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.
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Notes
Delinquent tax properties could be an opportunity for open space, but municipalities such as city of Los Angeles historically have been reluctant to do so (Harnik 2000).
The vacant lot value is based on the transaction data of this neighborhood in 2000. The improvement cost is based on 2006 data for a 0.32 acre pocket park construction project in Los Angeles County.
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We would like to thank the anonymous reviewers for their comments that helped improve the paper. All omissions or errors remain our own.
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Conway, D., Li, C.Q., Wolch, J. et al. A Spatial Autocorrelation Approach for Examining the Effects of Urban Greenspace on Residential Property Values. J Real Estate Finan Econ 41, 150–169 (2010). https://doi.org/10.1007/s11146-008-9159-6
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DOI: https://doi.org/10.1007/s11146-008-9159-6