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Optimal Spatial Prediction and the Construction of Regional Indexes

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  • Montes-Rojas, Gabriel V.

Abstract

This paper reviews the statistical methods for spatial prediction: the non-parametric “kriging” method and spatial autoregessive models. We discuss the main assumptions involved in each method as well as the advantages and disadvantages in each case. These methods are applied to the FPLI wage index for Florida counties, in order to illustrate a way to select the best econometric model and spatial weights.

Suggested Citation

  • Montes-Rojas, Gabriel V., 2012. "Optimal Spatial Prediction and the Construction of Regional Indexes," The Journal of Economic Asymmetries, Elsevier, vol. 9(1), pages 1-21.
    • Handle: RePEc:eee:joecas:v:9:y:2012:i:1:p:1-21
    DOI: 10.1016/j.jeca.2012.01.001
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    References listed on IDEAS

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    1. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    2. Roback, Jennifer, 1982. "Wages, Rents, and the Quality of Life," Journal of Political Economy, University of Chicago Press, vol. 90(6), pages 1257-1278, December.
    3. Dubin, Robin A, 1998. "Predicting House Prices Using Multiple Listings Data," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 35-59, July.
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