Statistical Discrimination and the Rationalization of Stereotypes

Abstract

The theory of statistical discrimination is a dominant social scientific framework for understanding discrimination in labor markets. To date, the literature has treated this theory as a model that merely explains employer behavior. This article contends that the idea of statistical discrimination, rather than simply providing an explanation, can lead people to view social stereotyping as useful and acceptable and thus help rationalize and justify discriminatory decisions. A preregistered survey experiment with more than 2,000 participants who had managerial experience shows that exposure to statistical discrimination theory strengthened people’s belief in the accuracy of stereotypes, their acceptance of stereotyping, and the extent to which they engaged in gender discrimination in a hiring simulation. Reading a critical commentary on the theory mitigated these effects. These findings imply that theories of discrimination, and the language associated with them, can rationalize—or challenge the rationality of—stereotypes and discrimination and, as a result, shape the attitudes and actions of decision-makers in labor markets.