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Optimal Harvesting of a Spatial Renewable Resource

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  • Stefan Behringer
  • Thorsten Upmann

Abstract

In this paper we investigate optimal harvesting of a renewable natural resource. While in the standard approach the resource is located at a single point in space we allow for the resource to be distributed over the plane. Consequently, an agent who exploits the resource has to travel from one location to another. For a fixed planning horizon we investigate the speed and the time path of harvesting chosen by the agent. We show that the agent adjusts the speed of movement so that he accomplishes to visit each location only once, even in the absence of travelling cost. Since he does not come back to any location for a second harvest, it is optimal for him to fully deplete the resource upon arrival. A society interested in conserving some of the resource thus has to take measures suitable to limit the exploitative behaviour of the agent.

Suggested Citation

  • Stefan Behringer & Thorsten Upmann, 2012. "Optimal Harvesting of a Spatial Renewable Resource," CESifo Working Paper Series 4019, CESifo.
    • Handle: RePEc:ces:ceswps:_4019
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Anastasios Xepapadeas & Athanasios Yannacopoulos, 2015. "Spatial Resource Management under Pollution Externalities," CEEES Paper Series CE3S-05/15, European University at St. Petersburg, Department of Economics.
    2. Yoshioka, Hidekazu & Yaegashi, Yuta, 2019. "A finite difference scheme for variational inequalities arising in stochastic control problems with several singular control variables," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 40-66.
    3. Emmanuelle Augeraud-Véron & Raouf Boucekkine & Vladimir Veliov, 2019. "Distributed Optimal Control Models in Environmental Economics: A Review," AMSE Working Papers 1902, Aix-Marseille School of Economics, France.
    4. Erik O. Sterner & Elizabeth J. Z. Robinson & H. J. Albers, 2018. "Location choice for renewable resource extraction with multiple non-cooperative extractors: a spatial Nash equilibrium model and numerical implementation," Letters in Spatial and Resource Sciences, Springer, vol. 11(3), pages 315-331, October.
    5. Fabbri, Giorgio & Faggian, Silvia & Freni, Giuseppe, 2020. "Policy effectiveness in spatial resource wars: A two-region model," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    6. William Brock & Anastasios Xepapadeas, 2020. "Spatial Environmental and Resource Economics," DEOS Working Papers 2002, Athens University of Economics and Business.
    7. Khan, M. Ali, 2016. "On a forest as a commodity and on commodification in the discipline of forestry," Forest Policy and Economics, Elsevier, vol. 72(C), pages 7-17.
    8. 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.
    9. Upmann, Thorsten & Uecker, Hannes & Hammann, Liv & Blasius, Bernd, 2021. "Optimal stock–enhancement of a spatially distributed renewable resource," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    10. Arabatzis, Garyfallos & Kyriakopoulos, Grigorios & Tsialis, Panagiotis, 2017. "Typology of regional units based on RES plants: The case of Greece," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1424-1434.

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    More about this item

    Keywords

    optimal harvesting; spatial renewable resource; continuous time; market failure;
    All these keywords.

    JEL classification:

    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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