[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]
[[Page 12631]]
-----------------------------------------------------------------------
Part II
Department of Housing and Urban Development
-----------------------------------------------------------------------
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]]
-----------------------------------------------------------------------
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.
-----------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\1\ 12 U.S.C. 4501 et seq.; Pub. L. 102-550, approved Oct. 28,
1992.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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).
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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
[[Page 12634]]
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\
---------------------------------------------------------------------------
\6\ U.S. Department of Treasury, Government Sponsorship of the
Federal National Mortage Association and the Federal Home Loan
Mortgage Corporation(1996), page 3.
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\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).
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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).
---------------------------------------------------------------------------
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
[[Page 12635]]
Housing Goal for purchases of single family and multifamily mortgages.
---------------------------------------------------------------------------
\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).
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\25\ Secs. 1332(d)(2)(A) and 1334(d)(2)(A).
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\34\ HUD issued the proposed rule on February 16, 1995 (60 FR
9154) and the final rule on December 1, 1995 (60 FR 61846).
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\35\ Sec. 1332.
\36\ 60 FR 61851.
---------------------------------------------------------------------------
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.
---------------------------------------------------------------------------
\37\ 24 CFR 81.12.
\38\ 24 CFR 81.13.
\39\ 24 CFR 81.14.
---------------------------------------------------------------------------
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:
BILLING CODE 4210-27-P
[[Page 12642]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.000
[[Page 12643]]
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.
[[Page 12644]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.001
[[Page 12645]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.002
[[Page 12646]]
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\
---------------------------------------------------------------------------
\51\ See footnote 40.
---------------------------------------------------------------------------
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;
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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:
BILLING CODE 4210-27-P
[[Page 12649]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.003
BILLING CODE 4210-27-C
[[Page 12650]]
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:
BILLING CODE 4210-27-P
[[Page 12651]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.004
BILLING CODE 4210-27-C
[[Page 12652]]
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.
---------------------------------------------------------------------------
\54\ GSE to market ratio is calculated by dividing the
performance of the respective GSE by the performance of the market.
---------------------------------------------------------------------------
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.
[[Page 12653]]
(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.
---------------------------------------------------------------------------
\55\ GAO/RCED-98-49.
---------------------------------------------------------------------------
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:
BILLING CODE 4210-27-P
[[Page 12655]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.005
BILLING CODE 4210-27-C
[[Page 12656]]
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
----------------------------------------------------------------------------------------------------------------
2000 2001-2003
----------------------------------------------------------------------------------------------------------------
Proposed Goal Levels................... 0.9 percent........................ 1.0 percent.
[[Page 12657]]
Fannie Mae............................. $3.31 billion...................... $3.68 billion.
Freddie Mac............................ $2.46 billion...................... $2.73 billion.
----------------------------------------------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\60\ If this option were selected, appropriate subgoal
thresholds for the one-year transition period (2000) could be
developed.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\61\ A similar pro-rating technique is specified for the special
affordable multifamily subgoal in the 1995 Final Rule. See footnote
62.
---------------------------------------------------------------------------
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
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.
BILLING CODE 4210-27-P
[[Page 12687]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.007
[[Page 12688]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.008
[[Page 12689]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.009
BILLING CODE 4210-27-C
[[Page 12690]]
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
(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
[[Page 12701]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.010
[[Page 12702]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.011
[[Page 12703]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.012
BILLING CODE 4210-27-C
[[Page 12704]]
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).
BILLING CODE 4210-27-P
[[Page 12707]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.014
[[Page 12708]]
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.
---------------------------------------------------------------------------
[[Page 12709]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.015
BILLING CODE 4210-27-C
[[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.
---------------------------------------------------------------------------
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.
BILLING CODE 4210-P
[[Page 12720]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.017
[[Page 12721]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.018
[[Page 12722]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.019
BILLING CODE 4210-27-C
[[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\
---------------------------------------------------------------------------
\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.
BILLING CODE 4210-27-P
[[Page 12725]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.020
BILLING CODE 4210-27-C
[[Page 12726]]
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.
BILLING CODE 4210-27-P
[[Page 12733]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.022
[[Page 12734]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.023
BILLING CODE 4210-27-C
[[Page 12735]]
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).
BILLING CODE 4210-27-P
[[Page 12737]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.024
BILLING CODE 4210-27-C
[[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:
BILLING CODE 4210-27-P
[[Page 12740]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.025
[[Page 12741]]
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.
BILLING CODE 4210-27-P
[[Page 12742]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.026
[[Page 12743]]
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.
BILLING CODE 4210-27-P
[[Page 12744]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.027
[[Page 12745]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.028
[[Page 12746]]
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.
[[Page 12747]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.029
[[Page 12748]]
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).
[[Page 12749]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.030
BILLING CODE 4210-27-C
[[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).
[[Page 12752]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.031
[[Page 12753]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.032
[[Page 12754]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.033
BILLING CODE 4210-27-C
[[Page 12755]]
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).
BILLING CODE 4210-27-P
[[Page 12757]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.034
[[Page 12758]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.035
[[Page 12759]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.036
[[Page 12760]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.037
[[Page 12761]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.038
[[Page 12762]]
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.
BILLING CODE 4210-27-P
[[Page 12763]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.039
[[Page 12764]]
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.
[[Page 12765]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.040
BILLING CODE 4210-27-C
[[Page 12766]]
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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
(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\
---------------------------------------------------------------------------
\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.
---------------------------------------------------------------------------
[[Page 12779]]
[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
[[Page 12782]]
[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.
---------------------------------------------------------------------------
\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.
BILLING CODE 4210-27-P
[[Page 12791]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.047
[[Page 12792]]
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.
---------------------------------------------------------------------------
[[Page 12793]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.048
BILLING CODE 4210-27-C
[[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\
---------------------------------------------------------------------------
\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.
BILLING CODE 4210-27-P
[[Page 12796]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.049
[[Page 12797]]
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\
---------------------------------------------------------------------------
\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.
[[Page 12798]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.050
BILLING CODE 4210-27-C
[[Page 12799]]
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\
---------------------------------------------------------------------------
\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.
BILLING CODE 4210-27-P
[[Page 12804]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.051
[[Page 12805]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.052
[[Page 12806]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.053
[[Page 12807]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.054
[[Page 12808]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.055
[[Page 12809]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.056
[[Page 12810]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.057
[[Page 12811]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.058
[[Page 12812]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.059
[[Page 12813]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.060
[[Page 12814]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.061
[[Page 12815]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.062
[[Page 12816]]
[GRAPHIC] [TIFF OMITTED] TP09MR00.063
[FR Doc. 00-5122 Filed 3-1-00; 12:45 pm]
BILLING CODE 4210-27-C2CA 09MRN1.LOC