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Generalized least squares estimation of the functional multivariate linear errors-in-variables model

Author

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  • Dahm, P. Fred
  • Fuller, Wayne A.

Abstract

Estimators of the parameters of the functional multivariate linear errors-in-variables model are obtained by the application of generalized least squares to the sample matrix of mean squares and products. The generalized least squares estimators are shown to be consistent and asymptotically multivariate normal. Relationships between generalized least squares estimation of the functional model and of the structural model are demonstrated. It is shown that estimators constructed under the assumption of normal x are appropriate for fixed x.

Suggested Citation

  • Dahm, P. Fred & Fuller, Wayne A., 1986. "Generalized least squares estimation of the functional multivariate linear errors-in-variables model," Journal of Multivariate Analysis, Elsevier, vol. 19(1), pages 132-141, June.
    • Handle: RePEc:eee:jmvana:v:19:y:1986:i:1:p:132-141
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    Cited by:

    1. Scott Gilbert & Petr Zemčík, 2005. "Testing for Latent Factors in Models with Autocorrelation and Heteroskedasticity of Unknown Form," Southern Economic Journal, John Wiley & Sons, vol. 72(1), pages 236-252, July.
    2. Bai, Jushan, 2013. "Likelihood approach to dynamic panel models with interactive effects," MPRA Paper 50267, University Library of Munich, Germany.
    3. Patriota, Alexandre G. & Bolfarine, Heleno & Arellano-Valle, Reinaldo B., 2011. "A multivariate ultrastructural errors-in-variables model with equation error," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 386-392, February.
    4. Albert Satorra, 1996. "Fusion of data sets in multivariate linear regression with errors-in-variables," Economics Working Papers 183, Department of Economics and Business, Universitat Pompeu Fabra.

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