IDENTIFYING TREATMENT EFFECTS UNDER DATA COMBINATION

• 成果类型: Article
• 署名作者: Fan, Yanqin; Sherman, Robert; Shum, Matthew
• 署名单位: University of Washington; University of Washington Seattle; California Institute of Technology
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA10601
• 发表日期: 2014
• 页码: 811-822
• 关键词: propensity score; distributions; quantile; CHOICE

摘要

We consider the identification of counterfactual distributions and treatment effects when the outcome variables and conditioning covariates are observed in separate data sets. Under the standard selection on observables assumption, the counterfactual distributions and treatment effect parameters are no longer point identified. However, applying the classical monotone rearrangement inequality, we derive sharp bounds on the counterfactual distributions and policy parameters of interest.