Identification of Treatment Effects Under Conditional Partial Independence

• 成果类型: Article
• 署名作者: Masten, Matthew A.; Poirier, Alexandre
• 署名单位: Duke University; University of Iowa
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA14481
• 发表日期: 2018
• 页码: 317-351
• 关键词: sensitivity; variables; selection; regressions

摘要

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.