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An improved test for heteroskedasticity using adjusted modified profile likelihood inference

✍ Scribed by Silvia L.P. Ferrari; Audrey H.M.A. Cysneiros; Francisco Cribari-Neto

Book ID
104339942
Publisher
Elsevier Science
Year
2004
Tongue
English
Weight
258 KB
Volume
124
Category
Article
ISSN
0378-3758

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✦ Synopsis

This paper addresses the issue of testing for heteroskedasticity in linear regression models. We derive a Bartlett adjustment to the modiÿed proÿle likelihood ratio test (J. Roy. Statist. Soc. B 49 (1987) 1) for heteroskedasticity in the normal linear regression model. Our results generalize those in Ferrari and Cribari-Neto (Statist. Probab. Lett. 57 (2002) 353), since they allow for a vector-valued structure for the parameter that deÿnes the skedastic function. Monte Carlo evidence shows that the proposed test displays reliable ÿnite-sample behavior, outperforming the original likelihood ratio test, the Bartlett-corrected likelihood ratio test, and the modiÿed proÿle likelihood ratio test.

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