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Understanding the impact of trails on residential property values in the presence of spatial dependence

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Abstract

This paper examines the impacts of a multi-purpose trail on residential property values in a hedonic model. Using a large housing data set in combination with street network distances, we show that proximity to trail entrances positively effects property values. Among other things, our study compares the hedonic model results from three different spatial specifications. We pay specific attention to the direct and indirect effects on residential property prices associated with potential changes in house characteristics. In addition, our study predicts property values around trail entrances using a ‘modified spatial predictive process’ approach that is well suited for capturing spatial dependence in large data sets.

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Notes

  1. ‘Friends’ help out scenic Little Miami trail: Loveland—For supporters of the Little Miami Scenic Trail, their charge borders on a sacred trust, Cincinnati Enquirer August 21 2010. The 2 days of count were Wednesday, July 28 and Sunday, August 8 2010.

  2. Estimation results available on requests.

  3. Not to be confused with the assessed value used for property tax calculations which, in Ohio, is simply defined as 35 % of the true market value.

  4. Markov Chain Monte Carlo estimation results are based on a simulated chain where the first 5,000 samples are discarded as a ‘burn-in’ period, followed by 15,000 iterations that were collected to produce posterior summaries for the parameters of interest.

  5. Since the spacing of the locations is relatively irregular, we could use a space-covering design (see Royle and Nychka 1998). To overcome this issue, we implement a larger numbers of knots making sure that results are robust to the selection of knots.

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Acknowledgments

We would like to thank the University of Cincinnati for support of this research through an University Research Council (URC) Interdisciplinary Grant. We want to thank also David Brasington for providing us with data about school districts and tax rates, Thomas Wuerzer and Kat Haessler for their support with the ArcGis network analysis, and Andrea Yang for all of her editorial work.

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Authors and Affiliations

  1. Department of Economics, University of Cincinnati, Cincinnati, OH, 45221, USA

    Olivier Parent

  2. School of Planning, University of Cincinnati, Cincinnati, OH, 45221, USA

    Rainer vom Hofe

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  1. Olivier Parent
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  2. Rainer vom Hofe
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Correspondence to Olivier Parent.

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Parent, O., vom Hofe, R. Understanding the impact of trails on residential property values in the presence of spatial dependence. Ann Reg Sci 51, 355–375 (2013). https://doi.org/10.1007/s00168-012-0543-z

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