Statistical Discrimination and Affirmative Action in the Lab

Working Paper: CEPR ID: DP12915

Authors: Ahrash Dianat; Federico Echenique; Leeat Yariv

Abstract: We present results from laboratory experiments studying the impacts of affirmative action policies. We induce statistical discrimination in simple labor-market interactions between firms and workers. We then introduce affirmative-action policies that vary in the size and duration of a subsidy firms receive for hiring discriminated-against workers. These different affirmative-action policies have nearly the same effect and practically eliminate discriminatory hiring practices. However, once lifted, few positive effects remain and discrimination reverts to its initial levels. One exception is lengthy affirmative-action policies, which exhibit somewhat longer-lived effects. Stickiness of beliefs, which we elicit, helps explain the evolution of these outcomes.

Keywords: Statistical discrimination; Affirmative action; Experiments

JEL Codes: J71; D04; C91


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
affirmative action policies (J78)elimination of discriminatory hiring practices (J71)
subsidies provided (H20)willingness to hire purple workers (J79)
removal of affirmative action policies (J78)reversion to initial levels of discrimination (J78)
lengthy affirmative action policies (J78)longer-lasting effects (C41)
stickiness of beliefs about worker productivity (J29)reversion to discriminatory hiring patterns (J78)

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