Instrumental Variables Estimation in Political Science: A Readers’ Guide

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. Political scientists frequently seek to gauge the ef-fects of independent variables that are measuredwith error or are systematically related to unob-served determinants of the dependent variable. Recogniz-ing that ordinary least squares regression performs poorly in these situations, an increasing number of political sci-entists since the 1970s have turned to instrumental vari-ables (IV) regression. IV regression in effect replaces the problematic independent variable with a proxy variable