Quotation Marchenko, Maria, Mammen, Enno. 2016. Weighted Average Estimator in Nonparametric Quantile Regression for the Data of Higher Dimensions.


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Abstract

The standard approach to the asymptotic analysis of nonparametric quantile regression is the use of the Bahadur expansion. However, it restricts the possible dimensionality of the covariate vector, given the optimal choice of bandwidth. We propose the alternative weighted average estimator for nonparametric quantile regression models, which allows to obtain inference results for the covariates of higher dimensions in nonparametric setting. The paper exploits alternative mathematical approach: we apply the higher order Edgeworth expansions to calculate the moments of Bahadur expansions of the nonparametric estimators. The proposed estimator can be further applied for the testing procedures and in some treatment settings, as well as in single-index and partially-linear models. We conduct a series of simulations that confirm our findings.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Working/discussion paper, preprint
Language English
Title Weighted Average Estimator in Nonparametric Quantile Regression for the Data of Higher Dimensions
Year 2016
URL https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxtYXJpYXZtYXJjaGVua298Z3g6MjdiYTFiY2JkODE1YjczYw
JEL C14, C31

Associations

People
Marchenko, Maria (Details)
External
Mammen, Enno (University of Heidelberg, Germany)
Organization
Institute for Labor Economics IN (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1162 Statistics (Details)
5323 Econometrics (Details)
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