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Identification and Estimation of Dynamic Games with Unknown Information Structure

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Listed:
  • Konan Hara

    (Michigan State University)

  • Yuki Ito

    (Indiana University Bloomington)

  • Paul S. Koh

    (Yonsei University)

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.

Suggested Citation

  • Konan Hara & Yuki Ito & Paul S. Koh, 2025. "Identification and Estimation of Dynamic Games with Unknown Information Structure," Working papers 2025rwp-267, Yonsei University, Yonsei Economics Research Institute.
    • Handle: RePEc:yon:wpaper:2025rwp-267
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    References listed on IDEAS

    as
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