Please Call Again: Correcting Nonresponse Bias in Treatment Effect Models

• 成果类型: Article
• 署名作者: Behaghel, Luc; Crepon, Bruno; Gurgand, Marc; Le Barbanchon, Thomas
• 署名单位: INRAE; Paris School of Economics; Institut Polytechnique de Paris; ENSAE Paris; Paris School of Economics; Centre National de la Recherche Scientifique (CNRS); Bocconi University; Bocconi University
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00497
• 发表日期: 2015-12
• 页码: 1070-1080
• 关键词: sample selection; identification; attrition

摘要

We propose a novel selectivity correction procedure to deal with survey attrition in treatment effect models, at the crossroads of the Heckit model and the bounding approach of Lee (2009). As a substitute for the instrument needed in sample selectivity correction models, we use information on the number of prior calls made to each individual before obtaining a response to the survey. We obtain sharp bounds to the average treatment effect on the common support of responding individuals. Because the number of prior calls brings information, we can obtain tighter bounds than in other nonparametric methods.