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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.

Suggested Citation

  • Sibbertsen, Philipp & Willert, Juliane, 2012. "Estimating the number of mean shifts under long memory," Hannover Economic Papers (HEP) dp-496, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    • Handle: RePEc:han:dpaper:dp-496
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    References listed on IDEAS

    as
    1. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    2. Corvoisier, Sandrine & Mojon, Benoît, 2005. "Breaks in the mean of inflation: how they happen and what to do with them," Working Paper Series 451, European Central Bank.
    3. 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.
    4. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    5. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    6. Juan Carlos Moreno-Brid, 1998. "On Capital Flows and The Balance-of-Payments-Constrained Growth Model," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 21(2), pages 283-298, December.
    7. Milesi-Ferretti, G-M & Razin, A, 1996. "Current-Account Sustainability," Princeton Studies in International Economics 81, International Economics Section, Departement of Economics Princeton University,.
    8. Ricardo Azevedo Araujo & Gilberto Tadeu Lima, 2007. "A structural economic dynamics approach to balance-of-payments-constrained growth," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 31(5), pages 755-774, September.
    9. da Rosa, Joel Correa & Veiga, Alvaro & Medeiros, Marcelo C., 2008. "Tree-structured smooth transition regression models," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2469-2488, January.
    10. Juan Carlos Moreno-Brid, 1999. "On Capital Flows and the Balance-of-Payments-Constrained Growth Model," Journal of Post Keynesian Economics, M.E. Sharpe, Inc., vol. 21(2), pages 283-298, January.
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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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