Rural Housing Service
Overview of Program Issues Gao ID: GAO-05-382T March 10, 2005The rural America of 2005 is far different from the rural America of the 1930s, when the federal government first began to provide housing assistance to rural residents. Advances in transportation, computer technology, and telecommunications, along with the spread of suburbia, have linked many rural areas to urban areas. These changes, along with new fiscal and budget realities, raise questions about how Rural Housing Service (RHS) programs could most effectively and efficiently serve rural America.
This testimony is based on a report on how RHS determines which areas are eligible for rural housing programs, three reports on RHS's rental assistance budgeting and distribution processes, and a report we are releasing today on internal control issues with RHS's loans and grants databases. GAO found that while RHS has significantly improved the housing stock in rural America and has made progress in addressing problems, several issues prevent the agency from making the best use of resources. Specifically: (1) Statutory requirements for program eligibility, including those related to metropolitan statistical areas (MSA), "grandfathering" communities, and demonstrating a "serious lack of mortgage credit," are of marginal utility. For example, using density measures rather than MSAs might allow RHS to better differentiate urban and rural areas, and phasing out the "grandfathering" of communities could better ensure that RHS makes more consistent eligibility determinations; (2) RHS has consistently overestimated its rental assistance budget needs by using higher inflation rates than recommended by the Office of Management and Budget and incorrectly applying those rates. Also RHS lacked sufficient internal controls to adequately monitor the use of rental assistance funds, particularly for fund transfers and income verifications. RHS has been taking actions that should correct many of the rental assistance shortcomings GAO identified; and (3) GAO found incorrect, incomplete, and inconsistent entries in RHS's loans and grants databases. Until RHS can demonstrate that its system edit functions or other design features can ensure the accuracy of data in its databases, second-party review is necessary to meet internal control standards.
GAO-05-382T Rural Housing Service: Overview of Program Issues
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Testimony:
Before the Subcommittee on Housing and Community Opportunity, Committee
on Financial Services, House of Representatives:
United States Government Accountability Office:
GAO:
For Release on Delivery Expected at 2:00 p.m. EST:
Thursday, March 10, 2005:
Rural Housing Service:
Overview of Program Issues:
Statement of William B. Shear, Director, Financial Markets and
Community Investment:
GAO-05-382T:
GAO Highlights:
Highlights of GAO-05-382T, a testimony before the Subcommittee on
Housing and Community Opportunity, Committee on Financial Services,
House of Representatives
Why GAO Did This Study:
The rural America of 2005 is far different from the rural America of
the 1930s, when the federal government first began to provide housing
assistance to rural residents. Advances in transportation, computer
technology, and telecommunications, along with the spread of suburbia,
have linked many rural areas to urban areas. These changes, along with
new fiscal and budget realities, raise questions about how Rural
Housing Service (RHS) programs could most effectively and efficiently
serve rural America.
What GAO Found:
This testimony is based on a report on how RHS determines which areas
are eligible for rural housing programs, three reports on RHS‘s rental
assistance budgeting and distribution processes, and a report we are
releasing today on internal control issues with RHS‘s loans and grants
databases. GAO found that while RHS has significantly improved the
housing stock in rural America and has made progress in addressing
problems, several issues prevent the agency from making the best use of
resources. Specifically:
· Statutory requirements for program eligibility, including those
related to metropolitan statistical areas (MSA), ’grandfathering“
communities, and demonstrating a ’serious lack of mortgage credit,“ are
of marginal utility. For example, using density measures rather than
MSAs might allow RHS to better differentiate urban and rural areas, and
phasing out the ’grandfathering“ of communities could better ensure
that RHS makes more consistent eligibility determinations.
· RHS has consistently overestimated its rental assistance budget needs
by using higher inflation rates than recommended by the Office of
Management and Budget and incorrectly applying those rates. Also RHS
lacked sufficient internal controls to adequately monitor the use of
rental assistance funds, particularly for fund transfers and income
verifications. RHS has been taking actions that should correct many of
the rental assistance shortcomings GAO identified.
· GAO found incorrect, incomplete, and inconsistent entries in RHS‘s
loans and grants databases. Until RHS can demonstrate that its system
edit functions or other design features can ensure the accuracy of data
in its databases, second-party review is necessary to meet internal
control standards.
Statutory Requirements Can Impede Eligibility:
[See PDF for image]
MSA and grandfathering make more rural Taft ineligible (left), while
density-based measures could make it eligible (right).
[End of figure]
What GAO Recommends:
GAO suggested statutory changes to help improve eligibility
determinations in rural housing programs and enhance RHS‘s tenant
income verification process. GAO also made a number of recommendations
aimed at improving RHS program operations.
www.gao.gov/cgi-bin/getrpt?GAO-05-382T.
To view the full product, including the scope and methodology, click on
the link above. For more information, contact William B. Shear at (202)
512-4325 or shearw@gao.gov.
[End of section]
Mr. Chairman and Members of the Subcommittee:
I am pleased to be here today to discuss the management of Rural
Housing Service (RHS) programs and our examinations of agency efforts.
RHS makes a significant investment in affordable housing for low-income
rural Americans through a variety of direct and guaranteed loan and
grant programs. RHS manages a single-family and multifamily direct loan
portfolio of about $28 billion, oversees a program that guarantees
about $3 billion in single-family mortgages annually, and administers
over $500 million in rental assistance payments each year. However, the
rural America of 2005 is different from the rural America of the 1930s,
when the federal government first began to provide housing assistance
to rural residents. Advances in transportation, computer technology,
and telecommunications, along with the spread of suburbia, have linked
many rural to urban areas and blurred distinctions between them. Yet
the need for decent, safe, and affordable low-income housing remains
strong in rural areas. The changing face of rural America, advances in
technology affecting program administration, and new fiscal and budget
realities raise questions about how RHS programs could most effectively
and efficiently serve rural Americans.
Thus, my principle objective today is to present an overview of issues
you may want to consider as you deliberate on how to best improve
housing services for rural Americans.
This statement is primarily based on reports we did for this
Subcommittee as well as for the Ranking Minority Member of the
Subcommittee on Agriculture, Rural Development, and Related Agencies,
Senate Committee on Appropriations:
* a December 2004 report on how RHS determines which areas are eligible
for rural housing programs;[Footnote 1]
* three previous reports on RHS's rental assistance budgeting and
distribution processes;[Footnote 2] and:
* a report we are releasing today addressed to the RHS Administrator
that describes errors in, and internal control issues for, RHS's loans
and grants databases.[Footnote 3]
Finally, I will provide a few comments addressing the recently
completed Comprehensive Property Assessment, which RHS initiated in
response to our May 2002 study on long-term needs in the Section 515
multifamily housing program.[Footnote 4]
In summary, while RHS has significantly improved the housing stock in
rural America and RHS management has made progress in addressing
problems we have identified in the past, several issues still prevent
the agency from making the best use of its resources.
* Statutory requirements for program eligibility may not reflect
changes in rural areas or best determine which areas qualify for RHS
housing programs. Specifically, we found the statutory requirements
relating to metropolitan statistical areas (MSA), the ability to
"grandfather" eligibility, and demonstration of a serious lack of
mortgage credit for low-and moderate-income families to be of marginal
utility. Changes to these requirements, such as using density measures
rather than the currently used MSA criterion, might allow RHS to better
differentiate urban and rural areas. Also, phasing out the
"grandfathering" of communities that experience changes in eligibility
because of inclusion in an MSA could better ensure that RHS more
consistently makes eligibility determinations for rural housing
programs. Finally, "lack of credit" does not appear to be as great a
challenge to rural Americans gaining access to affordable housing as
lack of income or the inability to repay loans. RHS already targets its
programs and services, based on income, to areas and populations of
greatest need. As a result, the "lack of credit" requirement does not
appear necessary to appropriately determine program eligibility.
* Weaknesses in RHS's budget estimation and oversight of rental
assistance funds increase the risk that the agency is not efficiently
or appropriately allocating resources. We found that RHS had
consistently overestimated its budget needs for rental assistance
contracts in its Section 521 program by using higher inflation rates
than recommended and incorrectly applying those rates. Using and
correctly applying the inflation rates provided by the Office of
Management and Budget (OMB) would help the agency more accurately
estimate its rental assistance needs. Additionally, RHS lacked
sufficient internal controls to adequately monitor the use of rental
assistance funds, particularly in its funds transfer processes,
methodology for supervisory reviews, and tenant income verification
processes. Establishing centralized guidance on transferring unused
rental assistance, improving sampling methods in the tenant file review
process, and improving processes for verifying tenant information could
help ensure that these funds are being effectively administered and
used. Also, making a statutory change to give RHS access to the
Department of Health and Human Services' National Directory of New
Hires, which provides recent nationwide data on wages, could help the
agency verify tenant income information. RHS has recently moved on a
number of fronts to correct the many rental assistance program
shortcomings identified in our reports. While it is too early for us to
fully review the impact of these changes, we believe that changes in
how rental assistance budgets are estimated and the application or
strengthening of internal controls, consistent with our
recommendations, would result in greater efficiency and resource
savings in this pivotal program.
* Although RHS has worked to improve its management information
systems, we found incorrect, incomplete, and inconsistent entries in
its loans and grants databases, and the system "edit" functions do not
appear to flag or correct these errors. Further, RHS does not have a
process to review these databases for accuracy. Additional internal
control measures could ensure more accurate data entry and reporting,
particularly at the field office level, and such an effort could ensure
that RHS' investment in system upgrades would provide more meaningful
and useful information to the agency itself, Congress, and the public.
* RHS recently contracted for a study called the Comprehensive Property
Assessment. The study was done to develop a baseline for assessing the
portfolio's physical and financial condition. Its principal findings--
that RHS's multifamily housing portfolio is aging rapidly and property
reserves and cash flows do not appear sufficient for basic maintenance
or long-term rehabilitation needs--are consistent with our work in the
area. The study concludes that leveraging market-based solutions with
traditional approaches would provide a more cost-effective alternative
to using only federal dollars. It also concludes that while the
solutions proposed will cost more than current budget levels, delaying
actions to address the physical, fiscal, and market issues documented
in the study could result in even greater budget needs in the future.
Background:
The Housing Act of 1949 authorized new rural lending programs to
farmers, which were administered by RHS's predecessor, the Farmers Home
Administration, within the U.S. Department of Agriculture (USDA). RHS
now facilitates homeownership, develops rental housing, and promotes
community development through loan and grant programs in rural
communities. Over the decades, Congress changed the requirements for
rural housing eligibility--for example, by changing population limits-
-and rural housing programs have evolved to serve low-and moderate-
income people of all occupations. The current definition of rural
considers factors such as whether an area is contained in an MSA, is
"rural in character," and "has a serious lack of mortgage credit for
lower-and moderate-income families.":
RHS's Section 521 Rental Assistance Program is the agency's largest
line-item appropriation, with an annual budget of more than $500
million. The program provides rental subsidies for approximately
250,000 tenants who pay no more than 30 percent of their income for
rent (RHS pays the balance to the property owner). The units in which
the tenants live are created through RHS's Section 515 Multifamily
Direct Rural Rental Housing Loans and Section 514 Multifamily Housing
Farm Labor Loans programs. The Section 515 and 514 programs provide
developers loans subsidized with interest rates as low as 1 percent to
help build affordable rental housing for rural residents and farm
workers.
Some Eligibility Requirements for RHS Programs Can Result in Similar
Areas Receiving Dissimilar Treatment:
RHS staff determine which areas are eligible for RHS housing programs
by interpreting statutory requirements and agency guidance; however,
their determinations involve judgment and may be open to question.
Additionally, some eligibility requirements often result in areas with
similar characteristics receiving different designations. For example,
the requirement that an eligible area cannot be part of an MSA often
results in ineligibility for what appears to be a rural area. Also, the
"lack of credit" in rural areas remains an eligibility requirement,
even though USDA has reported that a lack of income and ability to pay
the mortgage appear to be the greater problems than a lack of credit
for rural Americans.
While Statute and Guidance Help RHS Staff, Determinations of
Eligibility Require Judgment and Can Be Problematic:
Section 520 of the Housing Act of 1949, as amended, defines rural for
most RHS housing programs. Using the statute and instructions
promulgated by the national office, state and local (together, field)
offices determine the boundaries to delineate eligible areas from
ineligible areas--a task field office officials acknowledged is time-
consuming, based on judgment, and can be problematic.[Footnote 5] The
statutory definition generally identifies eligible rural areas as those
with populations up to 20,000 and defines "rural" and "rural areas" as
any open country or any place, town, village, or city that is not part
of or associated with an urban area.
Specifically, there are several population levels at which communities
may be determined eligible, but as a community's population increases,
the statute imposes additional requirements that include being "rural
in character" (a concept that is not defined in the statute), having a
serious lack of mortgage credit, or not being located within an MSA.
Certain communities with populations above 10,000 but not exceeding
25,000 may be "grandfathered in," based on prior eligibility if they
still met the "rural in character" and "lack of credit" criteria.
USDA's instructions give its field offices flexibility in implementing
the statute. Field office officials said that drawing the eligibility
boundaries required an element of judgment because "rural in character"
is open to interpretation--even with the overall national guidance on
the statute and review of census populations, MSA standards, maps,
aerial photographs, and visits to communities.
Even when local supervisors fully understand the local conditions and
rural character of an area, finding a way to equitably decide on a
boundary is sometimes problematic. For instance, field staff in
Maryland told us that in response to December 2002 national guidance,
they stopped using natural features such as rivers or mountains as
eligibility boundaries for communities. Maryland now uses only roads.
Figure 1 shows a new boundary, a road that divides the eligible area on
the left from the ineligible area on the right. RHS local office
officials told us that the "road only" criteria forced them to find the
nearest public road to a populated section of Hagerstown, which happens
to go through farmland. The result is that apparently similar rural
areas received different designations.
Figure 1: Road Serving as Eligible Area Boundary outside Hagerstown,
Maryland:
[See PDF for image]
[End of figure]
Figure 2 shows an area in Brookside, Ohio, where the city line divides
the eligible from the ineligible area. The Maryland example illustrates
that using the only physical boundary available resulted in one piece
of farmland receiving a rural designation and the other not. The
Brookside example shows that using a political boundary also did not
necessarily result in a readily discernible urban-rural difference.
Figure 2: City Line of Brookside, Ohio, Divides Eligible from
Ineligible Area:
[See PDF for image]
[End of figure]
Eligibility Interpretations of Associations with Urban Areas May Be
Questionable:
Our analysis of RHS eligible areas nationwide, compared with census
data, found approximately 1,300 examples where communities with
populations at or below 10,000 were within or contiguous with urban
areas that had populations of 50,000 or more. The statute states that
eligible communities cannot be a part of or associated with an urban
area. Some field staff determinations of eligibility in these cases
might be questionable as some of these communities, despite their low
populations, might not be considered rural, and thus, eligible.
For example, field staff told us that Belpre, Ohio, is eligible for RHS
programs because it meets both the population and "rural in character"
requirements. However, Belpre is contiguous with Parkersburg, West
Virginia, which has a population of more than 33,000 (see fig.
3).[Footnote 6] In addition, the 2000 census considers Belpre, along
with Parkersburg and Vienna, West Virginia, as part of an urbanized
area because its total population exceeds 50,000. Although it is across
the Ohio River from Parkersburg, bridges have connected Belpre and
Parkersburg for decades and, according to a Belpre city employee, many
people from Belpre work in Parkersburg. Furthermore, most of Belpre has
a population density of 1,000 people or more per square mile, which the
Census Bureau considers "densely settled" and a measure of
urbanization. For these reasons, it is unclear whether Belpre meets the
eligibility requirements.
Figure 3: Belpre, Ohio, Is Part of the Parkersburg, West Virginia-Ohio,
Urbanized Area:
[See PDF for image]
Note: Area density levels are shown by census tract. Census tracts are
small, relatively permanent statistical subdivisions of a county or
statistically equivalent entity used to provide a stable set of
geographical units for presenting decennial census data.
[End of figure]
Changing Some Eligibility Requirements Could Better Delineate
Boundaries for Urban-Rural Areas and Address Inconsistent Treatment of
Similar Communities:
Changes to the way eligibility is defined might allow RHS to better
designate "rural" areas and treat communities with similar
characteristics more consistently. For instance, eliminating the MSA
requirement and "grandfathering" might help RHS better serve its
clients. To illustrate, we found rural communities with populations
exceeding 10,000 that were directly impacted by the MSA and
"grandfather" restrictions. Because MSAs are county-based and may
contain both urban and rural areas, the MSA restriction and the
grandfathering of certain communities resulted in some communities
being eligible while others with similar demographic profiles were
ineligible.
We looked at two communities within the Bakersfield, California, MSA,
which is basically rural outside the environs of Bakersfield (see fig.
4). Lamont was grandfathered because it lost eligibility when its
population went above 10,000 at the 1980 census. Taft's population was
already over 10,000 prior to the 1980 census, so Taft was not eligible
for grandfathering. The right side of the figure shows what would
happen if MSAs and grandfathered eligibility were removed from the
equation and a density-based system such as the Census Bureau's
urbanized areas/urban clusters were used to indicate changes in
population.[Footnote 7] Taft would be in its own urban cluster outside
of the Bakersfield urbanized area, which happens to include Lamont.
Based on our visit, we believe this scenario, where the more rural
community would be the one eligible, is more in line with the overall
purpose of the legislation than the current situation.
Figure 4: Taft, California, Could Be Eligible Under Density-based
Criteria:
[See PDF for image]
[End of figure]
In another example, by eliminating the MSA criterion, RHS could review
the eligibility of Washington Court House and Circleville, Ohio, based
on population and rural character criteria. Additionally, using density-
based mapping could help RHS draw boundaries around these communities,
which although Census-designated as "urban clusters," still meet rural
housing program population requirements (see fig. 5).
Figure 5: Eliminating MSA Criterion Could Allow Circleville to Be
Considered for Eligibility:
[See PDF for image]
[End of figure]
"Lack of Credit" Requirement Does Not Appear Central to Determining
Eligibility:
The statute imposes a requirement to demonstrate a serious lack of
mortgage credit for lower-and moderate-income families in communities
with populations of 10,001 to 25,000. RHS has a policy stating that a
serious lack of mortgage credit at rates and terms comparable with
those offered by the agency exists in all rural areas. However, a study
by USDA's Economic Research Service concluded that credit problems in
rural areas are primarily limited to sparsely populated or remote rural
areas; such communities generally do not fall into the population range
specified above. Many of the RHS officials and industry experts with
whom we spoke also saw the primary "credit" problem as lack of income
rather than lack of credit.
Additionally, eligibility requirements for RHS programs are based on
income levels. The agency uses funding set asides, funding allocations,
application reviews, and state-level strategic plans to determine areas
and populations of greatest need. As a result, RHS program activity
already is focused on income issues, and given RHS's blanket policy,
the "lack of credit" requirement is not central to determining
participant eligibility.
Opportunities to Improve RHS Rental Assistance Budgeting and Allocation
Processes Exist:
We reported that weaknesses in RHS's budget estimation and oversight of
rental assistance funds had resulted in largely overestimated budget
levels and increased the risk that the agency was not efficiently or
appropriately budgeting and allocating resources. Additionally, RHS
lacked sufficient internal control to adequately monitor the
disbursement of rental assistance funds.
RHS Overestimated Budgets for Section 521 Program:
In March 2004, we reported that since 1990, RHS had consistently
overestimated its budget needs for the rental assistance program.
Concern had arisen about this issue because in early 2003 RHS reported
hundreds of millions of dollars in unexpended balances tied to its
rental assistance contracts. Specifically, in estimating needs for its
rental assistance contracts, RHS used higher inflation factors than
recommended, did not apply the inflation rates correctly to each year
of the contract, and based estimates of future spending on recent high
usage rather than average rates.
First, the agency used inflation factors that were higher than those
recommended by OMB for use in the budget process. Second, RHS did not
apply its inflation rate separately to each year of a 5-year contract,
but instead compounded the rate to reflect the price level in the fifth
year and applied that rate to each contract year. The result was an
inflation rate that was more than five times the rate for the first
year. For example, using these two methods, RHS overestimated its 2003
budget needs by $51 million or 6.5 percent. Third, RHS based its
estimates of future expenditure rates on recent maximum expenditures,
rather than on the average rates at which rental assistance funds were
being expended.
Additionally, our analysis of rental assistance payment data showed
that the agency had overestimated its budget needs almost every year
since 1990, the earliest year for which we gathered data. Where we were
able to obtain sufficient data from RHS, our analysis showed that if
RHS had used and correctly applied OMB inflation rates to its base per-
unit rates, its estimates would have been closer to actual expenditures
(see fig. 6).
Figure 6: Actual and Estimated Rental Assistance Expenditures, Per-
Unit, Per-Year, 1990-2003:
[See PDF for image]
[End of figure]
RHS Rental Assistance Program Was Not Adhering to Internal Control
Standards:
We also reported that RHS was not adhering to internal control
standards regarding segregation of duties, rental assistance transfers,
and tenant income verification reviews.
A single employee within the agency was largely responsible for both
the budget estimation and allocation processes for the rental
assistance program. According to GAO internal control standards, key
duties and responsibilities need to be divided or segregated among
different people to reduce the risk of error or fraud.[Footnote 8]
Moreover, RHS did not have a comprehensive policy for transferring
rental assistance. As a result, insufficient guidance on the transfer
process limited RHS's ability to move unused rental assistance to
properties that had tenants with the greatest need.
Finally, because RHS conducts reviews infrequently and covers a small
percentage of tenant files, the agency cannot reasonably ensure that
tenants' income and assets, and ultimately rental assistance payments,
are adequately verified. RHS's national, state, and local offices share
responsibility for monitoring the rental assistance program, with the
local offices performing the primary supervisory review every 3 years.
These triennial supervisiory reviews are RHS's primary tool for
detecting misreporting of tenant income, which may result in
unauthorized rental assistance payments. But the shortcomings in the
review process increase the risk that RHS will provide rental
assistance to tenants that may not be eligible. Alternate methods of
verifying tenant information, such as internal database checks and wage
matching, also have limited effectiveness but could help improve
internal control if properly designed or implemented.
Internal Control Issues Contribute to Errors in Loan and Grants
Databases:
Today we are releasing a report addressed to the RHS Administrator on
internal control issues in the Information Resource Management (IRM)
databases. We issued the report as a follow-up to our work addressing
the definition of rural used for rural housing programs. During the
earlier review, we identified several issues that raised concerns about
the accuracy of the information in the IRM databases. For example,
while we originally intended to geocode (match) 5 years of the national
RHS housing loan and grant portfolio to specific communities, the time
needed to ensure the reliability of the data required us to limit much
of our analysis to five states.
In reviewing 29,000 records for five states we found incorrect,
incomplete, and inconsistent entries. For example, over 8 percent of
the community names or zip codes were incorrect. Additionally,
inconsistent spellings of community names distorted the number of
unique communities in the database. More than 400 entries lacked
sufficient information (street addresses, community names, and zip
codes) needed to identify the community to which the loan or grant had
been made. As a result, some communities served by RHS were double
counted, others could not be counted, and the ability to analyze the
characteristics of communities served was compromised.
Since these data form the basis of information used to inform Congress
(and the public) about the effectiveness of RHS programs, data accuracy
is central to RHS program management and the ability of Congress and
other oversight bodies to evaluate the agency and its programs. While
the agency has worked to improve its management information systems
(for example, since 2002, the agency has spent $10.3 million to improve
its management information systems including developing single and
multifamily program data warehouses which were designed to improve its
reporting capabilities), the system still relies upon information
collected and entered from field offices.
However, RHS does not have procedures for second-party review of the
data in IRM systems. Moreover, while the IRM databases have edit
functions in place that are intended to prevent the entry of
nonconforming data (such as the entry of a community name in a street
address field), the functions are not preventing incorrect or
incomplete entries. Until RHS can demonstrate that its edit functions
or other data entry design features can ensure the accuracy and
completeness of the data in the IRM databases, second-party review
would be necessary.
Comprehensive Property Assessment Advocates Leveraged Solutions:
Our 2002 report to this subcommittee on RHS's Section 515 multifamily
program concluded that with little new construction and limited
prepayment at that time, maintaining the long-term quality of the aging
housing stock in the program portfolio had become the overriding issue
for the program. We found that RHS did not have a process to determine
and quantify the portfolio's long-term rehabilitation needs. As a
result, RHS could not ensure that it was spending its limited funds as
cost-effectively as possible, providing Congress with a reliable or
well-supported estimate of what was needed to ensure the physical and
fiscal "health" of the multifamily portfolio, and prioritizing those
needs relative to the individual housing markets. We recommended that
USDA undertake a comprehensive assessment of long-term capital and
rehabilitation needs for the Section 515 portfolio. We also recommended
that USDA use the results of the assessment to set priorities for
immediate rehabilitation needs and develop an estimate for Congress on
the amounts and types of funding needed to deal with long-term needs.
In response to our recommendation, RHS commissioned a consulting firm
to assess the condition and rehabilitation needs of its multifamily
portfolio. RHS released the study in November 2004. The principal
findings--that the housing stock represented in the portfolio is aging
rapidly and that property reserves and cash flows are not sufficient
for basic maintenance or long-term rehabilitation needs--are in line
with our findings in 2002. The study concludes that continuing the
status quo would put undue stress on the rental assistance budget and
proposes leveraged solutions that combine market-based solutions with
private-sector funding as a more cost-effective alternative to using
only federal dollars. In addition, the study concludes that while its
proposed solutions will cost more than current budget levels, delaying
actions to address the portfolio's physical, fiscal, and market issues
will result in even greater budget needs in the future.
Conclusions:
RHS has made progress in improving program management over the past few
years. For example, when we began our work on the multifamily loan
program in June 2001, agency officials could not provide us with the
number of properties in the portfolio or a list of where properties
were located. Today, with the exception of some database errors we
pointed out that RHS officials have committed to correct, RHS knows
where its multifamily properties are located and has developed a
revitalization strategy to deal with the physical, fiscal, and market
issues identified. However, the agency still faces challenges in areas
that include the basic question of how best to determine what areas are
rural, how to best manage rental assistance (the largest budget item in
RHS), and how to ensure that data entered into management information
systems are accurate. Despite these challenges, opportunities exist to
provide more flexibility and improve existing processes that could
better help RHS serve its clients while responding to the challenges of
current fiscal and budget realities.
For example, while determining what areas are eligible for rural
housing programs will always require an element of judgment, several
changes to the current eligibility requirements could help RHS make
more consistent eligibility determinations. If MSAs were removed from
the eligibility criteria, RHS officials could make determinations for
more communities based on population data and "rural character." And,
using an alternative measure such as the Census Bureau's urbanized
areas and urban cluster classifications as a guide could help RHS
better draw boundaries around rural areas, because the density-based
measures provide finer-scale information. Additionally, eligible
communities within MSAs would not need to be "grandfathered" based on
previous eligibility, a provision which essentially gives these
communities an advantage over similar though ineligible towns located
in MSAs. Finally, the "lack of credit" requirement could be removed
with no detriment to RHS housing programs.
We noted further opportunities for improvement in RHS's largest
program--the rental assistance program, which has an annual budget of
over $500 million and provides rental subsidies to about 250,000 rural
tenants. Problems with its budget estimating processes caused the
agency to consistently overstate its spending needs, resulting in
hundreds of millions of dollars in unexpended balances. Consistently
overstating funding needs for one program also undermines the
congressional budget process by making funds unavailable for other
programs. In addition, RHS's internal controls had not provided
reasonable assurance that rental assistance resources were being used
effectively. We questioned whether internal control weaknesses were
preventing rental assistance funds from going to properties with the
neediest tenants. RHS has recently moved on a number of fronts to
correct the many rental assistance program shortcomings identified in
our reports. For example, RHS has told us that it will follow OMB
budget estimation guidance, that it is correcting the program's
segregation of duty issues, has issued standardized guidelines on
rental assistance transfers, and is revamping its supervisory review
process. While it is too early for us to fully review the impact of
these changes, we believe that changes in how rental assistance budgets
are estimated and the application or strengthening of internal
controls, consistent with our recommendations, would result in greater
efficiency and resource savings in this pivotal program.
Finally, in reviewing RHS property data for selected states, we
identified various errors that raise questions about the accuracy of
agency's data. Although the agency is making efforts to improve its
data systems, our findings suggest additional measures could ensure
more accurate data entry and reporting, particularly at the field
level. In addition to improving the accuracy of the information, such
an effort could ensure that RHS's investment in system upgrades would
provide more meaningful and useful information to the agency itself,
Congress, and the public.
Matters for Congressional Consideration:
To improve eligibility determinations in rural housing programs, we
suggested that Congress may wish to consider eliminating the MSA
criterion, recommending that RHS use density measures as a basis for
its eligibility decisions, phasing out the practice of "grandfathering"
communities, and eliminating the "lack of credit" requirement.
To help the agency verify tenant information, we also suggested that
the Congress consider giving RHS access to the Department of Health and
Human Services' National Directory of New Hires (New Hires), which
includes centralized sources of state wage, unemployment insurance, and
new hires data for all 50 states, and it would provide nationwide data
for wage matching. Congress already granted HUD the authority to
request and obtain data from New Hires in January 2004, and as part of
its initiative to reduce improper rent subsidies for its rental
assistance program, HUD is making New Hires information available to
public housing authorities who are responsible for, among other things,
verifying tenant income and calculating rent subsidies correctly. HUD
plans to make the data from the new hires database available to
property owners by fiscal year 2006.
Recommendations for Executive Action:
To more accurately estimate rental assistance budget needs, we
recommended that the Secretary of Agriculture require program officials
to use and correctly apply the inflation rates provided by OMB in its
annual budget estimation processes.
To ensure that rental assistance funds are effectively distributed to
properties that have tenants with the greatest need, we recommended
that the Secretary of Agriculture require program officials to
establish centralized guidance on transferring unused rental
assistance, improve sampling methods to ensure a sufficient number of
tenant households are selected for supervisory reviews, and improve
tenant verification of information, including more effective use of
alternate methods of income verification.
To improve data entry and accuracy, we recommend that RHS formally
advise field staff to establish a second-party review of data in the
IRM databases are accurate and complete, require correction of errors
in existing information, and ensure that system edit functions are
properly functioning.
Agency Comments:
USDA generally agreed with our matters for congressional consideration,
stating that our report on eligibility articulates how the use of MSAs
has resulted in disparate treatment of some communities. USDA added
that applying a density-based measure might have merit but that further
study would be needed to properly define such a measure for nationwide
application. We concur with this position. In addition, USDA stated
that the "lack of credit" requirement could be removed with no
detriment to RHS housing programs. USDA initially disagreed with our
finding that its rental assistance budget estimates were too high,
questioning whether we demonstrated that using inflation rate
projections from the President's Budget would provide a more accurate
budget estimate. However, USDA has now reported that it will adopt OMB
estimates, and it appears that RHS now agrees with our report findings.
USDA also generally agreed with most of our recommendations on
monitoring and internal controls. RHS has recently issued regulations
and an asset management handbook on transferring unused rental
assistance and expanded guidance on income verification. Also, it
appears that RHS is acting on our recommendation to improve sampling
methods to ensure a sufficient number of tenant households are selected
for supervisory reviews; that is, the agency has informed us that it is
revamping that process. Finally, the RHS Administrator has generally
agreed to implement our recommendations on the IRM databases.
Mr. Chairman, this concludes my statement. I would be pleased to
respond to any questions you or members of the Subcommittee may have.
Contacts and Acknowledgements:
For more information regarding this testimony, please contact William
B. Shear at (202) 512-4325 or shearw@gao.gov or Andy Finkel at (202)
512-6765 or finkela@gao.gov. Individuals making key contributions to
this testimony also included Martha Chow, Katherine Trimble, and
Barbara Roesmann.
FOOTNOTES
[1] GAO, Rural Housing: Changing the Definition of Rural Could Improve
Eligibility Determinations, GAO-05-110 (Washington, D.C.: Dec. 3, 2004).
[2] [2] GAO, Rural Housing Service: Updated Guidance and Additional
Monitoring Needed for Rental Assistance Distribution Process, GAO-04-
937 (Washington, D.C.: Sept. 13, 2004); Rural Housing Service: Agency
Has Overestimated Its Rental Assistance Budget Needs over the Life of
the Program,GAO-04-752 (Washington, D.C.: May 20, 2004); and Rural
Housing Service: Standardization of Budget Estimation Processes Needed
for Rental Assistance Programs, GAO-04-424 (Washington, D.C.: Mar. 25,
2004).
[3] GAO, Information Resource Management Internal Control Issues, GAO-
05-288R (Washington, D.C.: Mar. 10, 2005).
[4] GAO, Multifamily Rural Housing: Prepayment Potential and Long-Term
Rehabilitation Needs for Section 515 Properties, GAO-02-397
(Washington, D.C.: May 10, 2002).
[5] The definition of rural applies to most RHS housing programs.
However, two programs--farm labor housing loans and grants--do not
require that applicants live in rural areas.
[6] Parkersburg, West Virginia, is not an eligible area.
[7] Census defines an urbanized area as a continuously built-up area
with a population of at least 50,000, comprising one or more places and
adjacent densely settled areas. An urban cluster consists of densely
settled territory that has at least 2,500 people but fewer than 50,000
people.
[8] GAO, Standards for Internal Control in the Federal Government, GAO-
AIMD-00-21.3.1 (Washington, D.C.: November 1999).
