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weighted least squares (WLS) estimator: If the errors are heteroskedastic, then OLS is no longer BLUE. If the heteroskedasticity is known (i.e., if the conditional variance of given is known up to a constant factor of proportionality) then an alternate estimator exists with a smaller variance than the OLS estimator. This method, weighted least squares (WLS), weights the i th observation by the inverse of the square root of the conditional variance of given . Because of this weighting, the errors in this weighted regression are homoskedastic, so OLS, when applied to the weighted data, is BLUE.

This is what i read in your notes and also the Miller textbook. As it says if the error terms are heteroskedastic then there are other estimator apart of OLS estimator, whereas in the last line it says the errors are homeskedastic

This is what i read in your notes and also the Miller textbook. As it says if the error terms are heteroskedastic then there are other estimator apart of OLS estimator, whereas in the last line it says the errors are homeskedastic

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