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A Unified Approach to Asymptotic Equivalence of Aitken and Feasible Aitken Instrumental Variables Estimators

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  • Mandy, David M
  • Martins-Filho, Carlos

Abstract

Asymptotic equivalence of Aitken and feasible Aitken estimators in linear models with nonscalar identity error covariance matrices is usually established in a tedious case-by-case manner. Some general sufficient conditions for this equivalence exist but there are problems with the extant conditions. These problems are discussed and new widely applicable sufficient conditions are presented and applied to a variety of error structures. Copyright 1994 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Suggested Citation

  • Mandy, David M & Martins-Filho, Carlos, 1994. "A Unified Approach to Asymptotic Equivalence of Aitken and Feasible Aitken Instrumental Variables Estimators," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(4), pages 957-979, November.
    • Handle: RePEc:ier:iecrev:v:35:y:1994:i:4:p:957-79
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    Cited by:

    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    3. Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.
    4. David Mandy & Sandor Fridli, 2004. "Exact FGLS Asymptotics for MA Errors," Working Papers 0405, Department of Economics, University of Missouri, revised 16 Dec 2004.
    5. Marco Avarucci & Paolo Zaffaroni, 2019. "Robust Nearly-Efficient Estimation of Large Panels with Factor Structures," Papers 1902.11181, arXiv.org.

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