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The Use of the Geographically Weighted Regression for the Real Estate Market Analysis

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  • Cellmer Radosław

    (University of Warmia and Mazury in Olsztyn Faculty of Geodesy and Land Management Department of Real Estate Management and Regional Development Prawochenskiego 15, 10-720 Olsztyn, Poland)

Abstract

The article presents a method for developing geographically weighted regression models for analyzing real estate market transaction prices and evaluating the effect of selected property attributes on the prices and value of real estate. The property attributes were evaluated on a grading scale to determine the relative (percentage) indicators characterizing the relationships on the real estate market. The market data were analyzed to evaluate the influence of infrastructure availability on the prices of land in Olsztyn. The results were used to assess the effect of every utility service on the property transaction prices.

Suggested Citation

  • Cellmer Radosław, 2012. "The Use of the Geographically Weighted Regression for the Real Estate Market Analysis," Folia Oeconomica Stetinensia, Sciendo, vol. 11(1), pages 19-32, January.
    • Handle: RePEc:vrs:foeste:v:11:y:2012:i:1:p:19-32:n:4
    DOI: 10.2478/v10031-012-0009-6
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    References listed on IDEAS

    as
    1. Alain Bonnafous & Marko Kryvobokov, 2011. "Insight into apartment attributes and location with factors and principal components," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 4(2), pages 155-171, May.
    2. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
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