Identification of Treatment Effects Under Conditional Partial Independence

Published

Journal Article

© 2018 The Econometric Society 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 1, 2018

Published In

Volume / Issue

  • 86 / 1

Start / End Page

  • 317 - 351

Electronic International Standard Serial Number (EISSN)

  • 1468-0262

International Standard Serial Number (ISSN)

  • 0012-9682

Digital Object Identifier (DOI)

  • 10.3982/ECTA14481

Citation Source

  • Scopus