IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v81y2019icp812-821.html
   My bibliography  Save this article

A conditional dependence approach to CO2-energy price relationships

Author

Listed:
  • Chevallier, Julien
  • Khuong Nguyen, Duc
  • Carlos Reboredo, Juan

Abstract

This paper uses the conditional vine copula approach to model the dependence structure between European-based carbon allowances and major energy prices. It makes two central contributions to the related literature. First, we extend the previous works of Reboredo (2013, 2014) by allowing for complete coverage of energy markets including natural gas, coal, and electricity, beyond the carbon-oil dependencies. Second, we simultaneously investigate the multivariate dependence among all variables in the system so that each of them can interact with the others based on a rich variety of bivariate copula functions. The consideration of the electricity market in this context offers the possibility to gauge its influences through the computation of the fuel-switching mechanism. We mainly find that there is a reliable and positive link between coal and gas prices, and between coal and oil prices, with or without the presence of electricity prices, while a weak and positive link is detected between Brent and gas prices. Carbon prices co-move only weakly with energy prices, and their link to oil and gas prices is negative. Moreover, the switch from coal to gas does not occur when the relative price of fuels taking into account carbon costs is assessed. This happens because the fuel-switching mechanism is still more costly than carbon abatement. Our findings remain intact when alternative electricity prices are used.

Suggested Citation

  • Chevallier, Julien & Khuong Nguyen, Duc & Carlos Reboredo, Juan, 2019. "A conditional dependence approach to CO2-energy price relationships," Energy Economics, Elsevier, vol. 81(C), pages 812-821.
    • Handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:812-821
    DOI: 10.1016/j.eneco.2019.05.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319301550
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2019.05.010?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.

    Citations

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


    Cited by:

    1. Lovcha, Yuliya & Pérez Laborda, Àlex & Sikora, Iryna, 2019. "The Determinants of CO2 prices in the EU ETS System," Working Papers 2072/376031, Universitat Rovira i Virgili, Department of Economics.
    2. Pilar Gargallo & Luis Lample & Jesús A. Miguel & Manuel Salvador, 2021. "Co-Movements between Eu Ets and the Energy Markets: A Var-Dcc-Garch Approach," Mathematics, MDPI, vol. 9(15), pages 1-36, July.
    3. 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).
    4. Guo, Li-Yang & Feng, Chao & Yang, Jun, 2022. "Can energy predict the regional prices of carbon emission allowances in China?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    5. 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.
    6. 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).
    7. Saeed, Asif & Chaudhry, Sajid M. & Arif, Ahmed & Ahmed, Rizwan, 2023. "Spillover of energy commodities and inflation in G7 plus Chinese economies," Energy Economics, Elsevier, vol. 127(PA).
    8. Andr s Oviedo-G mez & Sandra Milena Londo o-Hern ndez & Diego Fernando Manotas-Duque, 2023. "Directional Spillover of Fossil Fuels Prices on a Hydrothermal Power Generation Market," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 85-90, January.
    9. 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).
    10. 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).
    11. 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).
    12. 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).
    13. Wei, Yu & Zhang, Jiahao & Chen, Yongfei & Wang, Yizhi, 2022. "The impacts of El Niño-southern oscillation on renewable energy stock markets: Evidence from quantile perspective," Energy, Elsevier, vol. 260(C).
    14. Fan, Shengyue & Zha, Shuai & Zhao, Chenxi & Sizheng, Fangyuan & Li, Meihui, 2022. "Using energy vulnerability to measure distributive injustice in rural heating energy reform: A case study of natural gas replacing bulk coal for heating in Gaocheng District, Hebei Province, China," Ecological Economics, Elsevier, vol. 197(C).
    15. Yeonjeong Lee & Seong-Min Yoon, 2020. "Dynamic Spillover and Hedging among Carbon, Biofuel and Oil," Energies, MDPI, vol. 13(17), pages 1-19, August.
    16. Berrisch, Jonathan & Pappert, Sven & Ziel, Florian & Arsova, Antonia, 2023. "Modeling volatility and dependence of European carbon and energy prices," Finance Research Letters, Elsevier, vol. 52(C).
    17. Jiang, Wei & Chen, Yunfei, 2022. "The time-frequency connectedness among metal, energy and carbon markets pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 77(C).
    18. Dai, Xingyu & Wang, Qunwei & Zha, Donglan & Zhou, Dequn, 2020. "Multi-scale dependence structure and risk contagion between oil, gold, and US exchange rate: A wavelet-based vine-copula approach," Energy Economics, Elsevier, vol. 88(C).
    19. Jonathan Berrisch & Sven Pappert & Florian Ziel & Antonia Arsova, 2022. "Modeling Volatility and Dependence of European Carbon and Energy Prices," Papers 2208.14311, arXiv.org, revised Feb 2023.
    20. 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).
    21. Hanif, Waqas & Arreola Hernandez, Jose & Mensi, Walid & Kang, Sang Hoon & Uddin, Gazi Salah & Yoon, Seong-Min, 2021. "Nonlinear dependence and connectedness between clean/renewable energy sector equity and European emission allowance prices," Energy Economics, Elsevier, vol. 101(C).
    22. Dorota Ciesielska-Maciągowska & Dawid Klimczak & Małgorzata Skrzek-Lubasińska, 2021. "Central and Eastern European CO 2 Market—Challenges of Emissions Trading for Energy Companies," Energies, MDPI, vol. 14(4), pages 1-14, February.
    23. Dou, Yue & Li, Yiying & Dong, Kangyin & Ren, Xiaohang, 2022. "Dynamic linkages between economic policy uncertainty and the carbon futures market: Does Covid-19 pandemic matter?," Resources Policy, Elsevier, vol. 75(C).
    24. Feng Liu & Yu Fu & Weiguo Wang, 2023. "Heterogeneous Effects of China’s Carbon Market on Carbon Emissions—Evidence from a Regression Control Method," Sustainability, MDPI, vol. 16(1), pages 1-20, December.

    More about this item

    Keywords

    Carbon price; Energy markets; Fuel-switching; Vine copula;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    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:eee:eneeco:v:81:y:2019:i:c:p:812-821. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.