IDEAS home Printed from https://ideas.repec.org/a/ucp/jlawec/doi10.1086-717755.html
   My bibliography  Save this article

A Study of Umbrella Damages from Bid Rigging

Author

Listed:
  • El Hadi Caoui

Abstract

If noncartel firms adjust their pricing to the supracompetitive level sustained by a cartel, purchasers from noncartel firms may suffer umbrella damages. This paper examines the bidding behavior of noncartel firms against the Texas school milk cartel between 1980 and 1992. The largest noncartel firm bid less aggressively when facing the cartel. Structural estimation reveals that, per contract, damages due to noncartel firms bidding higher are at least 35 percent of damages caused by the cartel. Inefficiencies raise the winner’s cost by 5.9 percent. These results shed light on the importance of umbrella damages from a civil liability perspective.

Suggested Citation

  • El Hadi Caoui, 2022. "A Study of Umbrella Damages from Bid Rigging," Journal of Law and Economics, University of Chicago Press, vol. 65(2), pages 239-277.
    • Handle: RePEc:ucp:jlawec:doi:10.1086/717755
    DOI: 10.1086/717755
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/717755
    Download Restriction: Access to the online full text or PDF requires a subscription.
    File URL: http://dx.doi.org/10.1086/717755
    Download Restriction: Access to the online full text or PDF requires a subscription.
    File URL: https://libkey.io/10.1086/717755?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 search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gabrielli, M. Florencia & Willington, Manuel, 2023. "Estimating damages from bidding rings in first-price auctions," Economic Modelling, Elsevier, vol. 126(C).
    2. Christoph Graf & Viktor Zobernig & Johannes Schmidt & Claude Klöckl, 2024. "Computational Performance of Deep Reinforcement Learning to Find Nash Equilibria," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 529-576, February.

    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:jlawec:doi:10.1086/717755. 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/JLE .

    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.