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

M/WBE Availability in the City of Cleveland’s Market Area
business was counted as nonminority male-owned for purposes of the M/WBE availability
calculation. If it indicated it was nonminority female-owned, it was counted as nonminority
female, and so on. For unclassified businesses that were not interviewed, we assigned probability
values (probability actually nonminority male-owned, probability actually nonminority femaleowned,
probability actually African American-owned, etc.) based on the interview responses.
We again carried out the probability assignment procedure within each stratum.
5. Understanding “Capacity”
As noted in the beginning of this chapter, some observers, primarily opponents of efforts to
address discrimination in contracting, have argued that, in order to be accurate, availability
estimates must be adjusted for “capacity.” These assertions are rarely accompanied by specific
suggestions about how such adjustments could be made consistent with professional social
science standards. This Study does adjust for certain appropriate characteristics of firms related
to capacity (such as industry affiliation, geographic location, owner labor market experience, and
educational attainment); however, we are careful to not adjust for capacity factors that are
themselves likely to be influenced by discrimination. In our view, all of the “capacity” indicators
recommended by program opponents (e.g., firm age, annual individual firm revenues, number of
employees, largest contract received, bonding limits) are subject to the impact of discrimination.
Further, the reality is that large, adverse statistical disparities between minority-owned or
women-owned businesses and nonminority male-owned businesses have been documented in
numerous research studies and reports since Croson. 223 Business outcomes, however, can be
influenced by multiple factors, and it is important that disparity studies examine the likelihood of
whether discrimination is an important contributing factor to observed disparities.
Moreover, terms such as “capacity,” “qualifications,” and “ability,” are not well defined in any
statistical sense. Does “capacity” mean the level of annual individual firm revenues, employment
size, bonding limits, or number of contracts bid or awarded? Does “qualified” or “able” mean
possession of a business license, certain amounts of training, types of work experience, or the
number of contracts a firm can perform at a given moment? What mix of business attributes
properly reflects “capacity”? Does the meaning of such terms differ from industry to industry,
locality to locality, or through time? Where and how might such data be reliably gathered? Even
if capacity is well-defined and adequate data are gathered, when measuring the existence of
discrimination, the statistical method used should not improperly limit the availability measure
by incorporating factors that are themselves impacted by discrimination, such as firm age, annual
individual firm revenues, bonding limits, or numbers of employees.
Consider an extreme example where discrimination has prevented the emergence of any minority
owned firms. Suppose that racial discrimination was ingrained in a state’s construction market.
As a result, few minority construction employees are given the opportunity to gain managerial
experience in the business; minorities who do end up starting construction firms are denied the
opportunity to work as subcontractors for nonminority prime contractors; and nonminority prime
contractors place pressure on unions not to work with minority firms and on bonding companies
223 See Enchautegui, et al. (1996).
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