Identification and Estimation of Dynamic Games with Unknown Information Structure

Konan Hara, Yuki Ito and Paul S. Koh
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Konan Hara: Michigan State University
Yuki Ito: Indiana University Bloomington
Paul S. Koh: Yonsei University

No 2025rwp-267, Working papers from Yonsei University, Yonsei Economics Research Institute

Abstract: We develop an empirical framework for analyzing dynamic games when the underlying information structure is unknown to the analyst. We introduce 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.

Keywords: Dynamic games; Markov; correlated equilibrium; information; partial identification (search for similar items in EconPapers)
Pages: 58pages
Date: 2025-10
New Economics Papers: this item is included in nep-ecm, nep-gth and nep-mic
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