Adding regressors to obtain efficiency created by Sung Jae Jun and Joris Pinkse

By:

Jun, Sung Jae [author]

Contributor(s):

Pinkse, Joris [author]

Material type: Text

TextSeries: Econometric theory ; Volume 25, number 1,Cambridge: Cambridge University Press, 2009Content type:

text

Media type:

unmediated

Carrier type:

volume

ISSN:

02664666

Subject(s):

Estimation theory -- Efficiency -- Regression analysis

LOC classification:

HB139.T52 ECO

Online resources:

Click here to access online

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.

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Item type	Current library	Call number	Vol info	Copy number	Status	Notes	Date due	Barcode
Journal Article	Main Library - Special Collections	HB139.T52 ECO (Browse shelf(Opens below))	Vol. 25, no.1 (pages 298-302)	SP3256	Not for loan	For In House Use Only

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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.

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