Nonparametric identification and estimation of sample selection models under symmetry
Yahong Zhou and
Journal of Econometrics, 2018, vol. 202, issue 2, 148-160
Under a conditional mean restriction Das et al. (2003) considered nonparametric estimation of sample selection models. However, their method can only identify the outcome regression function up to a constant. In this paper we strengthen the conditional mean restriction to a symmetry restriction under which selection biases due to selection on unobservables can be eliminated through proper matching of propensity scores; consequently we are able to identify and obtain consistent estimators for the average treatment effects and the structural regression functions. The results from a simulation study suggest that our estimators perform satisfactorily.
Keywords: Sample selection; Nonparametric estimation; Symmetry (search for similar items in EconPapers)
JEL-codes: C13 C14 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:202:y:2018:i:2:p:148-160
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