The Effect of Regression Design on Optimal Tests for Finding Break Positions

27 Pages Posted: 10 Nov 2016 Last revised: 1 Feb 2017

See all articles by Brendan P.M. McCabe

Brendan P.M. McCabe

University of Liverpool - Management School (ULMS)

Yao Rao

The University of Liverpool

Date Written: January 31, 2017

Abstract

In this paper, we derive an optimal test for determining break positions in Gaussian linear regressions. The procedure is an admissible rule in a multiple decision theory setting and the results are exact and valid in small samples. The analysis indicates that regression design can have a very significant effect on the ability of the optimal test to find the position of the break. Some regression designs make it all but impossible to successfully identify a break location in certain subsections of the sample span. Two graphical devices, the cq and ω-plots are available to identify those subsets of the sample span where locating a break position is difficult or impossible.

Keywords: Structural Change, CUSUM Test, Bayes Rules, Multiple Decision Theory, Regression

JEL Classification: C01, C12, C32, C44

Suggested Citation

McCabe, Brendan P.M. and Rao, Yao, The Effect of Regression Design on Optimal Tests for Finding Break Positions (January 31, 2017). Available at SSRN: https://ssrn.com/abstract=2867141 or http://dx.doi.org/10.2139/ssrn.2867141

Brendan P.M. McCabe (Contact Author)

University of Liverpool - Management School (ULMS) ( email )

Chatham Street
Liverpool, L69 7ZH
United Kingdom

Yao Rao

The University of Liverpool ( email )

Chatham Street
The University of Liverpool
Liverpool, L69 7ZH
United Kingdom

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