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 
What GAO Found

United States Government Accountability Office

Why GAO Did This Study

Highlights

Accountability Integrity Reliability

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.

Highlights of GAO-05-382T, a testimony 

before the Subcommittee on Housing and 

Community Opportunity, Committee on 

Financial Services, House of 

Representatives 

March 10, 2005

RURAL HOUSING SERVICE 

Overview of Program Issues 

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 

Urban cluster

Urbanized area

Source: GAO analysis of Census data.

Bakersfield MSA boundary

RHS ineligible area

0 20 40

miles

Bakersfield

Lamont

Taft

0 5 10

miles

Bakersfield

Lamont

Taft

MSA and grandfathering make more rural Taft ineligible (left), while density-based measures could 

make it eligible (right). 

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 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. 
Page 1 GAO-05-382T 

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;1

 1

GAO, Rural Housing: Changing the Definition of Rural Could Improve Eligibility 

Determinations, GAO-05-110 (Washington, D.C.: Dec. 3, 2004). 
Page 2 GAO-05-382T 

• three previous reports on RHS’s rental assistance budgeting and 

distribution processes;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.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.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 

 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). 
Page 3 GAO-05-382T 

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 
Page 4 GAO-05-382T 

and cash flows do not appear sufficient for basic maintenance or longterm 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. 

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 moderateincome 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. 

Background 
Page 5 GAO-05-382T 

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. 

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.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 

 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. 

Some Eligibility 

Requirements for RHS 

Programs Can Result 

in Similar Areas 

Receiving Dissimilar 

Treatment 

While Statute and 

Guidance Help RHS Staff, 

Determinations of 

Eligibility Require 

Judgment and Can Be 

Problematic 
Page 6 GAO-05-382T 

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 

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. 

Source: GAO.
Page 7 GAO-05-382T 

Figure 2: City Line of Brookside, Ohio, Divides Eligible from Ineligible Area 

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).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 

 6

Parkersburg, West Virginia, is not an eligible area. 

Eligibility Interpretations 

of Associations with Urban 

Areas May Be 

Questionable 

Source: GAO.
Page 8 GAO-05-382T 

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 

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. 

Fewer than 500 people/square mile

500 to 999 people/square mile

1,000 or more people/square mile

RHS ineligible area

Parkersburg urbanized area

Sources: RHS and Census data.

0 1.5 3

miles

Parkersburg

(33,099) Belpre

(6,660)

Vienna

(10,861)
Page 9 GAO-05-382T 

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 densitybased system such as the Census Bureau’s urbanized areas/urban clusters 

were used to indicate changes in population.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. 

 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. 

Changing Some Eligibility 

Requirements Could Better 

Delineate Boundaries for 

Urban-Rural Areas and 

Address Inconsistent 

Treatment of Similar 

Communities 
Page 10 GAO-05-382T 

Figure 4: Taft, California, Could Be Eligible Under Density-based Criteria 

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). 

Urban cluster

Urbanized area

Source: GAO analysis of Census data.

Bakersfield MSA boundary

RHS ineligible area

0 20 40

miles

Bakersfield

Lamont

Taft

0 5 10

miles

Bakersfield

Lamont

Taft
Page 11 GAO-05-382T 

Figure 5: Eliminating MSA Criterion Could Allow Circleville to Be Considered for 

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 

“Lack of Credit” 

Requirement Does Not 

Appear Central to 

Determining Eligibility 

Urban cluster

Urbanized area

Source: GAO analysis of Census data.

0 20 40

miles

Columbus

Circleville

Washington

Court House

RHS ineligible area

Columbus MSA boundary

Columbus

Circleville

Washington

Court House
Page 12 GAO-05-382T 

focused on income issues, and given RHS’s blanket policy, the “lack of 

credit” requirement is not central to determining participant eligibility. 

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. 

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). 

Opportunities to 

Improve RHS Rental 

Assistance Budgeting 

and Allocation 

Processes Exist 

RHS Overestimated 

Budgets for Section 521 

Program 
Page 13 GAO-05-382T 

Figure 6: Actual and Estimated Rental Assistance Expenditures, Per-Unit, Per-Year, 1990–2003 

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.8

 8

GAO, Standards for Internal Control in the Federal Government, GAO-AIMD-00-21.3.1 

(Washington, D.C.: November 1999). 

RHS Rental Assistance 

Program Was Not Adhering 

to Internal Control 

Standards 

Dollar expenditure per-unit per-year

OMB-based estimate of RHS expenditure

RHS estimate of RHS expenditure

Actual RHS expenditure

Source: GAO analysis of RHS data.

0

500

1,000

1,500

2,000

2,500

3,000

3,500

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003
Page 14 GAO-05-382T 

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. 

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. 

Internal Control 

Issues Contribute to 

Errors in Loan and 

Grants Databases 
Page 15 GAO-05-382T 

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. 

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 costeffectively as possible, providing Congress with a reliable or wellsupported 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 

Comprehensive 

Property Assessment 

Advocates Leveraged 

Solutions 
Page 16 GAO-05-382T 

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. 

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. 

Conclusions 
Page 17 GAO-05-382T 

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. 

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 

Matters for 

Congressional 

Consideration 
Page 18 GAO-05-382T 

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. 

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. 

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 

Recommendations for 

Executive Action 

Agency Comments 
Page 19 GAO-05-382T 

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. 

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. 

Contacts and 

Acknowledgements 

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