Asymptotic theory for certain regression models with long memory errors

The asymptotic distribution of a weighted linear combination of a linear long memory series is shown to be normal for certain weights. This result can be used to derive the limiting distribution of the least squares estimators for polynomial trends and of the periodogram at fixed Fourier frequencies...

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Veröffentlicht in:Journal of time series analysis 1997-07, Vol.18 (4), p.385-393
1. Verfasser: Deo, R. S.
Format: Artikel
Sprache:eng
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Zusammenfassung:The asymptotic distribution of a weighted linear combination of a linear long memory series is shown to be normal for certain weights. This result can be used to derive the limiting distribution of the least squares estimators for polynomial trends and of the periodogram at fixed Fourier frequencies. A closed form expression for the asymptotic relative bias of the tapered periodogram at fixed Fourier frequencies is also obtained. A weighted least squares estimator, which is asymptotically efficient for polynomial trend regressors, is shown to be asymptotically normal.
ISSN:0143-9782
1467-9892
DOI:10.1111/1467-9892.00057