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The optimal control of emissions and renewable resource harvesting under uncertainty

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  • J. Olsen
  • James Shortle

Abstract

A model of a renewable resource is developed where the growth and quality of the resource are reduced by pollution. Ambient pollution concentrations and the renewable resource stock are modeled as stochastic processes. Conditions for the optimal harvest plan and the optimal emissions rate are derived. The effect of stochastic variations on the optimal management of the resource is analyzed. The steady-state joint probability distribution of the resource and pollution stocks is shown to exist under certain conditions. Copyright Kluwer Academic Publishers 1996

Suggested Citation

  • J. Olsen & James Shortle, 1996. "The optimal control of emissions and renewable resource harvesting under uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 7(2), pages 97-115, March.
    • Handle: RePEc:kap:enreec:v:7:y:1996:i:2:p:97-115
    DOI: 10.1007/BF00699286
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    References listed on IDEAS

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    1. Olli Tahvonen, 1991. "On the dynamics of renewable resource harvesting and pollution control," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 1(1), pages 97-117, March.
    2. Kahn, James R. & Kemp, W. Michael, 1985. "Economic losses associated with the degradation of an ecosystem: The case of submerged aquatic vegetation in Chesapeake Bay," Journal of Environmental Economics and Management, Elsevier, vol. 12(3), pages 246-263, September.
    3. Plourde, Charles & Yeung, David, 1989. "A model of industrial pollution in a stochastic environment," Journal of Environmental Economics and Management, Elsevier, vol. 16(2), pages 97-105, March.
    4. Munro, Gordon R. & Scott, Anthony D., 1985. "The economics of fisheries management," Handbook of Natural Resource and Energy Economics, in: A. V. Kneese† & J. L. Sweeney (ed.), Handbook of Natural Resource and Energy Economics, edition 1, volume 2, chapter 14, pages 623-676, Elsevier.
    5. Robert S. Pindyck, 1984. "Uncertainty in the Theory of Renewable Resource Markets," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(2), pages 289-303.
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    2. Castellano, Rosella & Cerqueti, Roy & Spinesi, Luca, 2016. "Sustainable management of fossil fuels: A dynamic stochastic optimization approach with jump-diffusion," European Journal of Operational Research, Elsevier, vol. 255(1), pages 288-297.
    3. Motoh, Tsujimura, 2004. "Optimal natural resources management under uncertainty with catastrophic risk," Energy Economics, Elsevier, vol. 26(3), pages 487-499, May.
    4. Charles Sims & David Finnoff & Alan Hastings & Jacob Hochard, 2017. "Listing and Delisting Thresholds under the Endangered Species Act," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 549-570.
    5. Robert Deacon & Charles Kolstad & Allen Kneese & David Brookshire & David Scrogin & Anthony Fisher & Michael Ward & Kerry Smith & James Wilen, 1998. "Research Trends and Opportunities in Environmental and Natural Resource Economics," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 11(3), pages 383-397, April.
    6. Bulte, Erwin H. & van Kooten, G. Cornelis, 2001. "Harvesting and conserving a species when numbers are low: population viability and gambler's ruin in bioeconomic models," Ecological Economics, Elsevier, vol. 37(1), pages 87-100, April.
    7. repec:ehu:biltok:5844 is not listed on IDEAS

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