Abstract
This paper investigates the asymptotic theory of the least squares estimators (LSE) for a long-memory nearly unstable model when the innovation sequences are functionals of moving averages. It is shown that the limit distribution of the LSE is a functional of the Hermite Ornstein-Uhlenbeck process. This result not only generalizes the result of Buchmann and Chan [Ann. Statist. 35 (2007), 2001-2017], but also that of Wu [Economet. Theory 22 (2006), 1-14]. © 2012 - IOS Press and the authors. All rights reserved.
| Original language | English |
|---|---|
| Pages (from-to) | 239-246 |
| Journal | Risk and Decision Analysis |
| Volume | 3 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- Hermite Ornstein-Uhlenbeck processes
- least squares estimator
- long-memory noises
- nearly unstable processes
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