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Participation decisions, angler welfare, and the regional economic impact of sportfishing

Author

Listed:
  • Keith Criddle
  • M. Herrmann
  • S. Lee
  • C. Hamel

Abstract

Data from a stated preference survey of anglers who fished in marine waters off the Kenai Peninsula, Alaska, are used to model angler participation, angler welfare, and regional economic activity. The probability of taking a sportfishing trip is represented as a nonlinear function of predictable or controllable trip attributes and demographic characteristics. Conditional individual probabilities are aggregated into estimates of total recreation demand and compensating variation using a simulation-based sample enumeration, weighted to reflect differences in participant motivation. A regionally adjusted zip code-level input-output model is used to represent the level of primary and secondary expenditures conditioned on participation. This approach results in a behaviorally based integrated model for exploring the changes in angler welfare and regional economic activity occasioned by changes in the demand for sportfishing that arise from changes in trip costs or the expected number, size, or mix of species caught. Because the model allows for nonlinear marginal utility, and substitution and complementary effects across attributes, participation rates, angler welfare, and the magnitude of regional economic activities exhibit nonlinear responses to variations in trip attributes.

Suggested Citation

  • Keith Criddle & M. Herrmann & S. Lee & C. Hamel, 2001. "Participation decisions, angler welfare, and the regional economic impact of sportfishing," Working Papers 2001-13, Utah State University, Department of Economics.
  • Handle: RePEc:usu:wpaper:2001-13
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    File URL: https://repec.bus.usu.edu/RePEc/usu/pdf/ERI2001-13.pdf
    File Function: First version, 2001
    Download Restriction: no
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    Citations

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    Cited by:

    1. Daniel K. Lew & Chang K. Seung, 2014. "On the Statistical Significance of Regional Economic Impacts from Recreational Fishing Harvest Limits in Southern Alaska," Marine Resource Economics, University of Chicago Press, vol. 29(3), pages 241-257.
    2. Deisentroth, Daniel B. & Loomis, John B. & Bond, Craig A., 2013. "Using Revealed Preference Behavioral Models to Correctly Account for Substitution Effects in Economic Impact Analysis," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 43(2).
    3. Abbott, Joshua K. & Wilen, James E., 2008. "Rent Dissipation in Chartered Recreational Fishing: Inside the Black Box," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6521, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Devkota, Nirmala & Fannin, James Matthew & Paudel, Krishna P., 2006. "Economic Impact Estimation Using Bootstrap Samples Obtained From Internet And Intercept Survey Data," 2006 Annual meeting, July 23-26, Long Beach, CA 21150, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Daniel K. Lew & Douglas M. Larson, 2011. "A Repeated Mixed Logit Approach to Valuing a Local Sport Fishery: The Case of Southeast Alaska Salmon," Land Economics, University of Wisconsin Press, vol. 87(4), pages 712-729.

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