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Wild-bootstrapped variance-ratio test for autocorrelation in the presence of heteroskedasticity

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  • Jinook Jeong
  • Byunguk Kang

Abstract

The Breusch--Godfrey LM test is one of the most popular tests for autocorrelation. However, it has been shown that the LM test may be erroneous when there exist heteroskedastic errors in a regression model. Recently, remedies have been proposed by Godfrey and Tremayne [9] and Shim et al. [21]. This paper suggests three wild-bootstrapped variance-ratio (WB-VR) tests for autocorrelation in the presence of heteroskedasticity. We show through a Monte Carlo simulation that our WB-VR tests have better small sample properties and are robust to the structure of heteroskedasticity.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:7:p:1531-1542
    DOI: 10.1080/02664763.2012.658360
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    1. Lo, Andrew W. & MacKinlay, A. Craig, 1989. "The size and power of the variance ratio test in finite samples : A Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 40(2), pages 203-238, February.
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    Cited by:

    1. 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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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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