Identification and Estimation of Dynamic Games with Unknown Information Structure

Konan Hara, Yuki Ito and Paul Koh

Papers from arXiv.org

Abstract: We develop an empirical framework for analyzing dynamic games when the underlying information structure is unknown to the analyst. We introduce \textit{Markov correlated equilibrium}, a dynamic analog of Bayes correlated equilibrium, and show that its predictions coincide with the Markov perfect equilibrium predictions attainable when players observe richer signals than the analyst assumes. We provide tractable methods for informationally robust estimation, inference, and counterfactual analysis. We illustrate the framework with a dynamic entry game between Starbucks and Dunkin' in the US and study the role of informational assumptions.

Date: 2022-05, Revised 2025-10
New Economics Papers: this item is included in nep-ecm and nep-gth
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