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Titel
Including covariates in the regression discontinuity design / Markus Frölich (Center for Evaluation and Development (C4ED), University of Mannheim, IZA and J-PAL), Martin Huber (University of Fribourg) ; IZA Institute of Labor Economics
VerfasserFrölich, Markus In der Gemeinsamen Normdatei der DNB nachschlagen ; Huber, Martin In der Gemeinsamen Normdatei der DNB nachschlagen
KörperschaftForschungsinstitut zur Zukunft der Arbeit In der Gemeinsamen Normdatei der DNB nachschlagen
ErschienenBonn, Germany : IZA Institute of Labor Economics, November 2017
Ausgabe
Elektronische Ressource
Umfang1 Online-Ressource (33 Seiten)
SerieDiscussion paper ; no. 11138
URNurn:nbn:de:hbz:5:2-142976 Persistent Identifier (URN)
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Including covariates in the regression discontinuity design [0.33 mb]
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Zusammenfassung

This paper proposes a fully nonparametric kernel method to account for observed covariates in regression discontinuity designs (RDD), which may increase precision of treatment effect estimation. It is shown that conditioning on covariates reduces the asymptotic variance and allows estimating the treatment effect at the rate of one-dimensional nonparametric regression, irrespective of the dimension of the continuously distributed elements in the conditioning set. Furthermore, the proposed method may decrease bias and restore identification by controlling for discontinuities in the covariate distribution at the discontinuity threshold, provided that all relevant discontinuously distributed variables are controlled for. To illustrate the estimation approach and its properties, we provide a simulation study and an empirical application to an Austrian labor market reform.