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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).