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

Chris Bitter, Gordon Mulligan () and Sandy Dall'erba ()

MPRA Paper from University Library of Munich, Germany

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.

JEL-codes: R0 (search for similar items in EconPapers)
Date: 2006
New Economics Papers: this item is included in nep-geo, nep-mic and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Related works:
Journal Article: Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:1379

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