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Increasing Returns and Cycles in Fishing

Author

Listed:
  • Liski, M.
  • Kort, P.M.

    (Tilburg University, School of Economics and Management)

  • Novak, A.J.

Abstract

We consider optimal fishery management under the assumption of increasing returns that is supported by previous empirical evidence. We improve the tractability and realism of the previous approaches by introducing flow adjustment costs on changes in harvest rate. Our framework is the first to provide a link between stable limit cycle policies and increasing returns in harvesting. The type of the harvest policy depends on flow adjustment costs: for relatively costly adjustments the usual steady state harvest policy is conceivable, whereas for relatively cheap adjustments the harvest policy is cyclical. We also show a connection between chattering control policies and limit cycles, which helps us to develop a clear economic meaning for cyclical harvesting.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Liski, M. & Kort, P.M. & Novak, A.J., 2000. "Increasing Returns and Cycles in Fishing," Other publications TiSEM 5123ff94-84a5-429b-970a-7, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:5123ff94-84a5-429b-970a-72a4452bed72
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    1. Tracy R. Lewis & Richard Schmalensee, 1979. "Non-convexity and Optimal Harvesting Strategies for Renewable Resources," Canadian Journal of Economics, Canadian Economics Association, vol. 12(4), pages 677-691, November.
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    4. Dawid, Herbert & Kopel, Michael, 1997. "On the Economically Optimal Exploitation of a Renewable Resource: The Case of a Convex Environment and a Convex Return Function," Journal of Economic Theory, Elsevier, vol. 76(2), pages 272-297, October.
    5. Jørgensen, S. & Kort, P.M., 1990. "Optimal dynamic investment policies under concave-convex adjustment costs," Other publications TiSEM 97b16405-bdf6-4185-8f54-f, Tilburg University, School of Economics and Management.
    6. Jorgensen, Steffen & Kort, Peter M., 1993. "Optimal dynamic investment policies under concave-convex adjustment costs," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 153-180.
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    9. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
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    Cited by:

    1. Katrin Erdlenbruch & Alain Jean-Marie & Michel Moreaux & Mabel Tidball, 2013. "Optimality of impulse harvesting policies," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 52(2), pages 429-459, March.
    2. Moberg, Emily A. & Pinsky, Malin L. & Fenichel, Eli P., 2019. "Capital Investment for Optimal Exploitation of Renewable Resource Stocks in the Age of Global Change," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    3. Alain Jean-Marie & Mabel Tidball & Michel Moreaux & Katrin Erdlenbruch, 2009. "The Renewable Resource Management Nexus: Impulse versus Continuous Harvesting Policies," Working Papers 09-03, LAMETA, Universtiy of Montpellier, revised Mar 2009.
    4. Fenichel, Eli P. & Horan, Richard D. & Bence, James R., 2010. "Indirect management of invasive species through bio-controls: A bioeconomic model of salmon and alewife in Lake Michigan," Resource and Energy Economics, Elsevier, vol. 32(4), pages 500-518, November.
    5. Mette Termansen, 2007. "Economies of scale and the optimality of rotational dynamics in forestry," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 37(4), pages 643-659, August.
    6. Behringer, Stefan & Upmann, Thorsten, 2017. "Harvesting a Remote Renewable Resource," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168250, Verein für Socialpolitik / German Economic Association.
    7. Melstrom, Richard T., 2014. "Optimal Management of a Fishery with Bycatch," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 168316, Agricultural and Applied Economics Association.
    8. Melstrom, Richard T. & Horan, Richard D., 2012. "Managing Excessive Predation in a Predator-Prey Setting: The Case of Piping Plovers," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123350, Agricultural and Applied Economics Association.
    9. José-María Da-Rocha & Linda Nøstbakken & Marcos Pérez, 2014. "Pulse Fishing and Stock Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(2), pages 257-274, October.
    10. Naevdal, Eric & Olaussen, Jon Olaf & Skonhoft, Anders, 2012. "A bioeconomic model of trophy hunting," Ecological Economics, Elsevier, vol. 73(C), pages 194-205.
    11. Ralph Winkler, 2008. "Optimal compliance with emission constraints: dynamic characteristics and the choice of technique," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 39(4), pages 411-432, April.
    12. Melstrom, Richard T., 2015. "Cyclical harvesting in fisheries with bycatch," Resource and Energy Economics, Elsevier, vol. 42(C), pages 1-15.
    13. George Halkos & George Papageorgiou, 2013. "Dynamic modeling of pulse fishing: A game theoretic approach," DEOS Working Papers 1324, Athens University of Economics and Business.
    14. Heinzel, Christoph & Winkler, Ralph, 2006. "Gradual versus structural technological change in the transition to a low-emission energy industry: How time-to-build and differing social and individual discount rates influence environmental and tec," Dresden Discussion Paper Series in Economics 09/06, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    15. Sarkar, Sudipto, 2009. "Optimal fishery harvesting rules under uncertainty," Resource and Energy Economics, Elsevier, vol. 31(4), pages 272-286, November.

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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium

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