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research articles : An experimental study of information and mixed-strategy play in the three-person matching-pennies game

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Author Info
Arijit Mukherji () (University of Minnesota, Minneapolis, MN 55455, USA)
Kevin A. McCabe (Economic Science Laboratory and Department of Economics, College of Business and Public Administration, University of Arizona, Tucson, AZ 85721, USA)
David E. Runkle () (University of Minnesota, Minneapolis, MN 55455, USA)

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Abstract

Recent experiments on mixed-strategy play in experimental games reject the hypothesis that subjects play a mixed strategy even when that strategy is the unique Nash equilibrium prediction. However, in a three-person matching-pennies game played with perfect monitoring and complete payoff information, we cannot reject the hypothesis that subjects play the mixed-strategy Nash equilibrium. Given this support for mixed-strategy play, we then consider two qualitatively different learning theories (sophisticated Bayesian and naive Bayesian) which predict that the amount of information given to subjects will determine whether they can learn to play the predicted mixed strategies. We reject the hypothesis that subjects play the symmetric mixed-strategy Nash equilibrium when they do not have complete payoff information. This finding suggests that players did not use sophisticated Bayesian learning to reach the mixed-strategy Nash equilibrium.

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Publisher Info
Article provided by Springer in its journal Economic Theory.

Volume (Year): 15 (2000)
Issue (Month): 2 ()
Pages: 421-462
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Handle: RePEc:spr:joecth:v:15:y:2000:i:2:p:421-462

Note: Received: August 9, 1996; revised version: October 21, 1998
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Related research
Keywords: Nash equilibrium; Bayesian learning; Experimental.;

Find related papers by JEL classification:
C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information

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