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Aviation and the EU ETS: an overview and a data-driven approach for carbon price prediction

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  • Riccardo Colantuono

    (Department of Sciences, Technology and Society, Scuola Universitaria Superiore IUSS Pavia, Pavia, Italy)

  • Riccardo Colantuono

    (Department of Engineering, University of Ferrara, Ferrara, Italy)

  • Massimiliano Mazzanti

    (Department of Economics and Management, University of Ferrara, Ferrara, Italy)

  • Michele Pinelli

    (Department of Engineering, University of Ferrara, Ferrara, Italy)

Abstract

Aviation is generally recognized as one of the most carbon intensive forms of transport. The sector accounts for roughly 2.5% of global CO2 emissions (which would place it as a top-10 emitter if ranked as a country), but this absolute value is of less concern than its accelerated and continuous growth in the last decades. In order to tackle aviation’s environmental impact, in 2012 the sector has been (partially) included in the European Union Emission Trading System (EU ETS), a market-based mitigation mechanism designed to put a price on carbon emissions and create an economic incentive towards their reduction. In the recently announced Fit for 55 legislative package, proposed by the European Commission in order to reach its medium-term environmental objective (a 55% reduction of greenhouse gases emissions by 2030 compared to 1990 levels), a revision of the system is envisaged, reinforcing the rules concerning aviation and making emission mitigation through the system more and more costly in the upcoming years. In light of this, the need for a predictive model to forecast the carbon price is of main importance. Several studies in the literature faced the problem of finding a reliable predictive model for the carbon price, but no one seems to completely satisfy the scientific community, mainly for the complexity of the algorithms and their poor predictive reliability. In this work, after an introductory section exploring the history and the characteristics of aviation’s inclusion in the EU ETS, a literature review of the studies investigating the topic has been carried out. Then, a simple data-driven methodology has been developed by using the dynamic mode decomposition (DMD) algorithm. For this purpose, a freely available set of data containing the daily carbon price since 2015 has been used. The main advantage of this approach is its simplicity and its ability to catch the non-linear dynamics of the phenomena. The presented strategy could inform policy makers at European level and help the industrial and financial sectors in the prediction of the carbon price by using a simple methodology.

Suggested Citation

  • Riccardo Colantuono & Riccardo Colantuono & Massimiliano Mazzanti & Michele Pinelli, 2023. "Aviation and the EU ETS: an overview and a data-driven approach for carbon price prediction," SEEDS Working Papers 0123, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Feb 2023.
    • Handle: RePEc:srt:wpaper:0123
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    References listed on IDEAS

    as
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    2. Anger, Annela, 2010. "Including aviation in the European emissions trading scheme: Impacts on the industry, CO2 emissions and macroeconomic activity in the EU," Journal of Air Transport Management, Elsevier, vol. 16(2), pages 100-105.
    3. Steven L. Brunton & Bingni W. Brunton & Joshua L. Proctor & Eurika Kaiser & J. Nathan Kutz, 2017. "Chaos as an intermittently forced linear system," Nature Communications, Nature, vol. 8(1), pages 1-9, December.
    4. Steven L Brunton & Bingni W Brunton & Joshua L Proctor & J Nathan Kutz, 2016. "Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-19, February.
    5. Derigs, Ulrich & Illing, Stefan, 2013. "Does EU ETS instigate Air Cargo network reconfiguration? A model-based analysis," European Journal of Operational Research, Elsevier, vol. 225(3), pages 518-527.
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