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The effect of a variance shift on the Breusch-Godfrey's LM test

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  • Joo-Yeon Hyun
  • Hyeong Ho Mun
  • Tae-Hwan Kim
  • Jinook Jeong

Abstract

In 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.

Suggested Citation

  • Joo-Yeon Hyun & Hyeong Ho Mun & Tae-Hwan Kim & Jinook Jeong, 2010. "The effect of a variance shift on the Breusch-Godfrey's LM test," Applied Economics Letters, Taylor & Francis Journals, vol. 17(4), pages 399-404.
    • Handle: RePEc:taf:apeclt:v:17:y:2010:i:4:p:399-404
    DOI: 10.1080/13504850701748933
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    Cited by:

    1. 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.
    2. Sohail Chand & Nuzhat Aftab, 2018. "Modified Variance Ratio Test for Autocorrelation in the Presence of Heteroskedasticity," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 23(1), pages 1-19, Jan-June.

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