IDEAS home Printed from https://ideas.repec.org/a/eee/gamebe/v150y2025icp480-500.html
   My bibliography  Save this article

Nonparametric identification and estimation of the generalized second-price auction

Author

Listed:
  • Shakhgildyan, Ksenia

Abstract

In this paper, I establish the identification and present a nonparametric estimator for the incomplete information generalized second-price auction model. I recover the distribution of the bidders' quality-adjusted valuations from the CDF of the adjusted bids, win outcomes, and click-through rates. Through the Monte Carlo simulations, I evaluate the finite-sample performance of the proposed estimator. Additionally, I compare the estimator of the incomplete information model to the estimator of the misspecified model assuming that adjusted bids are the result of the bidding according to the locally envy-free equilibrium of complete information model.

Suggested Citation

  • Shakhgildyan, Ksenia, 2025. "Nonparametric identification and estimation of the generalized second-price auction," Games and Economic Behavior, Elsevier, vol. 150(C), pages 480-500.
  • Handle: RePEc:eee:gamebe:v:150:y:2025:i:c:p:480-500
    DOI: 10.1016/j.geb.2025.02.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0899825625000181
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.geb.2025.02.005?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.

    More about this item

    Keywords

    Generalized second-price auction; Nonparametric identification; Nonparametric estimation; Incomplete information;
    All these keywords.

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising

    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:eee:gamebe:v:150:y:2025:i:c:p:480-500. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622836 .

    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.