Bayesian Bigot? Statistical Discrimination, Stereotypes, and Employer Decision Making

Abstract

Much of the debate over the underlying causes of discrimination centers on the rationality of employer decision making. Economic models of statistical discrimination emphasize the cognitive utility of group estimates as a means of dealing with the problems of uncertainty. Sociological and social-psychological models, by contrast, question the accuracy of group-level attributions. Although mean differences may exist between groups on productivity-related characteristics, these differences are often inflated in their application, leading to much larger differences in individual evaluations than would be warranted by actual group-level trait distributions. In this study, the authors examine the nature of employer attitudes about black and white workers and the extent to which these views are calibrated against their direct experiences with workers from each group. They use data from fifty-five in-depth interviews with hiring managers to explore employers' group-level attributions and their direct observations to develop a model of attitude formation and employer learning.