Title

Unit Root Log Periodogram Regression

Publication Type

Journal Article

Publication Date

2007

Abstract

Log periodogram (LP) regression is shown to be consistent and to have a mixed normal limit distribution when the memory parameter d=1. Gaussian errors are not required. The proof relies on a new result showing that asymptotically infinite collections of discrete Fourier transforms (dft's) of a short memory process at the fundamental frequencies in the vicinity of the origin can be treated as asymptotically independent normal variates, provided one does not include too many dft's in the collection.

Keywords

Asymptotic independence; Discrete Fourier transform; Fractional integration; Log periodogram regression; Long memory parameter; Nonstationarity; Semiparametric estimation; Unit root

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

138

Issue

1

First Page

104

Last Page

124

ISSN

0304-4076

Identifier

10.1016/j.jeconom.2006.05.017

Publisher

Elsevier

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/10.1016/j.jeconom.2006.05.017

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