# White test

34,202pages on
this wiki

### Wikia is a free-to-use site that makes money from advertising. We have a modified experience for viewers using ad blockers Wikia is not accessible if you’ve made further modifications. Remove the custom ad blocker rule(s) and the page will load as expected.

In statistics, the White test, named after Halbert White, is a test that establishes whether the residual variance of a variable in a regression model is constant (homoscedasticity). To test for constant variance one regresses the squared residuals from a regression model onto the regressors, the cross-products of the regressors and the squared regressors. One then inspects the $R^{2}$. If homoskedasticity is rejected one can use a GARCH model.

An interesting fact is that the paper that published White's test, "A Heteroskedasticity—Consistent Covariance Matrix Estimator and a Direct Test for Hetereoskedasticity” (1980) is the one of the most cited articles in Economics journals [1].

The LM test statistic is the product of the $R^{2}$ value and sample size. It follows a chi square distribution, with degrees of freedom equal to one less than the number of independent variables.

$\ LM = n \cdot R^2$