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Optimal Management Under Institutional Constraints: Determining a Total Allowable Catch for Different Fleet Segments in the Northeast Arctic Cod Fishery

Author

Listed:
  • Andries Richter

    (University of Oslo
    Wageningen University)

  • Anne Maria Eikeset

    (University of Oslo)

  • Daan Soest

    (Tilburg University)

  • Florian Klaus Diekert

    (University of Oslo
    University of Heidelberg)

  • Nils Chr. Stenseth

    (University of Oslo)

Abstract

Many real world fisheries have an individual vessel quota system with restrictions on transferability of quota or entrance of new vessels into the fishery. While the standard economic reasoning is that these institutional constraints lead to welfare losses, the size of those losses and optimal second-best policies are usually unknown. We develop a dynamic bioeconomic model, in which a scientific body provides an optimal TAC given restrictions on (i) transferability between vessel segments and (ii) entrance of new vessels. Further, we also quantify welfare losses arising from not maximizing economic welfare, but physical yield—which is actually the case in many fisheries. We apply the model to the Northeast Arctic cod fishery, and estimate not only the cost and harvesting functions of the various vessel types, but also the parameters of the biological model as well as those of the demand function. This allows us to determine optimal second-best policies and quantify corresponding welfare effects for our case study fishery.

Suggested Citation

  • Andries Richter & Anne Maria Eikeset & Daan Soest & Florian Klaus Diekert & Nils Chr. Stenseth, 2018. "Optimal Management Under Institutional Constraints: Determining a Total Allowable Catch for Different Fleet Segments in the Northeast Arctic Cod Fishery," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(4), pages 811-835, April.
    • Handle: RePEc:kap:enreec:v:69:y:2018:i:4:d:10.1007_s10640-016-0106-3
    DOI: 10.1007/s10640-016-0106-3
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