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Quantile Treatment Effects in the Regression Discontinuity Design Author info | Abstract | Publisher info | Download info | Related research | Statistics Frölich, Markus () (University of Mannheim)
Melly, Blaise () (Brown University)
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This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design (RDD) and proposes simple estimators. Quantile treatment effects are a very helpful tool to characterize the effects of certain interventions on the outcome distribution. The distributional impacts of social programs such as welfare, education, training programs and unemployment insurance are of large interest to economists.
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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number
3638.
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Length: 14 pages
Date of creation: Aug 2008Date of revision:
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Keywords: quantile treatment effect causal effect endogeneity regression discontinuity Other versions of this item:
Find related papers by JEL classification: C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation 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
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"Does Corporate Governance Predict Firms' Market Values? Evidence from Korea ,"
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"The Central Role of Noise in Evaluating Interventions That Use Test Scores to Rank Schools ,"
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