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Testing for Serial Correlation: Generalized Andrews–Ploberger Tests

Nankervis, John C and Savin, N E (2010) 'Testing for Serial Correlation: Generalized Andrews–Ploberger Tests.' Journal of Business and Economic Statistics, 28 (2). pp. 246-255. ISSN 0735-0015

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Abstract

This paper considers testing the null hypothesis that a times series is uncorrelated when the time series is uncorrelated but statistically dependent. This case is of interest in economic and finance applications. The GARCH(1, 1) model is a leading example of a model that generates serially uncorrelated but statistically dependent data. The tests of serial correlation introduced by Andrews and Ploberger (1996, hereafter AP) are generalized for the purpose of testing the null. The rationale for generalizing the AP tests is that they have attractive properties for cases for which they were originally designed: they are consistent against all nonwhite-noise alternatives and have good all-round power against nonseasonal alternatives compared to several widely used tests in the literature. These properties are inherited by the generalized AP tests.

Item Type: Article
Uncontrolled Keywords: Autoregressive moving average model; Lagrange multiplier test; Nonstandard testing; Statistically dependent time series; Uncorrelatedness
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HG Finance
Divisions: Faculty of Social Sciences > Essex Business School
Depositing User: John Nankervis
Date Deposited: 10 May 2012 13:26
Last Modified: 10 May 2012 13:26
URI: http://repository.essex.ac.uk/id/eprint/1170

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