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Heterogeneous trembles and model selection in the strategy frequency estimation method

Published online by Cambridge University Press:  17 January 2025

James R. Bland Open the ORCID record for James R. Bland [Opens in a new window]
James R. Bland*
Affiliation:
Department of Economics, The University of Toledo, Toledo, USA
*
e-mail: [email protected]
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Abstract

The strategy frequency estimation method (Dal Bó and Fréchette in Am Econ Rev 101(1):411-429, 2011; Fudenberg in Am Econ Rev 102(2):720-749, 2012) allows us to estimate the fraction of subjects playing each of a list of strategies in an infinitely repeated game. Currently, this method assumes that subjects tremble with the same probability. This paper extends this method, so that subjects’ trembles can be heterogeneous. Out of 60 ex ante plausible specifications, the selected model uses the six strategies described in Dal Bó and Fréchette (2018), and allows the distribution of trembles to vary by strategy.

Keywords

Prisoner’s dilemmaStrategy frequency estimation methodMixture modelModel selectionTrembles

JEL classification

C52: Model Evaluation, Validation, and Selection C57: Econometrics of Games and Auctions C15: Statistical Simulation Methods: General C73: Stochastic and Dynamic Games • Evolutionary Games • Repeated Games
Type
Original Paper
Information
Journal of the Economic Science Association , Volume 6 , Issue 2: Special Issue: Statistical Issues for Experimental Economists , December 2020 , pp. 113 - 124
Copyright
Copyright © Economic Science Association 2020

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Footnotes

Electronic supplementary material The online version of this article (https://doi.org/10.1007/s40881-020-00097-y) contains supplementary material, which is available to authorized users.

I would like to thank Huanren Zhang and Guillaume Fréchette for valuable advice at the beginning of this project, and Aleksandr Alekseev, Xiaoxue Sherry Gao, John Ham, an anonymous reviewer, and attendees of the 2018 North American Economic Science Association meeting for helpful comments. I acknowledge funding support from the University of Toledo Kohler International Grants.

References

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