Finite Sample Comparison Of Parametric, Semiparametric, And Wavelet Estimators Of Fractional Integration

Morten Nielsen and Per Houmann Frederiksen
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Per Houmann Frederiksen: Nordea Markets

No 1189, Working Paper from Economics Department, Queen's University

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.

Keywords: bias; finite sample distribution; fractional integration; maximum likelihood; Monte Carlo simulation; parametric estimation; semiparametric estimation; wavelet (search for similar items in EconPapers)
JEL-codes: C14 C15 C22 (search for similar items in EconPapers)
Pages: 55 pages
Date: 2005-07
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (35)

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https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_1189.pdf First version 2005 (application/pdf)

Related works:
Journal Article: Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:qed:wpaper:1189

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