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Renewable resource management with stochastic recharge and environmental threats

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  • Leizarowitz, Arie
  • Tsur, Yacov

Abstract

Exploitation diminishes the capacity of renewable resources to withstand environmental stress, increasing their vulnerability to extreme conditions that may trigger abrupt changes. The onset of such events depends on the coincidence of extreme environmental conditions and on the resource state (determining its resilience). When the former is uncertain and the latter evolves stochastically, the uncertainty regarding the event occurrence is the result of the combined effect of these two uncertain components. We study optimal management in this setting. The environmental threat renders the single-period discount factor policy-dependent and, as a result, the compound discount factor becomes history-dependent. Existence of an optimal Markovian–deterministic stationary policy is established and the optimal state process is shown to converge to a steady state distribution.

Suggested Citation

  • Leizarowitz, Arie & Tsur, Yacov, 2012. "Renewable resource management with stochastic recharge and environmental threats," Journal of Economic Dynamics and Control, Elsevier, vol. 36(5), pages 736-753.
  • Handle: RePEc:eee:dyncon:v:36:y:2012:i:5:p:736-753
    DOI: 10.1016/j.jedc.2011.06.013
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    Cited by:

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    2. Roseta-Palma, Catarina & Saglam, Yigit, 2019. "Downside risk in reservoir management," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), April.
    3. Julia de Frutos & Katrin Erdlenbruch & Mabel Tidball, 2012. "Optimal adaptation strategies to shocks on groundwater resources," Working Papers hal-02804709, HAL.
    4. Fishman, Ram & B Krishnamurthy, Chandra Kiran, 2021. "An ecological golden rule," Resource and Energy Economics, Elsevier, vol. 64(C).
    5. López, Ramón E. & Yoon, Sang W., 2014. "Environmental Sustainability with a Pollution Tax," Working Papers 166244, University of Maryland, Department of Agricultural and Resource Economics.
    6. Yacov Tsur & Amos Zemel, 2017. "Water policy guidelines: A comprehensive approach," Discussion Papers 264871, Hebrew University of Jerusalem, Department of Agricultural Economics and Management.
    7. Tsur, Yacov & Zemel, Amos, 2012. "Dynamic and stochastic analysis of environmental and natural resources," Discussion Papers 120017, Hebrew University of Jerusalem, Department of Agricultural Economics and Management.
    8. Yiğit Sağlam, 2019. "Welfare Implications of Water Scarcity: Higher Prices of Desalination," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 995-1022, August.
    9. Nkuiya, Bruno & Diekert, Florian, 2023. "Stochastic growth and regime shift risk in renewable resource management," Ecological Economics, Elsevier, vol. 208(C).
    10. Arvaniti, Maria & Krishnamurthy, Chandra Kiran B. & Crépin, Anne-Sophie, 2023. "Time-consistent renewable resource management with present bias and regime shifts," Journal of Economic Behavior & Organization, Elsevier, vol. 207(C), pages 479-495.
    11. Rolf Groeneveld & Michael Springborn & Christopher Costello, 2014. "Repeated Experimentation to Learn About a Flow-Pollutant Threshold," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(4), pages 627-647, August.

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    More about this item

    Keywords

    Stochastic stock dynamics; Catastrophic event; Endogenous discounting; Markov decision process; Optimal stationary policy;
    All these keywords.

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General

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