Many claim that the designs of audit studies are not true between-subjects experiments because research subjects (e.g., employer or housing agent) are not assigned to treatment or control groups but are exposed to both treatment and control (see Chapter 7 for a discussion of issues in repeated-measures designs). Also, although the order of exposure for each subject is randomized so that it should balance out, the time lapse between exposures makes it possible for the difference to be unrelated to the concept of focus (i.e., discrimination). In the time between two visits to an establishment, for example, someone else other than a tester may take the job or apartment of interest.
In the housing market, newspaper advertisements are used as a sampling frame (National Research Council, 2002b), but they may not accurately represent the sample of houses that are available or affordable to members of disadvantaged racial groups. Newspaper advertisements can be limiting because the sampling frame is restricted to members of disadvantaged racial groups who respond to typical advertisements and are qualified for the advertised housing unit or job. This limited sample may lead to a very specific interpretation of discrimination. For example, members of the sample may not be aware of alternative search strategies or know of other available housing units or jobs of interest. The practical difficulties associated with any sampling frame other than newspaper advertisements (and the associated steps of training auditors and assigning characteristics to them) are difficult to overcome.
Inferential target: estimating an effect of discrimination. Researchers have also debated the validity of audit studies (see the discussion in Ross and Yinger, 2002). Heckman and colleagues criticize the calculation of measures of discrimination (Heckman, 1998; Heckman and Siegelman, 1993). They argue that an estimate of discrimination at a randomly selected firm (or in an advertisement) does not measure the impact of discrimination in a market. Rather, discrimination should be measured by looking at (1) the average difference in the treatment of disadvantaged racial groups and whites or (2) the actual experience of the average member of a disadvantaged racial group, as opposed to examining the average experience of members of disadvantaged racial groups in a random sample of firms (i.e., the focus should be on the average across the population of applicants rather than the population of firms). Both of these proposed approaches to measuring discrimination are valid, but each has limitations.
Researchers typically determine the incidence of discrimination by mea-