Spatial Autoregression Techniques for Real Estate Data |
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| Authors: | Robin Dubin R Kelley Pace Thomas G Thibodeau |
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| Institution: | (1) Department of Economics, Case Western Reserve University, Cleveland, OH, 44106;(2) Louisiana Real Estate Commission Chair of Real Estate, Department of Finance, E.J. Ourso College of Business Administration, Louisiana State University, Baton Rouge, LA, 70803;(3) Department of Real Estate, Southern Methodist University, Edwin L. Cox School of Business, Dallas, TX, 75275 |
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| Abstract: | This paper describes how spatial techniques can be used to improve the accuracy of market value estimates obtained using multiple regression analysis. Rather than eliminating the problem of spatial residual dependencies through the inclusion of many independent variables, spatial statistical methods typically keep fewer independent variables and augment these with a simple model of the spatial error dependence. We discuss alternative spatial autoregression model specifications, estimation methods, and prediction procedures. An empirical example is provided in the appendix. |
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