Space-time approach to commercial property prices valuation
AbstractThere exists three ways of approaching real estate prices: the cost approach, the market data approach and the income capitalization approach. In this article, we propose an improvement of the market data approach that takes into account the spatial component. In particular, we propose a modified market data approach based on interpolation, being the structure of the spatial correlation between the prices of properties the main factor to obtain the weights. Interpolation methods have been widely used for estimating real estate prices, but they do not take into account the structure of their spatial dependence. Although this drawback is overcome by kriged estimation, in the case of the prices of commercial properties, they do not provide good estimates because the scarceness of the market information. This is why auxiliary information is needed and cokriging methods are used to obtain estimates that are more accurate. The aim of this article is the comparison of cokriged estimation of premises prices in two different temporal moments in the emblematic old part of Toledo city (Spain), using housing prices as an auxiliary random function due to their strong correlation with the main one. Cokriging, kriging and inverse distance weighting results are compared.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 44 (2012)
Issue (Month): 28 (October)
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Web page: http://www.tandfonline.com/RAEC20
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- Fernandes, Guilherme Barreto & Artes , Rinaldo, 2013. "Spatial correlation in credit risk and its improvement in credit scoring," Insper Working Papers wpe_321, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
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