Identification of Treatment Effects Under Conditional Partial Independence

Monday, January 8, 2018
Matthew A. Masten
Alexandre Poirier

Abstract

Conditional independence of treatment assignment from potential outcomes is a commonly used but nonrefutable assumption. We derive identified sets for various treatment effect parameters under nonparametric deviations from this conditional independence assumption. These deviations are defined via a conditional treatment assignment probability, which makes it straightforward to interpret. Our results can be used to assess the robustness of empirical conclusions obtained under the baseline conditional independence assumption.

Citation: 

Masten, Matthew A. and Alexandre Poirier. 2018. "Identification of Treatment Effects Under Conditional Partial Independence" Econometrica, 86(1): 317-51

Identification of Treatment Effects Under Conditional Partial Independence