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Partial efficient estimation of SUR models

Author

Listed:
  • Hailong Qian

    (Saint Louis University)

  • Heather L. Bednarek

    (Saint Louis University)

Abstract

In this paper, we consider efficient estimation of coefficients of interest in seemingly unrelated regressions (SUR) models. Using the GMM interpretation of the usual OLS and GLS/FGLS estimation of regression coefficients in SUR models, we derive the necessary and sufficient condition for the equal asymptotic efficiency of the OLS and FGLS estimators of a subset of regression coefficients. As a result, our paper extends the current SUR literature on the numerical equality of the OLS and GLS/FGLS estimators of the whole coefficient vector (see for example, Dwivedi and Srivastava, 1978) to the asymptotic equivalence of the OLS and GLS/FGLS estimators of a subset of the coefficient vector.

Suggested Citation

  • Hailong Qian & Heather L. Bednarek, 2015. "Partial efficient estimation of SUR models," Economics Bulletin, AccessEcon, vol. 35(1), pages 338-348.
    • Handle: RePEc:ebl:ecbull:eb-14-00569
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    References listed on IDEAS

    as
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    Cited by:

    1. Heather L. Bednarek & Hailong Qian, 2016. "The optimality of non-optimal GMM estimation of parameters of interest and the partial asymptotic efficiency of 2SLS estimation," Economics Bulletin, AccessEcon, vol. 36(3), pages 1636-1649.

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    More about this item

    Keywords

    SUR models; OLS; GLS; FGLS; GMM; Moment conditions; Partial redundancy of moment conditions;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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