Cooperation Dynamic in Repeated Games of Adverse Selection

We study a class of repeated games with Markovian private information and characterize optimal equilibria as players become arbitrarily patient. We show that seemingly non-cooperative action may occur in equilibrium and serve as signals of changes in private information. Players forgive such actions, and use the information they convey to adjust their continuation play. However, to forgive is not to forget: players keep track of the number of aggressions and enter into a punishment phase if that number becomes suspiciously high. Our model explains features of long-run relationships that are only barely understood, such as equilibrium defaults, unilateral price cuts, collusive price leadership, graduated sanctions, and restitutions. We also explore a model in which interactions are frequent and show how increasing the persistence of the process of types reduces informational fictions. Key words: Keywords: Repeated games, adverse selection, signaling, tacit collusion, price leadership, price cuts, equilibrium defaults, graduated sanctions.