IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i19p6820-d1248092.html
   My bibliography  Save this article

Risk Spillovers between China’s Carbon and Energy Markets

Author

Listed:
  • Qianrui Hwang

    (College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Min Yao

    (College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Shugang Li

    (College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Fang Wang

    (Ningxia Coal Industry Co., Ltd. of China National Energy Group, Ningxia Hui Nationality Autonomous Region, Yinchuan 750011, China)

  • Zhenmin Luo

    (College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Zheng Li

    (College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Tongshuang Liu

    (College of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China)

Abstract

In recent years, with the intensification of global warming and the greenhouse effect, the global consensus has focused on efficient, clean, low-carbon, and green development as a means of achieving new economic growth. China, as a major carbon emitter, has been at the forefront of efforts to reduce carbon emissions. The establishment of the carbon emissions trading market, commonly known as the “carbon market”, provides an economic solution for reducing carbon emissions in both the carbon and energy markets. As China’s carbon market continues to grow rapidly, fluctuations in the energy or carbon markets caused by information shocks can easily spread between the two markets, leading to increased interconnectedness. Moreover, the spillover effect of the volatility between China’s carbon market and energy market is not constant, and the intensity and direction of this effect vary depending on different market volatility levels and periods. Therefore, it is crucial to conduct a comprehensive study on the characteristics of the volatility spillover effect between China’s carbon market and energy market and to fully understand the mechanism of energy regulation on carbon prices. This research will have significant practical implications for promoting the establishment of a well-functioning internal price transmission mechanism between China’s carbon market and energy market. This study took the risk spillover between the carbon market and energy market as the research object and systematically combed through its pricing mechanism and spillover impact. Through constructing the DY overflow index model based on a VAR model and generalized variance decomposition method, this study explored the linkage between China’s carbon and energy markets, i.e., the linkage of price fluctuations between China’s energy and carbon markets, as well as the time-varying nature of inter-market spillovers, and provides suggestions on the risk control of price fluctuations between the carbon and energy markets.

Suggested Citation

  • Qianrui Hwang & Min Yao & Shugang Li & Fang Wang & Zhenmin Luo & Zheng Li & Tongshuang Liu, 2023. "Risk Spillovers between China’s Carbon and Energy Markets," Energies, MDPI, vol. 16(19), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6820-:d:1248092
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/19/6820/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/19/6820/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fei Fan & Dailin Cao & Ning Ma, 2020. "Is Improvement of Innovation Efficiency Conducive to Haze Governance? Empirical Evidence from 283 Chinese Cities," IJERPH, MDPI, vol. 17(17), pages 1-20, August.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Fei Fan & Shangze Dai & Keke Zhang & Haiqian Ke, 2021. "Innovation agglomeration and urban hierarchy: evidence from Chinese cities," Applied Economics, Taylor & Francis Journals, vol. 53(54), pages 6300-6318, November.
    4. Fei Fan & Huan Lian & Song Wang, 2020. "Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities," Growth and Change, Wiley Blackwell, vol. 51(1), pages 440-463, March.
    5. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2016. "Risk spillovers across the energy and carbon markets and hedging strategies for carbon risk," Energy Economics, Elsevier, vol. 54(C), pages 159-172.
    6. Reddy, V. Ratna & Behera, Bhagirath, 2006. "Impact of water pollution on rural communities: An economic analysis," Ecological Economics, Elsevier, vol. 58(3), pages 520-537, June.
    7. Shuai Liu & Fei Fan & Jianqing Zhang, 2019. "Are Small Cities More Environmentally Friendly? An Empirical Study from China," IJERPH, MDPI, vol. 16(5), pages 1-16, February.
    8. Haichao Yu & Yan Liu & Chengliang Liu & Fei Fan, 2018. "Spatiotemporal Variation and Inequality in China’s Economic Resilience across Cities and Urban Agglomerations," Sustainability, MDPI, vol. 10(12), pages 1-19, December.
    9. Haiqian Ke & Wenyi Yang & Xiaoyang Liu & Fei Fan, 2020. "Does Innovation Efficiency Suppress the Ecological Footprint? Empirical Evidence from 280 Chinese Cities," IJERPH, MDPI, vol. 17(18), pages 1-23, September.
    10. Song Wang & Jiexin Wang & Chenqi Wei & Xueli Wang & Fei Fan, 2021. "Collaborative innovation efficiency: From within cities to between cities—Empirical analysis based on innovative cities in China," Growth and Change, Wiley Blackwell, vol. 52(3), pages 1330-1360, September.
    11. Jing Xie & Qi Sun & Shaohong Wang & Xiaoping Li & Fei Fan, 2020. "Does Environmental Regulation Affect Export Quality? Theory and Evidence from China," IJERPH, MDPI, vol. 17(21), pages 1-23, November.
    12. Roman V. Klyuev & Irbek D. Morgoev & Angelika D. Morgoeva & Oksana A. Gavrina & Nikita V. Martyushev & Egor A. Efremenkov & Qi Mengxu, 2022. "Methods of Forecasting Electric Energy Consumption: A Literature Review," Energies, MDPI, vol. 15(23), pages 1-33, November.
    13. Bekele, Wagayehu & Drake, Lars, 2003. "Soil and water conservation decision behavior of subsistence farmers in the Eastern Highlands of Ethiopia: a case study of the Hunde-Lafto area," Ecological Economics, Elsevier, vol. 46(3), pages 437-451, October.
    14. 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.
    15. 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.
    16. Wang, Yudong & Guo, Zhuangyue, 2018. "The dynamic spillover between carbon and energy markets: New evidence," Energy, Elsevier, vol. 149(C), pages 24-33.
    17. Zhengwen Wang & Yunxiao Zong & Yuwan Dan & Shi-Jie Jiang, 2021. "Country risk and international trade: evidence from the China-B&R countries," Applied Economics Letters, Taylor & Francis Journals, vol. 28(20), pages 1784-1788, November.
    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. Chen Li & Heng Li & Xionghe Qin, 2022. "Spatial Heterogeneity of Carbon Emissions and Its Influencing Factors in China: Evidence from 286 Prefecture-Level Cities," IJERPH, MDPI, vol. 19(3), pages 1-29, January.
    2. Jianwei Zhang & Heng Li & Guoxin Jiao & Jiayi Wang & Jingjing Li & Mengzhen Li & Haining Jiang, 2022. "Spatial Pattern of Technological Innovation in the Yangtze River Delta Region and Its Impact on Water Pollution," IJERPH, MDPI, vol. 19(12), pages 1-20, June.
    3. Min Qian & Zhenpeng Cheng & Zhengwen Wang & Dingyi Qi, 2022. "What Affects Rural Ecological Environment Governance Efficiency? Evidence from China," IJERPH, MDPI, vol. 19(10), pages 1-19, May.
    4. Jie Fan & Zhuo Shen & Zhengwen Wang, 2022. "The Threshold Effect of Urban Levels on Environmental Collaborative Governance: An Empirical Analysis from Chinese Cities," IJERPH, MDPI, vol. 19(7), pages 1-11, March.
    5. Ning Ma & Puyu Liu & Yadong Xiao & Hengyun Tang & Jianqing Zhang, 2022. "Can Green Technological Innovation Reduce Hazardous Air Pollutants?—An Empirical Test Based on 283 Cities in China," IJERPH, MDPI, vol. 19(3), pages 1-20, January.
    6. Zuoming Liu & Changbo Qiu & Min Sun & Dongmin Zhang, 2022. "Environmental Performance Evaluation of Key Polluting Industries in China—Taking the Power Industry as an Example," IJERPH, MDPI, vol. 19(12), pages 1-21, June.
    7. Jing Ma & Dan Liu & Zhengwen Wang, 2023. "Sponge City Construction and Urban Economic Sustainable Development: An Ecological Philosophical Perspective," IJERPH, MDPI, vol. 20(3), pages 1-17, January.
    8. Juan Hu & Chengjin Ma & Chen Li, 2022. "Can Green Innovation Improve Regional Environmental Carrying Capacity? An Empirical Analysis from China," IJERPH, MDPI, vol. 19(20), pages 1-15, October.
    9. Jianqing Zhang & Haichao Yu & Keke Zhang & Liang Zhao & Fei Fan, 2021. "Can Innovation Agglomeration Reduce Carbon Emissions? Evidence from China," IJERPH, MDPI, vol. 18(2), pages 1-24, January.
    10. Yunling Ye & Sheng Ye & Haichao Yu, 2021. "Can Industrial Collaborative Agglomeration Reduce Haze Pollution? City-Level Empirical Evidence from China," IJERPH, MDPI, vol. 18(4), pages 1-22, February.
    11. Liang Zhao & Lifei Xu & Ling Li & Jing Hu & Lin Mu, 2022. "Can Inbound Tourism Improve Regional Ecological Efficiency? An Empirical Analysis from China," IJERPH, MDPI, vol. 19(19), pages 1-19, September.
    12. Lili Yang & Ning Ma, 2022. "Empirical Study on the Influence of Urban Environmental Industrial Structure Optimization on Ecological Landscape Greening Construction," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    13. Wenyi Yang & Xueli Wang & Keke Zhang & Zikan Ke, 2020. "COVID-19, Urbanization Pattern and Economic Recovery: An Analysis of Hubei, China," IJERPH, MDPI, vol. 17(24), pages 1-21, December.
    14. Hoque, Mohammad Enamul & Soo-Wah, Low & Billah, Mabruk, 2023. "Time-frequency connectedness and spillover among carbon, climate, and energy futures: Determinants and portfolio risk management implications," Energy Economics, Elsevier, vol. 127(PB).
    15. Liang Zhao & Liangyu Chen, 2022. "Research on the Impact of Government Environmental Information Disclosure on Green Total Factor Productivity: Empirical Experience from Chinese Province," IJERPH, MDPI, vol. 19(2), pages 1-20, January.
    16. Haiqian Ke & Bo Yang & Shangze Dai, 2022. "Does Intensive Land Use Contribute to Energy Efficiency?—Evidence Based on a Spatial Durbin Model," IJERPH, MDPI, vol. 19(9), pages 1-17, April.
    17. 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).
    18. Wei, Yu & Zhang, Yaojie & Wang, Yudong, 2022. "Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent," International Review of Financial Analysis, Elsevier, vol. 81(C).
    19. 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).
    20. 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).

    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:19:p:6820-:d:1248092. 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.