Electric-carbon market coupling and price transmission mechanism in China: An empirical analysis and development barriers study

Under the ‘dual-carbon’ goal, China's carbon market is crucial for steering the power sector toward a clean transition via price signals. However, the coupling of electricity and carbon markets remains incomplete. This study investigates their coupling mechanism, price transmission, and the incentive effect of carbon pricing. Using provincial data from 2013 to 2023, our empirical analysis quantifies the transmission efficiency of carbon prices to generator-side electricity tariffs at 0.765. Rolling regression further indicates a dynamic pass-through effect, which experienced temporary attenuation during major institutional transitions. We construct an ecosystem panorama of the coupled market, outlining interactions among supply, circulation, and demand sides. The case of Huaneng International Group demonstrates that carbon costs effectively drive corporate energy transition, reducing carbon intensity by 37 % and raising clean energy share to 31.24 %. Finally, we identify key systemic barriers: undeducted CCERs distort the grid emission factor, creating unaccounted carbon liabilities for exporters, while generators internalize costs from the carbon price's “tidal effect” rather than fully passing them through. These practices highlight imperfections in market design and its linkage to policy. Therefore, addressing these issues urgently requires establishing a unified environmental attributes registry and reforming the compliance cycle to ensure carbon costs are transparently and efficiently reflected in prices.

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Publication Details

Journal
Journal of Cleaner Production
Published
2026-01-30
DOI
https://doi.org/10.1016/j.jclepro.2026.147692
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
21.93
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Electric-carbon market coupling and price transmission mechanism in China: An empirical analysis and development barriers study

R. Yang, Yanjun Shen, Jiajun Wu, Hang Fan et al.
1 citations
Journal of Cleaner Production
Integrated Energy Systems Optimization
21.93
article

Electric-carbon market coupling and price transmission mechanism in China: An empirical analysis and development barriers study

R. Yang, Yanjun Shen, Jiajun Wu, Hang Fan, Yunjie Duan
article en
1 citations

Abstract

Under the ‘dual-carbon’ goal, China's carbon market is crucial for steering the power sector toward a clean transition via price signals. However, the coupling of electricity and carbon markets remains incomplete. This study investigates their coupling mechanism, price transmission, and the incentive effect of carbon pricing. Using provincial data from 2013 to 2023, our empirical analysis quantifies the transmission efficiency of carbon prices to generator-side electricity tariffs at 0.765. Rolling regression further indicates a dynamic pass-through effect, which experienced temporary attenuation during major institutional transitions. We construct an ecosystem panorama of the coupled market, outlining interactions among supply, circulation, and demand sides. The case of Huaneng International Group demonstrates that carbon costs effectively drive corporate energy transition, reducing carbon intensity by 37 % and raising clean energy share to 31.24 %. Finally, we identify key systemic barriers: undeducted CCERs distort the grid emission factor, creating unaccounted carbon liabilities for exporters, while generators internalize costs from the carbon price's “tidal effect” rather than fully passing them through. These practices highlight imperfections in market design and its linkage to policy. Therefore, addressing these issues urgently requires establishing a unified environmental attributes registry and reforming the compliance cycle to ensure carbon costs are transparently and efficiently reflected in prices.

Journal of Cleaner ProductionVol. 544
North China Electric Power University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 1%
Integrated Energy Systems Optimization
21.93
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