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The Commensurability Problem: Conceptual Difficulties in Estimating the Effect of Behavior on Behavior

Published online by Cambridge University Press:  03 February 2020

ETHAN BUENO DE MESQUITA Open the ORCID record for ETHAN BUENO DE MESQUITA [Opens in a new window]  and
SCOTT A. TYSON Open the ORCID record for SCOTT A. TYSON [Opens in a new window]
ETHAN BUENO DE MESQUITA*
Affiliation:
University of Chicago
SCOTT A. TYSON*
Affiliation:
University of Rochester
*
*Ethan Bueno de Mesquita, Harris School, University of Chicago, [email protected].
†Scott A. Tyson, Department of Political Science, and W. Allen Wallis Institute of Political Economy, University of Rochester, [email protected].
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Abstract

We pose the commensurability problem: When do the estimates generated by actual research designs correspond to quantities of theoretical interest? We study this question in settings where both treatment and outcome are behavior and the treatment effect of interest is decomposable into direct and informational channels. We establish two results. First, the quantity estimated by an actual research design is only commensurate with the total effect in the ideal experiment if treatment status in the research design is a sufficient statistic for the decision-makers’ information. Second, a research design corresponding to a nonideal experiment isolates just the direct effect in the ideal experiment if two conditions hold: (i) there is no information effect in the nonideal experiment and (ii) the decision-maker’s response function is additively separable in treatment and information. We apply our results to three substantive literatures: the efficacy of protest, the empowerment of female candidates, and indiscriminate violence in counterinsurgency.

Type
Research Article
Information
American Political Science Review , Volume 114 , Issue 2 , May 2020 , pp. 375 - 391
Copyright
Copyright © American Political Science Association 2020 

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Footnotes

We have benefited from comments by Scott Ashworth, Mark Fey, Anthony Fowler, Glyn Morgan, Cyrus Samii, and Stephane Wolton, and participants in the Princeton Institutions & Inference Conference and the Petralia Sottana Applied Economics Workshop.

References

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