IDEAS home Printed from https://ideas.repec.org/p/snu/ioerwp/no113.html
   My bibliography  Save this paper

Learning Rival¡¯s Information in Interdependent Value Auctions

Author

Listed:
  • Jinwoo Kim
  • Youngwoo Koh

Abstract

We study a simple auction model with interdependent values in which bidders can learn their rival¡¯s information and compete in the first-price or second-price auction. We characterize unique symmetric equilibrium strategies-both learning and bidding strategies-for the two auction formats. While bidders learn rival¡¯s signals with higher probabilities in the first-price auction, they earn higher rent in the second-price auction. We also show that when learning cost is small, signal correlation is low, or value interdependence is weak, the first-price auction generates a higher revenue than the second-price auction, while the revenue ranking is reversed otherwise.

Suggested Citation

  • Jinwoo Kim & Youngwoo Koh, 2017. "Learning Rival¡¯s Information in Interdependent Value Auctions," Working Paper Series no113, Institute of Economic Research, Seoul National University.
    • Handle: RePEc:snu:ioerwp:no113
    as

    Download full text from publisher

    File URL: https://ier.snu.ac.kr/activity/working-papers?md=download&seqidx=13
    Download Restriction: no
    ---><---

    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:snu:ioerwp:no113. 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: Hojung Lee (email available below). General contact details of provider: https://edirc.repec.org/data/iesnukr.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.