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Model predictive control, the economy, and the issue of global warming

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  • BRECHET, Thierry

    (Université catholique de Louvain, CORE and Louvain School of Management, Chair Lhoist Berghemans in Environmental Economics and Management, B-1348 Louvain-la-Neuve, Belgium)

  • CAMACHO, Carmen

    (Université catholique de Louvain, Belgian National Foundation of Scientific Research and Economics Department, B-1348 Louvain- la-Neuve, Belgium)

  • VELIOV, Vladimir

    (ORCOS, Institute of Mathematical Methods in Economics, Vienna University of Technology, A-1040 Vienna, Austria)

Abstract

This study is motivated by the evidence of global warming, which is caused by human activity but affects the efficiency of the economy. We employ the integrated assessment Nordhaus DICE-2007 model [16]. Generally speaking, the framework is that of dynamic optimization of the discounted inter-temporal utility of consumption, taking into account the economic and the environmental dynamics. The main novelty is that several reasonable types of behavior (policy) of the economic agents, which may be non-optimal from the point of view of the global performance but are reasonable form an individual point of view and exist in reality, are strictly defined and analyzed. These include the concepts of “business as usual”, in which an economic agent ignores her impact on the climate change (although adapting to it), and of “free riding with a perfect foresight”, where some economic agents optimize in an adaptive way their individual performance expecting that the others would perform in a collectively optimal way. These policies are defined in a formal and unified way modifying ideas from the so-called “model predictive control”. The introduced concepts are relevant to many other problems of dynamic optimization, especially in the context of resource economics. However, the numerical analysis in this paper is devoted to the evolution of the world economy and the average temperature in the next 150 years, depending on different scenarios for the behavior of the economic agents. In particular, the results show that the “business as usual”, although adaptive to the change of the atmospheric temperature, may lead within 150 years to increase of temperature by 2°C more than the collectively optimal policy.

Suggested Citation

  • BRECHET, Thierry & CAMACHO, Carmen & VELIOV, Vladimir, 2010. "Model predictive control, the economy, and the issue of global warming," LIDAM Discussion Papers CORE 2010016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2010016
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    References listed on IDEAS

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    Cited by:

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    2. Tatiana Kiseleva, 2016. "Heterogeneous Beliefs and Climate Catastrophes," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(3), pages 599-622, November.
    3. Yue Liu & Jijian Zhang & Xuhui Ding & Xiling Zhang, 2023. "Intervene in advance or passively? Analysis and application on congestion control of smart grid," Annals of Operations Research, Springer, vol. 320(2), pages 887-899, January.
    4. Marcel Nutz & Florian Stebegg, 2021. "Climate Change Adaptation under Heterogeneous Beliefs," Papers 2101.08424, arXiv.org, revised Feb 2022.
    5. Bondarev, Anton & Greiner, Alfred, 2017. "Environmental pollution in a growing economy with endogenous structural change," Working papers 2017/03, Faculty of Business and Economics - University of Basel.
    6. Bondarev, Anton & Greiner, Alfred, 2020. "Global warming and technical change: Multiple steady-states and policy options," China Economic Review, Elsevier, vol. 62(C).
    7. Georges BASTIN & Isabelle CASSIERS, 2013. "Modelling the balanced transition to a sustainable economy," LIDAM Discussion Papers IRES 2013014, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    8. Thierry Bréchet & Carmen Camacho & Vladimir M. Veliov, 2012. "Adaptive Model-Predictive Climate Policies in a Multi-Country Setting," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00718659, HAL.
    9. Stefan Schaltegger & Jacob Hörisch, 2017. "In Search of the Dominant Rationale in Sustainability Management: Legitimacy- or Profit-Seeking?," Journal of Business Ethics, Springer, vol. 145(2), pages 259-276, October.
    10. Anton Bondarev & Alfred Greiner, 2022. "How ongoing structural change creates a double dividend: outdating of technologies and green growth," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(2), pages 125-160, May.
    11. Camacho, Carmen & Sun, Yu, 2019. "Longterm decision making under the threat of earthquakes?," LSE Research Online Documents on Economics 118927, London School of Economics and Political Science, LSE Library.
    12. BRECHET, Thierry & THENIE, Julien & ZEIMES, Thibaut & ZUBER, Stéphane, 2010. "The benefits of cooperation under uncertainty: the case of climate change," LIDAM Discussion Papers CORE 2010062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Marcel Nutz & Florian Stebegg, 2022. "Climate change adaptation under heterogeneous beliefs," Mathematics and Financial Economics, Springer, volume 16, number 3, December.
    14. Wesseh, Presley K. & Lin, Boqiang, 2016. "Modeling environmental policy with and without abatement substitution: A tradeoff between economics and environment?," Applied Energy, Elsevier, vol. 167(C), pages 34-43.
    15. Carmen Camacho & Yu Sun, 2017. "Longterm decision making under the threat of earthquakes," PSE Working Papers halshs-01670507, HAL.
    16. Marian Leimbach & Anselm Schultes & Lavinia Baumstark & Anastasis Giannousakis & Gunnar Luderer, 2017. "Solution algorithms for regional interactions in large-scale integrated assessment models of climate change," Annals of Operations Research, Springer, vol. 255(1), pages 29-45, August.
    17. Carmen Camacho & Yu Sun, 2017. "Longterm decision making under the threat of earthquakes," Working Papers halshs-01670507, HAL.

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    Keywords

    environmental economics; dynamic optimization; optimal control; global warming; model predictive control; integrated assessment;
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