Efficiency in Games With Markovian Private Information
Author(s)
Escobar, Juan F.; Toikka, Juuso
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We study repeated Bayesian games with communication and observable actions in which the players' privately known payoffs evolve according to an irreducible Markov chain whose transitions are independent across players. Our main result implies that, generically, 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 1. As an intermediate step, we construct an approximately efficient dynamic mechanism for long finite horizons without assuming transferable utility.
Date issued
2013-09Department
Massachusetts Institute of Technology. Department of EconomicsJournal
Econometrica
Publisher
The Econometric Society
Citation
Escobar, Juan F., and Juuso Toikka. “Efficiency in Games With Markovian Private Information.” Econometrica 81.5 (2013): 1887–1934.
Version: Author's final manuscript
ISSN
0012-9682
1468-0262