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Linking sportfishing trip attributes, participation decisions, and regional economic impacts in Lower and Central Cook Inlet, Alaska

Author

Listed:
  • Charles Hamel

    (Department of Economics, University of Alaska Fairbanks, Fairbanks, AK 99775-6080, USA)

  • Hans T. Geier

    (Department of Natural Resource Management, University of Alaska Fairbanks, Fairbanks, AK 99775-7580)

  • Mark Herrmann

    (Department of Economics, University of Alaska Fairbanks, Fairbanks, AK 99775-6080, USA)

  • Keith R. Criddle

    (Department of Economics, Utah State University, Logan, UT 84322-3530, USA)

  • S. Todd Lee

    (National Marine Fisheries Service, Alaska Fishery Science Center, 7600 Sand Point Way NE, Bldg 4, Seattle, WA 98115, USA)

Abstract

Forecasts of the regional economic impacts of changes in the demand for recreation occasioned by regulatory changes, changes in the quality of the recreation experience, or changes in average trip costs require a model that links changes in these trip attributes to individual participation decisions and population participation rates. The probability that an individual will take a particular recreational trip is described using a nonlinear random effects probit model based on variable trip attributes and individual economic and demographic characteristics. These conditional individual probabilities are transformed into predictions of changes in total recreation demand using a simulation-based sample enumeration method. The regional impacts associated with ensuing changes in primary and secondary expenditure patterns are elucidated with a stand-alone recreation-sector module linked to a regionally adjusted zip code-level input-output model. Because the participation model allows for non-constant marginal utility, primary and secondary impacts exhibit nonlinear responses to variations in trip attributes. The modeling approach is demonstrated in an application to the saltwater sport fisheries for Pacific halibut and salmon in Lower and Central Cook Inlet, Alaska.

Suggested Citation

  • Charles Hamel & Hans T. Geier & Mark Herrmann & Keith R. Criddle & S. Todd Lee, 2002. "Linking sportfishing trip attributes, participation decisions, and regional economic impacts in Lower and Central Cook Inlet, Alaska," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 36(2), pages 247-264.
    • Handle: RePEc:spr:anresc:v:36:y:2002:i:2:p:247-264
    Note: Received: February 2001/Accepted: December 2001
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    Citations

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    Cited by:

    1. Chang Seung & Daniel Lew, 2013. "Accounting for variation in exogenous shocks in economic impact modeling," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 51(3), pages 711-730, December.
    2. Richard T. Melstrom, 2017. "Estimating a model of sportfishing trip expenditures using a quasi-maximum likelihood approach," Tourism Economics, , vol. 23(2), pages 448-459, March.
    3. 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).
    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. Starbuck, C. Meghan & Berrens, Robert P. & McKee, Michael, 2006. "Simulating changes in forest recreation demand and associated economic impacts due to fire and fuels management activities," Forest Policy and Economics, Elsevier, vol. 8(1), pages 52-66, January.
    6. Adam Orens & Andrew Seidl, 2009. "Working Lands and Winter Tourists in the Rocky Mountain West: A Travel Cost, Contingent Behaviour and Input–Output Analysis," Tourism Economics, , vol. 15(1), pages 215-242, March.

    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • Q22 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Fishery
    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources

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