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Robustness of Spatial Autocorrelation Specifications: Some Monte Carlo Evidence

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  • Robin Dubin

Abstract

This paper examines the robustness of various models of spatial autocorrelation through a series of Monte Carlo experiments in which each model takes a turn at the data generator. The generated data are then used to estimate all of the models. The estimated models are evaluated primarily on their predictive power. Copyright Blackwell Publishing, Inc 2003

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  • Robin Dubin, 2003. "Robustness of Spatial Autocorrelation Specifications: Some Monte Carlo Evidence," Journal of Regional Science, Wiley Blackwell, vol. 43(2), pages 221-248.
  • Handle: RePEc:bla:jregsc:v:43:y:2003:i:2:p:221-248
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    Cited by:

    1. Yong Tu & Seow Ong & Ying Han, 2009. "Turnovers and Housing Price Dynamics: Evidence from Singapore Condominium Market," The Journal of Real Estate Finance and Economics, Springer, vol. 38(3), pages 254-274, April.
    2. Marko Kryvobokov, 2011. "Defining apartment neighbourhoods with Thiessen polygons and fuzzy equality clustering," ERES eres2011_142, European Real Estate Society (ERES).
    3. Takafumi Kato, 2008. "A Further Exploration Into The Robustness Of Spatial Autocorrelation Specifications," Journal of Regional Science, Wiley Blackwell, vol. 48(3), pages 615-639.
    4. Zengwang Xu & Robert Harriss, 2010. "A Spatial and Temporal Autocorrelated Growth Model for City Rank—Size Distribution," Urban Studies, Urban Studies Journal Limited, vol. 47(2), pages 321-335, February.
    5. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "The relative efficiencies of various predictors in spatial econometric models containing spatial lags," Regional Science and Urban Economics, Elsevier, vol. 37(3), pages 363-374, May.
    6. Jesus Mur & Ana Angulo, 2005. "A closer look at the Spatial Durbin Model," ERSA conference papers ersa05p392, European Regional Science Association.
    7. Takafumi Kato, 2013. "Usefulness of the Information Contained in the Prediction Sample for the Spatial Error Model," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 169-195, July.
    8. Yong Tu & Helen X.H. Bao, 2009. "Property Rights and Housing Value: The Impacts of Political Instability," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(2), pages 235-257.
    9. Kato, Takafumi, 2012. "Prediction in the lognormal regression model with spatial error dependence," Journal of Housing Economics, Elsevier, vol. 21(1), pages 66-76.
    10. repec:bla:presci:v:96:y:2017:i:2:p:357-380 is not listed on IDEAS
    11. Kato, Takafumi, 2013. "A comparison of spatial error models through Monte Carlo experiments," Economic Modelling, Elsevier, vol. 30(C), pages 743-753.

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