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Journal of Geographical Systems

Erschienen in:

01.04.2007 | Original Article

Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method

verfasst von: Christopher Bitter, Gordon F. Mulligan, Sandy Dall’erba

Erschienen in: Journal of Geographical Systems | Ausgabe 1/2007

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Abstract

Hedonic house price models typically impose a constant price structure on housing characteristics throughout an entire market area. However, there is increasing evidence that the marginal prices of many important attributes vary over space, especially within large markets. In this paper, we compare two approaches to examine spatial heterogeneity in housing attribute prices within the Tucson, Arizona housing market: the spatial expansion method and geographically weighted regression (GWR). Our results provide strong evidence that the marginal price of key housing characteristics varies over space. GWR outperforms the spatial expansion method in terms of explanatory power and predictive accuracy.

Vorheriger Artikel Spatial perspectives on urban systems: developments and directions

Nächster Artikel Geographic clustering of firms and urban form: a multivariate analysis

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Titel: Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method
verfasst von: Christopher Bitter
Gordon F. Mulligan
Sandy Dall’erba
Publikationsdatum: 01.04.2007
Verlag: Springer-Verlag
Erschienen in: Journal of Geographical Systems / Ausgabe 1/2007
Print ISSN: 1435-5930
Elektronische ISSN: 1435-5949
DOI: https://doi.org/10.1007/s10109-006-0028-7

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