IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i14p5578-d1201058.html
   My bibliography  Save this article

Dynamic Spillovers between Carbon Price and Power Sector Returns in China: A Network-Based Analysis before and after Launching National Carbon Emissions Trading Market

Author

Listed:
  • Jing Deng

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Yujie Zheng

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Yun Zhang

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Cheng Liu

    (Research Centre for the Two Mountains Theory and Sustainable Development, Beijing Forestry University, Beijing 100083, China)

  • Huanxue Pan

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

Abstract

The launch of the national carbon emissions trading (CET) market has resulted in a closer relationship between China’s CET market and its electricity market, making it easy for risks to transfer between markets. This paper utilizes data from China’s CET market and electric power companies between 2017 and 2023 to construct the spillover index model of Diebold and Yilmaz, the frequency-domain spillover approach developed by Barun’ik and Křehl’ik, and a minimum spanning tree model. The comparison is made before and after the launch of the national CET market. Subsequently, this paper examines the market spillover effects, as well as the static and dynamic properties of network structures, considering both the time domain and frequency-domain perspectives. The research findings suggest the following: (1) There is a strong risk spillover effect between China’s CET market and the stock prices of electric power companies; (2) There is asymmetry in the paired spillover effects between carbon trading pilot markets and the national CET market, and differences exist in the impact of risk spillovers from power companies between the two; (3) The results of the MST model indicate that the risk contagion efficiency is higher in the regional CET pilot stage compared to the national CET market launch stage, with significant changes occurring in key nodes before and after the launch of the national CET market; (4) Both the dynamic spillover index and the standardized tree length results demonstrate that crisis events can worsen the risk contagion between markets. Besides offering a theoretical foundation and empirical evidence for the development of China’s CET and electricity markets, the findings of this paper can provide recommendations for financial market participants as well.

Suggested Citation

  • Jing Deng & Yujie Zheng & Yun Zhang & Cheng Liu & Huanxue Pan, 2023. "Dynamic Spillovers between Carbon Price and Power Sector Returns in China: A Network-Based Analysis before and after Launching National Carbon Emissions Trading Market," Energies, MDPI, vol. 16(14), pages 1-27, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5578-:d:1201058
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/14/5578/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/14/5578/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qiyun Cheng & Huiting Qiao & Yimiao Gu & Zhenxi Chen, 2023. "Price Dynamics and Interactions between the Chinese and European Carbon Emission Trading Markets," Energies, MDPI, vol. 16(4), pages 1-12, February.
    2. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    3. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    4. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    5. Zhu, Bangzhu & Han, Dong & Chevallier, Julien & Wei, Yi-Ming, 2017. "Dynamic multiscale interactions between European carbon and electricity markets during 2005–2016," Energy Policy, Elsevier, vol. 107(C), pages 309-322.
    6. 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).
    7. Zhao, Yihang & Zhou, Zhenxi & Zhang, Kaiwen & Huo, Yaotong & Sun, Dong & Zhao, Huiru & Sun, Jingqi & Guo, Sen, 2023. "Research on spillover effect between carbon market and electricity market: Evidence from Northern Europe," Energy, Elsevier, vol. 263(PF).
    8. Rehman, Mobeen Ur & Shahzad, Syed Jawad Hussain & Ahmad, Nasir & Vo, Xuan Vinh, 2021. "Dependence among metals and mining companies of the US and Europe during normal and crises periods," Resources Policy, Elsevier, vol. 73(C).
    9. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    10. Gang-Jin Wang & Chi Xie & Shou Chen, 2017. "Multiscale correlation networks analysis of the US stock market: a wavelet analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(3), pages 561-594, October.
    11. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    12. 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.
    13. Yanbin Li & Dan Nie & Bingkang Li & Xiyu Li, 2020. "The Spillover Effect between Carbon Emission Trading (CET) Price and Power Company Stock Price in China," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    14. Deeney, Peter & Cummins, Mark & Dowling, Michael & Smeaton, Alan F., 2016. "Influences from the European Parliament on EU emissions prices," Energy Policy, Elsevier, vol. 88(C), pages 561-572.
    15. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2023. "Dynamic spillovers between clean energy and non-ferrous metals markets in China: A network-based analysis during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 83(C).
    16. Mo, Jian-Lei & Zhu, Lei & Fan, Ying, 2012. "The impact of the EU ETS on the corporate value of European electricity corporations," Energy, Elsevier, vol. 45(1), pages 3-11.
    17. Zeng, Zhi-Jian & Xie, Chi & Yan, Xin-Guo & Hu, Jue & Mao, Zhou, 2016. "Are stock market networks non-fractal? Evidence from New York Stock Exchange," Finance Research Letters, Elsevier, vol. 17(C), pages 97-102.
    18. Fang Zhang & Hong Fang & Xu Wang, 2018. "Impact of Carbon Prices on Corporate Value: The Case of China’s Thermal Listed Enterprises," Sustainability, MDPI, vol. 10(9), pages 1-14, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li Zhang & Hao Li & Zhumeng Song & Wei Shi & Wenxiang Sheng, 2024. "Measurement of Carbon Total Factor Productivity in the Context of Carbon–Electricity Market Collaboration: An Application of Biennial Luenberger Productivity Index," Energies, MDPI, vol. 17(5), pages 1-19, March.

    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. Yanbin Li & Dan Nie & Bingkang Li & Xiyu Li, 2020. "The Spillover Effect between Carbon Emission Trading (CET) Price and Power Company Stock Price in China," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    2. Jun Long & Xianghui Yuan & Liwei Jin & Chencheng Zhao, 2024. "Connectedness and risk spillover in China's commodity futures sectors," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(5), pages 784-802, May.
    3. Ye, Liping & Geng, Jiang-Bo, 2021. "Measuring the connectedness of global health sector stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    4. Wan, Jieru & Yin, Libo & Wu, You, 2024. "Return and volatility connectedness across global ESG stock indexes: Evidence from the time-frequency domain analysis," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 397-428.
    5. Mengli Xia & Zhang-Hangjian Chen & Piao Wang, 2022. "Dynamic Risk Spillover Effect between the Carbon and Stock Markets under the Shocks from Exogenous Events," Energies, MDPI, vol. 16(1), pages 1-15, December.
    6. Gabauer, David & Chatziantoniou, Ioannis & Stenfors, Alexis, 2023. "Model-free connectedness measures," Finance Research Letters, Elsevier, vol. 54(C).
    7. Cagli, Efe Caglar, 2023. "The volatility spillover between battery metals and future mobility stocks: Evidence from the time-varying frequency connectedness approach," Resources Policy, Elsevier, vol. 86(PA).
    8. Noureddine Benlagha & Wael Hemrit, 2022. "Does economic policy uncertainty matter to explain connectedness within the international sovereign bond yields?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(1), pages 1-21, January.
    9. Apergis, Nicholas & Baruník, Jozef & Lau, Marco Chi Keung, 2017. "Good volatility, bad volatility: What drives the asymmetric connectedness of Australian electricity markets?," Energy Economics, Elsevier, vol. 66(C), pages 108-115.
    10. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    11. Dang, Tam Hoang Nhat & Balli, Faruk & Balli, Hatice Ozer & Gabauer, David & Nguyen, Thi Thu Ha, 2024. "Sectoral uncertainty spillovers in emerging markets: A quantile time–frequency connectedness approach," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 121-139.
    12. Shang, Jin & Hamori, Shigeyuki, 2021. "Do crude oil prices and the sentiment index influence foreign exchange rates differently in oil-importing and oil-exporting countries? A dynamic connectedness analysis," Resources Policy, Elsevier, vol. 74(C).
    13. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    14. Costantini, Mauro & Maaitah, Ahmad & Mishra, Tapas & Sousa, Ricardo M., 2023. "Bitcoin market networks and cyberattacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    15. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    16. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    17. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    18. Kurka, Josef, 2019. "Do cryptocurrencies and traditional asset classes influence each other?," Finance Research Letters, Elsevier, vol. 31(C), pages 38-46.
    19. Lien, Donald & Lee, Geul & Yang, Li & Zhang, Yuyin, 2018. "Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 187-201.
    20. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).

    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:jeners:v:16:y:2023:i:14:p:5578-:d:1201058. 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.