Measuring Disparity in Government Procurement: Problems with Using Census Data in Estimating Availability

Introduction Public procurement is a multibillion-dollar business for vendors who provide a large variety of products and services to federal, state, and local governmental agencies. Thus, there are very large potential dollar benefits to firms that can qualify for minority and women procurement assistance programs. The goals set for awarding procurement contracts to minority and women firms in these types of programs are often quite substantial. Moreover, the use of minority and women procurement assistance programs has become widespread in most governmental agencies, and it is not unusual for a geographic area to have more than one of these programs. For example, a city, county, and school board in the same region often have separate programs with separate goals for using minority and women vendors in procurement. Many governmental agencies use procurement assistance programs for minority- and women-owned businesses on the premise that their procurement processes have subjected these firms to race/gender discrimination. In City of Richmond v. J.A. Croson (488 U.S. 469; 109 S.Ct. 706; 102L.Ed. 2d 854 [1989]), the United States Supreme Court established guidelines for determining the constitutionality of race/gender procurement assistance programs by state and local governments. The guidelines specify that a "strict scrutiny" standard must be applied in compiling evidence to show that discrimination exists in specific situations in order to justify their programs. Furthermore, the agencies must ensure that the programs are "narrowly tailored" to address the specific discrimination that is identified by the evidence. While Croson established the standards of strict scrutiny and narrow tailoring as they relate to state and local governments, the U.S. Supreme Court extended these two standards to federal minority procurement assistance programs in its ruling in Adarand Constructors v. Pena (515 U.S. 200 [1995]). The Croson guidelines also specify how statistical evidence is to be used to support an initial inference of disparity against race/gender groups by public administrators responsible for awarding procurement contracts. "Where there is a significant statistical disparity between the number of qualified minority contractors willing and able to perform a particular service and the number of such contractors actually engaged by the locality or the locality's prime contractors, an inference of discriminatory exclusion could arise." (City of Richmond v. J.A. Croson, 504). The application of the Croson guidelines to analyze government procurement is referred to as a disparity study. These guidelines require a state or local government agency implementing a race/gender procurement assistance program to first conduct a disparity study to document evidence of discrimination before the program is implemented. This requirement has spawned a new industry of consulting firms devoted to conducting disparity studies (Munk 1994, 50). The general methodology for conducting a disparity study has been documented in the literature (La Noue 1994a, 93-133; La Noue 1994b, 485-540; La Noue and Sullivan 1995, 348-55; Rice 1992, 482-90). As shown in Figure 1, there are two principal steps in the methodology used in essentially all disparity studies. First, statistical tests are performed to determine if the utilization proportions differ significantly from the availability proportions for each race/gender group. Disparity ratios and t-statistics have been commonly used in prior disparity studies. A disparity ratio is defined as the ratio of proportional utilization to proportional availability, with a ratio less than 1.00 indicating underutilization and a ratio less than 0.80 indicating statistical support for an inference of discriminatory exclusion (Paetzold and Willborn 1994). If an inference of discriminatory exclusion (disparity) is supported, the second step analyzes additional evidence including anecdotal data to determine if the cause of any discovered disparity is in fact due to race/gender discrimination. …