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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 7-27 |
| Number of pages | 21 |
| Journal | Journal of Geographical Systems |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| State | Published - Apr 2007 |
Fingerprint
Keywords
- Expansionmethod
- Geographically weighted regression
- Hedonic model
- Houseprice
- Spatialheterogeneity
ASJC Scopus subject areas
- Geography, Planning and Development
Cite this
Incorporating spatial variation in housing attribute prices : A comparison of geographically weighted regression and the spatial expansion method. / Bitter, Christopher; Mulligan, Gordon F.; Dall Erba, Sandy.
In: Journal of Geographical Systems, Vol. 9, No. 1, 04.2007, p. 7-27.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Incorporating spatial variation in housing attribute prices
T2 - A comparison of geographically weighted regression and the spatial expansion method
AU - Bitter, Christopher
AU - Mulligan, Gordon F.
AU - Dall Erba, Sandy
PY - 2007/4
Y1 - 2007/4
N2 - 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.
AB - 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.
KW - Expansionmethod
KW - Geographically weighted regression
KW - Hedonic model
KW - Houseprice
KW - Spatialheterogeneity
UR - http://www.scopus.com/inward/record.url?scp=33947097410&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33947097410&partnerID=8YFLogxK
U2 - 10.1007/s10109-006-0028-7
DO - 10.1007/s10109-006-0028-7
M3 - Article
AN - SCOPUS:33947097410
VL - 9
SP - 7
EP - 27
JO - Journal of Geographical Systems
JF - Journal of Geographical Systems
SN - 1435-5930
IS - 1
ER -