IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i9p5217-d801797.html
   My bibliography  Save this article

Co-Movement between Carbon Prices and Energy Prices in Time and Frequency Domains: A Wavelet-Based Analysis for Beijing Carbon Emission Trading System

Author

Listed:
  • Rundong Luo

    (Business School, Shandong University, Weihai 264209, China)

  • Yan Li

    (Business School, Shandong University, Weihai 264209, China)

  • Zhicheng Wang

    (Business School, Shandong University, Weihai 264209, China)

  • Mengjiao Sun

    (Business School, Shandong University, Weihai 264209, China)

Abstract

This study aims to investigate the co-movement and lead–lag relationship between carbon prices and energy prices in the time–frequency domain in the carbon emission trading system (ETS) of Beijing. Based on wavelet analysis method, this study examines the weekly data on oil and natural gas prices and carbon prices in Beijing ETS from its establishment in November 2013 to April 2019. Empirical results show the following important findings: (1) Carbon and natural gas prices are mainly negatively correlated, with natural gas prices occupying a leading position in the 12–20 weeks frequency band, indicating that the increase (decrease) of natural gas price will lead to the decrease (increase) of carbon price; (2) carbon and oil prices show an unstable dependence relationship, and their leadership position in the market constantly changes. The partial wavelet coherency and partial phase differences vary greatly in different time–frequency domains, indicating that there is no stable coherency between oil prices and carbon prices. The estimation results prove the existence of coherency between the carbon and energy prices in the Beijing ETS. The research findings of this paper provide quantifiable references for investors to achieve risk control in asset allocation and investment portfolio in the ETS market.

Suggested Citation

  • Rundong Luo & Yan Li & Zhicheng Wang & Mengjiao Sun, 2022. "Co-Movement between Carbon Prices and Energy Prices in Time and Frequency Domains: A Wavelet-Based Analysis for Beijing Carbon Emission Trading System," IJERPH, MDPI, vol. 19(9), pages 1-15, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5217-:d:801797
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/9/5217/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/9/5217/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hintermann, Beat, 2010. "Allowance price drivers in the first phase of the EU ETS," Journal of Environmental Economics and Management, Elsevier, vol. 59(1), pages 43-56, January.
    2. Bento, Nuno & Gianfrate, Gianfranco, 2020. "Determinants of internal carbon pricing," Energy Policy, Elsevier, vol. 143(C).
    3. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "What explain the short-term dynamics of the prices of CO2 emissions?," Energy Economics, Elsevier, vol. 46(C), pages 122-135.
    4. Vacha, Lukas & Barunik, Jozef, 2012. "Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis," Energy Economics, Elsevier, vol. 34(1), pages 241-247.
    5. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2017. "Wavelet-based test of co-movement and causality between oil and renewable energy stock prices," Energy Economics, Elsevier, vol. 61(C), pages 241-252.
    6. Zhu, Bangzhu & Ye, Shunxin & Han, Dong & Wang, Ping & He, Kaijian & Wei, Yi-Ming & Xie, Rui, 2019. "A multiscale analysis for carbon price drivers," Energy Economics, Elsevier, vol. 78(C), pages 202-216.
    7. Raphael Calel & Antoine Dechezleprêtre, 2016. "Environmental Policy and Directed Technological Change: Evidence from the European Carbon Market," The Review of Economics and Statistics, MIT Press, vol. 98(1), pages 173-191, March.
    8. Fan, Ying & Jia, Jun-Jun & Wang, Xin & Xu, Jin-Hua, 2017. "What policy adjustments in the EU ETS truly affected the carbon prices?," Energy Policy, Elsevier, vol. 103(C), pages 145-164.
    9. Christiane Baumeister & Lutz Kilian, 2016. "Forty Years of Oil Price Fluctuations: Why the Price of Oil May Still Surprise Us," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 139-160, Winter.
    10. Wang, Huan & Chen, Wenying, 2019. "Modeling of energy transformation pathways under current policies, NDCs and enhanced NDCs to achieve 2-degree target," Applied Energy, Elsevier, vol. 250(C), pages 549-557.
    11. Wang, Zheng & Zhu, Yanshuo & Zhu, Yongbin & Shi, Ying, 2016. "Energy structure change and carbon emission trends in China," Energy, Elsevier, vol. 115(P1), pages 369-377.
    12. 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).
    13. He, Yongxiu & Wang, Bing & Wang, Jianhui & Xiong, Wei & Xia, Tian, 2013. "Correlation between Chinese and international energy prices based on a HP filter and time difference analysis," Energy Policy, Elsevier, vol. 62(C), pages 898-909.
    14. Huang, Ren & Zhang, Sufang & Wang, Peng, 2022. "Key areas and pathways for carbon emissions reduction in Beijing for the “Dual Carbon” targets," Energy Policy, Elsevier, vol. 164(C).
    15. Chang, Chia-Lin & Mai, Te-Ke & McAleer, Michael, 2019. "Establishing national carbon emission prices for China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 1-16.
    16. Jiang, Jingjing & Xie, Dejun & Ye, Bin & Shen, Bo & Chen, Zhanming, 2016. "Research on China’s cap-and-trade carbon emission trading scheme: Overview and outlook," Applied Energy, Elsevier, vol. 178(C), pages 902-917.
    17. Feng Dong & Ruyin Long & Zhuolin Li & Yuanju Dai, 2016. "Analysis of carbon emission intensity, urbanization and energy mix: evidence from China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(2), pages 1375-1391, June.
    18. 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).
    19. Li, Wei & Sun, Wen & Li, Guomin & Jin, Baihui & Wu, Wen & Cui, Pengfei & Zhao, Guohao, 2018. "Transmission mechanism between energy prices and carbon emissions using geographically weighted regression," Energy Policy, Elsevier, vol. 115(C), pages 434-442.
    20. Yu, Jongmin & Mallory, Mindy L., 2014. "Exchange rate effect on carbon credit price via energy markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 145-161.
    21. Mo, Jian-Lei & Agnolucci, Paolo & Jiang, Mao-Rong & Fan, Ying, 2016. "The impact of Chinese carbon emission trading scheme (ETS) on low carbon energy (LCE) investment," Energy Policy, Elsevier, vol. 89(C), pages 271-283.
    22. Gernot Wagner & Tomas Kåberger & Susanna Olai & Michael Oppenheimer & Katherine Rittenhouse & Thomas Sterner, 2015. "Energy policy: Push renewables to spur carbon pricing," Nature, Nature, vol. 525(7567), pages 27-29, September.
    23. Zeng, Shihong & Nan, Xin & Liu, Chao & Chen, Jiuying, 2017. "The response of the Beijing carbon emissions allowance price (BJC) to macroeconomic and energy price indices," Energy Policy, Elsevier, vol. 106(C), pages 111-121.
    24. Jiang, Wei & Chen, Yunfei, 2022. "The time-frequency connectedness among carbon, traditional/new energy and material markets of China in pre- and post-COVID-19 outbreak periods," Energy, Elsevier, vol. 246(C).
    25. Duan, Kun & Ren, Xiaohang & Shi, Yukun & Mishra, Tapas & Yan, Cheng, 2021. "The marginal impacts of energy prices on carbon price variations: Evidence from a quantile-on-quantile approach," Energy Economics, Elsevier, vol. 95(C).
    26. Sun, Xiaotian & Fang, Wei & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Wu, Tao, 2022. "Complex causalities between the carbon market and the stock markets for energy intensive industries in China," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 404-417.
    27. Li, Mengyu & Weng, Yuyan & Duan, Maosheng, 2019. "Emissions, energy and economic impacts of linking China’s national ETS with the EU ETS," Applied Energy, Elsevier, vol. 235(C), pages 1235-1244.
    28. Batten, Jonathan A. & Maddox, Grace E. & Young, Martin R., 2021. "Does weather, or energy prices, affect carbon prices?," Energy Economics, Elsevier, vol. 96(C).
    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. Liu, Haiying & Pata, Ugur Korkut & Zafar, Muhammad Wasif & Kartal, Mustafa Tevfik & Karlilar, Selin & Caglar, Abdullah Emre, 2023. "Do oil and natural gas prices affect carbon efficiency? Daily evidence from China by wavelet transform-based approaches," Resources Policy, Elsevier, vol. 85(PB).
    2. Qiao, Sen & Dang, Yi Jing & Ren, Zheng Yu & Zhang, Kai Quan, 2023. "The dynamic spillovers among carbon, fossil energy and electricity markets based on a TVP-VAR-SV method," Energy, Elsevier, vol. 266(C).
    3. Maryam Aziz & Muhammad Zeeshan Shaukat & Abdul Aziz Khan Niazi & Abdul Basit & Tehmina Fiaz Qazi, 2023. "Wavelet Analysis of CO2 Emissions’ Co-movement: An Investigation of Lead–lag Effect among Emerging Asian Economies," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 9(3), pages 36-51.
    4. Rao, Amar & Lucey, Brian & Kumar, Satish, 2023. "Climate risk and carbon emissions: Examining their impact on key energy markets through asymmetric spillovers," Energy Economics, Elsevier, vol. 126(C).

    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. 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.
    2. Su, Chi Wei & Wei, Shenkai & Wang, Yan & Tao, Ran, 2024. "How does climate policy uncertainty affect the carbon market?," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    3. Chen, Linfei & Zhao, Xuefeng, 2024. "A multiscale and multivariable differentiated learning for carbon price forecasting," Energy Economics, Elsevier, vol. 131(C).
    4. Xu, Yingying & Salem, Sultan, 2021. "Explosive behaviors in Chinese carbon markets: are there price bubbles in eight pilots?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    5. Xu, Jia & Tan, Xiujie & He, Gang & Liu, Yu, 2019. "Disentangling the drivers of carbon prices in China's ETS pilots — An EEMD approach," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 1-9.
    6. Wang, Xiong & Li, Jingyao & Ren, Xiaohang & Bu, Ruijun & Jawadi, Fredj, 2023. "Economic policy uncertainty and dynamic correlations in energy markets: Assessment and solutions," Energy Economics, Elsevier, vol. 117(C).
    7. Wenjun Chu & Shanglei Chai & Xi Chen & Mo Du, 2020. "Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots," Sustainability, MDPI, vol. 12(14), pages 1-19, July.
    8. 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).
    9. Ding, Qian & Huang, Jianbai & Zhang, Hongwei, 2022. "Time-frequency spillovers among carbon, fossil energy and clean energy markets: The effects of attention to climate change," International Review of Financial Analysis, Elsevier, vol. 83(C).
    10. Liudmila Reshetnikova & Natalia Boldyreva & Anton Devyatkov & Zhanna Pisarenko & Danila Ovechkin, 2023. "Carbon Pricing in Current Global Institutional Changes," Sustainability, MDPI, vol. 15(4), pages 1-19, February.
    11. Dai, Xingyu & Xiao, Ling & Wang, Qunwei & Dhesi, Gurjeet, 2021. "Multiscale interplay of higher-order moments between the carbon and energy markets during Phase III of the EU ETS," Energy Policy, Elsevier, vol. 156(C).
    12. Lovcha, Yuliya & Perez-Laborda, Alejandro & Sikora, Iryna, 2022. "The determinants of CO2 prices in the EU emission trading system," Applied Energy, Elsevier, vol. 305(C).
    13. Tang, Chun & Liu, Xiaoxing & Chen, Guangkun, 2023. "The spillover effects in the “Energy – Carbon – Stock” system – Evidence from China," Energy, Elsevier, vol. 278(PA).
    14. 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).
    15. Yaqi Wu & Chen Zhang & Po Yun & Dandan Zhu & Wei Cao & Zulfiqar Ali Wagan, 2021. "Time–frequency analysis of the interaction mechanism between European carbon and crude oil markets," Energy & Environment, , vol. 32(7), pages 1331-1357, November.
    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. Zhang, Shengling & Wang, Yao & Hao, Yu & Liu, Zhiwei, 2021. "Shooting two hawks with one arrow: Could China's emission trading scheme promote green development efficiency and regional carbon equality?," Energy Economics, Elsevier, vol. 101(C).
    18. Xiaojian Su & Chao Deng, 2019. "The heterogeneous effects of exchange rate and stock market on CO2 emission allowance price in China: A panel quantile regression approach," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-11, August.
    19. 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).
    20. Ren, Xiaohang & Li, Yiying & yan, Cheng & Wen, Fenghua & Lu, Zudi, 2022. "The interrelationship between the carbon market and the green bonds market: Evidence from wavelet quantile-on-quantile method," Technological Forecasting and Social Change, Elsevier, vol. 179(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:jijerp:v:19:y:2022:i:9:p:5217-:d:801797. 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.