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Modelling the Dynamics of Fuel and EU Allowance Prices during Phase 3 of the EU ETS

Author

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  • M. Angeles Carnero

    (Fundamentos del Análisis Económico (FAE), Universidad de Alicante, 03690 Alicante, Spain)

  • Jose Olmo

    (Economics, University of Southampton, Southampton SO17 1BJ, UK)

  • Lorenzo Pascual

    (NEA Newbers Energy Analytics, 28012 Madrid, Spain)

Abstract

This article studies the relationship between the prices of fuel and EU Allowances (EUA) for carbon emissions during Phase 3 of the European Union Emissions Trading System. We find that the forward prices of EUA, coal, gas and Brent oil are jointly determined in equilibrium. The existence of such a long-run relationship entails a permanent-transitory decomposition for the series of EUA and fuel prices that reveals the short- and long-term causal influence of the EUA market in shaping the joint dynamics of fuel prices. This result complements the literature that suggests that EUA prices are driven by the dynamics of fuel prices. Interestingly, we do not find an equilibrium relationship in the spot market. EUA and fuel spot prices are driven by independent unit root processes. The differences between spot and forward markets are attributed to the tradability of forward prices that are used for speculation and hedging in financial markets. In contrast, spot prices are mainly driven by supply and demand in energy markets.

Suggested Citation

  • M. Angeles Carnero & Jose Olmo & Lorenzo Pascual, 2018. "Modelling the Dynamics of Fuel and EU Allowance Prices during Phase 3 of the EU ETS," Energies, MDPI, vol. 11(11), pages 1-23, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3148-:d:182707
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    References listed on IDEAS

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    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. Xing Zhang & Chongchong Zhang & Zhuoqun Wei, 2019. "Carbon Price Forecasting Based on Multi-Resolution Singular Value Decomposition and Extreme Learning Machine Optimized by the Moth–Flame Optimization Algorithm Considering Energy and Economic Factors," Energies, MDPI, vol. 12(22), pages 1-23, November.
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    6. 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.

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