Monitoring parameter changes in models with a trend

We develop a CUSUM-type monitoring procedure based on the ordinary least squares residuals for detecting structural changes in models with a trend. A proper boundary function is designed to control the size. We derive the limiting null distribution and the consistency of the procedure under the alte...

Full description

Saved in:
Bibliographic Details
Published in:Journal of statistical planning and inference 2020-07, Vol.207, p.288-319
Main Authors: Jiang, Peiyun, Kurozumi, Eiji
Format: Article
Language:English
Subjects:
CUSUM test
Fluctuation test
Sequential test
Structural change
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We develop a CUSUM-type monitoring procedure based on the ordinary least squares residuals for detecting structural changes in models with a trend. A proper boundary function is designed to control the size. We derive the limiting null distribution and the consistency of the procedure under the alternative. In addition, we derive the asymptotic distribution of the delay time for the CUSUM procedure as well as the fluctuation procedure proposed by Qi etal. (2016). The simulation and empirical results indicate that although neither procedure is uniformly superior to the other, the CUSUM test is more suitable for an early break. •We develop a CUSUM monitoring test to detect break in models with a trend.•The proposed test has good size and high power.•We derive the asymptotic distribution of the delay times.•We extend the CUSUM test to models with higher order polynomial trends.
ISSN:0378-3758
1873-1171
DOI:10.1016/j.jspi.2020.01.004