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Using OLS to test for normality

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  • Shalit, Haim

Abstract

The OLS estimator is a weighted average of the slopes delineated by adjacent observations. These weights depend only on the independent variable. Equal weights are obtained if and only if the independent variable is normally distributed. This feature is used to develop a new test for normality which is compared to standard tests and provides better power for testing normality.

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  • Shalit, Haim, 2012. "Using OLS to test for normality," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 2050-2058.
    • Handle: RePEc:eee:stapro:v:82:y:2012:i:11:p:2050-2058
    DOI: 10.1016/j.spl.2012.07.004
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    References listed on IDEAS

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    1. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January.
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    Cited by:

    1. Haim Shalit, 2020. "The Shapley value of regression portfolios," Journal of Asset Management, Palgrave Macmillan, vol. 21(6), pages 506-512, October.
    2. Haim Shalit, 2021. "The Shapley value decomposition of optimal portfolios," Annals of Finance, Springer, vol. 17(1), pages 1-25, March.
    3. Haim Shalit, 2014. "Measuring Risk In Israeli Mutual Funds: Conditional Value-At-Risk Vs. Aumann-Serrano Riskiness Index," Working Papers 1409, Ben-Gurion University of the Negev, Department of Economics.
    4. Doron Nisani, 2023. "On the General Deviation Measure and the Gini coefficient," International Journal of Economic Theory, The International Society for Economic Theory, vol. 19(3), pages 599-610, September.
    5. Doron Nisani & Amit Shelef, 2021. "A statistical analysis of investor preferences for portfolio selection," Empirical Economics, Springer, vol. 61(4), pages 1883-1915, October.
    6. Norbert Henze & Stefan Koch, 2020. "On a test of normality based on the empirical moment generating function," Statistical Papers, Springer, vol. 61(1), pages 17-29, February.

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