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A robust test for multivariate normality

Author

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  • Jönsson, Kristian

Abstract

The size of the Jarque–Bera test for multivariate normality can be severely distorted in small samples. An alternative test procedure, that turns out to have good size and power properties, is suggested.

Suggested Citation

  • Jönsson, Kristian, 2011. "A robust test for multivariate normality," Economics Letters, Elsevier, vol. 113(2), pages 199-201.
  • Handle: RePEc:eee:ecolet:v:113:y:2011:i:2:p:199-201 DOI: 10.1016/j.econlet.2011.06.018
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    References listed on IDEAS

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    1. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    2. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
    3. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    4. Deb, Partha & Sefton, Martin, 1996. "The distribution of a Lagrange multiplier test of normality," Economics Letters, Elsevier, vol. 51(2), pages 123-130, May.
    5. Maddala, G S & Wu, Shaowen, 1999. " A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-652, Special I.
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    Cited by:

    1. Kim, Namhyun, 2016. "A robustified Jarque–Bera test for multivariate normality," Economics Letters, Elsevier, vol. 140(C), pages 48-52.

    More about this item

    Keywords

    Normality testing; Finite sample; Size distortion;

    JEL classification:

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

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