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

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Market-Based Disparities in Business Formation <strong>and</strong> Business Owner Earnings<br />

prevents minorities <strong>and</strong> women from acquiring the financial credit <strong>and</strong> capital that are so <strong>of</strong>ten<br />

prerequisites to starting or exp<strong>and</strong>ing a business. Other things being equal, these phenomena<br />

would lead minority <strong>and</strong> female business formation rates to be lower than otherwise would be<br />

expected.<br />

Further, discrimination by <strong>com</strong>mercial customers <strong>and</strong> suppliers against M/WBEs, symptoms <strong>of</strong><br />

which are evidenced in Section B.4 above <strong>and</strong> elsewhere, operates to increase input prices <strong>and</strong><br />

lower output prices for M/WBEs. This discrimination leads to higher rates <strong>of</strong> failure for some<br />

minority- <strong>and</strong> women-owned firms, lower rates <strong>of</strong> pr<strong>of</strong>itability <strong>and</strong> growth for others, <strong>and</strong><br />

prevents some minorities <strong>and</strong> women from ever starting businesses at all. 242 All <strong>of</strong> these<br />

phenomena, other things equal, would contribute directly to relatively lower observed rates <strong>of</strong><br />

minority <strong>and</strong> female self-employment.<br />

1. Methods <strong>and</strong> Data<br />

To see if minorities or nonminority women are as likely to be business owners as are <strong>com</strong>parable<br />

nonminority males, we use a statistical technique known as Probit regression. Probit regression is<br />

used to determine the relationship between a categorical variable—one that can be characterized<br />

in terms <strong>of</strong> a “yes” or a “no” response as opposed to a continuous number—<strong>and</strong> a set <strong>of</strong><br />

characteristics that are related to the out<strong>com</strong>e <strong>of</strong> the categorical variable. Probit regression<br />

produces estimates <strong>of</strong> the extent to which each characteristic is positively or negatively related to<br />

the likelihood that the categorical variable will be a yes or no. For example, Probit regression is<br />

used by statisticians to estimate the likelihood that an individual participates in the labor force,<br />

retires this year, or contracts a particular disease—these are all variables that can be categorized<br />

by a response <strong>of</strong> “yes” (for example, she is in the labor force) or “no” (for example, she is not in<br />

the labor force)—<strong>and</strong> the extent to which certain factors are positively or negatively related to<br />

the likelihood (for example, the more education she has, the more likely that she is in the labor<br />

force). Probit regression is one <strong>of</strong> several techniques that can be used to examine qualitative<br />

out<strong>com</strong>es. Generally, other techniques such as Logit regression yield similar results. 243 In the<br />

present case, Probit regression is used to examine the relationship between the choice to own a<br />

business (yes or no) <strong>and</strong> the other demographic <strong>and</strong> socioeconomic characteristics in our basic<br />

model. <strong>The</strong> underlying data for this section is once again the 2006–2010 ACS PUMS.<br />

2. Findings: Race <strong>and</strong> Gender Disparities in Business Formation<br />

As a point <strong>of</strong> reference for what follows, Tables 5.7 <strong>and</strong> 5.8 provide a summary <strong>of</strong> business<br />

ownership rates in 2006–2010 by race <strong>and</strong> gender. A striking feature <strong>of</strong> both tables is how much<br />

higher, in general, business ownership rates are for nonminority males than for other groups.<br />

Table 5.7, for example, shows a 6.79 percentage point difference between the overall selfemployment<br />

rate <strong>of</strong> African Americans <strong>and</strong> nonminority males in the CLEVMA (11.18 – 4.39 =<br />

10.78). As shown in the rightmost column, this 6.79 percentage point gap translates into an<br />

242 See also the materials cited at fn. 227 supra.<br />

243 For a detailed discussion, see G.S. Maddala (1983). Probit analysis is performed here using the “dprobit”<br />

<strong>com</strong>m<strong>and</strong> in the statistical program STATA.<br />

NERA Economic Consulting 164

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