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Comparaison of Several Estimation Procedures for Long Term Behavior

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  • Dominique Guegan

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Zhiping Lu

    (ECNU - ECNU - East China Normal University [Shangaï])

  • Beijia Zhu

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, ECNU - ECNU - East China Normal University [Shangaï])

Abstract

In this paper, nine memory parameter estimation procedures for the fractionally integrated I(d) process, semi-parametric and parametric, which prevail in the existing literature are reviewed ; through the simulation study under the ARFIMA (p,d,q) setting we cast a light on the finite sample performance of these estimation procedures for the non-stationary long memory time series. As a by-product of this study, we provide a bandwidth parameter selection strategy for the frequency domain estimation and an upper-and-lower scale trimming strategy for the wavelet domain estimation from a practical stand-point. The other objective of this paper is to give a useful reference to the applied reserachers and practitioners.

Suggested Citation

  • Dominique Guegan & Zhiping Lu & Beijia Zhu, 2012. "Comparaison of Several Estimation Procedures for Long Term Behavior," Post-Print halshs-00673934, HAL.
    • Handle: RePEc:hal:journl:halshs-00673934
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00673934
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    References listed on IDEAS

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    1. Shimotsu, Katsumi, 2002. "Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend," Economics Discussion Papers 8844, University of Essex, Department of Economics.
    2. Peter C.B. Phillips, 1999. "Discrete Fourier Transforms of Fractional Processes," Cowles Foundation Discussion Papers 1243, Cowles Foundation for Research in Economics, Yale University.
    3. Morten Ørregaard Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 405-443.
    4. Tanaka, Katsuto, 1999. "The Nonstationary Fractional Unit Root," Econometric Theory, Cambridge University Press, vol. 15(4), pages 549-582, August.
    5. Frederiksen, Per & Nielsen, Frank S. & Nielsen, Morten Ørregaard, 2012. "Local polynomial Whittle estimation of perturbed fractional processes," Journal of Econometrics, Elsevier, vol. 167(2), pages 426-447.
    6. Shimotsu, Katsumi & Phillips, Peter C B, 2002. "Exact Local Whittle Estimation of Fractional Integration," Economics Discussion Papers 8838, University of Essex, Department of Economics.
    7. Katsumi Shimotsu & Peter C.B. Phillips, 2000. "Modified Local Whittle Estimation of the Memory Parameter in the Nonstationary Case," Cowles Foundation Discussion Papers 1265, Cowles Foundation for Research in Economics, Yale University.
    8. Frank S. Nielsen, 2008. "Local polynomial Whittle estimation covering non-stationary fractional processes," CREATES Research Papers 2008-28, Department of Economics and Business Economics, Aarhus University.
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    Cited by:

    1. Heni Boubaker, 2016. "A Comparative Study of the Performance of Estimating Long-Memory Parameter Using Wavelet-Based Entropies," Computational Economics, Springer;Society for Computational Economics, vol. 48(4), pages 693-731, December.

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