1. Credit Scores and Credit Market Outcomes: Evidence from the SSBF and KFS
Rebel A. Cole
DePaul University
For presentation at the
U.S. Small Business Administration
November 4, 2014

2. Credit Scores and Credit Market Outcomes
Summary:
This study uses data from the Fed’s 2003 Survey of Small Business Finance and from the 2007 Kauffman Firm Surveys to analyze whether credit ratings affect the availability of credit to minority-owned firms.
I break the credit allocation process down to three steps:
Who needs credit?
Who applies for credit?
Who gets credit?
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

3. Summary: Who needs credit?
There are three groups of firms that need credit:
Firms that apply for credit.
Firms that apply for and are granted credit.
Firms that apply for and are denied credit.
Firms that need credit but do not apply.
Who doesn’t need credit?
All other firms.
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

4. Summary: Why is this study important?
Contributes to the literature on credit scoring: provides the first rigorous test of how small-business credit scores differ across four types of firms: no-need borrowers, discouraged borrowers, denied borrowers and successful borrowers; and how credit scores affect the credit-market outcomes of these firms.
Adds to the literature on disparate outcomes in the small-business credit markets. Provides new evidence regarding how small-business credit scores affect the availability of credit to small and minority-owned firms.
Contribute to the literature on the availability of credit to small businesses and relationship lending. Documents how credit scores affect the availability of credit to small businesses, including whether credit scores reduce the importance of relationship lending.
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

5. Summary: Key Findings
Analyses of data from both surveys show that firms with lower business credit scores are:
(i) more likely to need additional credit because their credit needs have not already been met by past borrowings;
(ii) more likely to be discouraged from applying for credit when they report a need for additional credit; and
(iii) more likely to be denied credit when they need additional credit and apply for credit

6. Summary: Key Findings
However, when the analyses include a comprehensive set of control variables for firm characteristics, owner characteristics, and firm-lender relationships (SSBF data only), results indicate that business credit scores have no incremental explanatory power over that of the control variables, with the notable exceptions of denial of SSBF firms and discouragement of KFS firms.

7. Summary: Key Findings
The analyses find no evidence that business credit scores have a disproportionately adverse effect on the availability of credit either to
(i) female-owned firms relative to male-owned firms or
(ii) to minority-owned firms relative to non-Hispanic white-owned firms.
Nor is there any evidence from the SSBF data that business credit scores reduce the importance of firm-lender relationships.

8. Summary: Key Findings
The analyses do find that minority-owned firms are disproportionately denied credit when they need and apply for additional credit.
This is strong evidence consistent with taste-based discrimination in the small-business loan market.

9. Introduction
Among small businesses, who needs credit and who gets credit?
Do credit ratings affect who gets credit, especially among minority-owned firms?
These questions are of great importance not only to the small firms themselves, but also to prospective lenders to these firms and to policymakers interested in the financial health of these firms.

10. Introduction
The availability of credit is one of the most fundamental issues facing a small business and therefore, has received much attention in the academic literature (See, for example, Petersen and Rajan, 1994, 1997; Berger and Udell, 1995, 2006; Cole, 1998, 2008, 2009; Cole, Goldberg and White, 2004; and hundreds more).
However, many small firms—as many as one in four, according to data from the 2003 Survey of Small Business Finances—indicate that they do not need any additional credit. We refer to these firms as “no-need” firms.
These firms have received little attention from academic researchers.

11. Introduction
In this study, we first analyze firms that do and do not need additional credit.
We then analyze whether firms that do need credit apply for credit or are discouraged from applying because they fear rejection.
Finally, we analyze whether firms that apply for credit are successful or unsuccessful in obtaining credit.
We utilize data from the FRB’s 2003 SSBFs and the 2010 KFS to estimate set of three equations, where the manager of a firm (i) decides if the firm needs additional credit; (ii) decides whether or not to apply from credit; and (iii) then learns from its prospective lender whether or not the firm gets credit.

12. Data We extract data from the FRB’s 2003 SSBF: Last of Four surveys:
Cross sections as of 1988, 1993, 1998, 2003
Broadly representative of 5 million privately held firms with fewer than 500 employees.
Stratified random samples
Oversample large and minority-owned firms.
Also stratify by census region
Cannot use results from unweighted descriptive statistics or from OLS to make inferences about the population

13. Data
We also extract data from the 2010 iteration of the Kauffman Firm Surveys:
Seventh of Eight Longitudinal surveys:
Very similar to SSBF, but for different population: Start-up firms established during 2004.
Like SSBFS, stratified random samples
Oversamples tech firms, among others.
Again, cannot use results from unweighted descriptive statistics or from OLS to make inferences about the population.

14. Methodology: Classification of Firms
First, we classify firms into one of four categories of “borrower” types based upon their responses to three questions about their “most recent loan requests” during the previous three years:
Did they apply?
Were they approved or rejected?
Did they need credit, but not apply because they feared rejection?

15. Methodology: Three-Step Selection Process
(1)
Need Credit?
(2)
Apply for Credit?
(3)
Get Credit? No
Yes
Non-Borrower
Discouraged Borrower
Unsuccessful Borrower
Successful Borrower

16. Explanatory Variables:
To select our explanatory variables, we rely primarily upon the existing literature on the availability of credit, as this may be the most vexing issue facing small firms.
These variables are motivated by and used in Cole (1998), Cole, Goldberg and White (2004), and/or Cole (2009).
We group these variables into four vectors:
Firm Characteristics
Market Characteristics
Owner Characteristics
Firm-Creditor Relationship Characteristics

17. Explanatory Variables: Firm Characteristics
Size (Sales, Assets, Employment)
Age
Organizational form (C-Corp, S-Corp, Partnership, Proprietorship)
Creditworthiness (Firm Delinquent Obligations, Firm Bankruptcy, Firm Judgments, D&B Credit Score, Paid Late on Trade Credit)
Financial performance and condition (profitability, leverage, liquidity)

18. Explanatory Variables: Market Characteristics
Very limited information on firm location because of confidentiality concerns. Can only use what is available from the SSBFs.
Banking concentration
Categorical representation with three levels, which we convert into dummy variables for low, medium and high concentration
Urban/Rural Location of the Firm
Binary indicator variable

19. Explanatory Variables: Owner Characteristics
Age
Experience
Education (Grad, College, Some College, High School)
Personal Wealth
Personal Creditworthiness (Delinquent Obligations, Judgments, Bankruptcy)
Race and Ethnicity (Asian, Black, Hispanic)

20. Explanatory Variables: Firm-Creditor Relationship Characteristics
Type of Primary Financial Institution (Commercial Bank, Savings Association, Finance Company, or “Other”)
Distance from firm HQ to Primary FI.
Length of Relationship with Primary FI.
Total Number of FIs (also split by number of Commercial Banks and number of Non-Bank FIs.

21. Methodology: Univariate and Multivariate Test
Once we have classified each firm, we calculate univariate statistics for each group and test for significant differences in means across groups.
We then run a sequence of three logistic regression models to explain each step of the credit approval process:
1. Need credit? (Yes or No?)
2. Apply for credit? (Applied or Discouraged?)
3. Get credit? (Approved or Denied?)

22. Credit Scores and Credit Market Outcomes
Distribution of D&B Credit Scores: 2003 Survey of Small Business Finances
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

23. Distribution of D&B Credit Scores: 2010 Kauffman Firm Survey
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

24. Distribution of Credit Market Outcomes: 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

25. Distribution of D&B Credit Scores: By Minority Status 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

26. Distribution of D&B Credit Scores: By Gender 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

27. Distribution of D&B Credit Scores: By Credit Market Outcome 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

28. Distribution of Credit Market Outcomes: 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

29. Distribution of Credit Market Outcomes: 2010 KFS
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

30. Distribution of Credit Scores: By Industry 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

31. Distribution of Credit Scores: By Firm Age 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

32. Distribution of Credit Scores: By Firm Age 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

33. Distribution of Credit Scores: By Minority Status 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

34. Distribution of Credit Scores: By Industry 2010 KFS
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

35. Need Credit vs. No-Need Firms 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

36. Need Credit vs. No-Need Firms 2010 KFS
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

37. Discouraged vs. Applied Firms 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

38. Discouraged vs. Applied Firms 2010 KFS
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

39. Denied vs. Approved Firms 2003 SSBF
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

40. Denied vs. Approved Firms 2010 KFS
Rebel A. Cole:
Credit Scores and Credit Market Outcomes

41. Summary and Conclusions:
In this study, we use data from the 2003 SSBF and the 2007 KFS to examine how credit ratings affect the availability of credit to small and minority-owned privately held U.S. firms.
We make at least three important contributions to the literature.

42. Summary and Conclusions
Contributes to the literature on credit scoring: provides the first rigorous test of how small-business credit scores differ across four types of firms: no-need borrowers, discouraged borrowers, denied borrowers and successful borrowers; and how credit scores affect the credit-market outcomes of these firms.
Adds to the literature on disparate outcomes in the small-business credit markets. Provides new evidence regarding how small-business credit scores affect the availability of credit to small and minority-owned firms.
Contribute to the literature on the availability of credit to small businesses and relationship lending. Documents how credit scores affect the availability of credit to small businesses, including whether credit scores reduce the importance of relationship lending.

43. Summary and Conclusions
Analysis of both the SSBF data and the KFS also shows that business credit scores are important at all three steps of the model.
Firms with worse business credit scores are:
(i) more likely to need additional credit because their credit needs have not been met by past borrowings;
(ii) more likely to be discouraged from applying for credit when they report a need for additional credit; and
(iii) more likely to be denied credit when they need additional credit and apply for credit.

44. Summary and Conclusions
However, the significance of the business credit score in these models disappears when a comprehensive set of control variables for firm characteristics, owner characteristics, and firm lender relationships is included,
With the notable exception of KFS discouragement
This is unremarkable because Dun & Bradstreet is likely to utilize these same or similar control variables in calculating the business credit scores that are tested in this study.

45. Summary and Conclusions
Moreover, there is no evidence in this analysis that business credit scores have a disproportionately adverse effect on the availability of credit either to
(i) female-owned firms relative to male-owned firms or
(ii) to minority-owned firms relative to white-owned firms.
Nor is there any evidence that credit scores reduce the importance of firm-lender relationships.