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Bayesian persuasion with costly information acquisition

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  • Matysková, Ludmila
  • Montes, Alfonso

Abstract

We consider a Bayesian persuasion model, in which the receiver can gather independent information about the state at a uniformly posterior-separable cost. We show that the sender provides information that prevents the receiver from gathering independent information in equilibrium. When the receiver faces a lower cost of information, her ‘threat’ of gathering independent information increases, thus decreasing the sender's power to persuade. Lower cost of information can also hurt the receiver, because the sender may provide strictly less information in equilibrium. Furthermore, we propose a solution method that can be used to solve our model in specific applications.

Suggested Citation

  • Matysková, Ludmila & Montes, Alfonso, 2023. "Bayesian persuasion with costly information acquisition," Journal of Economic Theory, Elsevier, vol. 211(C).
  • Handle: RePEc:eee:jetheo:v:211:y:2023:i:c:s0022053123000741
    DOI: 10.1016/j.jet.2023.105678
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    References listed on IDEAS

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    1. Lipnowski, Elliot & Mathevet, Laurent & Wei, Dong, 2022. "Optimal attention management: A tractable framework," Games and Economic Behavior, Elsevier, vol. 133(C), pages 170-180.
    2. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    3. Elliot Lipnowski & Laurent Mathevet, 2018. "Disclosure to a Psychological Audience," American Economic Journal: Microeconomics, American Economic Association, vol. 10(4), pages 67-93, November.
    4. Wei, Dong, 2021. "Persuasion under costly learning," Journal of Mathematical Economics, Elsevier, vol. 94(C).
    5. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    6. Andrew Caplin & Mark Dean & John Leahy, 2022. "Rationally Inattentive Behavior: Characterizing and Generalizing Shannon Entropy," Journal of Political Economy, University of Chicago Press, vol. 130(6), pages 1676-1715.
    7. Elliot Lipnowski & Laurent Mathevet & Dong Wei, 2020. "Attention Management," American Economic Review: Insights, American Economic Association, vol. 2(1), pages 17-32, March.
    8. Hébert, Benjamin & Woodford, Michael, 2023. "Rational inattention when decisions take time," Journal of Economic Theory, Elsevier, vol. 208(C).
    9. Aoyagi, Masaki, 2014. "Strategic obscurity in the forecasting of disasters," Games and Economic Behavior, Elsevier, vol. 87(C), pages 485-496.
    10. Bizzotto, Jacopo & Rüdiger, Jesper & Vigier, Adrien, 2020. "Testing, disclosure and approval," Journal of Economic Theory, Elsevier, vol. 187(C).
    11. Gentzkow, Matthew & Kamenica, Emir, 2017. "Bayesian persuasion with multiple senders and rich signal spaces," Games and Economic Behavior, Elsevier, vol. 104(C), pages 411-429.
    12. Le Treust, Maël & Tomala, Tristan, 2019. "Persuasion with limited communication capacity," Journal of Economic Theory, Elsevier, vol. 184(C).
    13. Andrew Caplin & Mark Dean & John Leahy, 2019. "Rational Inattention, Optimal Consideration Sets, and Stochastic Choice," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(3), pages 1061-1094.
    14. Alonso, Ricardo & Câmara, Odilon, 2016. "Bayesian persuasion with heterogeneous priors," Journal of Economic Theory, Elsevier, vol. 165(C), pages 672-706.
    15. Anton Kolotilin & Tymofiy Mylovanov & Andriy Zapechelnyuk & Ming Li, 2017. "Persuasion of a Privately Informed Receiver," Econometrica, Econometric Society, vol. 85(6), pages 1949-1964, November.
    16. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    17. Jacopo Bizzotto & Jesper Rüdiger & Adrien Vigier, 2021. "Dynamic Persuasion with Outside Information," American Economic Journal: Microeconomics, American Economic Association, vol. 13(1), pages 179-194, February.
    18. Kolotilin, Anton, 2018. "Optimal information disclosure: a linear programming approach," Theoretical Economics, Econometric Society, vol. 13(2), May.
    19. Andrew Caplin & Mark Dean, 2013. "Behavioral Implications of Rational Inattention with Shannon Entropy," NBER Working Papers 19318, National Bureau of Economic Research, Inc.
    20. Scott Gehlbach & Alberto Simpser, 2015. "Electoral Manipulation as Bureaucratic Control," American Journal of Political Science, John Wiley & Sons, vol. 59(1), pages 212-224, January.
    21. Emir Kamenica, 2019. "Bayesian Persuasion and Information Design," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 249-272, August.
    22. Gick, Wolfgang & Pausch, Thilo, 2012. "Persuasion by stress testing: Optimal disclosure of supervisory information in the banking sector," Discussion Papers 32/2012, Deutsche Bundesbank.
    23. Tommaso Denti, 2022. "Posterior Separable Cost of Information," American Economic Review, American Economic Association, vol. 112(10), pages 3215-3259, October.
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    Cited by:

    1. Lily Ling Yang, 2024. "Information Design with Costly State Verifi cation," CRC TR 224 Discussion Paper Series crctr224_2024_502, University of Bonn and University of Mannheim, Germany.

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    More about this item

    Keywords

    Bayesian persuasion; Costly information acquisition; Information design;
    All these keywords.

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • 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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