IDEAS home Printed from https://ideas.repec.org/p/zbw/bonedp/62000.html

Through Trial & Error to Collusion - The Discrete Case

Author

Listed:
  • Huck, Steffen
  • Normann, Hans-Theo
  • Oechssler, Jörg

Abstract

In this note we study a very simple trial & error learning process in the context of a Cournot oligopoly. Without any knowledge of the payoff functions players increase, respectively decrease, their quantity by one unit as long as this leads to higher profits. We show that despite the absence of any coordination or punishing device this process converges to a collusive outcome.

Suggested Citation

  • Huck, Steffen & Normann, Hans-Theo & Oechssler, Jörg, 2000. "Through Trial & Error to Collusion - The Discrete Case," Bonn Econ Discussion Papers 6/2000, University of Bonn, Bonn Graduate School of Economics (BGSE).
    • Handle: RePEc:zbw:bonedp:62000
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/78373/1/bgse6_2000.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Milgrom, Paul & Roberts, John, 1991. "Adaptive and sophisticated learning in normal form games," Games and Economic Behavior, Elsevier, vol. 3(1), pages 82-100, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Bigoni, Maria & Fort, Margherita, 2013. "Information and learning in oligopoly: An experiment," Games and Economic Behavior, Elsevier, vol. 81(C), pages 192-214.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antonio Cabrales & Rosemarie Nagel & Roc Armenter, 2007. "Equilibrium selection through incomplete information in coordination games: an experimental study," Experimental Economics, Springer;Economic Science Association, vol. 10(3), pages 221-234, September.
    2. Sela, Aner, 1997. "One against all in the fictitious play process," Sonderforschungsbereich 504 Publications 97-09, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    3. Bigoni, Maria & Fort, Margherita, 2013. "Information and learning in oligopoly: An experiment," Games and Economic Behavior, Elsevier, vol. 81(C), pages 192-214.
    4. Ho, Teck-Hua, 1996. "Finite automata play repeated prisoner's dilemma with information processing costs," Journal of Economic Dynamics and Control, Elsevier, vol. 20(1-3), pages 173-207.
    5. David Cooper & John Kagel, 2008. "Learning and transfer in signaling games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 34(3), pages 415-439, March.
    6. Thijssen, J.J.J., 2003. "Investment under uncertainty, market evolution and coalition spillovers in a game theoretic perspective," Other publications TiSEM 672073a6-492e-4621-8d4a-0, Tilburg University, School of Economics and Management.
    7. Ellison, Glenn, 1997. "Learning from Personal Experience: One Rational Guy and the Justification of Myopia," Games and Economic Behavior, Elsevier, vol. 19(2), pages 180-210, May.
    8. Francetich, Alejandro & Kreps, David, 2020. "Choosing a good toolkit, I: Prior-free heuristics," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    9. Davis, Douglas, 2011. "Behavioral convergence properties of Cournot and Bertrand markets: An experimental analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 80(3), pages 443-458.
    10. Mathevet, Laurent & Taneva, Ina, 2013. "Finite supermodular design with interdependent valuations," Games and Economic Behavior, Elsevier, vol. 82(C), pages 327-349.
    11. Hong, Jieying & Moinas, Sophie & Pouget, Sébastien, 2021. "Learning in speculative bubbles: Theory and experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 1-26.
    12. Hopkins, Ed, 1999. "Learning, Matching, and Aggregation," Games and Economic Behavior, Elsevier, vol. 26(1), pages 79-110, January.
    13. Tombak, Mihkel M., 1995. "Process technologies, learning and brand proliferation," European Journal of Operational Research, Elsevier, vol. 82(1), pages 26-38, April.
    14. Chong, Juin-Kuan & Camerer, Colin F. & Ho, Teck H., 2006. "A learning-based model of repeated games with incomplete information," Games and Economic Behavior, Elsevier, vol. 55(2), pages 340-371, May.
    15. Sebastiano Della Lena & Fabrizio Panebianco, 2019. "Cultural Transmission with Incomplete Information: Parental Perceived Efficacy and Group Misrepresentation," Working Papers 2019:11, Department of Economics, University of Venice "Ca' Foscari".
    16. Sobel, Joel, 2000. "Economists' Models of Learning," Journal of Economic Theory, Elsevier, vol. 94(2), pages 241-261, October.
    17. Healy, Paul J., 2006. "Learning dynamics for mechanism design: An experimental comparison of public goods mechanisms," Journal of Economic Theory, Elsevier, vol. 129(1), pages 114-149, July.
    18. Battigalli, Pierpaolo & Panebianco, Fabrizio & Pin, Paolo, 2023. "Learning and selfconfirming equilibria in network games," Journal of Economic Theory, Elsevier, vol. 212(C).
    19. Potters, Jan & van Winden, Frans, 1996. "Comparative Statics of a Signaling Game: An Experimental Study," International Journal of Game Theory, Springer;Game Theory Society, vol. 25(3), pages 329-353.
    20. Jiequn Han & Ruimeng Hu & Jihao Long, 2020. "Convergence of Deep Fictitious Play for Stochastic Differential Games," Papers 2008.05519, arXiv.org, revised Mar 2021.

    More about this item

    Keywords

    ;
    ;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

    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:zbw:bonedp:62000. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/gsbonde.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.