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[This chapter discusses different specifications of linear spatial econometric models that can be considered once the hypothesis of no spatial autocorrelation in the disturbances is violated. A general form to take into account the violation of the ideal conditions for the applicability of OLS is given by the following set of equations: (3.1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$y=\lambda Wy+X{{\beta }_{{\left( 1 \right)}}}+WX{{\beta }_{{\left( 2 \right)}}}+u\quad \left| \lambda \right|<1$$\end{document}(3.2)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$u=\rho Wu+\varepsilon \quad \left| \rho \right|<1$$\end{document} with X a matrix of non-stochastic regressors, W a weight matrix exogenously given, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varepsilon \left| {X\approx i.i.d.N\left( {0,\sigma {{{_{\varepsilon }^{2}}}_{n}}{{I}_{n}}} \right)} \right.$$\end{document} and β(1), β(2) λ and ρ parameters to be estimated. The restrictions on the parameters λ and ρ hold if W is row-standardized. ]
Published: Nov 9, 2015
Keywords: Generalize Little Square; Spatial Error Model; Spatial Econometric; Spatial Autoregressive Model; Feasible Generalize Little Square
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