A general condition for an optimal limiting efficiency of OLS in the general linear regression model

Walter Krämer, Badi Baltagi

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

We give a general condition for disturbance covariance matrices in the general linear regression model which ensures that, in the limit, ordinary least squares is as efficient as generalized least squares as the disturbance covariance matrix approaches the edges of the parameter space. This condition includes many known efficiency results as special cases.

Original languageEnglish (US)
Pages (from-to)13-17
Number of pages5
JournalEconomics Letters
Volume50
Issue number1
DOIs
StatePublished - Jan 1996
Externally publishedYes

Keywords

  • Efficiency of OLS
  • Generalized least squares
  • Linear regression

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics

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