Treatment Evaluation With Multiple Outcome Periods Under Endogeneity and Attrition

• 成果类型: Article
• 署名作者: Froelich, Markus; Huber, Martin
• 署名单位: University of Mannheim; IZA Institute Labor Economics; University of St Gallen
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2014.896804
• 发表日期: 2014
• 页码: 1697-1711
• 关键词: principal stratification approach; job-training programs; panel-data; sample selection; semiparametric regression; nonparametric-estimation; randomized experiments; Causal Inference; propensity-score; sharp bounds

摘要

This article develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pretreatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment effect on the outcomes of compliers (the subpopulation whose treatment reacts on the instrument) in multiple periods based on inverse probability weighting. Treatment selection and attrition may depend on both observed characteristics and the unobservable compliance type, which is possibly related to unobserved factors. We also provide a simulation study and apply our methods to the evaluation of a policy intervention targeting college achievement, where we find that controlling for attrition considerably affects the effect estimates. Supplementary materials for this article are available online.