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Robust methods for detecting multiple level breaks in autocorrelated time series

Harvey, DI and Leybourne, SJ and Taylor, AMR (2010) 'Robust methods for detecting multiple level breaks in autocorrelated time series.' Journal of Econometrics, 157 (2). 342 - 358. ISSN 0304-4076

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Abstract

In this paper we propose tests for the null hypothesis that a time series process displays a constant level against the alternative that it displays (possibly) multiple changes in level. Our proposed tests are based on functions of appropriately standardized sequences of the differences between sub-sample mean estimates from the series under investigation. The tests we propose differ notably from extant tests for level breaks in the literature in that they are designed to be robust as to whether the process admits an autoregressive unit root (the data are I (1)) or stable autoregressive roots (the data are I (0)). We derive the asymptotic null distributions of our proposed tests, along with representations for their asymptotic local power functions against Pitman drift alternatives under both I (0) and I (1) environments. Associated estimators of the level break fractions are also discussed. We initially outline our procedure through the case of non-trending series, but our analysis is subsequently extended to allow for series which display an underlying linear trend, in addition to possible level breaks. Monte Carlo simulation results are presented which suggest that the proposed tests perform well in small samples, showing good size control under the null, regardless of the order of integration of the data, and displaying very decent power when level breaks occur. © 2010 Elsevier B.V. All rights reserved.

Item Type: Article
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
Depositing User: Jim Jamieson
Date Deposited: 30 Aug 2013 14:06
Last Modified: 05 Feb 2019 18:15
URI: http://repository.essex.ac.uk/id/eprint/7490

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