Article

The Journal of Real Estate Finance and Economics

, Volume 41, Issue 2, pp 150-169

First online:

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

  • Delores ConwayAffiliated withMarshall School of Business, University of Southern California
  • , Christina Q. LiAffiliated withDepartment of Geography, College of Letters, Arts and Sciences, University of Southern California Email author 
  • , Jennifer WolchAffiliated withDepartment of Geography, College of Letters, Arts and Sciences, University of Southern California
  • , Christopher KahleAffiliated withDepartment of Geography, College of Letters, Arts and Sciences, University of Southern California
  • , Michael JerrettAffiliated withSchool of Public health, University of California

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Abstract

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.

Keywords

Housing value Urban greenspace Hedonic pricing model Spatial dependence