IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v52y2018i1d10.1007_s10614-017-9664-x.html
   My bibliography  Save this article

Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market

Author

Listed:
  • Bangzhu Zhu

    (Jinan University)

  • Shujiao Ma

    (Hunan University)

  • Rui Xie

    (Hunan University)

  • Julien Chevallier

    (IPAG Business School)

  • Yi-Ming Wei

    (Beijing Institute of Technology)

Abstract

Exploring the effect of an economic crisis on the carbon market can be propitious to understand the formation mechanisms of carbon pricing, and prompt the healthy development of the carbon market. Through the ensemble empirical mode decomposition (EEMD), a multiscale event analysis approach is proposed for exploring the effect of an economic crisis on the European carbon market. Firstly, we determine the appropriate carbon price data of the estimation and event windows to embody the impact of the interested economic crisis on carbon market. Secondly, we use the EEMD to decompose the carbon price into simple modes. Hilbert spectra are adopted to identify the main mode, which is then used to estimate the strength of an extreme event on the carbon price. Thirdly, we perform a multiscale analysis that the composition of the low-frequency modes and residue is identifying as the main mode to capture the strength of the interested economic crisis on the carbon market, and the high-frequency modes are identifying as the normal market fluctuations with a little short-term effect on the carbon market. Finally, taking the 2007–2009 global financial crisis and 2009–2013 European debt crisis as two cases, the empirical results show that contrasted with the traditional intervention analysis and event analysis with the principle of “one divides into two”, the proposed method can capture the influences of an economic crisis on the carbon market at various timescales in a nonlinear framework.

Suggested Citation

  • Bangzhu Zhu & Shujiao Ma & Rui Xie & Julien Chevallier & Yi-Ming Wei, 2018. "Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 105-121, June.
  • Handle: RePEc:kap:compec:v:52:y:2018:i:1:d:10.1007_s10614-017-9664-x
    DOI: 10.1007/s10614-017-9664-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-017-9664-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10614-017-9664-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Xun & Lai, K.K. & Wang, Shou-Yang, 2008. "A new approach for crude oil price analysis based on Empirical Mode Decomposition," Energy Economics, Elsevier, vol. 30(3), pages 905-918, May.
    2. Zhu, Bangzhu & Ma, Shujiao & Chevallier, Julien & Wei, Yiming, 2014. "Modelling the dynamics of European carbon futures price: A Zipf analysis," Economic Modelling, Elsevier, vol. 38(C), pages 372-380.
    3. Bangzhu Zhu & Xuetao Shi & Julien Chevallier & Ping Wang & Yi‐Ming Wei, 2016. "An Adaptive Multiscale Ensemble Learning Paradigm for Nonstationary and Nonlinear Energy Price Time Series Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(7), pages 633-651, November.
    4. Jia, Jun-Jun & Xu, Jin-Hua & Fan, Ying, 2016. "The impact of verified emissions announcements on the European Union emissions trading scheme: A bilaterally modified dummy variable modelling analysis," Applied Energy, Elsevier, vol. 173(C), pages 567-577.
    5. Bangzhu Zhu & Julien Chevallier & Shujiao Ma & Yiming Wei, 2015. "Examining the structural changes of European carbon futures price 2005-2012," Applied Economics Letters, Taylor & Francis Journals, vol. 22(5), pages 335-342, March.
    6. Yu, Lean & Li, Jingjing & Tang, Ling & Wang, Shuai, 2015. "Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach," Energy Economics, Elsevier, vol. 51(C), pages 300-311.
    7. Bangzhu Zhu & Ping Wang & Julien Chevallier & Yiming Wei, 2015. "Carbon Price Analysis Using Empirical Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 195-206, February.
    8. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    9. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "An overview of current research on EU ETS: Evidence from its operating mechanism and economic effect," Applied Energy, Elsevier, vol. 87(6), pages 1804-1814, June.
    10. Alberola, Emilie & Chevallier, Julien & Cheze, Benoi^t, 2008. "Price drivers and structural breaks in European carbon prices 2005-2007," Energy Policy, Elsevier, vol. 36(2), pages 787-797, February.
    11. Bel, Germà & Joseph, Stephan, 2015. "Emission abatement: Untangling the impacts of the EU ETS and the economic crisis," Energy Economics, Elsevier, vol. 49(C), pages 531-539.
    12. Brouwers, Roel & Schoubben, Frederiek & Van Hulle, Cynthia & Van Uytbergen, Steve, 2016. "The initial impact of EU ETS verification events on stock prices," Energy Policy, Elsevier, vol. 94(C), pages 138-149.
    13. A. Craig MacKinlay, 1997. "Event Studies in Economics and Finance," Journal of Economic Literature, American Economic Association, vol. 35(1), pages 13-39, March.
    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. Zhu, Bangzhu & Huang, Liqing & Yuan, Lili & Ye, Shunxin & Wang, Ping, 2020. "Exploring the risk spillover effects between carbon market and electricity market: A bidimensional empirical mode decomposition based conditional value at risk approach," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 163-175.
    2. Xueqing Kang & Farman Ullah Khan & Raza Ullah & Muhammad Arif & Shams Ur Rehman & Farid Ullah, 2021. "Does Foreign Direct Investment Influence Renewable Energy Consumption? Empirical Evidence from South Asian Countries," Energies, MDPI, vol. 14(12), pages 1-15, June.
    3. Zhang, Dingxuan & Sun, Yuying & Duan, Hongbo & Hong, Yongmiao & Wang, Shouyang, 2023. "Speculation or currency? Multi-scale analysis of cryptocurrencies—The case of Bitcoin," International Review of Financial Analysis, Elsevier, vol. 88(C).
    4. Kai Wu & E Bai & Hejie Zhu & Zhijiang Lu & Hongxin Zhu, 2023. "Can Green Credit Policy Promote the High-Quality Development of China’s Heavily-Polluting Enterprises?," Sustainability, MDPI, vol. 15(11), pages 1-27, May.
    5. 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.
    6. Zhigui Guan & Yuanjun Zhao & Guojing Geng, 2022. "The Risk Early-Warning Model of Financial Operation in Family Farms Based on Back Propagation Neural Network Methods," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1221-1244, December.
    7. Christos Alexakis & Michael Dowling & Konstantinos Eleftheriou & Michael Polemis, 2021. "Textual Machine Learning: An Application to Computational Economics Research," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 369-385, January.
    8. Zhao, Yuhuan & Shi, Qiaoling & li, Hao & Qian, Zhiling & Zheng, Lu & Wang, Song & He, Yizhang, 2022. "Simulating the economic and environmental effects of integrated policies in energy-carbon-water nexus of China," Energy, Elsevier, vol. 238(PA).
    9. Bashir Muhammad & Sher Khan, 2021. "Understanding the relationship between natural resources, renewable energy consumption, economic factors, globalization and CO2 emissions in developed and developing countries," Natural Resources Forum, Blackwell Publishing, vol. 45(2), pages 138-156, May.

    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. Bangzhu Zhu & Shunxin Ye & Kaijian He & Julien Chevallier & Rui Xie, 2019. "Measuring the risk of European carbon market: an empirical mode decomposition-based value at risk approach," Annals of Operations Research, Springer, vol. 281(1), pages 373-395, October.
    2. Bangzhu Zhu & Ping Wang & Julien Chevallier & Yi‐Ming Wei, 2023. "Enriching the value‐at‐risk framework to ensemble empirical mode decomposition with an application to the European carbon market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2975-2988, July.
    3. Fang, Sheng & Lu, Xinsheng & Li, Jianfeng & Qu, Ling, 2018. "Multifractal detrended cross-correlation analysis of carbon emission allowance and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 551-566.
    4. Karpf, Andreas & Mandel, Antoine & Battiston, Stefano, 2018. "Price and network dynamics in the European carbon market," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 103-122.
    5. Jianfeng Guo & Bin Su & Guang Yang & Lianyong Feng & Yinpeng Liu & Fu Gu, 2018. "How Do Verified Emissions Announcements Affect the Comoves between Trading Behaviors and Carbon Prices? Evidence from EU ETS," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    6. 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.
    7. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.
    8. Zhu, Bangzhu & Ye, Shunxin & Wang, Ping & He, Kaijian & Zhang, Tao & Wei, Yi-Ming, 2018. "A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting," Energy Economics, Elsevier, vol. 70(C), pages 143-157.
    9. repec:ipg:wpaper:2014-422 is not listed on IDEAS
    10. repec:ipg:wpaper:2014-552 is not listed on IDEAS
    11. Jianguo Zhou & Xuechao Yu & Xiaolei Yuan, 2018. "Predicting the Carbon Price Sequence in the Shenzhen Emissions Exchange Using a Multiscale Ensemble Forecasting Model Based on Ensemble Empirical Mode Decomposition," Energies, MDPI, vol. 11(7), pages 1-17, July.
    12. Quande Qin & Huangda He & Li Li & Ling-Yun He, 2020. "A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1249-1273, April.
    13. Yue Xu & Dayu Zhai, 2022. "Impact of Changes in Membership on Prices of a Unified Carbon Market: Case Study of the European Union Emissions Trading System," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    14. Chang, Kai & Pei, Ping & Zhang, Chao & Wu, Xin, 2017. "Exploring the price dynamics of CO2 emissions allowances in China's emissions trading scheme pilots," Energy Economics, Elsevier, vol. 67(C), pages 213-223.
    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. Getachew Nigatu, 2016. "Assessing the effects of climate change policy on the volatility of carbon prices in reference to the Great Recession," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(2), pages 200-215, July.
    17. 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.
    18. Tiwari, Aviral K. & Dar, Arif B. & Bhanja, Niyati & Gupta, Rangan, 2016. "A historical analysis of the US stock price index using empirical mode decomposition over 1791-2015," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-15.
    19. Cretí, Anna & Joëts, Marc, 2017. "Multiple bubbles in the European Union Emission Trading Scheme," Energy Policy, Elsevier, vol. 107(C), pages 119-130.
    20. Cao, Guangxi & Xu, Wei, 2016. "Multifractal features of EUA and CER futures markets by using multifractal detrended fluctuation analysis based on empirical model decomposition," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 212-222.
    21. Jin, Xuejun & Zhu, Keer & Yang, Xiaolan & Wang, Shouyang, 2021. "Estimating the reaction of Bitcoin prices to the uncertainty of fiat currency," Research in International Business and Finance, Elsevier, vol. 58(C).
    22. 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.

    More about this item

    Keywords

    European carbon market; Economic crisis; Ensemble empirical mode decomposition; Event analysis; Hilbert transform;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    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:kap:compec:v:52:y:2018:i:1:d:10.1007_s10614-017-9664-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.