Quantile treatment effects in the regression discontinuity design

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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Year of publication:	2008
Authors:	Frölich, Markus ; Melly, Blaise
Publisher:	Bonn : Institute for the Study of Labor (IZA)
Subject:	Regression \| Nichtparametrisches Verfahren \| Kausalanalyse \| Theorie \| Quantile treatment effect \| causal effect \| endogeneity \| regression discontinuity

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Series:	IZA Discussion Papers ; 3638
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	576953458 [GVK] hdl:10419/34786 [Handle]
Classification:	C13 - Estimation
Source:	EconStor

Persistent link: https://www.econbiz.de/10010268551