IDEAS home Printed from https://ideas.repec.org/a/aea/aecrev/v112y2022i6p1949-84.html
   My bibliography  Save this article

Screening Inattentive Buyers

Author

Listed:
  • Jeffrey Mensch

Abstract

Information plays a crucial role in mechanism design problems. A potential complication is that buyers may be inattentive, and so their information may endogenously and flexibly depend on the offered mechanism. I show that it is without loss of generality to consider contour mechanisms, which comprise triplets of allocation probabilities, prices, and beliefs, and are uniquely determined by a single such point. The mechanism design problem then reduces to Bayesian persuasion along the optimal contour. This reduction has significant implications for both the implementation of the optimal mechanism and the revenues that can be achieved.

Suggested Citation

  • Jeffrey Mensch, 2022. "Screening Inattentive Buyers," American Economic Review, American Economic Association, vol. 112(6), pages 1949-1984, June.
  • Handle: RePEc:aea:aecrev:v:112:y:2022:i:6:p:1949-84
    DOI: 10.1257/aer.20201098
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/aer.20201098
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/aer.20201098.appx
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/aer.20201098.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.

    File URL: https://libkey.io/10.1257/aer.20201098?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. Brian C. Albrecht & Mark Whitmeyer, 2023. "Comparison Shopping: Learning Before Buying From Duopolists," Papers 2302.06580, arXiv.org, revised Apr 2023.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • 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:aecrev:v:112:y:2022:i:6:p:1949-84. 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.