An Investigation Of An Unbiased Corection For Heteroskedasticity And The Effects Of Misspecifying The Skedastic Function
The traditional two-step procedure for correcting for heteroskedasticity uses a consistent but biased estimator for the variances $\bfg\sigma_t^2$ in enacting the second step. An estimator is developed here that is unbiased in the presence of heteroskedasticity. Its behavior is examined along with the traditional estimator and another known to be unbiased in the absence of heteroskedasticity. The behavior of these corrective methods is also examined when the form and arguments of the skedastic function are misspecified. This is accomplished using Monte Carlo studies of several situations of interest.
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