On the estimation of short memory components in long memory time series models

Baillie Richard T. () and George Kapetanios
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Baillie Richard T.: School of Economics and Finance, Queen Mary University of London, UK

Studies in Nonlinear Dynamics & Econometrics, 2016, vol. 20, issue 4, 365-375

Abstract: A substantial amount of recent time series research has emphasized semi-parameteric estimators of a long memory parameter and we provide a selective review of the literature on this issue. We consider such estimators applied to the issue of estimating the parameters relating to a short memory process which is embedded within the long memory process. We consider the fractional differencing filter and the subsequent properties of a two step estimator of the short memory parameters. We conclude that while the semi-parametric estimators can have excellent properties in terms of estimating the long memory parameter, they do not have good properties when applied to the two step estimator of short memory I(0) parameters. In particular, these estimators compare poorly in terms of bias and mean squared error (MSE) with the systems based maximum likelihood estimator (MLE).

Keywords: long memory; nonlinear; time series (search for similar items in EconPapers)
JEL-codes: C12 C22 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1515/snde-2015-0120

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