Testing for a Change in Mean under Fractional Integration

Fabrizio Iacone, Stephen Leybourne () and Robert Taylor A.M.
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Robert Taylor A.M.: Essex Business School, University of Essex, Colchester, UK

Journal of Time Series Econometrics, 2017, vol. 9, issue 1, 8

Abstract: We consider testing for the presence of a change in mean, at an unknown point in the sample, in data that are possibly fractionally integrated, and of unknown order. This testing problem has recently been considered in a number of papers, most notably Shao (2011, “A Simple Test of Changes in Mean in the Possible Presence of Long-Range Dependence.” Journal of Time Series Analysis 32:598–606) and Iacone, Leybourne, and Taylor (2013b, “A Fixed-b Test for a Break in Level at an Unknown Time under Fractional Integration.” Journal of Time Series Analysis 35:40–54) who employ Wald-type statistics based on OLS estimation and rely on a self-normalization to overcome the fact that the standard Wald statistic does not have a well-defined limiting distribution across different values of the memory parameter. Here, we consider an alternative approach that uses the standard Wald statistic but is based on quasi-GLS estimation to control for the effect of the memory parameter. We show that this approach leads to significant improvements in asymptotic local power.

Keywords: change in mean; fractional integration; Wald statistic (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1515/jtse-2015-0006

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