IDEAS home Printed from https://ideas.repec.org/a/aea/aerins/v4y2022i1p123-38.html
   My bibliography  Save this article

Persuasion with Correlation Neglect: A Full Manipulation Result

Author

Listed:
  • Gilat Levy
  • Inés Moreno de Barreda
  • Ronny Razin

Abstract

We consider an information design problem in which a sender tries to persuade a receiver that has "correlation neglect," i.e., fails to understand that signals might be correlated. We show that a sender with unlimited number of signals can fully manipulate the receiver. Specifically, the sender can induce the receiver to hold any state-dependent posterior she wishes to. If the sender only wishes to induce a state-independent posterior, she can use fully correlated signals, but generally she needs to design more involved correlation structures.

Suggested Citation

  • Gilat Levy & Inés Moreno de Barreda & Ronny Razin, 2022. "Persuasion with Correlation Neglect: A Full Manipulation Result," American Economic Review: Insights, American Economic Association, vol. 4(1), pages 123-138, March.
    • Handle: RePEc:aea:aerins:v:4:y:2022:i:1:p:123-38
    DOI: 10.1257/aeri.20210007
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/aeri.20210007
    Download Restriction: no
    File URL: https://www.aeaweb.org/doi/10.1257/aeri.20210007.appx
    Download Restriction: no
    File URL: https://www.aeaweb.org/doi/10.1257/aeri.20210007.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    File URL: https://libkey.io/10.1257/aeri.20210007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

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


    Cited by:

    1. Andrew T Little, 2023. "Bayesian explanations for persuasion," Journal of Theoretical Politics, , vol. 35(3), pages 147-181, July.
    2. Maxim Senkov & Toygar T. Kerman, 2024. "Changing Simplistic Worldviews," Papers 2401.02867, arXiv.org.
    3. Ran Spiegler, 2023. "Behavioral Causal Inference," Papers 2305.18916, arXiv.org.
    4. Itai Arieli & Yakov Babichenko & Fedor Sandomirskiy, 2023. "Persuasion as Transportation," Papers 2307.07672, arXiv.org.

    More about this item

    JEL classification:

    • 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

    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:aea:aerins:v:4:y:2022:i:1:p:123-38. 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: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    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.