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A HIDDEN MARKOV MODEL FOR THE DETECTION OF PURE AND MIXED STRATEGY PLAY IN GAMES

Published online by Cambridge University Press:  24 October 2014

Jason Shachat ,
J. Todd Swarthout  and
Lijia Wei
Jason Shachat
Affiliation:
Durham University
J. Todd Swarthout
Affiliation:
Georgia State University
Lijia Wei*
Affiliation:
Wuhan University
*
*Address Correspondence to Lijia Wei, School of Economics and Management, Wuhan University, China 430072; e-mail: [email protected].
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Abstract

We propose a statistical model to assess whether individuals strategically use mixed strategies in repeated games. We formulate a hidden Markov model in which the latent state space contains both pure and mixed strategies. We apply the model to data from an experiment in which human subjects repeatedly play a normal form game against a computer that always follows its part of the unique mixed strategy Nash equilibrium profile. Estimated results show significant mixed strategy play and nonstationary dynamics. We also explore the ability of the model to forecast action choice.

Type
ARTICLES
Information
Econometric Theory , Volume 31 , Issue 4 , August 2015 , pp. 729 - 752
Copyright
Copyright © Cambridge University Press 2014 

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Footnotes

The authors thank John Duffy, John Wooders, Jan Bouckaert, and Leonidas Spiliopoulos for discussion and comments on earlier drafts. We also thank the seminar participants at the University of Otago, Monash University, the University of Sydney, the Antwerp-Lille-Xiamen joint workshop in Microeconomics, and the 3rd WISE-Humboldt joint workshop on high-dimensional nonstationary econometrics. Jason Shachat acknowledges the Fujian Overseas High Talent Organization for funding as well as the NSF of China under proposal number 71131008.

References

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