Heteroscedasticity Diagnostics Based on "Corrected" Standard Errors

Weights are found for weighted least squares estimates such that a selected coefficient (a) changes by one standard deviation or (b) changes in sign. The length of the vector of weight changes is equal to the usual OLS standard error divided by the White-corrected standard errors. Thus the White-corrected standard errors can help decide if it is necessary to adjust the location of the confidence sets to correct for heteroscedasticity. The vector of weight changes is similar to the effect of omitting observations, one at a time. The sensitivity diagnostics of Belsley, Kuh and Welsch are therefore linked with heteroscedasticity issues.