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Travel Cost Method Considering Trip-day Counts as Integers

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  • Kono, Tatsuhito
  • Yoshida, Jun

Abstract

The Travel Cost Method (TCM) is a typical benefit measurement method, using the fact that people substitute the benefit of visiting some sites for their travel cost. However, in the case of tourist sites, travelers do not choose the number of days spent in a tourist city as continuous numbers but integer numbers. We investigate how a bias could arise from ignoring integer numbers of nights in TCM. We derive the formula of what factors constitute the bias. Next, we numerically show that when measuring benefits of improving quality at sites, the maximum bias could be around 20%.

Suggested Citation

  • Kono, Tatsuhito & Yoshida, Jun, 2020. "Travel Cost Method Considering Trip-day Counts as Integers," MPRA Paper 99244, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:99244
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    References listed on IDEAS

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    1. Anton Nahman & Dan Rigby, 2008. "Valuing Blue Flag Status And Estuarine Water Quality In Margate, South Africa1," South African Journal of Economics, Economic Society of South Africa, vol. 76(4), pages 721-737, December.
    2. Loomis, John B. & Yorizane, Shizuka & Larson, Douglas M., 2000. "Testing Significance Of Multi-Destination And Multi-Purpose Trip Effects In A Travel Cost Method Demand Model For Whale Watching Trips," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 29(2), pages 1-9, October.
    3. Craig E. Landry & Kenneth E. McConnell, 2007. "Hedonic Onsight Cost Model of Recreation Demand," Land Economics, University of Wisconsin Press, vol. 83(2), pages 253-267.
    4. Ian M. Dobbs, 1993. "Individual Travel Cost Method: Estimation and Benefit Assessment with a Discrete and Possibly Grouped Dependent Variable," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(1), pages 84-94.
    5. Shrestha, Ram K. & Seidl, Andrew F. & Moraes, Andre S., 2002. "Value of recreational fishing in the Brazilian Pantanal: a travel cost analysis using count data models," Ecological Economics, Elsevier, vol. 42(1-2), pages 289-299, August.
    6. Kuriyama, Koichi & Michael Hanemann, W. & Hilger, James R., 2010. "A latent segmentation approach to a Kuhn-Tucker model: An application to recreation demand," Journal of Environmental Economics and Management, Elsevier, vol. 60(3), pages 209-220, November.
    7. Douglas M. Larson, 1993. "Joint Recreation Choices and Implied Values of Time," Land Economics, University of Wisconsin Press, vol. 69(3), pages 270-286.
    8. K. G. Mäler & J. R. Vincent (ed.), 2005. "Handbook of Environmental Economics," Handbook of Environmental Economics, Elsevier, edition 1, volume 3, number 3.
    9. K. E. McConnell, 1992. "On-Site Time in the Demand for Recreation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(4), pages 918-925.
    10. Berman, Matthew D. & Kim, Hong Jin, 1999. "Endogenous On-Site Time In The Recreation Demand Model," 1999 Annual meeting, August 8-11, Nashville, TN 21616, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Alan Randall, 1994. "Difficulty with the Travel Cost Method," Land Economics, University of Wisconsin Press, vol. 70(1), pages 88-96.
    12. Chia-Yu Yeh & Timothy Haab & Brent Sohngen, 2006. "Modeling Multiple-Objective Recreation Trips with Choices Over Trip Duration and Alternative Sites," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(2), pages 189-209, June.
    13. Matthew D. Berman & Hong Jin Kim, 1999. "Endogenous On-Site Time in the Recreation Demand Model," Land Economics, University of Wisconsin Press, vol. 75(4), pages 603-619.
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    More about this item

    Keywords

    Project Evaluation; Travel cost method; Integer property;
    All these keywords.

    JEL classification:

    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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