Identification of Treatment Effects Under Conditional Partial Independence

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Masten, MA; Poirier, A

Published Date

  • January 2018

Published In

  • Econometrica

Volume / Issue

  • 86 / 1

Start / End Page

  • 317 - 351