White Test
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High Quality Content by WIKIPEDIA articles! 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 R2. 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…mehr

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High Quality Content by WIKIPEDIA articles! 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 R2. 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 one of the most cited articles in Economics journals