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Spurious spatial regression with equal weights

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  • Baltagi, Badi H.
  • Liu, Long

Abstract

This note studies the Lee and Yu (2009) spurious regression model for the special case where the weight matrix is normalized and has equal elements, and where the nonstationarity is caused by near unit roots. It shows that spurious spatial regression will not occur in a spatially autoregressive (SAR) model when the spatial weight matrix is row-normalized and has equal weights. In fact, the asymptotic distribution of the OLS estimate will always converge to its true value zero. The only condition required is that the spatial coefficients of the dependent and independent variables be both less than 1, which is a requirement for the SAR model to be an equilibrium model.

Suggested Citation

  • Baltagi, Badi H. & Liu, Long, 2010. "Spurious spatial regression with equal weights," Statistics & Probability Letters, Elsevier, vol. 80(21-22), pages 1640-1642, November.
    • Handle: RePEc:eee:stapro:v:80:y:2010:i:21-22:p:1640-1642
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    References listed on IDEAS

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    1. Lung-Fei Lee & Jihai Yu, 2009. "Spatial Nonstationarity and Spurious Regression: the Case with a Row-normalized Spatial Weights Matrix," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(3), pages 301-327.
    2. Baltagi, Badi H., 2006. "Random Effects And Spatial Autocorrelation With Equal Weights," Econometric Theory, Cambridge University Press, vol. 22(5), pages 973-984, October.
    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. Harry H. Kelejian & Ingmar R. Prucha & Yevgeny Yuzefovich, 2006. "Estimation Problems In Models With Spatial Weighting Matrices Which Have Blocks Of Equal Elements," Journal of Regional Science, Wiley Blackwell, vol. 46(3), pages 507-515, August.
    5. Baltagi, Badi H. & Liu, Long, 2009. "Spatial lag test with equal weights," Economics Letters, Elsevier, vol. 104(2), pages 81-82, August.
    6. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    7. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
    8. Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 252-277, April.
    9. 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.
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    Cited by:

    1. Martellosio, Federico, 2011. "Efficiency of the OLS estimator in the vicinity of a spatial unit root," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1285-1291, August.

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