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The System Dynamics (SD) Analysis of the Government and Power Producers’ Evolutionary Game Strategies Based on Carbon Trading (CT) Mechanism: A Case of China

Author

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  • Xin-gang Zhao

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing 102206, China)

  • Yu-zhuo Zhang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Beijing 102206, China)

Abstract

Climate warming caused by carbon emissions is one of the most serious problems faced by human beings, and the carbon trading (CT) mechanism is an effective way to promote carbon emission reduction and achieve green and low-carbon development. Scholars have mainly studied the impact of CT on the energy economy system, and few scholars studied the game process and behavior strategies of government and power producers in the implementation of a CT mechanism. This paper will fill this gap. This paper firstly constructs the evolutionary game model of government and power producers based on CT, and then simulates the evolutionary process of game behavior strategies by establishing a system dynamics (SD) model, and finally studies the influence of government controllable key factors on system stability. The combination of evolutionary game and SD in our study not only clearly reveals the complex and dynamic evolution process of game models under bounded rationality, but also provides a qualitative and quantitative simulation platform for analyzing the dynamic game process between government and power producers. The results show that: (1) There is no evolutionarily stable strategy (ESS) in the game system between government and power producers under CT, and the system evolution is characterized by periodicity; (2) When the government implements dynamic subsidies or punitive measures, the mixed strategy of the game system has ESS; (3) Reducing the unit subsidy and raising the unit fine can both promote the participation of power producers in CT, but the former increases the probability of government supervision; thus, it is best to increase the fines when the government makes strategic adjustments, followed by reducing subsidies.

Suggested Citation

  • Xin-gang Zhao & Yu-zhuo Zhang, 2018. "The System Dynamics (SD) Analysis of the Government and Power Producers’ Evolutionary Game Strategies Based on Carbon Trading (CT) Mechanism: A Case of China," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1150-:d:140575
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    References listed on IDEAS

    as
    1. Yang, Lin & Li, Fengyu & Zhang, Xian, 2016. "Chinese companies’ awareness and perceptions of the Emissions Trading Scheme (ETS): Evidence from a national survey in China," Energy Policy, Elsevier, vol. 98(C), pages 254-265.
    2. Hu, Hui & Xie, Nan & Fang, Debin & Zhang, Xiaoling, 2018. "The role of renewable energy consumption and commercial services trade in carbon dioxide reduction: Evidence from 25 developing countries," Applied Energy, Elsevier, vol. 211(C), pages 1229-1244.
    3. Daniel Friedman, 1998. "On economic applications of evolutionary game theory," Journal of Evolutionary Economics, Springer, vol. 8(1), pages 15-43.
    4. Fan, Ruguo & Dong, Lili, 2018. "The dynamic analysis and simulation of government subsidy strategies in low-carbon diffusion considering the behavior of heterogeneous agents," Energy Policy, Elsevier, vol. 117(C), pages 252-262.
    5. Huiqin Jiang & Xinxiao Shao & Xiao Zhang & Jianqiang Bao, 2017. "A Study of the Allocation of Carbon Emission Permits among the Provinces of China Based on Fairness and Efficiency," Sustainability, MDPI, vol. 9(11), pages 1-17, November.
    6. Fang, Guochang & Tian, Lixin & Liu, Menghe & Fu, Min & Sun, Mei, 2018. "How to optimize the development of carbon trading in China—Enlightenment from evolution rules of the EU carbon price," Applied Energy, Elsevier, vol. 211(C), pages 1039-1049.
    7. Liang Liu & Cong Feng & Hongwei Zhang & Xuehua Zhang, 2015. "Game Analysis and Simulation of the River Basin Sustainable Development Strategy Integrating Water Emission Trading," Sustainability, MDPI, vol. 7(5), pages 1-21, April.
    8. Fang, Guochang & Tian, Lixin & Fu, Min & Sun, Mei, 2014. "Government control or low carbon lifestyle? – Analysis and application of a novel selective-constrained energy-saving and emission-reduction dynamic evolution system," Energy Policy, Elsevier, vol. 68(C), pages 498-507.
    9. Friedman, Daniel, 1991. "Evolutionary Games in Economics," Econometrica, Econometric Society, vol. 59(3), pages 637-666, May.
    10. Xingang Zhao & Yuzhuo Zhang & Ji Liang & Yanbin Li & Rongda Jia & Ling Wang, 2018. "The Sustainable Development of the Economic-Energy-Environment (3E) System under the Carbon Trading (CT) Mechanism: A Chinese Case," Sustainability, MDPI, vol. 10(1), pages 1-21, January.
    11. Zhao, Xin-gang & Jiang, Gui-wu & Nie, Dan & Chen, Hao, 2016. "How to improve the market efficiency of carbon trading: A perspective of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1229-1245.
    12. Lin, Boqiang & Jia, Zhijie, 2018. "Impact of quota decline scheme of emission trading in China: A dynamic recursive CGE model," Energy, Elsevier, vol. 149(C), pages 190-203.
    13. Yidan Chen & Yuwei Sun & Can Wang, 2018. "Influencing Factors of Companies’ Behavior for Mitigation: A Discussion within the Context of Emission Trading Scheme," Sustainability, MDPI, vol. 10(2), pages 1-15, February.
    14. Li, Wei & Jia, Zhijie, 2016. "The impact of emission trading scheme and the ratio of free quota: A dynamic recursive CGE model in China," Applied Energy, Elsevier, vol. 174(C), pages 1-14.
    15. Zhao, Xin-gang & Wu, Lei & Li, Ang, 2017. "Research on the efficiency of carbon trading market in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1-8.
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