Publication Type

Journal Article

Publication Date

2-2006

Abstract

We define a three-step procedure for more efficient estimation of the nonparametric regression mean with nonparametric autocorrelated errors. The procedure is based upon a nonparametric prewhitening transformation of the dependent variable that has to be estimated from the data by a local polynomial technique. We establish the asymptotic distribution of our estimator under weak dependence conditions and show that it is more efficient than the conventional local polynomial estimator. Furthermore, we consider criterion functions based on the linear exponential family, which include the local polynomial least squares criterion as a special case. Simulation evidence suggests that significant gains can be achieved in finite samples with our approach.The authors thank Oliver Linton for his many constructive and helpful suggestions. The very insightful comments from the referees are also gratefully acknowledged. The second author gratefully acknowledges financial support from the Academic Senate, UCR.

Discipline

Econometrics | Economic Theory

Research Areas

Econometrics

Publication

Econometric Theory

Volume

22`

Issue

1

First Page

98

Last Page

126

ISSN

0266-4666

Identifier

10.1017/S026646660606004X

Publisher

Cambridge University Press (CUP): HSS Journals

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org./10.1017/S026646660606004X

Share

COinS