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

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  • Christopher Bitter
  • Gordon Mulligan
  • Sandy Dall’erba

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.
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Suggested Citation

  • Christopher Bitter & Gordon Mulligan & Sandy Dall’erba, 2007. "Incorporating spatial variation in housing attribute prices: a comparison of geographically weighted regression and the spatial expansion method," Journal of Geographical Systems, Springer, vol. 9(1), pages 7-27, April.
  • Handle: RePEc:kap:jgeosy:v:9:y:2007:i:1:p:7-27
    DOI: 10.1007/s10109-006-0028-7
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    1. William M. Bowen & Brian A. Mikelbank & Dean M. Prestegaard, 2001. "Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Model Applications," Growth and Change, Wiley Blackwell, vol. 32(4), pages 466-490.
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    4. Timothy J. Fik & David C. Ling & Gordon F. Mulligan, 2003. "Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(4), pages 623-646, December.
    5. Schnare, Ann B. & Struyk, Raymond J., 1976. "Segmentation in urban housing markets," Journal of Urban Economics, Elsevier, vol. 3(2), pages 146-166, April.
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    More about this item

    Keywords

    Hedonic model; House price; Spatial heterogeneity; Expansion method; Geographically weighted regression; C31; C51; C52; R21; R31;
    All these keywords.

    JEL classification:

    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General

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