IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i10p4274-d1651685.html

Risk Spillover in the Carbon-Stock System and Sustainability Transition: Empirical Evidence from China’s ETS Pilots and A-Share Emission-Regulated Firms

Author

Listed:
  • Yifan Wang

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Yufeiyang Zeng

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Zongfa Wu

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

Abstract

This study employs the TVP-VAR-BK-DY spillover index model to investigate the risk spillover effects between China’s carbon emission trading system (ETS) pilots and A-share listed emission-regulated enterprises. The findings reveal that, due to the nascent stage of China’s carbon market, the overall risk spillover level within the “carbon-stock” system remains low; however, dynamic risk spillovers have shown an upward trend driven by the advancement of ETS pilots. In particular, during compliance periods, enterprises that exceed their emission limits must purchase sufficient allowances on the carbon trading market to avoid high penalties for non-compliance. This creates substantial demand, which drives a rapid increase in the spot prices of carbon allowances, triggering intense short-term price fluctuations and risk spillovers—a pronounced “compliance-driven trading” effect. Frequency domain analysis indicates that long-term shocks have a significantly greater impact on the market than short-term oscillations, reflecting moderate information processing efficiency within the “carbon-stock” system. Directional spillover analysis shows that A-share enterprises initially absorb risks from the carbon market in the short term, but over the long term, they transmit part of these risks back to the carbon market, forming a significant bidirectional risk transmission relationship. Furthermore, heterogeneity analysis reveals marked differences in risk spillover contributions among firms associated with different ETS pilots, as well as between enterprises with polluting behaviors and those with high ESG scores, with the latter contributing considerably higher spillovers to the overall carbon market. These findings offer nuanced insights into the dynamic, structural, and firm-level characteristics of risk spillovers, providing valuable guidance for policymakers and investors to enhance market stability and optimize investment strategies.

Suggested Citation

  • Yifan Wang & Yufeiyang Zeng & Zongfa Wu, 2025. "Risk Spillover in the Carbon-Stock System and Sustainability Transition: Empirical Evidence from China’s ETS Pilots and A-Share Emission-Regulated Firms," Sustainability, MDPI, vol. 17(10), pages 1-30, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4274-:d:1651685
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/10/4274/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/10/4274/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Qingyang, 2024. "Power play in carbon trading market: How status of executives with R&D background incentives companies’ low-carbon innovation," Energy Policy, Elsevier, vol. 188(C).
    2. Razzaq, Asif & Sharif, Arshian & An, Hui & Aloui, Chaker, 2022. "Testing the directional predictability between carbon trading and sectoral stocks in China: New insights using cross-quantilogram and rolling window causality approaches," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    3. Li, Hao & Guo, Hui & Hao, Xinyao & Zhang, Xuan, 2023. "The ESG rating, spillover of ESG ratings, and stock return: Evidence from Chinese listed firms," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    4. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    5. Munnings, Clayton & Morgenstern, Richard D. & Wang, Zhongmin & Liu, Xu, 2016. "Assessing the design of three carbon trading pilot programs in China," Energy Policy, Elsevier, vol. 96(C), pages 688-699.
    6. Chun, Dohyun & Cho, Hoon & Kim, Jihun, 2022. "The relationship between carbon-intensive fuel and renewable energy stock prices under the emissions trading system," Energy Economics, Elsevier, vol. 114(C).
    7. Stiassny, Alfred, 1996. "A Spectral Decomposition for Structural VAR Models," Empirical Economics, Springer, vol. 21(4), pages 535-555.
    8. Jintao Ma & Qiuguang Hu & Weiteng Shen & Xinyi Wei, 2021. "Does the Low-Carbon City Pilot Policy Promote Green Technology Innovation? Based on Green Patent Data of Chinese A-Share Listed Companies," IJERPH, MDPI, vol. 18(7), pages 1-18, April.
    9. Wu, Ruirui & Qin, Zhongfeng & Liu, Bing-Yue, 2022. "A systemic analysis of dynamic frequency spillovers among carbon emissions trading (CET), fossil energy and sectoral stock markets: Evidence from China," Energy, Elsevier, vol. 254(PA).
    10. Chatziantoniou, Ioannis & Gabauer, David & Gupta, Rangan, 2023. "Integration and risk transmission in the market for crude oil: New evidence from a time-varying parameter frequency connectedness approach," Resources Policy, Elsevier, vol. 84(C).
    11. Yang, Lu, 2022. "Idiosyncratic information spillover and connectedness network between the electricity and carbon markets in Europe," Journal of Commodity Markets, Elsevier, vol. 25(C).
    12. Li, Zheng-Zheng & Li, Yameng & Huang, Chia-Yun & Peculea, Adelina Dumitrescu, 2023. "Volatility spillover across Chinese carbon markets: Evidence from quantile connectedness method," Energy Economics, Elsevier, vol. 119(C).
    13. Zhang, Wei & Li, Guoxiang & Guo, Fanyong, 2022. "Does carbon emissions trading promote green technology innovation in China?," Applied Energy, Elsevier, vol. 315(C).
    14. Zheng, Jiali & Mi, Zhifu & Coffman, D'Maris & Milcheva, Stanimira & Shan, Yuli & Guan, Dabo & Wang, Shouyang, 2019. "Regional development and carbon emissions in China," Energy Economics, Elsevier, vol. 81(C), pages 25-36.
    15. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    16. Liu, Ming & Shan, Yanfei & Li, Yemei, 2022. "Study on the effect of carbon trading regulation on green innovation and heterogeneity analysis from China," Energy Policy, Elsevier, vol. 171(C).
    17. Oberndorfer, Ulrich, 2009. "EU Emission Allowances and the stock market: Evidence from the electricity industry," Ecological Economics, Elsevier, vol. 68(4), pages 1116-1126, February.
    18. Wen, Fenghua & Zhao, Lili & He, Shaoyi & Yang, Guozheng, 2020. "Asymmetric relationship between carbon emission trading market and stock market: Evidences from China," Energy Economics, Elsevier, vol. 91(C).
    19. Jiménez-Rodríguez, Rebeca, 2019. "What happens to the relationship between EU allowances prices and stock market indices in Europe?," Energy Economics, Elsevier, vol. 81(C), pages 13-24.
    20. Lu, Juan & Li, He, 2024. "The impact of ESG ratings on low carbon investment: Evidence from renewable energy companies," Renewable Energy, Elsevier, vol. 223(C).
    21. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    22. Xu, Lin & Wu, Chenyang & Qin, Quande & Lin, Xiaoying, 2022. "Spillover effects and nonlinear correlations between carbon emissions and stock markets: An empirical analysis of China's carbon-intensive industries," Energy Economics, Elsevier, vol. 111(C).
    23. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    24. Yigang Wei & Yan Li & Julien Chevallier & Michal Wojewodzki, 2024. "The Efficiency of China’s Carbon Trading Schemes: A Tale of Seven Pilot Markets," Commodities, MDPI, vol. 3(3), pages 1-21, August.
    25. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    26. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    27. Xiaosheng Li & Yunxia Shu & Xin Jin, 2022. "Environmental regulation, carbon emissions and green total factor productivity: a case study of China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2577-2597, February.
    28. Dong, Qingli & Zhao, Yanzhi & Ma, Xiaojun & Zhou, Yanan, 2024. "Risk spillover between carbon markets and stock markets from a progressive perspective: Measurements, spillover networks, and driving factors," Energy Economics, Elsevier, vol. 129(C).
    29. Kumar, Surender & Managi, Shunsuke & Matsuda, Akimi, 2012. "Stock prices of clean energy firms, oil and carbon markets: A vector autoregressive analysis," Energy Economics, Elsevier, vol. 34(1), pages 215-226.
    30. Feng, Zhen-Hua & Zou, Le-Le & Wei, Yi-Ming, 2011. "Carbon price volatility: Evidence from EU ETS," Applied Energy, Elsevier, vol. 88(3), pages 590-598, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi, Qing & Jiang, Yuanying, 2025. "Time-frequency spillovers between carbon, fossil fuels, and clean energy markets: New insights from the TVP-VAR framework," Energy, Elsevier, vol. 323(C).
    2. Yang, Ming-Yuan & Chen, Zhanghangjian & Liang, Zongzheng & Li, Sai-Ping, 2023. "Dynamic and asymmetric connectedness in the global “Carbon-Energy-Stock” system under shocks from exogenous events," Journal of Commodity Markets, Elsevier, vol. 32(C).
    3. Man, Yuanyuan & Zhang, Sunpei & He, Yongda, 2024. "Dynamic risk spillover and hedging efficacy of China’s carbon-energy-finance markets: Economic policy uncertainty and investor sentiment non-linear causal effects," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1397-1416.
    4. Yang, Guangyi & Tang, Chun & Liu, Xiaoxing, 2025. "The power of role models: A study on the efficiency connectedness of carbon markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 104(C).
    5. Zhao, Lu-Tao & Liu, Hai-Yi & Chen, Xue-Hui, 2024. "How does carbon market interact with energy and sectoral stocks? Evidence from risk spillover and wavelet coherence," Journal of Commodity Markets, Elsevier, vol. 33(C).
    6. Tabash, Mosab I. & Sheikh, Umaid A. & Selmi, Refk & Al-Faryan, Mamdouh Abdulaziz Saleh & Hammoudeh, Shawkat, 2025. "The asymmetric effects of European carbon emission trading system on European stock market returns: The moderating role of oil price uncertainty," International Review of Financial Analysis, Elsevier, vol. 104(PA).
    7. Liu, Chunna & Ma, Shihan & Lu, Shiyi & Zhi, Jiaqi & Shen, Jian & Li, Xiaoyan & Shi, Changfeng, 2025. "Study on the time-frequency risk spillover network of “carbon-energy-stock” system under climate risk shock," Energy, Elsevier, vol. 334(C).
    8. Guo, Li-Yang & Feng, Chao, 2021. "Are there spillovers among China's pilots for carbon emission allowances trading?," Energy Economics, Elsevier, vol. 103(C).
    9. Wu, Xinyu & Jiang, Zhengting, 2023. "Time-varying asymmetric volatility spillovers among China’s carbon markets, new energy market and stock market under the shocks of major events," Energy Economics, Elsevier, vol. 126(C).
    10. Wu, Ruirui & Qin, Zhongfeng & Liu, Bing-Yue, 2022. "A systemic analysis of dynamic frequency spillovers among carbon emissions trading (CET), fossil energy and sectoral stock markets: Evidence from China," Energy, Elsevier, vol. 254(PA).
    11. Yingying Xu & Xiang Li, 2023. "Green or grey stocks? Dynamic effects of carbon markets based on Chinese practices," Empirical Economics, Springer, vol. 65(6), pages 2521-2547, December.
    12. Xiaohan Cai & Bo Yan, 2025. "Tail Dependence of Liquidity and Volatility in Carbon Futures Market: Evidence From EU ETS," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(6), pages 3538-3570, September.
    13. Zhou, Yuqin & Wu, Shan & Zhang, Zeyi, 2022. "Multidimensional risk spillovers among carbon, energy and nonferrous metals markets: Evidence from the quantile VAR network," Energy Economics, Elsevier, vol. 114(C).
    14. Álvarez-Diez, Susana & Baixauli-Soler, J. Samuel & Lozano-Reina, Gabriel & Rodríguez-Linares Rey, Diego, 2025. "Block connectedness between the EU-ETS and corporate returns: Evidence from high- and low-emission firms," Journal of Commodity Markets, Elsevier, vol. 40(C).
    15. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Noman, Ambreen, 2021. "The volatility connectedness of the EU carbon market with commodity and financial markets in time- and frequency-domain: The role of the U.S. economic policy uncertainty," Resources Policy, Elsevier, vol. 74(C).
    16. Yi Yao & Lixin Tian & Guangxi Cao, 2022. "The Information Spillover among the Carbon Market, Energy Market, and Stock Market: A Case Study of China’s Pilot Carbon Markets," Sustainability, MDPI, vol. 14(8), pages 1-18, April.
    17. Lei, Heng & Xue, Minggao & Ye, Jing, 2024. "The nexus between ReFi, carbon, fossil energy, and clean energy assets: Quantile time–frequency connectedness and portfolio implications," Energy Economics, Elsevier, vol. 132(C).
    18. Li, Xin & Li, Zheng & Su, Chi-Wei & Umar, Muhammad & Shao, Xuefeng, 2022. "Exploring the asymmetric impact of economic policy uncertainty on China's carbon emissions trading market price: Do different types of uncertainty matter?," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    19. Su, Xianfang & Zhao, Yachao, 2025. "Asymmetric time-frequency risk spillovers between the Fourth Industrial Revolution assets and commodity futures: Is economic policy uncertainty a driving factor?," Global Finance Journal, Elsevier, vol. 64(C).
    20. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2022. "Carbon credit futures as an emerging asset: Hedging, diversification and downside risks," Energy Economics, Elsevier, vol. 113(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4274-:d:1651685. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.