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

Statistical Disparities in Capital Markets
the firm applied. 274 In total, these three columns add 176 variables to the more parsimonious
specification reported in Column (2). 275 Nevertheless, the estimated disadvantage experienced by
African American-owned firms in obtaining credit remains large and statistically significant. The
estimate from each of the three additional columns indicates that African American-owned firms
are 24 percentage points more likely than nonminority male-owned firms to have their loan
application denied even after controlling for the multitude of factors we have taken into
consideration.
The results also indicate that Asians/Pacific Islanders had significantly higher denial rates than
nonminority males—12 percentage points. There is little evidence in the 1993 national data,
however, that denial rates for firms owned by Native Americans or Hispanics were significantly
different from the denial rates of firms owned by nonminorities; or that denial rates for firms
owned by nonminority women were significantly different from those for firms owned by
nonminority men. 276
In Table 6.9, we see results for the ENC division similar to those reported in Table 6.8 for the
nation as a whole. The table shows that the results of our loan denial model in the ENC are not
substantially different from the nationwide results reported in Table 6.8. The indicator variable
for the ENC division is negative and significant, indicating that denial rates, on average, are
lower in the ENC than in the nation as a whole, but its significance decreases as more control
variables are included in the model. None of interaction terms between race, ethnicity or gender
and the ENC division indicator are statistically significant. 277
274 Approximately four out of five (80.5%) of the firms who required a loan applied to a commercial bank. Overall,
seventeen different types of financial institutions were tabulated, although only the following accounted for more
than 1% of the (weighted) total: Finance Companies (4.9%); Savings Banks (2.5%); Savings & Loans (2.3%);
Leasing Companies (2.1%); and Credit Unions (2.0%).
275 One piece of information to which we did not have access in the 1993 NSSBF or the 1998 SSBF because of
confidentiality concerns was each firm’s credit rating. A working paper by Cavalluzzo, Cavalluzzo, and Wolken
(1999) was able to incorporate Dun & Bradstreet credit ratings for each firm because the authors’ connection to
the Federal Reserve Board enabled them to access the confidential firm identifiers. They added these credit
rating variables in a model comparable to that reported here and found the results insensitive to the inclusion.
The 2003 SSBF includes Dun & Bradstreet credit ratings for each firm. Below, we discuss the impact of
incorporating them into a model similar to that presented in Table 6.8 (see Tables 6.27 and 6.28).
276 It would be a mistake to interpret a lack of statistical significance (as opposed to substantive significance) in any
of the Tables in Chapter 6 as a lack of adverse disparity. While tests for statistical significance are very useful for
assessing whether chance can explain disparities that we observe, they do have important limitations. First, the
fact that a disparity is not statistically significant does not mean that it is due to chance. It merely means that we
cannot rule out chance. Second, there are circumstances under which tests for statistical significance are not
helpful for distinguishing disparities due to chance from disparities due to other reasons (e.g., discrimination). In
the particular statistical application presented in this chapter, the chance that a test for statistical significance will
incorrectly attribute to chance disparities that are due to discrimination becomes greater when relatively small
sample sizes are present for an affected group.
277 The number of Native Americans and Hispanics in the ENC sample was too small to yield statistical results.
NERA Economic Consulting 198