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Exploitation of renewable resources with differentiated technologies: An evolutionary analysis

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  • Lamantia, F.
  • Radi, D.

Abstract

In this paper, we propose a dynamical model of technology adoption for the exploitation of a renewable natural resource. Each technology has a different efficiency and environmental impact. The process of technology adoption over time is modeled through an evolutionary game employed by profit maximizing exploiters. The loss in profits due to lower efficiency levels of environmentally-friendly technologies can be counterbalanced by the higher consumers’ propensity to pay for greener goods. The dynamics of the resource take place in continuous time, whereas the technology choice can be revised either in continuous-time or in discrete-time. In the latter case, the model assumes the form of a hybrid system, whose dynamics is mainly explored numerically. We shows that: (1) overexploitation of the resource arises whenever the reduction in harvesting due to a lower efficiency of clean technology is more than compensated by a higher propensity to pay for greener goods; (2) the difference between the fixed costs of these technologies can be exogenously fixed to provide an incentive for adopting clean technology without affecting the long-run level of the resource; and (3) in some cases, discrete switching of the technology causes overshooting in the dynamics whereas in others it enhances the stability of the system.

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  • Lamantia, F. & Radi, D., 2015. "Exploitation of renewable resources with differentiated technologies: An evolutionary analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 155-174.
  • Handle: RePEc:eee:matcom:v:108:y:2015:i:c:p:155-174
    DOI: 10.1016/j.matcom.2013.09.013
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    1. Petrohilos-Andrianos, Yannis & Xepapadeas, Anastasios, 2017. "Resource harvesting regulation and enforcement: An evolutionary approach," Research in Economics, Elsevier, vol. 71(2), pages 236-253.
    2. Tomáš Tichý & Davide Radi & Fabio Lamantia, 2022. "Hybrid evolutionary oligopolies and the dynamics of corporate social responsibility," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 87-114, January.
    3. Gian Italo Bischi & Fabio Lamantia & Davide Radi, 2018. "Evolutionary oligopoly games with heterogeneous adaptive players," Chapters, in: Luis C. Corchón & Marco A. Marini (ed.), Handbook of Game Theory and Industrial Organization, Volume I, chapter 12, pages 343-370, Edward Elgar Publishing.
    4. Mikhail Anufriev & Davide Radi & Fabio Tramontana, 2018. "Some reflections on past and future of nonlinear dynamics in economics and finance," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 91-118, November.
    5. José Daniel López-Barrientos & Ekaterina Viktorovna Gromova & Ekaterina Sergeevna Miroshnichenko, 2020. "Resource Exploitation in a Stochastic Horizon under Two Parametric Interpretations," Mathematics, MDPI, vol. 8(7), pages 1-29, July.
    6. Davide Radi & Fabio Lamantia & Tomáš Tichý, 2021. "Hybrid dynamics of multi-species resource exploitation," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 559-577, December.
    7. Fabio Lamantia & Anghel Negriu & Jan Tuinstra, 2018. "Technology choice in an evolutionary oligopoly game," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 335-356, November.
    8. Fausto Cavalli & Ahmad Naimzada & Mauro Sodini, 2018. "Oligopoly models with different learning and production time scales," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 297-312, November.

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