Information Design in Games: Certification Approach

Working Paper: CEPR ID: DP18282

Authors: Alex Smolin; Takuro Yamashita

Abstract: Several players participate in a game with a continuum of actions. A designer chooses an information structure - a joint distribution of a state and private signals - and evaluates it according to the expected designer's payoff in the induced Bayes Nash equilibrium. We show an information structure is designer-optimal whenever the equilibrium play it induces can also be induced in an auxiliary contracting problem. This finding gives rise to a tractable solution method, which we use to study two novel applications. In an investment game, an optimal structure fully informs a single investor while providing no information to others. This structure is robustly optimal, for any state distribution and number of investors. In a price competition game, an optimal structure is Gaussian and recommends prices linearly in the state. This structure is uniquely optimal.

Keywords: Bayesian persuasion; Information design; Certification approach; Large scale games; Selective informing; Gaussian signals

JEL Codes: C72; D83


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
information structure (L15)equilibrium actions of players (C72)
optimal information structure (D83)investment behavior (G11)
optimal information structure (D83)actions of uninformed investors (G41)
Gaussian information structure (C46)pricing strategies firms adopt (L11)
Gaussian information structure (C46)producer and consumer surplus (D11)

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