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Individual Travel Cost Method: Estimation and Benefit Assessment with a Discrete and Possibly Grouped Dependent Variable

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  • Ian M. Dobbs

Abstract

The trip/visit variable in the individual travel cost method is often regarded as discrete. Furthermore, it is often reported in surveys as a grouped variable (the number of visits reported falling into one of several classes). This paper develops a travel cost model which takes account of discreteness and grouping in both demand and benefit estimation. A case study and associated simulations are then reported which indicate the potential extent of bias that may arise from ignoring discreteness/grouping in demand and benefit estimation. The information loss involved in varying the size of visit classes is also examined.

Suggested Citation

  • 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.
  • Handle: RePEc:oup:ajagec:v:75:y:1993:i:1:p:84-94.
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    File URL: http://hdl.handle.net/10.2307/1242956
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    Cited by:

    1. Bowker, James Michael & Starbuck, C. Meghan & English, Donald B.K. & Bergstrom, John C. & Rosenberger, Randall S. & McCollum, Daniel W., 2009. "Estimating the Net Economic Value of National Forest Recreation: An Application of the National Visitor Use Monitoring Database," Faculty Series 59603, University of Georgia, Department of Agricultural and Applied Economics.
    2. Park, Timothy A. & Bowker, James Michael & Leeworthy, Vernon R., 2000. "Valuing Snorkeling Visits To The Florida Keys With Stated And Revealed Preference Models," Faculty Series 16713, University of Georgia, Department of Agricultural and Applied Economics.
    3. 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.
    4. Juan Walter Tudela-Mamani, 2017. "Estimación de beneficios económicos por el mejoramiento del sistema de tratamiento de aguas residuales en la ciudad de Puno (Perú)," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, vol. 79(6), August.
    5. Ruchi Badola & Syed Ainul Hussain & Bidyut Kumar Mishra & Bidyarani Konthoujam & Sneha Thapliyal & Parag Madhukar Dhakate, 2010. "An assessment of ecosystem services of Corbett Tiger Reserve, India," Environment Systems and Decisions, Springer, vol. 30(4), pages 320-329, December.
    6. Kono, Tatsuhito & Yoshida, Jun, 2020. "Travel Cost Method Considering Trip-day Counts as Integers," MPRA Paper 106188, University Library of Munich, Germany, revised 18 Feb 2021.
    7. Tobias Börger & Anna Maccagnan & Mathew P. White & Lewis R. Elliott & Tim Taylor, 2023. "Was the trip worth it? Consistency between decision and experienced utility assessments of recreational nature visits," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(2), pages 525-545, March.
    8. Manuel González Gómez & Philippe Polomé & Albino Prada Blanco, 2001. "Functional Forms, Sampling Considerations, and Estimation of Demand for Protected Natural Areas: The CÌes Islands Case Study in Galicia (Spain)," Documentos de trabajo - Analise Economica 0016, IDEGA - Instituto Universitario de Estudios e Desenvolvemento de Galicia.

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