IDEAS home Printed from https://ideas.repec.org/a/wly/emetrp/v93y2025i6p2007-2042.html

Marginal Reputation

Author

Listed:
  • Daniel Luo
  • Alexander Wolitzky

Abstract

We study reputation formation where a long‐run player repeatedly observes private signals and takes actions. Short‐run players observe the long‐run player's past actions but not her past signals. The long‐run player can thus develop a reputation for playing a distribution over actions, but not necessarily for playing a particular mapping from signals to actions. Nonetheless, we show that the long‐run player can secure her Stackelberg payoff if distinct commitment types are statistically distinguishable and the Stackelberg strategy is confound‐defeating. This property holds if and only if the Stackelberg strategy is the unique solution to an optimal transport problem. If the long‐run player's payoff is supermodular in one‐dimensional signals and actions, she secures the Stackelberg payoff if and only if the Stackelberg strategy is monotone. Applications include deterrence, delegation, signaling, and persuasion. Our results extend to the case where distinct commitment types may be indistinguishable, but the Stackelberg type is salient under the prior.

Suggested Citation

  • Daniel Luo & Alexander Wolitzky, 2025. "Marginal Reputation," Econometrica, Econometric Society, vol. 93(6), pages 2007-2042, November.
  • Handle: RePEc:wly:emetrp:v:93:y:2025:i:6:p:2007-2042
    DOI: 10.3982/ECTA23782
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/ECTA23782
    Download Restriction: no

    File URL: https://libkey.io/10.3982/ECTA23782?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
    ---><---

    Other versions of this item:

    More about this item

    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:wly:emetrp:v:93:y:2025:i:6:p:2007-2042. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.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.