IDEAS home Printed from https://ideas.repec.org/a/ucp/jpolec/doi10.1086-740223.html

A Method to Estimate Discrete Choice Models That Is Robust to Consumer Search

Author

Listed:
  • Jason Abaluck
  • Giovanni Compiani
  • Fan Zhang

Abstract

We state conditions under which choice data suffice to identify preferences when consumers may not be fully informed about attributes of goods. Our approach can be used to test for full information, forecast how consumers will respond to information, and conduct welfare analysis when consumers are imperfectly informed. In a lab experiment, we successfully forecast the average response to new information when consumers engage in costly search. In data from Expedia, our method identifies which attribute was not immediately visible to consumers in search results and allows us to compute the value of additional information.

Suggested Citation

  • Jason Abaluck & Giovanni Compiani & Fan Zhang, 2026. "A Method to Estimate Discrete Choice Models That Is Robust to Consumer Search," Journal of Political Economy, University of Chicago Press, vol. 134(7), pages 1967-2022.
    • Handle: RePEc:ucp:jpolec:doi:10.1086/740223
    DOI: 10.1086/740223
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/740223
    Download Restriction: Access to the online full text or PDF requires a subscription.
    File URL: http://dx.doi.org/10.1086/740223
    Download Restriction: Access to the online full text or PDF requires a subscription.
    File URL: https://libkey.io/10.1086/740223?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    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:ucp:jpolec:doi:10.1086/740223. 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: Journals Division (email available below). General contact details of provider: https://www.journals.uchicago.edu/JPE .

    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.