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Hauptverfasser: Yang, Wenzhi, Xu, Yueting, Shi, Xiaoping, Li, Qiong
Format: Preprint
Veröffentlicht: 2026
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2603.12561
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author Yang, Wenzhi
Xu, Yueting
Shi, Xiaoping
Li, Qiong
author_facet Yang, Wenzhi
Xu, Yueting
Shi, Xiaoping
Li, Qiong
contents This paper investigates change-point of variance in panel data models with time series of $α$-mixing. Based on the cumulative sum (CUSUM) method and the individual differences, we construct a CUSUM test for panel data models to detect variance changes. Under the null hypothesis, we derive the limit distribution of this test, which can be used to detect the change-point of variance. Under the alternative hypothesis, the limit behavior of the CUSUM test is also derived. To validate the performance of the test, we conducted simulation analyses on with Gaussian and Gamma errors. The results demonstrate that this testing method significantly outperforms existing approaches, particularly in detecting sparse variance changes. Finally, we conducted a practical case study using panel data from the Shanghai Shenzhen CSI 300 Index Components. Not only did we successfully identify the change-points of variance, but we also delved deeper into the underlying economic drivers behind these changes.
format Preprint
id arxiv_https___arxiv_org_abs_2603_12561
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Consistent and powerful CUSUM change-point test for panel data with changes in variance
Yang, Wenzhi
Xu, Yueting
Shi, Xiaoping
Li, Qiong
Methodology
This paper investigates change-point of variance in panel data models with time series of $α$-mixing. Based on the cumulative sum (CUSUM) method and the individual differences, we construct a CUSUM test for panel data models to detect variance changes. Under the null hypothesis, we derive the limit distribution of this test, which can be used to detect the change-point of variance. Under the alternative hypothesis, the limit behavior of the CUSUM test is also derived. To validate the performance of the test, we conducted simulation analyses on with Gaussian and Gamma errors. The results demonstrate that this testing method significantly outperforms existing approaches, particularly in detecting sparse variance changes. Finally, we conducted a practical case study using panel data from the Shanghai Shenzhen CSI 300 Index Components. Not only did we successfully identify the change-points of variance, but we also delved deeper into the underlying economic drivers behind these changes.
title Consistent and powerful CUSUM change-point test for panel data with changes in variance
topic Methodology
url https://arxiv.org/abs/2603.12561