Treatment Effects with Unobserved Heterogeneity: A Set Identification Approach

Yoonseok Lee, Sung Jae Jun and Youngki Shin
Additional contact information
Youngki Shin: University of Western Ontario

No 169, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: We propose the sharp identifiable bounds of the distribution functions of potential outcomes using a panel with fixed T. We allow for the possibility that the statistical randomization of treatment assignments is not achieved until unobserved heterogeneity is properly controlled for. We use certain stationarity assumptions to obtain the bounds. Dynamics in the treatment decisions is allowed as long as the stationarity assumptions are satisfied. In particular, we present an example where our assumptions are satisfied and the treatment decision of the present time may depend on the treatments and the observed outcomes of the past. As an empirical illustration we study the effect of smoking during pregnancy on infant birth weights. We found that for the group of switchers the birth weight with smoking is first order stochastically dominated by that with non-smoking.

Keywords: Treatment Effects; Dynamic Treatment Decisions; Partial Identification; Unobserved Heterogeneity; Stochastic Dominance; Panel Data (search for similar items in EconPapers)
JEL-codes: C12 C21 C23 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2014-07
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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https://surface.syr.edu/cpr/201/ (application/pdf)

Related works:
Journal Article: Treatment Effects With Unobserved Heterogeneity: A Set Identification Approach (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:169

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