Saved in:
Bibliographic Details
Main Authors: Zhou, Jing, Zou, Hui
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2311.05056
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911641186074624
author Zhou, Jing
Zou, Hui
author_facet Zhou, Jing
Zou, Hui
contents We propose a high-dimensional extension of the heteroscedasticity test proposed in Newey and Powell (1987). Our test is based on expectile regression in the proportional asymptotic regime where n/p \to δ\in (0,1]. The asymptotic analysis of the test statistic uses the Approximate Message Passing (AMP) algorithm, from which we obtain the limiting distribution of the test and establish its asymptotic power. The numerical performance of the test is validated through an extensive simulation study. As real-data applications, we present the analysis based on ``international economic growth" data (Belloni et al., 2011), which is found to be homoscedastic, and ``supermarket" data (Lan et al., 2016), which is found to be heteroscedastic.
format Preprint
id arxiv_https___arxiv_org_abs_2311_05056
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle High-dimensional Newey-Powell Test Via Approximate Message Passing
Zhou, Jing
Zou, Hui
Methodology
We propose a high-dimensional extension of the heteroscedasticity test proposed in Newey and Powell (1987). Our test is based on expectile regression in the proportional asymptotic regime where n/p \to δ\in (0,1]. The asymptotic analysis of the test statistic uses the Approximate Message Passing (AMP) algorithm, from which we obtain the limiting distribution of the test and establish its asymptotic power. The numerical performance of the test is validated through an extensive simulation study. As real-data applications, we present the analysis based on ``international economic growth" data (Belloni et al., 2011), which is found to be homoscedastic, and ``supermarket" data (Lan et al., 2016), which is found to be heteroscedastic.
title High-dimensional Newey-Powell Test Via Approximate Message Passing
topic Methodology
url https://arxiv.org/abs/2311.05056