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Uncertain Repeated Games
Abstract: Multiple long run players play one amongst multiple possible stage games in each period. They observe and recall past play and are aware of the current stage game being played, but are uncertain about the future evolution of stage games. This setup is termed an uncertain repeated game. The solution concept requires that a subgame perfect equilibrium be played no matter what sequence of stage games realize. The feasible set of payoffs is then so large and complex that it is not obvious how to frame standard results such as the folk theorem, and further how to construct credible rewards and punishments that work irrespective of the future evolution of games. The main goal of the paper is to build such a language through two different perspectives— one in which the modeler has access to the true stochastic process but not the players and another in which there is simply maximal uncertainty; and then to construct credible dynamic incentives that work generally for uncertain repeated games. A complete characterization of equilibria is presented for large discount factors and various extensions to related models and results are discussed.
Bio: Rohit Lamba is an assistant professor of economics at Cornell University. You can find more about him at rohitlamba.com