Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/34786 
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dc.contributor.authorFrölich, Markusen
dc.contributor.authorMelly, Blaiseen
dc.date.accessioned2008-09-23-
dc.date.accessioned2010-07-07T11:29:19Z-
dc.date.available2010-07-07T11:29:19Z-
dc.date.issued2008-
dc.identifier.piurn:nbn:de:101:1-20080820247en
dc.identifier.urihttp://hdl.handle.net/10419/34786-
dc.description.abstractThis 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.en
dc.language.isoengen
dc.publisher|aInstitute for the Study of Labor (IZA) |cBonnen
dc.relation.ispartofseries|aIZA Discussion Papers |x3638en
dc.subject.jelC13en
dc.subject.ddc330en
dc.subject.keywordQuantile treatment effecten
dc.subject.keywordcausal effecten
dc.subject.keywordendogeneityen
dc.subject.keywordregression discontinuityen
dc.subject.stwRegressionen
dc.subject.stwNichtparametrisches Verfahrenen
dc.subject.stwKausalanalyseen
dc.subject.stwTheorieen
dc.titleQuantile treatment effects in the regression discontinuity design-
dc.type|aWorking Paperen
dc.identifier.ppn576953458en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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