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

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

Research output: Contribution to journalArticle

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)399-404
Number of pages6
JournalApplied Economics Letters
Volume17
Issue number4
DOIs
Publication statusPublished - 2010 Mar 1

Fingerprint

LM test
Factors
Monte Carlo simulation
Serial correlation
Autocorrelation

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Cite this

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The effect of a variance shift on the Breusch-Godfrey's LM test. / Hyun, Joo Yeon; Mun, Hyeong Ho; Kim, Tae-Hwan; Jeong, Jinook.

In: Applied Economics Letters, Vol. 17, No. 4, 01.03.2010, p. 399-404.

Research output: Contribution to journalArticle

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