Hidalgo, Javier and Yajima, Y. (2003) Semiparametric estimation of the long-range parameter. Annals of the Institute of Statistical Mathematics, 55 (4). pp. 705-736. ISSN 0020-3157
Full text not available from this repository.Abstract
We study two estimators of the long-range parameter of a covariance stationary linear process. We show that one of the estimators achieve the optimal semiparametric rate of convergence, whereas the other has a rate of convergence as close as desired to the optimal rate. Moreover, we show that the estimators are asymptotically normal with a variance, which does not depend on any unknown parameter, smaller than others suggested in the literature. Finally, a small Monte Carlo study is included to illustrate the finite sample relative performance of our estimators compared to other suggested semiparametric estimators. More specifically, the Monte-Carlo experiment shows the superiority of the proposed estimators in terms of the Mean Squared Error.
| Item Type: | Article |
|---|---|
| Official URL: | http://www.springerlink.com/content/102845/ |
| Additional Information: | © 2003 The Institute of Statistical Mathematics |
| Divisions: | Economics STICERD |
| Subjects: | H Social Sciences > HB Economic Theory Q Science > QA Mathematics |
| JEL classification: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods |
| Date Deposited: | 07 Oct 2008 09:05 |
| Last Modified: | 11 Dec 2024 22:35 |
| URI: | http://eprints.lse.ac.uk/id/eprint/16146 |
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