Space-time approach to commercial property prices valuation
There 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.
Volume (Year): 44 (2012)
Issue (Month): 28 (October)
|Contact details of provider:|| Web page: http://www.tandfonline.com/RAEC20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RAEC20|
When requesting a correction, please mention this item's handle: RePEc:taf:applec:44:y:2012:i:28:p:3705-3715. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.