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Testing fractional order of long memory processes : a Monte Carlo study

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  • Laurent Ferrara

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne, DGEI-DAMEP - Banque de France)

  • Dominique Guegan

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

  • Zhiping Lu

    ()
    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne, ECNU - East China Normal University [Shangaï])

Abstract

Testing the fractionally integrated order of seasonal and non-seasonal unit roots is quite important for the economic and financial time series modelling. In this paper, Robinson test (1994) is applied to various well-known long memory models. Via Monte Carlo experiments, we study and compare the performances of this test using several sample sizes.

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Bibliographic Info

Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00259193.

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Date of creation: Feb 2008
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Handle: RePEc:hal:cesptp:halshs-00259193

Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00259193
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Related research

Keywords: Long memory processes; test; Monte Carlo simulations.;

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Cited by:
  1. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with seasonal-cyclical long memory models," Documents de travail du Centre d'Economie de la Sorbonne b08035, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  2. repec:ebl:ecbull:v:3:y:2008:i:29:p:1-10 is not listed on IDEAS
  3. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Post-Print halshs-00277379, HAL.
  4. Laurent Ferrara & Dominique Guegan, 2008. "Business surveys modelling with Seasonal-Cyclical Long Memory models," Post-Print halshs-00283710, HAL.

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