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Information Design in Concave Games

Author

Listed:
  • Takuro Yamashita

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Alexey Smolin

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

We study information design in games with a continuum of actions such that the players' payoffs are concave in their own actions. A designer chooses an information structure–a joint distribution of a state and a private signal of each player. The information structure induces a Bayesian game and is evaluated according to the expected designer's payoff under the equilibrium play. We develop a method that facilitates the search for an optimal information structure, i.e., one that cannot be outperformed by any other information structure, however complex. We show an information structure is optimal whenever it induces the strategies that can be implemented by an incentive contract in a dual, principal-agent problem which aggregates marginal payoffs of the players in the original game. We use this result to establish the optimality of Gaussian information structures in settings with quadratic payoffs and a multivariate normally distributed state. We analyze the details of optimal structures in a differentiated Bertrand competition and in a prediction game.

Suggested Citation

  • Takuro Yamashita & Alexey Smolin, 2022. "Information Design in Concave Games," Working Papers hal-04963984, HAL.
    • Handle: RePEc:hal:wpaper:hal-04963984
    Note: View the original document on HAL open archive server: https://hal.science/hal-04963984v1
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    Cited by:

    1. Itai Arieli & Yakov Babichenko & Fedor Sandomirskiy, 2023. "Feasible Conditional Belief Distributions," Papers 2307.07672, arXiv.org, revised Nov 2024.
    2. Junjie Chen & Takuro Yamashita, 2025. "The Design of Monopoly Information Broker," Papers 2503.19539, arXiv.org.

    More about this item

    Keywords

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    JEL classification:

    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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