IDEAS home Printed from https://ideas.repec.org/a/aea/apandp/v112y2022p431-37.html
   My bibliography  Save this article

Addressing Strategic Uncertainty with Incentives and Information

Author

Listed:
  • Marina Halac
  • Elliot Lipnowski
  • Daniel Rappoport

Abstract

A principal privately contracts with a set of agents who then simultaneously make a binary decision. Each contract specifies an individual allocation and the information the agent is given about a fundamental state and other agents' contracts. We study the principal's optimal scheme that induces a desired action profile as the unique rationalizable outcome. Our main result reduces this multiagent problem to a two-step procedure where information is designed agent-by-agent: the principal chooses a fundamental-state-contingent distribution over agent rankings and, separately for each agent, the agent's information about the realized ranking and fundamental states. We illustrate with a team-production application.

Suggested Citation

  • Marina Halac & Elliot Lipnowski & Daniel Rappoport, 2022. "Addressing Strategic Uncertainty with Incentives and Information," AEA Papers and Proceedings, American Economic Association, vol. 112, pages 431-437, May.
  • Handle: RePEc:aea:apandp:v:112:y:2022:p:431-37
    DOI: 10.1257/pandp.20221087
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20221087
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20221087.appx
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20221087.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.

    File URL: https://libkey.io/10.1257/pandp.20221087?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. Li, Fei & Song, Yangbo & Zhao, Mofei, 2023. "Global manipulation by local obfuscation," Journal of Economic Theory, Elsevier, vol. 207(C).

    More about this item

    JEL classification:

    • 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
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law

    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:apandp:v:112:y:2022:p:431-37. 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.