Valuing urban open space using the travel-cost method and the implications of measurement error

Urbanization has placed pressure on open space within and adjacent to cities. In recent decades, a greater awareness has developed to the fact that individuals derive multiple benefits from urban open space. Given the location, there is often a high opportunity cost to preserving urban open space, t...

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Veröffentlicht in:Journal of environmental management 2017-08, Vol.198 (Pt 2), p.50-65
Hauptverfasser: Hanauer, Merlin M., Reid, John
Format: Artikel
Sprache:eng
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Zusammenfassung:Urbanization has placed pressure on open space within and adjacent to cities. In recent decades, a greater awareness has developed to the fact that individuals derive multiple benefits from urban open space. Given the location, there is often a high opportunity cost to preserving urban open space, thus it is important for both public and private stakeholders to justify such investments. The goals of this study are twofold. First, we use detailed surveys and precise, accessible, mapping methods to demonstrate how travel-cost methods can be applied to the valuation of urban open space. Second, we assess the degree to which typical methods of estimating travel times, and thus travel costs, introduce bias to the estimates of welfare. The site we study is Taylor Mountain Regional Park, a 1100-acre space located immediately adjacent to Santa Rosa, California, which is the largest city (∼170,000 population) in Sonoma County and lies 50 miles north of San Francisco. We estimate that the average per trip access value (consumer surplus) is $13.70. We also demonstrate that typical methods of measuring travel costs significantly understate these welfare measures. Our study provides policy-relevant results and highlights the sensitivity of urban open space travel-cost studies to bias stemming from travel-cost measurement error. •Travel-cost method is used to estimate the recreational value of Taylor Mountain Regional Park.•Precise point of origin and routing is compared to traditional estimates of distance and time.•Traditional approaches significantly understate the welfare estimates.
ISSN:0301-4797
1095-8630
DOI:10.1016/j.jenvman.2017.05.005