Treatment Effects with Multidimensional Unobserved Heterogeneity: Identification of the Marginal Treatment Effect

TL;DR

This paper develops a method to identify marginal treatment effects in models with multiple treatments and unobserved heterogeneity, extending previous binary treatment frameworks to more complex scenarios.

Contribution

It introduces a generalized MTE framework for multinomial choice models, allowing for the analysis of treatment effects among individuals with specific preference structures.

Findings

Provides sufficient conditions for identification of MTE with multivalued treatments.

Extends the binary MTE concept to multinomial choice models.

Enables estimation of treatment effects for individuals with specific preference orders.

Abstract

This paper establishes sufficient conditions for the identification of the marginal treatment effects with multivalued treatments. Our model is based on a multinomial choice model with utility maximization. Our MTE generalizes the MTE defined in Heckman and Vytlacil (2005) in binary treatment models. As in the binary case, we can interpret the MTE as the treatment effect for persons who are indifferent between two treatments at a particular level. Our MTE enables one to obtain the treatment effects of those with specific preference orders over the choice set. Further, our results can identify other parameters such as the marginal distribution of potential outcomes.