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Coarsening Bias: How Coarse Treatment Measurement Upwardly Biases Instrumental Variable Estimates

Published online by Cambridge University Press:  04 January 2017

John Marshall
John Marshall*
Affiliation:
Department of Government, Harvard University, Cambridge, MA 02138
*
e-mail: [email protected]
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Abstract

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Political scientists increasingly use instrumental variable (IV) methods, and must often choose between operationalizing their endogenous treatment variable as discrete or continuous. For theoretical and data availability reasons, researchers frequently coarsen treatments with multiple intensities (e.g., treating a continuous treatment as binary). I show how such coarsening can substantially upwardly bias IV estimates by subtly violating the exclusion restriction assumption, and demonstrate that the extent of this bias depends upon the first stage and underlying causal response function. However, standard IV methods using a treatment where multiple intensities are affected by the instrument–even when fine-grained measurement at every intensity is not possible–recover a consistent causal estimate without requiring a stronger exclusion restriction assumption. These analytical insights are illustrated in the context of identifying the long-run effect of high school education on voting Conservative in Great Britain. I demonstrate that coarsening years of schooling into an indicator for completing high school upwardly biases the IV estimate by a factor of three.

Type
Articles
Information
Political Analysis , Volume 24 , Issue 2 , Spring 2016 , pp. 157 - 171
Copyright
Copyright © The Author 2016. Published by Oxford University Press on behalf of the Society for Political Methodology 

Footnotes

Authors' note: I thank Matt Blackwell, John Bullock, Anthony Fowler, Andy Hall, Torben Iversen, Horacio Larreguy, Rakeen Mabud, Daniel Moskowitz, Arthur Spirling, Brandon Stewart, Dustin Tingley, Tess Wise, the editor and two anonymous referees for illuminating discussions or useful comments. Replication materials are available online as Marshall (2016). Supplementary materials for this article are available on the Political Analysis Web site.

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Marshall supplementary material

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