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How to improve the market efficiency of carbon trading: A perspective of China

Author

Listed:
  • Zhao, Xin-gang
  • Jiang, Gui-wu
  • Nie, Dan
  • Chen, Hao

Abstract

Emissions trading scheme (ETS) is one of the effective measures to realize energy conservation and emission reduction. In order to set up a nationwide carbon emissions trading mechanism, seven ETS pilots have been launched in China. Firstly, based on empirical investigation and research of seven pilots, this paper analyzed the market efficiency of ETS pilots from four aspects: carbon price, trading volume, market liquidity, and information transparency. The result showed that the market efficiency of ETS pilots is not satisfactory in spite of the fact that system designs of ETS have achieved preliminary result. Then, the reason for low market efficiency of ETS pilots was discussed from some factors such as institutional arrangements, market participants, the supply and demand, etc. Finally, this paper puts forward some policy suggestions to improve the market efficiency of China׳s carbon trading market.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:rensus:v:59:y:2016:i:c:p:1229-1245
    DOI: 10.1016/j.rser.2016.01.052
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    References listed on IDEAS

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    2. Lin, Boqiang & Chen, Yufang, 2019. "Dynamic linkages and spillover effects between CET market, coal market and stock market of new energy companies: A case of Beijing CET market in China," Energy, Elsevier, vol. 172(C), pages 1198-1210.
    3. 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.
    4. Chang, Kai & Ye, Zhifang & Wang, Weihong, 2019. "Volatility spillover effect and dynamic correlation between regional emissions allowances and fossil energy markets: New evidence from China’s emissions trading scheme pilots," Energy, Elsevier, vol. 185(C), pages 1314-1324.
    5. Song, Yazhi & Liu, Tiansen & Liang, Dapeng & Li, Yin & Song, Xiaoqiu, 2019. "A Fuzzy Stochastic Model for Carbon Price Prediction Under the Effect of Demand-related Policy in China's Carbon Market," Ecological Economics, Elsevier, vol. 157(C), pages 253-265.
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    15. Wang, Zhaoxia & Zhao, Jing & Li, Meng, 2017. "Analysis and optimization of carbon trading mechanism for renewable energy application in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 435-451.
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