Trimming and tapering semi-parametric estimates in asymmetric long memory time series
AbstractThis 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.
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Bibliographic InfoPaper provided by Universidad Carlos III de Madrid in its series Open Access publications from Universidad Carlos III de Madrid with number info:hdl:10016/4358.
Length: 613 p.
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Seasonality; Cycles; Periodogram; Long range dependence; Asymptotic normality;
Other versions of this item:
- J. Arteche & C. Velasco, 2005. "Trimming and Tapering Semi-Parametric Estimates in Asymmetric Long Memory Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 581-611, 07.
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- Arteche González, Jesús María, 2005.
"Semiparametric estimation in perturbed long memory series,"
2005-02, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
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- Arteche González, Jesús María & Artiach Escauriaza, Miguel Manuel, 2011. "Doubly fractional models for dynamic heteroskedastic cycles," BILTOKI 2011-03, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
- Artiach, Miguel, 2012. "Leverage, skewness and amplitude asymmetric cycles," MPRA Paper 41267, University Library of Munich, Germany.
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