The Cook Center aims to design effective procedures for preventing or mitigating the effects of employment discrimination.

The longstanding racial inequities of American society are reflected in the job market: For decades, the unemployment rate for black Americans has long hovered at twice that of whites, and at every level of educational attainment, blacks are more likely than whites to be unemployed. More extreme examples—like the fact that black men with no criminal records face lower odds of a callback for a job than do white men with a criminal record—only heighten one’s understanding of the disparities in play.

But for myriad reasons, discrimination in employment proves difficult to accurately measure. Self-reports of discrimination are subject to respondent self-censorship, cognitive dissonance or error; systematic comparisons have shown blacks to substantially underreport their exposure to discrimination in employment while whites substantially overreport. Furthermore, group distinctions based exclusively on self-reports of race or ethnicity complicate these calculations. For example, Latinos, regardless of skin shade, report their race as white at high rates and rarely report their race as black, which leads to inaccurate estimates of the magnitude of discrimination. Therefore, data sets that enable researchers to make distinctions based upon skin shade will prove more useful in locating evidence of discrimination than data sets reliant solely on self-reported race.

The Cook Center researchers will aim to first understand how historical methods—the self-report, statistical decomposition, and field experiment—perform at a common set of geographical locations, in order to assess the consistency of measurement of discrimination generated by each. From there, these researchers will develop a context-specific protocol for detection of discrimination in employment. Additionally, they will design a way to measure the magnitude of discrimination directed against people with multiple stigmatized identities—in short, determining whether possessing multiple identities has an adverse effect on earnings and employment outcomes.