Dynamic Matching and Evolving Reputations

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.