Stereotypes and Willingness to Change Them: Testing Theories of Discrimination in South Africa

Employers often decide job assignments or wages after observing productivity signals from workers. Discrimination can occur because employers have stereotypes (priors) against a group of workers, or because they use signals differently depending on the worker’s group. This paper introduces an estimable Bayesian framework that allows us to recover both the priors and the updating behavior of evaluators who observe noisy signals from candidates. Using data from a quasi-experiment in South Africa I test for the precise form of racial discrimination. I find evidence of discrimination without overtly negative priors. Discrimination occurs because white evaluators use signals to update their priors about white candidates but not when evaluating black candidates. Blacks, on the other hand, use signals to update their priors about all candidates. The paper uses the estimated structural parameters to simulate how evaluators would choose among equally performing candidates as a tool to show the relative importance of stereotypes and updating behavior on discrimination.