Efficiency in Games with Markovian Private Information

By Juan F. Escobar, Juuso Toikka. 2013

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We study repeated Bayesian n-player games in which the players' privately known types evolve according an irreducible Markov chain. Our main result shows that, with communication, any Pareto-efficient payoff vector above a stationary minmax value can be approximated arbitrarily closely in a perfect Bayesian equilibrium as the discount factor goes to one. As an intermediate step we construct a dynamic mechanism (without transfers) which is approximately efficient for patient players given a sufficiently long time horizon.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/e11f5f1b78409cdc22a635133cbf821b7a1245a4