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ADDING REGRESSORS TO OBTAIN EFFICIENCY

Published online by Cambridge University Press:  01 February 2009

Sung Jae Jun*
Affiliation:
Pennsylvania State University
Joris Pinkse
Affiliation:
Pennsylvania State University
*
*Address correspondence to Sung Jae Jun, CAPCP, Department of Economics, 608 Kern Graduate Bldg., University Park, PA 16802, USA; e-mail: sjun@psu.edu.

Abstract

It is well known that in standard linear regression models with independent and identically distributed data and homoskedasticity, adding “irrelevant regressors” hurts (asymptotic) efficiency unless such irrelevant regressors are orthogonal to the remaining regressors. But we have found that under (conditional) heteroskedasticity “irrelevant regressors” can always be found such that one can achieve the asymptotic variance of the generalized least squares estimator by adding the “irrelevant regressors” to the model.

Type
NOTES AND PROBLEMS
Copyright
Copyright © Cambridge University Press 2009

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References

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