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Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors

Author

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  • Dong Shin
  • Dai-Gyoung Kim
  • Han Kim

Abstract

For spatial regressions with sinusoidal surfaces, the ordinary least squares estimator (OLSE) is shown to be asymptotically as efficient as the geeralized least squares estimator (GLSE) in that the covariance matrices of the two estimators have the same nontrivial limit under the same normalization. Copyright Springer-Verlag 2002

Suggested Citation

  • Dong Shin & Dai-Gyoung Kim & Han Kim, 2002. "Efficiency of the OLSE for regressions on two-dimensional grids with sinusoidal regressors and spatially correlated errors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 56(3), pages 247-258, December.
    • Handle: RePEc:spr:metrik:v:56:y:2002:i:3:p:247-258
    DOI: 10.1007/s001840100177
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    References listed on IDEAS

    as
    1. Shin, Dong Wan & Oh, Man Suk, 2002. "Asymptotic Efficiency Of The Ordinary Least Squares Estimator For Regressions With Unstable Regressors," Econometric Theory, Cambridge University Press, vol. 18(5), pages 1121-1138, October.
    2. Shin, Dong Wan & Song, Seuck Heun, 2000. "Asymptotic efficiency of the OLSE for polynomial regression models with spatially correlated errors," Statistics & Probability Letters, Elsevier, vol. 47(1), pages 1-10, March.
    Full references (including those not matched with items on IDEAS)

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