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Increasing returns and cycles in fishing

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  • M. Liski, P.M. Kort, A.J. Novak

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.

Suggested Citation

  • M. Liski, P.M. Kort, A.J. Novak, 2001. "Increasing returns and cycles in fishing," Computing in Economics and Finance 2001 126, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:126
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    References listed on IDEAS

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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.
    2. Rognvaldur Hannesson, 1975. "Fishery Dynamics: A North Atlantic Cod Fishery," Canadian Journal of Economics, Canadian Economics Association, vol. 8(2), pages 151-173, May.
    3. Jorgensen, Steffen & Kort, Peter M., 1997. "Optimal investment and finance in renewable resource harvesting," Journal of Economic Dynamics and Control, Elsevier, vol. 21(2-3), pages 603-630.
    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. 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.
    6. Russell Davidson & Richard Harris, 1981. "Non-Convexities in Continuous Time Investment Theory," Review of Economic Studies, Oxford University Press, vol. 48(2), pages 235-253.
    7. Wirl Franz, 1995. "The Cyclical Exploitation of Renewable Resource Stocks May Be Optimal," Journal of Environmental Economics and Management, Elsevier, vol. 29(2), pages 252-261, September.
    8. Feichtinger, Gustav & Novak, Andreas & Wirl, Franz, 1994. "Limit cycles in intertemporal adjustment models : Theory and applications," Journal of Economic Dynamics and Control, Elsevier, vol. 18(2), pages 353-380, March.
    9. Liski, Matti, 2002. "Taxing average emissions to overcome the shutdown problem," Journal of Public Economics, Elsevier, vol. 85(3), pages 363-384, September.
    10. Clark, Colin W & Clarke, Frank H & Munro, Gordon R, 1979. "The Optimal Exploitation of Renewable Resource Stocks: Problems of Irreversible Investment," Econometrica, Econometric Society, vol. 47(1), pages 25-47, January.
    11. Trond Bjørndal & Jon M. Conrad & Kjell G. Salvanes, 1993. "Stock Size, Harvesting Costs, and the Potential for Extinction: The Case of Sealing," Land Economics, University of Wisconsin Press, vol. 69(2), pages 156-167.
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    Citations

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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. 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.
    3. Thorsten Upmann & Stefan Behringer, 2017. "Harvesting a Remote Renewable Resource," CESifo Working Paper Series 6724, CESifo Group Munich.
    4. 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.
    5. Naevdal, Eric & Olaussen, Jon Olaf & Skonhoft, Anders, 2012. "A bioeconomic model of trophy hunting," Ecological Economics, Elsevier, vol. 73(C), pages 194-205.
    6. 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.
    7. 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, Universitiy of Montpellier, revised Mar 2009.
    8. 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.
    9. Melstrom, Richard T., 2015. "Cyclical harvesting in fisheries with bycatch," Resource and Energy Economics, Elsevier, vol. 42(C), pages 1-15.
    10. George Halkos & George Papageorgiou, 2013. "Dynamic modeling of pulse fishing: A game theoretic approach," DEOS Working Papers 1324, Athens University of Economics and Business.
    11. Sarkar, Sudipto, 2009. "Optimal fishery harvesting rules under uncertainty," Resource and Energy Economics, Elsevier, vol. 31(4), pages 272-286, November.

    More about this item

    Keywords

    non-convexities; adjustment costs; Hopf bifurcation; Renewable resources;

    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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