In: Journal of Business and Economic Statistics, 2019, vol. 37, no. 4, p. 736-748
This article 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...
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In: Foundations of Computational Mathematics, 2014, vol. 14, no. 3, p. 419-456
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In: Statistics and Computing, 2012, vol. 22, no. 2, p. 647-659
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In: Biometrika, 1993, vol. 80, no. 2, p. 373-383
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