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Spatial Econometric Approaches to Estimating Hedonic Property Value Models

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  • Wang, Li
  • Ready, Richard C.

Abstract

The inclusion of spatial correlation of house price in hedonic pricing model may produce better marginal implicit price estimate(s) of the environmental variable(s) of interest. Most applications where a spatial econometric model is applied to the estimation of a hedonic property value model have used either a spatial lag model or a spatial autoregressive (SAR) error model. Incorrect spatial specification may produce even worse estimate outcome than OLS. Three issues regarding the specification of a spatial hedonic pricing model are considered. First, we question the "convention" of row-standardizing the spatial weights matrix. Second, we argue that the spatial error component (SEC) model is more theoretically intuitive and appealing for modeling house price. Third, we explore whether the choice of spatial model is important, empirically, using a large house sale dataset that includes measures of proximity to landfills. With one exception, estimated marginal implicit prices are fairly robust across all models.

Suggested Citation

  • Wang, Li & Ready, Richard C., 2005. "Spatial Econometric Approaches to Estimating Hedonic Property Value Models," 2005 Annual meeting, July 24-27, Providence, RI 19174, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea05:19174
    DOI: 10.22004/ag.econ.19174
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    Cited by:

    1. Özyurt, Selin, 2014. "Spatial dependence in commercial property prices: micro evidence from the Netherlands," Working Paper Series 1627, European Central Bank.
    2. Khalid Haniza, 2015. "Spatial heterogeneity and spatial bias analyses in hedonic price models: some practical considerations," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 28(28), pages 113-128, June.
    3. Demetriou, Demetris, 2018. "Automating the land valuation process carried out in land consolidation schemes," Land Use Policy, Elsevier, vol. 75(C), pages 21-32.

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