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Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method 总被引:10,自引:3,他引:7
Christopher Bitter Gordon F. Mulligan Sandy Dall’erba 《Journal of Geographical Systems》2007,9(1):7-27
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.
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Christopher BitterEmail: |