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Weather Effects on the Demand for Coastal Recreational Fishing: Implications for a Changing Climate

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  • Dundas, Steven J.
  • von Haefen, Roger H.

Abstract

PLEASE SEE UPDATED VERSION, CEnREP Working Paper No. 19-016, at https://ageconsearch.umn.edu/record/283949... This paper estimates the demand for coastal recreational fishing in the Atlantic and Gulf Coast regions of the United States and evaluates the potential welfare implications resulting from climate change. Specifically, we use short-run variability in temperature and precipitation to estimate the effect of weather on participation in shoreline fishing in coastal waters. We then simulate how climate change may impact those choices over time. Parameter estimates are combined with predictions from five global climate models under three emissions scenarios to estimate welfare changes associated with climate change over multiple time horizons. Overall, our results suggest the effects of climate change on shoreline recreational fishing are positive and significant in the long run (2080-2099) with simulation results predicting annual gains of up to $6.83 per trip, or $304 million in the aggregate. The results are decomposed seasonally and regionally to reveal substantial heterogeneity. Welfare gains associated with increasing temperatures in the non-summer months outweigh modest losses in the summer months. The Gulf Coast region has the potential to realize welfare losses, while the Mid-Atlantic and New England are likely to experience welfare gains in all seasons. Of the nearly 45 million annual trips predicted by the model, climate change may increase participation by 0.2 to 2.2 percent in the aggregate. Given the modest negative demand responses in the Gulf and Southeast regions, evidence of adaptation is identified from a model of night fishing. Results suggest that recreational anglers may shift their activities to night as daily high temperatures increase rather than change their participation decision.

Suggested Citation

  • Dundas, Steven J. & von Haefen, Roger H., 2015. "Weather Effects on the Demand for Coastal Recreational Fishing: Implications for a Changing Climate," CEnREP Working Papers 264980, North Carolina State University, Department of Agricultural and Resource Economics.
  • Handle: RePEc:ags:nccewp:264980
    DOI: 10.22004/ag.econ.264980
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    1. Joseph A. Herriges & Catherine L. Kling, 1997. "The Performance of Nested Logit Models When Welfare Estimation Is the Goal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 792-802.
    2. George R. Parsons & GAndrew J. Plantinga & GKevin J. Boyle, 2000. "Narrow Choice Sets in a Random Utility Model of Recreation Demand," Land Economics, University of Wisconsin Press, vol. 76(1), pages 86-99.
    3. A. Brett Hauber & George R. Parsons, 2000. "The Effect of Nesting Structure Specification on Welfare Estimation in a Random Utility Model of Recreation Demand: An Application to the Demand for Recreational Fishing," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(3), pages 501-514.
    4. Hausman, Jerry A. & Leonard, Gregory K. & McFadden, Daniel, 1995. "A utility-consistent, combined discrete choice and count data model Assessing recreational use losses due to natural resource damage," Journal of Public Economics, Elsevier, vol. 56(1), pages 1-30, January.
    5. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    6. Hindsley, Paul & Landry, Craig E. & Gentner, Brad, 2011. "Addressing onsite sampling in recreation site choice models," Journal of Environmental Economics and Management, Elsevier, vol. 62(1), pages 95-110, July.
    7. Maximilian Auffhammer & Anin Aroonruengsawat, 2011. "Simulating the impacts of climate change, prices and population on California’s residential electricity consumption," Climatic Change, Springer, vol. 109(1), pages 191-210, December.
    8. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
    9. Smith, Martin D., 2005. "State dependence and heterogeneity in fishing location choice," Journal of Environmental Economics and Management, Elsevier, vol. 50(2), pages 319-340, September.
    10. Kling, Catherine L. & Herriges, Joseph A., 1997. "Model Performance of Nested Logit Models when Welfare Estimation is the Goal, The," Staff General Research Papers Archive 12331, Iowa State University, Department of Economics.
    11. Klaus Moeltner & Randall S. Rosenberger, 2014. "Cross-Context Benefit Transfer: A Bayesian Search for Information Pools," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(2), pages 469-488.
    12. Edward R. Morey & Robert D. Rowe & Michael Watson, 1993. "A Repeated Nested-Logit Model of Atlantic Salmon Fishing," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(3), pages 578-592.
    13. Linwood H. Pendleton & Robert Mendelsohn, 1998. "Estimating the Economic Impact of Climate Change on the Freshwater Sportsfisheries of the Northeastern U.S," Land Economics, University of Wisconsin Press, vol. 74(4), pages 483-496.
    14. Marshall Burke & John Dykema & David B. Lobell & Edward Miguel & Shanker Satyanath, 2015. "Incorporating Climate Uncertainty into Estimates of Climate Change Impacts," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 461-471, May.
    15. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    16. Robert Johnston & Klaus Moeltner, 2014. "Meta-Modeling and Benefit Transfer: The Empirical Relevance of Source-Consistency in Welfare Measures," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(3), pages 337-361, November.
    17. Frank J. Cesario, 1976. "Value of Time in Recreation Benefit Studies," Land Economics, University of Wisconsin Press, vol. 52(1), pages 32-41.
    18. George R. Parsons & Michael S. Needelman, 1992. "Site Aggregation in a Random Utility Model of Recreation," Land Economics, University of Wisconsin Press, vol. 68(4), pages 418-433.
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