Presentation on theme: "Heteroskedasticity Hill et al Chapter 11. Predicting food expenditure Are we likely to be better at predicting food expenditure at: –low incomes; –high."— Presentation transcript:
Consequences of Heteroskedasticity The least squares estimator is still a linear and unbiased estimator, but it is no longer best. It is no longer B.L.U.E. The standard errors usually computed for the least squares estimator are incorrect. Confidence intervals and hypothesis tests that use these standard errors may be misleading.
Whites estimator of the standard error in the presence of hetero.