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Effectiveness and risk of initial carbon quota allocation principle under the uncertainty of the Chinese electricity market

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  • Zhaohua, Wang
  • Jingyun, Li
  • Bin, Lu
  • Bo, Wang
  • Bin, Zhang
  • Kaining, Sun
  • Mao, Fan

Abstract

The carbon market's effectiveness in deep decarburization and energy transition has been widely proven. However, as other industries join the carbon market in China, the uncertainty and impact of it on the power industry are still under explored. Here, we define the industry-wide scenarios which power industry might confront in the carbon market. Then, we compare its economic output, market activity and environmental impact under initial carbon quota allocation principles based on efficiency and grandfather methods by the comprehensive evaluation model of energy and carbon markets combined with inverse DEA method. Our results show that when the power industry is in an advantageous position, the efficiency method is fairer and more efficient than the grandfather method. The potential economic output rate has more than doubled compared to that of the grandfather method. Market activity and emission reduction potential are 7% and 25% more than that in the grandfather principle, respectively. Nevertheless, when the power industry is in a disadvantageous position, the efficiency method leads to an imbalance between power supply and demand in the market and power shortages in 19 regions. Then the trading activity of the power market drops by 12%, resulting in serious economic loss, especially in China's eastern region (−7.29%). The economic risk caused by the grandfather method has been significantly reduced than that of the efficiency method. And there may be greater potential risks under the efficiency method. This study identifies the potential challenges and obstacles of future carbon market and addresses the urgency of policy to tackle this issue to facilitate a carbon market that operates robustly under uncertainty.

Suggested Citation

  • Zhaohua, Wang & Jingyun, Li & Bin, Lu & Bo, Wang & Bin, Zhang & Kaining, Sun & Mao, Fan, 2023. "Effectiveness and risk of initial carbon quota allocation principle under the uncertainty of the Chinese electricity market," China Economic Review, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:chieco:v:77:y:2023:i:c:s1043951x2200150x
    DOI: 10.1016/j.chieco.2022.101892
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    1. Meunier, Guy & Ponssard, Jean-Pierre & Quirion, Philippe, 2014. "Carbon leakage and capacity-based allocations: Is the EU right?," Journal of Environmental Economics and Management, Elsevier, vol. 68(2), pages 262-279.
    2. Mäler, Karl-Göran & Li, Chuan-Zhong, 2010. "Measuring sustainability under regime shift uncertainty: a resilience pricing approach," Environment and Development Economics, Cambridge University Press, vol. 15(6), pages 707-719, December.
    3. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    4. Wei, Quanling & Zhang, Jianzhong & Zhang, Xiangsun, 2000. "An inverse DEA model for inputs/outputs estimate," European Journal of Operational Research, Elsevier, vol. 121(1), pages 151-163, February.
    5. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    6. Zhou, P. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    7. Demailly, Damien & Quirion, Philippe, 2008. "European Emission Trading Scheme and competitiveness: A case study on the iron and steel industry," Energy Economics, Elsevier, vol. 30(4), pages 2009-2027, July.
    8. Du, Limin & Hanley, Aoife & Wei, Chu, 2015. "Estimating the Marginal Abatement Cost Curve of CO2 Emissions in China: Provincial Panel Data Analysis," Energy Economics, Elsevier, vol. 48(C), pages 217-229.
    9. Feng, Chenpeng & Chu, Feng & Ding, Jingjing & Bi, Gongbing & Liang, Liang, 2015. "Carbon Emissions Abatement (CEA) allocation and compensation schemes based on DEA," Omega, Elsevier, vol. 53(C), pages 78-89.
    10. Xie, Qiwei & Hu, Ping & Jiang, An & Li, Yongjun, 2019. "Carbon emissions allocation based on satisfaction perspective and data envelopment analysis," Energy Policy, Elsevier, vol. 132(C), pages 254-264.
    11. Wu, Yinyin & Wang, Ping & Liu, Xin & Chen, Jiandong & Song, Malin, 2020. "Analysis of regional carbon allocation and carbon trading based on net primary productivity in China," China Economic Review, Elsevier, vol. 60(C).
    12. Schmidt, Robert C. & Heitzig, Jobst, 2014. "Carbon leakage: Grandfathering as an incentive device to avert firm relocation," Journal of Environmental Economics and Management, Elsevier, vol. 67(2), pages 209-223.
    13. Yue-Jun Zhang & Jun-Fang Hao, 2017. "Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles," Annals of Operations Research, Springer, vol. 255(1), pages 117-140, August.
    14. Färe, Rolf & Grosskopf, Shawna & Pasurka,, Carl A., 2013. "Tradable permits and unrealized gains from trade," Energy Economics, Elsevier, vol. 40(C), pages 416-424.
    15. Feng, Zhiying & Tang, Wenhu & Niu, Zhewen & Wu, Qinghua, 2018. "Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1122-1135.
    16. Yan, Hong & Wei, Quanling & Hao, Gang, 2002. "DEA models for resource reallocation and production input/output estimation," European Journal of Operational Research, Elsevier, vol. 136(1), pages 19-31, January.
    17. Limin Du & Aoife Hanley & Chu Wei, 2015. "Marginal Abatement Costs of Carbon Dioxide Emissions in China: A Parametric Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(2), pages 191-216, June.
    18. Pang, Rui-zhi & Deng, Zhong-qi & Chiu, Yung-ho, 2015. "Pareto improvement through a reallocation of carbon emission quotas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 419-430.
    19. Zhu, Lei & Zhang, Xiao-Bing & Li, Yuan & Wang, Xu & Guo, Jianxin, 2017. "Can an emission trading scheme promote the withdrawal of outdated capacity in energy-intensive sectors? A case study on China's iron and steel industry," Energy Economics, Elsevier, vol. 63(C), pages 332-347.
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