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TESTING FOR ZERO AUTOCORRELATION IN THE PRESENCE OF STATISTICAL DEPENDENCE

Published online by Cambridge University Press:  15 May 2002

I.N. Lobato ,
John C. Nankervis  and
N.E. Savin
I.N. Lobato
Affiliation:
Instituto Tecnológico Autónomo de México
John C. Nankervis
Affiliation:
University of Surrey
N.E. Savin
Affiliation:
University of Iowa
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Abstract

The problem addressed in this paper is to test the null hypothesis that a time series process is uncorrelated up to lag K in the presence of statistical dependence. We propose an extension of the Box–Pierce Q-test that is asymptotically distributed as chi-square when the null is true for a very general class of dependent processes that includes non-martingale difference sequences. The test is based on a consistent estimator of the asymptotic covariance matrix of the sample autocorrelations under the null. The finite sample performance of this extension is investigated in a Monte Carlo study.

Type
Research Article
Information
Econometric Theory , Volume 18 , Issue 3 , June 2002 , pp. 730 - 743
Copyright
© 2002 Cambridge University Press

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