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A Variance Comparison of OLS and Feasible GLS Estimators

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  • Grubb, David
  • Magee, Lonnie

Abstract

Second-order approximations to the variances of OLS and GLS estimators are compared when the covariance matrix is locally nonscalar. Using a result of Rothenberg, the comparison of OLS and GLS variances is shown to be asymptotically equivalent to a weighted mean square error comparison of the error covariance parameter estimators used in those two procedures. When there is only one covariance parameter, this comparison depends only on the noncentrality parameter of a classical hypothesis test for a scalar covariance matrix.

Suggested Citation

  • Grubb, David & Magee, Lonnie, 1988. "A Variance Comparison of OLS and Feasible GLS Estimators," Econometric Theory, Cambridge University Press, vol. 4(02), pages 329-335, August.
  • Handle: RePEc:cup:etheor:v:4:y:1988:i:02:p:329-335_01
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    Cited by:

    1. Dewandaru, Ginanjar & Rizvi, Syed Aun R. & Bacha, Obiyathulla I. & Masih, Mansur, 2014. "What factors explain stock market retardation in Islamic Countries," Emerging Markets Review, Elsevier, vol. 19(C), pages 106-127.
    2. Beck, Thorsten & Lundberg, Mattias & Majnoni, Giovanni, 2006. "Financial intermediary development and growth volatility: Do intermediaries dampen or magnify shocks?," Journal of International Money and Finance, Elsevier, vol. 25(7), pages 1146-1167, November.
    3. W. Robert Reed & Haichun Ye, 2007. "A Monte Carlo Evaluation of Some Common Panel Data Estimators when Serial Correlation and Cross-sectional Dependence are Both Present," Working Papers in Economics 07/01, University of Canterbury, Department of Economics and Finance.

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