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Bayesian persuasion with optimal learning

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  • Liao, Xiaoye

Abstract

We study a model of Bayesian persuasion between a designer and a receiver with one substantial deviation from the standard setup—the designer offers once and for all a single statistical experiment from which the receiver can acquire costly i.i.d. signals over time. Taking a 2-state-2-action environment and employing a tractable continuous-time framework, we fully characterize the optimal persuasion policy. When the receiver features high skepticism, the optimal policy is to immediately reveal the truth, which is true for a large set of primitives. We construct the designer’s maximum payoff and find a discontinuous drop in it as compared with the standard model. Unlike in many standard persuasion models, the designer is not able to appropriate all the rents of information disclosure while the receiver often achieves the highest possible benefit from being able to repeatedly sample from the strategically offered information structure.

Suggested Citation

  • Liao, Xiaoye, 2021. "Bayesian persuasion with optimal learning," Journal of Mathematical Economics, Elsevier, vol. 97(C).
  • Handle: RePEc:eee:mateco:v:97:y:2021:i:c:s0304406821000975
    DOI: 10.1016/j.jmateco.2021.102534
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    References listed on IDEAS

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    1. Emeric Henry & Gianmarco Ottaviano, 2019. "Research and the Approval Process: the Organization of Persuasion," Sciences Po publications info:hdl:2441/1gr6n3t28b9, Sciences Po.
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    8. Emir Kamenica, 2019. "Bayesian Persuasion and Information Design," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 249-272, August.
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    Cited by:

    1. Aïd, René & Bonesini, Ofelia & Callegaro, Giorgia & Campi, Luciano, 2025. "Continuous-time persuasion by filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 176(C).
    2. Aïd, René & Bonesini, Ofelia & Callegaro, Giorgia & Campi, Luciano, 2025. "Continuous-time persuasion by filtering," LSE Research Online Documents on Economics 127889, London School of Economics and Political Science, LSE Library.
    3. Liao, Xiaoye & Szkup, Michal, 2026. "Coordination with sequential information acquisition," Theoretical Economics, Econometric Society, vol. 21(1), January.

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