IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v45y2024i2p237-260.html
   My bibliography  Save this article

Dependence Structure among Carbon Markets around the World: New Evidence from GARCH-Copula Analysis

Author

Listed:
  • Karishma Ansaram
  • Paolo Mazza

Abstract

In this paper, we investigate the dependence structure among carbon markets globally through different copulas. The analysis examines the relationship between carbon prices being traded across different emission trading systems (ETS) worldwide. The novelty of our approach lies in assessing carbon allowances for both futures and spot prices across all the key carbon markets as well as the three Chinese carbon markets for the period from 2011 to 2019 for future prices and the period from 2015 to 2020 for spot prices. The results demonstrate an asymmetric relationship between most carbon markets. A low tail dependence was observed between the European Union ETS and Regional Greenhouse Gas Initiative ETS, California and Quebec carbon markets, while higher tail dependence was found in the Asian carbon markets. Furthermore, carbon markets that have linkage agreements, ongoing cooperation or are geographically close tend to have positive and higher tail dependence. Our findings suggest the formation of regional carbon clubs based on the dependence structure.

Suggested Citation

  • Karishma Ansaram & Paolo Mazza, 2024. "Dependence Structure among Carbon Markets around the World: New Evidence from GARCH-Copula Analysis," The Energy Journal, , vol. 45(2), pages 237-260, March.
  • Handle: RePEc:sae:enejou:v:45:y:2024:i:2:p:237-260
    DOI: 10.5547/01956574.45.2.kans
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/01956574.45.2.kans
    Download Restriction: no

    File URL: https://libkey.io/10.5547/01956574.45.2.kans?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
    ---><---

    References listed on IDEAS

    as
    1. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    2. repec:dau:papers:123456789/4237 is not listed on IDEAS
    3. repec:dau:papers:123456789/6790 is not listed on IDEAS
    4. Karan Capoor & Philippe Ambrosi, "undated". "State and Trends of the Carbon Market 2007," World Bank Publications - Reports 13407, The World Bank Group.
    5. Richard Schmalensee & Robert N. Stavins, 2017. "Lessons Learned from Three Decades of Experience with Cap and Trade," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 11(1), pages 59-79.
    6. Hege Westskog, 1996. "Market Power in a System of Tradeable CO2 Quotas," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 85-103.
    7. Don Bredin and John Parsons, 2016. "Why is Spot Carbon so Cheap and Future Carbon so Dear? The Term Structure of Carbon Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    8. Julien Chevallier, 2012. "Time-varying correlations in oil, gas and CO 2 prices: an application using BEKK, CCC and DCC-MGARCH models," Applied Economics, Taylor & Francis Journals, vol. 44(32), pages 4257-4274, November.
    9. Kojadinovic, Ivan & Yan, Jun, 2010. "Modeling Multivariate Distributions with Continuous Margins Using the copula R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i09).
    10. Yu, Lean & Zha, Rui & Stafylas, Dimitrios & He, Kaijian & Liu, Jia, 2020. "Dependences and volatility spillovers between the oil and stock markets: New evidence from the copula and VAR-BEKK-GARCH models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    11. Julien Chevallier, 2011. "Anticipating correlations between EUAs and CERs: a Dynamic Conditional Correlation GARCH model," Economics Bulletin, AccessEcon, vol. 31(1), pages 255-272.
    12. Vlad-Cosmin Bulai & Alexandra Horobet & Oana Cristina Popovici & Lucian Belascu & Sofia Adriana Dumitrescu, 2021. "A VaR-Based Methodology for Assessing Carbon Price Risk across European Union Economic Sectors," Energies, MDPI, vol. 14(24), pages 1-21, December.
    13. Rolf Golombek & Jan Braten, 1994. "Incomplete International Climate Agreements: Optimal Carbon Taxes, Market Failures and Welfare Effects," The Energy Journal, , vol. 15(4), pages 141-165, October.
    14. Julien Chevallier, 2010. "A Note on Cointegrating and Vector Autoregressive Relationships between CO2 allowances spot and futures prices," Economics Bulletin, AccessEcon, vol. 30(2), pages 1564-1584.
    15. repec:dau:papers:123456789/5441 is not listed on IDEAS
    16. 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.
    17. repec:wbk:wboper:13406 is not listed on IDEAS
    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. Karishma Ansaram & Paolo Mazza, 2022. "Dependence structure among carbon markets around the world: New evidence from GARCH-copula analysis," Working Papers 2022-ACF-03, IESEG School of Management.
    2. Vellachami, Sanggetha & Hasanov, Akram Shavkatovich & Brooks, Robert, 2023. "Risk transmission from the energy markets to the carbon market: Evidence from the recursive window approach," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2022. "Spillovers and diversification benefits between oil futures and ASEAN stock markets," Resources Policy, Elsevier, vol. 79(C).
    4. Nguyen, Hoang & Virbickaitė, Audronė, 2023. "Modeling stock-oil co-dependence with Dynamic Stochastic MIDAS Copula models," Energy Economics, Elsevier, vol. 124(C).
    5. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    6. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "Energy prices and CO2 emission allowance prices: A quantile regression approach," Energy Policy, Elsevier, vol. 70(C), pages 201-206.
    7. Zhao, Lili & Wen, Fenghua & Wang, Xiong, 2020. "Interaction among China carbon emission trading markets: Nonlinear Granger causality and time-varying effect," Energy Economics, Elsevier, vol. 91(C).
    8. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
    9. Koop, Gary & Tole, Lise, 2013. "Modeling the relationship between European carbon permits and certified emission reductions," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 166-181.
    10. Feng, Yusen & Wang, Gang-Jin & Zhu, You & Xie, Chi, 2023. "Systemic risk spillovers and the determinants in the stock markets of the Belt and Road countries," Emerging Markets Review, Elsevier, vol. 55(C).
    11. Friedrich, Marina & Mauer, Eva-Maria & Pahle, Michael & Tietjen, Oliver, 2020. "From fundamentals to financial assets: the evolution of understanding price formation in the EU ETS," EconStor Preprints 196150, ZBW - Leibniz Information Centre for Economics, revised 2020.
    12. Reboredo, Juan C. & Ugando, Mikel, 2015. "Downside risks in EU carbon and fossil fuel markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 111(C), pages 17-35.
    13. 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.
    14. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
    15. Zhu, Pengfei & Tang, Yong & Wei, Yu & Lu, Tuantuan, 2021. "Multidimensional risk spillovers among crude oil, the US and Chinese stock markets: Evidence during the COVID-19 epidemic," Energy, Elsevier, vol. 231(C).
    16. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," Working Papers halshs-01148746, HAL.
    17. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Modeling the frequency dynamics of spillovers and connectedness between crude oil and MENA stock markets with portfolio implications," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 397-419.
    18. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    19. Selmi, Refk & Hammoudeh, Shawkat & Kasmaoui, Kamal & Sousa, Ricardo M. & Errami, Youssef, 2022. "The dual shocks of the COVID-19 and the oil price collapse: A spark or a setback for the circular economy?," Energy Economics, Elsevier, vol. 109(C).
    20. Song, Zhi & Mukherjee, Amitava & Zhang, Jiujun, 2021. "Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment," European Journal of Operational Research, Elsevier, vol. 289(1), pages 177-196.

    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:sae:enejou:v:45:y:2024:i:2:p:237-260. 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: SAGE Publications (email available below). General contact details of provider: .

    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.