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Testing for unit roots in the possible presence of multiple trend breaks using minimum Dickey–Fuller statistics

David Harvey, Stephen Leybourne () and Robert Taylor

Journal of Econometrics, 2013, vol. 177, issue 2, 265-284

Abstract: Trend breaks appear to be prevalent in macroeconomic time series, and unit root tests therefore need to make allowance for these if they are to avoid the serious effects that unmodelled trend breaks have on power. Carrion-i-Silvestre et al. (2009) propose a pre-test-based approach which delivers near asymptotically efficient unit root inference both when breaks do not occur and where multiple breaks occur, provided the break magnitudes are fixed. Unfortunately, however, the fixed magnitude trend break asymptotic theory does not predict well the finite sample power functions of these tests, and power can be very low for the magnitudes of trend breaks typically observed in practice. In response to this problem we propose a unit root test that allows for multiple breaks in trend, obtained by taking the infimum of the sequence (across all candidate break points in a trimmed range) of local GLS detrended augmented Dickey–Fuller-type statistics. We show that this procedure has power that is robust to the magnitude of any trend breaks, thereby retaining good finite sample power in the presence of plausibly-sized breaks. We also demonstrate that, unlike the OLS detrended infimum tests of Zivot and Andrews (1992), these tests display no tendency to spuriously reject in the limit when fixed magnitude trend breaks occur under the unit root null.

Keywords: Unit root test; Multiple breaks in trend; Minimum Dickey–Fuller test; Local GLS detrending (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (45)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:177:y:2013:i:2:p:265-284

DOI: 10.1016/j.jeconom.2013.04.012

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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