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Identification of Treatment Effects under Conditional Partial Independence (1707.09563v1)
Published 29 Jul 2017 in stat.ME and econ.EM
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.