IDEAS home Printed from https://ideas.repec.org/p/wat/wpaper/26005.html

Monitoring, Market Primitives, and the Stability of Algorithmic Collusion

Author

Listed:
  • Possnig, Clemens

    (School of Economics, University of Waterloo)

Abstract

This paper develops an analytical framework to study when sophisticated machine learning algorithms may learn to collude. Algorithms observe a state variable and update policies to maximize long-term payoffs; their long-run policies correspond to the stable equilibria of a tractable differential equation. In a repeated Bertrand game, I derive necessary and sufficient conditions under which Nash equilibria are learned. This reveals how the interplay between monitoring technology (state variables) and market conditions determines whether competitive or collusive outcomes emerge. I apply these insights to evaluate two key regulatory policies: limiting algorithmic data inputs and imposing competition in the software provider market.

Suggested Citation

  • Possnig, Clemens, 2026. "Monitoring, Market Primitives, and the Stability of Algorithmic Collusion," Working Papers 26005, University of Waterloo, Department of Economics.
    • Handle: RePEc:wat:wpaper:26005
    as

    Download full text from publisher

    File URL: https://hdl.handle.net/10012/23580
    File Function: First version, 2026
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:wat:wpaper:26005. 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: Sherri Anne Arsenault (email available below). General contact details of provider: https://edirc.repec.org/data/dewatca.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.