The effect of a variance shift on the Breusch-Godfrey's LM test
AbstractIn this article, we study the impact of an abrupt change in variance on the Breusch-Godfrey's LM test for autocorrelation. It is demonstrated by Monte Carlo simulations that a break in variance can generate spurious rejections of the null hypothesis of no serial correlation. Hence, a researcher might conclude that the error terms are serially correlated when in fact the contrary is true. It has been found that the likelihood of making this mistake depends on three factors: (i) break size, (ii) break location and (iii) the number of lagged terms included in the LM test.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics Letters.
Volume (Year): 17 (2010)
Issue (Month): 4 ()
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- Jinook Jeong & Byunguk Kang, 2012.
"Wild-bootstrapped variance-ratio test for autocorrelation in the presence of heteroskedasticity,"
Journal of Applied Statistics,
Taylor & Francis Journals, vol. 39(7), pages 1531-1542, January.
- Jeong, Jinook & Kang, Byunguk, 2006. "Wild-Bootstrapped Variance Ratio Test for Autocorrelation in the Presence of Heteroskedasticity," MPRA Paper 9791, University Library of Munich, Germany, revised May 2008.
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