Stationary Bayesian–Markov Equilibria in Bayesian Stochastic Games with Periodic Revelation

Eunmi Ko ()
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Eunmi Ko: Department of Economics, Rochester Institute of Technology, 92 Lomb Memorial Dr, Rochester, NY 14623, USA

Games, 2024, vol. 15, issue 5, 1-17

Abstract: I consider a class of dynamic Bayesian games in which types evolve stochastically according to a first-order Markov process on a continuous type space. Types are privately informed, but they become public together with actions when payoffs are obtained, resulting in a delayed information revelation. In this environment, I show that there exists a stationary Bayesian–Markov equilibrium in which a player’s strategy maps a tuple of the previous type and action profiles and the player’s current type to a mixed action. The existence can be extended to K -periodic revelation. I also offer a computational algorithm to find an equilibrium.

Keywords: Bayesian game; stochastic game; existence; stationary Markov equilibrium; periodic revelation (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2024
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