c.

b. Studies by Freddie Mac

    In 1995 Freddie Mac published Financing Homes for A Diverse 
America, which contained a wide variety of statistics and charts on 
the mortgage market. Several of the exhibits contained comparisons 
between the primary mortgage market and Freddie Mac's purchases in 
1993 and 1994:
    (i) While not asserting strict parity, this report presented 
comparable frequency distributions of primary market originations 
and Freddie Mac's purchases by borrower and census tract income, 
concluding that Freddie Mac ``finances housing for Americans of all 
incomes'' and it ``buys mortgages from neighborhoods of all 
incomes.''
    (ii) With regard to minority share of census tracts, the report 
stated that Freddie Mac's ``share of minority neighborhoods matches 
the primary market.''
    (iii) The report acknowledged that Freddie Mac's purchases did 
not match the primary market in terms of borrower race. It found 
that in 1994 African-Americans and Hispanics each accounted for 4.9 
percent of the primary market but only 2.7 percent and 4.0 percent 
respectively of Freddie Mac's purchases. On the other hand, Whites 
and Asian Americans accounted for 83.7 percent and 3.2 percent of 
the primary market, but 86.3 percent and 3.9 percent respectively of 
Freddie Mac's acquisitions.
    In its March 1998 Annual Housing Activities Report (AHAR) 
submitted to the Department and Congress, Freddie Mac presented data 
on this issue for 1996 and 1997. This report stated that its 
purchases ``essentially mirror[ed] the overall distribution of 
mortgage originations in terms of borrower income.'' However, the 
data underlying Exhibit 4 of the AHAR indicated that the share of 
Freddie Mac's 1997 purchases for borrowers with income (in 1996 
dollars) less than $40,000 was more than 4 percentage points below 
the corresponding share for the primary market in 1996. A similar 
pattern prevailed in terms of census tract income--the data 
underlying Exhibit 5 of the AHAR indicated that the share of Freddie 
Mac's 1997 purchases in tracts with income in excess of 120 percent 
of area median income exceeded the corresponding share for the 
primary market in 1996 by about 4 percentage points.
    In its March 1998 AHAR, Freddie Mac found a much closer match 
between the distributions of home purchase mortgages by down payment 
for Freddie Mac's 1997 acquisitions and the primary market in 1997, 
as the latter was reported by the Federal Housing Finance Board. 
Specifically, Exhibit 6 of the AHAR reported that 42 percent of 
borrowers in each category made down payments of less than 20 
percent.\182\
---------------------------------------------------------------------------

    \182\ Under their charter acts, loans purchased by the GSEs with 
down payments of less than 20 percent must carry private mortgage 
insurance or a comparable form of credit enhancement.
---------------------------------------------------------------------------

c. Studies by Fannie Mae

    Fannie Mae has not published any studies on the comparability of 
its mortgage purchases with the primary market. However, in an 
October 1998 briefing for

[[Page 12711]]

HUD staff, Fannie Mae presented the results of several comparisons 
of its purchases, based on the data supplied to the Department by 
Fannie Mae, with loans originated in the conventional conforming 
market, based on the HMDA data. In these analyses, Fannie Mae stated 
that:
    (i) The percentage of Fannie Mae's home purchase loans serving 
minorities exceeded the corresponding percentage in the conventional 
conforming market by 2.6 percentage points in 1995, 2.0 percentage 
points in 1996, and 2.7 percentage points (18.6 percent vs. 15.9 
percent) in 1997;
    (ii) The percentage of Fannie Mae's home purchase loans for low- 
and moderate-income households exceeded the corresponding percentage 
in the conventional conforming market by 0.2 percentage point in 
1995, fell 0.1 percentage point short of the market in 1996, but 
exceeded it again, by 1.2 percentage points (38.5 percent vs. 37.3 
percent), in 1997;
    (iii) The percentage of Fannie Mae's home purchase loans for 
households in underserved areas fell 0.04 percentage point short of 
the conventional conforming market in 1996, but exceeded the 
corresponding percentage in the conventional conforming market by 
1.4 percentage points (25.5 percent vs. 24.1 percent) in 1997;
    (iv) The percentage of Fannie Mae's home purchase loans for very 
low-income households and low-income households in low-income areas 
fell 1.0 percentage point short of the of the conventional 
conforming market in 1995 and 0.9 percentage point short in 1996, 
but exceeded the corresponding percentage in the conventional 
conforming market by 2.2 percentage points (12.7 percent vs. 10.5 
percent) in 1997.
    Some of these findings by Fannie Mae differ from those of other 
researchers. This is due in part to the fact that most other studies 
have utilized HMDA data for both the primary market and sales to the 
GSEs, but Fannie Mae compared the primary market, based on HMDA 
data, with the patterns in the GSE loan-level data submitted to the 
Department.\183\ \184\
---------------------------------------------------------------------------

    \183\ It is generally agreed that HMDA does not capture all 
loans originated in the primary market--for example, small lenders 
need not report under HMDA. But Fannie Mae believes that the 
undercount is not spread uniformly across all borrower classes--in 
particular, it argues that the HMDA data exclude relatively more 
loans made to minorities and lower-income families.
    \184\ Bunce and Scheessele (1998) contained a comparison (Table 
A.1) of HMDA-reported and GSE-reported data on the characteristics 
of GSE mortgage purchases in 1996. In most cases the differences 
between the results utilizing the two different data sources were 
minimal, but in some cases (such as lending in underserved areas) 
the evidence lent some support to Fannie Mae's assertion that the 
HMDA data underreports their level of activity. The discrepancies 
between HMDA data and GSE data at the national level are also due to 
the seasoned loan effect (see Section E.2.e above and Table A.4a).
---------------------------------------------------------------------------

d. Other Studies

    Lind. John Lind examines HMDA data in order to compare the GSEs' 
loan purchase activity to mortgage originations in the primary 
conventional conforming market.\185\ Like other studies, Lind 
presents an aggregate comparison of GSE/primary market 
correspondence for Black, Hispanic, low-income borrowers, and low- 
and moderate-income Census tracts. Unlike other studies, however, 
Lind also examines market correspondence at the individual 
metropolitan area and regional levels.
---------------------------------------------------------------------------

    \185\ John E. Lind. Community Reinvestment and Equal Credit 
Opportunity Performance of Fannie Mae and Freddie Mac from the 1994 
HMDA Data. San Francisco: Caniccor. Report, (February 1996).
---------------------------------------------------------------------------

    Lind finds that the GSEs are not leading the market, but that 
Fannie Mae, in particular, improved its performance between 1993 and 
1994. In 1994, Lind finds that the shares of Fannie Mae's home 
purchase loans to minority and low-income borrowers were comparable 
to the industry's shares. But the share of its home purchase loans 
for low- and moderate-income census tracts and the shares of Freddie 
Mac's home purchase loans for all categories examined trailed those 
for the industry as a whole. For refinance mortgages, on the other 
hand, both GSEs trailed the industry in terms of the shares of their 
loans for the groups analyzed. In a subsequent study, Lind found 
that the difference between the affordable lending performance of 
Fannie Mae and Freddie Mac was caused by differences in policy and 
operating procedures of the GSEs, and not differences in the make-up 
of their suppliers of loans.\186\
---------------------------------------------------------------------------

    \186\ John E. Lind. A Comparison of the Community Reinvestment 
and Equal Credit Opportunity Performance of Fannie Mae and Freddie 
Mac Portfolios by Supplier from the 1994 HMDA Data. San Francisco: 
Cannicor. Report, (April 1996).
---------------------------------------------------------------------------

    Ambrose and Pennington-Cross. There exists a wide variation in 
the market shares of the GSEs, FHA and portfolio lenders across 
geographic mortgage markets. Brent Ambrose and Anthony Pennington-
Cross analyze FHA, GSE and portfolio lender market shares to find 
insights into what factors affect the market shares for FHA eligible 
(under the FHA loan limit) loans.\187\ They hypothesize that the 
GSEs try to mitigate higher perceived risks at the MSA level by 
tightening lending standards, generating a prediction of higher FHA 
market share in locations with characteristically higher or 
dynamically worsening risk. A second hypothesis is that market share 
of portfolio lenders increases in areas with higher risk due to 
``reputation effects'' and GSE repurchase requirements. In their 
model, they account for cyclical risk, permanent risk, demographic, 
lender and regional differences.
---------------------------------------------------------------------------

    \187\ Brent W. Ambrose and Anthony Pennington-Cross, Spatial 
Variation in Lender Market Shares, Research Study submitted to the 
Office of Policy Development and Research, Department of Housing and 
Urban Development, (1999).
---------------------------------------------------------------------------

    Ambrose and Pennington-Cross found that the GSEs exhibit risk 
averse behavior as evidenced by lower GSE market presence in MSAs 
experiencing increasing risk and in MSAs that historically exhibit 
high-risk tendencies. FHA market shares, in contrast, are associated 
with high or deteriorating risk conditions. Portfolio lenders 
increase their mortgage portfolios during periods of economic 
distress, but increase the sale of originations out of portfolio 
during periods of increasing house prices. Lenders in MSAs with 
historically high delinquency hold more loans in portfolio. MSA risk 
is therefore concentrated among portfolio lenders and in FHA, with 
the GSEs bearing relatively little credit risk of this kind. The 
study does find that, other things being equal, the GSEs do have a 
higher presence in underserved areas and in areas where the minority 
population is highly segregated.
    MacDonald (1998). Heather MacDonald \188\ examined the impact of 
the central city housing goal from HUD's 1993-1995 interim housing 
goals. Census tracts were clustered according to five variables 
(median house value, median house age, proportion of renters, 
percent minority and proportion of 2 to 4 units) argued to impede 
secondary market purchases of homes in some neighborhoods. Borrower 
characteristics and lending patterns were compared across the 
clusters of tracts, and across central city and suburban tracts. 
Clustered tracts were found to be more strongly related to a set of 
key lending variables than are tracts divided according to central 
city/suburban boundaries. MacDonald concludes that targeting 
affirmative lending requirements on the basis of neighborhood 
characteristics rather than political or statistical divisions may 
provide a more appropriate framework for efforts to expand access to 
credit.
---------------------------------------------------------------------------

    \188\ Heather MacDonald. ``Expanding Access to the Secondary 
Mortgage Markets: The Role of Central City Lending Goals,'' Growth 
and Change. (27), (1998), pp. 298-312.
---------------------------------------------------------------------------

    MacDonald (1999). In a 1999 study, Heather MacDonald 
investigated variations in GSE market share among a sample of 426 
nonmetropolitan counties in eight census divisions.\189\ 
Conventional conforming mortgage originations were estimated using 
residential sales data, adjusted to exclude government-insured and 
nonconforming loans. Multivariate analysis was used to investigate 
whether GSE market shares differed significantly by location, after 
controlling for the economic, demographic, housing stock and credit 
market differences among counties that could affect use of the 
secondary markets. The study also investigated whether there were 
significant differences between the nonmetropolitan borrowers served 
by Fannie Mae and those served by Freddie Mac.
---------------------------------------------------------------------------

    \189\ Heather MacDonald, Fannie Mae and Freddie Mac in Non-
metropolitan Housing Markets: Does Space Matter, Research Study 
submitted to the Office of Policy Development and Research, 
Department of Housing and Urban Development, (1999).
---------------------------------------------------------------------------

    MacDonald found that space contributes significantly to 
explaining variations in GSE market shares among nonmetropolitan 
counties, but its effects are quite specific. One region--non-
adjacent West North Central counties--had significantly lower GSE 
market shares than all others. The disparity persisted when analysis 
was restricted to underserved counties only. The

[[Page 12712]]

study also suggested significant disparities between the income 
levels of the borrowers served by each agency, with Freddie Mac 
buying loans from borrowers with higher incomes than the incomes of 
borrowers served by Fannie Mae. An important limitation on any study 
of nonmetropolitan mortgages was found to be the lack of Home 
Mortgage Disclosure Act data. This meant that more precise 
conclusions about the extent to which the GSEs mirror primary 
mortgage originations in nometropolitan areas could not be reached.
    McClure. Kirk McClure examined the twin mandates of FHEFSSA: To 
direct mortgage credit to neighborhoods that have been underserved 
by mortgage lenders; and to direct mortgage credit to low-income and 
minority households.\190\ Using the Kansas City metropolitan area as 
a case study, mortgages purchased by the GSEs in 1993-96 were 
compared with mortgages held by portfolio lenders in order to 
determine the performance of the GSEs in serving these two 
objectives. Kansas City provides a useful case study area for this 
analysis, because it includes a range of weak and strong housing 
market areas where homebuyers have been able to move easily to serve 
their housing, employment, and neighborhood needs.
---------------------------------------------------------------------------

    \190\ Kirk McClure, The Twin Mandates Given to the GSEs: Which 
Works Best, Helping Low-Income Homebuyers or Helping Underserved 
Areas in the Kansas City Metropolitan Area? Research Study submitted 
to the Office of Policy Development and Research, Department of 
Housing and Urban Development, (1999).
---------------------------------------------------------------------------

    McClure found that borrowers are better served if credit is 
directed to them independent of location. Very low-income and 
minority borrowers fared better, in terms of the demographic, 
housing, and employment opportunities of the neighborhoods into 
which they located, than borrowers in underserved neighborhoods, 
suggesting that directing credit to low-income and minority 
households has had the desired effect of helping these households 
purchase homes in areas where they would find good homes and good 
employment prospects. According to McClure, HUD's 1996-99 housing 
goals defined underserved tracts very broadly, such that nearly one-
half of the tracts in the Kansas City area are categorized as 
underserved. Because the definition of underserved is so broad, 
directing credit to these tracts means only increasing the flow of 
mortgage credit to the lesser one-half of all tracts, which includes 
many areas with stable housing stocks and viable job markets. The 
alternative approach of directing credit to underserved areas was 
found to be helpful only insofar as it has helped direct credit to 
neighborhoods with slightly lower household income levels and higher 
incidence of minorities than found elsewhere in the metropolitan 
area. McClure concluded that neighborhoods that receive very low 
levels of mortgage credit seemed to provide insufficient housing or 
employment opportunities to justify the effort that would be 
required to direct additional mortgage credit to them.
    McClure concluded that whatever the approach, the GSEs have not 
been performing as well as the primary credit lenders in the Kansas 
City metropolitan area. In terms of helping underserved areas, the 
GSEs lagged behind the industry in the proportion of loans found in 
these areas. In terms of helping low-income and minority borrowers, 
the GSEs also lagged behind the industry. However, to the extent 
that the GSEs served these targeted populations, these households 
used this credit to move to neighborhoods with better housing and 
employment opportunities than were generally present in the 
underserved areas.
    Williams.\191\ This study looks at mortgage lending in 
underserved markets in the primary and secondary mortgage markets 
for the MSAs in Indiana. A more extensive analysis is provided for 
South Bend/St. Joseph County, Indiana that looks at the GSE 
purchases in underserved markets by type of primary market lender in 
both 1992 and 1996. It shows the percentage of loans bought by the 
GSEs and the loan they did not buy. This study found that the GSEs 
were more aggressive in closing the gap in St. Joseph County than in 
other MSAs in Indiana. It also found that Fannie Mae's underserved 
market performance was slightly better than Freddie Mac's 
performance.
---------------------------------------------------------------------------

    \191\ Richard Williams, ``The Effect of GSEs, CRA, and 
Institutional Characteristics on Home Mortgage Lending to 
Underserved Markets,'' Research Study submitted to the Office of 
Policy Development and Research, Department of Housing and Urban 
Development, 1999).
---------------------------------------------------------------------------

    Williams compared the GSEs performance in underserved markets 
and CRA institutions between 1992 and 1995. It shows that the GSEs 
have narrowed the gap between themselves and lenders while CRA 
institutions have lost ground relative to non-CRA lenders. A pattern 
observed across all Indiana MSAs is that the GSEs do not appear to 
lead the market but rather almost perfectly mirrored the performance 
of mortgage companies.
    Williams looked at the impact of size and location of lenders on 
the home mortgage market. Large lenders were more likely to finance 
mortgages for very low-income and African American borrowers than 
smaller lenders. Lenders headquartered in Indiana were more likely 
to purchase mortgages in underserved areas than lenders who only had 
branches or no apparent physical presence in Indiana. This suggests 
that served markets might benefit more than underserved areas from 
increased competition from non-local lenders.
    Gyourko and Hu. This study focuses on the GSEs' housing goals 
looking at the intra-metropolitan distribution of mortgage 
acquisitions by Fannie Mae and Freddie Mac and the spatial 
distribution of households within 22 MSAs.\192\ The data on the 
GSEs' mortgage purchases is provided by the Census Tract File of 
Public Use Data Base and data on households is provided by the 1990 
census. The study found that the distribution of goal-qualifying 
loan purchases by the GSEs does not match the distribution of goal-
qualifying households. On average 44 percent of Low- and Moderate-
Income Goal and 46 percent of Special Affordable Goal qualifying 
households are located in central cities. This compares to the GSEs' 
mortgage purchases where 26 percent of Low- and Moderate-Income Goal 
and 36 percent of Special Affordable Goal were located in central 
cities.
---------------------------------------------------------------------------

    \192\ Joseph Gyourko and Dapeng Hu. The Spatial Distribution of 
Secondary Market Purchases in Support of Affordable Lending, 
Research Study submitted to the Office of Policy Development and 
Research, Department of Housing and Urban Development, (1999).
---------------------------------------------------------------------------

    This study develops criteria for evaluating the GSEs' mortgage 
purchasing performance in census tracts. The first measure is a 
ratio. The numerator of the ratio is the share of the GSEs' mortgage 
purchases that qualify for the Special Affordable Housing Goal in 
the census tract. The denominator is the share of households that 
are targeted by the Special Affordable Housing Goal in the census 
tract. A ratio is also computed for the Low- and Moderate-Income 
Housing Goal. If the ratio is less than 0.80 then the census tract 
is called under-represented, meaning that the share of the GSEs' 
mortgage purchases which qualify for the housing goal is less than 
80 percent of the share of the households that the goal targets. The 
analysis of these ratios shows that: (1) Central cities are more 
likely to be under-represented in terms of the share of affordable 
loans purchased by the GSEs, (2) in suburbs, the larger the census 
tracts' percent minority the greater the probability that affordable 
loan purchases are under-represented, and (3) the higher the tract's 
median income, the greater the likelihood that census tract is over-
represented.
    Gyourko and Hu's results are broadly consistent across the 22 
MSAs analyzed; however, some noteworthy exceptions are made. In a 
few MSAs, particularly Miami and New York, the mismatch of 
affordable GSE purchases to affordable households is much less 
severe. In Boston, Los Angeles and New York, census tracts with 
higher relative median incomes are more likely to be under-
represented.

4. GSEs' Underwriting Guidelines

    Most studies on affordability of mortgage loans are quantitative 
using HMDA data, HUD's GSE Public Use Database or some other related 
database. To complement these studies, HUD commissioned a study by 
the Urban Institute (UI) to examine recent trends in the GSEs' 
underwriting criteria and to seek attitudes and opinions of informed 
players in four local mortgage market markets (Boston, Detroit, 
Miami and Seattle).\193\ Interviews were conducted with mortgage 
lenders, community advocates and local government officials--all 
local actors who would be knowledgeable about the impact of the 
GSEs' underwriting policies on their ability to fund affordable 
loans for lower-income borrowers.
---------------------------------------------------------------------------

    \193\ Kenneth Temkin, Roberto Quercia, George Galster and Sheila 
O'Leary. A Study of the GSE's Single Family Underwriting Guidelines: 
Final Report. Washington DC: U.S. Department of Housing and Urban 
Development, (April 1999).
---------------------------------------------------------------------------

    The UI report reveals three major trends in the GSEs' 
underwriting that affects affordable lending. These include 
increased flexibility in standard \194\ underwriting and appraisal 
guidelines, the introduction of affordable lending products, and the 
introduction of

[[Page 12713]]

automated underwriting and credit scores in the loan application 
process. Through these trends, Fannie Mae and Freddie Mac have 
attempted to increase their capacity to serve low- and moderate-
income homebuyers. They are also eliminating practices that could 
potentially have had disparate impacts on minority homebuyers. While 
both GSEs have made progress, ``most [of those interviewed] thought 
Fannie Mae has been more aggressive than Freddie Mac in outreach 
efforts, implementing underwriting changes and developing new 
products.'' \195\
---------------------------------------------------------------------------

    \194\ Standard guidelines refer to guidelines not associated 
with affordable lending programs.
    \195\ Temkin, et al. (1999), p. 4.
---------------------------------------------------------------------------

    While the GSEs improved their ability to serve low- and 
moderate-income borrowers, it does not appear that they have gone as 
far as some primary lenders to serve these borrowers and to minimize 
the disproportionate effects on minority borrowers. From previous 
published analyses of the GSEs' mortgage purchases, differences 
between the income characteristics and racial composition of 
borrowers served by the primary mortgage market and the purchase 
activity of the GSEs were found. ``This means that the GSEs are not 
serving lower-income and minority borrowers to the extent these 
families receive mortgages from primary lenders.'' \196\ From UI's 
discussions with lenders, it was revealed that primary lenders are 
originating mortgages to lower-income borrowers using underwriting 
guidelines that allow lower down payments, higher debt-to-income 
ratios and poorer credit histories than allowed by the GSEs' 
guidelines. These mortgages are originated to a greater extent to 
minority borrowers who have lower incomes and wealth. From this 
evidence, UI concludes that the GSEs appear to be lagging the market 
in servicing low- and moderate-income and minority borrowers.
---------------------------------------------------------------------------

    \196\ Temkin, et al. (1999), p. 5.
---------------------------------------------------------------------------

    Furthermore, UI found ``that the GSEs'' efforts to increase 
underwriting flexibility and outreach has been noticed and is 
applauded by lenders and community advocates. Despite the GSEs' 
efforts in recent years to review and revise their underwriting 
criteria, however, they could do more to serve low- and moderate-
income borrowers and to minimize disproportionate effects on 
minorities. Moreover, the use of automated underwriting systems and 
credit scores may place lower-income borrowers at a disadvantage 
when applying for a loan, even though they are acceptable credit 
risks.'' \197\
---------------------------------------------------------------------------

    \197\ Temkin, et al. (1999), p. 28.
---------------------------------------------------------------------------

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

    Single-family rental housing is an important part of the housing 
stock because it is an important source of housing for lower-income 
households. Based on the 1995 American Housing Survey, 62 percent of 
all rental units are in structures with fewer than five units and 
approximately 57 percent of the stock of single-family rental units 
are affordable to very-low income families (i.e., families earning 
60 percent or less of the area median income). Of the GSEs' mortgage 
purchases in 1997, around 34 percent of the single-family rental 
units financed were affordable to very-low income households.
    While single-family rental properties are a large segment of the 
rental stock for low-income families, they make up a small portion 
of the GSEs' overall business. In 1997, Fannie Mae and Freddie Mac 
purchased more than $11 billion in mortgages for these properties. 
These purchases represented 4 percent of the total dollar amount of 
their overall 1997 business.
    It follows that since single-family rentals make up such a small 
part of the GSEs business, they have not penetrated the single-
family rental market to the same degree that they have penetrated 
the owner-occupant market. Table A.7 in Section G shows that in 1997 
the GSEs financed 49 percent of owner-occupied dwelling units but 
only 13 percent of single-family rental units.
    There are a number of factors that have limited the development 
of the secondary market for single-family rental property mortgages 
thus explaining the lack of penetration by the GSEs. Little is 
collectively known about these properties as a result of the wide 
spatial dispersion of properties and owners, as well as a wide 
diversity of characteristics across properties and individuality of 
owners. This makes it difficult for lenders to properly evaluate the 
probability of default and severity of loss for these properties.
    Single-family rental properties are important for the GSEs 
housing goals, especially for meeting the needs of lower-income 
families. In 1997 around 70 percent of single-family rental units 
qualified for the Low-and Moderate-Income Goals, compared with 35 
percent of one-family owner-occupied properties. This heavy focus on 
lower-income families meant that single-family rental properties 
accounted for 10 percent of the units qualifying for the Low-and 
Moderate-Income Goal, even though they accounted for only 7 percent 
of the total units (single-family and multifamily) financed by the 
GSEs. Single-family rental properties account for 12 percent of the 
geographically-targeted and 13 percent of the special affordable 
housing goals.
    A comparison of the GSEs' single-family rental and one-family 
owner-occupied mortgage purchases reveals the following broad 
patterns of borrower and neighborhood characteristics. Borrowers for 
single-family rental properties are more likely to be minorities 
than borrowers for one-family owner-occupied properties. Mortgages 
purchased by the GSEs for single-family rental properties compared 
with one-family owner-occupied properties are more likely to be 
located in lower-income and higher minority neighborhoods. More 
single-family rental than one-family owner-occupied mortgages were 
refinance or prior-year loans.
    A closer look at borrower characteristics for single-family 
rental properties shows the following. First, based on ethnic/racial 
characteristics, borrowers for investor-owned properties are similar 
to borrowers for one-family owner-occupied properties. Second, 
borrowers for single-family rental properties, especially owner-
occupied 2- to 4-unit properties, are more likely to be nonwhite 
than are borrowers for one-family owner-occupied and investor-owned 
properties. About 37 percent of the borrowers for owner-occupied 2- 
to 4-unit properties are non-white compared with around 16 percent 
for both one-family and investor-owned properties. For one-family 
owner-occupied and investor-owned properties about 5 percent of 
borrowers are African American, compared with 9 percent for owner-
occupied 2- to 4-unit properties. A similar comparison applies for 
Hispanic borrowers, 6 percent and 16 percent respectively.
    With regard to neighborhood characteristics, a comparison of 
units in different types of rental properties purchased by the GSEs 
shows that investor 1-unit properties were more likely to be located 
in higher-income and lower-minority neighborhoods than were units in 
2- to 4-unit rental properties. For units in investor 1-unit 
properties, about 19 percent were in low-income neighborhoods, 
compared with 34 percent from units in 2- to 4-unit rental 
properties. About 25 percent of investor 1-unit properties were in 
high-minority neighborhoods, compared with 36 percent for units in 
2- to 4-unit rental properties. Units in 2- to 4-unit rental 
properties were commonly located in older cities where many low-
income and high-minority neighborhoods are located. Investor 1-unit 
properties were more characteristic of suburban neighborhoods where 
smaller populations of minorities and higher income households 
reside.
    The GSEs can mitigate risk by purchasing mortgages which are 
seasoned or refinanced. The data show that mortgages on properties 
with additional risk components such as being investor-owned, in 
low-income neighborhoods, and /or in high-minority neighborhoods are 
more likely to be seasoned or refinanced. For the GSEs' mortgage 
purchases, in general, mortgages on investor-owned properties are 
more likely to be prior-year than mortgages on owner-occupied 2- to 
4-unit properties (based on unit counts). These patterns are 
consistent with the notion that investor properties are more risky 
than owner-occupied 2- to 4-unit properties.

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

    The Department estimates that dwelling units serving low-and 
moderate-income families will account for 50-55 percent of total 
units financed in the overall conventional conforming mortgage 
market during 2000-2003, the period for which the Low-and Moderate-
Income Housing Goals are hereby established. Due to uncertainty 
about future market conditions, HUD has provided a plausible range, 
rather than a point estimate, for the market. 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

[[Page 12714]]

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].'' \198\
---------------------------------------------------------------------------

    \198\ 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 other lenders 
in funding lower-income borrowers and their communities. As required 
by FHEFSSA, the Department has produced estimates of the portion of 
the total (single-family and multifamily) mortgage market that 
qualifies for each of the three housing goals (see Appendix D). 
Congress intended that the Department use these market estimates as 
one factor in setting the percentage target for each of the housing 
goals. The Department's estimate for the size of the Low-and 
Moderate-Income market is 50-55 percent, which is substantially 
higher than the GSEs' performance on that goal.
    This section provides another perspective on the GSEs' 
performance by examining the share of the total mortgage market and 
the share of the goal-qualifying markets (low-mod, special 
affordable, and underserved areas) accounted for by the GSEs' 
purchases. This analysis, which is conducted by product type 
(single-family owner, single-family rental, and multifamily), shows 
the relative importance of the GSEs in each of the goal-qualifying 
markets.

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

    Table A.7 compares GSE mortgage purchases with HUD's estimates 
of the numbers of units financed in the conventional conforming 
market during 1997.\199\ HUD estimates that there were 7,443,736 
owner and rental units financed by new mortgages in 1997. Fannie 
Mae's and Freddie Mac's mortgage purchases financed 2,893,046 
dwelling units, or 39 percent of all dwelling units financed. As 
shown in Table A.7, the GSEs play a much smaller role in the goals-
qualifying markets than they do in the overall market. During 1997, 
new mortgages were originated for 4,290,860 dwelling units that 
qualified for the low-and moderate-income goal; the GSEs low-mod 
purchases financed 1,305,505 dwelling units, or only 30 percent of 
the low-mod market. Similarly, the GSEs' purchases accounted for 
only 24 percent of the special affordable market and 33 percent of 
the underserved areas market.\200\ Obviously, the GSEs are not 
leading the industry in financing units that qualify for the three 
housing goals.
---------------------------------------------------------------------------

    \199\ Table A.7 considers GSE purchases during 1997 and 1998 of 
conventional mortgages that were originated in 1997. HUD's 
methodology for deriving the 1997 market estimations is explained in 
Appendix D. B&C loans have been excluded from the market estimates 
in Table A.7.
    \200\ Two caveats about the data in Table A.7 should be 
mentioned here. First, the various market totals for underserved 
areas are probably understated due to the model's underestimation of 
mortgage activity in non-metropolitan underserved counties and of 
manufactured housing originations in non-metropolitan areas. Second, 
as discussed in Appendix D, some uncertainty exists around the 
adjustment for B&C single-family owner loans.

BILLING CODE 4210-27-P

[[Page 12715]]

[GRAPHIC] [TIFF OMITTED] TP09MR00.016


BILLING CODE 4210-27-C

[[Page 12716]]

    While the GSEs are free to meet the Department's goals in any 
manner that they deem appropriate, it is useful to consider their 
performance relative to the industry by property type. As shown in 
Table A.7, the GSEs accounted for 49 percent of the single-family 
owner market in 1997 but only 22 percent of the multifamily market 
and 13 percent of the single-family rental market (or a combined 
share of 19 percent of the rental market).
    Single Family Owner Market. This market is the bread-and-butter 
of the GSEs' business, and based on the financial and other factors 
discussed below, they clearly have the ability to lead the primary 
market in providing credit for low- and moderate-income owners of 
single-family properties. However, the GSEs have been lagging behind 
the market in their funding of single-family owner loans that 
qualify for the housing goals, as discussed in Section E.2.c. 
Between 1996 and 1998, low- and moderate-income borrowers accounted 
for 34.9 percent of Freddie Mac's mortgage purchases and 38.4 
percent of Fannie Mae's mortgage purchases, but 42.6 percent of 
primary market originations in metropolitan areas. The market share 
data reported in Table A.7 for the single-family owner market tell 
the same story. The GSEs' purchases of single-family owner loans 
represented 49 percent of all newly-originated owner loans in 1997, 
but only 43 percent of the low-mod loans that were originated, 35 
percent of the special affordable loans, and 48 percent of the 
underserved area loans. Thus, the GSEs need to improve their 
performance and it appears that there is ample room in the non-GSE 
portions of the goals-qualifying markets for them to do so. For 
instance, the GSEs are not involved in almost two-thirds of special 
affordable owner market.
    Single Family Rental Market. Single-family rental housing is a 
major source of low- and moderate-income housing. As discussed in 
Appendix D, data on the size of the primary market for mortgages on 
these properties is limited, but information from the American 
Housing Survey on the stock of such units and plausible rates of 
refinancing indicate that the GSEs are much less active in this 
market than in the single-family owner market. As shown in Table 
A.7, HUD estimates that the GSEs' purchases have totaled only 13 
percent of newly-mortgaged single-family rental units that were 
affordable to low- and moderate-income families.
    Many of these properties are ``mom-and-pop'' operations, which 
may not follow financing procedures consistent with the GSEs' 
guidelines. Much of the financing needed in this area is for 
rehabilitation loans on 2-4 unit properties in older areas, a market 
in which the GSEs' have not played a major role. However, this 
sector could certainly benefit from an enhanced role by the GSEs, 
and the Department believes that there is room for such an enhanced 
role.
    Multifamily Market. Fannie Mae is the largest single source of 
multifamily finance in the United States, and Freddie Mac has made a 
solid reentry into this market over the last five years. However, 
there are a number of measures by which the GSEs lag the multifamily 
market. For example, the share of GSE resources committed to the 
multifamily purchases falls short of the multifamily proportion 
prevailing in the overall mortgage market. HUD estimates that newly-
mortgaged units in multifamily properties represented 18 percent all 
(single-family and multifamily) dwelling units financed during 1997. 
\201\ By comparison, multifamily acquisitions represented 13 percent 
all units backing Fannie Mae's 1997 mortgage purchases, with a 
corresponding figure of only 8 percent for Freddie Mac. \202\ \203\ 
In other words, the GSEs place more emphasis on single-family 
mortgages than they do on multifamily mortgages.
---------------------------------------------------------------------------

    \201\ Table A.7 shows that multifamily represented 20 percent of 
total units financed during 1997 (obtained by dividing 1,491,990 
multifamily units by 7,443,736 ``Total Market'' units). Increasing 
the single-family-owner number in Table A.7 by 776,193 to account 
for excluded B&C mortgages increases the ``Total Market'' number to 
8,219,929, which is consistent with the 18 percent multifamily share 
reported in the text. See Appendix D for discussion of the B&C 
market.
    \202\ A similar imbalance is evident with regard to figures on 
the stock of mortgage debt published by the Federal Reserve Board. 
Within the single-family mortgage market the GSEs held loans or 
guarantees with an unpaid principal balance (UPB) of $1.5 trillion, 
comprising 36 percent of $4.0 trillion in outstanding single-family 
mortgage debt as of the end of 1997. At the end of 1997, the GSEs 
direct holdings and guarantees of $41.4 billion represented 13.7 
percent of $301 billion in multifamily mortgage debt outstanding. 
(Federal Reserve Bulletin, June 1998, A 35.)
    \203\ For the most part, GSE multifamily purchases are similar 
to those in the overall market. For example, 56 percent of units 
backing Fannie Mae's 1997 multifamily acquisitions met the Special 
Affordable Goal, with a corresponding proportion of 57 percent for 
Freddie Mac, compared with a market estimate of approximately 60 
percent, based on HUD's analysis of POMS data.
---------------------------------------------------------------------------

    The GSEs' focus on the single-family market means that they play 
a relatively small role in the multifamily market. As shown in Table 
A.7, the GSEs' purchases have accounted for only 22 percent of 
newly-financed multifamily units during 1997--a market share much 
lower than their 49 percent share of the single-family owner market. 
Thus, these data suggest that a further enlargement of the GSEs' 
role in the multifamily market seems feasible and appropriate in the 
future.
    There are a number of submarkets, such as the market for 
mortgages on 5-50 unit multifamily properties, where the GSEs' role 
have particularly lag the market. As mentioned above, the GSEs 
represented 22 percent of the overall conventional multifamily 
mortgage market in 1997, but their acquisitions of loans on small 
multifamily properties represented only about 2 percent of such 
properties financed that year.\204\ Certainly the GSEs face a number 
of challenges in better meeting the needs of the multifamily 
secondary market. For example, thrifts and other depository 
institutions may sometimes retain their best loans in portfolio, and 
the resulting information asymmetries may act as an impediment to 
expanded secondary market transaction volume.\205\ 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.
---------------------------------------------------------------------------

    \204\ This finding is based on the assumption that units in 
small multifamily properties represented approximately 37 percent of 
multifamily units financed in 1997, per the 1991 Residential Finance 
Survey, as discussed above. Additionally, it is assumed that 1997 
multifamily conventional origination volume was $40.7 billion, as 
discussed in Appendix D. An average loan amount per unit of $25,167 
is assumed, using a combination of loan-level GSE data and loan-
level data from securitized multifamily mortgages in prospectus 
disclosures.
    \205\ 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).
---------------------------------------------------------------------------

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.

[[Page 12717]]

a. Role in the Mortgage Market

    As discussed in Section C of this Appendix, the GSEs' single-
family mortgage acquisitions have generally followed the volume of 
originations in the primary market for conventional mortgages. 
However, in 1997, single-family originations rose by nearly 10 
percent, while the GSEs' acquisitions declined by 7 percent. As a 
result, the Office of Federal Housing Enterprise Oversight (OFHEO) 
estimates that the GSEs' share of conventional single-family 
mortgage originations declined from 42 percent in 1996 to 37 percent 
in 1997. The GSEs' conventional single-family mortgage share rose to 
an estimated 48 percent in 1998, but that is still well below the 
peak of 58 percent attained in 1993.\206\
---------------------------------------------------------------------------

    \206\ Office of Federal Housing Enterprise Oversight, 1998 
Report to Congress, Figure 9, page 32.
---------------------------------------------------------------------------

    The GSEs' high shares of originations during the 1990s led to a 
rise in their share of total conventional single-family mortgages 
outstanding, including both conforming mortgages and jumbo 
mortgages.\207\ OFHEO estimates that the GSEs' share of such 
mortgages outstanding jumped from 34 percent at the end of 1991 to 
40 percent at the end of 1994 and an estimated 45 percent at the end 
of 1998.\208\ All of the increase in the GSEs' relative role between 
1991 and 1998 was due to the growth in their portfolio holdings as a 
share of mortgages outstanding, from 5 percent at the end of 1991 to 
17 percent at the end of 1998; relative holdings of the GSEs' 
mortgage-backed securities by others actually declined as a share of 
mortgages outstanding, from 29 percent at the end of 1991 to 28 
percent at the end of 1998.
---------------------------------------------------------------------------

    \207\ A jumbo mortgage is one for which the loan amount exceeds 
the maximum principal amount for mortgages purchased by the 
enterprises--$240,000 for mortgages on 1-unit properties in 1999, 
with limits that are 50 percent higher in Alaska, Hawaii, Guam, and 
the Virgin Islands.
    \208\ Office of Federal Housing Enterprise Oversight, 1998 
Report to Congress, (June 15, 1998), Figure 9, p. 32; and 
unpublished OFHEO estimates for 1998.
---------------------------------------------------------------------------

    The dominant position of the GSEs in the mortgage market is 
reinforced by their relationships with other market institutions. 
Commercial banks, mutual savings banks, and savings and loans are 
their competitors as well as their customers--they compete to the 
extent they hold mortgages in portfolio, but at the same time they 
sell mortgages to the GSEs. They also buy mortgage-backed 
securities, as well as the debt securities used to finance the GSEs' 
portfolios. Mortgage bankers, who accounted for 58 percent of all 
single-family loans in 1997, sell virtually all of their 
conventional conforming loans to the GSEs.\209\ 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.
---------------------------------------------------------------------------

    \209\ Mortgage originations for 1997 were reported in the 
Department of Housing and Urban Development, HUD Survey of Mortgage 
Lending Activity: Fourth Quarter/Annual 1997, (September 24, 1998).
---------------------------------------------------------------------------

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.\210\ The 
guidelines are also commonly followed in underwriting ``jumbo'' 
mortgages, which exceed the maximum principal amount which can be 
purchased by the GSEs (the conforming loan limit)--such mortgages 
eventually might be sold to the GSEs, as the principal balance is 
amortized or when the conforming loan limit is otherwise increased. 
The GSEs, through their automated underwriting systems, have started 
adapting their underwriting for subprime loans and other loans that 
have not met their traditional underwriting standards.
---------------------------------------------------------------------------

    \210\ The underwriting guidelines published by the two GSEs are 
similar in most aspects. And since November 30, 1992, Fannie Mae and 
Freddie Mac have provided lenders the same Uniform Underwriting and 
Transmittal Summary (Fannie Mae Form 1008/Freddie Mac Form 1077), 
which is used by originators to collect certain mortgage information 
that they need for data entry when mortgages are sold to either GSE.
---------------------------------------------------------------------------

    Because the GSEs' guidelines set the credit standards against 
which the mortgage applications of lower-income families are judged, 
the enterprises have a profound influence on the rate at which 
mortgage funds flow to low- and moderate-income borrowers and 
underserved neighborhoods. Congress realized the crucial role played 
by the GSEs' underwriting guidelines when it required each 
enterprise to submit a study on its guidelines to the Secretary and 
to Congress in 1993, and when it called for the Secretary to 
``periodically review and comment on the underwriting and appraisal 
guidelines of each enterprise.'' Some of the conclusions from a 
study of the GSEs' single-family underwriting guidelines prepared 
for the Department by the Urban Institute have been discussed in 
Section E.

c. State-of-the-Art Technology

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

d. Staff Resources

    Both Fannie Mae and Freddie Mac are well-known throughout the 
mortgage industry for the expertise of their staffs in carrying out 
their current programs, conducting basic and applied research 
regarding mortgage markets, developing innovative new programs, and 
undertaking sophisticated analyses that may lead to new programs in 
the future. The leaders of these corporations frequently testify 
before Congressional committees on a wide range of housing issues, 
and both GSEs have developed extensive working relationships with a 
broad spectrum of mortgage market participants, including various 
nonprofit groups, academics, and government housing authorities. 
They also contract with outside leaders in the finance industry for 
technical expertise not available in-house and for advice on a wide 
variety of issues.

e. Financial Strength

    Fannie Mae. The benefits that accrue to the GSEs because of 
their GSE status, as well as their solid management, have made them 
two of the nation's most profitable businesses. Fannie Mae's net 
income has increased from $376 million in 1987 to $1.6 billion in 
1992, $3.1 billion in 1997, and $3.4 billion in 1998--an average 
annual rate of increase of 22 percent. Through the fourth quarter of 
1998, Fannie Mae has recorded 48 consecutive quarters of increased 
net income per share of common equity. Fannie Mae's return on equity 
averaged 23.8 percent over the 1993-97 period--far above the rates 
achieved by most financial corporations.
    Investors in Fannie Mae's common stock have seen their annual 
dividends per share nearly double over the last five years, rising 
from $1.84 in 1993 to $3.36 in 1997. If dividends were fully 
reinvested, an investment of $1000 in Fannie Mae common stock on 
December 31, 1987 would have appreciated to $27,983.98 by December 
31, 1997. This annualized total rate of return of 39.5 percent over 
the decade exceeded that of many leading U. S. corporations, 
including Intel (35.9 percent), Coca-Cola (32.4 percent), and 
General Electric (24.3 percent).
    Freddie Mac. Freddie Mac has shown similar trends. Freddie
    Mac's net income has increased from $301 million in 1987 to $622 
million in 1992, $1.4 billion in 1997, and $1.7 billion in 1998--an 
average annual rate of increase of 17 percent. Freddie Mac's return 
on equity averaged 22.7 percent over the 1993-97 period--also well 
above the rates achieved by most financial corporations.
    Investors in Freddie Mac's common stock have also seen their 
annual dividends per share nearly double over the last five years, 
rising from $0.88 in 1993 to $1.60 in 1997.

[[Page 12718]]

If dividends were fully reinvested, an investment of $1000 in 
Freddie Mac common stock on December 29, 1989 would have appreciated 
to $8,670.20 by December 31, 1997, for an annualized total rate of 
return of 31.0 percent over this period. This was slightly higher 
than the annual return on Fannie Mae common stock (29.9 percent) and 
substantially higher than the average gain in the S&P Financial-
Miscellaneous index (24.1 percent) over the 1990-97 period.\211\
---------------------------------------------------------------------------

    \211\ Freddie Mac stock was not publicly traded until after the 
passage of the Financial Institutions Reform, Recovery and 
Enforcement Act of 1989 (FIRREA), thus it is not possible to 
calculate a 10-year annualized rate of return.
---------------------------------------------------------------------------

    Other indicators. Additional indicators of the strength of the 
GSEs are provided by various rankings of American corporations. One 
survey found that at the end of 1997 Fannie Mae was first of all 
companies in total assets and Freddie Mac ranked 13th.\212\ Business 
Week has reported that among Standard & Poor's 500 companies in 1997 
Fannie Mae and Freddie Mac respectively ranked 25th and 61st in 
market value, and 28th and 57th in total profits.\213\
---------------------------------------------------------------------------

    \212\ Forbes, (April 20, 1998), p. 315.
    \213\ Business Week, (March 30, 1998), p. 154.
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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 proposed rule, which includes consideration of (a) the 
financial returns that the GSEs earn on low-and moderate-income 
loans and (b) the financial safety and soundness implications of the 
housing goals. Based on this economic analysis and discussions with 
the Office of Federal Housing Enterprise Oversight, HUD concludes 
that the proposed goals raise minimal, if any, safety and soundness 
concerns.

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

    The annual goal for each GSE's purchases of mortgages financing 
housing for low- and moderate-income families is established at 48 
percent of eligible units financed in calendar year 2000, and 50 
percent of eligible units financed in each of calendar years 2001, 
2002 and 2003. This goal will remain in effect for 2004 and 
thereafter, unless changed by the Secretary prior to that time. The 
goal represents an increase over the 1996 goal of 40 percent and the 
1997-99 goal of 42 percent. The goals for 2001-2003 are in the lower 
portion of the range of market share estimates of 50-55 percent, 
presented in Appendix D. The Secretary's consideration of the six 
statutory factors that led to the choice of these goals is 
summarized in this section.

1. Housing Needs and Demographic Conditions

    Data from the 1990 Census and the American Housing Surveys 
demonstrate that there are substantial housing needs among low- and 
moderate-income families, especially among lower-income and minority 
families in this group. Many of these households are burdened by 
high homeownership costs or rent payments and will likely continue 
to face serious housing problems, given the dim prospects for 
earnings growth in entry-level occupations. According to HUD's 
``Worst Case Housing Needs'' report, 21 percent of owner households 
faced a moderate or severe cost burden in 1995. Affordability 
problems were even more common among renters, with 40 percent paying 
more than 30 percent of their income for rent in 1995.\214\
---------------------------------------------------------------------------

    \214\ Rental Housing Assistance--The Crisis Continues: The 1997 
Report to Congress on Worst Case Housing Needs, Department of 
Housing and Urban Development, Office of Policy Development and 
Research, (April 1998).
---------------------------------------------------------------------------

    Single Family Mortgage Market. Many younger, minority and lower-
income families did not become homeowners during the 1980s due to 
the slow growth of earnings, high real interest rates, and continued 
house price increases. Over the past six years, economic expansion, 
accompanied by low interest rates and increased outreach on the part 
of the mortgage industry, has improved affordability conditions for 
these families. Between 1993 and 1998, record numbers of lower-
income and minority families purchased homes. First-time homeowners 
have become a major driving force in the home purchase market over 
the past five years. Thus, the 1990s have seen the development of a 
strong affordable lending market. Despite this growth in affordable 
lending to minorities, disparities in the mortgage market remain. 
For example, African-American applicants are still twice as likely 
to be denied a loan as white applicants, even after controlling for 
income.
    Several demographic changes will affect the housing finance 
system over the next few years. First, the U.S. population is 
expected to grow by an average of 2.4 million per year over the next 
20 years, resulting in 1.1 to 1.2 million new households per year. 
The aging of the baby-boom generation and the entry of the baby-bust 
generation into prime home buying age will have a dampening effect 
on housing demand. However, the continued influx of immigrants will 
increase the demand for rental housing, while those who immigrated 
during the 1980's will be in the market for owner-occupied housing. 
Non-traditional households have become more important, as overall 
household formation rates have slowed. With later marriages, 
divorce, and non-traditional living arrangements, the fastest 
growing household groups have been single-parent and single-person 
households. With continued house price appreciation and favorable 
mortgage terms, ``trade-up buyers'' will increase their role in the 
housing market. These demographic trends will lead to greater 
diversity in the homebuying market, which will require adaptation by 
the primary and secondary mortgage markets.
    As a result of the above demographic forces, housing starts are 
expected to average 1.5 million units between 2000 and 2003, 
essentially the same as in 1996-99.\215\ Refinancing of existing 
mortgages, which accounted for 50 percent of originations in 1998, 
will continue to play a major role in 1999, returning to more normal 
levels during 2000. Thus the mortgage market should remain strong in 
1999, while easing somewhat during 2000.
---------------------------------------------------------------------------

    \215\ Standard & Poor's DRI, The U.S. Economy. (September 1999), 
p. 54.
---------------------------------------------------------------------------

    Multifamily Mortgage Market. Since the early 1990s, the 
multifamily mortgage market has become more closely integrated with 
global capital markets, although not to the same degree as the 
single-family mortgage market. Loans on multifamily properties 
remain viewed as riskier than their single-family counterparts. 
Property values, vacancy rates, and market rents in multifamily 
properties appear to be highly correlated with local job market 
conditions, creating greater sensitivity of loan performance to 
economic conditions than may be experienced for single-family 
mortgages.
    Recent volatility in the market for Commercial Mortgage Backed 
Securities (CMBS), an important source of financing for multifamily 
properties, underlines the need for an ongoing GSE presence in the 
multifamily secondary market. The potential for an increased GSE 
presence is enhanced by virtue of the fact that an increasing 
proportion of multifamily mortgages is now originated in accordance 
with secondary market standards.
    The GSEs have the capability to increase the availability of 
long-term, fixed rate financing, thereby contributing greater 
liquidity in market segments where increased GSE presence can 
provide lenders with a more viable ``exit strategy'' than what is 
presently available. It appears that the cost of mortgage financing 
on properties with 5-50 units, where much of the nation's affordable 
housing stock is concentrated, may be higher than warranted by the 
degree of inherent credit risk.\216\ Presently, however, the GSEs 
purchase only about 5 percent of units in 5-50 unit properties 
financed annually. Borrowers have also experienced difficulty 
obtaining mortgage financing for multifamily properties with 
significant rehabilitation needs. Historically the flow of capital 
into multifamily housing for seniors has, moreover, been 
characterized by a great deal of volatility.
---------------------------------------------------------------------------

    \216\ See Drew Schneider and James Follain, ``A New Initiative 
in the Federal Housing Administration's Office of Multifamily 
Housing Programs: An Assessment of Small Projects Processing,'' 
Cityscape: A Journal of Policy Development and Research 4(1), 
(1998), pp. 43-58.
---------------------------------------------------------------------------

2. Past Performance and Ability To Lead the Industry

    The GSEs have played a major role in the conventional single-
family mortgage market in the 1990s. The GSEs' purchases of single-
family-owner mortgages have accounted for 49 percent of mortgages 
originated in the conventional conforming market during 1997. Many 
industry observers believe that the role of the GSEs in the late-
1980s and 1990s is a major reason why the decline of the thrift 
industry had only minor effects on the nation's housing finance 
system.

[[Page 12719]]

Additionally, the American mortgage market was not impacted 
adversely in any way by the recent volatility in world financial 
markets.
    The enterprises' role in the mortgage market is also reflected 
in their use of cutting edge technology, such as the development of 
Loan Prospector and Desktop Underwriter, the automated underwriting 
systems developed by Freddie Mac and Fannie Mae, respectively. Both 
GSEs are also entering new and challenging fields of mortgage 
finance, including activities involving subprime mortgages and 
mortgages on manufactured housing.
    The GSEs' performance on the Low- and Moderate-Income Housing 
Goal has also improved significantly in recent years, as shown in 
Figure A.1. Fannie Mae's performance increased from 34.2 percent in 
1993 to 42.3 percent in 1995, 45.6 percent in 1996, and 45.7 percent 
in 1997, then falling slightly to 44.1 percent in 1998. Freddie 
Mac's performance also increased, from 29.7 percent in 1993 to 38.9 
percent in 1995, 41.1 percent in 1996, 42.6 percent in 1997, and 
42.9 percent in 1998. Although Freddie Mac's low- and moderate-
income shares were below Fannie Mae's shares in every year, its goal 
performance was 97 percent of Fannie Mae's performance in 1998, the 
highest performance ratio for Freddie Mac since goals were 
instituted in 1993. This increase in Freddie Mac's relative 
performance on the Low- and Moderate-Income Housing Goal resulted 
primarily from its increased role in the multifamily mortgage 
market.

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[[Page 12723]]

    Single Family Affordable Lending Market. Despite these gains in 
goal performance, the Department remains concerned about the GSEs' 
support of lending for the lower-income end of the market. As shown 
in Figures A.2 and A.3, the lower-income shares of the GSEs' 
purchases are too low, particularly when compared with the 
corresponding shares for portfolio lenders and the primary market.
    This appendix has reached the following findings with respect to 
the GSEs' purchases of affordable loans for low- and moderate-income 
families and their communities.
    (i) While Fannie Mae and Freddie Mac have both improved their 
support for the single-family affordable lending market over the 
past six years, they have generally lagged the overall single-family 
market in providing affordable loans to lower-income borrowers. This 
finding is based on HUD's analysis of GSE and HMDA data and on 
numerous studies by academics and research organizations.
    (ii) The GSEs show somewhat different patterns of mortgage 
purchases--for example, Freddie Mac is less likely than Fannie Mae 
to fund mortgages for lower-income families. As a result, the 
percentage of Freddie Mac's purchases benefiting historically 
underserved families and their neighborhoods is less than the 
corresponding shares of total market originations, while Fannie 
Mae's purchases are closer to the patterns of originations in the 
primary market (see Figure A.3).
    (iii) A study by The Urban Institute of lender experience with 
the GSEs' underwriting guidelines finds that the enterprises have 
stepped up their outreach efforts and increased the flexibility in 
their standards to better accommodate the special circumstances of 
lower-income borrowers. However, this study concludes that the GSEs' 
guidelines remain somewhat inflexible and that the enterprises are 
often hesitant to purchase affordable loans. Lenders also tell The 
Urban Institute that Fannie Mae has been more aggressive than 
Freddie Mac in market outreach to underserved groups, in offering 
new affordable products, and in adjusting its underwriting 
standards.
    (iv) A large percentage of the lower-income loans purchased by 
the enterprises have relatively high down payments, which raises 
questions about whether the GSEs are adequately meeting the needs of 
lower-income families have difficulty raising enough cash for a 
large down payment.
    (v) There are important parts of the single-family market where 
the GSEs have played a minimal role. For example, single-family 
rental properties are an important source of low-income housing, but 
they represent only a small portion of the GSEs' business. GSE 
purchases have accounted for only 13 percent of the single-family 
rental units that received financing in 1997. An increased presence 
by Fannie Mae and Freddie Mac would bring lower interest rates and 
liquidity to this market, as well as improve their goals 
performance.
    (vi) The above points can be summarized by examining the GSEs' 
share of the single-family mortgage market. The GSEs' total 
purchases have accounted for 43 percent of all single-family (both 
owner and rental) units financed during 1997; however, their low-mod 
purchases have accounted for only one-third of the low- and 
moderate-income single-family units that were financed during that 
year.
    In conclusion, the Department's analysis suggests that the GSEs 
are not leading the single-family market in purchasing loans that 
qualify for the Low- and Moderate-Income Goal. There is room for 
Fannie Mae and, particularly, Freddie Mac to improve their 
performance in purchasing affordable loans at the lower-income end 
of the market. Moreover, evidence suggests that there is a 
significant population of potential homebuyers who might respond 
well to aggressive outreach by the GSEs. Specifically, both Fannie 
Mae and the Joint Center for Housing Studies expect immigration to 
be a major source of future homebuyers. Furthermore, studies 
indicate the existence of a large untapped pool of potential 
homeowners among the rental population. Indeed, the GSEs' recent 
experience with new outreach and affordable housing initiatives is 
important confirmation of this potential.
    Multifamily Market. Fannie Mae and, especially, Freddie Mac have 
rapidly expanded their presence in the multifamily mortgage market 
in the period since the passage of FHEFSSA. The Senate report on 
this legislation in 1992 referred to the GSEs' activities in the 
multifamily arena as ``troubling,'' citing Freddie Mac's September 
1990 suspension of its purchases of new multifamily mortgages and 
criticism of Fannie Mae for ``creaming'' the market.\217\
---------------------------------------------------------------------------

    \217\ Senate Report 102-282, (May 15, 1992), p. 36.
---------------------------------------------------------------------------

    Freddie Mac has successfully rebuilt its multifamily acquisition 
program, as shown by the increase in its purchases of multifamily 
mortgages from $27 million in 1992 to $847 million in 1994 and $6.6 
billion in 1998. As a result, concerns regarding Freddie Mac's 
multifamily capabilities no longer constrain their performance with 
regard to low- and moderate-income families in the manner that 
prevailed at the time of the December 1995 rule.
    Fannie Mae never withdrew from the multifamily market, but it 
has also stepped up its activities in this area substantially, with 
multifamily purchases rising from $3.0 billion in 1992 to $3.8 
billion in 1994 and $12.5 billion in 1998. Fannie Mae publicly 
announced in 1994 an aggressive goal of conducting $50 billion in 
multifamily transactions between 1994 and the end of the decade, and 
it appears likely that it will be successful in reaching this 
goal.\218\ Also, Fannie Mae's multifamily underwriting standards are 
highly influential and have been widely emulated throughout the 
multifamily mortgage market.
---------------------------------------------------------------------------

    \218\ See Fannie Mae's World Wide Web site at http://
www.fanniemae.com.
---------------------------------------------------------------------------

    The increased role of Fannie Mae and Freddie Mac in the 
multifamily market has major implications for the Low- and Moderate-
Income Housing Goal, since a very high percentage of multifamily 
units have rents which are affordable to low- and moderate-income 
families. However, the potential of the GSEs to lead the multifamily 
mortgage industry has not been fully developed. As reported earlier 
in Table A.7, the GSEs' purchases (through 1998) have accounted for 
only 22 percent of the multifamily units that received financing 
during 1997. Standard & Poor's recently described both GSEs' 
multifamily lending as ``extremely conservative.''\219\ In 
particular, their multifamily purchases do not appear to be 
contributing to mitigation of the excessive cost of mortgage 
financing for small multifamily properties, nor have the GSEs 
demonstrated market leadership with regard to rehabilitation loans, 
a segment where financing has sometimes been difficult to obtain. In 
conclusion, it appears that both GSEs can make improvements in their 
underwriting policies and procedures and introduce new products that 
will enable them to more effectively serve segments of the 
multifamily market that can benefit from greater liquidity.
---------------------------------------------------------------------------

    \219\ ``Final Report of Standard & Poor's to the Office of 
Federal Housing Enterprise Oversight (OFHEO),'' (February 3, 1997), 
p. 10.
---------------------------------------------------------------------------

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

    As detailed in Appendix D, the low-and moderate-income mortgage 
market accounts for 50 to 55 percent of dwelling units financed by 
conventional conforming mortgages. In estimating the size of the 
market, HUD excluded the effects of the B&C market. HUD also used 
alternative assumptions about future economic and market conditions 
that were less favorable than those that existed over the last five 
years. HUD is well aware of the volatility of mortgage markets and 
the possible impacts of changes in economic conditions on the GSEs' 
ability to meet the housing goals. Should conditions change such 
that the goals are no longer reasonable or feasible, the Department 
has the authority to revise the goals.

4. The Low- and Moderate-Income Housing Goals for 2000-03

    There are several reasons why the Secretary is increasing the 
Low- and Moderate-Income Housing Goal from 42 percent in 1997-99 to 
48 percent of eligible units financed in calendar year 2000 and 50 
percent of eligible units financed in each of calendar years 2001, 
2002 and 2003.
    First, when the 1996-99 goals were established in December 1995, 
Freddie Mac had only recently reentered the multifamily mortgage 
market, after its absence in the early 1990s. Freddie Mac has 
rebuilt its multifamily acquisition program over the past several 
years, with its 1998 purchases at a level nearly five times what 
they were in 1994. The limited role of Freddie Mac in the 
multifamily market was a significant constraint in setting the Low- 
and Moderate-Income Housing Goals for 1996-99. Freddie Mac's return 
as a major participant in the multifamily market was an important 
factor in the improvement in its performance on the Low- and 
Moderate-Income Housing Goal, as shown in Figure A.1, and it removes 
an impediment to higher goals for both GSEs. These goals will create 
new opportunities for the GSEs to further step up their support of 
mortgages on properties with rents affordable

[[Page 12724]]

to low- and moderate-income families. However, as discussed in the 
Preamble, to encourage Freddie Mac to further step up its role in 
the multifamily market, the Secretary is proposing a ``temporary 
adjustment factor'' for its purchases of loans on properties with 
more than 50 units. Specifically, each unit in such properties would 
be weighted as 1.2 units in the numerator of the housing goal 
percentage for both the Low and Moderate Income Goal and the Special 
Affordable Housing Goal for the years 2000-2003.
    Second, the single-family affordable market had only recently 
begun to grow in 1993 and 1994, the latest period for which data was 
available when the 1996-99 goals were established in December 1995. 
But the historically high low- and moderate-income share of the 
primary mortgage market attained in 1994 has been maintained over 
the 1995-98 period. The three-year average estimate of the low- and 
moderate-income share of the single-family owner mortgage market was 
38 percent for 1992-94, but 42 percent for 1995-98 and 41 percent 
for the 1992-98 period as a whole. The continued high affordability 
of housing suggests that a strong low-income market continued for a 
sixth straight year in 1999. Current economic forecasts suggest that 
the strong housing affordability of the past several years will be 
maintained in the post-1999 period, leading to additional 
opportunities for the GSEs to support mortgage lending benefiting 
low- and moderate-income families.\220\ And various surveys indicate 
that the demand for homeownership by minorities, immigrants, and 
younger households will remain strong for the foreseeable future.
---------------------------------------------------------------------------

    \220\ However, the Department's goals for the GSEs have been set 
so that they will be feasible even under less favorable conditions 
in the housing market.
---------------------------------------------------------------------------

    Although single-family owner 1-unit properties comprise the 
``bread-and-butter'' of the GSEs' business, evidence presented above 
demonstrates that the shares of their loans for low- and moderate-
income families taking out loans on such properties lag the 
corresponding shares for the primary market. For example, in 1997 
the Department finds that these shares amounted to 34.1 percent for 
Freddie Mac, 37.6 percent for Fannie Mae, and 42.5 percent for the 
primary market; as shown in Figure A.3, a similar pattern holds for 
1998. Thus the Secretary believes that the GSEs can do more to raise 
the low- and moderate-income shares of their mortgages on these 
properties. This can be accomplished by building on various programs 
that the enterprises have already started, including (1) their 
outreach efforts, (2) their incorporation of greater flexibility 
into their underwriting guidelines, (3) their purchases of seasoned 
CRA loans, (4) their entry into new single-family mortgage markets 
such as loans on manufactured housing, (5) their increased purchases 
of loans on small multifamily properties, and (6) their increased 
presence in other rental markets where they have had only a limited 
presence in the past.
    Third, one particular area where the GSEs could play a greater 
role is in the mortgage market for single-family rental dwellings. 
These properties, containing 1-4 rental units, are an important 
source of housing for low- and moderate-income families, but the 
GSEs have not played a major role in this mortgage market--they 
accounted for only 6.5 percent of units financed by Fannie Mae and 
6.4 percent of units financed by Freddie Mac in 1997. The Department 
believes that the GSEs' role in financing loans on such properties, 
which are generally owned by ``mom and pop'' businesses, can and 
should be enhanced, though it recognizes that single-family rental 
properties are very heterogeneous, making it more difficult to 
develop standardized underwriting standards for the secondary 
market. But the Secretary believes that the GSEs can do more to play 
a leadership role in providing financing for such properties.\221\
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    \221\ Another area where stepped-up GSE involvement could 
benefit low- and moderate-income families is lending for the 
rehabilitation of properties, which is especially needed in our 
urban areas. The GSEs have made some efforts in this complex area, 
but the benefits of stepped-up roles by the GSE could be sizable.
---------------------------------------------------------------------------

    Finally, a wide variety of quantitative and qualitative 
indicators indicate that the GSEs' have the financial strength to 
improve their affordable lending performance. For example, combined 
net income has risen steadily over the last decade, from $888 
million in 1988 to $5.12 billion in 1998, an average annual growth 
rate of 19 percent per year. This financial strength provides the 
GSEs with the resources to lead the industry in supporting mortgage 
lending for units affordable to low- and moderate-income families.
    Summary. Figure A.4 summarizes many of the points made in this 
section regarding opportunities for Fannie Mae and Freddie Mac to 
improve their overall performance on the Low- and Moderate-Income 
Goal. The GSEs' purchases have provided financing for 2,893,046 (or 
39 percent) of the 7,443,736 single-family and multifamily units 
that were financed in the conventional conforming market during 
1997. However, in the low- and moderate-income part of the market, 
the 1,305,505 units that were financed by GSE purchases represented 
only 30 percent of the 4,290,860 dwelling units that were financed 
in the market. Thus, there appears to ample room for the GSEs to 
increase their purchases of loans that qualify for the Low- and 
Moderate-Income Goal. Examples of specific market segments that 
would particularly benefit from a more active secondary market have 
been provided throughout this appendix.
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5. Conclusions

    Having considered the projected mortgage market serving low- and 
moderate-income families, economic, housing and demographic 
conditions for 2000-03, and the GSEs' recent performance in 
purchasing mortgages for low- and moderate-income families, the 
Secretary has determined that the annual goal of 48 percent of 
eligible units financed in calendar year 2000 and 50 percent of 
eligible units financed in each of calendar years 2001, 2002 and 
2003 is feasible. Moreover, the Secretary has considered the GSEs' 
ability to lead the industry as well as the GSEs' financial 
condition. The Secretary has determined that the goal is necessary 
and appropriate.

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 
``Geographically Targeted Goal'').
    In establishing this annual housing goal, Section 1334 of 
FHEFSSA requires the Secretary to consider:
    1. Urban and rural housing needs and the housing needs of 
underserved areas;
    2. Economic, housing, and demographic conditions;
    3. The performance and effort of the enterprises toward 
achieving the Geographically Targeted Goal in previous years;
    4. The size of the conventional mortgage market for central 
cities, rural areas, and other underserved areas relative to the 
size of the overall conventional mortgage market;
    5. The ability of the enterprises to lead the industry in making 
mortgage credit available throughout the United States, including 
central cities, rural areas, and other underserved areas; and
    6. The need to maintain the sound financial condition of the 
enterprises.
    Organization of Appendix. The remainder of Section A defines the 
Geographically Targeted 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 Geographically Targeted Goal (the third factor) and Sections 
E-G report the Secretary's findings for the remaining factors. 
Section H summarizes the Secretary's rationale for setting the level 
for the Geographically Targeted Goal.

2. HUD's Geographically Targeted Goal

    HUD's proposed definition of the geographic areas targeted by 
this goal is basically the same as that used during 1996-99. It is 
divided into a metropolitan component and a nonmetropolitan 
component.
    Metropolitan Areas. This proposed rule provides that within 
metropolitan areas, mortgage purchases will count toward the goal 
when those mortgages finance properties that are located in census 
tracts where (1) median income of families in the tract does not 
exceed 90 percent of area (MSA) median income or (2) minorities 
comprise 30 percent or more of the residents and median income of 
families in the tract does not exceed 120 percent of area median 
income.
    The definition includes 20,326 of the 43,232 census tracts (47 
percent) in metropolitan areas, which include 44 percent of the 
metropolitan population.\1\ The tracts included in this definition 
suffer from poor mortgage access and distressed socioeconomic 
conditions. The average mortgage denial rate in these tracts is 23.4 
percent, almost twice the denial rate in excluded tracts. The tracts 
include 73 percent of the number of poor persons in metropolitan 
areas.
---------------------------------------------------------------------------

    \1\ Tracts are excluded from the analysis if median income is 
suppressed or there are no owner-occupied 1-4 unit properties. There 
are 2,033 such tracts. When reporting denial, origination, and 
application rates, tracts are excluded from the analysis if there 
are no purchase or refinance applications. Tracts are also excluded 
from the analysis if: (1) Group quarters constitute more than 50 
percent of housing units or (2) there are less than 15 home purchase 
applications in the tract and the tract denial rates equal 0 or 100 
percent. Excluded tracts account for a small percentage of mortgage 
applications (1.4 percent). These tracts are not excluded from HUD's 
underserved areas if they meet the income and minority thresholds. 
Rather, the tracts are excluded to remove the effects of outliers 
from the analysis.
---------------------------------------------------------------------------

    This definition is based on studies of mortgage lending and 
mortgage credit flows conducted by academic researchers, community 
groups, the GSEs, HUD and other government agencies. While more 
research must be done before mortgage access for different types of 
people and neighborhoods is fully understood, one finding from the 
existing research literature stands out--high-minority and low-
income neighborhoods continue to have higher mortgage denial rates 
and lower mortgage origination rates than other neighborhoods. A 
neighborhood's minority composition and its level of income are 
highly correlated with measuring access to mortgage credit.
    Nonmetropolitan Areas. This proposed rule provides that in 
nonmetropolitan areas mortgage purchases that finance properties 
that are located in counties will count toward the Geographically 
Targeted Goal where (1) median income of families in the county does 
not exceed 95 percent of the greater of (a) state nonmetropolitan 
median income and (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 state nonmetropolitan median income.
    Two important factors influenced HUD's definition of 
nonmetropolitan underserved areas--lack of available data for 
measuring mortgage availability in rural areas and lenders' 
difficulty in operating mortgage programs at the census tract level 
in rural areas. Because of these factors, this proposed rule uses a 
more inclusive, county-based definition of underservedness in rural 
areas. HUD's definition includes 1,511 of the 2,305 counties (66 
percent) in nonmetropolitan areas and accounts for 54 percent of the 
nonmetropolitan population and 67 percent of the nonmetropolitan 
poverty population.
    Goal Levels. The proposed Geographically Targeted Goal is 29 
percent of eligible units financed in calendar year 2000 and 31 
percent of eligible units financed in calendar year 2001 and 
thereafter. HUD estimates that the mortgage market in areas included 
in the Geographically Targeted Goal accounts for 29-32 percent of 
the total number of newly-mortgaged dwelling units. HUD's analysis 
indicates that 28.8 percent of Fannie Mae's 1997 purchases and 27.0 
percent of 1998 purchases financed dwelling units located in these 
areas. The corresponding performance for Freddie Mac was 26.3 
percent in 1997 and 26.1 percent in 1998.

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

    This section discusses differential access to mortgage funding 
in urban areas and summarizes available evidence on identifying 
those neighborhoods that have historically experienced problems 
gaining access to mortgage funding. Section B.1 provides an overview 
of the problem of unequal access to mortgage funding in the nation's 
housing finance system, focusing on discrimination and other housing 
problems faced by minority families and the communities where they 
live. Section B.2 examines mortgage access at the neighborhood level 
and discusses in some detail the rationale for the Geographically 
Targeted Goal in metropolitan areas. The most thorough studies 
available provide strong evidence that in metropolitan areas low 
income and minority composition identify neighborhoods that are 
underserved by the mortgage market.
    Three main points are made in this section:
    There is evidence of racial disparities in both the housing and 
mortgage markets. Partly as a result of this, the homeownership rate 
for minorities is substantially below that for whites.
    The existence of substantial neighborhood disparities in 
mortgage credit is well documented for metropolitan areas. Research 
has demonstrated that census tracts with lower incomes and higher 
shares of minority population consistently have poorer access to 
mortgage credit, with higher mortgage denial rates and lower 
origination rates for mortgages. Thus, the income and minority 
composition of an area is a good measure of whether that area is 
being underserved by the mortgage market.
     Research supports a targeted definition. Studies 
conclude that characteristics of the applicant and the neighborhood 
where the property is located are the major determinants of mortgage 
denials and

[[Page 12727]]

origination rates. Once these characteristics are accounted for, 
other influences, such as location in an OMB-designated central 
city, play only a minor role in explaining disparities in mortgage 
lending.\2\
---------------------------------------------------------------------------

    \2\ For the sake of brevity, in the remainder of this appendix, 
the term ``central city'' is used to mean ``OMB-designated central 
city.''
---------------------------------------------------------------------------

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

    The nation's housing and mortgage finance markets are highly 
efficient systems where most homebuyers can put down relatively 
small amounts of cash and obtain long-term funding at relatively 
small spreads above the lender's borrowing costs. Unfortunately, 
this highly efficient financing system does not work everywhere or 
for everyone. Studies have shown that access to credit often depends 
on improper evaluation of characteristics of the mortgage applicant 
and the neighborhood in which the applicant wishes to buy. In 
addition, though racial discrimination has become less blatant in 
the home purchase market, studies have shown that it is still 
widespread in more subtle forms. Partly as a result of these 
factors, the homeownership rate for minorities is substantially 
below that of whites.
    Appendix A provided an overview of the homeownership gaps and 
lending disparities faced by minorities. A quick look at mortgage 
denial rates reported by the 1997 HMDA data reveals that minority 
denial rates were higher than those for white loan applicants. For 
lower-income borrowers, the conventional denial rate for African 
Americans was 1.7 times the denial rate for white borrowers, while 
for higher-income borrowers, the denial rate for African Americans 
was 2.5 times the rate for white borrowers. Similarly, the FHA 
denial rate for lower-income African Americans was 1.8 times the 
denial rates for lower-income white borrowers and twice as high for 
higher-income African Americans as for whites with similar incomes.
    Several analytical studies, some of which are reviewed later in 
this section, show that these differentials in denial rates are not 
fully accounted for by differences in credit risk. Perhaps the most 
publicized example is a study by the Federal Reserve Bank of Boston, 
described in more detail below, which found that differential denial 
rates were most prevalent among marginal applicants.\3\ Highly 
qualified borrowers of all races seemed to be treated equally, but 
in cases where there was some flaw in the application, white 
applicants seemed to be given the benefit of the doubt more 
frequently than minority applicants.
---------------------------------------------------------------------------

    \3\ Alicia H. Munnell, Lynn Browne, James McEneaney, and 
Geoffrey Tootell. 1996. ``Mortgage Lending in Boston: Interpreting 
HMDA Data,'' American Economic Review, 86(1) March:25-54.
---------------------------------------------------------------------------

    In addition to discrimination in the lending market, substantial 
evidence exists of discrimination in the housing market. The 1991 
Housing Discrimination Study sponsored by HUD found that minority 
home buyers encounter some form of discrimination about half the 
time when they visit a rental or sales agent to ask about advertised 
housing.\4\ The incidence of discrimination was higher for African 
Americans than for Hispanics and for homebuyers than for renters. 
For renters, the incidence of discrimination was 46 percent for 
Hispanics and 53 percent for African Americans. The incidence among 
buyers was 56 percent for Hispanics and 59 percent for African 
Americans.
---------------------------------------------------------------------------

    \4\ Margery A. Turner, Raymond J. Struyk, and John Yinger. 
Housing Discrimination Study: Synthesis, Washington, D.C., U.S. 
Department of Housing and Urban Development: 1991.
---------------------------------------------------------------------------

    While discrimination is rarely overt, minorities are more often 
told the unit of interest is unavailable, shown fewer properties, 
offered less attractive terms, offered less financing assistance, or 
provided less information than similarly situated non-minority 
homeseekers. Some evidence indicates that properties in minority and 
racially-diverse neighborhoods are marketed differently from those 
in White neighborhoods. Houses for sale in non-White neighborhoods 
are rarely advertised in metropolitan newspapers, open houses are 
rarely held, and listing real estate agents are less often 
associated with a multiple listing service.\5\
---------------------------------------------------------------------------

    \5\ Margery A. Turner, ``Discrimination in Urban Housing 
Markets: Lessons from Fair Housing Audits,'' Housing Policy Debate, 
Vol. 3, Issue 2, 1992, pp. 185-215.
---------------------------------------------------------------------------

    Discrimination, while not the only cause, contributes to the 
pervasive level of segregation that persists between African 
Americans and Whites in our urban areas. Because minorities tend to 
live in segregated neighborhoods, their difficulty in obtaining 
mortgage credit has a concentrated effect on the viability of their 
neighborhoods. In addition, there is evidence that denial rates are 
higher in minority neighborhoods regardless of the race of the 
applicant. The next section explores the issue of credit 
availability in neighborhoods in more detail.

2. Evidence About Access to Credit in Urban Neighborhoods

    The viability of neighborhoods--whether urban, rural, or 
suburban--depends on the access of their residents to mortgage 
capital to purchase and improve their homes. While neighborhood 
problems are caused by a wide range of factors, including 
substantial inequalities in the distribution of the nation's income 
and wealth, there is increasing agreement that imperfections in the 
nation's housing and mortgage markets are hastening the decline of 
distressed neighborhoods. Disparate denial of credit based on 
geographic criteria can lead to disinvestment and neighborhood 
decline. Discrimination and other factors, such as inflexible and 
restrictive underwriting guidelines, limit access to mortgage credit 
and leave potential borrowers in certain areas underserved.
    Data on mortgage credit flows are far from perfect, and issues 
regarding the identification of areas with inadequate access to 
credit are both complex and controversial. For this reason, it is 
essential to define ``underserved areas'' as accurately as possible 
from existing data. To provide the reasoning behind the Department's 
definition of underserved areas, this section first uses 1997 HMDA 
data to examine geographic variation in mortgage denial rates, and 
then it reviews three sets of studies that support HUD's definition. 
These include (1) studies examining racial discrimination against 
individual mortgage applicants, (2) studies that test whether 
mortgage redlining exists at the neighborhood level, and (3) studies 
that support HUD's targeted approach to measuring areas that are 
underserved by the mortgage market. In combination, these studies 
provide strong support for the definition of underseved areas chosen 
by HUD. The review of the economics literature draws heavily from 
Appendix B of the 1995 GSE Rule; readers are referred there for a 
more detailed treatment of issues discussed below.

a. HMDA Data on Mortgage Originations and Denial Rates

    Home Mortgage Disclosure Act (HMDA) data provide information on 
the disposition of mortgage loan applications (originated, approved 
but not accepted by the borrower, denied, withdrawn, or not 
completed) in metropolitan areas. HMDA data include the census tract 
location of the property being financed and the race and income of 
the individual loan applicant. Therefore, it is a rich data base for 
analyzing mortgage activity in urban neighborhoods. HUD's analysis 
using HMDA data for 1997 shows that high-minority and low-income 
census tracts have both relatively high loan application denial 
rates and relatively low loan origination rates.
    Table B.1 presents mortgage denial and origination rates by the 
minority composition and median income of census tracts for 
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, the denial rate for census 
tracts that are over 90 percent minority (28.8 percent) was more 
than twice that for census tracts with less than 10 percent minority 
(12.4 percent).
     Census tracts with lower incomes have higher denial 
rates and lower origination rates than higher income tracts. For 
example, mortgage denial rates declined from 26.8 to 8.4 percent as 
tract income increased from less than 60 percent of area median to 
over 150 percent of area median.\6\ Similar patterns arose in HUD's 
analysis of 1993 and 1994 HMDA data (see Appendix B of the 1995 GSE 
Rule).
---------------------------------------------------------------------------

    \6\ The denial rates in Table B.1 are for home purchase 
mortgages. Denial rates are several percentage points lower for 
refinance loans than for purchase loans, but denial rates follow the 
same pattern for both types of loans: rising with minority 
concentration and falling with increasing income.

BILLING CODE 4210-27-P

[[Page 12728]]

[GRAPHIC] [TIFF OMITTED] TP09MR00.013


[[Page 12729]]


[GRAPHIC] [TIFF OMITTED] TP09MR00.021

BILLING CODE 4210-27-C

[[Page 12730]]

    Table B.2 illustrates the interaction between percent minority 
and tract income by aggregating the data in Table B.1 into six 
minority and income combinations. The low-minority (less than 30 
percent minority), high-income (over 120 percent of area median) 
group has a denial rate of 9.1 percent and an origination rate of 
9.7 loans per 100 owner occupants. The high-minority (over 50 
percent), low-income (under 90 percent of area median) group has a 
denial rate of 27.7 percent and an origination rate of only 5.5 
loans per 100 owner occupants. The other groupings fall between 
these two extremes.
    The advantages of HUD's underserved area definition can be seen 
by examining the minority-income combinations highlighted in Table 
B.2. The sharp differences in denial rates and origination rates 
between the underserved and remaining served categories illustrate 
that HUD's definition delineates areas that have significantly less 
success in receiving mortgage credit. Underserved areas have almost 
twice the average denial rate of served areas (23.4 percent versus 
12.2 percent) and two-thirds the average origination rate per 100 
owner occupants (6.6 versus 9.1). HUD's definition does not include 
high-income (over 120 percent of area median) census tracts even if 
they meet the minority threshold. The mortgage denial rate (14.9) 
for high-income tracts with a minority share of population over 30 
percent is much less than the denial rate (23.4) in underserved 
areas as defined by HUD, and only slightly above the average (12.2 
percent) for all served areas.

b. Federal Reserve Bank Studies

    The analysis of denial rates in the above section suggests that 
HUD's definition is a good proxy for identifying areas experiencing 
credit problems. However, an important question is the degree to 
which variations in denial rates reflect lender bias against certain 
kinds of neighborhoods and borrowers versus the degree to which they 
reflect the credit quality of the potential borrower (as indicated 
by the applicant's available assets, credit rating, employment 
history, etc.). Some studies of credit disparities have attempted to 
control for credit risk factors that might influence a lender's 
decision to approve a loan. Without fully accounting for the 
creditworthiness of the borrower, racial differences in denial rates 
cannot be attributed to lender bias.
    The best example of accounting for credit risk is the study by 
researchers at the Federal Reserve Bank of Boston, which analyzed 
mortgage denial rates.\7\ To control for credit risk, the Boston Fed 
researchers included 38 borrower and loan variables indicated by 
lenders to be critical to loan decisions. For example, the Boston 
Fed study included a measure of the borrower's credit history, which 
is a variable not included in other studies. The Boston Fed study 
found that minorities' higher denial rates could not be explained 
fully by income and credit risk factors. African Americans and 
Hispanics were about 60 percent more likely to be denied credit than 
Whites, even after controlling for credit risk characteristics such 
as credit history, employment stability, liquid assets, self-
employment, age, and family status and composition. Although almost 
all highly-qualified applicants of all races were approved, 
differential treatment was observed among borrowers with more 
marginal qualifications.\8\
---------------------------------------------------------------------------

    \7\ 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.
    \8\ A HUD study also found mortgage denial rates for minorities 
to be higher in ten metropolitan areas, even after controlling for 
credit risk. In addition, the higher denial rates observed in 
minority neighborhoods were not purely a reflection of the higher 
denial rates experienced by minorities. Whites experienced higher 
denial rates in some minority neighborhoods than in some 
predominantly white neighborhoods. Ann B. Schnare and Stuart A. 
Gabriel, ``The Role of FHA in the Provision of Credit to 
Minorities,''ICF Incorporated, prepared for the U.S. Department of 
Housing and Urban Development, April 25, 1994.
---------------------------------------------------------------------------

    A subsequent reassessment and refinement of the data used by the 
Federal Reserve Bank of Boston confirmed the findings of that 
study.\9\ William C. Hunter of the Federal Reserve Bank of Chicago 
confirmed that race was a factor in denial rates of marginal 
applicants. While denial rates were comparable for borrowers of all 
races with ``good'' credit ratings, among those with ``bad'' credit 
ratings or high debt ratios, minorities were significantly more 
likely to be denied than similarly-situated whites. The study 
concluded that the racial differences in denial rates were 
consistent with a cultural gap between white loan officers and 
minority applicants, and conversely, a cultural affinity with white 
applicants.
---------------------------------------------------------------------------

    \9\ William C. Hunter, ``The Cultural Affinity Hypothesis and 
Mortgage Lending Decisions,'' WP-95-8, Federal Reserve Bank of 
Chicago, 1995.
---------------------------------------------------------------------------

    The two Fed studies concluded that the effect of borrower race 
on mortgage rejections persists even after controlling for 
legitimate determinants of lenders' credit decisions. Thus, they 
imply that variations in mortgage denial rates, such as given in 
Table B.2 are not determined entirely by borrower risk but reflect 
discrimination in the housing finance system. However, the 
independent race effect identified in these studies is still 
difficult to interpret. In addition to lender bias, access to credit 
can be limited by loan characteristics that reduce profitability 
\10\ and by underwriting standards that have disparate effects on 
minority and lower-income borrowers and their neighborhoods.\11\
---------------------------------------------------------------------------

    \10\ 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.
    \11\ 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.
---------------------------------------------------------------------------

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

    In its deliberations leading up to FHEFSSA, Congress was 
concerned about geographic redlining--the refusal of lenders to make 
loans in certain neighborhoods regardless of the creditworthiness of 
individual applicants. During the 1980's and early 1990's, a number 
of studies using HMDA data (such as that reported in Tables B.1 and 
B.2) attempted to test for the existence of mortgage redlining. 
Consistent with the redlining hypothesis, these studies found lower 
volumes of loans going to low-income and high-minority 
neighborhoods.\12\ However, such analyses were criticized because 
they did not distinguish between demand, risk, and supply effects 
\13\--that is, they didn't determine whether loan volume was low 
because families in high-minority and low-income areas were unable 
to afford home ownership and therefore were not applying for 
mortgage loans, or because borrowers in these areas were more likely 
to default on their mortgage obligations, or because lenders refused 
to make loans to creditworthy borrowers in these areas.\14\ \15\
---------------------------------------------------------------------------

    \12\ 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.
    \13\ For critques 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. Watcher, ``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.
    \14\ Likely 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.
    \15\ 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.
---------------------------------------------------------------------------

    Recent statistical studies have sought to test the redlining 
hypothesis by more

[[Page 12731]]

completely controlling for differences in neighborhood risk and 
demand. The first two studies reviewed below are good examples of 
the more recent literature. In these studies, the explanatory power 
of neighborhood race is reduced to the extent that the effects of 
neighborhood risk and demand are accounted for; thus, they do not 
support claims of racially induced mortgage redlining. However, as 
explained below, these studies cannot reach definitive conclusions 
about redlining because segregation in our inner cities makes it 
difficult to distinguish the impacts of geographic redlining from 
the effects of individual discrimination.
    Additional studies related to redlining and the credit problems 
facing low-income and minority neighborhoods are also summarized. 
Particularly important are studies that focus on the ``thin'' 
mortgage markets in these neighborhoods and the implications of 
lenders not having enough information about the collateral and other 
characteristics of these neighborhoods. The low numbers of house 
sales and mortgages originated in low-income and 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 minority neighborhoods, which 
increases their uncertainty about investing in these areas.
    Holmes and Horvitz Study. First, Andrew Holmes and Paul Horvitz 
used 1988-1991 HMDA data to examine variations of conventional 
mortgage originations across census tracts in Houston. Their single-
equation regression model included as explanatory variables the 
economic viability of the loan, characteristics of properties in and 
residents of the tract (e.g., house value, income, age distribution 
and education level), measures of demand (e.g., recent movers into 
the tract and change in owner-occupied units between 1980 and 1990), 
and measures of credit risk (defaults on government-insured loans 
and change in tract house values between 1980 and 1990). To test the 
existence of racial redlining, the model also included as 
explanatory variables the percentages of African American and 
Hispanic residents in the tract and the increase in the tract's 
minority percentage between 1980 and 1990. Most of the neighborhood 
risk and demand variables were significant determinants of the flow 
of conventional loans in Houston. The coefficients of the racial 
composition variables were insignificant, which led Holmes and 
Horvitz to conclude that allegations of redlining in the Houston 
market could not be supported.
    Schill and Wachter Study. Michael Schill and Susan Wachter posit 
that the probability that a lender will accept a specific mortgage 
application depends on characteristics of the individual loan 
application \16\ and characteristics of the neighborhood where the 
property collateralizing the loan is located. Schill and Wachter 
include neighborhood risk proxies that are likely to affect the 
future value of the properties,\17\ and they include the percentage 
of the tract population comprised by African Americans and Hispanics 
in order to test for the existence of racial discrepancies in 
lending patterns across census tracts.
---------------------------------------------------------------------------

    \16\ Individual loan characteristics include loan size 
(economies of scale cause lenders to prefer large loans to small 
loans) and all individual borrower variables included in the HMDA 
data (the applicant's income, sex, and race).
    \17\ Their neighborhood risk proxies include median income and 
house value (inverse indicators of risk), percent of households 
receiving welfare, median age of houses, homeownership rate (an 
inverse indicator), vacancy rate, and the rent-to-value ratio (an 
inverse indicator). A high rent-to-value ratio suggests lower 
expectations of capital gains on properties in the neighborhood.
---------------------------------------------------------------------------

    Testing their model for conventional mortgages in Philadelphia 
and Boston, Schill and Wachter 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). In an initial analysis that excluded the 
neighborhood risk variables from the model, the percentage of the 
census tract that was African American also showed a significant and 
negative coefficient, a result that is consistent with redlining. 
However, when the neighborhood risk proxies were included in the 
model along with the individual loan variables, the percentage of 
the census tract that was African American becomes insignificant. 
Thus, similar to Holmes and Horvitz, Schill and Wachter stated that 
``once the set of independent variables is expanded to include 
measures that act as proxies for neighborhood risk, the results do 
not reveal a pattern of redlining.'' \18\
---------------------------------------------------------------------------

    \18\ Schill and Wachter, page 271. Munnell, et al. reached 
similar conclusions in their study of Boston. The 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 develop a simultaneous equation 
model of the demand and supply of mortgages, which they estimate for 
the Washington, DC metropolitan area.\19\ Phillips-Patrick and Rossi 
find that the supply of mortgages is negatively associated with the 
racial composition of the neighborhood, which leads 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 note 
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.
---------------------------------------------------------------------------

    \19\ 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 study mortgage rejections in the state 
of New Jersey in 1990, develop a proxy for bad credit based on the 
reasons that lenders give in their HMDA reports for denying a 
loan.\20\ They find that 70 percent of the gap in rejection rates 
cannot be explained by differences in Black and white borrower 
characteristics, loan characteristics, neighborhoods or bad credit. 
Myers and Chan conclude 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 find that Blacks are 
more likely to be denied loans in racially integrated or 
predominately-white neighborhoods than in predominately-Black 
neighborhoods. They conclude that middle-class Blacks seeking to 
move out of the inner city would face problems of discrimination in 
the suburbs.\21\
---------------------------------------------------------------------------

    \20\ 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.
    \21\ For another study that uses HMDA data on reasons for denial 
to construct a proxy for bad credit, see Steven R. Holloway, 
``Exploring the Neighborhood Contingency of Race Discrimination in 
Mortgage Lending in Columbus, Ohio'', Annals of the Association of 
American Geographers, 88(2), 1998, pp. 252-276. Holloway finds that 
mortgage denial rates are higher for black applicants (particularly 
those who are making large loan requests) in all-white neighborhoods 
than in minority neighborhoods, while the reverse is true for white 
applicants making small loan requests.
---------------------------------------------------------------------------

    Geoffrey Tootell has authored two papers on neighborhood 
redlining based on the mortgage rejection data from the Boston Fed 
study.\22\ 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, at least to the same extent as 
previous redlining studies.\23\ Tootell finds that lenders in the 
Boston area do 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,

[[Page 12732]]

Tootell finds 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 
does find that the decision to require private mortgage insurance 
depends on the racial composition of the neighborhood. Tootell 
suggests that, rather than redline themselves, mortgage lenders may 
rely on private mortgage insurers to screen applications from 
minority neighborhoods. Tootell also notes that this indirect form 
of redlining would increase the price paid by applicants from 
minority areas that are approved by private mortgage insurers.
---------------------------------------------------------------------------

    \22\ See Geoffrey M. B. Tootell, ``Redlining in Boston: Do 
Mortgage Lenders Discriminate Against Neighborhoods?'', Quarterly 
Journal of Economics, 111, November, 1996, pp. 1049-1079; and 
``Discrimination, Redlining, and Private Mortgage Insurance'', 
unpublished manuscript, October , 1995.
    \23\ 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 use the 
Boston Fed data base to take a closer at both lender redlining and 
the role of private mortgage insurance (PMI) in neighborhood 
lending.\24\ They have two main findings. First, mortgage 
applications for properties in low-income neighborhoods are more 
likely to be denied if the applicant does not apply for PMI. Ross 
and Tootell conclude 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 are often forced 
to apply for PMI when the housing units are in low-income 
neighborhoods. Ross and Tootell conclude that lenders appear 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.
---------------------------------------------------------------------------

    \24\ 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. A recent group of studies 
that focus on economies of scale in the collection of information 
about neighborhood characteristics has implications for the 
identification of underserved areas and understanding the problems 
of mortgage access in low-income and minority neighborhoods. William 
Lang and Leonard Nakamura argue that individual home sale 
transactions generate information which reduce lenders' uncertainty 
about property values, resulting in greater availability of mortgage 
financing.\25\ 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.''
---------------------------------------------------------------------------

    \25\ Lang, William W. 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.\26\ 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 
finds 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.\27\
---------------------------------------------------------------------------

    \26\ Calem, Paul S. ``Mortgage Credit Availability in Low- and 
Moderate-Income Minority Neighborhoods: Are Information 
Externalities Critical?'' Journal of Real Estate Finance and 
Economics, Volume 13, 1996, pp. 71-89.
    \27\ Ling, David C. 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 find 
significant evidence of economies associated with the scale of 
operation of individual lenders in a neighborhood.\28\ They conclude 
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.
---------------------------------------------------------------------------

    \28\ 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.
---------------------------------------------------------------------------

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

    HUD's definition of underserved areas is a targeted neighborhood 
definition, rather than a broad definition that would encompass 
entire cities. It also focuses on these 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 the 
entire central city. HUD concluded that such broad definitions were 
not a good proxy for mortgage credit problems; to use them would 
allow the GSEs to focus on wealthier parts of cities rather than on 
neighborhoods experiencing credit problems. This section reports 
findings from several analyses by HUD and academic researchers that 
support defining underserved areas in terms of the minority and/or 
income characteristics of census tracts, rather than in terms of a 
broad definition such as all areas of all central cities.
    Socioeconomic Characteristics. The targeted nature of HUD's 
definition can be seen from the data presented in Table B.3, which 
show that families living in underserved areas experience much more 
economic and social distress than families living in served areas. 
For example, the poverty rate in underserved census tracts is 20.1 
percent, or almost four times the poverty rate (5.8 percent) in 
served census tracts. The unemployment rate and the high-school drop 
out rate are also higher in underserved areas. In addition, there 
are nearly three times more female-headed households in underserved 
areas (11.5 percent) than in served areas (4.3 percent)
    The majority of units in served areas are owner-occupied while 
the majority of units in underserved areas are renter-occupied.

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    Credit Characteristics. Tables B.1 and B.2 documented the 
relatively high denial rates and low mortgage origination rates in 
underserved areas as defined by HUD. This section extends that 
analysis by comparing underserved and served areas within central 
cities and suburbs. Figure B.1 shows that HUD's definition targets 
central city neighborhoods that are experiencing problems obtaining 
mortgage credit. The 23.2 percent denial rate in these neighborhoods 
in 1997 is twice the 12.6 percent denial rate in the remaining areas 
of central cities. A broad, inclusive definition of ``central city'' 
that includes all areas of all OMB-designated central cities would 
include these ``remaining'' portions of cities. Figure B.1 shows 
that these areas, which account for approximately 43 percent of the 
population in OMB-designated central cities, appear to be well 
served by the mortgage market. As a whole, they are not experiencing 
problems obtaining mortgage credit. \29\
---------------------------------------------------------------------------

    \29\ The Preamble to the 1995 Rule provides additional reasons 
why central city location should not be used as a proxy for 
underserved areas.
---------------------------------------------------------------------------

    HUD's definition also targets underserved census tracts in the 
suburbs as well as in central cities--for example, the average 
denial rate in underserved suburban areas (23.7 percent) is more 
than twice that in the remaining served areas of the suburbs (12.0 
percent). Low-income and high-minority suburban tracts appear to 
have credit problems similar to their central city counterparts. 
These suburban tracts, which account for 40 percent of the suburban 
population, are encompassed by the definition of other underserved 
areas.
    Another alternative definition proposed by some in 1995 would 
have relaxed HUD's definition by increasing the income threshold 
from 90 percent to 100 percent of area median income and by reducing 
the minority threshold from 30 percent to 20 percent of tract 
population. This definition would include all areas covered by HUD's 
definition as well as 5,367 additional census tracts where median 
income is between 90 and 100 percent of area median or minorities 
comprise 20-30 percent of tract population. As HUD argued in the 
1995 GSE Rule, these tracts do not appear to be experiencing 
problems obtaining mortgage credit. Their 17.8 percent mortgage 
denial rate is not much above the average of 15.3 percent and 
significantly below the 23.4 percent denial rate in tracts covered 
by HUD's Geographically Targeted Goal.
    As explained in the Preamble, HUD is asking for public comment 
on two options that would tighten the targeting of the underserved 
definition reducing the number of qualifying census tract. The first 
option would enhance the definition of the tract income ratio and 
reduce the ceiling of the qualifying tract income ratio from 90 
percent to 80 percent of area median income. The definition of tract 
income ratio would be enhanced as follows: the definition would 
change from tract median income as a percent of MSA median income to 
tract median income as a percent of the greater of either the 
national metropolitan median income or the MSA median income. 
Applying the definition changes the current definition in two ways: 
(1) 994 tracts, with an average denial rate of 26.8, would be added, 
and (2) 2,500 tracts, with an average denial rate of 17.8 percent, 
would be dropped due to reducing the income threshold to 80 percent. 
Of the tracts that would be dropped, the denial rate is not much 
higher than the average denial rate for all metropolitan areas, 
which is 15.3 percent. This suggests that these areas are not 
experiencing severe problems in obtaining mortgage credit and should 
not be targeted.
    The second option would change the definition of underserved 
areas to qualify census tracts with minority population of 50 
percent, an increase from the current definition of 30 percent. An 
increase in the tract minority population would focus GSE purchases 
in high-minority neighborhoods that have been traditionally 
underserved by the mortgage market. One shortcoming of this option 
is that it would exclude 1,045 tracts with minority population 
between 30 and 50 percent which have high denial rates (20.2 
percent).
    Shear, Berkovec, Dougherty, and Nothaft Study. William Shear, 
James Berkovec, Ann Dougherty, and Frank Nothaft conducted an 
analysis of mortgage flows and application acceptance rates in 32 
metropolitan areas that supports a targeted definition of 
underserved areas.\30\ They found: (a) Low-income census tracts and 
tracts with high concentrations of African American and Hispanic 
families had lower rates of mortgage applications, originations, and 
acceptance rates; \31\ and (b) once census tract influences were 
accounted for, central city location had only a minimal effect on 
credit flows.
---------------------------------------------------------------------------

    \30\ William Shear, James Berkovec, Ann Dougherty, and Frank 
Nothaft, ``Unmet Housing Needs: The Role of Mortgage Markets,'' 
Journal of Housing Economics, Volume 4 , 1996, pp. 291-306. These 
researchers regressed the number of mortgage originations per 100 
properties in the census tract on several independent variables that 
were intended to account for some of the demand and supply (i.e., 
credit risk) influences at the census tract level. The tract's 
minority composition and central city location were included to test 
if these characteristics were associated with underserved 
neighborhoods after controlling for the demand and supply variables. 
Examples of the demand and supply variables at the census tract 
level include: tract income relative to the area median income, the 
increase in house values between 1980 and 1990, the percentage of 
units boarded up, and the age distributions of households and 
housing units. See also Susan Wharton Gates, ``Defining the 
Underserved,'' Secondary Mortgage Markets, 1994 Mortgage Market 
Review Issue, 1995, pp. 34-48.
    \31\ For example, census tracts at 80 percent of area median 
income were estimated to have 8.6 originations per 100 owners as 
compared with 10.8 originations for tracts over 120 percent of area 
median income.
---------------------------------------------------------------------------

    Shear, Berkovec, Dougherty, and Nothaft recognized that it is 
difficult to interpret their estimated minority effects--the effects 
may indicate lender discrimination, supply and demand effects not 
included in their model but correlated with minority status, or some 
combination of these factors. They explain the implications of their 
results for measuring underserved areas as follows:
    While it is not at all clear how we might rigorously define, let 
alone measure, what it means to be underserved, it is clear that 
there are important housing-related problems associated with certain 
location characteristics, and it is possible that, in the second or 
third best world in which we live, mortgage markets might be useful 
in helping to solve some of these problems. We then might use these 
data to help single out important areas or at least eliminate some 
bad choices. * * * The regression results indicate that income and 
minority status are better indicators of areas with special needs 
than central city location.\32\
---------------------------------------------------------------------------

    \32\ Shear et al., p. 18.
---------------------------------------------------------------------------

    Avery, Beeson, and Sniderman Study. Robert Avery, Patricia 
Beeson, and Mark Sniderman of the Federal Reserve Bank of Cleveland 
presented a paper specifically addressing the issue of underserved 
areas in the context of the GSE legislation.\33\ Their study 
examines variations in application rates and denial rates for all 
individuals and census tracts included in the 1990 and 1991 HMDA 
data base. They seek to isolate the differences that stem from the 
characteristics of the neighborhood itself rather than the 
characteristics of the individuals that apply for loans in the 
neighborhood or lenders that happen to serve them. Similar to the 
studies of redlining reviewed in the previous section, Avery, Beeson 
and Sniderman hypothesize that variations in mortgage application 
and denial rates will be a function of several risk variables such 
as the income of the applicant and changes in neighborhood house 
values; they test for independent racial effects by adding to their 
model the applicant's race and the racial composition of the census 
tract. Econometric techniques are used to separate individual 
applicant effects from neighborhood effects.
---------------------------------------------------------------------------

    \33\ See Avery, et al.
---------------------------------------------------------------------------

    Based on their empirical work, Avery, Beeson and Sniderman reach 
the following conclusions:
    The individual applicant's race exerts a strong influence on 
mortgage application and denial rates. African American applicants, 
in particular, have unexplainably high denial rates.
     Once individual applicant and other neighborhood 
characteristics are controlled for, overall denial rates for 
purchase and refinance loans were only slightly higher in minority 
census tracts than non-minority census tracts.\34\ For white 
applicants, on the other hand, denial rates were significantly 
higher in minority tracts.\35\ That is,

[[Page 12736]]

minorities have higher denial rates wherever they attempt to borrow 
but whites face higher denials when they attempt to borrow in 
minority neighborhoods. In addition, Avery et al. found that home 
improvement loans had significantly higher denial rates in minority 
neighborhoods. Given the very strong effect of the individual 
applicant's race on denial rates, Avery et al. note that since 
minorities tend to live in segregated communities, a policy of 
targeting minority neighborhoods may be warranted.
---------------------------------------------------------------------------

    \34\ Avery et al. find very large unadjusted differences in 
denial rates between white and minority neighborhoods, and although 
the gap is greatly reduced by controlling for applicant 
characteristics (such as race and income) and other census tract 
characteristics (such as house price and income level), a 
significant difference between white and minority tracts remains 
(for purchase loans, the denial rate difference falls from an 
unadjusted level of 16.7 percent to 4.4 percent after controlling 
for applicant and other census tract characteristics, and for 
refinance loans, the denial rate difference falls from 21.3 percent 
to 6.4 percent). However, when between-MSA differences are removed, 
the gap drops to 1.5 percent and 1.6 percent for purchase and 
refinance loans, respectively. See Avery, et al., p. 16.
    \35\ Avery, et al., page 19, note that, other things equal, a 
black applicant for a home purchase loan is 3.7 percent more likely 
to have his/her application denied in an all-minority tract than in 
an all-white tract, while a white applicant from an all-minority 
tract would be 11.5 percent more likely to be denied.
---------------------------------------------------------------------------

    Other findings are:
    The median income of the census tract had strong effects on both 
application and denial rates for purchase and refinance loans, even 
after other variables were accounted for.
     There is little difference in overall denial rates 
between central cities and suburbs, once individual applicant and 
census tract characteristics are controlled for. Avery, Beeson and 
Sniderman conclude that a tract-level definition is a more effective 
way to define underserved areas than using the list of OMB-
designated central cities as a proxy.

e. Conclusions From HUD's Analysis and the Economics Literature About 
Urban Underserved Areas

    The implications of studies by HUD and others for defining 
underserved areas can be summarized briefly. First, the existence of 
large geographic disparities in mortgage credit is well documented. 
HUD's analysis of HMDA data shows that low-income and high-minority 
neighborhoods receive substantially less credit than other 
neighborhoods and fit the definition of being underserved by the 
nation's credit markets.
    Second, researchers are testing models that more fully account 
for the various risk, demand, and supply factors that determine the 
flow of credit to urban neighborhoods. The studies by Holmes and 
Horvitz, Schill and Wachter, and Tootell are examples of this 
research. Their attempts to test the redlining hypothesis show the 
analytical insights that can be gained by more rigorous modeling of 
this issue. However, the fact that our urban areas are highly 
segregated means that the various loan, applicant, and neighborhood 
characteristics currently being used to explain credit flows are 
often highly correlated with each other which makes it difficult to 
reach definitive conclusions about the relative importance of any 
single variable such as neighborhood racial composition. Thus, their 
results are inclusive and, thus, the need continues for further 
research on the underlying determinants of geographic disparities in 
mortgage lending.\36\
---------------------------------------------------------------------------

    \36\ 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's analysis shows that both credit and 
socioeconomic problems are highly concentrated in underserved areas 
within central cities and suburbs. The remaining, high-income 
portions of central cities and suburbs appear to be well served by 
the mortgage market.
    HUD recognizes that the mortgage origination and denial rates 
forming the basis for the research mentioned in the preceding 
paragraph, as well as for HUD's definition of underserved areas, are 
the result of the interaction of individual risk, demand and supply 
factors that analysts have yet to fully disentangle and interpret. 
The need continues for further research addressing this problem. HUD 
believes, however, that the economics literature is consistent with 
a targeted rather than a broad approach for defining underserved 
areas.

C. Consideration of Factors 1 and 2 in Nonmetropolitan Areas: The 
Housing Needs of Underserved Rural Areas and the Housing, Economic, and 
Demographic Conditions in Underserved Rural Areas

    Because of the absence of HMDA data for rural areas, the 
analysis for metropolitan underserved areas cannot be carried over 
to non-metropolitan areas. Based on discussions with rural lenders 
in 1995, the definition of underserved rural areas was established 
at the county level, since such lenders usually do not make 
distinctions on a census tract basis. But this definition parallels 
that used in metropolitan areas--specifically, a nonmetro county is 
classified as an underserved area if median income of families in 
the county does not exceed 95 percent of the greater of state 
nonmetro or national nonmetro median income, or minorities comprise 
30 percent or more of the residents and the median income of 
families in the county does not exceed 120 percent of state nonmetro 
median income. For nonmetro 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 
``enhanced income''--the greater of state nonmetro income and 
national nonmetro income. This is based on HUD's analysis of 1990 
census data, which indicated that comparing county nonmetro income 
only to state nonmetro income would lead to the exclusion of many 
lower-income low-minority counties from the definition, especially 
in Appalachia. Underserved counties account for 57 percent (8,091 of 
14,419) of the census tracts and 54 percent of the population in 
rural areas. By comparison, the definition of metropolitan 
underserved areas encompassed 47 percent of metropolitan census 
tracts and 44 percent of metropolitan residents.
    The county-wide definition of rural underserved areas could give 
the GSEs an incentive to purchase mortgages in the ``better served'' 
portions of underserved counties which may face few, if any, 
barriers to accessing mortgage credit in rural areas. This issue is 
discussed in more detail in the analysis of the GSEs' purchases 
below.
    The demographic characteristics of served and underserved 
counties are first presented in this section. Next, a literature 
review of recent studies provides an overview of rural mortgage 
markets, GSE activity, and the growing demand for manufactured 
housing in rural housing markets. It also discusses characteristics 
of rural housing markets that lead to higher interest rates and 
mortgage access problems and makes some policy recommendations for 
addressing market inefficiencies.

1. Demographics

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

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[[Page 12738]]

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

2. Literature Review

    Research related to housing and mortgage finance issues in rural 
areas is reviewed in this section. It finds that lack of competition 
between rural lenders and lack of participation in secondary 
mortgage markets may contribute to higher interest rates and lower 
mortgage availability in rural areas. The mortgages purchased by the 
GSEs on properties in underserved counties are not particularly 
focused on lower-income borrowers and first-time homebuyers, which 
suggests that additional research needs to be conducted to target 
areas in nonmetropolitan areas which experience difficulty accessing 
mortgage credit. The role of manufactured housing in providing 
affordable housing in rural areas is also discussed.
    Mikesell Study (1998).\37\ A study by Jim Mikesell provides an 
overview of mortgage lending in rural areas. It finds that home 
loans in rural areas have higher costs, which can be attributed to 
at least three factors that characterize rural mortgage markets. 
First, the fixed cost associated with rural lending may be higher as 
a result of the smaller loan size and remoteness of many rural 
areas. Second, there are fewer mortgage lenders in rural areas 
competing for business, which may account for higher interest rates. 
Third, the secondary mortgage market is not as well developed as in 
metropolitan areas.
---------------------------------------------------------------------------

    \37\ Mikesell, Jim. Can Federal Policy Changes Improve the 
Performance of Rural Mortgage Markets, Economic Research Service, 
U.S. Department of Agriculture, Issues in Agricultural and Rural 
Finance. Agriculture Information Bulletin No. 724-12, August 1998.
---------------------------------------------------------------------------

    Higher interest rates for rural mortgages are documented by the 
Federal Housing Finance Board's monthly survey of conventional home 
purchase mortgages. On average, relative to rates on mortgages in 
urban areas, rates on mortgages in rural areas in 1997 were 8 basis 
points (bp) higher on 30-year fixed rate mortgages (FRMs), 18 bp 
higher for 15-year FRMs, 38 bp higher for adjustable-rate mortgages 
(ARMs), and 52 bp higher for nonstandard loans.\38\ The higher rates 
in rural areas translate into differences in monthly payments of $3 
to $16 for a $100,000 mortgage.
---------------------------------------------------------------------------

    \38\ Standard mortgage types are 30-year fixed-rate mortgages, 
15-year FRMs and 30-year adjustable rate mortgages (ARMs). These are 
the ones most often traded in the secondary markets. Nonstandard 
mortgages generally have shorter terms than the standard mortgages.
---------------------------------------------------------------------------

    Mikesell finds that property location and small loan size are 
two factors that make lending more costly in rural areas. Borrower 
characteristics, such as income, assets, and credit history, and 
lender characteristics, such as ownership, size, and location, might 
influence loan pricing, but the influence of these factors could not 
be tested due to lack of data.
    Rural-based lenders are fewer and originate a smaller volume of 
loans than their urban counterparts. These factors contribute to 
less competition between rural lenders and a less efficient housing 
finance market, which result in higher costs for rural borrowers.
    Rural lenders are less likely than urban lenders to participate 
in the secondary mortgage market. As a result, rural borrowers do 
not receive the benefits associated with the secondary market--the 
increased competition between lenders, the greater potential supply 
of mortgage financing, and the alignment of financing costs more 
closely with those in urban markets.
    Some obstacles for rural lenders participating in the secondary 
market are that borrower characteristics and remote properties may 
not conform to the secondary market's underwriting standards. Rural 
households may have their borrowing capacity reduced by loan 
qualification standards which discount income that varies widely 
from year to year and income from self-employment held for less than 
several years. Rural properties' may have one or more of the 
following characteristics which preclude a mortgage from being 
purchased by the GSEs: Excessive distance to a firehouse, 
unacceptable water or sewer facilities, location on a less-than-all-
weather road, and dated plumbing or electrical systems.
    Mikesell concludes that increased participation by rural lenders 
in the secondary mortgage market would bring down lending costs and 
offset some of the higher costs characteristic of rural lending, and 
that HUD's goals for the GSEs could encourage such increased 
participation.
    MacDonald Study.\39\ This study investigates variations in GSE 
market shares among a sample of 426 non-metropolitan counties in 
eight census divisions. Conventional conforming mortgage 
originations are estimated using residential sales data, adjusted to 
exclude non-conforming mortgages. Multivariate analysis is used to 
investigate whether the GSE market share differs significantly by 
location, after controlling for the economic, demographic, housing 
stock, and credit market differences among counties that could 
affect use of the secondary markets by lenders.\40\
---------------------------------------------------------------------------

    \39\ MacDonald, Heather. Fannie Mae and Freddie Mac in Rural 
Housing Markets: Does Space Matter? Study funded as part of the 1997 
GSE Small Grants by HUD's Office of Policy Development and Research.
    \40\ MacDonald constructs a county-level mortgage market data in 
rural areas using information collected by the Department of Revenue 
for counties and states. Annual Sales Ratio Studies conducted by 
many states' Department of Revenue provide the number of sales for 
different property types. This is done by using residential sales 
recorded for property tax purposes. Other county-level variables 
used to compare rural counties are obtained from the 1990 Census of 
Population and Housing and Bureaus of labor Statistics. Data 
obtained from Census included county populations, racial 
composition, a variety of housing stock characteristics like home 
ownership rates, vacancy rates, proportion of owner-occupied mobile 
homes, median housing value in 1990, median age of the housing 
stock, proportion of units with complete plumbing, and access to 
infrastructure, e.g., public roads and sewage systems. Data 
collected from the Bureau of Labor Statistics included unemployment 
rates and residential building permits.
---------------------------------------------------------------------------

    MacDonald has four main findings regarding mortgage financing 
and the GSEs' purchases in rural mortgage markets. First, smaller, 
poorer and less rapidly growing non-metro areas have less access to 
mortgage credit than larger, wealthier and more rapidly growing 
areas. Second, the mortgages that are originated in the former areas 
are seldom purchased by the GSEs. Third, higher-income borrowers are 
more likely, and first-time homebuyers are less likely, to be served 
by the GSEs in underserved than in served areas. This suggests that 
the GSEs are not reaching out to marginal borrowers in underserved 
nonmetropolitan areas. Finally, the GSEs serve a smaller proportion 
of the low-income market in rural areas than do depository 
institutions. This finding is consistent with studies of the GSEs' 
affordable lending performance in metropolitan areas.
    With regard to the GSEs' underwriting guidelines MacDonald makes 
two points. First, the GSEs' purchase guidelines may adversely 
affect non-metro areas where many borrowers are seasonally- or self-
employed and where houses pose appraisal problems. Second, MacDonald 
speculates that mortgage originators in nonmetropolitan areas may 
interpret guidelines too conservatively, or may not try to qualify 
non-traditional borrowers for mortgages.
    MacDonald also echoes the findings of Mikesell that the 
existence and extent of mortgage lending problems are difficult to 
identify in many rural areas because of the lack of comprehensive 
mortgage lending data. Problems that have been identified include 
the lack of market competition among small, conservative lending 
institutions typical in rural and non-metropolitan areas; 
consolidation and other changes in the financial services industry, 
which may have different consequences in rural areas than in urban 
areas; lack of access to government housing finance programs in more 
rural locations; and weak development of secondary market sources of 
funds in rural areas, exacerbating liquidity problems.
    MacDonald discusses briefly the importance of low-cost 
homeownership alternatives in rural areas. One alternative is 
manufactured (mobile) housing. In general, manufactured housing is 
less costly to construct than site-built housing. Manufactured 
housing makes up more than 25 percent of the housing stock in rural 
counties in the South and Mountain states.
    MacDonald concludes that the lower participation of the GSEs in 
underserved areas compared with served areas may result from 
additional risk components for some borrowers and from lack of 
sophistication by the lenders that serve

[[Page 12739]]

small non-metro markets. In smaller and poorer counties, low volumes 
of loan sales to the GSEs may be a result of lower incomes and 
smaller populations. These counties may not have sufficient loan-
generating activity to justify mortgage originators pursuing 
secondary market outlets.
    The Role of Manufactured Housing.\41\ The Joint Center for 
Housing Studies at Harvard University conducted a comprehensive 
study of the importance of manufactured housing as an affordable 
housing choice in rural communities. In all segments of the housing 
market, but especially in rural areas and among low-income 
households, manufactured housing is growing. Based on the American 
Housing Survey, in 1985, 61 percent of manufactured housing stock 
was located in rural areas compared with 70 percent in 1993. Between 
1985 and 1993, manufactured housing increased over 2.2 percent 
annually while all other housing increased 0.7 percent per year. In 
1993, 6.0 percent (or 6 million) of households lived in manufactured 
housing.
---------------------------------------------------------------------------

    \41\ The Future of Manufactured Housing, Harvard University 
Joint Center for Housing Studies, February 1997.
---------------------------------------------------------------------------

    Since the 1970's, the face of manufactured housing has changed. 
Once a highly mobile form of recreational housing in this country, 
today manufactured housing provides basic quality, year-round 
housing for millions of American households. Most earlier units were 
placed in mobile home parks or on leased parcels of land. Today an 
increasing number of units are owned by households that also own the 
land on which the manufactured home is located.
    Manufactured housing's appeal lies in its affordability. The low 
purchase price, downpayments, and monthly cash costs of manufactured 
housing provide households who are priced out of the conventional 
housing market a means of becoming homeowners. The occupants of 
manufactured housing on average are younger, have less income, have 
less education and are more often white than occupants of single-
family detached homes. This type of housing is often found in areas 
with persistent poverty, retirement destinations, areas for 
recreation and vacations, and commuting counties.
    The manufactured housing industry is well positioned for 
continued growth. The affordability of manufacturing housing is 
increasingly attractive to the growing ranks of low-income 
households. Manufactured housing is becoming more popular among 
first-time homebuyers and the elderly, both of which are growing 
segments of the housing market. The migration of people to the 
South, where manufactured housing is already highly accepted, and to 
metropolitan fringes will further increase the demand for this type 
of housing.\42\
---------------------------------------------------------------------------

    \42\ Though future demand for manufactured housing is promising, 
the Joint Center notes some continued obstacles to growth. 
Challenges for the industry to overcome include a lack of 
standardization of installation procedures and product guarantees, 
exclusionary zoning laws, and certain provisions of the national 
building code.
---------------------------------------------------------------------------

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

    As discussed in Sections B and C, HUD has structured the 
Geographically Targeted Goal to increase mortgage credit to areas 
underserved by the mortgage markets. This section looks at the GSEs' 
past performance to determine the impact the Geographically Targeted 
Goal is having on borrowers and neighborhoods with particular 
emphasis on underserved areas. Section D.1 reports the past 
performance of each GSE with regard to the Geographically Targeted 
Goal. Section D.2 then examines the role that the GSEs are playing 
in funding single-family mortgages in underserved urban 
neighborhoods based on HUD's analysis of GSE and HMDA data. Section 
D.3 concludes this section with an analysis of the GSEs' purchases 
in rural (nonmetropolitan) areas.

1. GSE Performance on the Geographically Targeted Goal

    This section discusses each GSE's performance under the 
Geographically Targeted Goal over the 1993-98 period. The data 
presented here are ``official results''--i.e., they are based on 
HUD's in-depth analysis of the loan-level data submitted annually to 
the Department, subject and the counting provisions contained in 
Subpart B of HUD's December 1, 1995 Regulation of Fannie Mae and 
Freddie Mac. As explained below, in some cases these ``official 
results'' differ to some degree from goal performance reported by 
the GSEs in their Annual Housing Activities Reports to the 
Department.
    HUD's goals specified that in 1996 at least 21 percent of the 
number of units eligible to count toward the Geographically Targeted 
Goal should qualify as geographically targeted, and at least 24 
percent should qualify in 1997 and 1998. Actual performance, based 
on HUD analysis of GSE loan-level data, was as follows:

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    Thus, Fannie Mae surpassed the goals by 7.1 percentage points 
and 4.8 percentage points in 1996 and 1997, respectively, and 
Freddie Mac surpassed the goals by 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 slightly, by 0.2 percentage 
point.\43\
---------------------------------------------------------------------------

    \43\ The Fannie Mae figures for 1997 differ from corresponding 
figures presented by Fannie Mae in its Annual Housing Activity 
Report to HUD by 0.2 percentage points, reflecting minor differences 
in application of counting rules. The percentages shown above for 
Fannie Mae in 1996 and 1998 and for Freddie Mac in 1996-1998 are 
identical to the corresponding percentages in the GSEs' Annual 
Housing Activity Reports.
---------------------------------------------------------------------------

    Fannie Mae's performance on the Geographically Targeted Goal 
jumped sharply in just two years, from 23.6 percent in 1993 to 31.9 
percent in 1995, before tailing off to 28.1 percent in 1996. As 
indicated, it then rose slightly to 28.8 percent in 1997, before 
tailing off to 27.0 percent last year. Freddie Mac has shown more 
steady gains in performance on the Geographically Targeted Goal, 
from 21.3 percent in 1993 to 24.2 percent in 1994, 25 percent in 
1995-96, and just over 26 percent last year.
    Fannie Mae's performance on the Geographically Targeted Goal has 
surpassed Freddie Mac's in every year. However, Freddie Mac's 1998 
performance represented a 23 percent increase over the 1993 level, 
exceeding the 14percent increase for Fannie Mae. And Freddie Mac's 
performance was 97 percent of Fannie Mae's geographically targeted 
share in 1998, the highest ratio since the interim goals took effect 
in 1993.

2. GSEs' Mortgage Purchases in Metropolitan Neighborhoods

    As shown in Table B.5, metropolitan areas accounted for about 85 
percent of total GSE purchases under the Geographically Targeted 
Goal. This section uses HMDA and GSE data for metropolitan areas to 
examine the neighborhood characteristics of the GSEs' mortgage 
purchases. In subsection 2.a, the GSEs' performance in underserved 
neighborhoods is compared with that of portfolio lenders and the 
overall market. This section therefore expands on the discussion in 
Appendix A, which compared the GSEs' funding of affordable loans 
with the overall conventional conforming market. In subsection 2.b., 
the characteristics of the GSEs' purchases within underserved areas 
are compared with those for their purchases in served areas.
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Comparisons With the Primary Market

    Overview and Main Conclusions. Tables A.3 and A.4a in Appendix A 
provided information on the GSEs' funding of home purchase loans for 
properties located in underserved neighborhoods for the years 1993 
to 1998. The findings with respect to the GSEs' funding of 
underserved neighborhoods are similar to those reported in Appendix 
A regarding the GSEs' overall affordable lending performance. Both 
GSEs have improved their performance over the past six years but, on 
average, they continue to lag the conventional conforming market in 
providing affordable loans to underserved neighborhoods. As 
discussed in Appendix A, the two GSEs show very different patterns 
of lending--Freddie Mac has been much less likely than Fannie Mae to 
fund home loans in underserved neighborhoods. The percentage of 
Freddie Mac's purchases financing properties in underserved census 
tracts is substantially less than the percentage of total market 
originations in these tracts; furthermore, since 1992 Freddie Mac 
has not made any progress closing the gap with the primary market. 
Fannie Mae, on the other hand, is much closer to market levels in 
its funding of underserved areas. The same issue discussed in 
Appendix A about the down payment characteristics of the GSEs' 
purchases can also be raised about their purchases in underserved 
areas--the GSEs' typically purchase high down payment mortgages in 
these areas, which reduces their ability to help lower-income, cash-
constrained borrowers seeking to purchase properties in these 
neighborhoods. The remainder of this section present data to support 
these conclusions.
    Freddie Mac. During the 1993-1998 period, Freddie Mac has lagged 
Fannie Mae, portfolio lenders, and the overall conforming market in 
providing home loans to underserved neighborhoods. Underserved 
census tracts (as defined by HUD) accounted for 19.7 percent of 
Freddie Mac's single-family home mortgages, compared with 22.9 
percent of Fannie Mae's purchases, 26.3 percent of loans originated 
and held in portfolio by depository lenders, and 24.5 percent of the 
overall conforming primary market. If the analysis is restricted to 
the 1996-98 period during which the current housing goals have been 
in effect, the data continue to show that Freddie Mac has lagged the 
market in funding underserved neighborhoods (see Table A.3 in 
Appendix A). In 1998, underserved census tracts accounted for 20.0 
percent of Freddie Mac's purchases and 24.6 percent of loans 
originated in the conforming home purchase market, yielding a 
``Freddie Mac-to-market'' ratio of only 0.81 (i.e. 20.0 divided by 
24.6).
    Fannie Mae. Over the longer 1993-98 period and the more
    recent 1996-98 period, Fannie Mae has lagged the market and 
portfolio lenders in funding properties in underserved areas, but to 
a much smaller degree than Freddie Mac. During the 1996-98 period, 
underserved tracts accounted for 22.9 percent of Fannie Mae's 
purchases, compared with 25.8 percent of loans retained in portfolio 
by depositories and with 24.9 percent of home loans originated in 
the conventional conforming market. Fannie Mae's performance is much 
closer to the market than Freddie Mac's performance, as can be seen 
by the ``Fannie Mae-to-market'' ratio of 0.92 for the 1996-98 period 
(i.e. 22.9 divided by 24.9).
    Fannie Mae's performance improved during 1997, due mainly to 
Fannie Mae's increased purchases during 1997 of prior-year mortgages 
in underserved neighborhoods. Overall, Fannie Mae's purchases of 
home loans in underserved areas increased from 22.3 percent in 1996 
to 23.5 percent in 1997. The underserved area percentage for Fannie 
Mae's purchases of newly-originated mortgages was actually lower in 
1997 (20.8 percent) than in 1996 (21.9 percent). This decline was 
offset by the fact that a particularly high percentage (30.1 
percent) of Fannie Mae's 1997 purchases of prior-year mortgages was 
for properties in underserved areas. Thus, Fannie Mae improved its 
overall performance in 1997 by supplementing its purchases of newly-
originated mortgages with purchases of prior-year mortgages targeted 
to underserved neighborhoods. As shown in Table A.4a in Appendix A, 
Fannie Mae continued this strategy in 1998.
    The annual data in Table A.4a show the progress that Fannie Mae 
has made closing the gap between its performance and that of the 
overall market. In 1992, underserved areas accounted for 18.3 
percent of Fannie Mae's purchases and 22.2 percent of market 
originations, for a ``Fannie Mae-to-market'' ratio of 0.82. By 1998, 
underserved areas accounted for 22.9 percent of Fannie Mae's 
purchases and 24.6 percent of market originations, for a higher 
``Fannie Mae-to-market'' ratio of 0.93. Freddie Mac, on the other 
hand, fell further behind the market during this period. In 1992, 
Freddie Mac had a slightly higher underserved area percentage (18.6 
percent) than Fannie Mae (18.3 percent). However, Freddie Mac's 
underserved area percentage had only increased to 20.0 percent by 
1998 (versus 22.9 percent for Fannie Mae). Thus, the ``Freddie Mac-
to-market'' ratio fell from 0.84 in 1992 to 0.81 in 1998.
    Down Payment Characteristics. Table B.6 reports the down payment 
and borrower income characteristics of mortgages that the GSEs 
purchased in underserved areas during 1997. Two points stand out. 
First, loans on properties in underserved areas were more likely to 
have a high loan-to-value ratio than loans on properties in served 
areas. Specifically, about 18 percent of loans in undeserved areas 
had a down payment less than ten percent, compared with 15 percent 
of all loans purchased by the GSEs. Second, loans to low-income 
borrowers in underserved areas were typically high down payment 
loans. Approximately 70 percent of the GSE-purchased loans to very 
low-income borrowers living in underserved areas had a down payment 
more than 20 percent.

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

    Several characteristics of loans purchased by the GSEs in 
metropolitan underserved areas are presented in Table B.7. As shown, 
borrowers in underserved areas are more likely than borrowers in 
served areas to be first-time homebuyers, females, and older than 40 
or younger than 30. And, as expected, they are more likely to have 
below-median income and to be members of minority groups. For 
example, first-time homebuyers make up 21 percent of the GSEs' 
mortgage purchases in underserved areas and 17 percent of their 
business in served areas. In underserved areas, 53 percent of 
borrowers have incomes below the area median, compared with 33 
percent of borrowers in served areas.
    Minorities' share of the GSEs' mortgage purchases in underserved 
areas (29.2 percent) was nearly three times their share in served 
areas (10.5 percent). And the pattern was even more pronounced for 
African Americans and Hispanics, who accounted for 20.8 percent of 
the GSEs' business in underserved areas, but only 5.5 percent of 
their purchases in served areas.
    Other differences between the GSEs' purchases in underserved and 
served areas include the fact that prior-year mortgages comprised a 
higher percentage of Fannie Mae's loans in underserved areas (32.8 
percent) than in served areas (25.3 percent) in 1997, which suggests 
that Fannie Mae may be purchasing prior-year loans in underserved 
areas to raise its performance on the Geographically Targeted Goal. 
Also, refinance mortgages comprised a higher percentage of Freddie 
Mac's loans in underserved areas (44.6 percent) than in served areas 
(38.8 percent) in 1997, possibly due to the fact that refinance 
mortgages, which typically have lower loan-to-value ratios than home 
purchase mortgages, have lower probabilities of default or severity 
of loss.

3. GSE Mortgage Purchases in Nonmetropolitan Areas

    Nonmetropolitan mortgage purchases made up 14 percent of the 
GSEs' total mortgage purchases in 1997. Mortgages in underserved 
counties made up 38 percent of the GSEs' business in rural areas. 
\44\
---------------------------------------------------------------------------

    \44\ Underserved areas make up about 56 percent of the census 
tracts in nonmetropolitan areas and 47 percent of the census tracts 
in metropolitan areas. This is one reason why underserved areas 
comprise a larger portion of the GSEs' single-family mortgages in 
nonmetropolitan areas (38 percent) than in metropolitan areas (22 
percent).
---------------------------------------------------------------------------

    Unlike the underserved definition for metropolitan areas which 
was based on census tracts, the rural underserved definition was 
based on counties. Rural lenders argued that they identified 
mortgages by the counties in which they were located rather than the 
census tracts; and therefore, census tracts were not an operational 
concept in rural areas. Market data on trends in mortgage lending 
for metropolitan areas is provided by the Home Mortgage Disclosure 
Act (HMDA); however, no comparable data source exists for rural 
mortgage markets. The absence of rural market data is a constraint 
for evaluating credit gaps in rural mortgage lending and for 
defining underserved areas.
    The broad nature of the underserved definition for 
nonmetropolitan areas raises at least two concerns. The first 
concern is whether the broad definition overlooks differences in 
borrower characteristics in served and underserved counties that 
should be included in the definition. Table B.8 compares borrower 
and loan characteristics for the GSEs' mortgage purchases in served 
and underserved areas. The GSEs are less likely to purchase loans 
for first-time homebuyers and more likely to purchases mortgages for 
high-income borrowers in underserved than in served counties. 
Mortgages to first-time homebuyers account for 13.9 percent of the 
GSEs' mortgage purchases in served counties compared with 12.3 
percent in underserved counties. Surprisingly, borrowers in served 
counties are more likely to have incomes below the median than in 
underserved counties (34.5 percent compared to 28.8 percent). These 
findings support the claim that, in rural underserved counties, the 
GSEs purchase mortgages for borrowers that probably encounter few 
obstacles to obtaining mortgage credit.

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    The second concern is whether defining underserved areas in 
terms of an entire county gives the GSEs an incentive to purchase 
mortgages in the ``better off'' tracts. Based on an analysis of the 
GSEs' mortgage purchases by tract median income, it is unclear if 
the broad nature of the county definition has an impact on the GSEs' 
purchasing behavior at the tract level. For example, even though the 
GSEs purchase a larger percentage of mortgages in high-minority and 
low-income tracts in underserved than in served counties, they 
purchase nearly the same percentage of mortgages in both underserved 
and served counties in high-income tracts.
    In underserved areas, the GSEs are more likely to purchase 
mortgages in low-income and high-minority census tracts than in 
served counties. The GSEs are more than twice as likely to purchase 
mortgages in tracts with median incomes at or below 80 percent of 
AMI in underserved counties than in served counties (15.7 percent 
vs. 5.1 percent). For census tracts with percent minority above 30 
percent, 3.3 percent of the GSEs' purchases in served counties are 
in these high-minority tracts compared to 23.9 percent in 
underserved counties. These results are expected since underserved 
counties are made up of a greater number of low-income and high-
minority census tracts than are served counties.
    While the GSEs purchase nearly the same percentages of mortgages 
in the ``better off'' tracts in underserved counties and served 
counties, when compared to the percentage of owner-occupied units in 
these areas, two points stand out. First, as the ratio of tract 
income to area median income increases, so does the volume of GSE 
home mortgage purchases relative to the number of owner-occupied 
units in the tract. Second, this tendency is more pronounced in 
underserved than in served counties.
    Tables B.9 and B.10 provide distributions of owner-occupied 
units across tracts by tract income ratio, as reported in the 1990 
Census, and distributions of 1997 GSE home mortgage purchases by 
tract income ratio. The two tables provide data for underserved and 
for served counties, respectively. In underserved counties, 1.1 
percent of GSE 1997 purchases and 2.7 percent of owner-occupied 
units were in tracts with median income at or below 60 percent of 
area median income. The ratio of these two shares is 0.41 (1.1 
divided by 2.7). As the ratio of tract income to area median income 
increases, the ratio between the two shares increases (see Table 
B.9). This same result is found for served counties, but the ratios 
are both larger for low tract income ratios and smaller for high 
tract income ratios (Compare Table B.10 with Table B.9).

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[[Page 12750]]

    The fact that the ratio of shares for higher-income tracts is 
larger in underserved counties than in served counties suggests that 
the GSEs are purchasing a greater percentage of mortgages in 
``better off'' tracts as a result of the county-based geographically 
targeted goal. For example, in tracts where the median income is 
above 120 percent of the area median, the ratio of the GSEs' 
mortgage purchase share to the owner-occupied units share is 2.03 
for underserved counties, compared to 1.48 for served counties. 
Conversely, in tracts where the median income is at or below 60 
percent of the area median, the ratio of the GSEs' mortgage purchase 
share to the owner-occupied units share is 0.41, compared to 0.67 
for served counties.
    There are similarities and differences between the types of 
loans that Fannie Mae and Freddie Mac purchase in served and 
underserved counties. The GSEs are similar in that their mortgage 
purchases in underserved counties do not have lower downpayments 
than in served counties. In both served and underserved counties, 
approximately 28 percent of the GSEs' 1997 mortgage purchases have 
loan-to-value ratios above 80 percent. The GSEs differ in their 
mortgage purchases of refinanced and seasoned loans. Fannie Mae is 
more likely to purchase more seasoned mortgages in underserved than 
in served counties; Freddie Mac is more likely to purchase more 
refinanced mortgages in underserved than in served counties.

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

    HUD estimates that underserved areas account for 29-32 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.

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

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

H. Determination of the Geographically-Targeted Areas Housing Goals

    The annual goal for each GSE's purchases of mortgages financing 
housing for properties located in geographically-targeted areas 
(central cities, rural areas, and other underserved areas) is 
established at 29 percent of eligible units financed in calendar 
year 2000 and 31 percent of eligible units financed in calendar year 
2001. The year 2001 goal will remain in effect through 2003 and 
thereafter, unless changed by the Secretary prior to that time. The 
goal represents an increase over the 1996 goal of 21 percent and the 
1997-99 goal of 24 percent. However, it is commensurate with the 
market share estimates of 29-32 percent, presented in Appendix D.
    This section summarizes the Secretary's consideration of the six 
statutory factors that led to the choice of these goals. It 
discusses the Secretary's rationale for defining these 
geographically-targeted areas and it compares the characteristics of 
such areas and untargeted areas. The section draws heavily from 
earlier sections which have reported findings from HUD's analyses of 
mortgage credit needs as well as findings from other research 
studies investigating access to mortgage credit.

1. Credit Needs in Metropolitan Areas

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

2. Identifying Underserved Portions of Metropolitan Areas

    To identify areas underserved by the mortgage market, HUD 
focused on two traditional measures used in a number of studies 
based on HMDA data:\45\ application denial rates and mortgage 
origination rates per 100 owner-occupied units.\46\ Tables B.1 and 
B.2 in Section B of this Appendix presented detailed data on denial 
and origination rates by the racial composition and median income of 
census tracts for metropolitan areas.\47\ Aggregating this data is 
useful in order to examine denial and origination rates for broader 
groupings of census tracts:
---------------------------------------------------------------------------

    \45\ HMDA provides little useful information on rural areas. 
Therefore, the HMDA data reported here apply only to metropolitan 
areas.
    \46\ Analysis of application rates are not reported here. 
Although application rates are sometimes used as a measure of 
mortgage demand, they provide no additional information beyond that 
provided by looking at both denial and origination rates. The 
patterns observed for application rates are still very similar to 
those observed for origination rates.
    \47\ As shown in Table B.1, no sharp breaks occur in the denial 
and origination rates across the minority and income deciles--
mostly, the increments are somewhat similar as one moves across the 
various deciles that account for the major portions of mortgage 
activity.

----------------------------------------------------------------------------------------------------------------
                                      Denial rate                                       Denial rate
        Minority composition            (percent)   Orig. rate       Tract income         (percent)   Orig. rate
----------------------------------------------------------------------------------------------------------------
0-30%...............................         13.7          8.7  Less than 90%.........        24.0%          6.5
30-50%..............................        21.3%          6.8  90-120%...............         15.6          8.3
50-100%.............................        25.1%          5.8  Greater than 20%......          9.5          9.5
----------------------------------------------------------------------------------------------------------------

Two points stand out from these data. First, high-minority census 
tracts have higher denial rates and lower origination rates than 
low-minority tracts. Specifically, tracts that are over 50 percent 
minority have nearly twice the denial rate and two-thirds the 
origination rate of tracts that are under 30 percent minority.\48\ 
Second, census tracts with lower incomes have higher denial rates 
and lower origination rates than higher income tracts. Tracts with 
income less than or equal to 90 percent of area median income have 
2.5 times the denial rate and barely two-thirds the origination rate 
for tracts with income over 120 percent of area median income.
---------------------------------------------------------------------------

    \48\ 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 1995, HUD's research determined that ``underserved areas'' 
could best be characterized in metropolitan areas as census tracts 
with minority population of at least 30 percent in 1990 and/or 
census tract median income no greater than 90 percent of area median 
income in 1990, excluding high-minority high-income tracts. These 
cutoffs produce sharp differentials in denial and origination rates 
between underserved areas and adequately served areas. For example, 
the mortgage denial rate in underserved areas (23.4 percent) was 
nearly twice that in

[[Page 12751]]

adequately served areas (12.2 percent) in 1997.
    These minority population and income thresholds apply in the 
suburbs as well as in OMB-defined central cities. HUD's research has 
found that the average denial rate in underserved suburban areas is 
almost twice that in adequately served areas in the suburbs. (See 
Figure B.1 in Section B of this Appendix.) Thus HUD uses the same 
definition of underserved areas throughout metropolitan areas--there 
is no need to define such areas differently in central cities and in 
the suburbs. And HUD's definition, which covers 57 percent of the 
central city population and 33 percent of the suburban population, 
is clearly preferable to a definition which would count 100 percent 
of central city residents and zero percent of suburban residents as 
living in underserved areas.
    This definition of metropolitan underserved areas includes 
21,586 of the 46,904 census tracts in metropolitan areas, covering 
44 percent of the metropolitan population. It includes 73 percent of 
the population living in poverty in metropolitan areas. The 
unemployment rate in underserved areas is more than twice that in 
served areas, and rental units comprise 52.4 percent of total units 
in underserved tracts, versus 28.6 percent of total units in served 
tracts. As shown in Table B.11, this definition covers most of the 
population in the nation's most distressed central cities: Newark 
(99 percent), Detroit (96 percent), Hartford (97 percent), and 
Cleveland (90 percent). The nation's five largest cities also 
contain large concentrations of their population in underserved 
areas: New York (62 percent), Los Angeles (69 percent), Chicago (77 
percent), Houston (67 percent), and Philadelphia (80 percent).

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Identifying Underserved Portions of Nonmetropolitan Areas

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

4. Past Performance of the GSEs

    The GSEs' performance on the geographically-targeted goal has 
improved significantly in recent years, as shown in Figure B.2. 
Fannie Mae's performance, as measured by HUD, increased sharply from 
23.6 percent in 1993 to 31.9 percent in 1995, dropped to 28.1 
percent in 1996, and rose to 28.8 percent in 1997, and then dropped 
to 27.0 percent in 1998. Freddie Mac's performance, as measured by 
HUD, rose from 21.8 percent in 1993 to 26.4 percent in 1995, 
followed by 25.0 percent in 1996, 26.3 percent in 1997, and 26.1 
percent in 1998.
    Both GSEs have improved their performance in underserved areas 
over the past six years but, on average, they continue to lag the 
conforming primary market in providing single-family home loans to 
distressed neighborhoods. As discussed in Section D, the GSEs show 
different patterns of lending--Freddie Mac is less likely than 
Fannie Mae to purchase mortgages on properties in low-income and 
high-minority neighborhoods. During the 1996-98 period, Freddie Mac 
lagged Fannie Mae, portfolio lenders, and the overall conforming 
market in providing funds to underserved neighborhoods. As shown in 
Figure B.3, underserved areas accounted for 20.0 percent of Freddie 
Mac's 1998 purchases of home loans, compared with 22.9 percent of 
Fannie Mae's purchases, 26.1 percent of home loans retained in 
depositories' portfolios, and 24.6 percent of the overall conforming 
market. Freddie Mac has not made any progress since 1992 in reducing 
the gap between its performance and that of the conventional 
conforming home purchase market. Fannie Mae, on the other hand, has 
improved its funding in underserved areas and has closed the gap 
between its performance and the single-family primary market in 
funding low-income and high-minority neighborhoods.\49\
---------------------------------------------------------------------------

    \49\ Although this goal is targeted to lower-income and high 
minority areas, it does not mean that GSE purchase activity in 
underserved areas derives totally from lower income or minority 
families. In 1997, above-median income households accounted for 37 
percent of the mortgages that the GSEs purchased in underserved 
areas. This suggests that these areas are quite diverse.
---------------------------------------------------------------------------

    HUD also conducted an analysis of the share of the overall 
(single-family and multifamily) conventional conforming mortgage 
market accounted for by the GSEs. The GSEs' purchases represented 39 
percent of total dwelling units financed during 1997 but they 
represented only 33 percent of the dwelling units financed in 
underserved neighborhoods. In other words, the GSEs account for only 
one-third of the single-family and multifamily units financed in 
underserved areas. This suggests that there is room for the GSEs to 
increase their purchases in underserved neighborhoods.

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

    As detailed in Appendix D, the market for mortgages in 
geographically-targeted areas accounts for 29 to 32 percent of 
dwelling units financed by conventional conforming mortgages. In 
estimating the size of the market, HUD used alternative assumptions 
about future economic and market conditions that were less favorable 
than those that existed over the last five years. HUD is well aware 
of the volatility of mortgage markets and the possible impacts on 
the GSEs' ability to meet the housing goals. Should conditions 
change such that the goals are no longer reasonable or feasible, the 
Secretary has the authority to revise the goals.

6. The Geographically-Targeted Areas Housing Goal for 2000-03

    There are several reasons that the Secretary is increasing the 
Geographically Targeted Areas Goal. First, the present 24 percent 
goal level for 1997-99 and the GSEs' recent performance are below 
the estimated 29-32 percent of the primary mortgage market accounted 
for by units in properties located in geographically-targeted areas. 
Raising the goal reflects the Secretary's concern that the GSEs 
close the remaining gap between their performance and that of the 
primary mortgage market.
    Second, the single-family-owner mortgage market in underserved 
areas has demonstrated remarkable strength over the past few years 
relative to the preceding period. This market had only recently 
begun to grow in 1993 and 1994, the latest period for which data was 
available when the 1996-99 goals were established in December 1995. 
But the historically high undeserved areas share of the primary 
single-family mortgage market attained in 1994 has been maintained 
over the 1995-98 period. The three-year average of the underserved 
areas share of the single-family-owner mortgage market in 
metropolitan areas was 22.2 percent for 1992-94, but 25.1 percent 
for 1995-98 and 24.1 percent for the 1992-98 period as a whole.
    Third, as discussed in detail in Appendix A, there are several 
market segments that would benefit from a greater secondary market 
role by the GSEs; many of these market segments are concentrated in 
underserved areas. For example, one such area is single-family 
rental dwellings. These properties, containing 1-4 rental units, are 
an important source of housing for families in low-income and high-
minority neighborhoods. However, the GSEs' purchases have accounted 
for only 13 percent of the single-family rental units financed in 
underserved areas during 1997. The Secretary believes that the GSEs 
can do more to play a leadership role in providing financing for 
such properties. Examples of other market segments in need of an 
enhanced GSE role include small multifamily properties, 
rehabilitation loans, seasoned CRA loans, and manufactured housing. 
Additional efforts by the GSEs in these markets would benefit 
families living in underserved areas.
    Finally, a wide variety of quantitative and qualitative 
indicators indicate that the GSEs' have the financial strength to 
improve their affordable lending performance. For example, combined 
net income has risen steadily over the last decade, from $677 
million in 1987 to $4.5 billion in 1997, an average annual growth 
rate of 21 percent per year. This financial strength provides the 
GSEs with the resources to lead the industry in supporting mortgage 
lending for properties located in geographically-targeted areas.
    Summary. Figure A.4 of Appendix A summarizes many of the points 
made in this section regarding opportunities for Fannie Mae and 
Freddie Mac to improve their overall performance on the 
Geographically-Targeted Goal. The GSEs' purchases have provided 
financing for 2,893,046 dwelling units, which represented 39 percent 
of the 7,443,736 single-family and multifamily units that were 
financed in the conventional conforming market during 1997. However, 
in the underserved areas part of the market, the 795,981 units that 
were financed by GSE purchases represented only 33 percent of the 
2,408,393 dwelling units that were financed in the market. Thus, 
there appears to ample room for the GSEs to increase their purchases 
in underserved areas. It is hoped that expression of concern in the 
current rulemaking will foster additional effort by both GSEs to 
increase their purchases in underserved areas.

7. Conclusions

    Having considered the projected mortgage market serving 
geographically-targeted areas, economic, housing and demographic 
conditions for 2000-03, and the GSEs' recent performance in 
purchasing mortgages on properties in geographically-targeted areas, 
the Secretary has determined that the annual goal of 29 percent in 
calendar year 2000 and 31 percent in calendar year 2001 and the 
years following is feasible. Moreover, the Secretary has considered 
the GSEs' ability to lead the industry as well as the GSEs' 
financial condition. The Secretary has determined that these goal 
levels are necessary and appropriate.

[[Page 12756]]

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

    The final rule provides that the Special Affordable Housing Goal 
is 18 percent of the total number of dwelling units financed by each 
GSE's mortgage purchases in 2000, and 20 percent in 2001-2003. Of 
the total Special Affordable Housing Goal for each year, in 2000 
each GSE must purchase multifamily mortgages in an amount at least 
equal to 0.9 percent of the 1998 total dollar volume of mortgages 
purchased by the GSE, rising to 1.0 percent in 2001-2003.\1\
---------------------------------------------------------------------------

    \1\ While this proposed rule specifically proposes a dollar 
based subgoal, the Department is considering three alternative 
approaches to structuring the Special Affordable multifamily 
subgoal--a mortgage-based subgoal, a dollar-based subgoal, and a 
unit-based subgoal. These alternative approaches are described in 
the Preamble and in Section D of this Appendix.
---------------------------------------------------------------------------

    Approximately 23-26 percent of the conventional conforming 
mortgage market in 2000 would qualify under the Special Affordable 
Housing Goal as defined in the proposed rule, as projected by HUD.
    Units that count toward the goal: Subject to further provisions 
specified below, units that count toward the Special Affordable 
Housing Goal include units occupied by low-income owners and renters 
in low-income areas, and very-low-income owners and renters. Other 
low-income rental units in multifamily properties count toward the 
goal where at least 20 percent of the units in the property are 
affordable to families whose incomes are 50 percent of area median 
income or less, or where at least 40 percent of the units are 
affordable to families whose incomes are 60 percent of area median 
income or less.

B. Underlying Data

    In considering the factors under FHEFSSA to establish the 
Special Affordable Housing Goal, HUD relied upon data gathered from 
the American Housing Survey through 1995, the Census Bureau's 1991 
Residential Finance Survey, the 1990 Census of Population and 
Housing, Home Mortgage Disclosure Act (HMDA) data for 1992 through 
1997, and annual loan-level data from the GSEs on their mortgage 
purchases through 1997. 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.
    Section C discusses the factors listed above, and Section D 
provides the Secretary's rationale for establishing the special 
affordable goal.

Consideration of the 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.

a. GSE Performance Relative to the 1996-98 Goals

    This section discusses each GSE's performance under the Special 
Affordable Housing Goal over the 1993-98 period. The data presented 
here are ``official results''--i.e., they are based on HUD's in-
depth analysis of the loan-level data submitted annually to the 
Department and the counting provisions contained in HUD's 
regulations in 24 CFR part 81, subpart B. As explained below, in 
some cases these ``official results'' differ from goal performance 
reported to the Department by the GSEs in their Annual Housing 
Activities Reports.
    HUD's goals specified that in 1996 at least 12 percent of the 
number of units eligible to count toward the Special Affordable goal 
should qualify as Special Affordable, and at least 14 percent 
annually beginning in 1997. The actual performance in 1996 through 
1998, based on HUD analysis of loan-level data submitted by the 
GSEs, is shown in Table C.1 and Figure C.1. Fannie Mae surpassed the 
goal by 3.4 percentage points and 3.0 percentage points, 
respectively, in 1996 and 1997, while Freddie Mac surpassed the goal 
by 2.0 and 1.2 percentage points. In 1998, Fannie Mae surpassed the 
goal by 0.3 percentage points while Freddie Mac surpassed the goal 
by 1.9 percentage points (Table C.1).

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    Table C.1 also includes, for comparison purposes, comparable 
figures for 1993, 1994, and 1995, calculated according to the 
counting conventions of the 1995 Final Rule that became applicable 
in 1996. Each GSEs' percentages in 1996, 1997, and 1998 exceeded 
their percentages in any of the three preceding years.
    The Fannie Mae figures presented above are smaller than the 
corresponding figures presented by Fannie Mae in its Annual Housing 
Activity Reports to HUD by approximately 2 percentage points in both 
1996 and 1997 and 1.3 percentage points in 1998. The difference 
largely reflects HUD-Fannie Mae differences in application of 
counting rules relating to counting of seasoned loans for purposes 
of this goal. In particular, the tabulations reflect inclusion of 
seasoned loan purchases in the denominator in calculating 
performance under the Special Affordable goal, as discussed in 
Preamble section II(B)(6)(c) on the Seasoned Mortgage Loan Purchases 
``Recycling'' Requirement. Freddie Mac's Annual Housing Activity 
Report figures for this goal differ from the figures presented above 
by 0.1 percentage point, reflecting minor differences in application 
of counting rules.
    Since 1996 each GSE has been subject to an annual subgoal for 
multifamily Special Affordable mortgage purchases, established as 
0.8 percent of the dollar volume of single-family and multifamily 
mortgages purchased by the respective GSE in 1994. Fannie Mae's 
subgoal was $1.29 billion and Freddie Mac's subgoal was $988 million 
for each year. Fannie Mae surpassed the subgoal by $1.08 billion, 
$1.90 billion, and $2.24 billion in 1996, 1997, and 1998, 
respectively, while Freddie Mac surpassed the subgoal by $18 
million, $220 million, and $1.70 billion. Table C.1 includes these 
figures, and they are depicted graphically in Figure C.2.

b. Characteristics of Special Affordable Purchases

    The following analysis presents information on the composition 
of the GSEs' Special Affordable purchases according to area income, 
unit affordability, tenure of unit and property type (single- or 
multifamily).
    Increased reliance on multifamily housing to meet goal. Tables 
C.2 and C.3 show that both GSEs have increasingly relied on 
multifamily housing units to meet the special affordable goal since 
1993. Fannie Mae's multifamily purchases represented 44 percent of 
all purchases qualifying for the goal in 1997, compared with 28.1 
percent in 1993. Freddie Mac's multifamily purchases represented 
31.5 percent of all purchases qualifying for the goal in 1997, 
compared to 5.5 percent in 1993. The trends for both GSEs were 
steadily upward throughout the five-year period.
    The other two housing categories--single-family owner and 
single-family rental--both exhibited downward trends for both GSEs. 
In 1997 Fannie Mae's single-family owner units qualifying for the 
goal represented 45.9 percent of all qualifying units, and Fannie 
Mae's single-family rental units were 10.0 percent of all qualifying 
units. Freddie Mac's single-family owner units qualifying for the 
goal represented 54.7 percent of all qualifying units, and Freddie 
Mac's single-family rental units were 13.8 percent of all qualifying 
units.
    Reliance on household relative to area characteristics to meet 
goal. Tables C.2 and C.3 also show the allocation of units 
qualifying for the goal as related to the family income and area 
median income criteria in the goal definition. Very-low-income 
families (shown in the two leftmost columns in the tables) accounted 
for 83.4 percent of Fannie Mae's units qualifying under the goal in 
1997, compared to 80.2 percent in 1993. For Freddie Mac, very-low-
income families accounted for 81.0 percent of units qualifying under 
the goal in 1997 and 80.3 percent in 1993. In contrast, mortgage 
purchases from low-income areas (shown in the first and third 
columns in the tables) accounted for 33.7 percent of Fannie Mae's 
units qualifying under the goal in 1997, compared to 36.8 percent in 
1993. The corresponding percentages for Freddie Mac were 38.3 
percent in 1997 and 36.3 percent in 1993. Thus given the definition 
of special affordable housing in terms of household and area income 
characteristics, both GSEs have consistently relied substantially 
more on low-income characteristics of households than low-income 
characteristics of census tracts to meet this goal.

c. GSEs' Performance Relative to Market

    Section E in Appendix A uses HMDA data with 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. The main 
findings are: (a) both GSEs lag depositories and the overall market 
in providing mortgage funds for very low-income and other special 
affordable borrowers; and (b) the performance of Freddie Mac was 
particularly weak compared to Fannie Mae, the depositories, and the 
overall market. For example, between 1996 and 1998, special 
affordable borrowers accounted for 9.8 percent of the home loans 
purchased by Freddie Mac, 11.9 percent of Fannie Mae's purchases, 
16.7 percent of home loans originated and retained by depositories, 
and 15.3 percent of all home loans originated in the conventional 
conforming market (see Table A.3 in Appendix A). While Freddie Mac 
has improved its performance, it has not closed the gap between its 
performance and that of the overall market. In 1992, special 
affordable loans accounted for 6.5 percent of Freddie Mac's 
purchases and 10.4 percent of market originations, for a ``Freddie-
Mac-to-market'' ratio of 0.63. By 1998, that ratio had increased 
only to 0.73 (11.3 percent versus 15.5 percent). Thus, there is room 
for Freddie Mac to improve its purchases of home loans that qualify 
for the special affordable goals.
    Section G in Appendix A discusses the role of the GSEs both in 
the overall special affordable market and in the different segments 
(single-family owner, single-family rental, and multifamily rental) 
of the special affordable market. The GSEs' special affordable 
purchases have accounted for 24 percent of all special affordable 
owner and rental units that were financed in the conventional 
conforming market during 1997. The GSEs' 24-percent share of the 
special affordable market was approximately three-fifths of their 
39-percent share of the overall market. Even in the owner market, 
where the GSEs account for 50 percent of the market, their share of 
the special affordable market was only 35 percent. This analysis 
suggests that the GSEs are not leading the single-family market in 
purchasing loans that qualify for the Special Affordable Goal. There 
is room for the GSEs to improve their performance in purchasing 
affordable loans at the lower-income end of the market.

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

    This discussion concentrates on very-low-income families with 
the greatest needs. It complements Section C of Appendix A, which 
presents detailed analyses of housing problems and demographic 
trends for lower-income families which are relevant to the issue 
addressed in this part of Appendix C.
    Data from the 1995 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 Final 
Rule. Table C.4 displays figures on several types of housing 
problems--high housing costs relative to income, physical housing 
defects, and crowding--for both owners and renters. Figures are 
presented for households experiencing multiple (two or more) of 
these problems as well as households experiencing a severe degree of 
either cost burden or physical problems. Housing problems in 1995 
were much more frequent for the lowest-income groups.\2\ Incidence 
of problems is shown for households in the income range covered by 
the special affordable goal, as well as for higher income 
households.
---------------------------------------------------------------------------

    \2\ Tabulations of the 1995 American Housing Survey by HUD's 
Office of Policy Development and Research. The results in the table 
categorize renters reporting housing assistance as having no housing 
problems.

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    This analysis shows that priority problems of severe cost burden 
or severely inadequate housing are noticeably concentrated among 
renters and owners with incomes below 60 percent of area median 
income (31.5 percent of renter households and 23.8 percent of owner 
households). In contrast, 3.5 percent of renter households and 7.1 
percent of owner households with incomes above 60 percent of area 
median income, up to 80 percent of area median income, had priority 
problems. For more than two-thirds of the very-low-income renter 
families with worst case problems, the only problem was 
affordability--they do not have problems with housing adequacy or 
crowding.

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

    The discussion of the ability of Fannie Mae and Freddie Mac to 
lead the industry in Section C.5 of Appendix A is relevant to this 
factor--the GSEs' roles in the owner and rental markets, their role 
in establishing widely-applied underwriting standards, their role in 
the development of new technology for mortgage origination, their 
strong staff resources, and their financial strength. Additional 
analysis on the potential ability of the enterprises to lead the 
industry in the low- and very-low-income market appears below--in 
Section D.2 generally, and in Section D.3 with respect to 
multifamily housing.

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

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

D. Determination of the Goal

    Several considerations, many of which are reviewed in Appendixes 
A and B and in previous sections of this Appendix, led to the 
determination of the Special Affordable Housing Goal.

1. Severe Housing Problems

    The data presented in Section C.3 demonstrate that housing 
problems and needs for affordable housing are much more pressing in 
the lowest-income categories than among moderate-income families. 
The high incidence of severe problems among the lowest-income 
renters reflects severe shortages of units affordable to those 
renters. At incomes below 60 percent of area median, 34.7 percent of 
renters and 21.6 percent of owners pay 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 pay more than 30 percent of their 
income for housing. 31.5 percent of renters and 23.8 percent of 
owners exhibit ``priority problems'', meaning housing costs over 50 
percent of income or severely inadequate housing.

2. GSE Performance and the Market

a. GSEs' Single-Family Performance

    The Special Affordable Housing Goal is designed, in part, to 
ensure that the GSEs maintain a consistent focus on serving the very 
low-income portion of the housing market where housing needs are 
greatest. The bulk of the GSEs' low- and moderate-income mortgage 
purchases are for the higher-income portion of this category. The 
lowest-income borrowers account for a relatively small percentage of 
each GSE's below-median income purchases--25.9 percent of Freddie 
Mac's 1998 single-family low-mod owner-occupied mortgage purchases 
financed homes for single-family homeowners with incomes below 60 
percent of area median; the corresponding share was 25.6 percent for 
Fannie Mae in 1998.

b. Single-Family Market Comparisons in Metropolitan Areas

    Section C compared the GSEs' performance in special affordable 
lending to the performance of depositories and other lenders in the 
conventional conforming market for single-family home loans. The 
analysis showed that both GSEs lag depositories and the overall 
market in providing mortgage funds for very low-income and other 
special affordable borrowers; and that the performance of Freddie 
Mac was particularly weak compared to Fannie Mae, the depositories, 
and the overall market. Figure C.3 illustrates these findings. In 
1998, special affordable borrowers accounted for 11.3 percent of the 
home loans purchased by Freddie Mac, 13.2 percent of Fannie Mae's 
purchases, 17.7 percent of home loans originated and retained by 
depositories, and 15.5 percent of all home loans originated in the 
conventional conforming market. Section C also notes that Freddie 
Mac has improved its performance since 1992, but it has not made as 
much progress as Fannie Mae has in closing the gap between its 
performance and that of the overall market. Thus, there is room for 
both GSEs, but particularly Freddie Mac, to improve its purchases of 
home loans that qualify for the special affordable goals.

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c. Overall Market Comparisons

    Section C compared the GSEs' role in the overall market with 
their role in the special affordable market. The GSEs' purchases 
have provided financing for 2,893,046 dwelling units, which 
represented 39 percent of the 7,443,736 single-family and 
multifamily units that were financed in the conventional conforming 
market during 1997. However, in the special affordable part of the 
market, the 508,377 units that were financed by GSE purchases 
represented only 24 percent of the 2,158,750 dwelling units that 
were financed in the market. Thus, there appears to be ample room 
for the GSEs to improve their performance in the Special Affordable 
market.

3. Reasons for Increasing the Special Affordable Housing Goal

    The reasons the Secretary is increasing the Special Affordable 
Goal are essentially the same as those given in Section H.4 of 
Appendix A for the Low- and Moderate-Income Goal. Although that 
discussion will not be repeated here, the main considerations are 
the following: Freddie Mac's re-entry into the multifamily market; 
the underlying strength of the primary mortgage market for lower-
income families; the need for the GSEs, and particularly Freddie 
Mac, to improve their purchases of mortgages for lower-income 
families and their communities; the existence of several low-income 
market segments that would benefit from more active efforts by the 
GSEs; and the substantial profits and financial capacity of Fannie 
Mae and Freddie Mac. The Department's analysis shows that the GSEs 
are not leading the market in purchasing loans that qualify for the 
Special Affordable Goal. There are also plenty of opportunities for 
the GSEs to improve their performance in purchasing special 
affordable loans. The GSEs' accounted for only 24 percent of the 
special affordable market in 1997--a figure substantially below 
their 39-percent share of the overall market.

4. Multifamily Purchases--Further Analysis

    The multifamily sector is especially important in the 
establishment of the special affordable housing goals for Fannie Mae 
and Freddie Mac because of the relatively high percentage of 
multifamily units meeting the special affordable goal as compared 
with single-family. In 1997, 57 percent of units backing Freddie 
Mac's multifamily acquisitions met the special affordable goal, 
representing 31 percent of units counted toward its special 
affordable goal, at a time when multifamily units represented only 8 
percent of total annual purchase volume. Corresponding percentages 
for Fannie Mae were as follows: 54 percent of units backing 
multifamily acquisitions met the special affordable goal; 
multifamily represented 44 percent of units meeting the special 
affordable goal but only 13 percent of total purchase volume.\3\
---------------------------------------------------------------------------

    \3\ Source: HUD analysis of GSE loan-level data. Loans with 
missing data are excluded from the calculations of the special 
affordable proportions of multifamily and the multifamily proportion 
of special affordable.
---------------------------------------------------------------------------

    Significant new developments in the multifamily mortgage market 
have occurred since the publication of the current version of the 
GSE Final Rule in December 1995, most notably the increased rate of 
debt securitization via Commercial Mortgage Backed Securities (CMBS) 
and a higher level of equity securitization by Real Estate 
Investment Trusts (REITs). Fannie Mae has played a role in 
establishing underwriting standards that have been widely emulated 
in the growth of the CMBS market. Freddie Mac has contributed to the 
growth and stability of the CMBS sector by acting as an investor.
    Increased securitization of debt and equity interests in 
multifamily property present the GSEs with new challenges as well as 
new opportunities. The GSEs are currently experiencing a higher 
degree of secondary market competition than they did in 1995. At the 
same time, recent volatility in the CMBS market underlines the need 
for an ongoing GSE presence in the multifamily secondary market. The 
potential for an increased GSE presence is enhanced by virtue of the 
fact that an increasing proportion of multifamily mortgages are 
originated to secondary market standards.
    Despite the expanded presence of the GSEs in the multifamily 
mortgage market and the rapid growth in multifamily securitization 
by means of CMBS, increased secondary market liquidity does not 
appear to have benefited all segments of the market equally. Small 
properties with 5-50 units appear to have been adversely affected by 
excessive borrowing costs as described in Appendix A. Another market 
segment that appears experiencing difficulty in obtaining mortgage 
credit consists of multifamily properties with significant 
rehabilitation needs. Properties that are more than 10 years old are 
typically classified as ``C'' or ``D'' properties, and are 
considered less attractive than newer properties by many lenders and 
investors
    Context. As discussed above, in the 1995 Final Rule, the 
multifamily subgoal for the 1996-1999 period was set at 0.8 percent 
of the dollar value of each GSEs' respective 1994 origination 
volume, or $998 million for Freddie Mac and $1.29 billion for Fannie 
Mae. Freddie Mac exceeded the goal by a narrow margin in 1996 and 
more comfortably in 1997-1998. Fannie Mae has exceeded the goal by a 
wide margin in all three years.
    The experience of the past two years suggests the following 
preliminary findings regarding the multifamily special affordable 
subgoal:
    The goal has contributed toward a significantly increased 
presence by Freddie Mac in the multifamily market.
    Fannie Mae's performance has surpassed the goal by such a wide 
margin that it can be reasonably inferred that the goal has little 
effect on their behavior.
     The current goal is out of date, as it is based on 
market conditions in 1993-94.
     The goal has remained at a fixed level, despite 
significant growth in the multifamily market and in the GSEs' 
administrative capabilities with regard to multifamily.
     Given that the GSEs have relatively large fixed costs 
in purchasing multifamily loans, the minimum cost method of meeting 
the goal involves purchasing a relatively small number of mortgages, 
each with a relatively large UPB. Thus the goal may provide the GSEs 
with an additional incentive to purchase mortgages on large 
properties.
    HUD's proposed rule establishes the multifamily subgoal at 0.9 
percent of the dollar volume of combined (single family and 
multifamily) 1998 mortgage purchases in calendar year 2000, and 1.0 
percent in each of calendar years 2001-2003. This implies the 
following thresholds for the two GSEs: \4\
---------------------------------------------------------------------------

    \4\ HUD has determined that the total dollar volume of the GSEs' 
combined (single and multifamily) mortgage purchases in 1998, 
measured in unpaid principal balance at acquisition, was as follows: 
Fannie Mae $367.6 billion; Freddie Mac $273.2 billion.

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

    The proposed subgoal can be compared with Fannie Mae's and 
Freddie Mac's 1998 multifamily special affordable multifamily 
acquisition volumes of $3.5 billion and $2.7 billion, 
respectively.\5\ A 1.0 percent dollar-based multifamily subgoal for 
2001-2003 would sustain and likely increase the efforts of both GSEs 
in the multifamily mortgage market, with particular emphasis upon 
the special affordable segment.
---------------------------------------------------------------------------

    \5\ HUD analysis of GSE loan-level data.
---------------------------------------------------------------------------

    HUD has identified three alternative approaches for specifying 
multifamily subgoals for the GSEs, as follows:
    (1) Option One--Subgoal Based on Number of Units. In this 
approach, the multifamily special affordable subgoal would be 
expressed as a minimum number of units meeting the Special 
Affordable Housing Goal. A multifamily subgoal for 2001-2003 
established at the level of the dollar-based subgoal defined above, 
divided by $22,953, which is the average of Fannie Mae's and Freddie 
Mac's ratios of unpaid principal balance to number of units in 
multifamily properties counted toward the Special Affordable Housing 
Goal in 1997 (as

[[Page 12767]]

determined by HUD) would generate annual multifamily special 
affordable subgoals of 160,328 units for Fannie Mae and 118,939 
units for Freddie Mac. These compare with Fannie Mae's multifamily 
special affordable multifamily acquisition volumes of 130,374 units 
in 1997 and 138,822 units in 1998, and Freddie Mac's performance of 
56,255 units in 1997 and 120,776 units in 1998.\6\ Such a 
multifamily subgoal for 2001-2003 would sustain and likely increase 
the efforts of both GSEs in the multifamily mortgage market, with 
particular emphasis upon the special affordable segment.\7\
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    \6\ Source: HUD analysis of GSE loan-level data. Fannie Mae's 
1998 performance figures may not fully reflect its multifamily 
special affordable acquisition capabilities because Fannie Mae did 
not obtain data necessary to qualify many of their multifamily 
seasoned loan purchases for the special affordable goal.
    \7\ If this option were selected, appropriate subgoal thresholds 
for the year 2000 transition period could be developed.
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    (2) Option Two--Subgoal As A Percent of GSEs' Current 
Multifamily Mortgage Purchases. Another possible approach is to 
establish the special affordable multifamily subgoal as a minimum 
percentage of each GSE's current total dollar volume of multifamily 
mortgage purchases. For example, the subgoal level for 2001-2003 
could be expressed as 58.0 percent of a GSE's multifamily dollar 
volume. The 58.0 percent threshold under this subgoal option 
compares with 1997 performance of 54.2 percent for Fannie Mae and 
56.6 percent for Freddie Mac.\8\ A 58.0 percent multifamily subgoal 
for 2001-2003 would sustain and likely increase the efforts of both 
GSEs in the special affordable segment of the multifamily mortgage 
market.\9\
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    \8\ Source: HUD analysis of GSE loan-level data. 1997 figures 
are used here because the share of Fannie Mae's multifamily 
acquisitions meeting the special affordable goal is unusually low in 
1998 as noted above because Fannie Mae did not verify whether 
proceeds of seasoned multifamily loans it acquired were ``recycled'' 
into new lending per FHEFSSA requirements.
    \9\ If this option were selected, appropriate subgoal thresholds 
for the year 2000 transition period could be developed.
---------------------------------------------------------------------------

    (3) Option Three--Subgoal Based on Number of Mortgages Acquired. 
Because the GSEs incur relatively large fixed costs in purchasing 
multifamily mortgage loans, another alternative to the Special 
Affordable Multifamily Housing Subgoal would be to establish a 
subgoal that would be based on the number of mortgages acquired. In 
this approach, the Special Affordable multifamily subgoal would be 
expressed as a minimum number of each GSEs' total mortgage 
purchases. If all the units in the property securing the mortgage 
are not eligible for the Special Affordable Housing Goal, then 
subgoal performance would be pro-rated based on the number of 
qualifying units. In other words, if one mortgage secured a 100-unit 
property and 50 of the units qualified for the Special Affordable 
Housing Goal, then subgoal credit would be counted as one-half of a 
mortgage.\10\
---------------------------------------------------------------------------

    \10\ A similar pro-rating technique is specified in HUD's 
regulations at 24 CFR, Section 81.14(d)(2), for purposes of 
calculating credit toward the multifamily special affordable 
subgoal. Specifically, the mortgage loan amount is multiplied by the 
proportion of units qualifying toward the special affordable goal.
---------------------------------------------------------------------------

    A multifamily subgoal for 2001-2003 established at 0.035 percent 
of 1997 combined single-family and multifamily purchase dollar 
volume in number of mortgages acquired (as determined by HUD) would 
generate annual subgoals of 1,129 multifamily special affordable 
mortgages for Fannie Mae and 854 for Freddie Mac.\11\ A 0.035 
percent mortgage-based multifamily subgoal for 2001-2003 would 
sustain and likely increase the efforts of both GSEs in the 
multifamily mortgage market, with particular emphasis upon the 
special affordable segment.\12\
---------------------------------------------------------------------------

    \11\ HUD has determined that the number of mortgage loans 
purchased by the GSEs in 1998 was as follows: Fannie Mae--3,226,786; 
Freddie Mac--2,439,194.
    \12\ If this option were selected, appropriate subgoal 
thresholds for the year 2000 transition period could be developed.
---------------------------------------------------------------------------

    The preamble to this Proposed Rule includes a more complete 
analysis of these alternatives, with a request for public comments 
on the alternatives.

5. Conclusion

    HUD has determined that the proposed Special Affordable Housing 
Goal 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 18 percent in 2000, and 20 
percent in 2001-2003, is both necessary and achievable. HUD has also 
determined that a multifamily special affordable subgoal set at 0.9 
percent of the dollar volume of combined (single family and 
multifamily) 1998 mortgage purchases in 2000, and 1.0 percent in 
2001-2003, or one of the alternatives proposed here, is both 
necessary and achievable.

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 introduction, 
Section B describes 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 
rental properties. With this as background, 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 Central Cities, Rural Areas, and 
other Underserved Areas Goal, and the Special Affordable Housing 
Goal, respectively. Finally, Section I examines the impact of higher 
FHA loan limits on the conventional market.
    In developing this rule, HUD has carefully reviewed existing 
information on mortgage activity in order to understand the weakness 
of various data sources and has conducted sensitivity analyses to 
show the effects of alternative parameter assumptions. Data on the 
multifamily mortgage market from HUD's Property Owners and Managers' 
Survey (POMS), not available at the time published the 1995 GSE 
Final Rule, is utilized here. HUD is well aware of uncertainties 
with some of the data and much of this Appendix is spent discussing 
the effects of alternative assumptions about data parameters and 
presenting the results of an extensive set of sensitivity analyses.
    In a critique of HUD's market share model, Blackley and Follain 
(1995, 1996) concluded that conceptually HUD had chosen a reasonable 
approach to determining the size of the mortgage market that 
qualifies for each of the three housing goals.\1\ Blackley and 
Follain correctly note that the challenge lies in getting accurate 
estimates of the model's parameters.
---------------------------------------------------------------------------

    \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.
---------------------------------------------------------------------------

    This appendix reviews in some detail HUD's efforts to combine 
information from several mortgage market data bases to obtain 
reasonable values for the model's parameters. Numerous sensitivity 
analyses are performed in order to arrive at a set of reasonable 
market estimates.
    The single-family market analysis in this appendix is based 
heavily on HMDA data for the years 1992 to 1998. The HMDA data for 
1998 were not released until August 1999, which gave HUD little time 
to incorporate that data fully into the analyses reported in these 
Appendices; thus, the discussion below will often focus on the year 
1997, with any differences from 1998 briefly noted. However, it 
should be noted that the year 1997 represents a more typical 
mortgage market than the heavy refinancing year of 1998. Still, 
important shifts in mortgage funding that occurred during 1998 will 
be highlighted in order to offer as complete and updated analysis as 
possible.

B. Overview of HUD's Market Share Methodology

1. Definition

    The size of the market for each housing goal is one of the 
factors that the Secretary

[[Page 12768]]

is required to consider when setting the level of each housing 
goal.\2\ Using the Low- and Moderate-Income Housing Goal as an 
example, the market share in a particular year is defined as 
follows:

    \2\ 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.\3\ 
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).
---------------------------------------------------------------------------

    \3\ So-called ``jumbo'' mortgages, greater than $227,150 in 1998 
for 1-unit properties, are excluded in defining the conforming 
market. There is some overlap of loans eligible for purchase by the 
GSEs with loans insured by the FHA and guaranteed by the Veterans 
Administration.
---------------------------------------------------------------------------

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:
    (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); \4\
---------------------------------------------------------------------------

    \4\ 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).\5\
---------------------------------------------------------------------------

    \5\ 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 by the 
following illustration of Step 3's basic formula for calculating the 
size of the low- and moderate-income market: \6\
---------------------------------------------------------------------------

    \6\ 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.

----------------------------------------------------------------------------------------------------------------
                                                                     (Step 1)                        (Step 3)
                                                                     share  of    (Step 2)  low-   multiply  (1)
                          Property type                               market        mod  share         x (2)
                                                                     (percent)       (percent)       (percent)
----------------------------------------------------------------------------------------------------------------
(a) SF-0........................................................            71.1            40.0            28.4
(b) SF 2-4......................................................             2.0            90.0             1.8
(c) SF Investor.................................................            10.7            90.0             9.6
(d) MF..........................................................            16.2            90.0            14.6
                                                                 -----------------------------------------------
      Total Market..............................................           100.0                            54.4
----------------------------------------------------------------------------------------------------------------

In this example, low- and moderate-income dwelling units are 
estimated to account for 54 percent of the total number of dwelling 
units financed in the conforming mortgage market. 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 
Central Cities, Rural Areas, and Other Underserved Areas Goal \7\ 
would be derived as follows under one set of assumptions:
---------------------------------------------------------------------------

    \7\ This goal will be referred to as the ``Underserved Areas 
Goal''.

----------------------------------------------------------------------------------------------------------------
                                                                     (Step 1)        (Step 2)        (Step 3)
                                                                     share  of      underserved    multiply  (1)
                          Property Type                               market        area  share        x (2)
                                                                     (percent)       (percent)       (percent)
----------------------------------------------------------------------------------------------------------------
(a) SF-0........................................................            71.1            25.0            17.8
(b) SF 2-4......................................................             2.0            42.5             0.9
(c) SF Investor.................................................            10.7            42.5             4.5
(d) MF..........................................................            16.2            48.0             7.8
                                                                 -----------------------------------------------
      Total Market..............................................           100.0                            31.0
----------------------------------------------------------------------------------------------------------------

In this example, units eligible under the Underserved Areas Goal are 
estimated to account for 31 percent of the total number of dwelling 
units financed in the conforming mortgage market.

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

[[Page 12769]]

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, are based 
on HUD's SMLA. The SMLA does not provide information on conforming 
mortgages, on owner versus renter mortgages, or on the number of 
units financed. Thus, to estimate the number of single-family units 
financed in the conforming conventional market, HUD had to project 
certain market parameters based on its judgment about the 
reliability of different data sources. Sections D and E report HUD's 
findings related to the single-family market.
    Total market originations are obtained by adding multifamily 
originations to the single-family estimate. Because of the wide 
range of estimates available, the size of the multifamily mortgage 
market turned out to be one of the most controversial issues raised 
during the 1995 rule-making process. In 1997, HMDA reported about 
$20.0 billion in multifamily originations while the SMLA reported 
more than double that amount ($47.9 billion). Because most renters 
qualify under the Low- and Moderate-Income Goal, the chosen market 
size for multifamily can have a substantial effect on the overall 
estimate of the low- and moderate-income market (as well as on the 
estimate of the special affordable market). Thus, it is important to 
consider estimates of the size of the multifamily market in some 
detail, as Section C does. In addition, given the uncertainty 
surrounding estimates of the multifamily mortgage market, it is 
important to consider a range of market estimates, as Sections G-H 
do.
    Goal Percentages. To derive the goal percentages for each 
property type, HUD relied heavily on HMDA, AHS, and POMS data. For 
single-family owner originations, HMDA provides comprehensive 
information on borrower incomes and census tract locations for 
metropolitan areas. Unfortunately, it provides no information on the 
incomes of renters living in mortgaged properties (either single-
family or multifamily) or on the rents (and therefore the 
affordability) of rental units in mortgaged properties. The AHS, 
however, does provide a wealth of information on rents and the 
affordability of the outstanding stock of single-family and 
multifamily rental properties. An important issue here concerns 
whether rent data for the stock of rental properties can serve as a 
proxy for rents on newly-mortgaged rental properties. The POMS data, 
which were not available during the 1995 rule-making process, are 
used below to examine the rents of newly-mortgaged rental 
properties; thus, the POMS data supplements the AHS data. The data 
base issues as well as other technical issues related to the goal 
percentages (such as the need to consider a range of mortgage market 
environments) are discussed in Sections F, G, and H, which present 
the market share estimates for the Low- and Moderate-Income Goal, 
the Underserved Areas Goal, and the Special Affordable Goal, 
respectively.

4. Conclusions

    HUD is using the same basic methodology for estimating market 
shares that it used during 1995. As demonstrated in the remainder of 
this Appendix, HUD has attempted to reduce the range of uncertainty 
around its market estimates by carefully reviewing all known major 
mortgage data sources and by conducting numerous sensitivity 
analyses to show the effects of alternative assumptions. Sections C, 
D, and E report findings related to the property share distributions 
called for in Step 1, while Sections F, G, and H report findings 
related to the goal-specific market parameters called for in Step 2. 
These latter sections also report the overall market estimates for 
each housing goal calculated in Step 3.
    During the 1995 rule-making process, HUD contracted with the 
Urban Institute to comment on the reasonableness of its market share 
approach and to conduct analyses related to specific comments 
received from the public about its market share methodology. HUD 
continues to rely on several findings from the Urban Institute 
reports and they are again discussed throughout this Appendix. Since 
1995, HUD has continued to examine the reliability of data sources 
about mortgage activity. HUD's Office of Policy Development and 
Research has published several studies concerning the reliability of 
HMDA data.\8\ In addition, since 1995, HUD has gathered additional 
information regarding the mortgages for multifamily and single-
family rental properties through the Property Owners and Managers 
Survey (POMS). Findings regarding the magnitude of multifamily 
originations, as well as the rent and affordability characteristics 
of mortgages backing both single-family and multifamily rental 
properties have been made by combining data from POMS with that from 
internal Census Bureau files from the 1995 American Housing Survey-
National Sample. The results of these more recent analyses will be 
presented in the following sections.
---------------------------------------------------------------------------

    \8\ See Randall M. Scheessele, HMDA Coverage of the Mortgage 
Market, Housing Finance Working Paper No. 7, Office of Policy 
Development and Research, Department of Housing and Urban 
Development, July 1998; and 1998 HMDA Highlights, Housing Finance 
Working Paper No. HF-009, Office of Policy Development and Research, 
Department of Housing and Urban Development, October 1999.
---------------------------------------------------------------------------

C. Size of the Conventional Multifamily Mortgage Market

    This section derives projections of conventional multifamily 
mortgage origination volume.\9\
    The multifamily sector is especially important in the 
establishment of housing goals for Fannie Mae and Freddie Mac 
because multifamily properties are overwhelmingly occupied by low- 
and moderate-income families. For example, in 1997, 13 percent of 
units financed by Fannie Mae were multifamily, but 90 percent of 
those units met the Low- and Moderate-Income Goal, accounting for 27 
percent of all of Fannie Mae's low- and moderate-income purchases 
for that year.\10\ Multifamily acquisitions are also of strategic 
significance with regard to the Special Affordable Goal. In 1997, 57 
percent of units backing Freddie Mac's multifamily acquisitions met 
the Special Affordable Goal, representing 31 percent of units 
counted toward its Special Affordable Goal, at a time when 
multifamily units represented only 8 percent of total annual 
purchase volume.\11\
---------------------------------------------------------------------------

    \9\ Because they are not counted toward the GSE housing goals 
(with the exception of a relatively small risk-sharing program), FHA 
mortgages are excluded from this analysis. Other categories of 
mortgages, considering the type of insurer, servicer, or holder, do 
not tend to have mortgage characteristics that appear to differ 
substantially from the multifamily mortgages that are purchased by 
Fannie Mae and Freddie Mac. There is thus no particular basis for 
excluding them.
    \10\ Corresponding percentages for Freddie Mac were 95 percent 
and 19 percent. Missing data are excluded from these calculations. 
Source: Annual Housing Activity Reports, 1997.
    \11\ Corresponding percentages for Fannie Mae were 54 percent 
and 44 percent.
---------------------------------------------------------------------------

    This discussion is organized as follows: Section 1 identifies 
and evaluates available historical data resources. Section 2 
undertakes an analysis of estimated conforming multifamily 
origination volume for 1995 through 1998. Section 3 establishes 
projections regarding conventional multifamily origination volume 
for the year 2000 and beyond.

1. Conventional multifamily origination volumes, 1987-1997

    Two of the principal sources of evidence on conventional 
multifamily origination volumes are Home Mortgage Disclosure Act 
data base (HMDA) and the HUD Survey of Mortgage Lending Activity 
(SMLA).

a. Survey of Mortgage Lending Activity (SMLA)

    The data that enter into SMLA are compiled by HUD from source 
materials generated in various ways from the different institutional 
types of mortgage lenders. Data on savings associations are 
collected for HUD by the Office of Thrift Supervision; these data 
cover all thrifts, not a sample. Mortgage company and life insurance 
company data are collected through sample surveys conducted by the 
Mortgage Bankers Association of America and the American Council of 
Life Insurance, respectively. Data on commercial banks and mutual 
savings banks are collected through sample surveys conducted by the 
American Bankers Association. The Federal credit agencies and State 
credit agencies report their data directly to HUD. Local credit 
agency data are collected by HUD staff from a publication that lists 
their mortgage financing activities.

b. Home Mortgage Disclosure Act (HMDA)

    HMDA data are collected by lending institutions and reported to 
their respective regulators as required by law. HMDA was

[[Page 12770]]

enacted as a mechanism to permit the public to determine locations 
of properties on which local depository institutions make mortgage 
loans, ``to enable them to determine whether depository institutions 
are filling their obligations to serve the housing needs of the 
communities and neighborhoods in which they are located. . .'' (12 
USC 2801). HMDA reporting requirements generally apply to all 
depository lenders with more than $29 million in total assets and 
which have offices in Metropolitan Statistical Areas. Reporting is 
generally required of other mortgage lending institutions (e.g. 
mortgage bankers) originating at least 100 home purchase loans 
annually provided that home purchase loan originations exceed 10 
percent of total loans. Reporting is required for all loans closed 
in the name of the lending institution and loans approved and later 
acquired by the lending institution, including multifamily loans. 
Thus, the HMDA data base concentrates on lending by depository 
institutions in metropolitan areas but, unlike SMLA and RFS, it is 
not a sample survey; it is intended to include loan-level data on 
all loans made by the institutions that are required to file 
reports.
    Table D.1 presents figures for 1987 through 1997 for SMLA and 
HMDA.\12\ The main question raised by this comparison is why SMLA 
and HMDA report such different multifamily estimates. Part of the 
problem arises from double-counting of originations by mortgage 
banks in the American Bankers Association (ABA) and Mortgage Bankers 
Association (MBA) surveys conducted as part of SMLA. Originations by 
mortgage banks which are affiliated with commercial banks may be 
counted in both surveys.
---------------------------------------------------------------------------

    \12\ The comparison between SMLA and HMDA is provided only 
through 1997 because 1998 SMLA data were not available as of the 
time of this writing.
---------------------------------------------------------------------------

    There is also evidence that undercounting of multifamily 
originations in HMDA contributes to observed discrepancies between 
HMDA and SMLA. For example, less than half of Fannie Mae's 1997 
acquisition volume of mortgages originated in 1997 are reported in 
HMDA. HMDA reports that Freddie Mac purchased 14 loans from mortgage 
banks in 1997, yet in loan-level data provided to HUD, Freddie Mac 
indicates that purchased 453 loans from mortgage bankers.\13\ 
Further evidence of the poor quality of the HMDA multifamily data is 
the fact that it reported that in 1997 a larger volume of 
multifamily loans were sold to Freddie Mac than to Fannie Mae, when 
in fact Freddie Mac's purchases were less than that of Fannie Mae's, 
based on loan-level data provided by the GSEs to HUD.
---------------------------------------------------------------------------

    \13\ Some of loans in the GSE data may have been originated 
prior to 1997, and therefore not included in 1997 HMDA totals. 
However, because mortgage banks ordinarily do not hold mortgages in 
portfolio, it is implausible that a majority of Freddie Mac's 
purchases from mortgage banks were originated prior to 1997.

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

[[Page 12771]]

[GRAPHIC] [TIFF OMITTED] TP09MR00.041

BILLING CODE 4210-27-C

[[Page 12772]]

    In addition, the HMDA data base does not cover a number of 
important categories of multifamily lenders such as life insurance 
companies and State housing finance agencies, providing another 
reason that the HMDA data understates the size of the multifamily 
market.
    With this in mind, we proceed to an examination of origination 
volumes reported by these two data sources by type of lender. Table 
D.2 shows the basic figures. The columns headed ``SMLA'' and 
``HMDA'' show aggregate dollar volumes of loan originations by 
category of originator in 1997.
    In 1995, the Urban Institute conducted extensive analysis to 
address the issue of discrepancies between HMDA and SMLA. The 
researchers found that the 1993 SMLA multifamily figure ($30 billion 
in conventional originations) was too high, chiefly because of 
upward bias in the commercial bank originations figure, and the HMDA 
estimate ($12.8 billion) was too low for a variety of reasons 
including the omission of some categories of lenders.\14\
---------------------------------------------------------------------------

    \14\ Amy D. Crews, Robert M. Dunsky, and James R. Follain, 
``What We Know about Multifamily Mortgage Originations,'' report for 
the U.S. Department of Housing and Urban Development, October 1995.
---------------------------------------------------------------------------

2. Alternative Measures

    The inconsistencies between SMLA and HMDA underscore the 
importance of finding other ways to measure the size of the 
conventional multifamily market. The remainder of this discussion 
analyzes alternative measures based on (a) analysis of the HUD 
Property Owners and Managers Survey (POMS); (b) a statistical model 
developed by Urban Institute researchers; and (c) combining data 
from a variety of sources in a manner that avoids double-counting.

a. HUD Property Owners and Managers Survey (POMS)

    HUD's analysis of data in the HUD Property Owners and Managers 
Survey (POMS) yields an estimated size of the 1995 multifamily 
origination market of approximately $37 billion. Analysis of this 
survey data is complicated by virtue of the fact that data on 
mortgage loan amount are missing for a large number of properties, 
requiring the imputation of missing values, and also because the 
mortgage loan amount is ``topcoded'' on some observations in order 
to protect the privacy of respondents. Such topcoding complicates 
the use of multiple regression techniques for imputation of missing 
values. In order to more effectively utilize regression techniques, 
HUD staff and contractors were sworn in as special employees of the 
Census Bureau in order to gain access to the internal Census file. 
The regression specification with the greatest explanatory power 
imputed missing loan amounts on the basis of number of units, region 
of the country, and a dummy variable for large properties with more 
than 1,000 units.\15\ The use of this specification yielded an 
estimated total multifamily market size of $39.1 billion. After 
subtracting $2.3 billion in FHA-insured originations, this yields 
$36.7 billion as the estimated size of the conforming multifamily 
mortgage market in 1995, compared with the SMLA figure of $37.9 
billion and the HMDA figure of $12.8 billion.\16\ These results 
suggest that SMLA figures more accurately represent the overall size 
of the conventional multifamily mortgage market than does HMDA.
---------------------------------------------------------------------------

    \15\ R2, a measure of the degree to which the 
regression specification explains the variation in mortgage loan 
amount for observations where this field was populated, was 0.69 for 
this specification.
    \16\ FHA volume for 1995 is from U.S. Housing Market Conditions, 
1998:4, Table 15.
---------------------------------------------------------------------------

b. Urban Institute Statistical Model

    In 1995, Urban Institute researchers developed a model to 
project multifamily origination volumes from 1992 forward, based on 
data from the 1991 Survey of Residential Finance. \17\ They applied 
a statistical model of mortgage terminations based on Freddie Mac's 
experience from the mid-1970s to around 1990. While mortgage 
characteristics in 1990 are not wholly similar to the 
characteristics of these historical mortgages financed by Freddie 
Mac, nevertheless the prepayment propensities of contemporary 
mortgages may at least be approximated by the prepayment experience 
of these historical mortgages. The research methodology took account 
of the influence of interest rate fluctuations on prepayments of the 
historical mortgages; the projections assumed that prepayments are 
motivated mainly by property sales. Forecast total mortgage 
origination volume (including FHA) based on mortgages existing in 
1991 were $40.8 billion for 1995. After removing FHA-insured loans 
totaling $2.3 billion, this method yields $38.5 billion as the 
estimated size of the conforming multifamily mortgage market. The 
latter figure is closer to the $36.7 billion POMS estimate and the 
$37.9 billion SMLA figure than to the $12.8 billion HMDA number.
---------------------------------------------------------------------------

    \17\ Robert Dunsky, James R. Follain, and Jan Ondrich, ``An 
Alternative Methodology to Estimate the Volume of Multifamily 
Mortgage Originations,'' report for the U.S. Department of Housing 
and Urban Development, October 1995.
---------------------------------------------------------------------------

    Turning to 1997, the Urban Institute model generates a 
prediction of $47.2 billion. After removing $3.3 billion in FHA-
insured originations, this generates an estimated conventional 
multifamily market figure of $43.9 billion, indicating that actual 
1997 conventional origination volume may be closer to the $44.6 
billion SMLA figure than to the $19.5 billion HMDA number cited 
earlier.

c. Alternative Approach

    The increased availability of data on mortgages originated for 
the securitization market suggests yet another alternative method of 
deriving a rough estimate of the size of the conventional 
multifamily market as a further check on the accuracy of estimates 
derived from SMLA, HMDA, POMS, and the Urban Institute model. Total 
conventional multifamily volume can be estimated as the sum of (i) 
conventional nonagency (non-FHA, non-GSE) securitization; (ii) 
commercial bank originations less securitizations and secondary 
market sales or current-year and seasoned loans in portfolio; and 
(iii) GSE acquisitions. These data are from data published annually 
by Inside MBS & ABS, a trade newsletter; SMLA, and the loan-level 
data provided by the GSEs to the Department. Annual commercial bank 
securitization volume was calculated from a database published by 
Commercial Mortgage Alert, another trade newsletter.
    Perhaps the most significant potential shortcoming of this 
approach is that nonagency securitization and GSE acquisitions 
include seasoned loans that are originated in years prior to those 
in which they are securitized or purchased on the secondary market. 
It is assumed here that seasoned loan transaction volume is 
relatively constant, in absolute volume, from year to year, which 
implies that the inclusion of seasoned loans will not bias the 
results. For example, some non-bank loans originated in 1996 will 
not be counted under the method proposed here until they are 
securitized, or purchased by a GSE, in 1997, but a similar volume of 
1995 originations are not securitized or sold on the secondary 
market until 1996.\18\ Hence the above technique generates a useful 
approximation to actual 1996 origination volume. A similar argument 
applies to other years.
---------------------------------------------------------------------------

    \18\ Loans originated by banks in 1996 and then sold on the 
secondary market in 1997 would count only toward the 1996 total. 
Such loans would count toward the 1996 total because these loans 
would be counted in 1996 commercial bank originations less sales per 
the SMLA, since they are not sold in 1996. In 1997, when they are 
sold on the secondary market, such loans would be added to either 
the GSE acquisition or nonagency securitization totals, but would be 
subtracted from commercial bank originations less loan sales per the 
SMLA. The net effect of adding such loans to the GSE/nonagency 
categories and subtracting them from the commercial bank category is 
that they would not be counted toward the 1997 total.
---------------------------------------------------------------------------

    It can also be argued that the SMLA commercial bank figure 
includes some originations by mortgage banks because of the double-
counting issue discussed previously. It is assumed that these are 
removed when securitizations and secondary market sales are 
subtracted. This problem aside, the SMLA commercial bank figure 
appears to be derived using a new, and relatively carefully designed 
stratified survey, and therefore may be considered fairly reliable 
when used in the manner proposed here.
    This method does not consider unsecuritized acquisitions by 
thrifts, life insurance companies, and other smaller entities in the 
multifamily mortgage market. In this regard, this method provides a 
conservative estimate of the size of the conventional multifamily 
market.
    This method generates the following results for multifamily 
conventional origination volume for 1995-1997:

1995--$32.3 billion
1996--$37.2 billion
1997--$40.7 billion

The 1995 and 1997 estimates can be compared with the following 
estimates discussed previously.

[[Page 12773]]



------------------------------------------------------------------------
                                               1995            1997
                                            (billions)      (billions)
------------------------------------------------------------------------
Urban Institute.........................           $38.5           $47.2
POMS....................................            36.7
SMLA figure.............................            37.9            44.6
HMDA....................................            12.8            19.5
Alternative Approach....................            32.3            40.7
------------------------------------------------------------------------

The market estimates based on securitization data are thus somewhat 
lower that those derived from the POMS and SMLA surveys and by the 
Urban Institute model, but are considerably higher than those 
derived from HMDA.
    In discussions with HUD staff, Fannie Mae has put the estimated 
size of the 1997 conforming multifamily market at approximately $35-
$40 billion, based upon a combination of various data sources. This 
range is slightly more conservative than the $40.7 million figure 
derived here using securitization, GSE, and ABA data.
    Preliminary indications suggest that multifamily origination 
volume in 1998 is unusually high. Unfortunately, 1998 SMLA data were 
not yet available as of the time of this writing. If 1997 SMLA data 
are used as a proxy for 1998 multifamily commercial bank 
originations, and added to nonagency securitization and GSE 
acquisitions (which were available), a figure of $59.2 billion can 
be derived. In written comments provided to HUD in early 1999, in 
contrast, Fannie Mae asserted that 1998 multifamily volume was 
approximately $38-43 billion. In a meeting with HUD staff, Freddie 
Mac staff provided an estimate of $40-50 billion. Given the 
uncertainty regarding 1998 origination activity as of the time of 
this writing, an adjusted figure of $50 billion may be used on an 
interim basis until further data becomes available.\19\
---------------------------------------------------------------------------

    \19\ The Urban Institute model predicts $50 billion for the 
entire 1998 multifamily market, including FHA.
---------------------------------------------------------------------------

3. Projections for 2000 and Beyond

    Considerations influencing future multifamily origination volume 
include interest rates, property values, and construction starts. 
Taking all of these factors into consideration, Fannie Mae forecasts 
of a 10 percent decrease in 1999 relative to 1998 followed by a 2 
percent increase in 2000, included in comments provided to the 
Department, appear reasonable. \20\
---------------------------------------------------------------------------

    \20\ Multifamily interest rates increased in September, 1998 as 
part of a broader ``flight to quality'' precipitated by volatility 
in the world economy. While CMBS spreads were the most strongly 
affected, agency yield spreads also widened during this period. 
Further detail is provided in Appendix A. ``Expectations may have 
begun to adjust downward even before the recent troubles in the 
financial markets'' according to ``The Multifamily Outlook,'' Jack 
Goodman, Urban Land, November 1998. p. 92. The CMBS market, of which 
approximately 25 percent is multifamily, is expected by Morgan 
Stanley to fall from approximately $80 billion in 1998 to $50 
billion in 1999 (``A Cloudy '99 for Subprime Lenders, HELs, CMBS,'' 
Mortgage Backed Securities Letter, January 4, 1999, p. 1). 
Donaldson, Lufkin & Jenrette anticipates a decrease from $76 billion 
to $55 billion (March Hochstein, ``Commercial Mortgage Bond Issuance 
Seen Falling,'' American Banker, December 22, 1998, p. 2). To the 
extent that multifamily origination volume falls in late 1999 
associated with concerns regarding Y2K, the contraction in lending 
volume from 1998 to 1999 could exceed 10 percent. This possibility 
is taken into consideration here by providing a range of estimates 
for year 2000 origination volume as discussed below.
---------------------------------------------------------------------------

    If these projections regarding 1999 and year 2000 origination 
volume are applied to the Department's of $50 billion estimate of 
1998 conventional multifamily origination volume, a projection of 
$46 billion in year 2000 volume can be derived. Alternatively, if 
1998 origination volume is in the $38-43 billion range indicated by 
Fannie Mae, year 2000 conventional origination volume is expected to 
lie in the $35-$40 billion range. On the other hand, if 1998 
origination volume reached $59 billion, the high end of the 
estimates discussed previously, year 2000 volume could be as high as 
$54 billion. Turning to the Urban Institute statistical model 
discussed earlier, total multifamily originations (including FHA) 
are projected to reach $54 billion in 2000. After removing $2.9 
billion in anticipated FHA-insured originations, this leaves 
projected conventional volume of $51.1 billion.\21\
---------------------------------------------------------------------------

    \21\ Projected year 2000 FHA volume was calculated as the mean 
of 1997 and 1998 volume pursuant to discussions with staff in HUD's 
Housing Finance Analysis Division.
---------------------------------------------------------------------------

    Taking all of these estimates into consideration, year 2000 
multifamily conventional origination volume is likely to lie in the 
$40-$52 billion range, with an expected ``baseline'' value of $46 
billion.
    Average Loan Amounts. Another issue regarding the multifamily 
mortgage market concerns average loan amount per unit. This ratio is 
used in converting year-2000 estimates of conventional multifamily 
lending volume as measured in dollars into a number of units 
financed. For this purpose, the ratio of total UPB to total units 
financed, rather than UPB on a ``typical'' multifamily unit, is the 
appropriate measure.
    HUD anticipates overall conventional multifamily loan amount per 
unit of $30,000 in the year 2000 based on analysis of newly-
originated GSE and non-GSE multifamily mortgage loans. GSE figures 
on loan amount per unit can be obtained from GSE loan-level data 
provided to HUD. Non-GSE loan amount per unit figures are from HUD's 
analysis of recently-originated conventional non-GSE multifamily 
mortgages. \22\ Combining these sources, and calculating a weighted 
average based on relative market shares yields an estimated UPB per 
unit of $25,167 in 1997 and $29,506 in 1998. The increase from 1997-
1998 appears to be largely due to a significant increase in 
appraised value per unit, which may be associated with the 
relatively low interest rates prevailing in 1998. \23\ Because 
interest rates are not expected to fall significantly from 1998 
levels at the time of this writing, it appears reasonable to project 
that year-2000 conventional multifamily average loan amount will 
continue at the 1998 level of $30,000 under HUD's baseline 
projection of $46 billion for the year 2000. Under the lower 
projection of $40 billion, an average loan amount of $29,000 is 
assumed.
---------------------------------------------------------------------------

    \22\ Sample sizes on conventional non-GSE multifamily loans are 
1,047 and 535 in 1997 and 1998, respectively.
    \23\ Commercial property values are inversely related to 
interest rates because a reduction in interest rates reduces the 
rate at which income streams are discounted.
---------------------------------------------------------------------------

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 data combine mortgage originations for the three different 
types of single-family properties: owner-occupied, one-unit 
properties (SF-O); 2-4 unit rental properties (SF 2-4); and 1-4 unit 
rental properties owned by investors (SF-Investor). The fact that 
the goal percentages are much higher for the two rental categories 
argues strongly for disaggregating single-family mortgage 
originations by property type. This section discusses available data 
for estimating the relative size of the single-family rental 
mortgage market.
    The RFS and HMDA are the two data sources for estimating the 
relative size of the single-family rental market. The RFS, based on 
mortgages originated between 1987 and 1991, provides mortgage 
origination estimates for each of the three single-family property 
types. HMDA divides newly-originated single-family mortgages into 
two property types:\24\
---------------------------------------------------------------------------

    \24\ This ignores the 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 as follows:

[[Page 12774]]



----------------------------------------------------------------------------------------------------------------
                                                1997 HMDA (percent)
                                 ------------------------------------------------  1987-911  RFS    HUD's  1995
                                     Purchase        Refinance          All                            Rule
----------------------------------------------------------------------------------------------------------------
SF-O............................            90.6            92.6            91.5            80.4            88.0
SF 2-4..........................       (included                                             2.3             2.0
                                          above)
SF Investor.....................             9.4             7.4             8.5            17.3            10.0
                                 -------------------------------------------------------------------------------
      Total.....................           100.0           100.0           100.0           100.0          100.0
----------------------------------------------------------------------------------------------------------------
1 The year-by-year distributions from the RFS were not too different from the average distribution given in the
  text.

Because HMDA combines the first two categories, the comparisons 
between the data bases must necessarily focus on the SF investor 
category. According to HMDA, investors account for 9.4 percent of 
home purchase loans and 7.4 percent of refinance loans.\25\ The RFS 
estimate of 17.3 percent is over twice HMDA's overall estimate of 
8.5 percent. In its 1995 rule, HUD projected a 10.0 percent share 
for the SF investor group, only 1.5 percentage points higher than 
the 1997 HMDA figure. As discussed below, HUD's projection was 
probably quite conservative; however, given the uncertainty around 
the data, it is difficult to draw firm conclusions about the size of 
the single-family rental market.
---------------------------------------------------------------------------

    \25\ The single-family owner percentages based on 1998 HMDA data 
are as follows: Purchase (91.0 percent), Refinance (94.5 percent), 
and All (93.2 percent). The higher ``All'' percent reflects the 
higher share of refinance mortgages during 1998.
---------------------------------------------------------------------------

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.\26\ Blackley and Follain provide 
reasons why HMDA should be adjusted upward as well as reasons why 
the RFS should be adjusted downward. One reason for adjusting HMDA's 
investor share upward is that the investor share of mortgage 
originations as reported by HMDA is much lower than the investor 
share of the single-family rental stock as reported by the AHS.
---------------------------------------------------------------------------

    \26\ 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.
---------------------------------------------------------------------------

    Blackley and Follain also noted that the fact that investor 
loans prepay at a faster rate than other single-family loans 
suggests that the investor share of single-family mortgage 
originations should be higher not lower than the investor share of 
the single-family housing stock. Blackley and Follain (1995) 
conclude that ``this brings into question the investor share based 
upon HMDA data'' (page 15).
    The RFS's investor share should be adjusted downward in part 
because the RFS assigns all vacant properties to the rental group, 
but some of these are likely intended for the owner market, 
especially among one-unit properties. Blackley and Follain's 
analysis of this issue suggests lowering the investor share from 
17.3 percent to about 14-15 percent.
    Finally, Blackley and Follain note that a conservative estimate 
of the SF investor share is advisable because of the difficulty of 
measuring the magnitudes of the various effects that they 
analyzed.\27\ In their 1996 paper, they conclude that 12 percent is 
a reasonable estimate of the investor share of single-family 
mortgage originations.\28\ Blackley and Follain caution that 
uncertainty exists around this estimate because of inadequate data.
---------------------------------------------------------------------------

    \27\ For example, they note that discussions with some lenders 
suggest that because of higher mortgage rates on investor 
properties, some HMDA-reported owner-occupants may in fact be 
``hidden'' investors; however, it would be difficult to quantify 
this effect. They also note that some properties may switch from 
owner to renter properties soon after the mortgage is originated. 
While such loans would be classified by HMDA as owner-occupied at 
the time of mortgage origination, they could be classified by the 
RFS as rental mortgages. Again, it would be difficult to quantify 
this effect given available data.
    \28\ 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 above in 
Section D.1 were adjusted in two ways. First, the owner-occupied 
HMDA data were disaggregated between SF-O and SF 2-4 mortgages based 
on RFS data, which show that SF 2-4 mortgages represent 
approximately 2 percent of all single-family mortgages. Second, the 
resulting mortgage-based distributions were shifted to unit-based 
distributions by applying the unit-per-mortgage assumptions in HUD's 
proposed rule. HUD assumed 2.25 units per SF 2-4 property and 1.35 
units per SF investor property; both figures were derived from the 
1991 RFS.\29\
---------------------------------------------------------------------------

    \29\ The unit-per-mortgage data from the 1991 RFS match closely 
the GSE purchase data for 1996 and 1997. Blackley and Follain show 
that an adjustment for vacant investor properties would raise the 
average units per mortgage to 1.4; however, this increase is so 
small that it has little effect on the overall market estimates.

----------------------------------------------------------------------------------------------------------------
                                                                                                     Blackley/
                                                    1997  HMDA      1987-91 RFS     HUD's 1995        Follain
                                                     (percent)       (percent)    rule (percent)    Alternative
                                                                                                     (percent)
----------------------------------------------------------------------------------------------------------------
SF-O............................................            84.8            73.8            83.0            80.6
SF-2-4 Owner 1..................................           * 1.9             2.1             1.9             1.9
SF 2-4 Renter...................................           * 2.4             2.7             2.4             2.3
SF Investor 1...................................            10.9            21.4            12.7            15.2
      Total.....................................           100.0           100.0           100.0           100.0
                                                 ---------------------------------------------------------------
SF-Rental.......................................            13.3            24.1            15.1           17.5
----------------------------------------------------------------------------------------------------------------
1 Notice that the SF 2-4 category has been divided into its owner and renter subcomponents. This is easily done
  based on the assumption of 2.25 units per SF 2-4 mortgage. For each mortgage, one unit represents the owner
  occupant and 1.25 additional units represent renter occupants. The owner-occupant is included in the SF-O
  category in this Appendix. This is necessary because different data sources are used to estimate the owner's
  income and the affordability of the rental units. The income of owners of 2-4 properties are included in the
  borrower income data reported by HMDA. The AHS and POMS will be used to estimate the affordability of the
  rental units.
* Estimate


[[Page 12775]]

    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 rule is slightly 
larger than that reported by HMDA. The rental share in the 
``Blackley-Follain'' alternative is slightly above that in HUD's 
1995 Rule.

4. Conclusions

    This section has reviewed data and analyses related to 
determining the rental share of the single-family mortgage market. 
There are two main conclusions:
    (1) While there is uncertainty concerning the relative size of 
this market, the projections made by HUD appear reasonable and, in 
fact, are below the estimate provided by Blackley and Follain.
    (2) HMDA likely underestimates the single-family rental mortgage 
market. Thus, this part of the HMDA data are not considered reliable 
enough to use in computing the market shares for the housing goals. 
Various sensitivity analyses of the market shares for single-family 
rental properties are conducted in Sections F, G, and H. These 
analyses will show the effects on the overall market estimates of 
the different projections about the size of the single-family rental 
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.\30\ 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.
---------------------------------------------------------------------------

    \30\ The property distribution reported in Section A is an 
example of the output of the market share model. Thus, this section 
completes Step 1 of the three-step procedure outlined in Section A.
---------------------------------------------------------------------------

1. Basic Equations for Determining Units Financed in the Mortgage 
Market

    The model first estimates the number of dwelling units financed 
by conventional conforming mortgage originations for each of the 
four property types. It then determines each property type's share 
of the total number of dwelling units financed.

a. Single-Family Units

    This section estimates the number of single-family units that 
will be financed in the conventional conforming market, where 
single-family units (SF-UNITS) are defined as:

SF-UNITS=SF-O+SF 2-4+SF-INVESTOR

    First, the dollar volume of conventional conforming single-
family mortgages (CCSFM$) is derived as follows:

(1) CCSFM$=CONF%*CONV%*SFORIG$
Where:

CONV%=conforming mortgage originations as a percent (measured in 
dollars) of conventional single-family originations; estimated to be 
87%.\31\
---------------------------------------------------------------------------

    \31\ From MBA volume estimates, the conventional share of the 1-
4 family market was between 86 and 88 percent of the market from 
1993 to 1998, with a one-time low of 81 percent in 1994. Calculated 
from ``1-4 Family Mortgage Origination Volume'' tables in Mortgage 
Finance Review, Vol. 6, No. 4, p. 7, and Vol. 7, No. 1, p. 7, and 
from ``MBA Mortgage Finance Forecast,'' September 1999, at 
www.mbaa.org/marketkdata/forecasts/mffore0999.html.
---------------------------------------------------------------------------

CONF%=conventional mortgage originations as a percent of total 
mortgage originations; forecasted to 78% by industry and GSEs.\32\
---------------------------------------------------------------------------

    \32\ Data provided by Fannie Mae show that conforming loans have 
been about 78 percent of total conventional loans over the past few 
years.
---------------------------------------------------------------------------

SFORIG$=dollar volume of single-family one-to-four unit mortgages; 
$1,100 billion is used here as a starting assumption to reflect 
market conditions during the years 2000-2003.\33\ Alternative 
assumptions will be examined later.\34\

    \33\ Single-family mortgage originations of $1,100 billion is 
$370 billion less than the record setting $1,470 billion in 1998 and 
$266 billion higher than the $834 billion in 1997. As discussed 
later, single-family originations could differ from $1,100 billion 
during the 2000-2003 period that the goals will be in effect. As 
recent experience shows, market projections often change. For 
example, $1,100 billion is similar to year-2000 projections by the 
Mortgage Bankers Association made in June, 1999. (See Mortgage 
Finance Review, Vol. 7, No. 2, ``Mortgage Finance Forecasts,'' p. 
2.) However, more recently, MBA estimates for year 2000 volume have 
dropped to $952 billion (see MBA Mortgage Finance Forecast, 
September 1999). Section F will report the effects on the market 
estimates of alternative estimates of single-family mortgage 
originations. As also explained later, the important concept for 
deriving the goal-qualifying market shares is the relative 
importance of single-family versus multifamily mortgage originations 
(the ``mix effect'') rather than the total dollar volume of single-
family originations considered in isolation.
    \34\ The model also requires an estimated refinance rate because 
purchase and refinance loans have different shares of goals-
qualifying units. Over the past year, the MBA has estimated the year 
2000 refinance rate to be 20, 30, and 38 percent for the total 
market (expressed in dollar terms), with 20 percent the latest 
estimate. The model uses a refinance rate of 40 percent for 
conforming conventional loans, which is consistent with the MBA's 30 
percent estimate, since refinance rates are higher for the number of 
conventional conforming loans than for the total market expressed in 
dollar terms. The 40 percent refinance assumption (compared with the 
recent, lower MBA projections) results in conservative estimates of 
goals-qualifying units in the market, since the low-mod share of 
refinance units is lower than the low-mod share of purchase units. 
Sensitivity analyses for alternative refinance rates are presented 
in Sections F-H.
---------------------------------------------------------------------------

Substituting these values into (1) yields an estimate for the 
conventional conforming market (CCSFM$) of $746 billion.
    Second, the number of conventional conforming single-family 
mortgages (CCSFM#) is derived as follows:

(2) CCSFM#=CCSFM$/SFLOAN$

Where:
SFLOAN$=the average conventional conforming mortgage amount for 
single-family properties; estimated to be $100,000.\35\
---------------------------------------------------------------------------

    \35\ The average 1997 loan amount is estimated at $92,844 for 
owner occupied units using 1997 HMDA metro average loan amounts for 
purchase and refinance loans, and then weighting by an assumed 40 
percent refinance rate. A small adjustment is made to this figure to 
account for a small number of two-to-four and investor properties 
(see Section C above). This produces an average loan size of $91,544 
for 1997, which is then inflated 3 percent a year for three years to 
arrive at an estimated $100,000 average loan size for 2000.
---------------------------------------------------------------------------

    Substituting this value into (2) yields an estimate of 7.46 
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 C), 
the following results are obtained:

(3a) SF-OM#=.88*CCSFM#=number of owner-occupied, one-unit 
mortgages=6.56 million.
(3b) SF-2-4M#=.02*CCSFM#=number of owner-occupied, two-to-four unit 
mortgages=.15 million.
(3c) SF-INVM#=.10*CCSFM#=number of one-to-four unit investor 
mortgages=.75 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=6.72 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=.18 million.\36\
---------------------------------------------------------------------------

    \36\ 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=1.01 million.

Summing equations 4a-4c gives 7.91 million for the projected number 
of newly-mortgaged single-family units (SF-UNITS).

b. Multifamily Units

    The number of dwelling units financed by conventional conforming 
multifamily originations is:

(5) MF-UNITS=CCMFM$/MFLOAN$

Where:

CCMFM$=conventional conforming mortgage originations, which are 
assumed to be $46 billion as a starting point; as discussed in 
Section C, alternative estimates of the multifamily market will be 
included in the analysis.

[[Page 12776]]

MFLOAN$=average loan amount per housing unit in multifamily 
properties=$30,000.\37\

    \37\ See Section C for a discussion of average multifamily loan 
amounts.
---------------------------------------------------------------------------

Substituting these values into (5) yields a projection for MF-UNITS 
of 1.53 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=9.44 million
(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.\38\
---------------------------------------------------------------------------

    \38\ 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:

----------------------------------------------------------------------------------------------------------------
                                                 Percent share                                     Percent share
----------------------------------------------------------------------------------------------------------------
SF-O..........................................            71.1    ..............................
SF 2-4........................................             2.0  SF-O............................          1 71.1
SF INVESTOR...................................            10.7  SF-RENTER.......................            12.7
MF-UNITS......................................            16.2  MF-UNITS........................            16.2
                                               ----------------                                  ---------------
      Total...................................           100.0  ................................          100.0
----------------------------------------------------------------------------------------------------------------
1 Owners of 2-4 properties account for 1.6 percentage points of the 71.1 percent for SF-O.

    Sections C and D discussed alternative projections for the 
volume of the multifamily originations and the investor share of 
single-family mortgages. The analysis in this appendix will consider 
three multifamily origination levels--$40 billion, $46 billion, and 
$52 billion--and three projections about the investor share of 
single-family mortgages--8 percent, 10 percent, and 12 percent. The 
middle values ($46 billion and 10 percent) are used in the above 
calculations and will be considered the ``baseline'' projections 
throughout the Appendix. However, HUD recognizes the uncertainty of 
projecting origination volume in markets such as multifamily; 
therefore, the analysis in Sections G-H will also consider market 
assumptions other than the baseline assumptions.
    Table D.3 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 7 percentage points, 
from a low of 67.2 percent (multifamily originations of $52 billion 
coupled with an investor mortgage share of 12 percent) to a high of 
74.3 percent (multifamily originations of $40 billion coupled with 
an investor mortgage share of 8 percent). The owner share under the 
baseline projections ($46 billion and 10 percent) is 71.1 percent, 
which is approximately the same as the owner share (71.0 percent) in 
the baseline projection of HUD's 1995 Rule.

BILLING CODE 4210-27-P

[[Page 12777]]

[GRAPHIC] [TIFF OMITTED] TP09MR00.042


[[Page 12778]]


    Comparison with the RFS. The Residential Finance Survey is the 
only mortgage data source that provides unit-based property 
distributions similar to those reported in Table D.3. 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.\39\ 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.\40\
---------------------------------------------------------------------------

    \39\ Restricting the RFS analysis to 1991 resulted in only minor 
changes to the market shares.
    \40\ Between 1987 and 1991, annual multifamily mortgage 
originations averaged $32 billion, representing 7.2 percent of 
conventional mortgage originations. In 1997, conventional 
multifamily originations stood at $40.7 billion but because of the 
increase in single-family originations since the late 1980s, the 
multifamily share of total originations had dropped to 4.7 percent.
---------------------------------------------------------------------------

3. Sensitivity of Property Distributions to Changes in Other Model 
Parameters

    The multifamily and single-family rental markets are not the 
only areas where some degree of uncertainty exists about their 
magnitudes. HUD examined the sensitivity of the property 
distributions given in Table D.3 to changes in several other model 
parameters. Most of these sensitivity analyses will be reported when 
discussing the market estimates for each of the housing goals. 
Suffice it to say here that any changes that reduce the owner 
category such as reducing the overall level of single-family 
origination activity or raising the per unit loan amounts for 
single-family mortgages tend to increase the market estimates for 
each of the housing goals. This occurs because the goal percentages 
for owner mortgages are lower than those for rental housing.

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.3. This section essentially 
accomplishes Steps 2 and 3 of the three-step procedure discussed in 
Section B.
    Technical issues and data adjustments related to the low- and 
moderate-income percentages for owners and renters are discussed in 
the first two subsections. Then, estimates of the size of the low- 
and moderate-income market are presented along with several 
sensitivity analyses. Based on these analyses, HUD concludes that 
50-55 percent is a reasonable estimate of the mortgage market's low- 
and moderate-income share for the years (2000-2003) which the new 
goals will be in effect.
    This rule proposes that the Low- and Moderate-Income Goal be 
established at 48 percent of eligible units financed in calendar 
year 2000, and 50 percent of eligible units financed in each of 
calendar years 2001-2003.

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.\41\ Table D.4 gives the percentage of mortgages 
originated for low- and moderate-income families for the years 1992-
1998. Data for home purchase and refinance loans are presented 
separately; the discussion will focus on home purchase loans because 
they typically account for the majority of all single-family owner 
mortgages. For each year, a low- and moderate-income percentage is 
also reported for the conforming market without loans originated by 
lenders that primarily originate manufactured home loans (discussed 
below).
---------------------------------------------------------------------------

    \41\ As noted earlier, HMDA data are expressed in terms of 
number of loans rather than number of units. In addition, HMDA data 
do not distinguish between owner-occupied one-unit properties and 
owner-occupied 2-4 properties. This is not a particular problem for 
this section's analysis of owner incomes.

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[GRAPHIC] [TIFF OMITTED] TP09MR00.043

BILLING CODE 4210-27-C

[[Page 12780]]

    Table D.4 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 
major component of the special affordable mortgage market.
    Two trends in the income data should be mentioned--one related 
to the market's funding of low-and moderate-income families since 
the 1995 Rule was written and the other related to the different 
borrower income distributions for refinance and home purchase 
mortgages.
    Low-Mod Market Share Since 1995. As discussed in the 1995 Rule, 
the percentage of borrowers with less than area median income 
increased significantly between 1992 and 1994. Mortgages to low-mod 
borrowers increased from 34.4 percent of the home purchase market in 
1992 to 41.8 percent of that market in 1994. Over the next four 
years (1995-98), the low-mod share of the home purchase market 
remained at a high level, averaging about 42 percent, or almost 40 
percent if manufactured loans are excluded from the market totals. 
The share of the market accounted for by very-low-income borrowers 
followed a similar trend, increasing from 8.7 percent in 1992 to 
11.9 percent in 1994 and then remaining at a high level through 
1998. As discussed in Appendix A, this jump in low-income lending 
has been attributed to several factors, including: a favorable 
economy accompanied by historically low interest rates; the entry 
into the housing market of more diverse groups including non-
traditional households (e.g., singles), immigrants, and minority 
families seeking homeownership for the first time; and, affordable 
lending initiatives and outreach efforts on the part of the mortgage 
industry. Essentially, the affordable lending market is much 
stronger than it appeared to be when HUD wrote the 1995 Rule. At 
that time, there had been two years (1993 and 1994) of increasing 
affordable lending for lower-income borrowers. The four additional 
years of data for 1995-98 show more clearly the underlying strength 
of this market. While lending patterns could change with sharp 
changes in the economy, the fact that there has been six years 
(1993-98) of strong affordable lending suggests the market has 
changed in fundamental ways from the mortgage market of the early 
1990s.
    Refinance Mortgages. HUD's model for determining the size of the 
low-and moderate-income market assumes that low-mod borrowers will 
represent a smaller share of refinance mortgages than they do of 
home purchase mortgages. However, as shown in Table D.4, the income 
characteristics of borrowers refinancing mortgages seem to depend on 
the overall level of refinancing in the market. During the 
refinancing wave of 1992 and 1993, refinancing borrowers had much 
higher incomes than borrowers purchasing homes. For example, during 
1993 low-and moderate-income borrowers accounted for 29.3 percent of 
refinance mortgages, compared to 38.9 percent of home purchase 
borrowers. In 1998, another period of high refinance activity, low-
and moderate-income borrowers accounted for 39.7 percent of 
refinance loans, versus 43.0 percent of home purchase loans. But 
during the years (1995-97) characterized by lower levels of 
refinancing activity, the low-mod share for refinance mortgages was 
about the same as that for home purchase mortgages. In 1997, the 
low-mod share of refinance mortgages (45.0) was even higher than the 
low-mod share of home loans (42.5 percent).
    The projection model assumes that refinancing will be 40 percent 
of the single-family mortgage market. However given the volatility 
of refinance rates from year to year, it is important to conduct 
sensitivity tests using different refinance rates.

b. Manufactured Housing Loans

    The mortgage market definition in this appendix includes 
manufactured housing loans, which have become an important source of 
affordable housing and which the GSEs have started to purchase. 
Because the market estimates in HUD's 1995 Rule were adjusted to 
exclude manufactured housing loans, several tables in this appendix 
will show how the goals-qualifying shares of the single-family-owner 
market change depending on the treatment of manufactured housing 
loans. As explained later, the effect of manufactured housing on 
HUD's metropolitan area market estimate for each of the three 
housing goals is a modest one percentage point.
    As discussed in Appendix A, the manufactured housing market has 
been increasing rapidly over the past few years, as sales volume has 
increased from $4.7 billion in 1991 to $16.3 billion in 1998. The 
affordability of manufactured homes for lower-income families is 
demonstrated by their average price of $41,000 in 1997, a fraction 
of the $176,000 for new homes and $154,000 for existing homes. Many 
households live in manufactured housing because they simply cannot 
afford site-built homes, for which the construction costs per square 
foot are much higher.
    Data on the incomes of purchasers of manufactured homes is not 
readily available, but HMDA data on home loans made by 21 lenders 
that primarily originate manufactured home loans, discussed below, 
indicate that: \42\
---------------------------------------------------------------------------

    \42\ 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.
---------------------------------------------------------------------------

    (i) A very high percentage of these loans--76 percent in 1998--
would qualify for the Low- and Moderate-Income Goal,
    (ii) A substantial percentage of these loans--42 percent in 
1998--would qualify for the Special Affordable Goal, and
    (iii) Almost half of these loans--47 percent in 1998--would 
qualify for the Underserved Areas Goal.
    Thus an enhanced presence in this market by the GSEs would 
benefit many lower-income families. It would also contribute to 
their presence in underserved rural areas, especially in the South.
    To date the GSEs have played a minimal role in the manufactured 
home loan market, but both enterprises have expressed an interest in 
expanding their roles.\43\ Except in structured transactions, the 
GSEs do not purchase manufactured housing loans under their seller/
servicer guidelines unless they are real estate loans. That is, such 
homes must have a permanent foundation and the site must be either 
purchased as part of the transaction or already owned by the 
borrower. Industry trends toward more homes on private lots and on 
concrete foundations suggest that the percentage of manufactured 
homes that would qualify as real estate loans under GSE guidelines 
has grown in the past few years. There has also been a major shift 
from single-section homes to multisection homes, which contain two 
or three units which are joined together on site.
---------------------------------------------------------------------------

    \43\ Freddie Mac, the Manufactured Housing Institute and the Low 
Income Housing Fund have formed an alliance to utilize manufactured 
housing along with permanent financing and secondary market 
involvement to bring affordable, attractive housing to underserved, 
low- and moderate-income urban neighborhoods. Origination News. 
(December 1998), p. 18.
---------------------------------------------------------------------------

    Although manufactured home loans cannot be identified in the 
HMDA data, HUD staff have identified 21 lenders that primarily 
originate manufactured home loans and likely account for most of 
these loans in the HMDA data for metropolitan areas. In Table D.4, 
the data presented under ``Conforming Market Without Manufactured 
Home Loans'' excludes loans originated by manufactured housing 
lenders, as well as loans less than $15,000. The lenders include 
companies such as Green Tree Financial; Vanderbilt Mortgage; 
Deutsche Financial Capital; Oakwood Acceptance Corporation; Allied 
Acceptance Corporation; Belgravia Financial Services; Ford Consumer 
Finance Company; and the CIT Group.\44\
---------------------------------------------------------------------------

    \44\ Randall M. Scheessele had developed a list of nine 
manufactured home lenders that has been used by several researchers 
in analyses of HMDA data prior to 1997. Scheessele recently 
developed the expanded list of 21 manufactured home loan lenders in 
his analysis of 1998 HMDA data. (See Randall M. Scheessele, 1998 
HMDA Highlights, op. cit.) In these appendices, the number of 
manufactured home loans deducted from the market totals for the 
years 1993 to 1997 are the same as reported by Scheessele (1999) in 
his Table D.2b.
---------------------------------------------------------------------------

c. American Housing Survey Data

    The American Housing Survey also reports borrower income data 
similar to that reported in Table D.3.\45\ The low- and moderate-
income market shares from the AHS are as follows:

    \45\ See Appendix D of the 1995 Rule for a detailed discussion 
of the AHS data and improvements that have been made to the survey 
to better measure borrower incomes and rent affordability.
---------------------------------------------------------------------------

1985--27.0%
1987--32.0%
1989--34.0%
1991--36.0%
1993--33.0% (38.7% home purchase and 28.6% refinance)
1995--40.0% (38.5% home purchase and 43.2% refinance)

    According to the AHS, 38.5 percent of those families surveyed 
during 1995 who had recently purchased their homes, and who obtained 
conventional mortgages below the

[[Page 12781]]

conforming loan limit, had incomes below the area median; this 
compares with 39.3 percent based on 1995 HMDA data that excludes 
manufactured homes (as the AHS data do).
    A longer-term perspective of the mortgage market can be gained 
by examining income data from the last six American Housing Surveys. 
During the earlier period between 1987 and 1991, the low- and 
moderate-income share increased from 27 percent to 36 percent, and 
averaged 32.3 percent. After remaining at a relatively low 
percentage (33.0 percent) during the heavy refinance year of 1993, 
the low- and moderate-income share rebounded to 40.0 percent in 
1995. As noted earlier, this is about the same market share reported 
by HMDA data for 1995.
    Since HMDA data cover over 80 percent of the single-family-owner 
mortgage market, and the American Housing Survey represents only a 
very small sample of this market, the HMDA data will be the major 
source of information on the characteristics of single-family 
property owners receiving mortgage financing. As discussed next, the 
American Housing Survey and the Property Owners and Managers Survey 
will be relied on for information about the rents and affordability 
of single-family and multifamily rental properties.

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

    The 1995 Rule relied on the American Housing Survey for a 
measure of the rent affordability of the single-family rental stock 
and the multifamily rental stock. As explained below, the AHS 
provides rent information for the stock of rental properties rather 
than for the flow of mortgages financing that stock. This section 
discusses a new survey, the Property Owners and Managers Survey 
(POMS), that provides information on the flow of mortgages financing 
rental properties. As discussed below, the AHS and POMS data provide 
very similar estimates of the low- and moderate-income share of the 
rental market.

a. American Housing Survey Data

    The American Housing Survey does not include data on mortgages 
for rental properties; rather, it includes data on the 
characteristics of the existing rental housing stock and recently 
completed rental properties. Current data on the income of 
prospective or actual tenants has also not been readily available 
for rental properties. Where such income information is not 
available, FHEFSSA provides that the rent of a unit can be used to 
determine the affordability of that unit and whether it qualifies 
for the Low- and Moderate-Income Goal. A unit qualifies for the Low- 
and Moderate-Income Goal if the rent does not exceed 30 percent of 
the local area median income (with appropriate adjustments for 
family size as measured by the number of bedrooms). Thus, the GSEs' 
performance under the housing goals is measured in terms of the 
affordability of the rental dwelling units that are financed by 
mortgages that the GSEs purchase; the income of the occupants of 
these rental units is not considered in the calculation of goal 
performance. For this reason, it is appropriate to base estimates of 
market size on rent affordability data rather than on renter income 
data.
    A rental unit is considered to be ``affordable'' to low- and 
moderate-income families, and thus qualifies for the Low- and 
Moderate-Income Goal, if that unit's rent is equal to or less than 
30 percent of area median income. Table D.5 presents AHS data on the 
affordability of the rental housing stock for the survey years 
between 1985 and 1995. The 21995 AHS shows that for 1-4 unit 
unsubsidized single-family rental properties, 97 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 95 
percent. The AHS data for 1989, 1991 and 1993 are similar to the 
1995 data.

BILLING CODE 4210-27-P

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[GRAPHIC] [TIFF OMITTED] TP09MR00.044


[[Page 12783]]



b. Property Owners and Managers Survey (POMS)

    During the 1995 rule-making, concern was expressed about using 
data on rents from the outstanding rental stock to proxy rents for 
newly mortgaged rental units.\46\ At that time, HUD conducted an 
analysis of this issue using the Residential Finance Survey and 
concluded that the existing stock was an adequate proxy for the 
mortgage flow when rent affordability is defined in terms of less 
than 30 percent of area median income, which is the affordability 
definition for the Low- and Moderate-Income Goal. More specifically, 
that analysis suggested that 85 percent of single-family rental 
units and 90 percent of multifamily units are reasonable estimates 
for projecting the percentage of financed units affordable at the 
low- and moderate-income level.\47\ HUD has investigated this issue 
further using the POMS.
---------------------------------------------------------------------------

    \46\ Some even argued that data based on the recently completed 
stock would be a better proxy for mortgage flows. In the case of the 
Low- and Moderate-Income Goal, there is not a large difference 
between the affordability percentages for the recently constructed 
stock and those for the outstanding stock of rental properties. But 
this is not the case when affordability is defined at the very-low-
income level. As shown in Table D.5, the recently completed stock 
houses substantially fewer very-low-income renters than does the 
existing stock. Because this issue is important for the Special 
Affordable Goal, it will be further analyzed in Section H when that 
goal is considered.
    \47\ In 1997, 75.6 percent of GSE purchases of single-family 
investor rental units and over 90 percent of their purchases of 
multifamily units qualified under the Low- and Moderate-Income Goal.
---------------------------------------------------------------------------

    POMS Methodology. The affordability of multifamily and single-
family rental housing backing mortgages originated in 1993-1995 was 
calculated using internal Census Bureau files from the American 
Housing Survey-National Sample (AHS) from 1995 and the Property 
Owners and Managers Survey from 1995-1996. The POMS survey was 
conducted on the same units included in the AHS survey, and provides 
supplemental information such as the origination year of the 
mortgage loan, if any, recorded against the property included in the 
AHS survey. Monthly housing cost data (including rent and 
utilities), number of bedrooms, and metropolitan area (MSA) location 
data were obtained from the AHS file.
    In cases where units in the AHS were not occupied, the AHS 
typically provides rents, either by obtaining this information from 
property owners or through the use of imputation techniques. 
Estimated monthly housing costs on vacant units were therefore 
calculated as the sum of AHS rent and utility costs estimated using 
utility allowances published by HUD as part of its regulation of the 
GSEs. Observations where neither monthly housing cost nor monthly 
rent was available were omitted, as were observations where MSA 
could not be determined. Units with no cash rent and subsidized 
housing units were also omitted. Because of the shortage of 
observations with 1995 originations, POMS data on year of mortgage 
origination were utilized to restrict the sample to properties 
mortgaged during 1993-1995. POMS weights were then applied to 
estimate population statistics. Affordability calculations were made 
using 1993-95 area median incomes calculated by HUD.
    POMS Results. The rent affordability estimates from POMS of the 
affordability of newly-mortgaged rental properties are quite 
consistent with the AHS data reported in Table D.5 on the 
affordability of the rental stock. Ninety-six (96) percent of 
single-family rental properties with new mortgages between 1993 and 
1995 were affordable to low- and moderate-income families, and 56 
percent were affordable to very-low-income families. The 
corresponding percentages for newly-mortgaged multifamily properties 
are 96 percent and 51 percent, respectively. Thus, these percentages 
for newly-mortgaged properties from the POMS are similar to those 
from the AHS for the rental stock. As discussed in the next section, 
the baseline projection from HUD's market share model assumes that 
90 percent of newly-mortgaged, single-family rental and multifamily 
units are affordable to low- and moderate-income families.

3. Size of the Low- and Moderate-Income Mortgage Market

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

a. Comparison of Market Estimates with Actual Performance

    The market share estimates that HUD made during 1995 can now be 
compared with actual market shares for 1995 to 1997. Projections for 
1998 will be discussed in the next section. This discussion of the 
accuracy of HUD's past market estimates considers all three housing 
goals, since the explanations for the differences between the 
estimated and actual market shares are common across the three 
goals. HUD estimated the market for each housing goal for 1995-97, 
and obtained the following results:\48\
---------------------------------------------------------------------------

    \48\ The following goals-qualifying shares for 1995-97 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, which 
leads to a range of estimates rather than precise point estimates. 
For example, HUD had two sets of average per-unit loan amounts for 
multifamily properties. HUD's ``higher'' estimates ($24,698 in 1995, 
$25,268 in 1996, and $27,279 in 1997) are used in the text. HUD's 
``lower'' estimates ($22,310 in 1995, $24,047 in 1996, and $25,167 
in 1997) provided slightly higher market shares. For example, the 
1997 figures under the ``lower'' estimates of per-unit multifamily 
loan amounts were as follows: Low- and Moderate-Income Goal (58.4 
percent); Special Affordable Goal (29.5 percent; and Underserved 
Areas Goal (33.9 percent). The ``lower'' per-unit loan amounts 
result in a larger number of multifamily units in HUD's model, which 
leads to higher percentages of goals-qualifying loans in the overall 
market.

----------------------------------------------------------------------------------------------------------------
                                                                                      Special       Underserved
                                                                      Low-Mod       affordable        areas 1
                                                                     (percent)       (percent)       (percent)
----------------------------------------------------------------------------------------------------------------
1995............................................................            56.8            28.4            32.9
1996............................................................            57.2            28.5            32.7
1997............................................................            57.8            29.0           33.7
----------------------------------------------------------------------------------------------------------------
1 The underserved area market shares presented here are based on data for metropolitan areas; as discussed in
  the next section, accounting for non-metropolitan areas would likely raise the overall market share for this
  goal by as much as a percentage point.

    HUD market estimates in 1995 were 48-52 percent for the Low- and 
Moderate-Income Goal, 20-23 percent for the Special Affordable Goal, 
and 25-28 percent for the Underserved Areas Goal. Thus, even the 
upper bound figures for the market share ranges in the 1995 Rule 
proved to be low- for the low-mod estimate, 52 percent versus 57-58 
percent; for the special affordable estimate, 23 versus 28-29 
percent, and for the underserved areas estimate, 28 percent versus 
33 percent.
    There are several factors explaining HUD's underestimate of the 
goals-qualifying market shares. The 1995-97 mortgage markets 
originated more affordable single-family mortgages than anticipated, 
mainly due to historically low interest rates and strong economic 
expansion. In 1997, for instance, almost 44 percent of all (home 
purchase and refinance) single-family-owner mortgages qualified for 
the Low- and Moderate-Income Goal, 16 percent qualified for the 
Special Affordable Goal, and 28 percent qualified for the 
Underserved Areas Goal.\49\ HUD's 1995 estimates anticipated smaller 
shares of new

[[Page 12784]]

mortgages being originated for low-income families and in their 
neighborhoods.\50\ \51\
---------------------------------------------------------------------------

    \49\ The 1995-97 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.
    \50\ HUD had based its earlier projections heavily on market 
trends between 1992 and 1994. During this period, low- and moderate-
income borrowers accounted for only 38 percent of home purchase 
loans, which is consistent with an overall market share for the Low- 
and Moderate-Income Goal of 52 percent (see Table D.7 below), which 
was HUD's upper bound in the 1995 Rule. Based on the 1993 and 1994 
mortgage markets, HUD's earlier estimates also assumed that 
refinance mortgages would have smaller shares of lower-income 
borrowers than home purchase loans; the experience during the 1995-
1997 period was the reverse, with refinance loans having higher 
shares of lower-income borrowers than home purchase loans. For 
example, in 1997, 45 percent of refinancing borrowers had less-than-
area-median incomes, compared with 42.5 percent of borrowers 
purchasing a home.
    \51\ The 1995-97 estimates also include the effects of small 
loans (less than $15,000) and manufactured housing loans which 
increase the market shares for metropolitan areas by approximately 
one percentage point. For example, assuming a constant mix of owner 
and rental properties, excluding these loans would reduce the goals-
qualifying shares as follows: the Low- and Moderate-Income Goal by 
1.4 percentage points, and the Special Affordable Goal and 
Underserved Areas Goals by one percentage point. However, dropping 
manufactured housing from the market totals would increase the 
rental share of the market, which would tend to lower these impact 
estimates. It should also be mentioned that manufactured housing in 
non-metropolitan areas is not included in HUD's analysis due to lack 
of data; including this segment of the market would tend to increase 
the goals-qualifying shares of the overall market. Thus, the 
analyses of manufactured housing reported above and throughout the 
text pertain only to manufactured housing loans in metropolitan 
areas, as measured by loans originated by the manufactured housing 
lenders identified by Scheessele, op. cit.
---------------------------------------------------------------------------

    The financing of rental properties during 1995-97 was larger 
than anticipated. HUD's earlier estimates assumed a rental share of 
29 percent, which was lower than the approximately 31 percent rental 
share for the years 1995-97. The underestimate for rental housing 
was due to a larger multifamily market ($32 billion for 1995, $37 
billion for 1996, and $41 billion for 1997) than anticipated in the 
1995 GSE Rule ($30 billion) and to lower per unit multifamily loan 
amounts than assumed in HUD's earlier model.\52\
---------------------------------------------------------------------------

    \52\ The accuracy of the single-family portion of HUD's model 
can be tested using HMDA data. The number of single-family loans 
reported to HMDA for the years 1995 to 1997 can be compared with the 
corresponding number predicted by HUD's model. Single-family loans 
reported to HMDA during 1995 were 79 percent of the number of loans 
predicted by HUD's model; comparable percentages for 1996 and 1997 
were 83 percent and 82 percent, respectively. Studies of the 
coverage of HMDA data conclude that HMDA covers approximately 85 
percent of the conventional conforming market. (See Randall M. 
Scheessele, HMDA Coverage of the Mortgage Market, op. cit.) The fact 
that the HMDA data account for lower percentages of the single-
family loans predicted by HUD's model suggests that HUD's model may 
be slightly overestimating the number of single-family loans during 
the 1995-97 period. The only caveat to this concerns manufactured 
housing in non-metropolitan areas. The average loan amount that HUD 
used in calculating the number of units financed from mortgage 
origination dollars did not include the effects of manufactured 
housing in non-metropolitan areas; thus, HUD's average loan amount 
is too high, which suggests that single-family-owner mortgages are 
underestimated. (Similarly, the goals-qualifying percentages in 
HUD's model are based on metropolitan area data and therefore do not 
include the effects of manufactured housing in non-metropolitan 
areas.)
---------------------------------------------------------------------------

    B&C Mortgages. As discussed in Appendix A, the market for 
subprime mortgages has experienced rapid growth over the past 2-3 
years. Comprehensive data for measuring the size of this market are 
not available. However, estimates by various industry observers 
suggest that the subprime market could have accounted for as much as 
15 percent of all mortgages originated during 1997, which would have 
amounted to approximately $125 billion.\53\ In terms of credit risk, 
this $125 billion includes a wide range of mortgage types. ``A-
minus'' loans, which represented about half of the subprime market 
in 1997, make up the least risky category. The GSEs are involved in 
this market--for instance, Freddie Mac has initiated programs to 
purchase A-minus loans through its Loan Prospector system. The 
remaining categories (mainly ``B'' and ``C'' loans) experience much 
higher delinquency rates than A-minus loans.\54\
---------------------------------------------------------------------------

    \53\ A 15 percent estimate for 1997 is reported by Michelle C. 
Hamecs and Michael Benedict, ``Mortgage Market Developments'', in 
Housing Economics, National Association of Home Builders, April 
1998, pages 14-17. Hamecs and Benedict draw their estimate from a 
survey by Inside B&C Lending, an industry publication. A 12 percent 
estimate is reported in ``Subprime Products: Originators Still Say 
Subprime Is `Wanted Dead or Alive' '' in Secondary Marketing 
Executive, August 1998, 34-38. Forest Pafenberg reports that 
subprime mortgages accounted for 10 percent of the conventional 
conforming market in 1997; see his article, ``The Changing Face of 
Mortgage Lending: The Subprime Market'', Real Estate Outlook, 
National Association of Realtors, March 1999, pages 6-7. Pafenberg 
draws his estimate from Inside Mortgage Capital, which used data 
from the Mortgage Information Corporation. The uncertainty about 
what these various estimates include should be emphasized; for 
example, they may include second mortgages and home equity loans as 
well as first mortgages, which are the focus of this analysis.
    \54\ Based on information from The Mortgage Information 
Corporation, Pafenberg reports the following serious delinquency 
rates (either 90 days past due or in foreclosure) for 1997 by type 
of subprime loan: 2.97 percent for A-minus; 6.31 percent for B; 9.10 
percent for C; and 17.69 percent for D. The D category accounted for 
only 5 percent of subprime loans. Also see ``Subprime Mortgage 
Delinquencies Inch Higher, Prepayments Slow During Final Months of 
1998'', 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 effects of excluding B&C mortgages on the estimated market 
shares for goals-qualifying loans in 1997 can be derived by 
combining information from various sources. First, the $125 billion 
estimate for the subprime market was reduced by 15 percent to arrive 
at an estimate of $106 billion for subprime loans that were less 
than the conforming loan limit of $214,600 in 1997. This figure was 
reduced by one-half to arrive at an estimate of $53 billion for the 
conforming B&C market; with an average loan amount of $68,289 
(obtained from HMDA data, as discussed below), the $53 billion 
represented approximately 776,000 B&C loans originated during 1997 
under the conforming loan limit.
    HMDA data was used to provide an estimate of the portion of 
these 776,000 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, HUD staff have identified HMDA reporters that primarily originate 
subprime loans. The goals-qualifying percentages of the loans 
originated by these subprime lenders in 1997 were as follows: 59.3 
percent qualified for the Low- and Moderate-Income Goal, 29.4 
percent for the Special Affordable Goal, and 46.1 percent for the 
Underserved Areas Goal.\55\ Applying the goals-qualifying 
percentages to the estimated B&C market total of 776,000 gives the 
following estimates of B&C loans that qualified for each of the 
housing goals in 1997: Low- and Moderate Income (460,000), Special 
Affordable (228,000), and Underserved Areas (358,000).
---------------------------------------------------------------------------

    \55\ These percentages are based on 42 subprime lenders 
identified by Randall M. Scheessele; slightly lower goals-qualifying 
percentages for 1997 (57.3 percent, 28.1 percent, and 44.7 percent, 
respectively) were obtained based on Scheessele's more recent list 
of subprime lenders. Given the similarity of the two sets of 
percentages, the analysis was not repeated using the more recent 
list. For further comparison between the two lists, see Randall M. 
Scheessele, 1998 HMDA Highlights, op. cit. Not surprisingly, the 
goals-qualifying percentages for subprime lenders are much higher 
than the percentages (43.6 percent, 16.3 percent, and 27.8 percent, 
respectively) for the overall single-family conventional conforming 
market in 1997.
---------------------------------------------------------------------------

    Adjusting HUD's model to exclude the B&C market involves 
subtracting the above four figures for the overall B&C market and 
for B&C loans that qualify for each of the three housing goals from 
the corresponding figures estimated by HUD for the total single-
family and multifamily market inclusive of B&C loans. HUD's model 
estimates that 8,220,000 single-family and multifamily units were 
financed during 1997; of these, 4,751,000 (57.8 percent) qualified 
for the Low- and Moderate-Income Goal, 2,387,000 (29.0 percent) for 
the Special Affordable Goal, and 2,767,000 (33.7 percent) for the 
Underserved Areas Goal. Deducting the B&C market estimates produces 
the following adjusted market estimates: a total market of 
7,444,000, of which 4,291,000 (57.6 percent) qualified for the Low- 
and Moderate-Income Goal, 2,159,000 (29.0 percent) for the Special 
Affordable Goal, and 2,409,000 (32.4 percent) for the Underserved 
Areas Goal.
    As seen, the low-mod market share estimate exclusive of B&C 
loans (57.6 percent) is similar to the original market estimate 
(57.8 percent) and the corresponding special affordable market 
estimate (29.0 percent) is the same as the original estimate. This 
occurs because the B&C loans that were dropped from the analysis had 
similar low-mod and special affordable percentages as the overall 
(both single-family and multifamily) market. For example, the low-
mod share of the B&C was projected to be 59.3 percent and HUD's 
market model projected the overall low-mod share to be 57.8 percent. 
Thus, dropping B&C

[[Page 12785]]

loans from the market totals does not change the overall low-mod 
share of the market appreciably.
    The situation is different for the Underserved Areas Goal. 
Underserved areas account for 46.1 percent of the B&C loans, which 
is a higher percentage than the underserved area share of the 
overall market (33.7 percent). Thus, dropping the B&C loans leads to 
a reduction in the underserved areas market share of 1.3 percentage 
points, from 33.7 percent to 32.4 percent.\56\
---------------------------------------------------------------------------

    \56\ As discussed later, the underserved area share is probably 
a percentage point higher than this due to HUD's model not 
accounting for the high percentage of loans in underserved counties 
of non-metropolitan areas.
---------------------------------------------------------------------------

    Dropping B&C loans from HUD's model changes the mix between 
rental and owner units in the final market estimate. Based on 
assumptions about the size of the owner and rental markets for 1997, 
HUD's model calculates that single-family-owner units accounted for 
about 69.5 percent of total units financed during 1997. Dropping the 
B&C owner loans, as described above, reduces the owner percentage of 
the market by about three percentage points to 66.3 percent. Thus, 
another way of explaining why the goals-qualifying market shares are 
not affected so much by dropping B&C loans is that the rental share 
of the overall market increases as the B&C owner units are dropped 
from the market. Since rental units have very high goals-qualifying 
percentages, their increased importance in the market partially 
offsets the negative effects on the goals-qualifying shares of any 
reductions in B&C owner loans. In fact, this rental mix effect would 
come into play with any reduction in owner units from HUD's model.
    There are caveats that should be mentioned concerning the above 
adjustments for the B&C market. The adjustment for B&C loans depends 
on several estimates relating to the 1997 mortgage market, derived 
from various sources. Different estimates of the size of the B&C 
market in 1997 or the goals-qualifying shares of the B&C market 
could lead to different estimates of the goals-qualifying shares for 
the overall market. The goals-qualifying shares of the B&C market 
were based on HMDA data for selected lenders that primarily 
originate subprime loans; since these lenders are likely originating 
both A-minus and B&C loans, the goals-qualifying percentages used 
here may not be accurately measuring the goals-qualifying 
percentages for only B&C loans. The above technique of dropping B&C 
loans also assumes that the coverage of B&C and non-B&C loans in 
HMDA's metropolitan area data is the same; however, it is likely 
that HMDA coverage of non-B&C loans is higher than its coverage of 
B&C loans.\57\ 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.
---------------------------------------------------------------------------

    \57\ 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.4 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.
---------------------------------------------------------------------------

    1998 Projections. As discussed earlier in Section C.2.c, there 
is particular uncertainty regarding multifamily origination activity 
for the year 1998 due to, among other things, HUD's SMLA data not 
yet being available. The discussion in Section C.2.c concluded that 
1998 multifamily originations could have ranged from $50 to $60 
billion. In this section, the 1998 goals-qualifying market shares 
are first estimated assuming $50 billion in multifamily 
originations, although it is important to recognize the uncertainty 
of this estimate. The high volume of single-family mortgages in 1998 
increased the share of single-family-owner units to 73.1 percent, 
while single-family rental units comprised 13.0 percent, and 
multifamily units comprised a reduced 13.9 percent of the market. 
This shift toward single-family loans, combined with the higher 
level of single-family refinance activity in 1998, results in market 
shares for metropolitan areas that are slightly smaller than 
reported earlier for 1995-97: low-mod, 54.1 percent; special 
affordable, 26.0 percent; and underserved areas, 30.4 percent. While 
lower, these estimates remain higher than the market estimates that 
HUD made in 1995 (see earlier discussion for reasons).\58\
---------------------------------------------------------------------------

    \58\ If B&C loans are excluded from the market (using the 
techniques discussed earlier), the market estimates fall slightly as 
follows: low-mod, 53.8 percent; special affordable, 25.8 percent; 
and underserved areas, 29.4 percent. In 1998, the conforming B&C 
market is estimated to be $65 billion, with an average loan amount 
of $77,796, representing an estimated 836,000 B&C conforming loans. 
The 1998 goals-qualifying percentages (low-mod, 58.0 percent; 
special affordable, 28.5 percent; and underserved areas, 44.7 
percent) used to ``proxy'' the B&C market were similar to those 
reported earlier for 1997. As noted earlier, there is much 
uncertainty about the size of the B&C market.
---------------------------------------------------------------------------

b. Market Estimates

    This section provides HUD's estimates for the size of the low- 
and moderate-income mortgage market that will serve as a proxy for 
the four-year period (2000-2003) when the new housing goals will be 
in effect. Three alternative sets of projections about property 
shares and property low- and moderate-income percentages are given 
in Table D.6. 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.

BILLING CODE 4210-27-P

[[Page 12786]]

[GRAPHIC] [TIFF OMITTED] TP09MR00.045


[[Page 12787]]


[GRAPHIC] [TIFF OMITTED] TP09MR00.046

BILLING CODE 4210-27-C

[[Page 12788]]

    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.\59\ Thus, Table D.7 provides market estimates for 
different owner percentages as well as for different sizes of the 
multifamily market--the $46 billion projection bracketed by $40 and 
$52 billion. Several low-mod percentages of the owner market are 
given in Table D.7 to account for different perceptions about the 
low-mod share of that market. Essentially, HUD's approach throughout 
this appendix is to provide several sensitivity analyses to 
illustrate the effects of different views about the goals-qualifying 
share of the single-family-owner market on the goals-qualifying 
share of the overall mortgage market. This approach recognizes that 
there is some uncertainty in the data and that there can be 
different viewpoints about the various market definitions and other 
model parameters.
---------------------------------------------------------------------------

    \59\ The percentages in Table D.7 refer to borrowers purchasing 
a home. In HUD's model, the low-mod share of refinancing borrowers 
is assumed to be three percentage points lower than the low-mod 
share of borrowers purchasing a home; three percentage points is the 
average differential between 1992 and 1998. Thus, the market share 
model with the 40 percent owner percentage in Table D.7 assumes that 
40 percent of home purchase loans and 37 percent of refinance loans 
are originated for borrowers with low- and moderate-income. If the 
same low-mod percentage were used for both refinancing and home 
purchase borrowers, the overall market share for the Low- and 
Moderate-Income Goal would increase by 0.8 of a percentage point.
---------------------------------------------------------------------------

    As shown in Table D.7, the market estimate is 54-56 percent if 
the owner percentage is at or above 40 percent (slightly less than 
its 1994-98 levels), and it is 53 percent if the owner percentage is 
39 percent (its 1993 level). If the low- and moderate-income 
percentage for owners fell from its 1997-98 level of 43 percent to 
36 percent, the overall market estimate would be approximately 51 
percent. Thus, 51 percent is consistent with a rather significant 
decline in the low-mod share of the single-family home purchase 
market. Under HUD's baseline projections, the home purchase 
percentage can fall as low as 34 percent--about four-fifths of the 
1997-98 level--and the low- and moderate-income market share would 
still be above 49 percent.
    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 E.2, the baseline assumption of $46 billion in 
multifamily originations produces a rental mix of 28.9 percent, 
which is about the same as the baseline projection in HUD's 1995 
Rule. Lowering the multifamily projection to $40 billion reduces the 
rental mix to 27.6 percent, which produces the set of overall low-
mod market estimates that are reported in the first column of Table 
D.7. Compared with $46 billion, the $40 billion assumption reduces 
the overall low-mod market estimates by slightly over a half 
percentage point. For example, when the low-mod share of the owner 
market is 42 percent, the low-mod share of the overall market is 
55.0 percent assuming $46 billion in multifamily originations but is 
54.4 percent assuming $40 billion in multifamily originations.
    The market estimates for Case 2 and Case 3 bracket those for 
Case 1. The smaller single-family rental market and lower low- and 
moderate-income percentages for rental properties result in the Case 
2 estimates being almost two percentage points below the Case 1 
estimates. Conversely, the higher percentages under Case 3 result in 
estimates of the low-mod market approximately three percentage 
points higher than the baseline estimates.
    The various market estimates presented in Table D.7 are not all 
equally likely. Most of them equal or exceed 51 percent; in the 
baseline model, estimates below 51 percent would require the low-mod 
share of the single-family owner market for home purchase loans to 
drop to approximately 36 percent which would be over six percentage 
points lower than the 1993-98 average for the low-mod share of the 
home purchase market. With multifamily volume at $40 billion, the 
low-mod share of the owner market can fall to almost 36 percent 
before the average market share falls below 51 percent.
    The upper bound (56 percent) of the low-mod estimates reported 
in Table D.7 for the baseline case is lower than the low-mod share 
of the market between 1995 and 1997. As reported above, HUD 
estimates that the low-mod market share during this period was 57-58 
percent. There are two reasons the upper bound of 56 percent is 
lower than the recent, 1995-97 experience. First, the projected 
rental share of 29 percent is slightly lower than the rental share 
of 32 percent for the 1995-97 period; a smaller market share for 
rental units lowers the market share. Second, HUD's projections 
assume that refinancing borrowers will have higher incomes than 
borrowers purchasing a home (explained below). As Table D.4 shows, 
this was the reverse of the situation between 1995 and 1997 when 
refinancing borrowers had higher incomes than borrowers purchasing a 
home.\60\ This fact, along with the larger single-family mix effect, 
resulted in the low-mod share of the market falling below the 1997 
level of 57-58 percent.
---------------------------------------------------------------------------

    \60\ On the other hand, in the heavy refinance year of 1998, 
refinancing borrowers had higher incomes than borrowers purchasing a 
home.
---------------------------------------------------------------------------

    B&C Loans. B&C loans can be deducted from HUD's low-mod market 
estimates using the same procedure described earlier. But before 
doing that, some comments about how HUD's projection model operates 
are in order. HUD's projection model assumes that the low-mod share 
of refinance loans will be three percentage points lower than the 
low-mod share of home purchase loans, even though there have been 
years recently (1995-97) when the low-mod share of refinance loans 
has been as high or higher than that for home purchase loans (see 
Table D.4).\61\ Since B&C loans are primarily refinance loans, this 
assumption of a lower low-mod share for refinance loans partially 
adjusts for the effects of B&C loans, based on 1995-97 market 
conditions. For example, in Table D.7, the low-mod home purchase 
percentage of 43 percent, which reflects 1997 conditions, is 
combined with a low-mod refinance percentage of 40 percentage when, 
in fact, the low-mod refinance percentage in 1997 was 45 percent. 
Thus, by taking the 1992-98 average low-mod differential between 
home purchase and refinance loans, the projection model deviates 
from 1995-97 conditions in the single-family owner market.\62\
---------------------------------------------------------------------------

    \61\ The three percentage point differential is the average for 
the years 1992 to 1998 (see Table D.4).
    \62\ Rather, this approach reflects 1998 market conditions when 
the low-mod differential between home purchase and refinance loans 
was approximately three percentage points.
---------------------------------------------------------------------------

    The effects of deducting the B&C loans from the projection model 
can be illustrated using the above example of a low-mod home 
purchase percentage of 43 percent and a low-mod refinance percentage 
of 40 percent; as Table D.7 shows, this translates into an overall 
low-mod market share of 55.7 percent. As in Section F.3.a, it is 
assumed that the subprime market accounts for 15 percent of all 
mortgages originated, which would be $144 billion based on $957 
billion for the conventional market. This $144 billion estimate for 
the subprime market is reduced by 15 percent to arrive at $122 
billion for subprime loans that will be less than the conforming 
loan limit. This figure is reduced by one-half to arrive at 
approximately $60 billion for the conforming B&C market; with an 
average loan amount of $75,043, the $60 billion represents 799,542 
B&C loans projected to be originated under the conforming loan 
limit.\63\
---------------------------------------------------------------------------

    \63\ The $75,043 is derived by adjusting the 1997 figure of 
$68,289 upward based on recent growth in the average loan amount for 
all loans. Also, it should be mentioned that one recent industry 
report suggests that the B&C part of the subprime market has fallen 
to 37 percent. See ``Retail Channel Surges in the Troubled '98 
Market'' in Inside B&C Lending, March 25, 1999, page 3. If the 1998 
average ($76,223) for the 200 subprime lenders had been adjusted 
upward, the projected year 2000 average would have been higher 
($81,164), which would have reduced the projected number of B&C 
loans to 739,244.
---------------------------------------------------------------------------

    Following the procedure discussed in Section F.3.a, the low-mod 
share of the market exclusive of B&C loans is estimated to be 55.4 
percent, which is only slightly lower than the original estimate 
(55.7 percent).\64\ As noted earlier, this occurs

[[Page 12789]]

because the B&C loans that were dropped from the analysis had 
similar low-mod percentages as the overall (both single-family and 
multifamily) market (59.3 percent and 55.7 percent, respectively). 
The impact of dropping B&C loans is larger when the overall market 
share for low-mod loans is smaller. As shown in Table D.7, a 38 
percent low-mod share for single-family owners is associated with an 
overall low-mod share of 52.2 percent. In this case, dropping B&C 
loans would reduce the low-mod market share by almost one percentage 
point (0.7 percent) to 51.5 percent. Still, dropping B&C loans from 
the market totals does not change the overall low-mod share of the 
market appreciably.
---------------------------------------------------------------------------

    \64\ As before, 1997 HMDA data for the 42 lenders were used to 
provide an estimate of 59.3 percent for the portion of the B&C 
market that would qualify as low- and moderate-income; using the 
low-mod percentage (58.0 percent) for the larger, 200 sample of 
subprime lenders would have given similar results. Applying the 59.3 
percentage to the estimated B&C market total of 799,542 gives an 
estimate of 474,128 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 799,542 B&C loans and the 474,128 
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 9,445,809 single-family 
and multifamily units will be financed and of these, 5,263,085 (55.7 
percent as in Table D.7) 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 8,646,268 of 
which 4,788,957 (55.4 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; rental 
units accounted for 31.5 percent of total units after dropping B&C 
loans compared with 28.9 percent before dropping B&C loans. Since 
practically all rental units qualify for the low-mod goal, their 
increased importance in the market partially offsets the negative 
effects on the goals-qualifying shares of any reductions in B&C 
owner loans.
    Section F.3.a discussed several caveats concerning the analysis 
of B&C loans. It is not clear what types of loans (e.g., first 
versus second mortgages) are included in the B&C market estimates. 
There is only limited data on the borrower characteristics of B&C 
loans and the extent to which these loans are included in HMDA is 
not clear. Still, the analysis of Table D.7 and the above analysis 
of the effects of dropping B&C loans from the market suggest that 
50-55 percent is a reasonable range of estimates for the low- and 
moderate-income market for the years 2000-2003. This range covers 
markets without B&C loans and allows for market environments that 
would be much less affordable than recent market conditions. The 
next section presents additional analyses related to market 
volatility and affordability conditions.

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

    During the 1995 rule-making, there was a concern that the market 
share estimates and the housing goals failed to recognize the 
volatility of housing markets and the existence of macroeconomic 
cycles. There was particular concern that the market shares and 
housing goals were based on a period of economic expansion 
accompanied by record low interest rates and high housing 
affordability. This section discusses these issues, noting that the 
Secretary can consider shifts in economic conditions when evaluating 
the performance of the GSEs on the goals, and noting further that 
the market share estimates can be examined in terms of less 
favorable market conditions than existed during the 1993 to 1998 
period.
    Volatility of Market. The starting point for HUD's estimates of 
market share is the projected $1,100 billion in single-family 
originations. Shifts in economic activity could obviously affect the 
degree to which this projection is borne out. Changing economic 
conditions can affect the validity of HUD's market estimates as well 
as the feasibility of the GSEs' accomplishing the housing goals.
    One only has to recall the volatile nature of the mortgage 
market in the past few years to appreciate the uncertainty around 
projections of that market. Large swings in refinancing, consumers 
switching between adjustable-rate mortgages and fixed-rate 
mortgages, and increased first-time homebuyer activity due to record 
low interest rates, have all characterized the mortgage market 
during the nineties. These conditions are beyond the control of the 
GSEs but they would affect their performance on the housing goals. A 
mortgage market dominated by heavy refinancing on the part of 
middle-income homeowners would reduce the GSEs' ability to reach a 
specific target on the Low- and Moderate-Income Goal, for example. A 
jump in interest rates would reduce the availability of very-low-
income mortgages for the GSEs to purchase. But on the other hand, 
the next few years may be highly favorable to achieving the goals 
because of the high refinancing activity in 1998 and anticipated in 
1999. A period of low interest rates would sustain affordability 
levels without causing the rush to refinance seen earlier in 1993 
and more recently in 1998. A high percentage of potential 
refinancers have already done so, and are less likely to do so 
again.
    HUD conducted numerous sensitivity analyses of the market 
shares. For example, increasing the single-family mortgage 
origination projection by $200 billion, from $1,100 billion to 
$1,300 billion, would reduce the market share for the Low- and 
Moderate-Income Goal by approximately one percentage point, assuming 
the other baseline assumptions remain unchanged. This reduction in 
the low-mod share of the mortgage market share occurs because the 
rental share of newly-mortgaged units is reduced (from 28.9 percent 
to 27.1 percent).
    HUD also examined potential changes in the market shares under 
two very different macroeconomic environments, one assuming a 
recession and one assuming a period of low interest rates and heavy 
refinancing. The recessionary environment was simulated using Fannie 
Mae's minimum projections of single-family mortgage originations 
($880 billion) and multifamily originations ($35 billion) for the 
year 2000. The low- and moderate-income share of the home purchase 
market was reduced to 34 percent, or 8.5 percentage points lower 
than its 1997 share.\65\ Under these rather severe conditions, the 
overall market share for the Low- and Moderate-Income Goal would 
decline to 49 percent.
---------------------------------------------------------------------------

    \65\ Refinance mortgages were assumed to account for 15 percent 
of all single-family originations; 31 percent of refinancing 
borrowers were assumed to have less-than-area-median incomes, which 
is 14 percentage points below the 1997 level. The average per unit 
multifamily loan amount was assumed to be $29,000.
---------------------------------------------------------------------------

    The heavy refinance environment was simulated assuming that the 
single-family origination market increased to $1,650 billion 
(compared with HUD's baseline of $1,100 billion) and that the 
multifamily market increased to $52 billion (compared with HUD's 
baseline of $46 billion). The relatively high level of single-family 
originations increases the owner share of newly-mortgaged dwelling 
units from 71 percent under HUD's baseline model to 74 percent in 
the simulated heavy refinance environment. Refinances were assumed 
to account for 60 percent of all single-family mortgage 
originations. If low- and moderate-income borrowers accounted for 40 
percent of borrowers purchasing a home but only 36 percent of 
refinancing borrowers, then the market share for the Low- and 
Moderate-Income Goal would be 51 percent. If the first two 
percentages were reduced to 39 percent and 32 percent, respectively, 
then the market share for the Low- and Moderate-Income Goal would 
fall to 49 percent. However, if the refinance market resembled 1998 
conditions, the low-mod share would be 54 percent, as reported 
earlier.
    Finally, HUD simulated the specific scenario based on the MBA's 
most recent market estimate of $950 billion and a refinance rate of 
20 percent. In this case, assuming a low- mod home purchase 
percentage of 40, the overall low-mod market share was 54.9 percent, 
assuming $46 billion in multifamily loans, and 54.3 percent, 
assuming $40 billion in multifamily loans.
    Feasibility Determination. As stated in the 1995 Rule, HUD is 
well aware of the volatility of mortgage markets and the possible 
impacts on the GSEs' ability to meet the housing goals. FHEFSSA 
allows for changing market conditions.\66\ If HUD has set a goal for 
a given year and market conditions change dramatically during or 
prior to the year, making it infeasible for the GSE to attain the 
goal, HUD must determine ``whether (taking into consideration market 
and economic conditions and the financial condition of the 
enterprise) the achievement of the housing goal was or is 
feasible.'' This provision of FHEFSSA clearly allows for a finding 
by HUD that a goal was not feasible due to market conditions, and no 
subsequent actions would be taken. As HUD noted in the 1995 GSE 
Rule, it does not set the housing goals so that they can be met even 
under the worst of circumstances. Rather, as explained above, HUD 
has conducted numerous sensitivity analyses for economic 
environments much more adverse than has existed in recent years. If 
macroeconomic conditions change even more dramatically, the levels 
of the goals can be revised to reflect the changed conditions. 
FHEFSSA and HUD recognize that conditions could change in ways that 
require revised expectations.
---------------------------------------------------------------------------

    \66\ Section 1336(b)(3)(A).
---------------------------------------------------------------------------

    Affordability Conditions and Market Estimates. The market share 
estimates rely on 1992-1998 HMDA data for the percentage of low- and 
moderate-income borrowers. As discussed in Appendix A, record low 
interest rates, a more diverse socioeconomic group of households 
seeking homeownership, and affordability initiatives of the private 
sector have encouraged first-time buyers and low-income borrowers to 
enter the market during the six-year period between 1993 and 1998.

[[Page 12790]]

A significant increase in interest rates over their 1993-98 levels 
would reduce the presence of low-income families in the mortgage 
market and the availability of low-income mortgages for purchase by 
the GSEs. As discussed above, the 50-55 percent range for the low-
mod market share covers economic and housing market conditions less 
favorable than recent conditions of low interest rates and economic 
expansion. The low-mod share of the single-family home purchase 
market could fall to 34 percent, which is over nine percentage 
points lower than its 1998 level of about 43 percent, before the 
baseline market share for the Low- and Moderate-Income Goal would 
fall below 50 percent.

d. Conclusions About the Size of Low- and Moderate-Income Market

    Based on the above findings as well as numerous sensitivity 
analyses, HUD concludes that 50-55 percent is a reasonable range of 
estimates of the mortgage market's low- and moderate-income share 
for the year 2000 and beyond. This range covers much more adverse 
market conditions than have existed recently, allows for different 
assumptions about the multifamily market, and excludes the effects 
of B&C loans. HUD recognizes that shifts in economic conditions 
could increase or decrease the size of the low- and moderate-income 
market during that period.

G. Size of the Conventional Conforming Market Serving Central Cities, 
Rural Areas, and Other Underserved Areas

    The following discussion presents estimates of the size of the 
conventional conforming market for the Central City, Rural Areas, 
and other Underserved Areas Goal; this housing goal will also be 
referred to as the Underserved Areas Goal or the Geographically-
Targeted Goal. The first two sections focus on underserved census 
tracts in metropolitan areas. Section 1 presents underserved area 
percentages for different property types while Section 2 presents 
market estimates for metropolitan areas. Section 3 discusses B&C 
loans and rural areas.
    This rule proposes that the Central Cities, Rural Areas, and 
other Underserved Areas Goal for the years 2000 and thereafter be 
set at 29 percent of eligible units financed in calendar year 2000, 
and 31 percent of eligible units financed in each of calendar years 
2001-2003.

1. Geographically-Targeted Goal Shares by Property Type

    For purposes of the Geographically-Targeted Goal, underserved 
areas in metropolitan areas are defined as census tracts with:
    (a) Tract median income at or below 90 percent of the MSA median 
income; or
    (b) A minority composition equal to 30 percent or more and a 
tract median income no more than 120 percent of MSA median income.
    Owner Mortgages. The first set of numbers in Table D.8 are the 
percentages of single-family-owner mortgages that financed 
properties located in underserved census tracts of metropolitan 
areas between 1992 and 1998. In 1997 and 1998, approximately 25 
percent of home purchase loans financed properties located in these 
areas; this represents an increase from 22 percent in 1992 and 1993. 
In some years, refinance loans are even more likely than home 
purchase loans to finance properties located in underserved census 
tracts. Between 1994 and 1997, 28.5 percent of refinance loans were 
for properties in underserved areas, compared to 25.1 percent of 
home purchase loans.\67\ In the heavy refinance year of 1998, 
underserved areas accounted for about 25 percent of both refinance 
and home purchase loans.
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    \67\ As shown in Table D.8, excluding loans less than $15,000 
and manufactured home loans reduces the 1997 underserved area 
percentage by 1.2 percentage points for all single-family-owner 
loans from 27.8 to 26.6 percent. Dropping only small loans reduces 
the underserved areas share of the metropolitan market by 0.4 and 
dropping manufactured loans (above $15,0000) reduces the market by 
0.8.

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    Since the 1995 Rule was written, the single-family-owner market 
in underserved areas has remained strong, similar to the low-and 
moderate-income market discussed in Section F. Over the past five 
years, the underserved area share of the metropolitan mortgage 
market has leveled off at 25-28 percent, considering both home 
purchase and refinance loans. This is higher than the 23 percent 
average for the 1992-94 period, which was the period that HUD was 
considering when writing the 1995 Rule. As discussed earlier, 
economic conditions could change and reduce the size of the 
underserved areas market; however, that market appears to have 
shifted to a higher level over the past five years.
    Renter Mortgages. The second and third sets of numbers in Table 
D.8 are the underserved area percentages for single-family rental 
mortgages and multifamily mortgages, respectively. Based on HMDA 
data for single-family, non-owner-occupied (investor) loans, the 
underserved area share of newly-mortgaged single-family rental units 
has been in the 43-45 percent range over the past five years. HMDA 
data also show that about half of newly-mortgaged multifamily rental 
units are located in underserved areas.

2. Market Estimates for Underserved Areas in Metropolitan Areas

    In the 1995 GSE Rule, HUD estimated that the market share for 
underserved areas would be between 25 and 28 percent. This estimate 
turned out to be below market experience, as underserved areas 
accounted for approximately 33 percent of all mortgages originated 
in metropolitan areas between 1995 and 1997 and for 30 percent in 
1998 (see Section F.3.a above).\68\
---------------------------------------------------------------------------

    \68\ As mentioned earlier, dropping B&C loans reduces the 
underserved area estimate for 1997 from 33.7 percent to 32.4 
percent. The main reason for HUD's underestimate in 1995 was not 
anticipating the high percentages of single-family-owner mortgages 
that would be originated in underserved areas. During the 1995-97 
period, about 27 percent of single-family-owner mortgages financed 
properties in underserved areas; this compares with 24 percent for 
the 1992-94 period which was the basis for HUD's earlier analysis. 
There are other reasons the underserved area market shares for 1995 
to 1997 were higher than HUD's 25-28 percent estimate. As discussed 
earlier, rental properties accounted for a larger share (31 percent) 
of the market during this period than assumed (29 percent) in HUD's 
1995 model. Single-family rental and multifamily mortgages 
originated during this period were also more likely to finance 
properties located in underserved areas than assumed in HUD's 
earlier model. In 1997, 45 percent of single-family rental mortgages 
and 48 percent of multifamily mortgages financed properties in 
underserved areas, both figures larger than HUD's assumptions (37.5 
percent and 42.5 percent, respectively) in its earlier model. Even 
in the heavy refinance year of 1998, the underserved areas market 
share (30 percent) was higher than projected by HUD during the 1995 
rule-making process.
---------------------------------------------------------------------------

    Table D.9 reports HUD's estimates of the market share for 
underserved areas based on the projection model discussed 
earlier.\69\ After presenting these estimates, which are based 
mainly on HMDA data for metropolitan areas, the effects of dropping 
B&C loans and including non-metropolitan areas will be discussed.
---------------------------------------------------------------------------

    \69\ Table D.9 presents estimates for the same combinations of 
projections used to analyze the Low- and Moderate-Income Goal. Table 
D.6 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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[[Page 12794]]

    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.9 reports 
market shares for different single-family-owner percentages ranging 
from 28 percent (1997 HMDA) to 20 percent (1993 HMDA) to 18 percent. 
If the single-family-owner percentage for underserved areas is at 
its 1994-98 HMDA average of 26 percent, the market share estimate is 
almost 32 percent. The overall market share for underserved areas 
peaks at 33 percent when the single-family-owner percentage is at 
its 1997 figure of 28 percent. Most of the estimated market shares 
for the owner percentages that are slightly below recent experience 
are in the 30-31 percent range. In the baseline case, the single-
family-owner percentage can go as low as 23 percent, which is over 3 
percentage points lower than the 1994-98 HMDA average, and the 
estimated market share for underserved areas remains almost 30 
percent.\70\
---------------------------------------------------------------------------

    \70\ The recession scenario described in Section F.3.c assumed 
that the underserved area percentage for single-family-owner 
mortgages was 21 percent or almost seven percentage points lower 
than its 1997 value. In this case, the overall market share for 
underserved areas declines to 28 percent.
---------------------------------------------------------------------------

    Unlike the Low- and Moderate-Income Goal, the market estimates 
differ only slightly as one moves from Case 1 to Case 3 and from $40 
billion to $52 billion in the size of the multifamily market. For 
example, reducing the assumed volume to $40 billion reduces the 
overall market projection for underserved areas by only about 0.3 
percentage points. This is because the underserved area 
differentials between owner and rental properties are not as large 
as the low- and moderate-income differentials reported earlier. 
Several additional sensitivity analyses were conducted. For example, 
adding (deducting) $200 billion to the $1,100 billion single-family 
originations would reduce (increase) the underserved area market 
share by about 0.7 (1.0) percent, assuming there were no other 
changes. The MBA estimated in September 1999 that year 2000 single-
family mortgage volume would be about $950 billion, with a refinance 
rate of 20 percent. With these assumptions and a single-family owner 
underserved area percentage of 25 percent, the overall market share 
for underserved units is 31.4 percent if multifamily loans total $46 
billion, and 31.1 percent if multifamily loans total $40 billion.

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

    B&C Loans. The procedure for dropping B&C loans from the 
projections is the same as described in Section F.3.b for the Low- 
and Moderate-Income Goal. The underserved area percentage for B&C 
loans is 46.1 percent, which is much higher than the projected 
percentage for the overall market (slightly over 30 percent as 
indicated in Table D.9). Thus, dropping B&C loans will reduce the 
overall market estimates. Consider in Table D.9, the case of a 
single-family-owner percentage of 28 percent, which yields an 
overall market estimate for underserved areas of 33.1 percent. 
Dropping B&C loans from the projection model reduces the underserved 
areas market share by 1.2 percentage points to 31.9.
    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 does not provide mortgage data for non-metropolitan 
counties, which 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.
    In 1997, 36 percent of the GSE's total purchases in non-
metropolitan areas were in underserved counties while 27 percent of 
their purchases in metropolitan areas were in underserved census 
tracts. These figures also suggest the market share for underserved 
counties in rural areas is higher than the market share for 
underserved census tracts in metropolitan areas. Thus, HUD's use of 
the metropolitan estimate to proxy the overall market for this goal, 
including rural areas, is conservative. If mortgage data for non-
metropolitan areas were available, the estimated market share for 
the Underserved Areas Goal could be as much as one percentage point 
higher. \71\
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    \71\ Assuming that non-metropolitan areas account for 15 percent 
of all single-family-owner mortgages and recalling that the 
projected single-family-owner market for the year 2000 accounts for 
71 percent of newly-mortgaged dwelling units, then the underserved 
area differential of 9 percent in the GSE purchase data would raise 
the overall market estimate by 0.96 of a percentage point (9 times 
0.15 times 0.71). Of course, the market differential may not be the 
same as that reflected in the GSE data.
---------------------------------------------------------------------------

    The estimates presented in Table D.9 and this section's analysis 
of dropping B&C loans and including non-metropolitan areas suggest 
that 29-32 percent is a reasonable range for the market estimate for 
underserved areas based on the projection model described earlier. 
This range incorporates market conditions that are more adverse than 
have existed recently and it excludes B&C loans from the market 
estimates.

4. Conclusions

    Based on the above findings as well as numerous sensitivity 
analyses, HUD concludes that 29-32 percent is a reasonable estimate 
of mortgage market originations that would qualify toward 
achievement of the Geographically Targeted Goal if purchased by a 
GSE. HUD recognizes that shifts in economic and housing market 
conditions could affect the size of this market; however, the market 
estimate allows for the possibility that adverse economic conditions 
can make housing less affordable than it has been in the last few 
years. In addition, the market estimate incorporates a range of 
assumptions about the size of the multifamily market.

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).\72\ HUD estimates that the special affordable market is 23-
26 percent of the conventional conforming market.
---------------------------------------------------------------------------

    \72\ 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 that the annual goal for mortgage purchases 
qualifying under the Special Affordable Housing Goal be 18 percent 
of eligible units financed in calendar year 2000, and 20 percent of 
eligible units financed in each of calendar years 2001-2003. This 
proposed rule further provides that of the total mortgage purchases 
counted toward the Special Affordable Housing Goal, each GSE must 
annually purchase multifamily mortgages in an amount equal to at 
least 0.9 percent of the dollar volume of combined (single family 
and multifamily) 1998 mortgage purchases in each of calendar year 
2000, and 1.0 percent in each of calendar years 2001-2003. This 
implies the following thresholds for the two GSEs: \73\
---------------------------------------------------------------------------

    \73\ HUD has determined that the total dollar volume of the 
GSEs' combined (single and multifamily) mortgage purchases in 1998, 
measured in unpaid principal balance at acquisition, was as follows: 
Fannie Mae $367,589 million; Freddie Mac $273,231 million.

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

    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.

[[Page 12795]]

1. Special Affordable Shares by Property Type

    The basic approach involves estimating for each property type 
the share of dwelling units financed by mortgages in a particular 
year that are occupied by very-low-income families or by low-income 
families living in low-income areas. HUD has combined mortgage 
information from HMDA, the American Housing Survey, and the Property 
Owners and Managers Survey in order to estimate these special 
affordable shares.

a. Special Affordable Owner Percentages

    The percentage of single-family-owners that qualify for the 
Special Affordable Goal is reported in Table D.10. Table D.10 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. HMDA data show that special affordable 
borrowers accounted for 15.3 percent of all conforming home purchase 
loans between 1996 and 1998. The special affordable share of the 
market has followed a pattern similar to that discussed earlier for 
the low-mod share of the market. The percentage of special 
affordable borrowers increased significantly between 1992 and 1994, 
from 10.4 percent of the conforming market to 12.6 percent in 1993, 
and then to 14.1 percent in 1994. The additional years since the 
1995 Rule was written have seen the special affordable market 
maintain itself at an even higher level. Over the past four years 
(1995-98), the special affordable share of the market has averaged 
15.1 percent, or almost 13.0 percent if manufactured and small loans 
are excluded from the market totals. As mentioned earlier, lending 
patterns could change with sharp changes in the economy, but the 
fact that there have been several years of strong affordable lending 
suggests that the market has changed in fundamental ways from the 
mortgage market of the early 1990s. The effect of one factor, the 
growth in the B&C loans, on the special affordable market is 
discussed below in Section H.2.

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b. Very-Low-Income Rental Percentages

    Table D.5 in Section F reported the percentages of the single-
family rental and multifamily stock affordable to very-low-income 
families. According to the AHS, 57 percent of single-family units 
and 49 percent of multifamily units were affordable to very-low-
income families in 1995. The corresponding average values for the 
AHS's six surveys between 1985 and 1995 were 58 percent and 47 
percent, respectively.
    Outstanding Housing Stock versus Mortgage Flow. As discussed in 
Section F, an important issue concerns whether rent data based on 
the existing rental stock from the AHS can be used to proxy rents of 
newly mortgaged rental units.\74\ HUD's analysis of POMS data 
suggests that it can--estimates from POMS of the rent affordability 
of newly-mortgaged rental properties are quite consistent with the 
AHS data reported in Table D.5 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.
---------------------------------------------------------------------------

    \74\ Previous analysis of this issue has focused on the relative 
merits of data from the recently completed stock versus data from 
the outstanding stock. The very-low-income percentages are much 
lower for the recently completed stock--for instance, the average 
across the five AHS surveys were 15 percent for recently completed 
multifamily properties versus 46 percent for the multifamily stock. 
But it seems obvious that data from the recently completed stock 
would underestimate the affordability of newly-mortgaged units 
because they exclude purchase and refinance transactions involving 
older buildings, which generally charge lower rents than newly-
constructed buildings. Blackley and Follain concluded that newly-
constructed properties did not provide a satisfactory basis for 
estimating the affordability of newly-mortgaged properties. See ``A 
Critique of the Methodology Used to Determine Affordable Housing 
Goals for the Government Sponsored Housing Enterprises.''
---------------------------------------------------------------------------

c. Low-Income Renters in Low-Income Areas

    HMDA does not provide data on low-income renters living in low-
income census tracts. As a substitute, HUD used the POMS and AHS 
data. The share of single-family and multifamily rental units 
affordable to low-income renters at 60-80 percent of area median 
income (AMI) and located in low-income tracts was calculated using 
the internal Census Bureau AHS and POMS data files.\75\ 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.\76\ 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.\77\
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    \75\ 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.
    \76\ 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.
    \77\ Therefore, combining the assumed very-low-income percentage 
of 50 percent (47 percent) for single-family rental (multifamily) 
units with the assumed low-income-in-low-income-area percentage of 8 
percent (11 percent) for single-family rental (multifamily) units 
yields the special affordable percentage of 58 percent (58 percent) 
for single-family rental (multifamily) units. This is the baseline 
Case 1 in Table D.6.
---------------------------------------------------------------------------

2. Size of the Special Affordable Market

    During the 1995 rule making, HUD estimated a market share for 
the Special Affordable Goal of 20-23 percent. This estimate turned 
out to be below market experience, as the special affordable market 
accounted for almost 29 percent of all housing units financed in 
metropolitan areas between 1995 and 1997. As explained in Section 
F.3.a, there are several explanations for HUD's underestimate of the 
1995-97 market. The financing of rental properties during 1995-97 
was larger than anticipated. HUD's earlier estimates assumed a 
rental share of 29 percent, which was lower that the approximately 
31 percent rental share for the years 1995-97. Another important 
reason for HUD's underestimate was not anticipating the high 
percentage of single-family-owner mortgages that would be originated 
for special affordable borrowers. During the 1995-97 period, 15.4 
percent of all (both home purchase and refinance) single-family-
owner mortgages financed properties for special affordable 
borrowers; this compares with 9.5 percent for the 1992-94 period 
which was the basis for HUD's earlier analysis. The 1995-97 mortgage 
markets originated more affordable single-family mortgages than 
anticipated.\78\ Furthermore, the special affordable market remained 
strong during the heavy refinance year of 1998. Over 26 percent of 
all dwelling units financed in 1998 qualified for the Special 
Affordable Goal.
---------------------------------------------------------------------------

    \78\ The 29.0 percent estimate for 1997 also includes 
manufactured housing and small loans while HUD's earlier 20-23 
percent estimate excluded the effects of these loans. Excluding 
manufacturing housing and small loans from the 1997 market would 
reduce the special affordable share of 29.0 percent by a percentage 
point to 28.0 percent. This can be approximated by multiplying the 
single-family-owner property share (0.69) for 1997 by the 1.4 
percentage point differential between the special affordable share 
of all (home purchase and refinance) single-family-owner mortgages 
in 1997 with manufactured and small loans included (16.3 percent) 
and the corresponding share with these loans excluded (14.9 
percent). This gives a reduction of 0.97 percentage point. These 
calculations overstate the actual reduction because they do not 
include the effect of the increase in the rental share of the market 
that accompanies dropping manufactured housing and small loans from 
the market totals.
---------------------------------------------------------------------------

    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.11 gives new market 
estimates for different combinations of these factors. As before, 
Case 2 is slightly more conservative than the baseline projections 
(Case 1) mentioned above. For instance, Case 2 assumes that only 6 
percent of rental units are affordable to low-income renters living 
in low-income areas.

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    When the special affordable share of the single-family market 
for home mortgages is at its 1994-98 level of 14-15 percent, the 
special affordable market estimate is 26-27 percent under HUD's 
baseline projections. In fact, the market estimates remain above 24 
percent even if the special affordable percentage for home loans 
falls from its 15-percent-plus level during 1996-1998 to as low as 
10-11 percent, which is similar to the 1992 level. Thus, a 24 
percent market estimate allows for the possibility that adverse 
economic conditions could keep special affordable families out of 
the housing market. On the other hand, if the special affordable 
percentage stays at its recent levels, the market estimate is as 
high as 27 percent.\79\
---------------------------------------------------------------------------

    \79\ The upper bound of 27 percent from HUD's baseline special 
affordable model is obtained when the special affordable share of 
home purchase loans is 15.0 percent, which was the figure for 1997 
(see Table D.10). However, the upper bound of 27 percent is below 
the 1997 estimate of the special affordable market of 29.0 percent 
presented earlier (see Section F.3.a). There are several reasons for 
this discrepancy. As mentioned earlier, the rental share in HUD's 
baseline projection model is less than the rental share of the 1997 
market. In addition, HUD's projection model assumes that the special 
affordable share of refinance mortgages will be 1.4 percentage 
points less than the corresponding share for home purchase loans 
(1.4 percent is the average difference between 1992 and 1998). But 
in 1997, the special affordable share (17.6 percent) of refinance 
mortgages was larger than the corresponding share (15.3 percent) for 
home loans.
---------------------------------------------------------------------------

    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 29.4 percent, which is not much higher than the projected 
percentages for the overall market given in Table D.9). Thus, 
dropping B&C loans will not appreciably reduce the overall market 
estimates. Consider in Table D.11, the case of a single-family-owner 
percentage of 15 percent, which yields an overall market estimate 
for Special Affordable Goal of 27 percent. Dropping B&C loans from 
the projection model reduces the special affordable market share by 
0.2 percentage points to 26.8. The effect would be slightly larger 
for the other cases given in Table D.11.
    Based on the data presented in Table D.11 and the analysis of 
the effects of excluding B&C loans from the market, a range of 23-26 
percent is a reasonable estimate of the special affordable market. 
This range includes market conditions that are much more adverse 
than have recently existed. Additional sensitivity analyses are 
provided in the remainder of this section.
    Additional Sensitivity Analyses. The market estimate declines by 
one-half of a percentage point if the estimate of the multifamily 
mortgage market is changed from $46 billion to $40 billion. For 
example, when the special affordable share of the owner market is 13 
percent, the overall market estimate is reduced from 25.6 percent to 
25.1 percent when the multifamily volume assumption is reduced from 
$46 billion to $40 billion. The market estimates under the more 
conservative Case 2 projections are approximately two percentage 
points below those under the Case 1 projections. This is due mainly 
to Case 2's lower share of single-family investor mortgages (8 
percent versus 10 percent in Case 1) and its lower affordability and 
low-income-area percentages for rental housing (e.g., 53 percent for 
single-family rental units in Case 2 versus 58 percent in Case 1).
    Increasing the volume of single-family originations by $200 
billion to $1,300 billion reduces the market estimate by 0.7 
percentage points, while reducing the volume of single-family 
originations by $200 billion to $900 billion increases the market 
estimate by about one percentage point. Using a recent MBA 
projection of $950 billion in single-family originations and a 20 
percent refinance rate, the special affordable market is projected 
to be 26.6 percent if multifamily originations are $46 billion, and 
26.0 percent if multifamily originations are $40 billion, assuming 
that the single-family owner-occupied special affordable share is 13 
percent.
    A recession scenario and a heavy refinance scenario were 
described during the discussion of the Low- and Moderate-Income Goal 
in Section F. The recession scenario assumed that special affordable 
borrowers would account for only 9-10 percent of newly-originated 
home loans. In these cases, the market share for the Special 
Affordable Goal declines to 23-24 percent. In the heavy refinance 
scenario, the special affordable percentage for refinancing 
borrowers was assumed to be four percentage points lower that the 
corresponding percentage for borrowers purchasing a home. In this 
case, the market share for the Special Affordable Goal was typically 
in the 23-25 percent range, depending on assumptions about the 
incomes of borrowers in the home purchase market. As noted earlier, 
the special affordable market share was approximately 26 percent 
during 1998, a period of heavy refinance activity.
    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 increases 
Fannie Mae's 1997 performance by only half a percentage point, from 
16.5 to 17 percent. At first glance, this small effect seems at odds 
with the fact that 26.5 percent of Fannie Mae's multifamily 
purchases during 1997 involved properties with a very-low-income 
occupancy of 100 percent, and 43.0 percent involved properties with 
a very-low-income occupancy of over 40 percent. The explanation, of 
course, is that most of the rental units in these ``tax-credit'' 
properties are covered by the very-low-income and low-income-in-low-
income-areas components of the Special Affordable Goal.

3. Conclusions

    Sensitivity analyses were conducted for the market shares of 
each property type, for the very-low-income shares of each property 
type, and for various assumptions in the market projection model. 
These analyses suggest that 23-26 percent is a reasonable estimate 
of the size of the conventional conforming market for the Special 
Affordable Housing Goal. This estimate excludes B&C loans and allows 
for the possibility that homeownership will not remain as affordable 
as it has over the past five years. In addition, the estimate covers 
a range of projections about the size of the multifamily market.

I. Impact of New FHA Loan Limits

    This section discusses recent statutory changes that raised the 
FHA loan limits and the impact of these changes on the conventional 
market and the ability of the GSEs to meet their housing goals.
    Studies have shown that the FHA has been the primary bearer of 
credit risk on home mortgage loans to lower-income and African 
American or Hispanic borrowers and in low-income, central city, and 
minority neighborhoods. Many of the loans that FHA insures would 
qualify for one or more of the GSEs' housing goals. Raising the FHA 
loan limits will increase the portion of the mortgage market that is 
eligible for FHA, possibly resulting in a shift of loans from the 
conventional market to FHA. It could also shift loans that would 
otherwise meet the GSE goals from the conventional market to FHA. To 
the extent this occurs, the new FHA loan limits could have an impact 
on the conventional market and on the GSEs.
    The information in this section suggests that many of the new 
FHA loans would not qualify for conventional financing. Some of the 
above mentioned studies have also shown that there has been little 
overlap between FHA and the conventional market prior to the loan 
limit increase. This is likely to be the case for newly eligible FHA 
loans as the higher loan limits extend FHA access to more families 
who are denied mortgage credit or otherwise underserved by the 
conventional market. The new FHA loans are likely to collectively 
resemble current FHA loans in many respects, but with higher loan 
amounts and borrower incomes. Differential homeownership rates as 
well as mortgage credit denials which persist across income levels 
for minority families and inner city residents provide evidence that 
underserved markets exist for FHA to serve at these higher loan 
amounts and incomes.
    The number of new FHA loans resulting from the loan limit 
increase is likely to be relatively small. While reasonable 
estimates of new FHA volume could vary, their range is likely to be 
under 50,000 new loans compared to FHA's total home purchase loan 
volume of about 800,000 in 1998. Standard and Poor's Insurance 
Ratings Service does not offer a numerical estimate, but this rating 
agency finds the outlook for the private mortgage insurance industry 
is stable through 2001, and suggests that the portion of the market 
that FHA will serve near the new loan limits will be less than the 
portion it presently serves at lower levels. Similarly, Moody's 
Investors Service believes the higher FHA loan limits will ``dent'' 
the volumes of private mortgage insurers, but is not a source of 
significant concern with regard to the industry outlook.
    Furthermore, most new loans are expected to come from higher 
cost housing markets. In

[[Page 12800]]

many of these markets the old FHA loan limit ceiling denied FHA 
access to all but the bottom tier of the local housing market. In 
these higher cost markets, the new FHA loans will typically be above 
$150,000 requiring borrower incomes in excess of $60,000 to qualify.
    The discussion of this issue is organized as follows. Section I 
describes the statutory changes in the FHA floor and ceiling. 
Section 2 discusses the estimated budget impact of the changes in 
the legislation, including the FHA volume increases that were 
assumed for making this estimate. Section 3 provides the estimated 
range of new FHA loan volume. Section 4 discusses why the overlap 
with the conventional market for the new FHA loans should be small. 
Finally Section 5 discusses the impacts on the conventional market 
and the GSEs.

1. Changes in the Statutory FHA Loan Limit Floor and Ceiling

    The Department's FY 1999 Appropriations Act raised the FHA loan 
limit floor and ceiling to 48 and 87 percent, respectively, of the 
GSEs' conforming loan limit. Prior to this change the FHA loan limit 
floor and ceiling were 38 and 75 percent, respectively, of the 
conforming loan limit. The statute did not change the method of 
establishing FHA loan limits by locality: FHA loan limits for a 1-
family dwelling continue to be set at 95 percent of local median 
home sales price, subject to the statutory floor and ceiling as the 
minimum and maximum, respectively.\80\
---------------------------------------------------------------------------

    \80\ Different percentages of local median sales price apply to 
2-, 3-, and 4-family dwellings.
---------------------------------------------------------------------------

    The Department implemented the new FHA loan limit floor and 
ceiling in October 1998. In January 1999 the Department again 
revised FHA loan limits to reflect the higher conforming loan limit 
that went into effect on January 1.\81\
---------------------------------------------------------------------------

    \81\ The Department's January 1999 update also represented a 
comprehensive update of FHA loan limits based on an analysis of 1998 
local median sales prices from various data sources. This 
comprehensive update, the first undertaken by the Department since 
1995, raised FHA loan limits in over 90 percent of the nation's 
3,141 counties. In many of the counties which received increases in 
January 1999, the FHA loan limit had not changed since the previous 
comprehensive update in 1995. For many of these areas the 1999 
increase was due to the Department's reestimation of the local 
median sales price, and not due to the statutory changes.
---------------------------------------------------------------------------

2. Estimated Budget Impacts

    Prior to passage of the 1999 HUD Appropriations Act, the 
Department estimated the budget impact of the legislative proposal 
to raise the FHA loan limit floor and ceiling to 48 and 87 percent, 
respectively, of the conforming loan limit.\82\ At that time the 
Department estimated the percentage increase in the number of FHA-
insured home purchase loans in FY 1999 relative to the prior year 
would be about 2.6 percent in metropolitan areas and about 11 
percent in non-metropolitan areas. The average loan amount of the 
new loans was estimated at the time to be about $143,000, reflecting 
the fact that some new loans would come in at or near the new floor 
of (then) $109,032 and others in higher cost markets would come in 
at or near the new ceiling of (then) $197,621. Areas with 1998 loan 
limits between the new floor of $109,032 and the 1998 ceiling of 
$170,362 were considered to unaffected by the statutory changes 
because their loan limit would continue to be set at 95 percent of 
local median sales price. The Department estimated that 36 high-cost 
metropolitan areas would be affected by the higher proposed ceiling, 
174 lower-cost metropolitan areas and most non-metropolitan counties 
would be affected by the higher floor, and 115 moderate-cost 
metropolitan areas would be unaffected.
---------------------------------------------------------------------------

    \82\ The budget impact was estimated to be $80 million in first 
year savings, which represents the net present value of future cash 
flows associated with the new loans the Department expected to make 
as a result of the higher loan limit floor and ceiling.
    The methodology used by the Department to arrive at these budget 
estimates was reviewed by the Office of Management and Budget and by 
the Congressional Budget Office. The methodology was based on a 
detailed analysis of the 1996 Home Mortgage Disclosure Act data 
disaggregated to the individual metropolitan area level. For each 
metropolitan area, the Department analyzed the HMDA distribution of 
all home purchase loans made in 1996.
    The first step in the Department's methodology was to determine 
the number and size of newly eligible loans in metropolitan areas 
(as reported in HMDA) had the higher FHA floor and ceiling 
provisions been in effect in 1996. To do this, the Department used 
the actual 1996 FHA loan limit for each area and estimated new 
hypothetical FHA limits for each are using 48 and 87 percent of the 
1996 conforming loan limit of $207,000 as the new floor and ceiling. 
The next step was to estimate the share of the newly eligible loans 
in each area that might come to FHA. The FHA shares were estimated 
for each decile of the HMDA distribution in the local market, 
assuming that FHA's average share of the eligible market in each MSA 
would decline as FHA's penetration extended into the higher deciles 
of the market. The assumption of declining FHA market shares in the 
upper deciles of the market was reasonable for two reasons. First, 
higher income borrowers generally have more choices in terms of 
access to conventional financing. Second, FHA's downpayment 
requirements at the time were greater for higher priced homes. Under 
FHA downpayment rules in effect at the time this analysis was 
performed, FHA required a 10 percent marginal downpayment on the 
amount of property acquisition cost above $125,000. (Acquisition 
cost is defined as the lesser of sales price or appraised value plus 
allowable borrower-paid closing costs.) Higher downpayment 
requirements in the upper end of the market made FHA financing a 
less attractive alternative to conventional financing for potential 
borrowers who could qualify for a conventional loan.
    For non-metropolitan areas, the methodology was less area 
specific because HMDA data do not generally cover non-metropolitan 
areas. Rather, 1995 American Housing Survey data was used to 
determine that about 75 percent of the rural market was already 
eligible for FHA under the old floor (38 percent of conforming loan 
limit). Despite the high eligibility, only 7 percent of the rural 
market was actually financed with FHA-insured loans. Raising the FHA 
floor to 48 percent of the conforming loan limit was estimated to 
increase FHA volume by about 11 percent, assuming a declining share 
of the newly eligible existing housing market, plus some additional 
demand for new construction.
---------------------------------------------------------------------------

    The biggest impact on FHA volume was expected from raising the 
ceiling in the 36 highest cost metropolitan areas. In these high 
cost areas, the old FHA ceiling (75 percent of the conforming loan 
limit) was lower than 95 percent of the local median house price. 
Thus, the old ceiling limited FHA eligibility to the lower-priced 
portion of the local market. Raising the ceiling would extend FHA 
eligibility into the higher volume middle of the local sales market 
for these high cost markets.
    In lower cost areas where the old FHA floor applied, FHA 
eligibility was already above the middle of the local market. That 
is, the old floor (38 percent of the conforming loan limit) was 
higher than 95 percent of the local median house price.\83\ Raising 
the FHA floor would have a relatively small impact in these lower 
cost areas, as FHA is likely to capture a smaller share of the newly 
eligible upper portion of the lower market.
---------------------------------------------------------------------------

    \83\ The Department used 1995 American Housing Survey data to 
estimate that 75 percent of the rural market was already covered by 
the old FHA floor at 38 percent of conforming loan limit.
---------------------------------------------------------------------------

    Two additional provisions enacted by the HUD Appropriations Act 
were not incorporated into the Department's original budget 
estimate. These are (1) the provision which directed the Department 
to set new loan limits for entire metropolitan areas based on the 
median home sales price of the highest cost county within the 
metropolitan area, and (2) the downpayment simplification provision, 
which not only simplified the minimum FHA downpayment calculation 
but also eliminated the 10 percent marginal downpayment requirement 
for higher priced homes.\84\
---------------------------------------------------------------------------

    \84\ Prior to the enactment of HUD's FY 1999 Appropriations Act, 
FHA's statutory downpayment requirements were 3 percent of the first 
$25,000 of property acquisition cost, 5 percent of the next $100,000 
of acquisition cost, and 10 percent of the acquisition cost above 
$125,000. (Acquisition cost is defined as the lesser of sales price 
or appraised value of the property plus allowable borrower-paid 
closing costs.) The new provision limits the mortgage to 97.75 
percent (or 97.15 percent in areas with lower than average closing 
costs), subject to the borrower having a 3 percent minimum cash 
investment. (Borrower cash investment includes allowable borrower-
paid closing costs.) This change in the FHA downpayment provisions 
will raise the maximum FHA mortgage amount for buyers of higher 
priced homes.
---------------------------------------------------------------------------

    The high cost county provision was estimated to raise the budget 
impact by about 6 percent to $85 million. The impact was at first 
considered to be small because the Department did not have access to 
county-level median sales prices in most metropolitan areas with 
which to implement this provision. Rather, changes due to the 
highest cost county provision were assumed to come from locally 
generated sales data submitted to the Department by individual 
counties to appeal their FHA loan limits. Loan limit changes based 
on previously approved local appeals would not have a large impact 
on FHA volume, and would affect primarily moderate cost metropolitan 
areas (most being among the 115 moderate cost areas unaffected by 
the new floor and ceiling as noted above). However, the impact of 
this provision may prove to be larger than the original estimate as 
additional appeals are being filed from multiple county metropolitan 
areas, and as the Department

[[Page 12801]]

seeks out new national sources of county level median sales 
prices.\85\
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    \85\ The Department is working with the Office of Federal 
Housing Enterprise Oversight to develop additional data on local 
median sales price that may prove useful for future FHA loan limit 
determinations.
---------------------------------------------------------------------------

    The downpayment provisions in the HUD Appropriations Act were 
tested in pilot programs conducted by FHA in Alaska and Hawaii 
during 1997. In both these states, where home prices are generally 
higher than the rest of the nation, the downpayment simplification 
pilot raised the percentage of large loans that FHA insured in 1997 
relative to the pre-pilot year of 1996. In the Department's 1998 
report to Congress on the Alaska and Hawaii pilots, it was reported 
that during these two years loans over $150,000 increased from 20 
percent to 28 percent in Alaska, and from 51 percent to 54 percent 
in Hawaii.\86\ This experience suggests that the downpayment 
simplification provision will affect the volume of large loans the 
Department insures and could produce a higher impact from raising 
the FHA loan limit ceiling.
---------------------------------------------------------------------------

    \86\ ``A Study of FHA Downpayment Simplification,'' April 1998, 
Tables 11 and 12.
---------------------------------------------------------------------------

3. Estimated FHA Loan Volume

    The inclusion of the high cost county and the downpayment 
simplification provisions in the HUD FY 1999 Appropriations Act 
suggest that the estimate of about a 3 percent increase in FHA home 
purchase volume due to the higher FHA loan limits may be low. The 
impacts of these two additional provisions are difficult to quantify 
with precision. A volume estimate for FHA which takes into account 
the high cost county and downpayment simplification provisions could 
be two times the original 3 percent estimate. That is, the combined 
impact of all the statutory changes on FHA loan volume would be an 
increase of approximately 6 percent in home purchase mortgages 
insured.
    In addition, the average loan amount of new loans, which had 
been estimated at $143,000, should now be estimated at about 
$154,000, reflecting new loans now coming from moderate-cost 
previously unaffected areas (due to the high cost county provision), 
and more loans than originally estimated coming from the highest 
cost areas (due to downpayment simplification).
    The 1999 dollar volume of new FHA business associated with the 
loan limit increase and the other provisions of the 1999 
Appropriations Act is estimated as follows. In FY 1998, the 
Department insured about 800,000 home purchase loans. Using 6 
percent as the estimated increase in the number of home purchase 
loan cases that FHA will insure in a typical year gives about 50,000 
new loans. At an average loan amount of $154,000 per new loan, the 
estimated annual dollar volume impact would be over $7.0 billion.
    An estimate of the breakdown of the new loans by size and 
minimum income to qualify is as follows. If one assumes the upper 
end of the likely range of new FHA home purchase loan cases (that 
is, a 6 percent increase), then the following is an estimated 
breakdown of loan size and minimum borrower incomes: \87\
---------------------------------------------------------------------------

    \87\ Minimum incomes based on a 7.5 percent, 30-year fixed-rate 
mortgage loan and a front-end ratio of 29 percent.

----------------------------------------------------------------------------------------------------------------
                                                                                                  Minimum income
                      Range of loan amounts                        Number of new    Average New   to qualify for
                                                                       loans        loan amount    average loan
----------------------------------------------------------------------------------------------------------------
Under $150,000..................................................          12,000         $92,000         $33,000
$150,000 and Over...............................................          36,000         175,000          60,000
                                                                 -----------------------------------------------
      Total.....................................................          48,000         154,000
----------------------------------------------------------------------------------------------------------------

4. Overlap with the Conventional Market Should be Small

    The Department based its original budget impact estimate and the 
revised volume estimate on an analysis of HMDA data because this 
data source was determined to be the best available indicator of 
local market activity by loan size. By using HMDA data for this 
purpose, one might infer that all the new FHA-insured loans will 
result in a one-for-one reduction in conventional lending. Rather, 
as will be discussed below, the Department believes that FHA will 
extend new housing opportunities to those who are inadequately 
served by the conventional markets. HMDA data are limited in that 
they do not support an analysis of the potential overlap between the 
new FHA loans and the existing conventional market. The question of 
overlap will instead be addressed by the discussion and analysis 
presented below.

a. FHA Competition with Private Mortgage Insurance

    In a February 1999 commentary on the outlook for the U.S. 
residential mortgage insurance industry, Standard and Poor's 
Insurance Ratings Service projected a stable outlook for the PMI 
industry through 2001 and makes the following comments on the impact 
of the higher FHA loan limits:

    Congress recently increased the size limits of loans eligible 
for Federal Housing Administration insurance. The [FHA] limit in 
``high cost'' areas is . . . not far below the GSE limit of 
$240,000. While FHA borrowers meet lower standards than conforming 
borrowers, and pay higher rates and fees for their loans, a good 
number of FHA borrowers are thought to qualify for the conforming 
market. There is no doubt that the increase in the FHA size 
limitation will pull eligible borrowers from the conforming market. 
However, borrowers who qualify for private mortgages generally have 
more financing alternatives as the loan amounts rise. Therefore, the 
portion of eligible loans that the FHA takes at these upper levels 
should be less than that of the loans it insures at lower 
levels.\88\
---------------------------------------------------------------------------

    \88\ Standard and Poor's, 1999. ``Stable Outlook Projected for 
U.S. Domestic Residential Mortgage Insurance, Industry Conditions 
and Outlook 1998 to 2001,'' Insurance Ratings Service Commentary, 
February 17, p. 9.
---------------------------------------------------------------------------

    Similarly, Moody's Investors Service, in an October, 1998 report 
on the outlook of the U.S. mortgage insurance industry, states

    The recently approved increase of the size of eligible mortgages 
under the FHA programs, while denting the private mortgage insurers' 
volumes, is not a source of significant additional concern.\89\

    \89\ Moody's Investors Service, Inc., 1998. ``US Mortgage 
Insurers Industry Outlook,'' October, p. 8.
---------------------------------------------------------------------------

    The Standard and Poor's analysis is correct in focusing on the 
impact of the new high cost ceiling and not the new floor. In areas 
affected by the higher floor, the old floor already gave borrowers 
access to well over half of the local sales market. Raising the 
floor only increased FHA access to the upper tiers of these low 
costs markets and made FHA financing of new construction more 
feasible. Rather, in the highest cost markets, which were capped by 
the old ceiling, the new FHA ceiling will have the greatest impact. 
In these high cost areas, FHA access was previously limited to the 
lower tiers of the local market. The increase in the ceiling will 
now extend FHA access to more of the higher-volume middle portion of 
the market. Yet, as the Standard and Poor's analysis also correctly 
points out, the higher dollar loan amounts suggest potential 
borrowers will have more alternatives in the conventional market, 
and when comparing FHA premiums with PMI premiums, most who qualify 
for a conventional loan will do so.

b. Cost Comparison: FHA Premiums are Higher

    Standard and Poor's acknowledgment that FHA costs are higher 
than PMI costs is consistent with the Department's own analysis of 
the premium differentials between FHA and PMI. Except for loan to 
value ratios above 95 percent (which represent a very small, albeit 
growing, fraction of the loans that the PMIs insure) FHA's premiums 
are much higher than PMI premiums. For example, a 30-year $100,000 
conventional loan with a 90 percent LTV

[[Page 12802]]

ratio will typically cost a borrower about $2,900 (net present value 
at origination) in PMI premiums, assuming the PMI coverage is 
canceled when the LTV is amortized down to 80 percent. The FHA 
premium, which cannot be canceled without the lender's consent, will 
cost $6,000 for a similar loan if the loan is held to term, or 
$5,200 if the loan is prepaid after 8 years.\90\ For the highest LTV 
loans--those with LTVs above 95 percent--the PMI premium, assuming 
cancellation when the LTV amortizes down to 80 percent, is $6,600, 
or $5,500 if the loan is prepaid after 8 years. The comparable FHA 
premium is $7,300, or $5,200 if the loan is prepaid after 8 
years.\91\ Although the present value of the FHA premium on these 
highest LTV loans can be less than the typical PMI premium if the 
loan is prepaid early, very-low-downpayment loans have a tendency to 
prepay more slowly than loans with higher initial equity.
---------------------------------------------------------------------------

    \90\ Assumes 25 percent PMI coverage, an annual PMI premium of 
0.52 percent, a mortgage rate of 7.5 percent, and a discount rate of 
7 percent. The PMI cost for a loan prepaid after 8 years is not 
shown because the PMI coverage would be canceled before the 8th 
year. The FHA premium is 2.25 percent upfront, plus 0.5 percent 
annually for 12 years. These assumptions do not reflect recent 
premium reduction initiatives by the GSEs and FHA under which the 
GSEs will reduce PMI coverage requirements and FHA will reduce its 
upfront premium for some borrowers. None of these initiatives have 
achieved high volumes as yet.
    \91\ Assumes 30 percent PMI coverage, an annual PMI premium of 
0.9 percent, a mortgage rate of 7.5 percent, and a discount rate of 
7 percent. The FHA premium is 2.25 percent upfront, plus 0.5 percent 
for 30 years. As noted in the prior footnote, the assumptions do not 
reflect recent premium reduction initiatives by the GSEs and FHA.
---------------------------------------------------------------------------

c. Evidence of Little Overlap Before Loan Limit Increase

    Although the Standard and Poor's report states that ``a good 
number'' of FHA borrowers (prior to the loan limit increase) were 
thought to qualify for the conventional market, there have been 
numerous studies showing that the overlap between FHA and the 
conventional market has actually been rather small. A 1996 study by 
the United States General Accounting Office (GAO) documents that FHA 
leads in the provision of insurance for riskier low-downpayment 
mortgages.\92\ The GAO report goes on to provide evidence that there 
has in fact been very little overlap between FHA and PMI loans. 
According to the GAO:
---------------------------------------------------------------------------

    \92\ United States General Accounting Office, 1998. ``FHA's Role 
in Helping People Obtain Home Mortgages.'' GAO/RCED-96-123.
---------------------------------------------------------------------------

    (i) 65 percent of FHA loans have downpayments of 5 percent or 
less, compared to 8 percent of PMI loans and less than 2 percent of 
loans purchased by the GSEs.
    (ii) More than three-fourths of FHA-insured first-time borrowers 
would not have met PMI downpayment requirements. And FHA borrowers 
who do have the cash for a conventional loan downpayment often fail 
to meet the more stringent PMI credit standards.
    In addition, a recent study by the Board of Governors of the 
Federal Reserve concluded that FHA is the primary bearer of credit 
risk for home purchase loans to lower-income and black or Hispanic 
borrowers and in low-income and minority neighborhoods.\93\ The 
Federal Reserve Board study concluded that FHA bears about two-
thirds of the aggregate credit risk for low-income and minority 
borrowers and their neighborhoods, while private mortgage insurers 
bear only 6 to 8 percent of this risk, and the GSEs bear only 4 to 5 
percent of this risk. With this demonstrated capacity to carry 
greater risk than the conventional market, FHA complements, not 
competes with, private sector efforts to expand homeownership 
opportunities.
---------------------------------------------------------------------------

    \93\ Glenn B. Canner, Wayne Passmore, and Brian J. Surette, 
1996. ``Distribution of Credit Risk Among Providers of Mortgages to 
Lower-Income and Minority Homebuyers.'' Federal Reserve Bulletin, 
82(12), 1077-1102.
---------------------------------------------------------------------------

d. The New FHA Loans Will Continue to Address Underserved Markets

    Other sources confirm that the higher FHA loan limits, 
particularly those in the highest cost areas (but also other areas), 
can be useful in addressing many of the same underserved markets 
that FHA currently addresses. Appendix A refers to studies which 
show that homeownership rates for young married couples, female-
headed households, center city residents, and racial and ethnic 
minorities lag far behind the national average. In addition, these 
homeownership gaps persist across income levels.
    FHA, which currently serves a disproportionate share of young 
married couples, female-headed households, center city residents, 
and racial and ethnic minorities, will continue to address these 
underserved markets with the new loans based on higher loan 
limits.\94\ Given these homeownership differences which persist 
across income levels, the higher FHA loan limits will enable FHA 
extend its service to underserved markets at higher income levels.
---------------------------------------------------------------------------

    \94\ FHA has already been filling credit gaps by serving a 
disproportionate number of young first-time buyers, borrowers making 
low downpayments, households living in urban areas, African-
Americans and Hispanics, and lower-income borrowers. HMDA data from 
1996 indicate that while FHA provided mortgage credit to about 20 
percent of conforming loans in metropolitan areas, it insured nearly 
40 percent of all such loans made to African American or Hispanic 
borrowers.
---------------------------------------------------------------------------

e. HMDA Denials by Income Level

    Another source that suggests higher FHA loan limits can be 
useful in addressing many of the same underserved markets that FHA 
currently addresses is HMDA. Mortgage lending information gathered 
by the Federal Reserve Board under requirements of the Home Mortgage 
Disclosure Act shows that in 1996 some 350,000 households--about one 
in eight applicants--were denied credit in the conforming 
conventional market. These denials limit homebuying opportunities 
for both minority and white households seeking to live in urban and 
suburban communities. Mortgage denial rates are particularly high 
for racial and ethnic minorities, but white households accounted for 
nearly two-thirds of the 350,000 denials. In addition to the high 
denial rates for racial and ethnic minorities seeking to purchase 
homes in inner city areas, whites choosing to live in the city are 
also denied mortgages at higher rates than their suburban 
counterparts. About a third of the 350,000 denials were made to 
applicants with incomes above the area median income, and nearly a 
fourth were made to applicants with incomes greater than 120 percent 
of area median income.

6. Why Small Impacts on the Conventional Market and the GSEs Are 
Likely

    The impacts of the higher FHA loan limits on the conventional 
market and on the ability of the GSEs to meet their housing goals 
are likely to be small. The reasons for this conclusion are as 
follows.
    First, there has been little overlap between FHA and the 
conventional market prior to the loan limit increase, and this is 
likely to be the case for newly eligible loans as well. The loan 
limit increase will extend FHA access to more families who are 
denied mortgage credit or otherwise underserved by the conventional 
market.
    Second, the number of new FHA loans resulting from the loan 
limit increase is likely to be relatively small. While reasonable 
estimates of new FHA volume could vary, their range is likely to be 
under 50,000 new loans compared to FHA's total home purchase loan 
volume of about 800,000 in 1998. Two major Wall Street rating 
agencies, while not offering specific volume estimates, have 
suggested that the impacts of the FHA changes will be small on the 
private mortgage insurance industry.
    Finally, many of these new FHA loans are expected to come from 
high cost housing markets with loan amounts typically above $150,000 
and borrowers with annual incomes in excess of $60,000. Even at 
these higher loan amounts and borrower incomes, the FHA's higher 
premium costs would motivate most borrowers to favor conventional 
financing with private mortgage insurance if they qualified.
    The new FHA loans are likely to come from borrowers who are 
being underserved by the conventional market, collectively 
resembling current FHA loans in many respects, but with higher loan 
amounts and borrower incomes. Differential homeownership rates as 
well as mortgage credit denials which persist across income levels 
for minority families and inner city residents provides evidence 
that underserved markets exist for FHA to serve at these higher loan 
amounts and incomes.

Appendix E--GSE Mortgage Data and AHAR Information: Proprietary 
Information/Public-Use Data

    The following matrices distinguish proprietary from public-use 
mortgage data elements. A ``YES'' designation indicates that the 
data element is proprietary and not included in the public use 
database in the format indicated. A ``NO'', ``NO, Added field'', 
``Yes, but recode'', and ``YES, but redefine and recode as'' 
indicate that the data element is included in the public use 
database. Certain data are coded as missing or not available either 
because the data was not submitted or because the data is 
proprietary.
    The first matrix relates to GSE data on single-family owner-and 
renter-occupied 1-

[[Page 12803]]

4-unit properties. The second matrix relates to property-level data 
on multifamily properties. The third matrix relates to unit-class 
level data on multifamily properties. The unit-classes are defined 
by the GSEs for each property and are differentiated based on the 
number of bedrooms in the units and on the average contract rent for 
the units. A unit-class must be included for each bedroom/rent 
category represented in the property.

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[FR Doc. 00-5122 Filed 3-1-00; 12:45 pm]
BILLING CODE 4210-27-C2CA 09MRN1.LOC