Is MORE LESS? The role of data augmentation in testing for structural breaks

Yao Rao () and Brendan McCabe

Economics Letters, 2017, vol. 155, issue C, 131-134

Abstract: In this paper, we examine the impact of increasing the size of a data set in detecting structural breaks. Based on an empirical application, supported by theoretical justification and a simulation experiment, we find that larger sample sizes may make it more rather than less difficult to determine the existence of a structural break.

Keywords: Structural change; CUSUM test; Regression (search for similar items in EconPapers)
JEL-codes: C01 C15 C44 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:155:y:2017:i:c:p:131-134

DOI: 10.1016/j.econlet.2017.03.033

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