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A Generalized Spatial Two Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances

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Abstract

Cross sectional spatial models frequently contain a spatial lag of the dependent variable as a regressor, or a disturbance term which is spatially autoregressive. In this paper we describe a computationally simple procedure for estimating cross sectional models which contain both of these characteristics. We also give formal large sample results.

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  • Harry H. Kelejian & Ingmar R. Prucha, 1997. "A Generalized Spatial Two Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," Electronic Working Papers 97-002, University of Maryland, Department of Economics, revised Aug 1997.
  • Handle: RePEc:umd:umdeco:97-002
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    1. Herman J. Bierens & A. R. Gallant (ed.), 1997. "Nonlinear Models," Books, Edward Elgar Publishing, volume 0, number 878.
    2. Blommestein, Hans J., 1983. "Specification and estimation of spatial econometric models : A discussion of alternative strategies for spatial economic modelling," Regional Science and Urban Economics, Elsevier, vol. 13(2), pages 251-270, May.
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    6. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-965, July.
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    More about this item

    Keywords

    Spatial Models; Autocorrelation; Two Stage Least Squares; Generalized Moments Estimator;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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