Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2007
Abstract
We propose a corrected plug-in method for constructing confidence intervals of the conditional quantiles of an original response variable through a transformed regression with heteroscedastic errors. The interval is easy to compute. Factors affecting the magnitude of the correction are examined analytically through the special case of Box-Cox regression. Monte Carlo simulations show that the new method works well in general and is superior over the commonly used delta method and the quantile regression method. An empirical application is presented. [PUBLICATION ABSTRACT]
Keywords
Analytical correction, Finite-sample performance, Heteroscedasticity, Living standards in South Africa, Transformation
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Business and Economic Statistics
Volume
25
Issue
3
First Page
356
Last Page
376
ISSN
0735-0015
Identifier
10.1198/073500106000000684
Publisher
American Statistical Association
Citation
YANG, Zhenlin and TSE, Yiu Kuen.
A Corrected Plug-in Method for Quantile Interval Construction through a Transformed Regression. (2007). Journal of Business and Economic Statistics. 25, (3), 356-376.
Available at: https://ink.library.smu.edu.sg/soe_research/352
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1198/073500106000000684