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Uncertain long-run emissions targets, CO2 price and global energy transition : a general equilibrium approach

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  • DURAND-LASSERVE, Olivier

    (Center for Operations Research and Econometrics (CORE), Université catholique de Louvain (UCL), Louvain la Neuve, Belgium; IFP, Economics Department, Rueil- Malmaison, France.)

  • PIERRU, Axel

    (IFP, Economics Department, Rueil- Malmaison, France.)

  • SMEERS, Yves

    (Center for Operations Research and Econometrics (CORE), Université catholique de Louvain (UCL), Louvain la Neuve, Belgium)

Abstract

The persistent uncertainty about mid-century CO2 emissions targets is likely to affect not only the technological choices that energy-producing firms will make in the future but also their current invest- ment decisions. We illustrate this effect on CO2 price and global energy transition within a MERGE-type general-equilibrium model framework, by considering simple stochastic CO2 policy scenarios. In these scenarios, economic agents know that credible long-run CO2 emissions targets will be set in 2020, with two possible outcomes: either a ”hard cap” or a ”soft cap”. Each scenario is characterized by the relative probabilities of both possible caps. We derive consistent stochastic trajectories - with two branches after 2020 - for prices and quantities of energy commodities and CO2 emissions permits. The impact of uncertain long-run CO2 emissions targets on prices and technological trajectories is discussed. In addition, a simple marginal approach allows us to analyze the Hotelling rule with risk premia observed for certain scenarios

Suggested Citation

  • DURAND-LASSERVE, Olivier & PIERRU, Axel & SMEERS, Yves, 2010. "Uncertain long-run emissions targets, CO2 price and global energy transition : a general equilibrium approach," LIDAM Discussion Papers CORE 2010027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2010027
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    2. Standardi, Gabriele & Cai, Yiyong & Yeh, Sonia, 2017. "Sensitivity of modeling results to technological and regional details: The case of Italy's carbon mitigation policy," Energy Economics, Elsevier, vol. 63(C), pages 116-128.
    3. Locatelli, Giorgio & Mancini, Mauro, 2010. "Small-medium sized nuclear coal and gas power plant: A probabilistic analysis of their financial performances and influence of CO2 cost," Energy Policy, Elsevier, vol. 38(10), pages 6360-6374, October.
    4. Erin Baker & Olaitan Olaleye & Lara Aleluia Reis, 2015. "Decision Frameworks and the Investment in R&D," Working Papers 2015.42, Fondazione Eni Enrico Mattei.
    5. Chang, Kai & Ge, Fangping & Zhang, Chao & Wang, Weihong, 2018. "The dynamic linkage effect between energy and emissions allowances price for regional emissions trading scheme pilots in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 415-425.
    6. Olivier Durand-Lasserve & Axel Pierru & Yves Smeers, 2011. "Effects of the Uncertainty about Global Economic Recovery on Energy Transition and CO2 Price," Working Papers 1105, Massachusetts Institute of Technology, Center for Energy and Environmental Policy Research.
    7. Baker, Erin & Olaleye, Olaitan & Aleluia Reis, Lara, 2015. "Decision frameworks and the investment in R&D," Energy Policy, Elsevier, vol. 80(C), pages 275-285.
    8. Tarek Atallah & Jorge Blazquez, 2015. "Quantifying the impact of coal on global economic growth and energy productivity in the early 21st century," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2015(2), pages 93-106.
    9. Bistline, John E., 2015. "Electric sector capacity planning under uncertainty: Climate policy and natural gas in the US," Energy Economics, Elsevier, vol. 51(C), pages 236-251.
    10. Axel Pierru and Walid Matar, 2014. "The Impact of Oil Price Volatility on Welfare in the Kingdom of Saudi Arabia: Implications for Public Investment Decision-making," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    11. Aude Pommeret & Katheline Schubert, 2018. "Intertemporal Emission Permits Trading Under Uncertainty and Irreversibility," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 73-97, September.
    12. Alshammari, Yousef M., 2021. "Scenario analysis for energy transition in the chemical industry: An industrial case study in Saudi Arabia," Energy Policy, Elsevier, vol. 150(C).
    13. Durand-Lasserve, Olivier & Pierru, Axel, 2021. "Modeling world oil market questions: An economic perspective," Energy Policy, Elsevier, vol. 159(C).
    14. Arie ten Cate, 2012. "The socially optimal energy transition in a residential neighbourhood in the Netherlands," CPB Discussion Paper 222, CPB Netherlands Bureau for Economic Policy Analysis.
    15. Arie ten Cate, 2012. "The socially optimal energy transition in a residential neighbourhood in the Netherlands," CPB Discussion Paper 222.rdf, CPB Netherlands Bureau for Economic Policy Analysis.

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    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects

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