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Participation, Trip Frequency and Site Choice: A Multinomial-Poisson Hurdle Model of Recreation Demand

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  • Yen, Steven
  • Adamowicz, Wiktor L.

Abstract

Data used in recreation demand modeling are characterized by the facts that trip frequencies are non-negative integers and that consumers are often faced with alternative destinations. This paper considers these features by estimating a multivariate recreation demand model that accounts for trip frequency and choice among alternative recreation sites using a mixed multinomial-Poisson hurdle distribution. The specification of the Poisson hurdle distribution at the aggregate level accounts for participation and trip frequency, and avoids the restrictive mean-variance property of the basic Poisson model. The model is estimated using data from Bighorn sheep hunters in Alberta, Canada. Simulation results suggest that changing price and quality variables cause substitution among sites. The welfare implications of changes in these variables are also examined.

Suggested Citation

  • Yen, Steven & Adamowicz, Wiktor L., 1994. "Participation, Trip Frequency and Site Choice: A Multinomial-Poisson Hurdle Model of Recreation Demand," Staff General Research Papers Archive 764, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genres:764
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    Citations

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    Cited by:

    1. Zandersen, Marianne & Termansen, Mette & Jensen, Frank S., 2007. "Evaluating approaches to predict recreation values of new forest sites," Journal of Forest Economics, Elsevier, vol. 13(2-3), pages 103-128, August.
    2. Termansen, Mette & Zandersen, Marianne & McClean, Colin J., 2008. "Spatial substitution patterns in forest recreation," Regional Science and Urban Economics, Elsevier, vol. 38(1), pages 81-97, January.
    3. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
    4. Daniel J. Phaneuf & Catherine L. Kling & Joseph A. Herriges, 2000. "Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 83-92, February.
    5. Phaneuf, Daniel James, 1997. "Generalized corner solution models in recreation demand," ISU General Staff Papers 1997010108000013022, Iowa State University, Department of Economics.
    6. Jakus, Paul M. & Dowell, Paula & Murray, Matthew N., 2000. "The Effect Of Fluctuating Water Levels On Reservoir Fishing," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(2), pages 1-13, December.
    7. Abdulbaki Bilgic & Wojciech Florkowski, 2009. "The impact of license regulation on the number of recreation trips: is it worth considering?," Journal of Regulatory Economics, Springer, vol. 35(1), pages 45-69, February.
    8. Reilly, Michael & Landis, John, 2003. "The Influence of Built-Form and Land Use on Mode Choice," University of California Transportation Center, Working Papers qt46r3k871, University of California Transportation Center.
    9. Phaneuf, Daniel J., 1999. "A Dual Approach to Modeling Corner Solutions in Recreation Demand," Journal of Environmental Economics and Management, Elsevier, vol. 37(1), pages 85-105, January.
    10. William Greene, 2009. "Models for count data with endogenous participation," Empirical Economics, Springer, vol. 36(1), pages 133-173, February.
    11. Allen, S. & Goddard, E., 2018. "The Effectiveness of High Sugar Warning Labels on Breakfast Cereals," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275885, International Association of Agricultural Economists.
    12. Sfeir, Georges & Abou-Zeid, Maya & Kaysi, Isam, 2020. "Multivariate count data models for adoption of new transport modes in an organization-based context," Transport Policy, Elsevier, vol. 91(C), pages 59-75.

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