We consider asymptotic properties of the least squares estimator (LSE) in a regression model with long-memory stationary errors. First we derive a necessary and sufficient condition that the LSE be asymptotically efficient relative to the best linear unbiased estimator (BLUE). Then we derive the asymptotic distribution of the LSE under a condition on the higher-order cumulants of the white-noise process of the errors.
Publié le : 1991-03-14
Classification:
Long-memory models,
regression,
least squares estimators,
62M10,
62J05
@article{1176347975,
author = {Yajima, Yoshihiro},
title = {Asymptotic Properties of the LSE in a Regression Model with Long-Memory Stationary Errors},
journal = {Ann. Statist.},
volume = {19},
number = {1},
year = {1991},
pages = { 158-177},
language = {en},
url = {http://dml.mathdoc.fr/item/1176347975}
}
Yajima, Yoshihiro. Asymptotic Properties of the LSE in a Regression Model with Long-Memory Stationary Errors. Ann. Statist., Tome 19 (1991) no. 1, pp. 158-177. http://gdmltest.u-ga.fr/item/1176347975/