Allison J. Sovey is a Ph.D. student in Political Science, Yale University, 115 Prospect Street, Rosenkranz Hall, Room 437, New Haven, CT 06520 (email@example.com). Donald P. Green is A. Whitney Griswold Professor of Political Science, Yale University, 115 Prospect Street, Rosenkranz Hall, Room 437, New Haven, CT 06520 (firstname.lastname@example.org).
Instrumental Variables Estimation in Political Science: A Readers’ Guide
Article first published online: 30 SEP 2010
©2010, Midwest Political Science Association
American Journal of Political Science
Volume 55, Issue 1, pages 188–200, January 2011
How to Cite
Sovey, A. J. and Green, D. P. (2011), Instrumental Variables Estimation in Political Science: A Readers’ Guide. American Journal of Political Science, 55: 188–200. doi: 10.1111/j.1540-5907.2010.00477.x
An earlier version of this article was prepared for the 26th Annual Society for Political Methodology Summer Conference, Yale University. We are grateful to Jake Bowers, John Bullock, Daniel Butler, Thad Dunning, Andrew Gelman, Holger Kern, and Jan Box-Steffensmeier for helpful comments. We also thank Peter Aronow and Mario Chacon, who assisted us in data collection and provided valuable suggestions. This project was funded by support from Yale’s Institution for Social and Policy Studies. We are responsible for any errors.
- Issue published online: 7 JAN 2011
- Article first published online: 30 SEP 2010
The use of instrumental variables regression in political science has evolved from an obscure technique to a staple of the political science tool kit. Yet the surge of interest in the instrumental variables method has led to implementation of uneven quality. After providing a brief overview of the method and the assumptions on which it rests, we chart the ways in which these assumptions are invoked in practice in political science. We review more than 100 articles published in the American Journal of Political Science, the American Political Science Review, and World Politics over a 24-year span. We discuss in detail two noteworthy applications of instrumental variables regression, calling attention to the statistical assumptions that each invokes. The concluding section proposes reporting standards and provides a checklist for readers to consider as they evaluate applications of this method.