Giraitis, L. and Robinson, P.M.
(2003)
Edgeworth expansions for semiparametric Whittle estimation of long memory.
Annals of Statistics, 31 (4).
pp. 1325-1375.
ISSN 0090-5364
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 m-1/2 (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: |
Article
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| Official URL: |
http://www.imstat.org/aos/ |
| Additional Information: |
Published 2003 © Institute of Mathematical Statistics. LSE has developed LSE Research Online so that users may access research output of the School. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LSE Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the URL (http://eprints.lse.ac.uk) of the LSE Research Online website. |
| Divisions: |
Economics |
| Subjects: |
H Social Sciences > HA Statistics |
| Date Deposited: |
15 Feb 2008 |
| Last Modified: |
13 Sep 2024 21:42 |
| URI: |
http://eprints.lse.ac.uk/id/eprint/291 |
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