Treatment Effects With Unobserved Heterogeneity: A Set Identification Approach. Issue 2 (2nd April 2016)

• Record Type: Journal Article
• Authors: Jun, Sung Jae; Lee, Yoonseok; Shin, Youngki
• Is Part Of: Journal of business & economic statistics. Volume 34:Issue 2(2016)
• Page Start: 302
• Page End: 311
• Publication Date: 2016-04-02
• Subjects: Dynamic treatment decisions -- Panel data -- Partial identification -- Stochastic dominance; Economics -- Statistical methods -- Periodicals; Commercial statistics -- Periodicals; Économie politique -- Méthodes statistiques -- Périodiques; Statistique commerciale -- Périodiques; 330.015195
• DOI: 10.1080/07350015.2015.1044008
• Languages: English
• ISSNs: 0735-0015

Abstract

Abstract : We propose the sharp identifiable bounds of the potential outcome distributions using panel data. We allow for the possibility that statistical randomization of treatment assignments is not achieved until unobserved heterogeneity is properly controlled for. We use certain stationarity assumptions to obtain the sharp bounds. Our approach allows for dynamic treatment decisions, where the current treatment decisions may depend on the past treatments or the past observed outcomes. As an empirical illustration, we study the effect of smoking during pregnancy on infant birthweight. We find that for the group of switchers the infant birthweight of a smoking mother is first-order stochastically dominated by that of a nonsmoking mother.