Statistical discrimination without knowing statistics: blame social interactions?

We consider a model where decision makers repeatedly receive candidates and assign to them a binary decision that we can interpret as hire/not hire. The decision makers base their decision on the characteristics of the candidate but they are also sensitive to the social influence exerted by the observed hiring decisions of other employers. We characterize the long run frequency of decisions in the model, and show in particular that for candidates belonging to a group with “unfavorable” characteristics, the dynamics increase the rejection rate compared to a scenario with independent decisions, suggesting that social influence between decision makers can generate effects very similar to those that result from statistical discrimination. We then analyze how the existence and magnitude of a reinforcement in rejection rates depends on different properties of the distribution of characteristics in the candidate population.