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A Contingent Trip Model for Estimating Rail-trail Demand

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  • Carter Betz
  • John Bergstrom
  • J. M. Bowker

Abstract

The authors develop a contingent trip model to estimate the recreation demand for and value of a potential rail-trail site in north-east Georgia. The contingent trip model is an alternative to travel cost modelling useful for ex ante evaluation of proposed recreation resources or management alternatives. The authors estimate the empirical demand for trips using a negative binomial regression specification. Their findings indicate a per-trip consumer surplus ranging from US$18.46 to US$29.23 and a price elasticity of m 0.68. In aggregate, they estimate that the rail-trail would receive approximately 416 213 recreation visits per year by area households and account for a total consumer surplus in excess of US$7.5 million.

Suggested Citation

  • Carter Betz & John Bergstrom & J. M. Bowker, 2003. "A Contingent Trip Model for Estimating Rail-trail Demand," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 46(1), pages 79-96.
  • Handle: RePEc:taf:jenpmg:v:46:y:2003:i:1:p:79-96
    DOI: 10.1080/713676704
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    Cited by:

    1. Munhyang (Moon) Oh & Seongseop (Sam) Kim & Youngjoon Choi, 2020. "Analyses of determinants of hiking tourism demands on the Jeju Olle hiking trail using zero-truncated negative binomial regression analysis," Tourism Economics, , vol. 26(8), pages 1327-1343, December.
    2. Bowker, James Michael & Murphy, D. & Cordell, H. Ken & English, Donald B.K. & Bergstrom, John C. & Starbuck, C. Meghan & Betz, Carter J. & Green, Gary T., 2006. "Wilderness and Primitive Area Recreation Participation and Consumption: An Examination of Demographic and Spatial Factors," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(2), pages 1-10, August.
    3. Blackwell, Melanie & Pagoulatos, Angelos & Hu, Wuyang & Auchter, Katharine, 2009. "Recreational Demand for Equestrian Trail-Riding," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 38(2), pages 1-11, October.
    4. Luís Cruz & Paula Simões & Eduardo Barata, 2014. "Combining Observed and Contingent Travel Behaviour: The Best of Both Worlds?," Notas Económicas, Faculty of Economics, University of Coimbra, issue 40, pages 7-25, December.
    5. R. Martínez-Espiñeira, 2007. "‘Adopt a Hypothetical Pup’: A Count Data Approach to the Valuation of Wildlife," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 37(2), pages 335-360, June.
    6. Rovelli, Roberto & Senes, Giulio & Fumagalli, Natalia & Sacco, Jessica & De Montis, Andrea, 2020. "From railways to greenways: a complex index for supporting policymaking and planning. A case study in Piedmont (Italy)," Land Use Policy, Elsevier, vol. 99(C).
    7. Mataria, Awad & Donaldson, Cam & Luchini, Stephane & Moatti, Jean-Paul, 2004. "A stated preference approach to assessing health care-quality improvements in Palestine: from theoretical validity to policy implications," Journal of Health Economics, Elsevier, vol. 23(6), pages 1285-1311, November.
    8. John C. Whitehead & John Lehman & Melissa Weddell, 2016. "A Benefit-Cost Analysis of the Middle Fork Greenway Trail," Working Papers 16-01, Department of Economics, Appalachian State University, revised 2016.
    9. Simões, Paula & Barata, Eduardo & Cruz, Luís, 2013. "Joint estimation using revealed and stated preference data: An application using a national forest," Journal of Forest Economics, Elsevier, vol. 19(3), pages 249-266.
    10. Abdulrahman A. Zawawi & Nicole Porter & Christopher D. Ives, 2023. "Influences on Greenways Usage for Active Transportation: A Systematic Review," Sustainability, MDPI, vol. 15(13), pages 1-37, July.
    11. Senes, Giulio & Rovelli, Roberto & Bertoni, Danilo & Arata, Laura & Fumagalli, Natalia & Toccolini, Alessandro, 2017. "Factors influencing greenways use: Definition of a method for estimation in the Italian context," Journal of Transport Geography, Elsevier, vol. 65(C), pages 175-187.
    12. Amoako-Tuffour, Joe & Martınez-Espineira, Roberto, 2008. "Leisure and the Opportunity Cost of Travel Time in Recreation Demand Analysis: A Re-Examination," MPRA Paper 8573, University Library of Munich, Germany.
    13. Ruiz, Tomás & Bernabé, José C., 2014. "Measuring factors influencing valuation of nonmotorized improvement measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 195-211.
    14. Roberto Martinez-Espineira & Joe Amoako-Tuffour, 2005. "Recreation Demand Analysis under Truncation, Overdispersion, and Endogenous Stratification: An Application to Gros Morne National Park," Econometrics 0511007, University Library of Munich, Germany.

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