ROBUST CRITICAL VALUES FOR THE JARQUE-BERA TEST FOR NORMALITY

We introduce the “sample” technique to generate robust critical values for the Jarque and Bera (JB) Lagrangian Multiplier (LM) test for normality, JBCV( 1 2 k ,k ), by using improved critical values the true size of the test approaches its nominal value. Monte Carlo methods are used to study the size, and the power of the JB normality test with the “sample” critical values and compare with three alternatives to the Jarque and Bera LM test for normality: the Urzúa (1996) modification of the Jarque- Bera test, JBM; the Omnibus K2 statistic made by D’Agostino, Belanger and D’Agostino (1990), JBK; and finally the, Jarque and Bera LM test for normality by using the quantities 1 k and 2 k are the definitions of sample skewness and kurtosis JB( 1 2 k ,k ). The JBCV( 1 2 k ,k ), shows superiority as it has the right size for all samples, small, medium and large, and at the same time has the higher power.