Dynamic Matching and Evolving Reputations

Abstract

This paper introduces a general model of matching that includes evolving public Bayesian reputations and stochastic production. Despite productive complementarity, assortative matching robustly fails for high discount factors, unlike in Becker (1973) . This failure holds around the highest (lowest) reputation agents for “high skill” (“low skill”) technologies. We find that matches of likes eventually dissolve. In another life-cycle finding, young workers are paid less than their marginal product, and old workers more. Also, wages rise with tenure but need not reflect marginal products: information rents produce non-monotone and discontinuous wage profiles.