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The Effects of Random and Seasonal Environmental Fluctuations on Optimal Harvesting and Stocking

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Listed:
  • Hening, A.
  • Tran, K. Q.
  • Ungureanu, S.

Abstract

. We analyze the harvesting and stocking of a population that is affected by random and seasonal environmental fluctuations. The main novlty comes from having three layers of environmental fluctuations. The first layer is due to the environment switching at random times between different environmental states. This is similar to having sudden environmental changes or catastrophes. The second layer is due to seasonal variation, where there is a significant change in the dynamics between seasons. Finally, the third layer is due to the constant presence of environmental stochasticity|between the seasonal or random regime switches, the species is affected by fluctuations which can be modelled by white noise. This framework is more realistic because it can capture both significant random and deterministic environmental shifts as well as small and frequent uctuations in abiotic factors. Our framework also allows for the price or cost of harvesting to change deterministically and stochastically, something that is more realistic from an economic point of view. The combined effects of seasonal and random fluctuations make it impossible to find the optimal harvesting-stocking strategy analytically. We get around this roadblock by developing rigorous numerical approximations and proving that they converge to the optimal harvesting-stocking strategy. We apply our methods to multiple population models and explore how prices, or costs, and environmental fluctuations in uence the optimal harvesting-stocking strategy. We show that in many situations the optimal way of harvesting and stocking is not of threshold type.

Suggested Citation

  • Hening, A. & Tran, K. Q. & Ungureanu, S., 2021. "The Effects of Random and Seasonal Environmental Fluctuations on Optimal Harvesting and Stocking," Working Papers 21/05, Department of Economics, City University London.
  • Handle: RePEc:cty:dpaper:21/05
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    File URL: https://openaccess.city.ac.uk/id/eprint/26919/1/WP2105.pdf
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    References listed on IDEAS

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    1. K. R. Miltersen, 2003. "Commodity price modelling that matches current observables: a new approach," Quantitative Finance, Taylor & Francis Journals, vol. 3(1), pages 51-58.
    2. Nguyen, Dang Hai & Yin, George & Zhu, Chao, 2017. "Certain properties related to well posedness of switching diffusions," Stochastic Processes and their Applications, Elsevier, vol. 127(10), pages 3135-3158.
    3. Alvarez, Luis H.R. & Koskela, Erkki, 2007. "Optimal harvesting under resource stock and price uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2461-2485, July.
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