Instrumental variable (IV) strategies are widely used to estimate causal effects in economics, political science, epidemiology, and many 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 these subpopulations. In this paper, we introduce the ivmte package (Shea and Torgovitsky, 2019), which provides a flexible framework for implementing MTE methods in both point identified and partially identified settings.

More on this topic

BFI Working Paper·Apr 22, 2025

The Law and Economics of Lawyers: Evidence from the Revolving Door in China’s Judicial System

John Zhuang Liu, Wenwei Peng, Shaoda Wang, and Daniel Xu
Topics: Uncategorized
BFI Working Paper·Apr 14, 2025

Paths to the Periphery

James Robinson
Topics: Uncategorized
BFI Working Paper·Apr 7, 2025

The Conflict-of-Interest Discount in the Marketplace of Ideas

John M. Barrios, Filippo Lancieri, Joshua Levy, Shashank Singh, Tommaso Valletti, and Luigi Zingales
Topics: Uncategorized