Testing for Structural Breaks at Unknown Time: A Steeplechase

Makram El-Shagi and Sebastian Giesen

Computational Economics, 2013, vol. 41, issue 1, 123 pages

Abstract: This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975 ) and Zeileis (Stat Pap 45(1):123–131, 2004 ), Nyblom (J Am Stat Assoc 84(405):223–230, 1989 ) and Hansen (J Policy Model 14(4):517–533, 1992 ), and Andrews et al. (J Econ 70(1):9–38, 1996 ). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper. Copyright Springer Science+Business Media, LLC. 2013

Keywords: Structural breaks; Small sample Monte Carlo study; Size adjusted power; C12; C15 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (7)

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Working Paper: Testing for Structural Breaks at Unknown Time: A Steeplechase (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:kap:compec:v:41:y:2013:i:1:p:101-123

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DOI: 10.1007/s10614-011-9271-1

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