Econometrica: Jan 2018, Volume 86, Issue 1

Identification of Treatment Effects under Conditional Partial Independence

DOI: 10.3982/ECTA14481
p. 317-351

Matthew A. Masten, Alexandre Poirier

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.

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