Testing for a break in persistence under long-range dependencies and mean shifts
AbstractWe show that the CUSUM-squared based test for a change in persistence by Leybourne et al. (2007) is not robust against shifts in the mean. A mean shift leads to serious size distortions. Therefore, adjusted critical values are needed when it is known that the data generating process has a mean shift. These are given for the case of one mean break. Response curves for the critical values are derived and a Monte Carlo study showing the size and power properties under this general de-trending is given
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Bibliographic InfoArticle provided by Springer in its journal Statistical Papers.
Volume (Year): 53 (2012)
Issue (Month): 2 (May)
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Web page: http://www.springer.com/statistics/business/journal/362
Other versions of this item:
- Sibbertsen, Philipp & Willert, Juliane, 2009. "Testing for a break in persistence under long-range dependencies and mean shifts," Diskussionspapiere der Wirtschaftswissenschaftlichen FakultÃ¤t der Leibniz UniversitÃ¤t Hannover dp-422, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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