The State of Minority- and Women- Owned ... - Cleveland.com

Statistical Disparities in Capital Markets
provide a powerful test of the causal impact of race, ethnicity or gender on loan decisions. In an
unpublished paper, Cole (1998) uses the 1993 NSSBF and estimates models of loan denials
similar in nature to those discussed in this Study.
The present analysis takes advantage of the 1993 NSSBF data, the 1998 Survey of Small
Business Finances (SSBF) data, and the 2003 SSBF data. All three datasets have better
information on creditworthiness than did the earlier NSSBF data, and the 1993 and 1998 surveys
have a larger sample of minority-owned firms than did the earlier NSSBF data. These datasets
are also used to conduct an extensive set of specification checks designed to weigh the
possibility that our results are subject to alternative interpretations.
C. Empirical Framework and Description of the Data
1. Introduction
Disputes about discrimination typically originate in differences in the average outcomes for two
groups. To determine whether a difference in the loan denial rate for African American-owned
firms compared to nonminority-owned firms is consistent with discrimination, it is necessary to
compare African American- and nonminority-owned firms that have similar risks of default; that
is, the fraction of the African American firms’ loans that would be approved if they had the same
creditworthiness as the nonminority-owned firms. A standard approach to this problem is to
statistically control for firms’ characteristics relevant to the loan decision. If African Americanowned
firms with the same likelihood of default as nonminority-owned firms are less likely to be
approved, then it is appropriate to attribute such a difference to discrimination.
Following Munnell, et al. (1996) we estimated the following loan denial equation:
(1) Prob(Di = 1) = Φ(β0 + β1CWi + β2Xi + β3Ri),
where Di represents an indicator variable for loan denial for firm i (that is, 1 if the loan is denied
and 0 if accepted), CW represents measures of creditworthiness, X represents other firm
characteristics, R represents the race, ethnicity or gender of the firm’s ownership, and Φ is the
cumulative normal probability distribution. 259 This econometric model can be thought of as a
reduced form version of a structural model that incorporates firms’ demand for and financial
institutions’ supply of loan funds as a function of the interest rate and other factors. 260 Within the
259 Additional discussion of Probit regression appears in Chapter V, Section C.1.
260 Maddala and Trost (1994) describe two variants of such a model, one in which the interest rate is exogenous and
another in which the interest rate is endogenously determined, but is capped so that some firms’ loan
applications are approved and others are rejected. If the interest rate is exogenous, they show that a reduced form
model which controls for the loan amount, such as we report below, uniquely identifies supply-side differences
in the treatment of African American-owned firms. If the interest rate is endogenous, a reduced form approach
requires an assumption that the determinants of demand for nonminority and African American-owned firms are
identical, other things being equal. The main alternative empirical strategy is to estimate a structural supply and
demand model, in which proper identification generally is not feasible. Any characteristic of the borrower that
affects his/her expected rate of return on the investment will affect his/her ability to repay and should be taken
into consideration by the lender as well. For instance, in their structural model of mortgage decisions, Maddala
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