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The impact of trails on property values: a spatial analysis

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Abstract

Convenient and local access to open green space is highly valued in many communities, particularly those comprised largely of individuals who participate in natural resource outdoor recreation. Understanding the value outdoor recreation communities place on access to open space is critical for informing policy decisions on land use including zoning and other restrictions, government open space purchases, and open space access points such as trailheads. In this article, we analyze the impact of trail access on property values in Ogden, Utah, using spatial hedonic pricing models. We consistently find substantial premiums for properties located closer to trailheads. Using a spatial Durbin error model, we find a 0.6% direct effect premium for each minute closer in driving time to the nearest trailhead, and a 1.4% premium when accounting for the total impact. We also find direct premiums between 0.4 and 1.9% for each minute closer in driving time to individual trailheads in this region. Additionally, homes adjacent to trailheads do not experience negative spillovers that homeowners may experience from increased traffic and congestion.

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Notes

  1. In addition to spatial fixed effects (Abbott and Klaiber 2010) and spatial parametric models (Anselin 1988), there are a wide variety of other techniques used to correct for spatial data issues, including geographically weighted regression (McMillen 2010), mixed geographically weighted regression (Helbich et al. 2013), generalized additive models (Hastie and Tibshirani 1990), and semi-parametric models (McMillen 2003). An overview and application of spatial econometric techniques as it applies to hedonic price models for a housing sample in Norway is presented by Osland (2010).

  2. The results in this paper are best interpreted as capitalization measures. Stronger assumptions are needed to extrapolate our findings of a capitalization effect into willingness-to-pay (WTP) since household sorting behavior may cause there to be a correlation between latent household characteristics and trail accessibility (Kuminoff and Pope 2014). For example, if a new trailhead were introduced, the adjustment to the hedonic function would cause households’ WTP to not equal the capitalization effect (Kuminoff and Pope 2014). We thank an anonymous reviewer for drawing our attention to this dynamic.

  3. Combining the valuation of these trailheads also makes intuitive sense due to the overlap in the trails for which they provide access.

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Author information

Authors and Affiliations

  1. Goddard School of Business and Economics, Weber State University, 1337 Edvalson St., Ogden, UT, 84403, USA

    Matthew Gnagey & Therese Grijalva

Authors
  1. Matthew Gnagey
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  2. Therese Grijalva
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Correspondence to Matthew Gnagey.

Appendix

Appendix

See Tables 7, 8, and 9.

Table 7 Linear regression results different trailheads—dependent variable: real log sale price (2016 USD)
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Table 8 Spatial Durbin error model regression—dependent variable: real log sale price (2016 USD)
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Table 9 Spatial Durbin error model regression with neighborhood variables—dependent variable: real log sale price (2016 USD)
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Gnagey, M., Grijalva, T. The impact of trails on property values: a spatial analysis. Ann Reg Sci 60, 73–97 (2018). https://doi.org/10.1007/s00168-017-0846-1

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