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Trimming and Tapering Semi-Parametric Estimates in Asymmetric Long Memory Time Series

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  • J. Arteche
  • C. Velasco

Abstract

This paper considers semi-parametric frequency domain inference for seasonal or cyclical time series with asymmetric long memory properties. It is shown that tapering the data reduces the bias caused by the asymmetry of the spectral density at the cyclical frequency. We provide a joint treatment of different tapering schemes and of the log-periodogram regression and Gaussian semi-parametric estimates of the memory parameters. Tapering allows for a less restrictive trimming of frequencies for the analysis of the asymptotic properties of both estimates when allowing for asymmetries. Simple rules for inference are feasible thanks to tapering and their validity in finite samples is investigated in a simulation exercise and for an empirical example. Copyright 2005 Blackwell Publishing Ltd.

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Bibliographic Info

Article provided by Wiley Blackwell in its journal Journal of Time Series Analysis.

Volume (Year): 26 (2005)
Issue (Month): 4 (07)
Pages: 581-611

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Handle: RePEc:bla:jtsera:v:26:y:2005:i:4:p:581-611

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782

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Cited by:
  1. Arteche, J., 2006. "Semiparametric estimation in perturbed long memory series," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 51(4), pages 2118-2141, December.
  2. Arteche González, Jesús María & Artiach Escauriaza, Miguel Manuel, 2011. "Doubly fractional models for dynamic heteroskedastic cycles," BILTOKI, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística) 2011-03, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
  3. Artiach, Miguel, 2012. "Leverage, skewness and amplitude asymmetric cycles," MPRA Paper 41267, University Library of Munich, Germany.
  4. Reisen, Valdério A. & Zamprogno, Bartolomeu & Palma, Wilfredo & Arteche, Josu, 2014. "A semiparametric approach to estimate two seasonal fractional parameters in the SARFIMA model," Mathematics and Computers in Simulation (MATCOM), Elsevier, Elsevier, vol. 98(C), pages 1-17.

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