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An Empirical Likelihood Ratio Test for Normality in Linear Regression

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Author Info
Lauren Bin Dong () (Statistics Canada)
David E. A. Giles () (Department of Economics, University of Victoria)

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Abstract

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

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File URL: http://web.uvic.ca/econ/research/papers/ewp0402.pdf
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Publisher Info
Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0402.

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Length: 18 pages
Date of creation: 08 Apr 2004
Date of revision:
Handle: RePEc:vic:vicewp:0402

Note: ISSN 1485-6441
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Web page: http://web.uvic.ca/econ
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Related research
Keywords: Regression residual; Empirical likelihood ratio; Monte Carlo simulation; Normality;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions

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  1. Lauren Bin Dong & David E. A. Giles, 2004. "An Empirical Likelihood Ratio Test for Normality," Econometrics Working Papers 0401, Department of Economics, University of Victoria. [Downloadable!]
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This page was last updated on 2009-12-22.

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