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Edgeworth expansions for semiparametric Whittle estimation of long memory

Giraitis, Liudas and Robinson, Peter (2002) Edgeworth expansions for semiparametric Whittle estimation of long memory. Econometrics; EM/2002/438, EM/02/438. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London.

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Identification Number: EM/02/438

Abstract

The semiparametric local Whittle or Gaussian estimate of the long memory parameter is known to have especially nice limiting distributional properties, being asymptotically normal with a limiting variance that is completely known. However in moderate samples the normal approximation may not be very good, so we consider a refined, Edgeworth, approximation, for both a tapered estimate, and the original untapered one. For the tapered estimate, our higher-order correction involves two terms, one of order 1/√m (where m is the bandwidth number in the estimation), the other a bias term, which increases in m; depending on the relative magnitude of the terms, one or the other may dominate, or they may balance. For the untapered estimate we obtain an expansion in which, for m increasing fast enough, the correction consists only of a bias term. We discuss applications of our expansions to improved statistical inference and bandwidth choice. We assume Gaussianity, but in other respects our assumptions seem mild.

Item Type: Monograph (Discussion Paper)
Official URL: http://sticerd.lse.ac.uk
Additional Information: © 2002 the authors
Subjects: H Social Sciences > HB Economic Theory
Sets: Collections > Economists Online
Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Date Deposited: 27 Apr 2007
Last Modified: 01 Oct 2010 08:46
URI: http://eprints.lse.ac.uk/id/eprint/2130

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