IDEAS home Printed from https://ideas.repec.org/a/igg/jabe00/v5y2016i2p31-45.html
   My bibliography  Save this article

What Model Best Describes Initial Choices in a Cournot Duopoly Experiment?

Author

Listed:
  • Mariano Gabriel Runco

    (Economics Department, Auburn University at Montgomery, Montgomery, AL, USA)

Abstract

This paper tests empirically four models of bounded rationality using data from first responses in a Cournot duopoly experiment. Specifically, the models considered are Level-k, Quantal Response Equilibrium, Noisy Introspection and Logit Cognitive Hierarchy. It is found that the Level-k model (with proportions of Level-0, Level-1 and Level-8 given by 68.5%, 13.2% and 18.3% respectively) provides the best fit in terms of Log-Likelihood and BIC. Moreover, the robustness of our findings is corroborated analyzing subsets of the original data.

Suggested Citation

  • Mariano Gabriel Runco, 2016. "What Model Best Describes Initial Choices in a Cournot Duopoly Experiment?," International Journal of Applied Behavioral Economics (IJABE), IGI Global, vol. 5(2), pages 31-45, April.
  • Handle: RePEc:igg:jabe00:v:5:y:2016:i:2:p:31-45
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJABE.2016040103
    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:igg:jabe00:v:5:y:2016:i:2:p:31-45. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.