A Corrected Plug-in Method for Quantile Interval Construction through a Transformed Regression

A Corrected Plug-in Method for Quantile Interval Construction through a Transformed Regression

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 anal...

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Bibliographic Details
Main Authors: YANG, Zhenlin, TSE, Yiu Kuen
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2007
Subjects:
Analytical correction
Finite-sample performance
Heteroscedasticity
Living standards in South Africa
Transformation
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/352
https://ink.library.smu.edu.sg/context/soe_research/article/1351/viewcontent/YangTse_JBES2007at.pdf
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Institution: Singapore Management University
Language: English
Description
Summary: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]

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