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Efficient Semiparametric Estimation of Quantile Treatment Effects Author info | Abstract | Publisher info | Download info | Related research | Statistics Sergio Firpo
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This paper presents calculations of semiparametric efficiency bounds for quantile treatment effects parameters when selection to treatment is based on observable characteristics. The paper also presents three estimation procedures for these parameters, all of which have two steps: a nonparametric estimation and a computation of the difference between the solutions of two distinct minimization problems. Root-$N$ consistency, asymptotic normality, and the achievement of the semiparametric efficiency bound is shown for one of the three estimators. In the final part of the paper, an empirical application to a job training program reveals the importance of heterogeneous treatment effects, showing that for this program the effects are concentrated in the upper quantiles of the earnings distribution.
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Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number
605.
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Date of creation: 11 Aug 2004Date of revision:
Handle: RePEc:ecm:nasm04:605Contact details of provider: Phone: 1 212 998 3820 Fax: 1 212 995 4487 Email: Web page: http://www.econometricsociety.org/pastmeetings.asp More information through EDIRC
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Keywords: Quantile Treatment Effects Propensity Score Semiparametric Efficiency Bounds Efficient Estimation Semiparametric Estimation Other versions of this item:
Find related papers by JEL classification: C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
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