Publication Type
Journal Article
Version
publishedVersion
Publication Date
7-2008
Abstract
We define a nonparametric prewhitening method for estimating conditional quantiles based on local linear quantile regression. We characterize the bias, variance and asymptotic normality of the proposed estimator. Under weak conditions our estimator can achieve bias reduction and have the same variance as the local linear quantile estimators. A small set of Monte Carlo simulations is carried out to illustrate the performance of our estimators. An application to US gross domestic product data demonstrates the usefulness of our methodology.
Keywords
Local linear quantile regression, nonparametric quantile regression, prediction interval, prewhitening estimator, weighted Nadaraya-Watson estimator
Discipline
Econometrics
Research Areas
Econometrics
Publication
Statistica Sinica
Volume
18
Issue
3
First Page
1131
Last Page
1152
ISSN
1017-0405
Publisher
Academia Sinica
Citation
SU, Liangjun and ULLAH, Aman.
Nonparametric Prewhitening Estimators for Conditional Quantiles. (2008). Statistica Sinica. 18, (3), 1131-1152.
Available at: https://ink.library.smu.edu.sg/soe_research/436
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://www3.stat.sinica.edu.tw/statistica/oldpdf/A18n317.pdf