IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

Identifying Strategies and Beliefs without Rationality Assumptions

  • Amos Golan
  • James Bono

In this paper we formulate a solution concept without making assumptions about expected utility maximization, common knowledge or beliefs. Beliefs, strate- gies and the degree to which players are expected utility maximizers are endoge- nously determined as part of the solution. To achieve this, rather than solving the game from the players' point of view, we analyze the game as an "observer" who is not engaged in the process of the game. Our approach is an information theoretic one in which the observer utilizes an observation of play and the Maximum Entropy principle. We compare our solution concept with Bayesian Nash equilibrium and over the entropy ratio test as a method for determining the appropriateness of common modeling assumptions. We also demonstrate that the QRE concept can be signicantly generalized when viewed from the observer's perspective. For games of incomplete information we discover that alternative uses of the observer's information lead to alternative interpretations of rationality. These alternative in- terpretations of rationality may prove useful, especially in the context of ex post arbitration, as they indicate who is motivating whom.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
File Function: First version, 2010
Download Restriction: no

Paper provided by American University, Department of Economics in its series Working Papers with number 2010-12.

in new window

Date of creation: May 2010
Date of revision:
Handle: RePEc:amu:wpaper:2010-12
Contact details of provider: Web page:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Miguel A. Costa-Gomes & Vincent P. Crawford, 2004. "Cognition and Behavior in Two-Person Guessing Games: An Experimental Study," ISER Discussion Paper 0613, Institute of Social and Economic Research, Osaka University.
  2. repec:tpr:qjecon:v:119:y:2004:i:3:p:861-898 is not listed on IDEAS
  3. Golan, Amos, 2007. "Information and entropy econometrics - volume overview and synthesis," Journal of Econometrics, Elsevier, vol. 138(2), pages 379-387, June.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:amu:wpaper:2010-12. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Meal)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.