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Global competition dynamics of fossil fuels and renewable energy under climate policies and peak oil: A behavioural model

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  • Zeppini, Paolo
  • van den Bergh, Jeroen C.J.M.

Abstract

We develop a stochastic decision model to analyse the global competitive dynamics of fossil fuels and renewable energy. It describes coal, oil/gas, solar and wind. These differ not only in pollution intensities but also in profitability and innovation potential. The model accounts for the effect of learning curves, path-dependence and climate policies. Adoption shares endogenously affect agents' utility through increasing returns to adoption, learning, and a ‘peak oil’ capacity constraint. We find that peak oil induces a transition to coal rather than renewable energy, which worsens climate change. By introducing climate policies - such as a carbon tax, market adoption or R&D subsidies for renewables, and eliminating existing subsidies for fossil fuels - we identify potential transition patterns to a low-carbon energy system. Model analysis clarifies two main features of climate policies: which ones solve the climate problem, i.e. do not surpass the critical carbon budget; and how uncertain or variable are final market shares of energy sources.

Suggested Citation

  • Zeppini, Paolo & van den Bergh, Jeroen C.J.M., 2020. "Global competition dynamics of fossil fuels and renewable energy under climate policies and peak oil: A behavioural model," Energy Policy, Elsevier, vol. 136(C).
  • Handle: RePEc:eee:enepol:v:136:y:2020:i:c:s0301421519304859
    DOI: 10.1016/j.enpol.2019.110907
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    1. Mr. David Coady & Ian W.H. Parry & Louis Sears & Baoping Shang, 2015. "How Large Are Global Energy Subsidies?," IMF Working Papers 2015/105, International Monetary Fund.
    2. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," Review of Economic Studies, Oxford University Press, vol. 68(2), pages 235-260.
    3. Zeppini, Paolo, 2015. "A discrete choice model of transitions to sustainable technologies," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 187-203.
    4. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    5. Hommes,Cars, 2015. "Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems," Cambridge Books, Cambridge University Press, number 9781107564978.
    6. Safarzyńska, Karolina & Frenken, Koen & van den Bergh, Jeroen C.J.M., 2012. "Evolutionary theorizing and modeling of sustainability transitions," Research Policy, Elsevier, vol. 41(6), pages 1011-1024.
    7. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    8. Stephen P. Holland, 2008. "Modeling Peak Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 61-80.
    9. Andrea Baranzini & Jeroen C. J. M. van den Bergh & Stefano Carattini & Richard B. Howarth & Emilio Padilla & Jordi Roca, 2017. "Carbon pricing in climate policy: seven reasons, complementary instruments, and political economy considerations," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 8(4), July.
    10. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    11. Joeri Rogelj & Michiel Schaeffer & Pierre Friedlingstein & Nathan P. Gillett & Detlef P. van Vuuren & Keywan Riahi & Myles Allen & Reto Knutti, 2016. "Differences between carbon budget estimates unravelled," Nature Climate Change, Nature, vol. 6(3), pages 245-252, March.
    12. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    13. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    14. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    15. Paolo Zeppini & Jeroen C. J. M. van den Bergh, 2011. "Competing Recombinant Technologies for Environmental Innovation: Extending Arthur's Model of Lock-In," Industry and Innovation, Taylor & Francis Journals, vol. 18(3), pages 317-334.
    16. Brian Arthur, W. & Ermoliev, Yu. M. & Kaniovski, Yu. M., 1987. "Path-dependent processes and the emergence of macro-structure," European Journal of Operational Research, Elsevier, vol. 30(3), pages 294-303, June.
    17. Chapman, Ian, 2014. "The end of Peak Oil? Why this topic is still relevant despite recent denials," Energy Policy, Elsevier, vol. 64(C), pages 93-101.
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    7. Yuriy Leonidovich Zhukovskiy & Daria Evgenievna Batueva & Alexandra Dmitrievna Buldysko & Bernard Gil & Valeriia Vladimirovna Starshaia, 2021. "Fossil Energy in the Framework of Sustainable Development: Analysis of Prospects and Development of Forecast Scenarios," Energies, MDPI, vol. 14(17), pages 1-28, August.
    8. Yuexiang Yang & Xiaoyu Zheng & Zhen Sun, 2020. "Coal Resource Security Assessment in China: A Study Using Entropy-Weight-Based TOPSIS and BP Neural Network," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    9. Wang, Kai-Hua & Kan, Jia-Min & Qiu, Lianhong & Xu, Shulin, 2023. "Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 256-272.
    10. Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022. "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    11. Pingkuo, Liu & Huan, Peng, 2022. "What drives the green and low-carbon energy transition in China?: An empirical analysis based on a novel framework," Energy, Elsevier, vol. 239(PE).
    12. Jiang, Hong-Dian & Liu, Li-Jing & Dong, Kangyin & Fu, Yu-Wei, 2022. "How will sectoral coverage in the carbon trading system affect the total oil consumption in China? A CGE-based analysis," Energy Economics, Elsevier, vol. 110(C).
    13. Su, Chi-Wei & Pang, Li-Dong & Qin, Meng & Lobonţ, Oana-Ramona & Umar, Muhammad, 2023. "The spillover effects among fossil fuel, renewables and carbon markets: Evidence under the dual dilemma of climate change and energy crises," Energy, Elsevier, vol. 274(C).
    14. Vicknair, David & Tansey, Michael & O'Brien, Thomas E., 2022. "Measuring fossil fuel reserves: A simulation and review of the U.S. Securities and Exchange Commission approach," Resources Policy, Elsevier, vol. 79(C).
    15. Shantha Indrajith H. Liyanage & Fulu Godfrey Netswera & Abel Motsumi, 2021. "Insights from EU Policy Framework in Aligning Sustainable Finance for Sustainable Development in Africa and Asia," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 459-470.

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