ADDING REGRESSORS TO OBTAIN EFFICIENCY
Sung Jae Jun () and
Econometric Theory, 2009, vol. 25, issue 1, 298-301
It is well known that in standard linear regression models with independent and identically distributed data and homoskedasticity, adding â€œirrelevant regressorsâ€ hurts (asymptotic) efficiency unless such irrelevant regressors are orthogonal to the remaining regressors. But we have found that under (conditional) heteroskedasticity â€œirrelevant regressorsâ€ can always be found such that one can achieve the asymptotic variance of the generalized least squares estimator by adding the â€œirrelevant regressorsâ€ to the model.
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