If the errors are heteroskedastic, then
A)OLS is BLUE.
B)WLS is BLUE if the conditional variance of the errors is known up to a constant factor of proportionality.
C)LAD is BLUE if the conditional variance of the errors is known up to a constant factor of proportionality.
D)OLS is efficient.

Question

Quizplus · Accepted Answer

Heteroskedasticity means that the variance of the error terms is not constant across all observations. In this case, OLS is inefficient and produces biased estimators. Weighted Least Squares (WLS) is one possible solution, where the weights are chosen based on the inverse of the conditional variance function of the errors. However, this requires knowledge of the functional form of the variance function, which is often unknown. If the variance function is known up to a constant factor of proportionality, then WLS is BLUE. LAD is not a suitable method for correcting heteroskedasticity.

If the Errors Are Heteroskedastic, Then