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Estimating signaling games in international relations: problems and solutions

Published online by Cambridge University Press:  09 December 2019

Casey Crisman-Cox Open the ORCID record for Casey Crisman-Cox [Opens in a new window]  and
Michael Gibilisco
Casey Crisman-Cox*
Affiliation:
Department of Political Science, Texas A&M University, College Station, TX, USA
Michael Gibilisco
Affiliation:
Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA
*
*Corresponding author. Email: [email protected]
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Abstract

Signaling games are central to political science but often have multiple equilibria, leading to no definitive prediction. We demonstrate that these indeterminacies create substantial problems when fitting theory to data: they lead to ill-defined and discontinuous likelihoods even if the game generating the data has a unique equilibrium. In our experiments, currently used techniques frequently fail to uncover the parameters of the canonical crisis-signaling game, regardless of sample size and number of equilibria in the data generating process. We propose three estimators that remedy these problems, outperforming current best practices. We fit the signaling model to data on economic sanctions. Our solutions find a novel U-shaped relationship between audience costs and the propensity for leaders to threaten sanctions, which current best practices fail to uncover.

Keywords

Maximum likelihood estimation (MLE)Structural estimationCrisis-signalingEconomic sanctions
Type
Original Article
Information
Political Science Research and Methods , Volume 9 , Issue 3 , July 2021 , pp. 565 - 582
Copyright
Copyright © The European Political Science Association 2019

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Supplementary material: Link

Crisman-Cox and Gibilisco Dataset

Dataset

https://doi.org/10.7910/DVN/1JBNDC
Link
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Crisman-Cox and Gibilisco supplementary material

Crisman-Cox and Gibilisco supplementary material

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