An investigation of an unbiased correction 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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- David A. Belsley, 1996.
"A Small-Sample Correction for Testing for gth-Order Serial Correlation with Artificial Regressions,"
Boston College Working Papers in Economics
331., Boston College Department of Economics.
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