Publication Type
Working Paper
Version
publishedVersion
Publication Date
11-2002
Abstract
In this paper we propose an analytically corrected plug-in method for constructing confidence intervals of the conditional quantiles of a response variable with data transformation. The method can be applied to (i) a general conditional regression quantile, (ii) a general monotonic transformation, and (iii) a transformation model with heteroscedastic errors. Our results extend those in Yang (2002a), in which the median of a response variable under the Box-Cox transformation with homoscedastic errors was considered. A Monte Carlo experiment is conducted to compare the performance of the corrected plug-in method, the plug-in method and the delta method. The corrected plug-in method provides superior results over the other two methods.
Keywords
Analytical calibration, Box-Cox transformation, Heteroscedasticity, Plug-in quantile limits, Regression quantile
Discipline
Econometrics
Research Areas
Econometrics
Volume
22-2002
First Page
1
Last Page
35
Publisher
SMU Economics and Statistics Working Paper Series, No. 22-2002
City or Country
Singapore
Citation
YANG, Zhenlin and TSE, Yiu Kuen.
A Corrected Plug-in Method for the Quantile Confidence Interval of a Transformed Regression. (2002). 22-2002, 1-35.
Available at: https://ink.library.smu.edu.sg/soe_research/697
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.
Comments
Published in Journal of Business & Economic Statistics, Vol. 25, No. 3 (Jul., 2007), pp. 356-376, https://doi.org/10.1198/073500106000000684