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Normality Testing- A New Direction

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  • Islam, Tanweer ul

Abstract

This paper is concerned with the evaluation of the performance of the normality tests to ensure the validity of the t-statistics used for assessing significance of regressors in a regression model. For this purpose, we have explored 40 distributions to find the most damaging distribution on the t-statistic. Power comparisons are conducted to find the best performing test against these distributions. It is found that Anderson-Darling statistic is the best option among the five normality tests, Jarque-Bera, Shapiro-Francia, D’Agostino & Pearson, Anderson-Darling & Lilliefors.

Suggested Citation

  • Islam, Tanweer ul, 2008. "Normality Testing- A New Direction," MPRA Paper 16452, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:16452
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    References listed on IDEAS

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    1. Bartolucci, F. & Scaccia, L., 2005. "The use of mixtures for dealing with non-normal regression errors," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 821-834, April.
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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
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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