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Structural Change and the Problem of Phantom Break Locations

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  • Yao Rao
  • Brendan McCabe

Abstract

It is well known, in structural break problems, that it is much easier to detect the existence of a break in a data set than to determine the location of such a break in the sample span. This paper investigates why, in the context of Gaussian linear regressions, using a decision theory framework. The nub of the problem, even for moderately sized breaks, is that the posterior probability distribution of the possible break points is usually not very informative about the true break location. The information content is measured here by a proper scoring rule. Hence, even a locally optimal break location procedure, as introduced here, is ineffective. In the regression context, it turns out to be quite common, indeed the norm, for break location procedures to misidentify the true break position up to 100% of the time. Unfortunately too, the magnitude of the di§erence between the misidentified and true break locations is usually not small.

Suggested Citation

  • Yao Rao & Brendan McCabe, 2018. "Structural Change and the Problem of Phantom Break Locations," Working Papers 20185, University of Liverpool, Department of Economics.
    • Handle: RePEc:liv:livedp:20185
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    References listed on IDEAS

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    Keywords

    CUSUM test; Phantom Break Locations; Structural change;
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