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Information Sharing and Cooperative Search in Fisheries

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Listed:
  • Evans, Keith S.
  • Weninger, Quinn

Abstract

We present a dynamic game of search and learning about the productivity of com-peting fishing locations. Perfect Bayesian Nash equilibrium search patterns for non-cooperating fishermen and members of an information sharing cooperative are com-pared with first-best outcomes. Independent fishermen do not internalize the full valueof information, and do not replicate first-best search. A fishing cooperative faces afree-riding problem, as each coop member prefers that other members undertake costlysearch for information. Pooling contracts among coop members may mitigate, butare not likely to eliminate free riding. Our results explain the paucity of informationsharing in fisheries and suggest regulators use caution in advocating cooperatives as asolution to common pool inefficiencies in fisheries.

Suggested Citation

  • Evans, Keith S. & Weninger, Quinn, 2010. "Information Sharing and Cooperative Search in Fisheries," Staff General Research Papers Archive 31606, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genres:31606
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    References listed on IDEAS

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    Cited by:

    1. Ronald G. Felthoven & Jean Lee & Kurt E. Schnier, 2014. "Cooperative Formation and Peer Effects in Fisheries," Marine Resource Economics, University of Chicago Press, vol. 29(2), pages 133-156.
    2. Jihad C. Elnaboulsi & Wassim Daher & Yiğit Sağlam, 2023. "Environmental taxation, information precision, and information sharing," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 25(2), pages 301-341, April.
    3. Matthieu Barbier & James R Watson, 2016. "The Spatial Dynamics of Predators and the Benefits and Costs of Sharing Information," PLOS Computational Biology, Public Library of Science, vol. 12(10), pages 1-22, October.
    4. Barnes, Michele L. & Arita, Shawn & Kalberg, Kolter & Leung, PingSun, 2017. "When does it pay to cooperate? Strategic information exchange in the harvest of common-pool fishery resources," Ecological Economics, Elsevier, vol. 131(C), pages 1-11.
    5. 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.
    6. Burgess, Matthew G. & Carrella, Ernesto & Drexler, Michael & Axtell, Robert L. & Bailey, Richard M. & Watson, James R. & Cabral, Reniel B. & Clemence, Michaela & Costello, Christopher & Dorsett, Chris, 2018. "Opportunities for agent-based modeling in human dimensions of fisheries," SocArXiv gzhm5, Center for Open Science.
    7. Dépalle, Maxime & Sanchirico, James N. & Thébaud, Olivier & O’Farrell, Shay & Haynie, Alan C. & Perruso, Larry, 2021. "Scale-dependency in discrete choice models: A fishery application," Journal of Environmental Economics and Management, Elsevier, vol. 105(C).
    8. Nicolas Sanz & Bassirou Diop, 2015. "A search-matching model of fisheries," Working Papers hal-01228851, HAL.

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    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation

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