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Optimal Bandwidth Selection in Non-Parametric Spectral Density Estimation

Listed author(s):
  • Fortin, Ines

    (Abteilung Finanzwirtschaft, Institut fuer Hoehere Studien)

  • Kuzmics, Christoph

    (Abteilung Finanzwirtschaft, Institut fuer Hoehere Studien)

This paper deals with optimal window width choice in non-parametric lag- or spectral window estimation of the spectral density of a stationary zero-mean process. Several approaches are reviewed: the cross-validation based methods described by Hurvich (1985), Beltrao & Bloomfield (1987) and Hurvich & Beltrao (1990), an iterative procedure due to Buehlmann (1996), and a bootstrap approach followed by Franke & Haerdle (1992). These methods are compared in terms of the mean square error, the mean square percentage error, and a third measure of distance between the true spectral density and its estimate. The comparison is based on a small simulation study. The processes that are simulated are in the class of ARMA (5,5) processes. Based on the simulation evidence, we suggest to use a slightly modified version of Buehlmann's (1996) iterative method.

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File Function: First version, 1999
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Paper provided by Institute for Advanced Studies in its series Economics Series with number 62.

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Length: 39 pages
Date of creation: Feb 1999
Handle: RePEc:ihs:ihsesp:62
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  1. Franke,J. & Haerdle,W., 1987. "On bootstrapping Kernel spectral estimates," Discussion Paper Serie A 121, University of Bonn, Germany.
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