Title

Gaussian Inference in Ar(1) Time Series with or without a Unit Root

Publication Type

Journal Article

Publication Date

6-2008

Abstract

This paper introduces a simple first-difference-based approach to estimation and inference for the AR(1) model. The estimates have virtually no finite-sample bias and are not sensitive to initial conditions, and the approach has the unusual advantage that a Gaussian central limit theory applies and is continuous as the autoregressive coefficient passes through unity with a uniform ... rate of convergence. En route, a useful central limit theorem (CLT) for sample covariances of linear processes is given, following Phillips and Solo (1992, Annals of Statistics, 20, 971-1001). The approach also has useful extensions to dynamic panels. (ProQuest-CSA LLC:: ... denotes formulae/symbols omitted.)

Discipline

Econometrics

Research Areas

Econometrics

Publication

Econometric Theory

Volume

24

Issue

3

First Page

631

Last Page

650

ISSN

0266-4666

Identifier

10.1017/s0266466608080262

Publisher

Cambridge University Press

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://dx.doi.org/10.1017/s0266466608080262

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