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Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration

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  • Orregaard Nielsen, Morten
  • Frederiksen, Per

Abstract

In this paper we compare through Monte Carlo simulations the finite sample properties of estimators of the fractional differencing parameter, d. This involves frequency domain, time domain, and wavelet based approaches and we consider both parametric and semiparametric estimation methods. The estimators are briefly introduced and compared, and the criteria adopted for measuring finite sample performance are bias and root mean squared error. Most importantly, the simulations reveal that 1) the frequency domain maximum likelihood procedure is superior to the time domain parametric methods, 2) all the estimators are fairly robust to conditionally heteroscedastic errors, 3) the local polynomial Whittle and bias reduced log-periodogram regression estimators are shown to be more robust to short-run dynamics than other semiparametric (frequency domain and wavelet) estimators and in some cases even outperform the time domain parametric methods, and 4) without sufficient trimming of scales the wavelet based estimators are heavily biased.

Suggested Citation

  • Orregaard Nielsen, Morten & Frederiksen, Per, 2005. "Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration," Queen's Economics Department Working Papers 273666, Queen's University - Department of Economics.
  • Handle: RePEc:ags:quedwp:273666
    DOI: 10.22004/ag.econ.273666
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    Cited by:

    1. Aouad Hadjer, Soumia & Taouli, Mustapha Kamel & Benbouziane, Mohamed, 2012. "Modélisation du Comportement du Taux de Change du Dinar Algérien: Une Investigation Empirique par la Méthode ARFIMA [Modeling of the Algerian Dinar Exchange Rate: An empirical investigation using t," MPRA Paper 38605, University Library of Munich, Germany.
    2. Javier Hualde & Morten {O}rregaard Nielsen, 2022. "Fractional integration and cointegration," Papers 2211.10235, arXiv.org.

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