IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2003.07338.html
   My bibliography  Save this paper

Keeping the Listener Engaged: a Dynamic Model of Bayesian Persuasion

Author

Listed:
  • Yeon-Koo Che
  • Kyungmin Kim
  • Konrad Mierendorff

Abstract

We consider a dynamic model of Bayesian persuasion in which information takes time and is costly for the sender to generate and for the receiver to process, and neither player can commit to their future actions. Persuasion may totally collapse in a Markov perfect equilibrium (MPE) of this game. However, for persuasion costs sufficiently small, a version of a folk theorem holds: outcomes that approximate Kamenica and Gentzkow (2011)'s sender-optimal persuasion as well as full revelation and everything in between are obtained in MPE, as the cost vanishes.

Suggested Citation

  • Yeon-Koo Che & Kyungmin Kim & Konrad Mierendorff, 2020. "Keeping the Listener Engaged: a Dynamic Model of Bayesian Persuasion," Papers 2003.07338, arXiv.org, revised Sep 2022.
    • Handle: RePEc:arx:papers:2003.07338
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2003.07338
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Herresthal, Claudia, 2022. "Hidden testing and selective disclosure of evidence," Journal of Economic Theory, Elsevier, vol. 200(C).
    2. Raphael Boleslavsky, 2023. "Waiting for Fake News," Papers 2304.04053, arXiv.org, revised Apr 2023.
    3. Emir Kamenica & Kyungmin Kim & Andriy Zapechelnyuk, 2021. "Bayesian persuasion and information design: perspectives and open issues," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(3), pages 701-704, October.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2003.07338. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.