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Journal of Geographical Systems

Erschienen in:

01.12.2009 | Original Article

Estimating commercial property prices: an application of cokriging with housing prices as ancillary information

verfasst von: José-María Montero-Lorenzo, Beatriz Larraz-Iribas, Antonio Páez

Erschienen in: Journal of Geographical Systems | Ausgabe 4/2009

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Abstract

A vast majority of the recent literature on spatial hedonic analysis has been concerned with residential property values, with only very few examples of studies focused on commercial property prices. The dearth of studies can be attributed to some of the challenges faced in the analysis of commercial properties, in particular the scarcity of information compared to residential transactions. In order to address this issue, in this paper we propose the use of cokriging and housing prices as ancillary information to estimate commercial property prices. Cokriging takes into account the spatial autocorrelation structure of property prices, and the use of more abundant information on housing prices helps to improve the accuracy of property value estimates. A case study of Toledo in Spain, a city for which commercial activity stemming from tourism is one of the key elements of the economy in the city, demonstrates that substantial accuracy and precision gains can be obtained from the use of cokriging.

Vorheriger Artikel Area-to-point Kriging in spatial hedonic pricing models

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The analysis has been conducted in terms of price per square meter.

Adjusted for housing and commercial property mix, in Fotheringham et al. (2002) terminology, although these authors also use the expression “equivalent houses”.

See http://www.geovariances.fr.

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Titel: Estimating commercial property prices: an application of cokriging with housing prices as ancillary information
verfasst von: José-María Montero-Lorenzo
Beatriz Larraz-Iribas
Antonio Páez
Publikationsdatum: 01.12.2009
Verlag: Springer-Verlag
Erschienen in: Journal of Geographical Systems / Ausgabe 4/2009
Print ISSN: 1435-5930
Elektronische ISSN: 1435-5949
DOI: https://doi.org/10.1007/s10109-009-0095-7

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