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Generalized Least Squares

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References

  • Baltagi, B.H. (1992), “Sampling Distributions and Efficiency Comparisons of OLS and GLS in the Presence of Both Serial Correlation and Heteroskedasticity,” Econometric Theory, Problem 92.2.3, 8: 304–305.

    Google Scholar 

  • Breusch, T.S. (1979), “Conflict Among Criteria for Testing Hypotheses: Extensions and Comments,” Econometrica, 47: 203–207.

    Article  Google Scholar 

  • Dufour, J.M. (1986), “Bias of s2 in Linear Regressions with Dependent Errors,” The American Statistician, 40: 284–285.

    Google Scholar 

  • Goldberger, A.S. (1962), “Best Linear Unbiased Prediction in the Generalized Linear Regression Model,” Journal of the American Statistical Association, 57: 369–375.

    Article  Google Scholar 

  • Ioannides, Y.M. and J.E Zabel (2003), “Neighbourhood Effects and Housing Demand,” Journal of Applied Econometrics 18: 563–584.

    Article  Google Scholar 

  • Krämer, W. and S. Berghoff (1991), “Consistency of s2 in the Linear Regression Model with Correlated Errors,” Empirical Economics, 16: 375–377.

    Article  Google Scholar 

  • Neudecker, H. (1977), “Bounds for the Bias of the Least Squares Estimator of s2 in Case of a First-Order Autoregressive Process (positive autocorrelation),” Econometrica, 45: 1257–1262.

    Article  Google Scholar 

  • Neudecker, H. (1978), ”Bounds for the Bias of the LS Estimator in the Case of a First-Order (positive) Autoregressive Process Where the Regression Contains a Constant Term,” Econometrica, 46: 1223–1226.

    Article  Google Scholar 

  • Sathe, S.T. and H.D. Vinod (1974), “Bounds on the Variance of Regression Coefficients Due to Heteroscedastic or Autoregressive Errors,” Econometrica, 42: 333–340.

    Article  Google Scholar 

  • Zyskind, G. (1967), “On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models,” The Annals of Mathematical Statistics, 38: 1092–1109.

    Article  Google Scholar 

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Baltagi, B.H. (2015). Generalized Least Squares. In: Solutions Manual for Econometrics. Springer Texts in Business and Economics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54548-1_9

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  • DOI: https://doi.org/10.1007/978-3-642-54548-1_9

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