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Lm Tests In The Presence Of Non-Normal Error Distributions

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  • Furno, Marilena

Abstract

The paper considers different versions of the Lagrange multiplier (LM) tests for autocorrelation and/or for conditional heteroskedasticity. These versions differ in terms of the residuals, and of the functions of the residuals, used to build the tests. In particular, we compare ordinary least squares versus least absolute deviation (LAD) residuals, and we compare squared residuals versus their absolute value. We show that the LM tests based on LAD residuals are asymptotically distributed as a χ2 and that these tests are robust to nonnormality. The Monte Carlo study provides evidence in favor of the LAD residuals, and of the absolute value of the LAD residuals, to build the LM tests here discussed.

Suggested Citation

  • Furno, Marilena, 2000. "Lm Tests In The Presence Of Non-Normal Error Distributions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 249-261, April.
    • Handle: RePEc:cup:etheor:v:16:y:2000:i:02:p:249-261_16
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    Cited by:

    1. Iglesias, Emma M., 2006. "Higher-order asymptotic properties of QML in [beta]-ARCH and [mu]-ARCH models," Economics Letters, Elsevier, vol. 93(2), pages 261-266, November.
    2. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
    3. Furno, Marilena, 2001. "LAD estimation with random coefficient autocorrelated errors," Computational Statistics & Data Analysis, Elsevier, vol. 36(4), pages 511-523, June.
    4. Alejo, Javier & Montes-Rojas, Gabriel & Sosa-Escudero, Walter, 2018. "Testing for serial correlation in hierarchical linear models," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 101-116.

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