Regression diagnostics | Statistical tests

White test

In statistics, the 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. These methods have become extremely widely used, making this paper one of the most cited articles in economics. 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. (Wikipedia).

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Variance | Breusch–Pagan test | Heteroskedasticity-consistent standard errors | R (programming language) | Statistics | Chi-squared distribution | Stata