Ivmte: An R Package for Implementing Marginal Treatment Effect Methods

Abstract

Instrumental variable (IV) strategies are widely used to estimate causal effects in
economics, political science, epidemiology, psychology, and other fields. When there is
unobserved heterogeneity in causal effects, standard linear IV estimators only represent
effects for complier subpopulations (Imbens and Angrist, 1994). Marginal treatment
effect (MTE) methods (Heckman and Vytlacil, 1999, 2005) allow researchers to use
additional assumptions to extrapolate beyond complier subpopulations. We discuss a
flexible framework for MTE methods based on linear regression and the generalized
method of moments. We show how to implement the framework using the ivmte
package for R.