Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/171838
Authors: 
Paolella, Marc S.
Year of Publication: 
2015
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 3 [Year:] 2015 [Issue:] 3 [Pages:] 532-560
Abstract: 
Several graphical methods for testing univariate composite normality from an i.i.d. sample are presented. They are endowed with correct simultaneous error bounds and yield size-correct tests. As all are based on the empirical CDF, they are also consistent for all alternatives. For one test, called the modified stabilized probability test, or MSP, a highly simplified computational method is derived, which delivers the test statistic and also a highly accurate p-value approximation, essentially instantaneously. The MSP test is demonstrated to have higher power against asymmetric alternatives than the well-known and powerful Jarque-Bera test. A further size-correct test, based on combining two test statistics, is shown to have yet higher power. The methodology employed is fully general and can be applied to any i.i.d. univariate continuous distribution setting.
Subjects: 
calibration for simultaneity
combined tests
distribution testing
P-P plot
Q-Q plot
simultaneous null bands
JEL: 
C12
C52
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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