Efficiency in Games with Markovian Private Information

Juan Escobar and Juuso Toikka ()

No 289, Documentos de Trabajo from Centro de Economía Aplicada, Universidad de Chile

Abstract: 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.

Date: 2012
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Journal Article: Efficiency in Games With Markovian Private Information (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:edj:ceauch:289

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