Small Business Administration: Additional Measures Needed to
Assess 7(a) Loan Program's Performance (13-JUL-07, GAO-07-769).						 
                                                                 
The Small Business Administration's (SBA) 7(a) program,
initially established in 1953, provides loan guarantees to small
businesses that cannot obtain credit in the conventional lending
market. In fiscal year 2006, the program assisted more than
80,000 businesses with loan guarantees of nearly $14 billion.
This report examines (1) the program's purpose, based on its
legislative history, and performance measures; (2) evidence of
constraints, if any, affecting small businesses' access to
credit; (3) the types of small businesses served by 7(a) and
conventional loans; and (4) differences in SBA's estimates and
reestimates of the program's credit subsidy costs. GAO analyzed
agency documents, studies on the small business lending market,
and data on the characteristics of small business borrowers and
loans.

-------------------------Indexing Terms------------------------- 
REPORTNUM:   GAO-07-769						        
    ACCNO:   A72646 						        
  TITLE:     Small Business Administration: Additional Measures
Needed to Assess 7(a) Loan Program's Performance							 
     DATE:   07/13/2007 
  SUBJECT:   Credit
             Cost analysis
             Government guaranteed loans
             Lending institutions
             Loan interest rates
             Minority businesses
             Performance measures
             Program evaluation
             SBA 7(a) Loan Program
             Small business
             Small business assistance
             Small business loans
             Subsidies

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GAO-07-769



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Report to the Ranking Member, Subcommittee on Federal Financial 
Management, Government Information, Federal Services, and International 
Security, Committee on Homeland Security and Governmental Affairs, U.S. 
Senate: 

United States Government Accountability Office: 

GAO: 

July 2007: 

Small Business Administration: 

Additional Measures Needed to Assess 7(a) Loan Program's Performance: 

GAO-07-769: 

GAO Highlights: 

Highlights of GAO-07-769, a report to the Ranking Member, Subcommittee 
on Federal Financial Management, Government Information, Federal 
Services, and International Security, Committee on Homeland Security 
and Governmental Affairs, U.S. Senate 

Why GAO Did This Study: 

The Small Business Administrationï¿½s (SBA) 7(a) program, initially 
established in 1953, provides loan guarantees to small businesses that 
cannot obtain credit in the conventional lending market. In fiscal year 
2006, the program assisted more than 80,000 businesses with loan 
guarantees of nearly $14 billion. 

This report examines (1) the programï¿½s purpose, based on its 
legislative history, and performance measures; (2) evidence of 
constraints, if any, affecting small businessesï¿½ access to credit; (3) 
the types of small businesses served by 7(a) and conventional loans; 
and (4) differences in SBAï¿½s estimates and reestimates of the programï¿½s 
credit subsidy costs. GAO analyzed agency documents, studies on the 
small business lending market, and data on the characteristics of small 
business borrowers and loans. 

What GAO Found: 

As the 7(a) programï¿½s underlying statutes and legislative history 
suggest, the loan program is intended to help small businesses obtain 
credit. The program reflects this intent, in part, by guaranteeing a 
portion of each loan, alleviating some of the lenderï¿½s risk. However, 
determining the programï¿½s success is difficult, as the performance 
measures show only outputsï¿½the number of loans providedï¿½and not 
outcomes, or the fate of the businesses borrowing with the guarantee. 
The agency is currently undertaking efforts to develop additional, 
outcome-based performance measures for the 7(a) program, but is not 
certain when any outcome-based measures may be introduced or what they 
may capture. 

Limited evidence from economic studies suggests that some small 
businesses may face constraints in accessing credit in the conventional 
lending market, but this evidenceï¿½which dates from the early 1970s 
through the early 1990sï¿½does not account for recent developments that 
have occurred in the small business lending market. Several studies 
concluded, for example, that credit rationingï¿½that is, when lenders do 
not provide loans to all creditworthy borrowersï¿½was more likely to 
affect small businesses in part because these firms might not have 
sufficient information for lenders to assess their risk. However, the 
studies did not address recent significant changes to the small 
business lending market, such as the use of credit scoring, which may 
reduce the extent to which credit rationing occurs. 

GAO found that 7(a) loans went to certain segments of the small 
business lending market in higher proportions than conventional loans. 
A higher percentage of 7(a) loans went to minority-owned and start-up 
businesses compared with conventional loans from 2001 to 2004. More 
similar percentages of loans with and without SBA guarantees went to 
small businesses owned by women and those located in economically 
distressed neighborhoods. The characteristics of 7(a) and market loans 
differed in several key respects, however. For example, loans 
guaranteed by the 7(a) program were more likely to be larger and have 
variable interest rates, longer maturities, and higher interest rates. 

SBAï¿½s recent reestimates of the credit subsidy costs for 7(a) loans 
made during fiscal years 1992 through 2004 show that the long-term 
costs of these loans have generally been lower than the initial 
estimates. Since fiscal year 2005, initial estimates have shown a ï¿½zero 
credit subsidy.ï¿½ But the ultimate credit subsidy cost for any cohort of 
loans made will not be known until no loans are left outstanding. 
Reestimated costs may change because of uncertainties in forecasting 
and factors such as the number of loan defaults. Since 2002, the agency 
has employed an econometric model that incorporates historical data and 
other economic assumptions for its credit subsidy cost estimates and 
reestimates instead of relying primarily on predictions based on 
historical average loan performance. 

What GAO Recommends: 

GAO recommends that SBA take steps to ensure that the 7(a) programï¿½s 
performance measures provide information on program outcomes. 

In written comments, SBA agreed with the recommendation in this report 
but disagreed with one comparison in a section of the report on credit 
scores of small businesses with 7(a) and conventional loans. 

[Hyperlink, http://www.gao.gov/cgi-bin/getrpt?GAO-07-769]. 

To view the full product, including the scope and methodology, click on 
the link above.For more information, contact William B. Shear at (202) 
512-8678 or [email protected]. 

[end of section] 

Contents: 

Letter: 

Results in Brief: 

Background: 

Though Incorporating Policy Objectives from the 7(a) Program's 
Legislative History, 7(a)'s Performance Measures Do Not Gauge the 
Program's Impact on Participating Firms: 

Limited Evidence Suggests That Certain Market Imperfections May 
Restrict Access to Credit for Some Small Businesses: 

A Higher Percentage of 7(a) Loans Went to Certain Segments of the Small 
Business Lending Market, but Conventional Loans Were Widely Available: 

Current Reestimates Show Lower-than-Expected Subsidy Costs, but Final 
Costs May be Higher or Lower for Several Reasons: 

Conclusions: 

Recommendation for Executive Action: 

Agency Comments and Our Evaluation: 

Appendix I: Objectives, Scope and Methodology: 

Analysis of Statutory Framework of 7(a) Program and Its Performance 
Measures: 

Economic Literature on Credit Rationing and Discrimination: 

Comparison between 7(a) and Conventional Loans: 

Description of Credit Subsidy Cost Estimates and Reestimates: 

Analysis of 504 Loan Program: 

Appendix II: Summary of Economic Literature on the Empirical Evidence 
for Credit Rationing and Discrimination in the Conventional Lending 
Market: 

Appendix III: Descriptive Statistics of 504 Loan Program: 

Appendix IV: Comments from the Small Business Administration: 

Appendix V: GAO Contact and Staff Acknowledgments: 

Tables: 

Table 1: Attributes of Successful Performance Measures: 

Table 2: 7(a) Performance Measure Targets and Results, 2004-2006: 

Figures: 

Figure 1: Loan Volume for 7(a) and Conventional Small Business Loans, 
2005: 

Figure 2: Percentage of 7(a) and Conventional Loans by Minority Status 
of Ownership, 2001-2004: 

Figure 3: Percentage of 7(a) and Conventional Loans by Status as a New 
Business, 2001-2004: 

Figure 4: Percentage of 7(a) and Conventional Loans by Gender of 
Ownership, 2001-2004: 

Figure 5: Percentage of 7(a) and Conventional Loans by Census 
Divisions, 2001-2004: 

Figure 6: Percentage of Small Business Credit Scores (2003-2006) for 
Firms That Received 7(a) and Conventional Credit in D&B/FIC Sample 
(1996-2000), by Credit Score Range: 

Figure 7: Percentage of 7(a) Loans and Conventional Loans by Loan Size, 
2001-2004: 

Figure 8: Percentage of 7(a) and Conventional Loans by Loan Maturity 
Category, 2001-2004: 

Figure 9: Interest Rates Comparison for Loans under $1 Million and 
Prime Rate, 2001-2004: 

Figure 10: Original and Current Reestimated Credit Subsidy Rates for 
Loans Made from 1992 through 2006: 

Figure 11: Percentage of 504 Loans by Minority Status of Ownership, 
2001-2004: 

Figure 12: Percentage of 504 Loans by Status as a New Business, 2001- 
2004: 

Figure 13: Percentage of 504 Loans by Gender of Ownership, 2001-2004: 

Figure 14: Percentage of Small Business Credit Scores for Firms That 
Received 504 Loans by Credit Score Range, 2003-2006: 

Figure 15: Percentage of 504 Loans by Loan Size, 2001-2004: 

Figure 16: Percentage of 504 Loans in Distressed Neighborhoods, 2001- 
2004: 

Figure 17: Percentage of 504 Loans by Number of Employees in the Firm, 
2001-2004: 

Figure 18: Percentage of 504 Loans by Census Divisions, 2001-2004: 

Figure 19: Percentage of 504 Loans by Business Organization Type, 2001- 
2004: 

Abbreviations: 

D&B: Dun & Bradstreet Corporation: 

EZ/EC: Empowerment Zone and Enterprise Community: 

FCRA: Federal Credit Reform Act of 1990: 

FDIC: Federal Deposit Insurance Corporation: 

FIC: Fair Isaac Corporation: 

FSS: Financial Stress Score: 

GPRA: Government Performance and Results Act of 1993: 

PAR: Performance and Accountability Report: 

RC: Renewal Community: 

SBA: Small Business Administration: 

SBPS: Small Business Predictive Score: 

SSBF: Survey of Small Business Finances: 

[End of section] 

United States Government Accountability Office: 
Washington, DC 20548: 

July 13, 2007: 

The Honorable Tom Coburn, M.D. 
Ranking Member: 
Subcommittee on Federal Financial Management, Government Information, 
Federal Services, and International Security: 
Committee on Homeland Security and Governmental Affairs: 
United States Senate: 

Dear Dr. Coburn, 

Small businesses represent more than 99 percent of American firms and 
employ half of all private sector employees. The Small Business 
Administration (SBA) was created in 1953 to assist and protect the 
interests of small businesses in order to preserve free competition, in 
part by addressing constraints in the supply of credit for these firms. 
SBA's 7(a) Loan Program--the agency's largest loan program for small 
businesses--is intended to help small businesses obtain credit that 
they would be unable to obtain in the conventional lending market. For 
example, small businesses may be unable to obtain credit from 
conventional lenders because these firms may lack the financial and 
other information that larger, more established firms can provide. By 
providing a loan guarantee that covers a portion of a lender's losses 
if a small business is no longer able to meet its loan obligations, the 
7(a) program decreases the risk to the lender and may make more credit 
available to small businesses. In fiscal year 2006, the 7(a) program 
assisted slightly more than 80,000 businesses by guaranteeing loans 
valued at nearly $14 billion. 

Loan guarantee programs can result in subsidy costs to the federal 
government, and the Federal Credit Reform Act of 1990 (FCRA) requires, 
among other things, that agencies estimate the cost of these programs-
-that is, the cost of the loan guarantee to the federal government. 
FCRA also recognizes the difficulty of estimating credit subsidy costs 
and acknowledges that the eventual cost of the program may deviate from 
initial estimates. SBA makes its best initial estimate of the 7(a) 
program's credit subsidy costs and revises (reestimates) the estimate 
annually as new information becomes available. In fiscal years 2005 and 
2006, SBA estimated that the credit subsidy cost of the 7(a) program 
would be equal to zero--that is, the program would not require annual 
appropriations of budget authority for new loan guarantees. To offset 
some of the costs of the program, such as default costs, SBA assesses 
lenders two fees on each 7(a) loan. The guarantee fee must be paid by 
the lender at the time of loan application or within 90 days of the 
loan being approved, and is based on the guaranteed portion of the loan 
amount approved and can be passed on to the borrower.[Footnote 1] The 
ongoing servicing fee must be paid annually by the lender and is based 
on the outstanding balance of the guaranteed portion of the 
loan.[Footnote 2] In making its 2005 and later estimates, SBA adjusted 
the ongoing servicing fee so that the initial credit subsidy estimates 
would be zero based on expected loan performance.[Footnote 3] Although 
the 7(a) loan guarantee program is intended to be a "zero credit 
subsidy" program, FCRA provides that higher reestimates of subsidy 
costs, when they occur, are funded separately.[Footnote 4] According to 
FCRA, permanent indefinite budget authority is available to cover any 
higher reestimates of subsidy costs for the 7(a) loan program.[Footnote 
5] Thus, any reestimates exceeding the initial estimates would 
represent a cost to the federal government. 

We have noted elsewhere the challenges that Congress faces in 
reexamining the appropriate role and size of many federal programs that 
entail costs to the federal government.[Footnote 6] At your April 2006 
hearing on the effectiveness of SBA, you asked what types of businesses 
were assisted by SBA and whether the agency's activities have 
measurable results for small businesses.[Footnote 7] In light of the 
challenges facing Congress, as well as your concerns about the goals 
and impact of SBA's 7(a) loan program, you asked us to look into 
several aspects of the 7(a) loan program. Specifically, this report 
discusses (1) the 7(a) program's purpose, based on its underlying 
statutes and legislative history, and the performance measures SBA uses 
to assess the program's results; (2) evidence of market constraints, if 
any, that may affect small businesses' access to credit in the 
conventional lending market; (3) the segments of the small business 
lending market that are served by 7(a) loans and the segments that are 
served by conventional loans; and (4) differences in SBA's estimates 
and reestimates of the 7(a) program's credit subsidy costs and the 
factors that may cause uncertainty about the costs of the 7(a) program 
to the federal government. As agreed with your office, we have also 
included in appendix III information on the characteristics of loans 
financed under SBA's 504 program, which provides long-term, fixed-rate 
financing for major fixed assets, such as land and buildings.[Footnote 
8] 

To describe the purpose of the 7(a) program, we reviewed the program's 
underlying statutes and legislative history to understand how the 
program was intended to help small businesses. To assess SBA's 
performance measures for the 7(a) program, we examined performance and 
accountability reports and other related documents that describe the 
measures SBA uses to assess the performance of the 7(a) program and 
compared those performance measures to established GAO criteria for 
successful performance measures. We also interviewed SBA officials on 
the agency's efforts to improve its performance measures. To identify 
any evidence of constraints that could affect small businesses' access 
to credit, we summarized peer-reviewed studies on market imperfections 
in the lending market. To determine which segments of the small 
business lending market the 7(a) and conventional loans serve, we 
compared characteristics and loan terms of 7(a) borrowers to those of 
small business borrowers. We primarily relied on SBA data from 2001 
through 2004 and on the Federal Reserve's 2003 Survey of Small Business 
Finances (SSBF).[Footnote 9] In describing 7(a)'s credit subsidy costs, 
we compared SBA's original credit subsidy cost estimates for fiscal 
years 1992 through 2006 to SBA's most recent reestimates (as reported 
in the fiscal year 2008 Federal Credit Supplement) and interviewed SBA 
officials about the differences.[Footnote 10] We also reviewed SBA 
documents related to the 7(a) credit subsidy cost model. We conducted 
our work in Washington, D.C., and Chicago from May 2006 through July 
2007 in accordance with generally accepted government auditing 
standards. Appendix I discusses our scope and methodology in further 
detail. 

Results in Brief: 

The 7(a) program's design and performance measures in part reflect the 
program's legislative history, but the performance measures provide 
limited information about the impact of the loans on the small 
businesses receiving them. The underlying statutes and legislative 
history of the 7(a) program help establish the federal government's 
role in assisting and protecting the interests of small businesses, 
especially those with minority ownership. The program's performance 
measures focus on loan guarantees that are provided to small business 
owners identified in the program's authorizing statutes and legislative 
history. These firms include start-ups, existing small businesses, and 
businesses whose owners face "special competitive opportunity gaps," 
such as minority-or female-owned businesses. However, all of the 7(a) 
program's performance indicators are primarily output measures--for 
instance, they report on the number of loans approved and funded. As a 
result, no information is available on how well firms do after 
receiving a 7(a) loan (outcomes). The current measures do not indicate 
how well the agency is meeting its strategic goal of helping small 
businesses within these groups succeed. The agency is currently 
undertaking efforts to develop additional outcome-based performance 
measures for the 7(a) program, but agency officials said that it was 
not clear when any outcome-based measures might be introduced or what 
they might measure. 

Limited evidence from economic studies suggests that some small 
businesses may face constraints in accessing credit because of 
imperfections, such as credit rationing, in the conventional lending 
market. Some studies showed, for example, that lenders might lack the 
information needed to distinguish between creditworthy and 
noncreditworthy borrowers and thus could "ration" credit by not 
providing loans to all creditworthy borrowers. Several studies we 
reviewed generally concluded that credit rationing was more likely to 
affect small businesses because lenders could face challenges in 
obtaining enough information on these businesses to assess their risk. 
The literature we reviewed on credit rationing relied on data from the 
early 1970s through the early 1990s, however, and did not account for 
recent trends in the small business lending market. Among these trends 
is the increased use of credit scoring, which provides lenders with 
additional information on borrowers and may have had a significant 
impact on the extent of credit rationing in the current conventional 
lending market. In addition to credit rationing, some lenders may deny 
credit to firms owned by specific segments of society. Though studies 
we reviewed noted some disparities among races and genders in the 
conventional lending market, the studies did not offer conclusive 
evidence on the reasons for those differences. 

7(a) loans went to certain segments of the small business lending 
market in higher proportions than conventional loans. For example, 28 
percent of 7(a) loans compared with an estimated 9 percent of 
conventional loans went to minority-owned small businesses from 2001 
through 2004. In addition, 25 percent of 7(a) loans went to small 
business start-ups, while the overall lending market served almost 
exclusively established firms (about 95 percent). A more similar 
percentage of 7(a) and conventional loans went to other segments of the 
small business lending market, such as businesses owned by women or 
located in distressed neighborhoods. Finally, the characteristics of 
7(a) and conventional loans differed in several ways. For example, 7(a) 
loans typically were larger and more likely to have variable rates, 
longer maturities, and higher interest rates than conventional loans to 
small businesses. 

SBA's most recent reestimates of the credit subsidy costs for 7(a) 
loans made during fiscal years 1992 through 2004 indicate that, in 
general, the long-term costs of these loans would be lower than 
initially estimated. The 7(a) program has been estimated to be a "zero 
credit subsidy" program since fiscal year 2005. The most recent 
reestimates, including those made since 2005, may change because of the 
inherent uncertainties of forecasting subsidy costs and the influence 
of economic conditions, such as interest rates on several factors, 
including loan defaults (which exert the most influence over projected 
costs) and prepayment rates. Unemployment is another factor related to 
the condition of the national economy that could affect the credit 
subsidy cost--for instance, if unemployment rises above projected 
levels, loan defaults are likely to increase. Beginning in 2003, the 
agency has moved from primarily using historical averages of loan 
performance data to an econometric model that incorporates historical 
data and other economic assumptions to project credit subsidy costs. 

This report makes a recommendation to the SBA Administrator to complete 
and expand SBA's current work on evaluating the program's performance 
measures. In addition, we recommend that SBA use the loan performance 
information it already collects, including but not limited to defaults, 
prepayment rates, and the number of loans in good standing, to better 
report how small businesses fare after they participate in the 7(a) 
program. 

We provided a draft of this report to SBA for review and comment. In 
written comments, SBA agreed with our recommendation (see app. IV). 
However, SBA disagreed with a comparison in the section of our report 
discussing credit scores of borrowers with 7(a) and conventional loans. 
Specifically, we reported limited differences in the credit scores of 
small businesses with 7(a) and conventional loans. Although stating in 
its letter that "the numbers have not been worked out," SBA concluded 
that the impact on loan defaults from the higher share of 7(a) loans in 
the riskier credit score categories would not be insignificant. Our 
analyses of credit scores and other borrower and loan characteristics 
was not intended to quantify the impact of differences in these 
characteristics on 7(a) defaults. We continue to believe that our 
analysis of credit scores provides a reasonable basis for comparing the 
scores of business in different credit score categories. Further 
analyses of these types are consistent with our recommendation that SBA 
expand its abilities to assess the overall effectiveness of the 7(a) 
program. In addition, SBA provided technical comments, which we 
incorporated into the report as appropriate. 

Background: 

Initially established in 1953, the 7(a) program guarantees loans made 
by commercial lenders--mostly banks--to small businesses for working 
capital and other general business purposes.[Footnote 11] The guarantee 
assures the lender that if a borrower defaults on a loan, the lender 
will receive an agreed-upon portion (generally between 50 percent and 
85 percent) of the outstanding balance. Because the guarantee covers a 
portion of the outstanding amount, both the lender and SBA share some 
of the risk associated with a potential default. SBA is not liable for 
the guarantee should the lender not comply materially with the 
program's regulations--for instance, by not paying the guarantee fee to 
SBA in a timely manner. As figure 1 shows, SBA's share of loans 
guaranteed by the 7(a) program was an estimated 4.1 percent of all 
outstanding small business loan dollars for loans under $1 million 
($24.7 billion out of $600.8 billion). This share accounts for about 
1.3 percent of the number of outstanding small business loans of under 
$1 million in 2005 (about 264,000 out of 21 million loans).[Footnote 
12] SBA's shares of outstanding small business loans under $1 million 
for the years 2003 and 2004 were similar.[Footnote 13] 

Figure 1: Loan Volume for 7(a) and Conventional Small Business Loans, 
2005: 

[See PDF for image] 

Source: GAO analysis of SBA outstanding 7(a) loan data and Office of 
Advocacy special tabulations of call reports (Consolidated Reports of 
Condition and Income for U.S. Banks). 

[End of figure] 

SBA relies on lenders to process and service 7(a) loans and to ensure 
that borrowers meet the program's eligibility requirements.[Footnote 
14] To be eligible for the 7(a) loan program, a business must be an 
operating for-profit small firm (according to SBA's size standards) 
located in the United States. To determine whether a business qualifies 
as small for the purposes of the 7(a) program, SBA uses size standards 
that it has established by industry.[Footnote 15] These standards set 
the maximum average number of employees or annual receipts that a small 
business may have. While SBA gives special consideration to certain 
groups of business owners, the program does not set aside loans for or 
require that a certain number of loans be made to targeted groups. 
Nevertheless, SBA has performance measures that track how many loans go 
to new small businesses and that include information on various types 
of businesses, such as minority-, women-, and veteran-owned firms. 

In addition to making sure that borrowers meet the size requirements, 
lenders must certify that small businesses meet the "credit elsewhere" 
requirement. SBA does not extend credit to businesses if the financial 
strength of the individual owners or the firm itself is sufficient to 
provide or obtain all or part of the financing or if the business can 
access conventional credit. To certify borrowers as having met the 
credit elsewhere requirement, lenders must first determine that the 
firm's owners are unable to provide the desired funds from their 
personal resources. Second, the credit elsewhere test requires that 
lenders determine that the desired credit, for similar purposes and 
period of time, is unavailable to the firm on reasonable terms and 
conditions from nonfederal sources without SBA assistance, taking into 
consideration prevailing rates and terms in the community or locale 
where the firm conducts business. Nonfederal sources may include any 
lending institutions or a borrower's personal resources. 

According to SBA's fiscal year 2003-2008 Strategic Plan, the agency's 
mission is to maintain and strengthen the nation's economy by enabling 
the establishment and viability of small businesses and by assisting in 
the economic recovery of communities after disasters. SBA describes the 
7(a) program as contributing to an agencywide goal to "increase small 
business success by bridging competitive opportunity gaps facing 
entrepreneurs." As reported annually in SBA's Performance and 
Accountability Reports (PAR), the 7(a) program contributes to this 
strategic goal by fulfilling each of the following three long-term, 
agencywide objectives: (1) increasing the positive impact of SBA 
assistance on the number and success of small business start-ups, (2) 
maximizing the sustainability and growth of existing small businesses 
that receive SBA assistance, and (3) significantly increasing 
successful small business ownership within segments of society facing 
special competitive opportunity gaps. Groups facing these special 
competitive opportunity gaps include those that SBA considers to own 
and control little productive capital and to have limited opportunities 
for small business ownership (such as African Americans, American 
Indians, Alaska Natives, Hispanics, Asians, and women) and those that 
are in certain rural or low-income areas. The 7(a) program has nine 
performance measures. For each of its three long-term objectives, SBA 
collects and reports on (1) the number of loans approved, (2) the 
number of loans funded (i.e., money that was disbursed), and (3) the 
number of firms assisted. 

To report on its performance measures, SBA collects data from lenders. 
Loan-level data for the 7(a) program are housed in the Loan Accounting 
System. This system contains data describing the loan, such as the 
percentage of the loan guaranteed by SBA, the number of months to 
maturity, and the interest rate (fixed or variable). The data also 
include information on the small firm, such as the ethnicity and gender 
of the principal owner, the number of employees, and the firm's status 
as "new" (i.e., less than 2 years old). Furthermore, the system 
contains data on the loan's status--for example, whether the loan has 
been purchased by SBA (i.e., is in default), has been prepaid, or is in 
good standing. 

According to provisions in FCRA, at the time a guaranteed loan is made, 
the credit subsidy cost is financed with the program's annual 
appropriations. Also under FCRA, SBA makes annual revisions 
(reestimates) of credit subsidy costs for each cohort of loans made 
during a given fiscal year using new information about loan 
performance, revised expectations for future economic conditions and 
loan performance, and improvements in cash flow projection methods. 
These reestimates represent additional costs or savings to the 
government and are recorded in the budget. FCRA provides permanent 
indefinite budget authority for any reestimated increases of credit 
subsidy costs (upward reestimates) that occur after the year in which a 
loan is disbursed. Reestimated reductions of subsidy costs (downward 
reestimates) are credited to the Treasury and are unavailable to the 
agency. In addition, FCRA does not count administrative expenses 
against the appropriation for credit subsidy costs. Instead, 
administrative expenses are subject to separate appropriations and are 
recorded each year as they are paid, rather than as loans are 
originated. 

Though Incorporating Policy Objectives from the 7(a) Program's 
Legislative History, 7(a)'s Performance Measures Do Not Gauge the 
Program's Impact on Participating Firms: 

The performance measures for the 7(a) program incorporate the various 
policy objectives described in the program's underlying statutes and 
legislative history but do not assess the impact of the loan guarantees 
on small businesses receiving loans. We compared criteria for the 
characteristics of effective performance measures and found that the 
7(a) performance measures incorporated several of these attributes. For 
example, the performance measures track the main activity of the 7(a) 
program by identifying the number of loans that are approved for small 
firms that have been unable to obtain credit in the conventional 
lending market. However, the performance measures do not show whether 
the program is meeting the agency's goal of improving the success of 
small firms that participate in the program. None of the 7(a) 
performance measures provide information on how well firms do after 
they have received a loan. SBA has been undertaking efforts to develop 
additional performance measures to describe the program's impact on 
participating firms. But the agency has yet to define specific outcome- 
based performance measures and does not have a time line for 
implementing such measures. 

The 7(a) Program's Legislative History Emphasizes the Program's Role in 
Meeting Credit Needs of Certain Small Businesses: 

The 7(a) program's underlying statutes and legislative history have 
helped establish the federal government's role in assisting and 
protecting the interests of small business, taking into account the 
importance of these businesses to the overall functioning of the 
national economy. The legislative basis for the 7(a) program recognizes 
that the conventional lending market is the principal source of 
financing for small businesses and that the loan assistance that SBA 
provides is intended to supplement rather than compete with that 
market. However, as the legislative history suggests, conventional 
lending may not be a feasible financing option for some small 
businesses under certain circumstances. For example, conventional 
lenders may be unwilling to make loans when the risk of a small 
business is difficult to assess--for instance, when they believe that 
the small business has insufficient assets or specialized inventory and 
equipment or lacks a credit history, as in the case of a start-up. In 
addition, the loan terms offered to a small business in the 
conventional lending market may not be practical--for example, a small 
business may need loans with longer-term maturities than conventional 
lenders may be willing to provide. 

The design of the 7(a) program is consistent with the program's 
underlying statutes and legislative history in that SBA collaborates 
with the conventional market in identifying and supplying credit to 
small businesses in need of assistance. Specifically, the 7(a) program 
has three design features that help it address concerns identified in 
its legislative history. First, the loan guarantee, which plays the 
same role as collateral, limits the lender's risk in extending credit 
to a small firm that may not have met the lender's own requirements for 
a conventional loan. According to SBA officials, a lender's willingness 
to underwrite the loan only with the guarantee confirms that the 7(a) 
program fills a credit gap. Second, the "credit elsewhere" requirement 
is intended to provide some assurance that guaranteed loans are offered 
only to firms that are unable to access credit on reasonable terms and 
conditions in the conventional lending market. Lenders follow SBA 
policies and procedures in determining whether a small business 
fulfills this key 7(a) program requirement. SBA officials explained 
that the agency is currently reviewing how lenders apply the credit 
elsewhere requirement, though the results of this review are not yet 
complete. Third, an active secondary market for the guaranteed portion 
of a 7(a) loan allows lenders to sell the guaranteed portion of the 
loan to investors, providing additional liquidity that lenders can use 
for additional loans. 

Numerous amendments to the Small Business Act and to the 7(a) program 
have laid the groundwork for broadening small business ownership among 
certain groups, including veterans, handicapped individuals, women, 
African Americans, Hispanics, Native Americans, and Asians. The 7(a) 
program also includes provisions for extending financial assistance to 
small businesses that are located in urban or rural areas with high 
proportions of unemployed or low-income individuals or that are owned 
by low-income individuals. The program's legislative history highlights 
its role in helping small businesses, among other things, get started, 
allowing existing firms to expand, and enabling small businesses to 
develop foreign markets for their products and services. 

The 7(a) Program's Performance Measures Are Related to the Program's 
Core Activity, but Do Not Provide Information on Its Impact on 
Participating Firms: 

We stated in earlier work that a clear relationship should exist 
between an agency's long-term strategic goals and its program's 
performance measures.[Footnote 16] Outcome-based goals or measures 
showing a program's impact on those it serves should be included in an 
agency's performance plan whenever possible. Most plans typically 
supplement outcome goals with output goals showing the number and type 
of services provided because the program may not meet an outcome goal 
in the year covered by the plan. In some cases, a goal may be too 
difficult to measure. In previous work, we have also identified 
specific attributes of successful performance measures.[Footnote 17] 
For example, each performance measure should have a measurable target 
and explicit methodology showing how that target was determined. 
Without a measurable target, an organization may be unable to determine 
whether it is meeting its goals. Table 1 provides a detailed 
description of these key attributes and discusses the potentially 
adverse consequences of not incorporating them into performance 
measures. 

Table 1: Attributes of Successful Performance Measures: 

Attribute: Core program activity; 
Definitions: Measure covers the activities that an entity is expected 
to perform in support of the program's intent; 
Potentially adverse consequences of not meeting attribute: Managers and 
stakeholders may not have enough information in core program areas. 

Attribute: Measurable target; 
Definitions: Measure has a numerical goal; 
Potentially adverse consequences of not meeting attribute: It may be 
impossible to determine whether a program's performance is meeting 
expectations. 

Attribute: Reliability; 
Definitions: Measure produces the same result under similar conditions; 
Potentially adverse consequences of not meeting attribute: Reported 
performance data are inconsistent and uncertainty exists about them. 

Attribute: Clarity; 
Definitions: Measure is clearly stated and the name and definition are 
consistent with the methodology used to calculate it; 
Potentially adverse consequences of not meeting attribute: Data could 
be misleading to users and not capture what is intended to be measured. 

Attribute: Objectivity; 
Definitions: Measure is reasonably free from significant bias or 
manipulation; 
Potentially adverse consequences of not meeting attribute: Performance 
assessments may be systematically over-or understated. 

Attribute: Linkage; 
Definitions: Measure is aligned with division and agencywide goals and 
mission; 
Potentially adverse consequences of not meeting attribute: Behaviors 
and incentives created by measures do not support achieving division or 
agencywide goals or mission. 

Source: GAO-03-143. 

[End of table] 

We reviewed SBA's performance measures for the 7(a) loan program and 
found that the measures generally exhibited all of the traits described 
above, except for the measurable target and linkage attribute. 
According to SBA's fiscal year 2006 PAR, the nine performance measures 
were: 

1. number of new loans approved to start-up small businesses, 

2. number of new loans funded to start-up small businesses, 

3. number of start-up small businesses assisted, 

4. number of new loans approved to existing small businesses, 

5. number of new loans funded to existing small businesses, 

6. number of existing small businesses assisted, 

7. number of new loans approved to small businesses facing special 
competitive opportunity gaps, 

8. number of new loans funded to small businesses facing special 
competitive opportunity gaps, and: 

9. number of small businesses facing special competitive opportunity 
gaps assisted. 

All nine performance measures we reviewed provided information that 
related to the 7(a) loan program's core activity, which is to provide 
loan guarantees to small businesses. In particular, the indicators all 
provided the number of loans approved, loans funded, and firms assisted 
by subgroups of small businesses the 7(a) program is intended to 
assist. As stated earlier, the program's legislative history indicates 
that SBA's specific lending objectives include stimulating small 
business in distressed areas, promoting small businesses' contribution 
to economic growth, and promoting minority enterprise opportunity. 
Consequently, SBA has developed performance measures that specifically 
track how many guaranteed loans go to those small business owners that 
the agency refers to collectively as facing special competitive 
opportunity gaps. Similarly, SBA separately tracks loan data regarding 
start-up small businesses, another group that the 7(a) program's 
legislative history specifically cites as having challenges in 
obtaining credit within the conventional lending market. 

As table 2 shows, in 2004 and 2005 SBA generally met or exceeded its 
goals for the number of loans approved for start-ups, existing small 
businesses, and businesses facing special competitive opportunity gaps. 
In 2006, SBA did not meet any of its targets for these measures. 
However, while the 7(a) program did not meet its targets, it approved 
slightly more than 90 percent of the loans that it had set as its goal. 
SBA also did not always meet its target for the number of firms 
assisted. In years when SBA did not meet these targets, the 7(a) 
program again met almost 90 percent of its goal for firms assisted. 
Though it is not clear why SBA did not meet these targets, SBA's fiscal 
year 2006 PAR suggests that there may have been less demand for 7(a) 
loans. In addition, SBA officials explained that the agency did not 
make loans to small businesses directly and therefore had less control 
over the number of loans made. Instead, the agency relies primarily on 
marketing and community outreach to inform both lenders and prospective 
borrowers about the 7(a) program. Furthermore, SBA officials explained 
that the 7(a) program staff leverages other SBA offices, such as those 
that offer technical assistance to small businesses, to further raise 
the awareness among the general public and potential lenders about the 
7(a) program. 

Table 2: 7(a) Performance Measure Targets and Results, 2004-2006: 

Performance measures: Number of loans approved: Start-up small 
business; 
Fiscal year: 2004: Target: 18,000; 
Fiscal year: 2004: Result: 18,134; 
Fiscal year: 2005: Target: 22,671; 
Fiscal year: 2005: Result: 29,587; 
Fiscal year: 2006: Target: 33,024; 
Fiscal year: 2006: Result: 32,983. 

Performance measures: Number of loans approved: Existing small 
business; 
Fiscal year: 2004: Target: 72,000; 
Fiscal year: 2004: Result: 62,999; 
Fiscal year: 2005: Target: 65,305; 
Fiscal year: 2005: Result: 66,313; 
Fiscal year: 2006: Target: 73,536; 
Fiscal year: 2006: Result: 64,307. 

Performance measures: Number of loans approved: Small business facing 
special competitive opportunity gap; 
Fiscal year: 2004: Target: 44,617; 
Fiscal year: 2004: Result: 60,787; 
Fiscal year: 2005: Target: 68,621; 
Fiscal year: 2005: Result: 74,307; 
Fiscal year: 2006: Target: 76,690; 
Fiscal year: 2006: Result: 71,326. 

Performance measures: Number of firms assisted: Start-up small 
business; 
Fiscal year: 2004: Target: 18,000; 
Fiscal year: 2004: Result: 15,351; 
Fiscal year: 2005: Target: 22,671; 
Fiscal year: 2005: Result: 25,086; 
Fiscal year: 2006: Target: 28,224; 
Fiscal year: 2006: Result: 27,368. 

Performance measures: Number of firms assisted: Existing small 
business; 
Fiscal year: 2004: Target: 72,000; 
Fiscal year: 2004: Result: 53,544; 
Fiscal year: 2005: Target: 65,305; 
Fiscal year: 2005: Result: 57,296; 
Fiscal year: 2006: Target: 62,144; 
Fiscal year: 2006: Result: 52,935. 

Performance measures: Number of firms assisted: Small business facing 
special competitive opportunity gap; 
Fiscal year: 2004: Target: 44,617; 
Fiscal year: 2004: Result: 52,075; 
Fiscal year: 2005: Target: 68,621; 
Fiscal year: 2005: Result: 64,390; 
Fiscal year: 2006: Target: 64,377; 
Fiscal year: 2006: Result: 60,691. 

Source: GAO analysis of SBA's fiscal years 2006 and 2007 Budget Request 
and Performance Plan and fiscal year 2006 PAR. 

[End of table] 

By having quantifiable goals, all of the performance measures partly 
met our criterion for having a measurable target attribute. SBA 
annually reports performance measure data, publishing goals in the 
agency's annual Budget Request and Performance Plan for the upcoming 
fiscal year and results for the preceding fiscal year in its PAR. 

Though having measurable targets is a positive attribute, the PAR does 
not contain information about how SBA set its goals. According to SBA 
officials, the actual targets set for all of the measures related to 
the 7(a) program are based on historical data. SBA officials explained 
that the number of loans approved is calculated by dividing the amount 
appropriated for loan guarantees in a given fiscal year by the previous 
fiscal year's average loan amount, producing a target for the number of 
loans approved. SBA also measures the number of loans funded and firms 
assisted, both of which closely track the number of loans approved. 
According to SBA officials, both of these measures are always slightly 
lower than the number of loans approved because not all approved loans 
are funded and the number of firms assisted does not include multiple 
loans to the same firm in a given fiscal year. 

In addition, the 7(a) program's performance measures are generally 
reliable, clearly defined, and objective. Our assessment of SBA's 
databases that contain information on the agency's performance measures 
concluded that these data were sufficiently reliable for the purposes 
of evaluating key loan characteristics. Additionally, most of the 
measures are clearly described in the SBA documents that addressed the 
7(a) program's performance measures, since each performance measure's 
name is also its definition. Finally, the performance measures are 
objective and generally free from any biases, in part because they 
simply report the overall annual volume (i.e., outputs) of guaranteed 
lending business. 

Since all of the 7(a) program's performance measures are primarily 
output measures--that is, they report on the number of loans approved 
and funded and firms assisted--SBA does not collect any information 
that discusses how well firms are doing after receiving a 7(a) loan 
(outcomes). Further, none of the measures link directly to SBA's long- 
term objectives. As a result, the performance measures do not fully 
support SBA's strategic goal to "increase small business success by 
bridging competitive opportunity gaps facing entrepreneurs." We noted 
in 1999 that SBA relies on output measures, such as an increase in the 
number of loans, but does not show how these measures are related to 
increasing opportunities for small businesses to be successful--SBA's 
main goal.[Footnote 18] SBA's Inspector General also concluded in a 
2000 report that most 7(a) performance measures were output based and 
did not provide information showing the extent to which the program was 
accomplishing its mission under the Small Business Act.[Footnote 19] 
SBA management concurred with the Inspector General's conclusion and 
recommendations, including that the agency develop performance measures 
to gauge outcomes and goals for meeting the requirements set forth in 
the Government Performance and Results Act of 1993 (GPRA). 

SBA is Working to Gauge the 7(a) Program's Impact on Participating 
Firms: 

SBA officials have recognized the importance of developing performance 
measures that better assess the 7(a) program's impact on the small 
firms that receive the guaranteed loans. SBA is expecting a final 
report in the summer of 2007 from the Urban Institute, which has been 
contracted to undertake several evaluative studies of several programs, 
including 7(a), that provide financial assistance to small businesses. 
Components of this work include assessing potential duplication of 
SBA's main financial assistance programs by state or local programs, 
establishing a baseline measure of SBA customer satisfaction, and 
interviewing participating lenders about their underwriting practices. 
One component of the study that will not be undertaken is an analysis 
to determine how outcomes for firms assisted through financial 
assistance programs, such as 7(a), would differ in the absence of SBA 
assistance. The impact study, as designed by the Urban Institute, 
required the use of credit scores for firms that did not receive SBA 
assistance.[Footnote 20] Though costs associated with this component of 
the study initially prohibited SBA from undertaking it, SBA officials 
explained that they were advised that they are legally prohibited from 
obtaining credit score data from firms with which they have no 
relationship. 

SBA officials explained that no formal decision had yet been made about 
how the agency might alter or enhance the current set of performance 
measures to provide more outcome-based information related to the 7(a) 
program, for several reasons. These included the agency's reevaluation 
of its current strategic plan in response to GPRA's requirement that 
agencies reassess their strategic plans every 3 years, a relatively new 
administrator who may make changes to the agency's performance measures 
and goals, and the cost and legal constraints associated with the Urban 
Institute study.[Footnote 21] However, SBA already collects information 
showing how firms are faring after they obtain a guaranteed loan. In 
particular, SBA regularly collects information on how well 
participating firms are meeting their loan obligations. This 
information generally includes, among other things, the number of firms 
that have defaulted on or prepaid their loans--data that can serve as 
reasonable proxies for determining a firm's financial status. Though 
this information provides some indication of how successful firms are 
after receiving a 7(a) guaranteed loan, the agency primarily uses the 
data only to estimate some of the costs associated with the program and 
for internal reporting purposes, such as monitoring participating 
lenders and analyzing its current loan portfolio. Expanding uses of 
this information as part of its performance measures could provide SBA 
and others helpful information for describing the financial status of 
firms that have been assisted by the 7(a) program. 

Limited Evidence Suggests That Certain Market Imperfections May 
Restrict Access to Credit for Some Small Businesses: 

Limited evidence from economic studies suggests that some small 
businesses may face constraints in accessing credit because of 
imperfections, such as credit rationing, in the conventional lending 
market. But this evidence is based on data that end with the early 
1990s and do not account for developments that have occurred in the 
small business lending market since then. We focused on evidence of 
credit rationing reported in academic studies published in peer- 
reviewed journals.[Footnote 22] With some exceptions, the studies we 
reviewed generally concluded that credit rationing was more likely to 
exist when there was a lack of information about the borrower--for 
example, with small businesses--and that the effect of this type of 
credit constraint on the national economy was not likely to be 
significant. However, the research on credit rationing was limited by 
at least two factors. First, researchers do not all use a similar 
definition for credit rationing. Second, as we have noted the studies 
we reviewed did not consider recent developments in the small business 
lending market, such as the increasing use of credit scores, that may 
reduce credit rationing. Finally, though researchers have noted 
disparities in lending options among different races and genders, 
inconclusive evidence exists as to whether discrimination explains 
these differences. 

Studies We Reviewed Provide Limited Evidence of Credit Rationing: 

We found limited information that credit constraints, such as credit 
rationing, could have some effect on small businesses. Credit 
rationing, or denying loans to creditworthy individuals and firms, 
generally stems from lenders' uncertainty or lack of information 
regarding a borrower's ability to repay debt. Economic reasoning 
suggests that there exists an interest rate (i.e., the price of the 
loan) beyond which banks will not lend, even though there may be 
creditworthy borrowers willing to accept a higher interest 
rate.[Footnote 23] Because the market interest rate will not climb high 
enough to convince lenders to grant credit to these borrowers, these 
applicants will be unable to access credit and will also be left out of 
the lending market.[Footnote 24] Of the studies we identified that 
empirically looked for evidence of credit rationing within the 
conventional U.S. lending market, almost all provided some evidence 
consistent with credit rationing.[Footnote 25] For example, one study 
found evidence of credit rationing across all sizes of firms.[Footnote 
26] However, another study suggested that the effect of credit 
rationing on small firms was likely small, and another study suggested 
that the impact on the national economy was not likely to be 
significant.[Footnote 27] Specifically, one of these two studies, which 
used data on small businesses, concluded that though crediting 
rationing was associated with firm size, it was economically 
unimportant to the small businesses within their dataset.[Footnote 28] 
Only one study that we reviewed found no evidence of credit rationing, 
though it could not rule out the existence of this market 
imperfection.[Footnote 29] 

In some studies we reviewed, we also found that researchers used 
different definitions of credit rationing and that a broader definition 
was more likely to yield evidence of the existence of credit rationing 
than a narrower definition. For example, one study defined a firm as 
being credit rationed if the firm was either denied a loan or 
discouraged from applying for credit.[Footnote 30] However, another 
study pointed out that firms could be denied credit for reasons other 
than credit rationing, such as not being creditworthy.[Footnote 31] 
Because the underlying reason for having been denied credit can be 
difficult to determine, true credit rationing is difficult to measure. 

Other studies of small business lending that we reviewed found evidence 
for credit rationing by testing whether the circumstances of denial 
were consistent with a "credit rationing" explanation, such as a lack 
of information. For example, two studies concluded that having a 
preexisting relationship with the lender had a positive effect on the 
borrower's chance of obtaining a loan.[Footnote 32] The empirical 
evidence from another study suggested that lenders use information 
accumulated over the duration of a financial relationship with a 
borrower to define loan terms. This study's results suggested that 
firms with longer relationships received more favorable terms--for 
instance, they were less likely to have to provide collateral. Because 
having a relationship with a borrower would lead to the lender's having 
more information, the positive effect of a preexisting relationship is 
consistent with the theory behind credit rationing.[Footnote 33] 

Aside from credit rationing, lenders could potentially deny 
creditworthy firms a loan because of the race or gender of the owner. 
This practice would also constitute a market imperfection because 
lenders would be denying credit for reasons other than interest rate or 
another risk associated with the borrower. A 2003 survey of small 
businesses conducted by the Federal Reserve examined differences in 
credit use among racial groups and between genders. The survey found 
that differences did not exist across all comparison groups.[Footnote 
34] For example, the survey found that 48 percent of small businesses 
owned by African Americans and women and 52 percent of those owned by 
Asians had some form of credit, while 61 percent of white-owned or 
Hispanic-owned businesses had some form of credit.[Footnote 35] 

Studies have attempted to determine whether such disparities are due to 
discrimination, but the evidence from the studies we reviewed was 
inconclusive. For example, one study found evidence that discrimination 
existed against Hispanics and Asians, but not against African Americans 
and women.[Footnote 36] A different study that was able to control for 
the effects of a variety of variables, such as whether the borrower had 
experienced bankruptcy and the borrower's credit score, found some 
evidence of discrimination against African Americans and women, but not 
against other minorities.[Footnote 37] Finally, a third study found 
significant evidence that only firms owned by African Americans faced 
obstacles in obtaining credit and were charged higher interest rates, 
while the study did not find significant evidence that other minority- 
and women-owned firms face discrimination.[Footnote 38] 

The Literature Does Not Address Recent Trends in the Small Business 
Lending Market: 

The studies we reviewed regarding credit rationing used data from the 
early 1970s through the early 1990s and thus did not account for 
several recent trends that may have impacted the extent of credit 
rationing within the small business lending market. According to a 
Federal Reserve report on the availability of credit for small 
businesses, lenders are increasingly using credit scores in loan 
decisions involving small businesses. Credit scores provide additional 
information about borrowers and may reduce the cost to lenders of 
evaluating the risk potential borrowers present. As a result, credit 
scores may decrease the extent to which credit rationing occurs. 
Further, our economic literature review identified one study suggesting 
that the recent changes in bankruptcy laws may also impact the small 
business lending market because loans to small businesses are often 
secured by personal credit. Specifically, the change in bankruptcy laws 
that occurred in October 2005 may have made it more difficult for some 
individuals to declare bankruptcy and thus decreased the risk to 
lenders, making lenders more willing to extend credit. In addition, 
because it has become harder to declare bankruptcy, potential borrowers 
may be less likely to apply for a loan. These trends may also lead to 
less credit rationing in the conventional lending market. Finally, 
considerable consolidation has taken place in the banking industry and 
may have led to a decrease in the number of small banks. Historically, 
smaller banks have been more involved with small business lending 
because of the relationships between small local banks and local firms. 
As noted previously, relationships with lenders can limit credit 
rationing. With the potential decline in the number of small banks, 
these relationships may diminish, possibly leading to more credit 
rationing. 

A Higher Percentage of 7(a) Loans Went to Certain Segments of the Small 
Business Lending Market, but Conventional Loans Were Widely Available: 

7(a) loans went to certain segments of the small business lending 
market in higher proportions than conventional loans. From 2001 to 
2004, a higher percentage of 7(a) loans went to minority-owned and 
start-up businesses compared with conventional loans. However, more 
similar percentages of loans with and without SBA guarantees went to 
small businesses owned by women and those located in economically 
distressed neighborhoods. The characteristics of 7(a) and market loans 
differed in several key respects. For example, loans guaranteed by the 
7(a) program were more likely to be larger and have variable interest 
rates, longer maturities, and higher interest rates. 

Higher Proportion of 7(a) Loans Went to Minority-Owned and Start-Up 
Small Businesses: 

From 2001 to 2004, minority-owned small businesses received a larger 
share of 7(a) than conventional loans. More than a quarter of 7(a) 
loans went to small businesses with minority ownership, compared with 
an estimated 9 percent of conventional loans (fig. 2). However, in 
absolute numbers many more conventional loans went to the segments of 
the small business lending market we could measure, including minority- 
owned small businesses, than loans with 7(a) guarantees. For example, 
if we apply the percentage of 7(a) loans going to minority-owned firms 
(28 percent) from 2001 through 2004 to the number of outstanding 7(a) 
loans under $1 million in 2004 (223,939), an estimated 62,000 of these 
outstanding 7(a) loans went to minority-owned small firms. In 
comparison, if we apply the percentage of conventional loans going to 
minority-owned firms over the same period (9 percent) to the number of 
outstanding loans under $1 million in 2004 (17.13 million), we estimate 
that there were more than 1.6 million outstanding loans to minority- 
owned small businesses in June 2004. 

Figure 2: Percentage of 7(a) and Conventional Loans by Minority Status 
of Ownership, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA and Federal Reserve Board of Governors' 
data. 

Note: The brackets on the conventional loans represent confidence 
intervals. Because the data from the SSBF are from a probability survey 
based on random selections, this sample is only one of a large number 
of samples that might have been drawn. Since each sample could have 
provided different estimates, we express our confidence in the 
precision of the particular results as a 95 percent confidence 
interval. This is the interval that would contain the actual population 
value for 95 percent of the samples that could have been drawn. As a 
result, we are 95 percent confident that each of the confidence 
intervals in this report will include the true values in the study 
population. Data on SBA 7(a) loans do not have confidence intervals 
because we obtained data on all the loans SBA approved and disbursed 
from 2001 to 2004. 

[End of figure] 

Compared with conventional loans, a higher percentage of 7(a) loans 
went to small start-up firms from 2001 through 2004 (fig. 3).[Footnote 
39] Specifically, 25 percent of 7(a) loans went to small business start-
ups from 2001 through 2004. In contrast, an estimated 5 percent of 
conventional loans went to newer small businesses over the same period. 

Figure 3: Percentage of 7(a) and Conventional Loans by Status as a New 
Business, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA and Federal Reserve Board of Governors' 
data. 

Note: The brackets on the conventional loans represent a 95 percent 
confidence interval. 

[End of figure] 

More Similar Proportions of 7(a) and Conventional Loans Served Other 
Segments of the Small Business Lending Market: 

Compared with the differences in the shares of 7(a) and conventional 
loans going to minority-owned and start-up small businesses, only 
limited differences exist between the shares of 7(a) and conventional 
loans that went to other types of small businesses from 2001 through 
2004. For example, the share of 7(a) loans going to small women-owned 
firms was much closer to the estimated share of conventional loans 
going to these firms. Specifically, women-owned firms received 22 
percent of all 7(a) loans and an estimated 16 percent of conventional 
loans (fig. 4). Furthermore, the percentages of loans going to firms 
owned equally by men and women were also more similar--17 percent of 
7(a) loans and an estimated 14 percent of conventional loans (see fig. 
4). However, these percentages are small compared with those for small 
firms headed by men, which captured most of the small business lending 
market from 2001 to 2004. These small businesses received an estimated 
70 percent of conventional loans and 61 percent of 7(a) loans. 

Figure 4: Percentage of 7(a) and Conventional Loans by Gender of 
Ownership, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA and Federal Reserve Board of Governors' 
data. 

Note: The brackets on the conventional loans represent a 95 percent 
confidence interval. 

[End of figure] 

Similarly, compared with the differences in the shares of 7(a) and 
conventional loans going to minority-owned and start-up small 
businesses, relatively equal shares of 7(a) and conventional loans 
reached small businesses in economically distressed neighborhoods 
(i.e., zip code areas) from 2001 through 2004--14 percent of 7(a) loans 
and an estimated 10 percent of conventional loans.[Footnote 40] In 
order to apply a single measure uniformly across the country, we based 
our measure on the minimum poverty level eligibility requirement 
employed by two federal programs designed to assist distressed 
communities.[Footnote 41] Specifically, we defined distressed 
neighborhoods as zip code areas where at least 20 percent of the 
population had incomes below the national poverty line (see app. I for 
more information on our methodology). 

SBA does not specifically report whether a firm uses its 7(a) loan in 
an economically distressed neighborhood. Nevertheless, SBA does track 
loans that go to firms located in areas it considers "underserved" by 
the conventional lending market. SBA defines an "underserved" area as 
any one of these federally defined areas: Historically Underutilized 
Business Zone, Empowerment Zone/Enterprise Community, low-and moderate-
income census tract (median income of census tract is no greater than 
80 percent of the associated metropolitan area or nonmetropolitan 
median income), or rural as classified by the U.S. Census.[Footnote 42] 
Using this measure, SBA's analysis found that 49 percent of 7(a) loans 
approved and disbursed in fiscal year 2006 went to geographic areas 
that SBA considered "underserved" by the conventional lending market. 

Although a higher proportion of 7(a) loans went to smaller firms (that 
is, firms with up to 5 employees), we found that the differences in the 
shares of 7(a) and conventional loans were more similar for categories 
of larger firms that have 5 or more employees. Specifically, 57 percent 
of all 7(a) loans went to small businesses with up to 5 employees, 
compared with the estimated 42 percent of conventional loans that went 
to firms with a similar number of employees. In contrast, firms with 5 
to 9 employees received 21 percent of the 7(a) loans and 24 percent of 
conventional loans, and firms with 10 to 19 employees received 12 
percent of 7(a) loans and 17 percent of conventional loans. Firms with 
20 to 499 employees (the maximum number of employees a business can 
have and still be considered small by SBA's standards) also received 
more similar shares of 7(a) and conventional loans.[Footnote 43] 

More similar proportions of 7(a) and conventional loans also went to 
small businesses with different types of organizational structures and 
in different geographic locations. For instance, between 2001 and 2004 
most 7(a) loans (69 percent) and most conventional loans (an estimated 
60 percent) went to corporations.[Footnote 44] Additionally, similar 
shares of 7(a) loans (28 percent) and conventional loans (approximately 
32 percent) went to sole proprietorships. Similar percentages of 7(a) 
and conventional loans went to small firms across geographic locations 
(based on the nine Census divisions). The central regions of the 
country (e.g., Mountain, West North Central, and West South Central) 
received the most similar shares of 7(a) and conventional loans (fig. 
5). 

Figure 5: Percentage of 7(a) and Conventional Loans by Census 
Divisions, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA data; Art Explosion (map). 

Note: The brackets on the conventional loans represent a 95 percent 
confidence interval. 

[End of figure] 

Our analysis of information on the credit scores of small businesses 
that accessed credit without SBA assistance showed only limited 
differences in these credit scores and those of small firms that 
received 7(a) loans. As reported in a database developed by two private 
business research and information providers, The Dun & Bradstreet 
Corporation and Fair Isaac Corporation (D&B/FIC), the credit scores we 
compared are typically used to predict the likelihood that a borrower, 
in this case a small business, will repay a loan.[Footnote 45] In our 
comparison of firms that received 7(a) loans and those that received 
conventional credit, we found that for any particular credit score band 
(e.g., 160-<170) the differences were no greater than 5 percentage 
points and the average difference for these credit score bands was 1.7 
percentage points (see fig. 6). More credit scores for 7(a) borrowers 
were concentrated in the lowest (i.e., more risky) bands compared with 
general borrowers, but most firms in both the 7(a) and the D&B/FIC 
portfolios had credit scores of between 170 and 200. Finally, the 
percentage of firms that had credit scores in excess of 210 was less 
than 1 percent for both groups. 

The results of our analysis of credit scores should be interpreted with 
some caution. First, the time periods for the two sets of credit scores 
are different. Initial credit scores for businesses receiving 7(a) 
loans in our analysis are from 2003 to 2006.[Footnote 46] The scores 
developed by D&B/FIC for small businesses receiving conventional credit 
are based on data from 1996 through 2000 that include information on 
outstanding loans that may have originated during or many years before 
that period.[Footnote 47] Second, D&B/FIC's scores for small businesses 
receiving conventional loans may not be representative of the 
population of small businesses. Although D&B/FIC combined hundreds of 
thousands of financial records from many lenders and various loan 
products with consumer credit data for their credit score development 
sample, they explained that the sample was not statistically 
representative of all small businesses. 

Figure 6: Percentage of Small Business Credit Scores (2003-2006) for 
Firms That Received 7(a) and Conventional Credit in D&B/FIC Sample 
(1996-2000), by Credit Score Range: 

[See PDF for image] 

Source: GAO analysis of initial credit scores for loans in the SBA 
portfolio (2003-2006) and D&B/FIC's analysis of credit scores from data 
on small businesses in the small business portfolio score (SBPS) 
development sample (1996-2000). 

Note: See app. I for details on the data used to perform this analysis. 

[End of figure] 

Another score developed by D&B, called the Financial Stress Score 
(FSS), gauges the likelihood that a firm will experience financial 
stress--for example, that it will go out of business.[Footnote 48] SBA 
officials said that based on analyses of these scores, the difference 
in the repayment risk of lending associated with 7(a) loans was higher 
than the risk posed by small firms able to access credit in the 
conventional lending market. According to an analysis D&B performed 
based on these scores, 32 percent of 7(a) firms showed a moderate to 
high risk of ceasing operations with unpaid obligations in 2006, while 
only 17 percent of general small businesses had a similar risk profile. 

7(a) Loans Tended to Be Larger than Conventional Loans and to Have 
Variable Rates, Longer Maturities, and Higher Interest Rates: 

Compared with conventional loans, a greater percentage of 7(a) loans 
were for larger dollar amounts. For example, 61 percent of the number 
of 7(a) loans had dollar amounts in the range of more than $50,000 to 
$2 million (the maximum 7(a) loan amount), compared to an estimated 44 
percent of the number of conventional loans (see fig. 7).[Footnote 49] 
A larger share of conventional loans had dollar amounts of $50,000 or 
less--an estimated 53 percent, compared with 39 percent of 7(a) loans. 

Figure 7: Percentage of 7(a) Loans and Conventional Loans by Loan Size, 
2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA and Federal Reserve Board of Governors' 
data. 

Note: The brackets on the conventional loans represent a 95 percent 
confidence interval. The maximum gross 7(a) loan amount is $2 million. 
The dollar range categories on this chart reflect program thresholds 
for loan amounts associated with different interest rates or guarantee 
fee levels. 

[End of figure] 

Although more conventional than 7(a) loans were made for smaller 
amounts (i.e., less than $50,000), a higher proportion of conventional 
loan dollars were concentrated in the highest loan amount category 
(i.e., more than $2 million). In contrast, 70 percent of loans with 
7(a) guarantees were for amounts less than $150,000, while 78 percent 
of 7(a) loan dollars were concentrated in loans with amounts of 
$150,000 or greater. In addition, almost all 7(a) loans had variable 
interest rates and maturities that tended to exceed those for 
conventional loans. Nearly 90 percent of all 7(a) loans but only an 
estimated 43 percent of conventional loans had variable rates, and, 
almost 80 percent of 7(a) loans had maturities of more than 5 years, 
compared with 5 years or less for an estimated 83 percent of 
conventional loans (fig. 8). 

Figure 8: Percentage of 7(a) and Conventional Loans by Loan Maturity 
Category, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA and Federal Reserve Board of Governors' 
data. 

Note: The brackets on the conventional loans represent a 95 percent 
confidence interval. 

[End of figure] 

Finally, for loans under $1 million, interest rates were generally 
higher for 7(a) loans than for conventional loans. As shown in figure 
9, from 2001 through 2004 quarterly interest rates for loans guaranteed 
by the 7(a) program were on average an estimated 1.8 percentage points 
higher than interest rates for conventional loans.[Footnote 50] 
Interest rates for small business loans offered in the conventional 
market tracked the prime rate closely and were, on average, an 
estimated 0.4 percentage points higher.[Footnote 51] Because the 
maximum interest rate allowed by the 7(a) program was the prime rate 
plus 2.25 percent or more, over the period, the quarterly interest rate 
for 7(a) loans on average exceeded the prime rate.[Footnote 52] 

Figure 9: Interest Rates Comparison for Loans under $1 Million and 
Prime Rate, 2001-2004: 

[See PDF for image] 

Source: GAO's analysis of SBA data, the Federal Reserve Board of 
Governors' quarterly Survey of Terms of Bank Lending (2001 to 2004), 
and the Federal Reserve Board of Governors' H.15 statistical release 
for bank prime loan rates. 

[End of figure] 

Current Reestimates Show Lower-than-Expected Subsidy Costs, but Final 
Costs May be Higher or Lower for Several Reasons: 

SBA has predicted that the current reestimated credit subsidy costs of 
7(a) loans made during fiscal years 1992 through 2004 generally will be 
lower than the original estimates (see fig. 10). Original estimates are 
made at least a year before any loan is made. The credit subsidy cost 
is often expressed as a percentage of loan amounts--that is, a credit 
subsidy rate of 1 percent indicates a subsidy cost of $1 for each $100 
of loans. As figure 10 shows, the original credit subsidy cost 
estimated for fiscal years 2005 and 2006 was zero, since the 7(a) 
program became a "zero credit subsidy" program. Although the federal 
budget recognizes costs as loans are made and adjusts for these costs 
throughout the lives of the loans, the ultimate cost to taxpayers is 
certain only when none of the loans in a cohort remain outstanding and 
the agency makes a final, closing reestimate. For loans made in fiscal 
years 2005 and 2006, SBA adjusted the ongoing servicing fee it charges 
participating lenders so that the initial subsidy estimate would be 
zero based on expected loan performance at that time. In addition to 
the subsidy costs, SBA incurs administrative expenses for operating the 
loan guarantee program, though these costs are appropriated separately 
from the cost of the credit subsidy. In its fiscal year 2007 budget 
request, SBA requested nearly $80 million to cover administrative costs 
associated with the 7(a) program. 

Figure 10: Original and Current Reestimated Credit Subsidy Rates for 
Loans Made from 1992 through 2006: 

[See PDF for image] 

Source: 2008 Federal Credit Supplement. 

[End of figure] 

Any forecasts of the expected costs of a loan guarantee program such as 
7(a) are subject to change, since the forecasts are unlikely to include 
all the changes in the factors that can influence the estimates. In 
part, the estimates are based on predictions about borrowers' behavior-
-how many borrowers will pay early or late or default on their loans 
and at what point in time. According to SBA officials, loan defaults 
are the factor that exerts the most influence on the 7(a) credit 
subsidy cost estimates and are themselves influenced by various 
economic factors, such as the prevailing interest rates. Since the 7(a) 
program primarily provides variable rate loans, changes in the 
prevailing interest rates would result in higher or lower loan 
payments, affecting borrowers' ability to pay and subsequently 
influencing default and prepayment rates. For example, if the 
prevailing interest rates fall, more firms could prepay their loans to 
take advantage of lower interest rates, resulting in fewer fees for 
SBA. Loan defaults could also be affected by changes in the national or 
a regional economy. Generally, as economic conditions worsen--for 
example, as unemployment rises--loan defaults increase. To the extent 
that SBA cannot anticipate these changes in the initial estimates, it 
would include them in the reestimates. 

Beginning in fiscal year 2003, SBA has employed an econometric model 
that incorporates historical data and other economic assumptions for 
its credit subsidy cost estimates and reestimates instead of relying 
primarily on predictions based on historical average loan performance. 
In previous work we found that the econometric models SBA used to 
estimate defaults, prepayments, and recoveries were reasonable but that 
the agency could expand the type of data it used and its method of 
documenting its decisions regarding the models.[Footnote 53] According 
to SBA officials, the agency has made some recent enhancements to the 
7(a) credit subsidy cost model, including using more current financial 
data on borrowers participating in the 7(a) program. SBA officials 
explained that the agency had also begun validating loan data extracted 
for use in its econometric model by comparing these data to cohort-and 
program-level data from another SBA database containing summary loan 
data. Further, the model now better accounts for amounts SBA recovers 
from borrowers. SBA officials said that the annual review the agency 
conducts of the 7(a) credit subsidy cost model may result in minor 
future changes but that those changes would probably not have any 
significant impact on the subsidy estimates and reestimates. 

Conclusions: 

According to the 7(a) loan program's underlying statutes and 
legislative history, 7(a) is intended to supplement, not compete with, 
the conventional lending market by helping address credit constraints 
that small businesses face. The 7(a) program's design is consistent 
with this intent--for example, the program's credit elsewhere 
requirement is designed to help ensure that loans made through the 7(a) 
program do not supplant credit already available in the conventional 
lending market. Reflecting the evolving mission of the program, 7(a)'s 
performance measures focus on the extent to which the program provides 
guaranteed loans to distinct groups of small businesses, such as start- 
ups and those whose owners face "special competitive opportunity gaps," 
including minority-or women-owned businesses. Our evaluation of the 
program's performance measures found that they were useful in showing 
how many loans had been made--that is the measures effectively show 
outputs, but that they did not provide adequate information on the 
extent to which SBA was meeting its strategic goal of helping small 
businesses succeed by identifying outcomes. As a result, the actual 
impact of the 7(a) program remains unclear. 

Further, only limited evidence exists on the extent to which small 
businesses face credit constraints, such as credit rationing, in the 
conventional lending market. The studies we reviewed suggest that some 
small firms may face credit rationing within the conventional lending 
market, but these studies relied on older data. As a result, they did 
not account for recent trends in the conventional lending market, such 
as the use of credit scores, that could impact lending to small 
businesses by providing lenders with additional information to assess a 
small firm's risk. The effect that these developments may have on the 
credit constraints that some small businesses face is not yet known. 

Based on our analysis, the 7(a) loan program appears to serve certain 
segments of the small business lending market in different proportions 
than conventional loans. A higher proportion of 7(a) loans went to 
minority-owned firms and start-ups, and these results are consistent 
with the program's legislative intent. But the shares of 7(a) and 
conventional loans that went to other segments of the small business 
lending market, such as women-owned businesses and those located in 
economically distressed areas, were more similar. These results may be 
useful to SBA as it considers how it administers the program, including 
its efforts to promote the 7(a) program to lenders and small 
businesses, and how it oversees participating lenders. 

Beginning with fiscal year 2005, the 7(a) program's credit subsidy cost 
has been estimated at zero; however, the credit subsidy costs estimated 
for any fiscal year can change due to various factors and are not final 
until no loans from that year's cohort remain outstanding. Current 
credit subsidy reestimates of loans made in fiscal years prior to 2005 
are lower than originally estimated. Nevertheless, changes in certain 
important factors, such as 7(a) loan defaults, can influence the 7(a) 
program's credit subsidy costs. 

Recognizing its lack of outcome-based information on the firms that the 
7(a) program assists, SBA has efforts underway to develop and implement 
performance measures to better track outcomes of the 7(a) program 
including how small firms fare after they participate in the 7(a) loan 
program. However, SBA has not made clear when, or even if, it plans to 
complete these efforts, in part because of the costs and legal concerns 
associated with obtaining the necessary information to undertake this 
impact analysis. Furthermore, since firms with SBA-guaranteed loans 
represent various geographic areas, go to both existing and new 
businesses, and have loan terms sensitive to prevailing economic 
conditions, many factors unrelated to the loans may impact how well 
firms do after receiving assistance. It is also unclear what benchmark 
for success SBA should adopt for these firms. But without some 
information on outcomes, SBA is unable to provide clear evidence about 
the impact its 7(a) program is having on firms it assists. 

Firms able to meet their loan obligations signal that their businesses 
are continuing to operate in the communities they are located in and 
are, at a minimum, experiencing enough financial success to repay their 
loans. SBA already has loan performance data, such as the number of 
loans that are in default, prepaid, or in good standing, and other 
information on firms that receive assistance from the 7(a) program. 
These data may be reasonable proxies for how well firms are faring 
after receiving guaranteed loans. In addition, although SBA could incur 
costs for collecting additional outcome-based information, data 
reflecting the success of assisted businesses--such as the number that 
go out of business or begin to rely on conventional credit--could be 
useful performance measures. 

Recommendation for Executive Action: 

To better ensure that the 7(a) program is meeting its mission 
responsibility of helping small firms succeed through guaranteed loans, 
we recommend that the SBA Administrator complete and expand SBA's 
current work on evaluating the program's performance measures. As part 
of this effort, at a minimum SBA should further utilize the loan 
performance information it already collects, including but not limited 
to defaults, prepayments, and number of loans in good standing, to 
better report how small businesses fare after they participate in the 
7(a) program. 

Agency Comments and Our Evaluation: 

We provided SBA with a draft of this report for review and comment. SBA 
provided comments in a letter from the Deputy Associate Administrator 
of SBA's Office of Capital Access. The letter is reprinted in appendix 
IV. SBA agreed with our recommendation but disagreed with a comparison 
in the section of our report on credit scores, one of a number of 
comparisons included in our analysis of the segments of the small 
business lending market that are served by 7(a) and conventional loans. 

Specifically, to assess the relative creditworthiness of firms 
receiving 7(a) loans to firms receiving conventional credit, we 
compared the initial credit scores for loans in SBA's 7(a) portfolio to 
scores for conventional loans calculated from a database developed by 
D&B/FIC. Our analysis of this information showed only limited 
differences in the credit scores of borrowers with 7(a) and 
conventional loans. Our draft and final report also disclosed that the 
results of this analysis should be interpreted with some caution 
because the time periods of the two sets of credit scores are different 
and the credit scores for small businesses with conventional loans may 
not be representative of the population of small businesses. In its 
written comments, SBA primarily reiterated the cautions included in our 
report and stated that it disagreed with the results of our analysis 
showing limited differences in the credit scores of borrowers with 7(a) 
and conventional loans. SBA stated that the riskiness of a portfolio is 
determined by the distribution in the riskier credit score categories. 
Although stating that "the numbers have not been worked out," SBA 
concluded that the impact on loan defaults from the higher share of 
7(a) loans in these categories would not be insignificant. 

The intent of our analyses of credit scores and other borrower and loan 
characteristics is to provide a comparison of the segments of the small 
business lending market that are served by 7(a) and conventional loans, 
and our analyses are not intended to quantify the impact of differences 
in these characteristics on 7(a) defaults. We continue to believe that 
our analysis of credit scores provides a reasonable basis for comparing 
the share of businesses in different credit score categories. 
Specifically, the data we used were derived from a very large sample of 
financial transactions and consumer credit data and reflect the 
broadest and most recent information readily available to us on small 
business credit scores in the conventional lending market. Recognizing 
the limitations associated with these data, in the future analyzing 
more comparable data on credit scores for small business borrowers with 
conventional loans may provide SBA and others with a more conclusive 
picture of the relative riskiness of borrowers with 7(a) and 
conventional loans. Such an analysis would be consistent with our 
recommendation. 

In addition, SBA provided technical comments, which we incorporated 
into the report as appropriate. 

As agreed with your offices, unless you publicly announce the contents 
of this report earlier, we plan no further distribution until 30 days 
from the report date. At that time, we will send copies of this report 
to other interested congressional committees and the Administrator of 
the Small Business Administration. We will also make copies available 
to others upon request. In addition, the report will be available at no 
charge on the GAO Web site at http://www.gao.gov. 

If you have any questions about this report, please contact me at (202) 
512-8678 or [email protected]. Contact points for our Offices of 
Congressional Relations and Public Affairs may be found on the last 
page of this report. Key contributors to this report are listed in 
appendix V. 

Sincerely yours, 

Signed by: 

William B. Shear: 
Director, Financial Markets and Community Investment: 

[End of section] 

Appendix I: Objectives, Scope and Methodology: 

In this report, we examined (1) the statutory framework and legislative 
history of the 7(a) program and performance measures the Small Business 
Administration (SBA) utilizes to assess program results; (2) factors in 
the conventional lending market that may affect small businesses' 
access to credit, including market imperfections; (3) how the segments 
of the small business lending market served by 7(a) loans compare with 
segments served by conventional loans; and (4) differences in SBA's 
estimates and reestimates of 7(a)'s credit subsidy costs and the 
factors that may cause uncertainty about the costs of the 7(a) program 
to the federal government. 

Analysis of Statutory Framework of 7(a) Program and Its Performance 
Measures: 

To describe the purpose of the 7(a) program, we reviewed the program's 
underlying statutes and legislative history to understand how the 
program was intended to help small businesses. To assess SBA's 
performance measures for the 7(a) program, we selected performance 
measures specific to the 7(a) program as reported in the SBA's recent 
Performance and Accountability Reports. We evaluated nine different 
performance measures against six attributes identified in our earlier 
work as being indicative of successful performance measures. 

Taken from SBA's fiscal year 2006 Performance and Accountability 
Report, the nine performance measures were: 

1. number of new loans approved to start-up small businesses, 

2. number of new loans funded to start-up small businesses, 

3. number of start-up small businesses assisted, 

4. number of new loans approved to existing small businesses, 

5. number of new loans funded to existing small businesses, 

6. number of existing small businesses assisted, 

7. number of new loans approved to small businesses facing special 
competitive opportunity gaps, 

8. number of new loans funded to small businesses facing special 
competitive opportunity gaps, and: 

9. number of small businesses facing special competitive opportunity 
gaps assisted. 

Taken from our earlier report, Tax Administration: IRS Needs to Further 
Refine Its Tax Filing Season Performance Measures (GAO-03-143), the six 
attributes we assessed the above mentioned performance measures against 
were: 

1. core program activity (measures cover the activities that an entity 
is expected to perform to support the intent of the program), 

2. measurable target (measure has a numerical goal), 

3. reliability (measure produces the same result under similar 
conditions), 

4. clarity (measure is clearly stated and the name and definition are 
consistent with the methodology used to calculate it), 

5. objectivity (measure is reasonably free from significant bias or 
manipulation), and: 

6. linkage (measure is aligned with division and agencywide goals and 
mission). 

We reviewed and summarized agency documents relating to its ongoing 
contract with the Urban Institute regarding evaluative studies of SBA's 
lending programs, including the 7(a) program, currently underway. We 
also interviewed SBA officials to understand agency efforts to improve 
its 7(a) program performance measures. 

Economic Literature on Credit Rationing and Discrimination: 

To identify constraints that may limit credit to small businesses we 
summarized published, peer-reviewed articles that discuss the subject 
of credit rationing with regard to firms. We identified articles 
through reviews of citations of the most recent literature, and by 
identifying current papers that cite the influential papers in this 
field (e.g., Stiglitz and Weiss (1981)), and by using article search 
engines, such as "google scholar" and "jstor." The review concentrated 
on empirical studies of the U.S. financial market, although studies of 
the non-U.S. market were included in order to understand the various 
empirical methodologies employed in this area. In addition, we 
summarized recent peer-reviewed studies that explore the extent of 
racial, ethnic, and gender disparities within the conventional lending 
market. Studies published by think tanks and others that were not peer- 
reviewed were not included in our review. Appendix II includes a more 
detailed description of the studies we reviewed about credit rationing 
and discrimination. 

Comparison between 7(a) and Conventional Loans: 

As described more fully in the following sections, to assess 
similarities and differences in the small business lending market 
segments served by 7(a) and conventional loans, we compared relevant 
information on loan terms and borrower characteristics using several 
data sources. Our analysis was restricted to loans made to firms 
located within the 50 states, and did not include Puerto Rico or any 
U.S. territories. To assess the reliability of the data used, we 
reviewed applicable documentation associated with the specific data 
source, such as a data dictionary, survey questionnaire, and 
methodology report. We interviewed officials at the Board of Governors 
of the Federal Reserve System (Federal Reserve) and SBA who provided us 
the data in order to understand any data limitations and how the data 
are collected and stored. We also consulted with Dun & Bradstreet 
Corporation and Fair Isaac Corporation (D&B/FIC) officials about their 
data used to generate credit scores for small businesses, including 
those used by the SBA. Finally, we conducted logic and electronic tests 
of each data source. We determined the data to be sufficiently reliable 
for use in our report. 

Number of Loans and Loan Dollars Outstanding: 

To compare the number and amount of outstanding small business loans to 
7(a) loans, we used the Federal Deposit Insurance Corporation's (FDIC) 
Consolidated Reports of Condition and Income (call reports) for U.S. 
banks. U.S. commercial banks and insured savings institutions are 
required by federal law to report certain financial information to 
their appropriate bank regulator quarterly, which FDIC then 
consolidates and maintains in a database. For the purposes of the call 
reports, a small business loan is defined by SBA's Office of Advocacy 
as a commercial and industrial loan or a non-farm, nonresidential loan 
for which the original amount was $1 million or less. Therefore, we 
considered the call report data on loans under $1 million to be a proxy 
for general small business loans, even though there is no attempt to 
directly link the loans to the size of the firm accessing credit in the 
call report data. SBA reports tabulations of call report data prepared 
for the agency by an external contractor as of June 2005, the latest 
data available. We requested that SBA provide us with similar 
information on the number and amount of outstanding 7(a) loans under $1 
million as of September 30, 2005. 

Loan and Borrower Characteristics: 

To evaluate SBA's 7(a) borrowers and loan terms, we used data from two 
SBA administrative data systems: (1) the Loan Accounting System and (2) 
the Loan/Lender Monitoring System for information to describe 7(a) 
loans and borrowers. To assess general small business borrowers and 
loan terms, we used the 2003 Survey of Small Business Finances (SSBF) 
conducted by the Federal Reserve. We also used Federal Reserve's 
historical reports on the monthly bank prime rate in its Survey of 
Terms of Bank Lending to report the quarterly interest rates for loans 
under $1 million. In addition, we obtained from the D&B/FIC small 
business credit scores derived from their Small Business Predictive 
Score development sample. 

SBA's data include various information describing the loan, such as the 
percentage of the loan guaranteed by SBA, the number of months to 
maturity, and whether the loan had a fixed or variable interest rate. 
The data also include information on the small firm, such as the 
ethnicity and gender of the principal owner, the number of employees, 
and the firm's status as new (i.e., less than 2 years old). SBA 
provided us with 304,032 records from its administrative data systems, 
which contained information on all loans approved and disbursed in 
calendar years 2001 through 2005. Based on discussions with SBA 
officials about the data and logic testing, we eliminated certain cases 
from the data provided that had missing values, zero values where 
appropriate, or that SBA officials confirmed as incorrect data. We 
eliminated records with any missing or confirmed incorrect information 
in order to have the same number of cases for each analysis performed. 
This reduced the number of 7(a) records by 7,495.[Footnote 54] SBA 
officials identified an additional 1,730 incorrect social security 
numbers, which further reduced the number of 7(a) records. We also 
eliminated 24,010 records to delete multiple loans to the same 
business. In order to make the SBA data more comparable to the SSBF 
data, we included only SBA loans a borrower received between 2001 and 
2004, which further reduced the number of 7(a) records by 78,056. The 
final number of 7(a) records we used in our analysis was 192,741, 
representing a 36 percent decrease in the number of records originally 
provided by SBA. 

We used information from the SSBF as a proxy for loans made to small 
firms within the conventional lending market (i.e., not made with the 
assistance of the 7(a) program).[Footnote 55] The SSBF interviewed 
4,240 firms in 2004 and early 2005 that were selected to provide a 
representative sample of all small businesses in the United 
States.[Footnote 56] Among other things, the SSBF assesses credit 
availability for small businesses, provides financial data for small 
businesses currently unavailable from other sources, and validates 
geographic and product market definitions. SSBF data are used to study 
the effects of changes within the lending industry on credit use by 
small businesses and to monitor technological and competitive changes 
in markets for financial services used by small businesses. We used 
records in which firms reported that the last loan they had applied for 
had been approved. Applying this standard reduced the number of records 
by 2,479. We further eliminated records in which firms reported 
obtaining their most recent loan outside of 2001 to 2004 and firms 
reporting zero employees, which further decreased the number of records 
by 23. The final unweighted number of records from the SSBF data was 
1,738. Since the data were from a sample with statistical weights, all 
the percentages in the body of the report reflect weighted percentages. 
In addition, the SSBF includes multiple imputed values. Our standard 
error and confidence interval calculations incorporate the multiple 
imputations where appropriate. We calculated the standard error and 
confidence intervals for each of the analyses performed using these 
data since they are based on a random sample. Unless otherwise noted, 
all percentage estimates have a 95 percent confidence interval within 
plus or minus 5 percentage points. 

The following are more detailed descriptions of actions we took to make 
the data from SBA and SSBF more comparable: 

Minority Status of Ownership: 

SBA's data include an indicator for whether more than 50 percent of the 
small business owners are from racial or ethnic minority categories. 
For the first time, the 2003 SSBF combined data on up to three owners 
and calculated various indicators by majority owner share. The SSBF 
data included two data fields related to race and ethnicity that we 
used. The first field designated whether more than 50 percent of the 
ownership was white, and the second field designated whether 50 percent 
or more of the ownership was minority or Hispanic. Using these fields, 
we compared the share of 7(a) and conventional loans that went to small 
businesses with 50 percent or greater minority ownership. 

Longevity of Business: 

SBA's data include information indicating whether or not the business 
was new, which SBA defines as being less than 2 years old. The SSBF's 
information included information on the year of the survey and the year 
when the firm applied for its most recently approved loan. In addition, 
the survey included an age for the firm. We calculated the age of the 
firm when it applied for the most recent loan. We considered a business 
as new if its age was 2 years or less when it applied for its most 
recently approved loan. 

Number of Employees: 

The number of employees in SBA's data is the number provided by the 
prospective borrower at the time of loan approval. According to SBA, 
the number of employees is required as part of the application process, 
so any zeros in this field should be treated as missing values. 
Additionally, we eliminated SBA records that listed the number of 
employees as 500 or greater to match the SSBF's selection criteria. The 
SSBF's data included information on the number of full-and part-time 
employees. All cases specifying zero employees were eliminated. 

Gender of Ownership: 

Both SBA's data and the SSBF's data had information designating whether 
more than 50 percent, less than 50 percent, or exactly 50 percent of 
the firm was female-owned. We compared the groups of more than 50 
percent female ownership, exactly 50 percent female/male ownership, and 
more than 50 percent male ownership receiving 7(a) and conventional 
loans. 

Economically Distressed Areas: 

We created a variable indicating whether or not a given geographic 
location in which a business receiving a loan is situated, is in 
economic distress. The indicator we chose was based on the minimum 
eligibility criteria for the Empowerment Zone and Enterprise Community 
(EZ/EC) and the Renewal Community (RC) programs, which target federal 
grant monies to public and private entities, tax benefits to 
businesses, or both in order to improve conditions in competitively 
selected, economically distressed communities. The minimum poverty 
level eligibility requirement for EZ/EC and RC is that at least 20 
percent of the population in the census tracts that make up the zone 
must have incomes below the national poverty line. Using data from the 
2000 Census, we used the Census Zip Code Tabulation Areas (which 
approximate zip code boundaries) to identify zip codes in which 20 
percent or more of the individuals had income below the poverty level. 
We matched the zip codes of businesses receiving 7(a) loans from 2001 
through 2004 (using updated geography to account for changes to zip 
code boundaries) to the 2000 Census file to quantify how many 7(a) 
loans went to businesses in economically distressed areas. The business 
locations for respondents to the SSBF are not included in the public 
use data file. However, Federal Reserve staff matched our distress 
indicator to the zip codes for their respondents and returned the data 
to us for merging with the public file without revealing respondents' 
business locations. We then compared the shares of 7(a) and 
conventional loans that went to economically distressed areas. 

Business Organization: 

SBA's data included three organizational types--individual (or sole 
proprietorship), partnership, and corporation. The SSBF included nine 
organization types--sole proprietorship, partnership, S corporation, C 
corporation, limited liability partnerships tax filed as partnerships 
or corporations, and limited liability corporations tax filed as sole 
proprietorships, partnerships, or corporations. We combined the two 
types of sole proprietorships, the three types of partnerships, and the 
four types of corporations in the SSBF's data to provide comparable 
information. 

Geographic Information: 

The only geographic information in the SSBF's data was the census 
region in which the firm was located.[Footnote 57] The state listed in 
SBA's data was used to group the 7(a) data according to census regions. 

Interest Rates: 

In order to compare interest rates on 7(a) loans to loans general small 
businesses obtained in the conventional lending market, we used data 
from the Federal Reserve's Survey of Terms of Bank Lending. The survey 
provides information quarterly on the number of commercial and 
industrial loans by four size categories (less than $100,000; between 
$100,000 and $999,999; between $1 million and $999,999,000; and $10 
million or more) made only by commercial banks.[Footnote 58] The survey 
reports an average interest rate in each category that is weighted by 
loan amount. We only used data related to the first two categories 
because those loan amounts most resembled the 7(a) loans in the SBA 
data and because SBA's Office of Advocacy considers in call report 
data, discussed previously, loans of $1 million or less to be for small 
businesses. Limitations to these data regarding our analysis include 
that the information is gathered during 1 week in the middle month of 
each quarter and does not distinguish between the sizes of the business 
obtaining the loan.[Footnote 59] In addition, the data in the survey do 
not include loans made by finance companies or small business loans 
made on credit cards. In order to compare interest rate data we derived 
from the survey, we used SBA data to calculate the calendar year and 
quarter in which each loan was disbursed and calculated the average 
interest rates for all loans disbursed in a given quarter that were for 
under $1 million. In order to be consistent with the survey, we 
calculated the average quarterly interest rate using the loan amounts 
as weights. Finally, we used Federal Reserve's historical reports on 
the monthly bank prime rate to estimate the prime rate for every 
quarter from 2001 through 2004. 

Credit Scores: 

To assess the relative creditworthiness of firms receiving 7(a) loans 
to firms receiving conventional credit, we compared the initial credit 
scores for loans in SBA's 7(a) portfolio to scores calculated from D&B/ 
FIC's large sample of data from small businesses in the conventional 
lending market and from consumer credit bureaus. In comparing credit 
scores for 7(a) firms with other firms, we relied on D&B/FIC's analysis 
of credit scores based on data from small business transactions, 
consumer credit bureaus, and loan performance from their user's lending 
portfolios from 1996 through 2000, known as the Small Business 
Predictive Score (SBPS) development sample. The loans D&B/FIC used for 
its sample were outstanding loans including those that originated 
between 1996 and 2000 and older loans. We relied on the D&B/FIC data 
from a different time period because time and resource constraints 
prohibited obtaining more recent data. As stated previously, our 
comparison of credit scores should be interpreted with caution because 
the data come from different time periods and the D&B/FIC credit scores 
may not be representative of the population of general small 
businesses. However, although the data D&B/FIC used to develop its 
small business credit score may not be statistically representative of 
all small businesses, the data sample is very large and reflects the 
broadest and most recent information readily available to us on small 
business credit scores in the conventional lending market. 

Description of Credit Subsidy Cost Estimates and Reestimates: 

To describe 7(a)'s credit subsidy cost estimates and reestimates we 
compared SBA's original credit subsidy cost estimates for fiscal years 
1992 through 2006 to SBA's reestimates in fiscal year 2008, as reported 
in the fiscal year 2008 Federal Credit Supplement. We reviewed 
documents related to the 7(a) credit subsidy cost model, which the 
agency uses to generate its estimates and reestimates. We also 
interviewed SBA officials to understand any differences in the reported 
original credit subsidy cost estimates and subsequent reestimates, as 
well as to describe what factors may influence future reestimates. 

Analysis of 504 Loan Program: 

We were unable to undertake a similar comparative analysis between 504 
loans and loans made to general small businesses within the 
conventional lending market primarily due to the limited number of 
observations of conventional loans that were comparable to loans with 
504 guarantees and lack of generalizability with the SSBF data. We have 
included in appendix III information on the characteristics of 
borrowers and loans financed under SBA's 504 program based on analysis 
done using data provided by SBA. We performed the same eliminations of 
observations for missing or incorrect data that we applied to the 7(a) 
data as described above, which resulted in a 28 percent (from 28,341 to 
20,289) decrease in the number of cases used in our analysis. 

We performed our work in Washington, D.C., and Chicago from May 2006 
through July 2007 in accordance with generally accepted government 
auditing standards. 

[End of section] 

Appendix II: Summary of Economic Literature on the Empirical Evidence 
for Credit Rationing and Discrimination in the Conventional Lending 
Market: 

Study: Berger, Allen N., and Gregory F. Udell, "Some Evidence on the 
Empirical Significance of Credit Rationing," The Journal of Political 
Economy, vol. 100, no. 5 (1992): 1047-1077; 
Objective: One implication of credit rationing is that commercial loan 
rates do not respond quickly to changes in the market interest rate--
i.e., are sticky. Objective was to develop and implement a series of 
empirical tests able to determine whether loan rate stickiness is 
explained by credit rationing or something else; 
Data: Contract information from 1977 through 1988 on approximately 1 
million bank loan contracts; 
Method: Tested for "stickiness" and whether it is mitigated by specific 
loan contract features, such as commitment or collateral. Because 
commitment loans act as insurance against rationing, they can be used 
as a test for whether stickiness stems from credit rationing. Because 
rationing is more likely when open market interest rates are high, also 
examines the proportion of loans that are made in commitment agreement 
and whether it increases with the interest rate; 
Conclusions and limitations: Found evidence inconsistent with credit 
rationing. Could not conclude that stickiness stems from credit 
rationing, since nearly half of the loan rate stickiness occurs with 
commitment loans. The proportion of loans that were commitment loans 
decreased during credit market tightness, the direction opposite from 
that predicted by credit rationing; Concluded that these results did 
not disprove the existence of credit rationing of commercial bank 
borrowers but indicated that rationing does not constitute an important 
macroeconomic phenomenon. 

Study: Berger, Allen N., and Gregory F. Udell, "Relationship Lending 
and Lines of Credit in Small Firm Finance," The Journal of Business, 
vol. 68, no. 3 (1995): 351-381; 
Objective: To examine the effect of relationship lending in small firm 
finance. Hypothesized that banks may acquire private information over 
the course of a relationship; therefore, focused on lines of credit 
issued to small business; 
Data: 1988-89 National Survey of Small Business Finances survey of 
3,404 businesses; 
Method: Assessed the empirical relationship between relationship 
lending and collateral. Focused exclusively on lines of credit, using 
the firm's age and the number of years it had done business with the 
lender as measures of how information can change the terms of credit; 
Conclusions and limitations: Found evidence consistent with credit 
rationing. Highlighted the role of relationship lending in loan 
contracts and provided support for credit rationing. The evidence 
indicated that small firms with longer relationships pay lower interest 
rates and are also less likely to pledge collateral. Results suggested 
that banks accumulate increasing amounts of private information over 
the duration of the bank-borrower relationship and use the information 
when defining contract terms. Found that results were consistent with 
theoretical arguments that relationship lending generates valuable 
information about borrower quality, which is consistent with credit 
rationing. 

Study: Berkowitz, Jeremy, and Michelle J. White, "Bankruptcy and Small 
Firms' Access to Credit," The RAND Journal of Economics, vol. 35, no.1 
(2004): 69-84; 
Objective: To examine how personal bankruptcy law affects small firm 
access to credit by exploiting state variation in assets shielded from 
bankruptcy proceedings. Because many small business loans are secured 
with personal credit, hypothesized that firms in high-exemption states 
are more likely to be denied credit or be credit rationed; 
Data: 1993 National Survey of Small Business Finances survey of 5,356 
small businesses operating as of year-end 1992; 
Method: Tested for credit rationing by exploiting state variation in 
the type and amount of assets shielded from bankruptcy proceedings. 
This follows from the study's model, derived from economic theory, 
which suggests that the more assets shielded from bankruptcy, the 
greater the incentive to declare bankruptcy; 
Conclusions and limitations: Found evidence of credit rationing but 
under a broader definition than other studies. According to the study's 
definition, managers who are denied credit or discouraged from applying 
have been "credit rationed." Concluded that higher personal exemptions 
increase credit rationing. Firms are more likely to be denied credit 
and, if offered credit, at higher interest rates. 

Study: Blanchflower, David G., Philip B. Levine, and David J. 
Zimmerman, "Discrimination in the Small-Business Credit Market," The 
Review of Economics and Statistics, vol. 85, no. 4 (2003): 930-943; 
Objective: To examine the presence of discrimination in the small 
business credit market; 
Data: 1993 and 1998 editions of the National Survey of Small Business 
Finances; 
Method: Using a regression approach, tested whether differences in 
rates of loan denial or interest by demographic group can be explained 
by differences in credit worthiness or other factors, including credit 
scores; 
Conclusions and limitations: Found mixed results with respect to 
discrimination. Using a large amount of controls, found significant 
evidence that African American-owned firms face obstacles in obtaining 
credit, with lower application rates and higher denial rates. Also 
found that African American-owned firms were charged higher interest 
rates. The study referred to the magnitude of the difference for 
African Americans as substantial but could not find evidence of similar 
discrimination against women or other ethnic groups. 

Study: Bodt, Eric de, Frederic Lobez, and Jean-Christophe Statnik, 
"Credit Rationing, Customer Relationship, and the Number of Banks: An 
Empirical Analysis," European Financial Management, vol. 11, no. 2 
(2005): 195-228; 
Objective: To estimate the effect of bank mergers on access to credit; 
Data: Data from a questionnaire sent to 4,932 Belgian firms that met 
certain selection criteria on data quality and being a small business; 
Method: Analyzed the relationship between the numbers of banks used by 
the firm, customer relationship, and credit rationing for these 
businesses; 
Conclusions and limitations: Found no general rule that related the 
number of banks a firm does business with to the extent of credit 
rationing. For example, found that smaller firms dealing with big main 
banks should increase the number of banks in order to minimize the 
probability of being rationed. Larger firms, dealing with local banks, 
in contrast, should concentrate financing to limit rationing. 

Study: Cavalluzzo, Ken S., and Linda C. Cavalluzzo, "Market Structure 
and Discrimination: The Case of Small Business," Journal of Money, 
Credit and Banking, vol. 30, no. 4 (1998): 771-792; 
Objective: To estimate the prevalence of prejudicial discrimination in 
small business lending; 
Data: 1988-89 National Survey of Small Business Finances survey of 
3,404 businesses, including information on applications for credit and 
their outcome; 
Method: Using the insight that the more competitive a market is, the 
less the likelihood is of prejudicial discrimination, the study 
regressed interest rates, rates of application, and denial of credit on 
measures of concentration of the banking industry where loans were 
made; 
Conclusions and limitations: Evidence on discrimination was mixed. 
Found evidence of prejudicial discrimination against Hispanics and 
Asians. Found that African American-owned small businesses hold fewer 
loans but did not find that this stemmed from prejudicial treatment. 
Found that prejudicial discrimination may favor women. 

Study: Cavalluzzo, Ken S., Linda C. Cavalluzzo, and John D. Wolken, 
"Competition, Small Business Financing, and Discrimination: Evidence 
from a New Survey," Journal of Business, vol. 75, no. 4 (2002): 641- 
679; 
Objective: To examine whether differences in interest rates, rates of 
denial, and application rates by gender and race can be linked to 
discrimination; 
Data: 1993 National Survey of Small Business Finances survey of 5,356 
small businesses operating as of year-end 1992; 
Method: Using a regression, used bank concentration to identify 
prejudicial discrimination. Examined loan application, denial, and 
interest rates, as well as firms discouraged from applying for credit. 
Used a rich set of control variables, such as whether borrowers had 
experienced bankruptcy and the borrowers' credit scores; 
Conclusions and limitations: Found evidence of discrimination in the 
small business lending market. Found some evidence of prejudicial 
discrimination against African Americans and more robust evidence of 
prejudicial discrimination against women. 

Study: Cole, Rebel A., "The Importance of Relationships to the 
Availability of Credit," Journal of Banking and Finance, vol. 22 
(1998): 959-977; 
Objective: To examine the effect of preexisting relationships between 
lenders and firms on credit availability; 
Data: 1993 National Survey of Small Business Finances survey of 5,356 
small businesses operating as of year-end 1992; 
Method: Estimated the effect of relationships on credit availability. 
Used other types of bank services the firms used, as well as length of 
relationships, as measures of the strength of the relationship. Whether 
a firm was extended credit was a measure of credit availability; 
Conclusions and limitations: Provided evidence consistent with credit 
rationing, concluding that a preexisting relationship between firm and 
lender increases the chances that credit will be extended but that the 
length of the relationship is unimportant. 

Study: Cowling, Marc, and Peter Mitchell, "Is the Small Firms Loan 
Guarantee Scheme Hazardous for Banks or Helpful to Small Business?" 
Small Business Economics, vol. 21, no. 1 (2003): 63-71; 
Objective: To test an underpinning of credit rationing--that the rate 
of default increases with the cost of capital--i.e., the interest rate; 
Data: Data on 42,316 loans issued with collateral provided by the U.K. 
Small Firm Loan Guarantee Scheme; 
Method: Presented two alternative tests. First, estimated the effect of 
firm and loan level characteristics on default, and second tested for 
the effect of factors that change over time; 
Conclusions and limitations: Found that consistent with credit 
rationing, default rate increases with the interest rate. However, also 
found that a series of other factors not addressed by the credit 
rationing literature, such as the loan's purpose, also affect default 
rate. 

Study: Cressy, Robert, "Are Business Startups Debt-Rationed?" The 
Economic Journal, vol. 106 (1996): 1253-1270; 
Objective: If financial capital affects business survival, this is 
evidence that credit constraints exist for some businesses. Objective 
was to examine whether human capital (such as education) might be an 
alternative explanation. If human capital is correlated with access to 
credit, then previous studies that failed to correct for this might 
incorrectly associate financial assets with business survival; 
Data: A sample of 2,000 U.K. start-ups that opened business accounts in 
1988; 
Method: Tested for debt rationing after correcting for human capital. 
Used several measures for human capital--proprietors' age, education, 
work experience in the area of the start-up; 
Conclusions and limitations: Found no evidence for debt rationing. 
Evidence suggested that human capital is the true determinant of 
survival and that the importance of financial capital is spurious. 
Firms with more human capital are more likely to accept a bank's offer. 
Concluded that, rather than a bank's selecting firms, they self-select 
for finance and those firms with more human capital are more likely to 
accept the bank's offer. 

Study: Holtz-Eakin, Douglas, David Joulfaian, and Harvey S. Rosen, 
"Sticking It Out: Entrepreneurial Survival and Liquidity Constraints," 
The Journal of Political Economy, vol. 102, no. 1 (1994): 53-75; 
Objective: To examine why some individuals survive as entrepreneurs and 
some do not. Focused on the role of access to capital. Tested an 
implication of credit rationing--that individuals will face liquidity 
constraints; 
Data: 1981 and 1985 federal tax return data on individuals who received 
inheritances; 
Method: Tested whether an inheritance affects business survival. One 
implication of liquidity constraints would be that entrepreneurs who 
have access to financial resources independent of the credit market, 
such as inheritances, are more likely to succeed; 
Conclusions and limitations: Although not on the subject of small 
business lending, provided support for credit rationing. Results 
suggested that a sizable inheritance has a small but noticeable effect 
on business survival and a larger effect on business receipts, which is 
consistent with an implication of credit rationing and liquidity 
constraints. 

Study: Levenson, Alec R., and Kristen L Willard, "Do Firms Get the 
Financing They Want? Measuring Credit Rationing Experienced by Small 
Businesses in the U.S." Small Business Economics, vol. 14, no. 2 
(2000): 83-94; 
Objective: To measure the extent to which small businesses in the late 
1980s were able to access external credit at a level they desired. The 
extent to which this is not true forms the upper bound of credit 
rationing, since some firms denied credit are actually credit unworthy; 
Data: 1988-89 National Survey of Small Business Finances survey of 
3,404 businesses; 
Method: To find an upper bound for the existence of credit rationing, 
estimated the percentage of small businesses denied credit. Included in 
the analysis firms denied credit and firms discouraged from applying 
for credit; 
Conclusions and limitations: Found evidence consistent with credit 
rationing. Estimated that an upper bound of 6.36% of firms was 
rationed. The firms that were rationed represented 3.22% and 3.46% of 
sales and employment in the survey. Consistent with expectations, 
credit rationing was associated with firm size. While finding evidence 
consistent with credit rationing, the evidence suggested that 
equilibrium credit rationing is economically unimportant for the small 
firms analyzed. 

Study: Perez, Stephen J., "Testing for Credit Rationing: An Application 
of Disequilibrium Econometrics," Journal of Macroeconomics, vol. 20, 
no. 4 (1998): 721-739; 
Objective: To test whether firms experience credit rationing by testing 
for excess demand. If there is no credit rationing, then the market 
will be at equilibrium and the supply of credit will equal demand; 
Data: 5,000 firm-year observations from the CompuStat database of 
publicly traded firms for each year from 1981 through 1991; 
Method: Developed a model that allowed an empirical test for credit 
rationing. To implement the model, used maximum likelihood methods to 
test three samples of the population: firms with assets less than $10 
million, assets $10 million to $25 million, and assets $25 million to 
$50 million; 
Conclusions and limitations: Concluded that credit rationing exists. In 
all three samples, concluded that some firms face excess demand and are 
credit rationed while some do not. Found that the mean probability that 
the smallest firms are rationed was 61.9%, medium firms 59.1%, largest 
firms 59.8%. This suggested that smaller firms are more likely to be 
credit rationed. Did not test for whether the differences were 
statistically significant. 

Study: Petersen, Mitchel A., and Raghuram G. Rajan, "The Benefits of 
Lending Relationships: Evidence from Small Business Data," The Journal 
of Finance, vol. 49, no. 1 (1994): 3-37; 
Objective: To test whether ties between a firm and its creditor affect 
the cost and availability of credit to the firm and whether they 
mitigate the effect of credit rationing. Argued that "adverse selection 
and moral hazard may have a sizeable effect when firms are young and 
small," which made the sample likely to show the effects of credit 
rationing; 
Data: 1988-89 National Survey of Small Business Finances survey of 
3,404 businesses; 
Method: Estimated the effect relationships have on credit availability 
and interest rates. Using a regression, tested for the significance of 
a variety of relationship measures, such as relationship length in 
years, use of other financial services at the bank, and number of other 
banks the firm borrows from; 
Conclusions and limitations: Presented evidence consistent with credit 
rationing. For interest rates, found a small effect of concentrating 
business with a single bank on the price charged by lenders; found that 
firms that borrowed from multiple banks had increased interest rates; 
and that there was little effect on the length of the relationship. On 
credit availability, found stronger effects of relationships: the 
availability of credit from institutions increases as the firm spends 
more time in the financial relationship and increases the number of 
financial services used, as that concentrates borrowing at that bank. 
Argued that these results are consistent with credit rationing but 
might also be consistent with a reduction in lender's expected cost. 

Study: Sofianos, George, Paul Wachtel, and Arie Melnik, "Loan 
Commitments and Monetary Policy," Journal of Banking and Finance, vol. 
14 (1990): 677-689; 
Objective: To measure the effect of loan commitments on how monetary 
policy affects the economy. Commitment is an agreement between the bank 
and the firm to lend an amount but not at a fixed interest rate. 
Consequently, a loan commitment should, in the short run, prevent a 
firm from being credit rationed; 
Data: A 1973-87 monthly survey of commercial banks conducted by the 
Board of Governors of the Federal Reserve; 
Method: Examined whether loans under commitment are less affected by a 
period of monetary tightening, since the bank cannot choose to refuse 
credit; 
Conclusions and limitations: Presented evidence consistent with credit 
rationing. While both types of loans are affected by interest rates, 
found evidence of a differential effect of monetary policy on loans 
under commitment. Concluded that quantity rationing occurs in the 
market for bank loans. Also concluded that borrowers' willingness to 
obtain commitment loans, at an expense, is consistent with the desire 
to insure against credit rationing. 

Study: Trovato, Giovanni, and Marco Alfo, "Credit Rationing and the 
Financial Structure of Italian Small and Medium Enterprises," Journal 
of Applied Economics, vol. 9, no. 1 (2006): 167-184; 
Objective: To analyze the effect of credit subsidies on the development 
of small and medium Italian enterprises; 
Data: Survey data from 1989 through 1994 of approximately 1,919 Italian 
firms; 
Method: Tested whether firms that gain subsidies are more likely to 
reduce their financial constraints and increase investment levels; 
Conclusions and limitations: Presented evidence consistent with credit 
rationing. Found that firms' leverage is positively related to the 
presence of public subsidies. 

Source: GAO analysis. 

[End of table] 

[End of section] 

Appendix III: Descriptive Statistics of 504 Loan Program: 

As stated previously, 504 loans generally provide long-term, fixed-rate 
financing to small businesses for major fixed assets, such as land and 
buildings. The following figures provide descriptive statistics for 504 
loans approved and disbursed from 2001 through 2004, including 
information on the characteristics of 504 loans and borrowers. Not all 
information available for the 7(a) loans described in the body of the 
report was available for the 504 loans. For example, SBA does not 
collect interest rate data for 504 loans. Additionally, because 504 
loans are only offered with set maturities (mostly 10 or 20 year) and 
fixed interest rates, there are no data on revolving loans or loans 
with variable interest rates. 

Figure 11: Percentage of 504 Loans by Minority Status of Ownership, 
2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA data. 

[End of figure] 

Figure 12: Percentage of 504 Loans by Status as a New Business, 2001- 
2004: 

[See PDF for image] 

Source: GAO analysis of SBA data. 

[End of figure] 

Figure 13: Percentage of 504 Loans by Gender of Ownership, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA data. 

[End of figure] 

Figure 14: Percentage of Small Business Credit Scores for Firms That 
Received 504 Loans by Credit Score Range, 2003-2006: 

[See PDF for image] 

Source: GAO analysis of credit scores for borrowers receiving 504 loans 
in SBA portfolio (2003-2006). 

[End of figure] 

Figure 15: Percentage of 504 Loans by Loan Size, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA data. 

[End of figure] 

Figure 16: Percentage of 504 Loans in Distressed Neighborhoods, 2001- 
2004: 

[See PDF for image] 

Source: GAO analysis of SBA data. 

[End of figure] 

Figure 17: Percentage of 504 Loans by Number of Employees in the Firm, 
2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA data. 

[End of figure] 

Figure 18: Percentage of 504 Loans by Census Divisions, 2001-2004: 

[See PDF for image] 

Source: GAO analysis of SBA data; Art Explosion (map). 

[End of figure] 

Figure 19: Percentage of 504 Loans by Business Organization Type, 2001- 
2004: 

[See PDF for image] 

Source: GAO analysis of SBA data. 

[End of figure] 

[End of section] 

Appendix IV: Comments from the Small Business Administration: 

U.S. Small Business Administration: 
Washington, D.C. 24416: 

Jun 29 2007: 

Mr. Daniel Garcia-Diaz: 
Assistant Director: 
Financial Markets and Community Investment: 
Government Accountability Office: 
441 G Street, NW: 
Washington, DC 20548: 

Dear Mr. Garcia-Diaz: 

We appreciate the opportunity to provide comments in response to the 
GAO draft report entitled Small Business Administration. Additional 
Measures Needed to Assess 7(a) Loan Program's Performance (GAD-07-769). 

We note that the report contains one recommendation. GAO has 
recommended that SBA complete and expand its current work on 
evaluating; the 7(a) program's performance measures, and that as part 
of this effort, at a minimum, SBA should further utilize the loan 
performance information it already collects to better report how small 
businesses fare after they participate in the 7(a) program. We agree 
with the recommendation. 

We have the following comments regarding the section discussing Small 
Business Predictive Scores (SBPS) credit scores which begins on page 27 
of your draft report. 

SBA disagrees with the main thesis of this section which states that 
GAO's "analysis of information on the credit scores of small businesses 
that accessed credit without SBA assistance showed only limited 
differences in these credit scores and those of small firms that 
received 7(a) loans." GAO states that the differences between 10 point 
score bands were "no greater than 5 percentage points," and the average 
difference "was 1.7 percentage points." However, the higher score bands 
(less risk) consistently show a lower percentage for 7(a); while the 
lower score bands (greater risk) consistently show a higher percentage 
for 7(a). It is in the riskier bands where the differences in the two 
portfolios are exposed. All portfolios end up with the bulk of scores 
around the middle or higher bands; the riskiness of a portfolio is 
determined by the distribution in the lower (riskier) bands. While the 
numbers have not been worked out, if other things were held equal, a 
shift in the credit scores distribution of this amount would likely 
cause at least a 10% difference in the number of loans going into 
default or purchased over a 12-month period, and perhaps a 15% 
increase. Such a shift would not be insignificant. 

As GAO has stated, the results of its analysis should be interpreted 
with some caution, particularly since D&B and FIC have stated that the 
FIC development sample was not statistically representative of all 
small businesses. Additionally, the SBPS sample includes only those 
lenders who agreed to be in the development sample. There may be a 
common factor among these lenders, which does not make them 
representative of all outstanding loans, let alone all small 
businesses. For example, only those lenders that focused on particular 
types of business (or other factors) may have felt the need for the 
credit scoring product. Further, banks typically do not score very good 
credits at all, so normal comparisons of portfolios would miss these 
loans, thus lowering a lender's average SBPS development sample scores 
and making their contemporary portfolio look worse than it really is by 
leaving the good credits out. It is possible that this effect is 
prevalent in the development sample as well. 

Moreover, as GAO points out, the time periods of the two sets of credit 
scores are different. The FIC and D&B SBPS sample was from 1996 through 
2000, and the SBA 7(a) sample was from 2003 through 2006. So the two 
samples could have loans scored as far apart as a decade. Too much can 
change in a decade to make the scores comparable. The 7(a) credit 
scores are SBA's "surrogate origination scores" which are the first 
scores after a loan is made, about one to three months after it is 
disbursed. The SBPS development sample credit scores are different 
types of outstanding loans and at various stages of loan aging, from a 
month or two to almost 30 years (if commercial real estate) when they 
were scored for the sample. Combine this with a possible 10 year 
difference between scoring dates, and this makes it possible that one 
sample may have some loans that are almost 40 years older than all of 
the loans in the other sample. 

Finally, the 7(a) sample of small loans includes only small businesses 
which meet the SBA definition of a small business at the time of 
origination. Not only do businesses in the SBPS sample not have to meet 
the SBA definition of a small business, they do not have to be to small 
businesses at all. Some of the loans in the SBPS sample were likely 
made to businesses that may not have been small at the time of loan 
origination. 

We are attaching additional technical correction comments to this 
letter. 

Again, thank you for the opportunity to comment on this most important 
issue. 

Sincerely, 

Signed by: 

Janet Tasker: 
Deputy Associate Administrator: 
Office of Capital Access: 

[End of section] 

Appendix V: GAO Contact and Staff Acknowledgments: 

GAO Contact: 

William B. Shear (202) 512-8678 or [email protected]: 

Acknowledgments: 

In addition to the individual named above, Daniel Garcia-Diaz 
(Assistant Director), LaKeisha Allen, Benjamin Bolitzer, Christine 
Bonham, Tania Calhoun, Marcia Carlsen, Emily Chalmers, Elizabeth Curda, 
Julianne Dieterich, Carol Henn, Alison Martin, Jose Matos, Lisa Mirel, 
Marc Molino, Anita Visser, and Mijo Vodopic made contributions to this 
report. 

FOOTNOTES 

[1] Section 7(a)(18) of the Small Business Act. 

[2] Section 7(a)(23) of the Small Business Act. 

[3] As authorized by section 7(a)(23)(A) of the Small Business Act. 

[4] 2 U.S.C. ï¿½ 661c(f). 

[5] Permanent, indefinite budget authority is available as a result of 
previously enacted legislation (in this case, FCRA) and is available 
without further legislative action or until Congress affirmatively 
rescinds the authority. The amount of the budget authority is 
indefinite--that is, unspecified at the time of enactment--but becomes 
determinable at some future date (in this case, when reestimates are 
made). 

[6] GAO, 21ST Century Challenges: Reexamining the Base of Federal 
Government, GAO-05-352T (Washington, D.C.: Feb. 16, 2005). 

[7] Chairman's Statement, Sen. Tom Coburn, The Effectiveness of the 
Small Business Administration, April 6, 2006. 

[8] 504 projects consist of three sources of funds: (1) a loan backed 
by a 100-percent SBA-guaranteed debenture from a community development 
company limited to a maximum of 40 percent of the project, (2) a loan 
from a third party lender (usually a conventional lender), and (3) a 
contribution of at least 10 percent equity from the small business that 
is receiving the assistance. 

[9] The Board of Governors of the Federal Reserve System's (Federal 
Reserve) SSBF is the best available data on loans made to small firms 
in the conventional lending market. Information in the SSBF may include 
some loans that were guaranteed by the 7(a) loan program. 

[10] Office of Management and Budget, Federal Credit Supplement, Budget 
of the U.S. Government, Fiscal Year 2008 (Washington, D.C.: Feb. 5, 
2007). 

[11] Section 7(a) of the Small Business Act, as amended, codified at 15 
U.S.C. ï¿½ 636(a); see also 13 C.F.R. Part 120. Although SBA has limited 
legislative authority to make direct loans to borrowers unable to 
obtain loans from conventional lenders, SBA has not received any 
funding for these programs since fiscal year 1996. 

[12] To compare the number and amount of outstanding small business 
loans to 7(a) loans, we used SBA reports based on the Federal Deposit 
Insurance Corporation's (FDIC) Consolidated Reports of Condition and 
Income for U.S. Banks (call reports) and SBA data on outstanding 7(a) 
loans. In analyzing data from call reports, SBA defines a small 
business loan as a commercial and industrial loan for which the 
original amount was less than $1 million. 

[13] SBA has data available to make this comparison only for 2003, 
2004, and 2005. 

[14] Within the 7(a) program, there are several program delivery 
methods--regular 7(a), the certified lender program, the preferred 
lender program, SBAExpress, Community Express, Export Express, and 
Patriot Express. SBA provides final approval for loans made under the 
regular 7(a) program. Certified lenders must perform a thorough credit 
analysis on the loan application packages they submit to SBA so that 
SBA can rely on that analysis to allow it to perform a credit review 
only, thereby shortening the time for SBA loan processing. Preferred 
lenders have delegated authority to make SBA-guaranteed loans, subject 
only to a brief eligibility review and assignment of a loan number by 
SBA. Lenders participating in SBAExpress, Community Express, Export 
Express, and Patriot Express also have delegated authority to make SBA- 
guaranteed loans. 

[15] In establishing size standards, SBA considers economic 
characteristics comprising the structure of the industry, including 
degree of competition, average firm size, start-up costs and entry 
barriers, and distribution of firms by size. It also considers growth 
trends, competition from other industries, and other factors that may 
distinguish small firms from other firms. SBA's size standards seek to 
ensure that a firm that meets a specific size standard is not dominant 
in its field of operation. 

[16] Some earlier work includes GAO, Executive Guide: Effectively 
Implementing the Government Performance and Results Act, GAO/GGD-96-118 
(Washington, D.C.: June 1996) and GAO, The Results Act: An Evaluator's 
Guide to Assessing Agency Annual Performance Plans, GAO/GGD-10.1.20 
(Washington, D.C.: April 1998). 

[17] GAO, Tax Administration: IRS Needs to Further Refine Its Tax 
Filing Season Performance Measures, GAO-03-143 (Washington, D.C.: Nov. 
12, 2002). 

[18] GAO, Managing for Results: Opportunities for Continued 
Improvements in Agencies' Performance Plans, GAO/GGD/AIMD-99-215 
(Washington, D.C.: July 20, 1999). 

[19] Small Business Administration Inspector General, Results Act 
Performance Measurement for the 7(a) Business Loan Program, Report No. 
1-01 (Washington, D.C.: December 2000). 

[20] Small business credit scores are a range of numeric values derived 
using a mathematical model that takes into account information from 
consumer credit bureaus and business performance data from lenders. The 
scores attempt to predict the likelihood that a business will repay a 
loan. 

[21] 5 U.S.C. 306(b). 

[22] Appendix II identifies and provides information on the studies we 
reviewed, including their objectives, data, methodologies, limitations, 
and conclusions. 

[23] For more details on how economic theory predicts credit rationing, 
see J. E. Stiglitz and A. Weiss, "Credit Rationing in Markets with 
Imperfect Information," The American Economic Review, vol. 71, no. 3 
(1981). 

[24] However, under certain circumstances, economic reasoning suggests 
that lack of information about certain types of borrowers could result 
in the opposite--an excess of credit. See D. De Meza and D.C. Webb, 
"Too Much Investment: A Problem of Asymmetric Information," The 
Quarterly Journal of Economics, vol. 102, no. 2 (1987). 

[25] We also identified additional studies that examined evidence for 
credit rationing between lenders and borrowers, but these studies were 
all based on data from foreign countries. 

[26] S.J. Perez, "Testing for Credit Rationing: An Application of 
Disequilibrium Econometrics," Journal of Macroeconomics, vol. 20, no. 4 
(1998). 

[27] A.R. Levison and K.L. Willard, "Do Firms Get the Financing They 
Want? Measuring Credit Rationing Experienced by Small Businesses in the 
U.S.," Small Business Economics, vol. 14, no. 2 (2000) and A.N. Berger 
and G.F. Udell, "Some Evidence on the Empirical Significance of Credit 
Rationing," The Journal of Political Economy, vol. 100, no. 5 (1992). 

[28] Levinson and Willard, "Do Firms Get the Financing They Want? 
Measuring Credit Rationing Experienced by Small Businesses in the 
U.S.," 90. 

[29] Berger and Udell, "Some Evidence on the Empirical Significance of 
Credit Rationing," 1076. 

[30] J. Berkowitz and M.J. White, "Bankruptcy and Small Firms' Access 
to Credit," The RAND Journal of Economics, vol. 35, no. 1 (2004). 

[31] Levinson and Willard, "Do Firms Get the Financing They Want? 
Measuring Credit Rationing Experienced by Small Businesses in the 
U.S.," 90. 

[32] M.A. Petersen and R.G. Rajan, "The Benefits of Lending 
Relationships: Evidence from Small Business Data," The Journal of 
Finance, vol. 49, no. 1 (1994) and R. A. Cole, "The Importance of 
Relationships to the Availability of Credit," Journal of Banking and 
Finance, vol. 22 (1998). 

[33] A.N. Berger and G.F. Udell, "Relationship Lending and Lines of 
Credit in Small Firm Finance," The Journal of Business, vol. 68, no. 3 
(1995). 

[34] T.L. Mach, and J.D. Wolken, "Financial Services Used by Small 
Businesses: Evidence from the 2003 Survey of Small Business Finances," 
Federal Reserve Bulletin Oct.: A167-A195 (2006). 

[35] The survey question specifically asked respondents about having a 
credit line, loan, or capital lease. 

[36] K.S. Cavalluzzo and L.C. Cavalluzzo, "Market Structure and 
Discrimination: The Case of Small Businesses," Journal of Money, Credit 
and Banking, vol. 30, no. 4 (1998). 

[37] K.S. Cavalluzzo, L.C. Cavalluzzo, and J.D. Wolken, "Competition, 
Small Business Financing, and Discrimination: Evidence from a New 
Survey," Journal of Business, vol. 75, no. 4 (2002). 

[38] D.G. Blanchflower, P.B. Levine, and D.J. Zimmerman, 
"Discrimination in the Small-Business Credit Market," The Review of 
Economics and Statistics, vol. 85, no. 4 (2003). 

[39] SBA officials explained that the agency defines start-up 
businesses as businesses in operation for less than 2 years. To make 
the data on conventional loans from the SSBF comparable to the SBA 
data, we defined a business with a conventional loan as a start-up if 
the business had been in operation for less than 2 years when the firm 
applied for the most recently approved loan. 

[40] The confidence interval for the estimate of the share of 
conventional loans that went to small businesses in economically 
distressed neighborhoods (10 percent) is 7.9 to 11.7 percent. 

[41] The Empowerment Zone/Enterprise Community program (EZ/EC) and 
Renewal Community program (RC) target federal grant monies to public 
and private entities, tax benefits to businesses, or both in order to 
improve conditions in competitively selected, economically distressed 
communities. For an area to be eligible for these programs at least 20 
percent of the population in the census tracts that make up the area 
must have incomes below the national poverty line. 

[42] A Historically Underutilized Business Zone is an area located in 
one or more qualified census tracts, qualified nonmetropolitan 
counties, or lands within the external boundaries of an Indian 
reservation. 

[43] The maximum number of employees a business can have and still be 
considered small varies from industry to industry, but the most common 
standard is 500 employees. The confidence interval for the estimate of 
the share of conventional loans that went to small businesses with up 
to 5 employees (42 percent) is 38.0 to 45.2 percent, for businesses 
with 5 to 9 employees (24 percent) is 21.2 to 27.5 percent, and for 
businesses with 10 to 19 employees (17 percent) 14.0 to 19.7 percent. 

[44] The confidence interval for the estimate of the share of 
conventional loans that went to small businesses organized as 
corporations (60 percent) is 56.2 to 63.5 percent, and those organized 
as sole proprietorships (32 percent) is 28.2 to 35.3 percent. 

[45] The portfolio management score used by SBA is the Small Business 
Predictive Score (SBPS). The SBPS is based on consumer and business 
data, and assigns small businesses with scores in the absolute range of 
1 to 300, but the practical range of 50 to 250. A lower score generally 
indicates a greater likelihood of repayment risk, while a higher score 
indicates a greater likelihood that the loan will be repaid. 

[46] SBA says it first received SBPS credit scores for the outstanding 
7(a) loans in its portfolio in March 2003. Since then, SBA has received 
an initial score, known as the Surrogate Origination Score, for a 7(a) 
loan 1 to 4 months after the loan is disbursed. SBA subsequently has 
received SBPS scores on a quarterly basis for almost all of the active 
loans in its portfolio. We obtained data for all 7(a) loans approved 
and disbursed from 2001 through 2005, so the dates of the initial 
credit scores ranged from 2003 to 2006. 

[47] The earlier period of credit scores for firms that obtained credit 
in the conventional lending market represents data D&B/FIC had readily 
available and could provide us. Appendix I contains details on the data 
used to perform this analysis. 

[48] The FSS predicts the likelihood that a business will cease 
operations without paying creditors in full or go into receivership. 

[49] An estimated 3 percent of conventional loans had dollar amounts 
greater than $2 million. 

[50] We used SBA data to calculate the calendar year and quarter in 
which each loan was approved and to calculate interest rates for all 
loans in a given quarter that were for under $1 million. 

[51] We used the Federal Reserve's Survey of Terms of Business Lending, 
which provides information quarterly on commercial and industrial loans 
of loans in four size categories (less than $100,000; from $100,000 
through $999,999; from $1 million through $999,999,000; and $10 million 
or more) made only by commercial banks. We used only data related to 
the first two categories because those loan amounts most resembled the 
7(a) loans in the SBA data and, as discussed previously, SBA considers 
loans reported in call report data of $1 million or less to be for 
small businesses. 

[52] We used the Federal Reserve's historical reports on the monthly 
bank prime rate to estimate the prime rate for every quarter from 2001 
through 2004. 

[53] GAO, Small Business Administration: Model for 7(a) Program Subsidy 
Had Reasonable Equations, but Inadequate Documentation Hampered 
External Reviews, GAO-04-9 (Washington, D.C.: Mar. 31, 2004). 

[54] For example, we eliminated records where a loan maturity date 
preceded or equaled the disbursement date or records in which the SBA- 
guaranteed percentage exceeded the maximum level allowed by the 
program. 

[55] According to Financial Services Used by Small Businesses: Evidence 
From the 2003 Survey of Small Business Finances, about 1 percent of 
small businesses indicated that the government was the supplier of 
their financial services. Federal Reserve staff noted that this 
percentage may understate the incidence of 7(a) loans because, among 
other reasons, some respondents may have been unaware that they 
received an SBA-guaranteed loan. 

[56] The SSBF initially selected 37,600 firms from D&B's Dun's Market 
Identifier file, of which 9,687 passed to the main questionnaire stage, 
and 4,268 firms completed their interviews, resulting in a weighted 
overall response rate of 32.4 percent. These firms represent 6.3 
million small businesses. Firms eligible for the SSBF include for- 
profit, nonagricultural, nondepository institutions, nongovernment 
businesses in operation in December 2003 and during the interview, that 
also had less than 500 employees. 

[57] The Bureau of Census organizes the 50 states and District of 
Columbia into nine regions, as follows: (1) East North Central (Ohio, 
Indiana, Illinois, Michigan, and Wisconsin); (2) East South Central 
(Kentucky, Tennessee, Alabama, and Mississippi); (3) Middle Atlantic 
(New York, New Jersey, and Pennsylvania) (4) Mountain (Montana, Idaho, 
Wyoming, Colorado, New Mexico, Arizona, Utah, and Nevada); (5) New 
England (Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, 
and Connecticut); (6) Pacific (Washington, Oregon, California, Alaska, 
and Hawaii); (7) South Atlantic (Delaware, Maryland, District of 
Columbia, Virginia, West Virginia, North Carolina, South Carolina, 
Georgia, and Florida); (8) West North Central (Minnesota, Iowa, 
Missouri, North Dakota, South Dakota, Nebraska, and Kansas); and (9) 
West South Central (Arkansas, Louisiana, Oklahoma, and Texas). 

[58] The survey does not include information on loans under $1,000. 

[59] Gross loan extensions made during the first full business week in 
the middle month of each quarter by a sample of 348 commercial banks of 
all sizes. The sample data are used to estimate the terms of loans 
extended during that week at all insured commercial banks. The survey 
notes that the estimated terms of bank lending are not intended for use 
in measuring the terms of loans extended over the entire quarter or 
residing in the portfolios of those banks. 

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