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Testing for Normality in the Linear Regression Model: An Empirical Likelihood Ratio Test

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Abstract

The empirical likelihood ratio (ELR) test for the problem of testing for normality in a linear regression model is derived in this paper. The sampling properties of the ELR test and four other commonly used tests are explored and analyzed using Monte Carlo simulation. The ELR test has good power properties against various alternative hypotheses.

Suggested Citation

  • Lauren Bin Dong & Davod E. A. Giles, 2024. "Testing for Normality in the Linear Regression Model: An Empirical Likelihood Ratio Test," Department Discussion Papers 2004, Department of Economics, University of Victoria.
    • Handle: RePEc:vic:vicddp:0402
    Note: ISSN 1485-6441
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    File URL: https://www.uvic.ca/socialsciences/economics/_assets/docs/econometrics/ewp0402.pdf
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    More about this item

    Keywords

    Regression residual; empirical likelihood ratio; Monte Carlo simulation; normality JEL Classifications: C12; C15; C16;
    All these keywords.

    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
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions

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