A Hidden Markov Model for the Detection of Pure and Mixed Strategy Play in Games

26 Pages Posted: 8 Jul 2012

See all articles by Jason Shachat

Jason Shachat

Durham University

J. Todd Swarthout

Georgia State University - Andrew Young School of Policy Studies

Lijia Wei

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Wuhan University - School of Economics and Management

Date Written: July 7, 2012

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, and allows switching between these states. 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 non-stationary dynamics. We also explore the ability of the model to forecast action choice.

Keywords: Mixed Strategy; Experiment; Hidden Markov Model

JEL Classification: C11, C72, C92

Suggested Citation

Shachat, Jason and Swarthout, J. Todd and Wei, Lijia and Wei, Lijia, A Hidden Markov Model for the Detection of Pure and Mixed Strategy Play in Games (July 7, 2012). Available at SSRN: https://ssrn.com/abstract=2101849 or http://dx.doi.org/10.2139/ssrn.2101849

Jason Shachat (Contact Author)

Durham University ( email )

Durham University Business School
Mill Hill Lane
Durham, Fujian DH1 3LB
United Kingdom

J. Todd Swarthout

Georgia State University - Andrew Young School of Policy Studies ( email )

P.O. Box 3992
Atlanta, GA 30302-3992
United States

Lijia Wei

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 361005
China

Wuhan University - School of Economics and Management ( email )

Wu Han, Hu-Bai 430072
China

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