The robustness of the systemwise breusch-godfrey autocorrelation test for non-normal distributed error terms
作者:
Ghazi Shukur,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 2000)
卷期:
Volume 29,
issue 2
页码: 419-448
ISSN:0361-0918
年代: 2000
DOI:10.1080/03610910008813620
出版商: Marcel Dekker, Inc.
关键词: tests of autocorrelation;systems of equations;AR(1) and MA(1) error terms;Monte Carlo methods
数据来源: Taylor
摘要:
Using Monte Carlo methods, the properties of systemwise generalisations of the Breusch-Godfrey test for autocorrelated errors are studied in situations when the error terms follow either normal or non-normal distributions, and when these errors follow either AR(1) or MA(1) processes. Edgerton and Shukur (1999) studied the properties of the test using normally distributed error terms and when these errors follow an AR(1) process. When the errors follow a non-normal distribution, the performances of the tests deteriorate especially when the tails are very heavy. The performances of the tests become better (as in the case when the errors are generated by the normal distribution) when the errors are less heavy tailed.
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