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Breaks or long memory behaviour : an empirical investigation

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  • Lanouar Charfeddine

    ()
    (OEP - Université Paris-Est Marne-la-Vallée (UPEMLV))

  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

Abstract

Are structural breaks models true switching models or long memory processes ? The answer to this question remain ambiguous. A lot of papers, in recent years, have dealt with this problem. For instance, Diebold and Inoue (2001) and Granger and Hyung (2004) show, under specific conditions, that switching models and long memory processes can be easily confused. In this paper, using several generating models like the mean-plus-noise model, the STOchastic Permanent BREAK model, the Markov switching model, the TAR model, the sign model and the Structural CHange model (SCH) and several estimation techiques like the GPH technique, the Exact Local Whittle (ELW) and the Wavelet methods, we show that, if the answer is quite simple in some cases, it can be mitigate in other cases. Using French and American inflation rates, we show that these series cannot be characterized by the same class of models. The main result of this study suggests that estimating the long memory parameter without taking account existence of breaks in the data sets may lead to misspecification and to overestimate the true parameter.

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Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00722032.

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Date of creation: 31 Jul 2012
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Handle: RePEc:hal:cesptp:halshs-00722032

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Keywords: Structural breaks models; spurious long memory behavior; inflation series.;

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Cited by:
  1. Dominique Guégan, 2009. "A Meta-Distribution for Non-Stationary Samples," CREATES Research Papers 2009-24, School of Economics and Management, University of Aarhus.

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