Identification of Treatment Effects Under Conditional Partial Independence
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.