Three different measures of sample skewness and kurtosis and their effects on the Jarque–Bera test for normality
by Panagiotis Mantalos
International Journal of Computational Economics and Econometrics (IJCEE), Vol. 2, No. 1, 2011

Abstract: Monte Carlo methods are used to study the size and the power of three versions of the Jarque and Bera Lagrangian multiplier test for normality, JB(g₁, g₂), JB(b₁, b₂) and, finally, JB(k₁, k₂). The difference between these tests comes from the different definitions (estimates) of sample skewness and kurtosis. The Jarque and Bera test has rather poor small sample properties: the slow convergence of the test statistic to its limiting distribution makes the test oversized for small nominal level and undersized for larger than 3% levels even in a reasonably large sample. However, the JB(k₁, k₂) for a 5% nominal level shows good properties for all samples. The power of the tests shows the same erratic form.

Online publication date: Tue, 07-Jun-2011

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Economics and Econometrics (IJCEE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com