Title: Identification of Treatment Effects under Conditional Partial Independence,
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.