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Beyond LATE: Estimation of the Average Treatment Effect with an Instrumental Variable

Published online by Cambridge University Press:  04 January 2017

Peter M. Aronow  and
Allison Carnegie
Peter M. Aronow*
Affiliation:
Department of Political Science, Yale University, New Haven, CT 06520
Allison Carnegie
Affiliation:
Department of Political Science, Princeton University, Princeton, NJ 08540, and Department of Political Science, University of Chicago, Chicago, IL 60637 e-mail: [email protected]
*
e-mail: [email protected] (corresponding author)
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Abstract

Political scientists frequently use instrumental variables (IV) estimation to estimate the causal effect of an endogenous treatment variable. However, when the treatment effect is heterogeneous, this estimation strategy only recovers the local average treatment effect (LATE). The LATE is an average treatment effect (ATE) for a subset of the population: units that receive treatment if and only if they are induced by an exogenous IV. However, researchers may instead be interested in the ATE for the entire population of interest. In this article, we develop a simple reweighting method for estimating the ATE, shedding light on the identification challenge posed in moving from the LATE to the ATE. We apply our method to two published experiments in political science in which we demonstrate that the LATE has the potential to substantively differ from the ATE.

Type
Research Article
Information
Political Analysis , Volume 21 , Issue 4 , Autumn 2013 , pp. 492 - 506
Copyright
Copyright © The Author 2013. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Authors' note: The replication archive for this article is available online at Aronow and Carnegie (2013). The authors acknowledge support from the Yale University Faculty of Arts and Sciences High-Performance Computing facility and staff. Helpful comments from Jake Bowers, John Bullock, Dan Butler, Lara Chausow, Adam Dynes, Ivan Fernandez-Val, Adam Glynn, Holger Kern, Malte Lierl, Mary McGrath, Joel Middleton, Cyrus Samii, two anonymous reviewers, and the participants of the Yale American Politics and Public Policy Workshop, the New Faces in Political Methodology Conference, and the Midwest Political Science Association Conference are greatly appreciated. We also thank Jonathan Katz for helpful editorial guidance. Special thanks to Bethany Albertson, Adria Lawrence, and David Nickerson for generous data sharing and to Dean Eckles, Alan Gerber, Don Green, Greg Huber, and Ken Scheve for particularly helpful conversations. All remaining errors are our own. Supplementary materials for this article are available on the Political Analysis Web site.

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