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The exact bias of s2 in linear panel regressions with spatial autocorrelation

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  • Hanck, Christoph
  • Krämer, Walter

Abstract

We investigate the OLS-based estimator s2 of the disturbance variance in an error component linear panel regression model when the disturbances are homoskedastic, but spatially correlated. Although consistent (Song and Lee, Econ. Lett. 2008), s2 can be arbitrarily biased towards zero in finite samples.

Suggested Citation

  • Hanck, Christoph & Krämer, Walter, 2011. "The exact bias of s2 in linear panel regressions with spatial autocorrelation," Economics Letters, Elsevier, vol. 110(1), pages 67-70, January.
  • Handle: RePEc:eee:ecolet:v:110:y:2011:i:1:p:67-70
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    References listed on IDEAS

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    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. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    3. Kelejian, Harry H. & Prucha, Ingmar R., 2002. "2SLS and OLS in a spatial autoregressive model with equal spatial weights," Regional Science and Urban Economics, Elsevier, vol. 32(6), pages 691-707, November.
    4. Sathe, S T & Vinod, H D, 1974. "Bounds on the Variance of Regression Coefficients Due to Heteroscedastic or Autoregressive Errors," Econometrica, Econometric Society, vol. 42(2), pages 333-340, March.
    5. Song, Seuck Heun & Lee, Jaejun, 2008. "A note on S2 in a spatially correlated error components regression model for panel data," Economics Letters, Elsevier, vol. 101(1), pages 41-43, October.
    6. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
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