White test

In statistics the White test is a test which establishes whether the residual variance of a variable in a regression model is constant (homoskedasticity). 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.

The 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 the number of independent variables.

$$LM = n * R2$$ The LM statistic for heteroskedasticity is the sample size times the R-squared value.

$$\ LM = n * R^2 $$

The LM statistic for heteroskedasticity is the sample size times the R-squared value and is distributed asymptotically chi-squared.


 * Breusch-Pagan test