Saved in:
Bibliographic Details
Main Authors: Pretorius, Charl, Roodt, Heinrich
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.00598
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866918485533130752
author Pretorius, Charl
Roodt, Heinrich
author_facet Pretorius, Charl
Roodt, Heinrich
contents New procedures for detecting a change in the cross-sectional mean of panel data are proposed. The procedures rely on estimating nuisance parameters using certain cross-sectional means across panels using a weighted least squares regression. In the case of weak cross-sectional dependence between panels, we show how test statistics can be constructed to have a limit null distribution not depending on any choice of bandwidths typically needed to estimate the long-run variances of the panel errors. The theoretical assertions are derived for general choices of the regression weights, and it is shown that consistent test procedures can be obtained from the proposed process. The theoretical results are extended to the case where strong cross-sectional dependence exist between panels. The paper concludes with a numerical study illustrating the behavior of several special cases of the test procedure in finite samples.
format Preprint
id arxiv_https___arxiv_org_abs_2510_00598
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Weighted Regression Approach to Break-Point Detection in Panel Data
Pretorius, Charl
Roodt, Heinrich
Methodology
Statistics Theory
62G10
New procedures for detecting a change in the cross-sectional mean of panel data are proposed. The procedures rely on estimating nuisance parameters using certain cross-sectional means across panels using a weighted least squares regression. In the case of weak cross-sectional dependence between panels, we show how test statistics can be constructed to have a limit null distribution not depending on any choice of bandwidths typically needed to estimate the long-run variances of the panel errors. The theoretical assertions are derived for general choices of the regression weights, and it is shown that consistent test procedures can be obtained from the proposed process. The theoretical results are extended to the case where strong cross-sectional dependence exist between panels. The paper concludes with a numerical study illustrating the behavior of several special cases of the test procedure in finite samples.
title A Weighted Regression Approach to Break-Point Detection in Panel Data
topic Methodology
Statistics Theory
62G10
url https://arxiv.org/abs/2510.00598