Not to be confused with White information matrix test.
White test is a statistical test that establishes whether the variance of the errors in a regression model is constant: that is for homoskedasticity.
This test, and an estimator for heteroscedasticity-consistent standard errors, were proposed by Halbert White in 1980.[1] These methods have become widely used, making this paper one of the most cited articles in economics.[2]
In cases where the White test statistic is statistically significant, heteroskedasticity may not necessarily be the cause; instead the problem could be a specification error. In other words, the White test can be a test of heteroskedasticity or specification error or both. If no cross product terms are introduced in the White test procedure, then this is a test of pure heteroskedasticity.
If cross products are introduced in the model, then it is a test of both heteroskedasticity and specification bias.
^White, H. (1980). "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity". Econometrica. 48 (4): 817–838. CiteSeerX 10.1.1.11.7646. doi:10.2307/1912934. JSTOR 1912934. MR 0575027.
^Kim, E.H.; Morse, A.; Zingales, L. (2006). "What Has Mattered to Economics since 1970" (PDF). Journal of Economic Perspectives. 20 (4): 189–202. doi:10.1257/jep.20.4.189.
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