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A comparison of the operation of China's carbon trading market and energy market and their spillover effects

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  • Song, Xiang
  • Wang, Dingyu
  • Zhang, Xuantao
  • He, Yuan
  • Wang, Yong

Abstract

This study measures the liquidity and volatility of the operation of the carbon trading and energy markets using liquidity ratio indicators and log return indicators. It adopts China's carbon trading and energy markets as the research objects, and evaluates the mean spillover effects and volatility spillover effects between the two using the vector autoregression (VAR) model and the BEKK-MGARCH model. The findings indicate that: (1) The liquidity of China's carbon trading market is better than that of the energy market. The average liquidity ratio of the Hubei and Shenzhen carbon trading markets is much lower than that of the coal market, 43016.131. It may be attributed to the fact that China's carbon trading market is currently small and easy to regulate. (2) The volatility of both the Chinese carbon trading market and energy market is small, and the absolute values of the mean log return rate are close to 0. It could be because China's carbon trading market is mainly distributed through free quota allocation, while the energy market has been mature and stable for many years. (3) There is a spillover effect between the carbon trading and energy markets in some parts of China, but the direction and degree of spillover effect vary, which may be due to differences in the economic development level, energy consumption structure, and environmental policies of each pilot carbon trading region. (4) The spillover effect between the two markets is stronger, perhaps due to China's current model of using coal as the main fuel.

Suggested Citation

  • Song, Xiang & Wang, Dingyu & Zhang, Xuantao & He, Yuan & Wang, Yong, 2022. "A comparison of the operation of China's carbon trading market and energy market and their spillover effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  • Handle: RePEc:eee:rensus:v:168:y:2022:i:c:s1364032122007468
    DOI: 10.1016/j.rser.2022.112864
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    References listed on IDEAS

    as
    1. Xu, Yingying & Salem, Sultan, 2021. "Explosive behaviors in Chinese carbon markets: are there price bubbles in eight pilots?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    2. Kong, Yuan & Feng, Chao & Yang, Jun, 2020. "How does China manage its energy market? A perspective of policy evolution," Energy Policy, Elsevier, vol. 147(C).
    3. Dai, Xingyu & Xiao, Ling & Wang, Qunwei & Dhesi, Gurjeet, 2021. "Multiscale interplay of higher-order moments between the carbon and energy markets during Phase III of the EU ETS," Energy Policy, Elsevier, vol. 156(C).
    4. 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.
    5. Chang, Kai & Chen, Rongda & Chevallier, Julien, 2018. "Market fragmentation, liquidity measures and improvement perspectives from China's emissions trading scheme pilots," Energy Economics, Elsevier, vol. 75(C), pages 249-260.
    6. Fu, Yang & Zheng, Zeyu, 2020. "Volatility modeling and the asymmetric effect for China’s carbon trading pilot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    7. Zeng, Sheng & Su, Bin & Zhang, Minglong & Gao, Yuan & Liu, Jun & Luo, Song & Tao, Qingmei, 2021. "Analysis and forecast of China's energy consumption structure," Energy Policy, Elsevier, vol. 159(C).
    8. Chang, Chia-Lin & Mai, Te-Ke & McAleer, Michael, 2019. "Establishing national carbon emission prices for China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 1-16.
    9. Zhang, Yue-Jun & Liang, Ting & Jin, Yan-Lin & Shen, Bo, 2020. "The impact of carbon trading on economic output and carbon emissions reduction in China’s industrial sectors," Applied Energy, Elsevier, vol. 260(C).
    10. Weng, Qingqing & Xu, He, 2018. "A review of China’s carbon trading market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 613-619.
    11. Hu, Huanling & Wang, Lin & Peng, Lu & Zeng, Yu-Rong, 2020. "Effective energy consumption forecasting using enhanced bagged echo state network," Energy, Elsevier, vol. 193(C).
    12. 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.
    13. Wang, Meng & Wang, Wei & Wu, Lifeng, 2022. "Application of a new grey multivariate forecasting model in the forecasting of energy consumption in 7 regions of China," Energy, Elsevier, vol. 243(C).
    14. Sun, Limei & Xiang, Meiqi & Shen, Qing, 2020. "A comparative study on the volatility of EU and China’s carbon emission permits trading markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    15. Gao, Yuning & Li, Meng & Xue, Jinjun & Liu, Yu, 2020. "Evaluation of effectiveness of China's carbon emissions trading scheme in carbon mitigation," Energy Economics, Elsevier, vol. 90(C).
    16. Guo, Li-Yang & Feng, Chao, 2021. "Are there spillovers among China's pilots for carbon emission allowances trading?," Energy Economics, Elsevier, vol. 103(C).
    17. Tang, Ling & Wang, Haohan & Li, Ling & Yang, Kaitong & Mi, Zhifu, 2020. "Quantitative models in emission trading system research: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    18. Zhang, Wei & Li, Jing & Li, Guoxiang & Guo, Shucen, 2020. "Emission reduction effect and carbon market efficiency of carbon emissions trading policy in China," Energy, Elsevier, vol. 196(C).
    19. Mu, Yaqian & Wang, Can & Cai, Wenjia, 2018. "The economic impact of China's INDC: Distinguishing the roles of the renewable energy quota and the carbon market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2955-2966.
    20. Gong, Xu & Shi, Rong & Xu, Jun & Lin, Boqiang, 2021. "Analyzing spillover effects between carbon and fossil energy markets from a time-varying perspective," Applied Energy, Elsevier, vol. 285(C).
    21. Zhang, Meng & Guo, Huan & Sun, Ming & Liu, Sifeng & Forrest, Jeffrey, 2022. "A novel flexible grey multivariable model and its application in forecasting energy consumption in China," Energy, Elsevier, vol. 239(PE).
    22. Liu, Yunqiang & Liu, Sha & Shao, Xiaoyu & He, Yanqiu, 2022. "Policy spillover effect and action mechanism for environmental rights trading on green innovation: Evidence from China's carbon emissions trading policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    23. Guo, Yaoqi & Shi, Fengyuan & Yu, Zhuling & Yao, Shanshan & Zhang, Hongwei, 2022. "Asymmetric multifractality in China’s energy market based on improved asymmetric multifractal cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    24. Peng-Fei Dai & Xiong Xiong & Toan Luu Duc Huynh & Jiqiang Wang, 2020. "The impact of economic policy uncertainties on the volatility of European carbon market," Papers 2007.10564, arXiv.org, revised Aug 2021.
    25. Guo, Wen & Liu, Xiaorui, 2022. "Market fragmentation of energy resource prices and green total factor energy efficiency in China," Resources Policy, Elsevier, vol. 76(C).
    26. Peng, Cheng & Chen, Heng & Lin, Chaoran & Guo, Shuang & Yang, Zhi & Chen, Ke, 2021. "A framework for evaluating energy security in China: Empirical analysis of forecasting and assessment based on energy consumption," Energy, Elsevier, vol. 234(C).
    27. Peng, Lu & Wang, Lin & Xia, De & Gao, Qinglu, 2022. "Effective energy consumption forecasting using empirical wavelet transform and long short-term memory," Energy, Elsevier, vol. 238(PB).
    28. Jiang, Ping & Yang, Hufang & Li, Hongmin & Wang, Ying, 2021. "A developed hybrid forecasting system for energy consumption structure forecasting based on fuzzy time series and information granularity," Energy, Elsevier, vol. 219(C).
    29. Hu, Yucai & Ren, Shenggang & Wang, Yangjie & Chen, Xiaohong, 2020. "Can carbon emission trading scheme achieve energy conservation and emission reduction? Evidence from the industrial sector in China," Energy Economics, Elsevier, vol. 85(C).
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