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Eco-labeling and dolphin avoidance: A dynamic model of tuna fishing in the Eastern Tropical Pacific

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  • Hicks, Robert L.
  • Schnier, Kurt E.

Abstract

This paper examines the impact of dolphin-safe eco-labeling on the spatial distribution of fishing effort and fishermen's willingness to pay to avoid dolphins using a dynamic discrete choice model applied to the Eastern Tropical Pacific tuna fishery. This estimator couples the contemporaneous expected utility associated with fishing a specific site with the expected value of future optimal behavior for all future location choices on the cruise. We show that producers attempting to avoid dolphins faced a smaller set of viable sites as compared to producers actively targeting dolphins. Thus, the spatial distribution of effort within the fishery was significantly altered following the implementation of "dolphin-safe" tuna labeling in the early 1990s. We also show that vessels attempting to meet the label criteria were willing to pay substantial amounts to increase the spatial distribution of fishing grounds amenable to dolphin avoidance, but a mandatory eco-label would have been quite costly to all fishermen in the Eastern Tropical Pacific Ocean (ETP) compared to the voluntary label implemented in 1990.

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  • Hicks, Robert L. & Schnier, Kurt E., 2008. "Eco-labeling and dolphin avoidance: A dynamic model of tuna fishing in the Eastern Tropical Pacific," Journal of Environmental Economics and Management, Elsevier, vol. 56(2), pages 103-116, September.
  • Handle: RePEc:eee:jeeman:v:56:y:2008:i:2:p:103-116
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    Cited by:

    1. Stafford, Tess M., 2018. "Accounting for outside options in discrete choice models: An application to commercial fishing effort," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 159-179.
    2. Goytom Abraha Kahsay & Laura Mørch Andersen & Lars Gårn Hansen, 2014. "Price reactions when consumers are concerned about pro-social reputation," IFRO Working Paper 2014/09, University of Copenhagen, Department of Food and Resource Economics.
    3. C. Haynie, Alan & F. Layton, David, 2010. "An expected profit model for monetizing fishing location choices," Journal of Environmental Economics and Management, Elsevier, vol. 59(2), pages 165-176, March.
    4. Abbott, Joshua K. & Wilen, James E., 2011. "Dissecting the tragedy: A spatial model of behavior in the commons," Journal of Environmental Economics and Management, Elsevier, vol. 62(3), pages 386-401.
    5. Blackman, Allen & Rivera, Jorge, 2010. "The Evidence Base for Environmental and Socioeconomic Impacts of “Sustainable” Certification," RFF Working Paper Series dp-10-17, Resources for the Future.
    6. Hicks, Robert L. & Schnier, Kurt E., 2010. "Spatial regulations and endogenous consideration sets in fisheries," Resource and Energy Economics, Elsevier, vol. 32(2), pages 117-134, April.
    7. Anna M. Birkenbach & Andreea L. Cojocaru & Frank Asche & Atle G. Guttormsen & Martin D. Smith, 2020. "Seasonal Harvest Patterns in Multispecies Fisheries," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(3), pages 631-655, March.
    8. Kathleen Segerson, 2013. "Voluntary Approaches to Environmental Protection and Resource Management," Annual Review of Resource Economics, Annual Reviews, vol. 5(1), pages 161-180, June.
    9. Joshua K. Abbott & James E. Wilen, 2010. "Voluntary Cooperation in the Commons? Evaluating the Sea State Program with Reduced Form and Structural Models," Land Economics, University of Wisconsin Press, vol. 86(1), pages 131-154.
    10. Zinnia Mukherjee, 2016. "Controlling stochastic externalities with penalty threats: the case of bycatch," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 18(1), pages 93-113, January.
    11. Lamantia, F. & Radi, D., 2015. "Exploitation of renewable resources with differentiated technologies: An evolutionary analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 155-174.
    12. Sun, Junxiu & Yin, Haitao & Wang, Feng, 2014. "Net private benefits of purchasing eco-labeled air conditioners and subsidization policies in China," Energy Policy, Elsevier, vol. 73(C), pages 186-195.
    13. Hicks, Robert L. & Holland, Daniel S. & Kuriyama, Peter T. & Schnier, Kurt E., 2020. "Choice sets for spatial discrete choice models in data rich environments," Resource and Energy Economics, Elsevier, vol. 60(C).
    14. Dayna Simpson & Damien Power & Robert Klassen, 2012. "When One Size Does Not Fit All: A Problem of Fit Rather than Failure for Voluntary Management Standards," Journal of Business Ethics, Springer, vol. 110(1), pages 85-95, September.
    15. Hutniczak, Barbara & Münch, Angela, 2018. "Fishermen's location choice under spatio-temporal update of expectations," Journal of choice modelling, Elsevier, vol. 28(C), pages 124-136.
    16. Blackman, Allen & Rivera, Jorge, 2010. "The Evidence Base for Environmental and Socioeconomic Impacts of “Sustainable†Certification," RFF Working Paper Series dp-10-10-efd, Resources for the Future.
    17. Keita Abe & Christopher M. Anderson & Matthew N. Reimer, 2022. "Catch More to Catch Less: Estimating Timing Choice as Dynamic Bycatch Avoidance Behavior," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(4), pages 953-984, August.
    18. Reimer, Matthew N. & Abbott, Joshua K. & Haynie, Alan C., 2022. "Structural behavioral models for rights-based fisheries," Resource and Energy Economics, Elsevier, vol. 68(C).

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