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Prediction of Housing Location Price by a Multivariate Spatial Method: Cokriging

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  • Jorge Chica-Olmo

    (Universidad de Granada, Facultad de Ciencias Económicas y Empresariale, Campus Cartuja s/n. 18011-Granada. Spain.)

Abstract

Cokriging is a multivariate spatial method to estimate spatial correlated variables. This method allows spatial estimations to be made and interpolated maps of house price to be created. These maps are interesting for appraisers, real estate companies, and bureaus because they provide an overview of location prices. Kriging uses one variable of interest (house price) to make estimates at unsampled locations, and cokriging uses the variable of interest and auxiliary correlated variables. In this paper, housing location price is estimated using kriging methods, isotopic data cokriging, and heterotopic data cokriging methods. The results of these methods are then compared.

Suggested Citation

  • Jorge Chica-Olmo, 2007. "Prediction of Housing Location Price by a Multivariate Spatial Method: Cokriging," Journal of Real Estate Research, American Real Estate Society, vol. 29(1), pages 95-114.
    • Handle: RePEc:jre:issued:v:29:n:1:2007:p:95-114
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    References listed on IDEAS

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    2. Narula, Subhash C. & Wellington, John F. & Lewis, Stephen A., 2012. "Valuating residential real estate using parametric programming," European Journal of Operational Research, Elsevier, vol. 217(1), pages 120-128.
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    6. Jos魍ar𨁍ontero-Lorenzo & Beatriz Larraz-Iribas, 2012. "Space-time approach to commercial property prices valuation," Applied Economics, Taylor & Francis Journals, vol. 44(28), pages 3705-3715, October.
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