Identification of Treatment Effects Under Conditional Partial Independence

Matthew Masten and Alexandre Poirier

Econometrica, 2018, vol. 86, issue 1, 317-351

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.

Date: 2018
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https://doi.org/10.3982/ECTA14481

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Working Paper: Identification of Treatment Effects under Conditional Partial Independence (2017)
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