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Estimating the number of mean shifts under long memory

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  • Sibbertsen, Philipp
  • Willert, Juliane

Abstract

Detecting the number of breaks in the mean can be challenging when it comes to the long memory framework. Tree-based procedures can be applied to time series when the location and number of mean shifts are unknown and estimate the breaks consistently though with possible overfitting. For pruning the redundant breaks information criteria can be used. An alteration of the BIC, the LWZ, is presented to overcome long-range dependence issues. A Monte Carlo Study shows the superior performance of the LWZ to alternative pruning criteria like the BIC or LIC.

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Bibliographic Info

Paper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Hannover Economic Papers (HEP) with number dp-496.

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Length: 16 pages
Date of creation: Mar 2012
Date of revision:
Handle: RePEc:han:dpaper:dp-496

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Keywords: long memory; mean shift; regression tree; ART; LWZ; LIC.;

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  1. Ricardo Azevedo Araujo & Gilberto Tadeu Lima, 2007. "A structural economic dynamics approach to balance-of-payments-constrained growth," Cambridge Journal of Economics, Oxford University Press, vol. 31(5), pages 755-774, September.
  2. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
  3. Corvoisier, Sandrine & Mojon, Benoît, 2005. "Breaks in the mean of inflation: how they happen and what to do with them," Working Paper Series 0451, European Central Bank.
  4. Cunado, J. & Gil-Alana, L. A. & Perez de Gracia, F., 2004. "Is the US fiscal deficit sustainable?: A fractionally integrated approach," Journal of Economics and Business, Elsevier, vol. 56(6), pages 501-526.
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