IDEAS home Printed from https://ideas.repec.org/a/the/publsh/4742.html
   My bibliography  Save this article

Persuasion with unknown beliefs

Author

Listed:
  • Kosterina, Svetlana

    (Department of Economics, University of Pittsburgh)

Abstract

A sender designs an information structure to persuade a receiver to take an action. The sender is ignorant about the receiver's prior, and evaluates each information structure using the receiver's prior that is the worst for the sender. I characterize the optimal information structures in this environment. I show that there exists an optimal signal with two realizations, characterize the support of the signal realization recommending approval and show that the optimal signal is a hyperbola. The lack of knowledge of the receiver's prior causes the sender to hedge her bets: the optimal signal induces the high action in more states than in the standard model, albeit with a lower probability. Increasing the sender's ignorance can hurt both the sender and the receiver.

Suggested Citation

  • Kosterina, Svetlana, 2022. "Persuasion with unknown beliefs," Theoretical Economics, Econometric Society, vol. 17(3), July.
  • Handle: RePEc:the:publsh:4742
    as

    Download full text from publisher

    File URL: http://econtheory.org/ojs/index.php/te/article/viewFile/20221075/34317/1006
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Alexei Parakhonyak & Anton Sobolev, 2022. "Persuasion without Priors," Economics Series Working Papers 977, University of Oxford, Department of Economics.
    2. Krishnamurthy Iyer & Haifeng Xu & You Zu, 2023. "Markov Persuasion Processes with Endogenous Agent Beliefs," Papers 2307.03181, arXiv.org, revised Jul 2023.
    3. Shiri Alon & Sarah Auster & Gabi Gayer & Stefania Minardi, 2023. "Persuasion With Limited Data: A Case-Based Approach," CRC TR 224 Discussion Paper Series crctr224_2023_443, University of Bonn and University of Mannheim, Germany.
    4. Yiling Chen & Tao Lin, 2023. "Persuading a Behavioral Agent: Approximately Best Responding and Learning," Papers 2302.03719, arXiv.org, revised Feb 2024.
    5. Babichenko, Yakov & Talgam-Cohen, Inbal & Xu, Haifeng & Zabarnyi, Konstantin, 2022. "Regret-minimizing Bayesian persuasion," Games and Economic Behavior, Elsevier, vol. 136(C), pages 226-248.
    6. Maxim Senkov & Toygar T. Kerman, 2024. "Changing Simplistic Worldviews," Papers 2401.02867, arXiv.org.
    7. Tommaso Denti & Doron Ravid, 2023. "Robust Predictions in Games with Rational Inattention," Papers 2306.09964, arXiv.org.

    More about this item

    Keywords

    Bayesian persuasion; robust mechanism design;

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

    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:the:publsh:4742. 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: Martin J. Osborne (email available below). General contact details of provider: http://econtheory.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.