A {Spatial} {Autocorrelation} {Approach} for {Examining} the {Effects} of {Urban} {Greenspace} on {Residential} {Property} {Values}

  • Conway D
  • Li C
  • Wolch J
 et al. 
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This paper presents spatially explicit analyses of the greenspace contribution to residential property values in a hedonic model. The paper utilizes data from the housing market near downtown Los Angeles. We first used a standard hedonic model to estimate greenspace effects. Because the residuals were spatially autocorrelated, we implemented a spatial lag model as indicated by specification tests. Our results show that neighborhood greenspace at the immediate vicinity of houses has a significant impact on house prices even after controlling for spatial autocorrelation. The different estimation results from non-spatial and spatial models provide useful bounds for the greenspace effect. Greening of inner city areas may provide a valuable policy instrument for elevating depressed housing markets in those areas.

Author-supplied keywords

  • Finance /Banking
  • Hedonic pricing model
  • Housing value
  • Regional/Spatial Science
  • Spatial dependence
  • Urban greenspace

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  • Delores Conway

  • Christina Q Li

  • Jennifer Wolch

  • Christopher Kahle

  • Michael Jerrett

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