ivmte: An R Package for Implementing Marginal Treatment Effect Methods

Joshua Shea, Alexander Torgovitsky

Research output: Working paper


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.
Original languageEnglish (US)
Number of pages38
StatePublished - Sep 3 2021
Externally publishedYes


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