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dc.contributor.authorFrölich, Markusen_US
dc.contributor.authorMelly, Blaiseen_US
dc.date.accessioned2008-09-23en_US
dc.date.accessioned2010-07-07T11:29:19Z-
dc.date.available2010-07-07T11:29:19Z-
dc.date.issued2008en_US
dc.identifier.piurn:nbn:de:101:1-20080820247en_US
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_US
dc.language.isoengen_US
dc.publisherIZA Bonnen_US
dc.relation.ispartofseriesIZA Discussion Papers 3638en_US
dc.subject.jelC13en_US
dc.subject.ddc330en_US
dc.subject.keywordQuantile treatment effecten_US
dc.subject.keywordcausal effecten_US
dc.subject.keywordendogeneityen_US
dc.subject.keywordregression discontinuityen_US
dc.subject.stwRegressionen_US
dc.subject.stwNichtparametrisches Verfahrenen_US
dc.subject.stwKausalanalyseen_US
dc.subject.stwTheorieen_US
dc.titleQuantile treatment effects in the regression discontinuity designen_US
dc.typeWorking Paperen_US
dc.identifier.ppn576953458en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
Appears in Collections:IZA Discussion Papers, Forschungsinstitut zur Zukunft der Arbeit (IZA)

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