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

Market-Based Disparities in Business Formation and Business Owner Earnings
earnings among individuals in similar geographic and product markets at similar points in time
and with similar years of education and potential labor market experience and see if any adverse
race or gender differences remain. In a discrimination free market area, one would not expect to
observe significant differences in earnings by race or gender among such similarly situated
observations.
Regression also allows us to narrowly tailor our statistical tests to the City of Cleveland’s
relevant geographic market, and assess whether disparities in that market are statistically
significantly different from those observed elsewhere in the nation. Starting from an economywide
data set, we first estimated the basic model of earnings differences just described and also
included an indicator variable for the City of Cleveland Market Area (CLEVMA), which is
comprised of the Cleveland-Elyria-Mentor, OH Metropolitan Statistical Area (MSA) and the
Akron, OH MSA. This variable estimates the differential effect of location in the CLEVMA
relevant to the rest of the country. This model appears as Specification 1 in Tables 5.1 through
5.6. Next, we estimated Specification 2, which is the same model as Specification 1 but with the
addition of indicator variables that interact race and gender with the CLEVMA indicator. These
variables estimate the differential effect of location in the CLEVMA and membership in the
given race or gender group. Specification 3 represents our ultimate specification, which includes
all the variables from the basic model as well as any of the interaction terms from Specification 2
that were statistically significant. 235
Any negative and statistically significant differences by race or gender that remain in
Specification 3 after holding all of these other factors constant—time, age, education, geography,
and industry—are consistent with what would be observed in a market suffering from businessrelated
discrimination. 236
2. Data
The analyses undertaken in this Study require individual-level data (i.e., “microdata”) with
relevant information on business ownership status and other key socioeconomic characteristics.
The data source used is the American Community Survey (ACS) Public Use Microdata Sample
(PUMS) for 2006–2010. The Census Bureau’s ACS is an ongoing survey covering the same type
of information collected in the decennial census. The ACS is sent to approximately 3 million
addresses annually, including housing units in all counties in the 50 states and the District of
Columbia. The PUMS file from the ACS contains records for a subsample of the full ACS. The
data used here are the multi-year estimates combining the 2006 through 2010 ACS PUMS
records. The combined file contains over six million person-level records. Released in early
2012, the ACS PUMS provides the full range of population and housing information collected in
the annual ACS and in the decennial census. Business ownership status is identified in the ACS
235 If none of these terms is significant then Specification 3 reduces to Specification 1.
236 Typically, a given test statistic is considered to be statistically significant if there is a reasonably low probability
that the value of the statistic is due to random chance alone. Unless otherwise indicated, in this and subsequent
chapters, we employ three levels of statistical significance, corresponding to 10 percent, 5 percent, and 1 percent
probabilities that results were the result of random chance.
NERA Economic Consulting 152