Categorization and coordination

This paper considers the use of categories to make predictions. It presents a framework to examine when decision makers may be better off using fewer rather than more categories, even without exogenous costs of using more. We study three cases: individual prediction, coordination of predictions, and the convex combination of the two. The analysis focuses on how the attempt to coordinate predictions with others affects incentives for coarse categorization in different environments. We show that while a coordination motive does not provide incentives for coarse categorization in deterministic environments, it could provide such incentives in stochastic environments.