On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference

Abstract

Nonparametric methods play a central role in modern empirical work. While they provide inference procedures that are more robust to parametric misspecification bias, they may be quite sensitive to tuning parameter choices. We study the effects of bias correction on confidence interval coverage in the context of kernel density and local polynomial regression… (More)

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Cite this paper

@inproceedings{Calnico2017OnTE, title={On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference}, author={Sebasti{\'a}n Cal{\'o}nico and Matias D. Cattaneo and Max H. Farrell}, year={2017} }