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Invariance of equilibrium to the strategy method I: theory

Published online by Cambridge University Press:  17 January 2025

Daniel L. Chen Open the ORCID record for Daniel L. Chen [Opens in a new window]  and
Martin Schonger
Daniel L. Chen*
Affiliation:
Toulouse School of Economics, Institute for Advanced Study in Toulouse, University of Toulouse Capitole, Toulouse, France
Martin Schonger
Affiliation:
ETH Zurich, Center for Law and Economics, Zurich, Switzerland
*
e-mail: daniel.chen@iast.fr
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Abstract

This article highlights a potential and significant economic–theoretical bias in the widely used strategy method (SM) technique. Although SM is commonly employed to analyze numerous observations per subject regarding rare or off-equilibrium behaviors unattainable through direct elicitation (DE), researchers often overlook a critical distinction. The strategic equivalence between SM and DE is applicable in the context of monetary payoff games, but not in the actual utility-based games played by participants. This oversight may lead to inaccurate conclusions and demand a reevaluation of existing research in the field. We formalize the mapping from the monetary payoff game to this actual game and delineate necessary and sufficient conditions for strategic equivalence to apply.

Keywords

Theory of experimentsStrategy methodSocial preferencesIntentionsDeontological motivations

JEL classification

D64: Altruism • Philanthropy • Intergenerational Transfers A13: Relation of Economics to Social Values C90: General
Type
Original Paper
Information
Journal of the Economic Science Association , Volume 10 , Issue 1 , June 2024 , pp. 15 - 30
Copyright
Copyright © The Author(s), under exclusive licence to Economic Science Association 2023.

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Footnotes

Daniel L. Chen acknowledges IAST funding from the French National Research Agency (ANR) under the Investments for the Future (Investissements d’Avenir) program, Grant ANR-17-EUR-0010. This research has benefited from financial support of the research foundation TSE-Partnership and ANITI funding, and of Alfred P. Sloan Foundation (Grant No. 2018-11245), European Research Council (Grant No. 614708), Swiss National Science Foundation (Grant Nos. 100018-152678 and 106014-150820), and Templeton Foundation (Grant No. 22420).

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