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Comparison of ex-ante modelling assessments of emissions trading - 2023
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2467-4540
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EUI; RSC; Policy Brief; 2023/24; Florence School of Regulation; LIFE COASE - Collaborative Observatory for ASsessment of the EU ETS; [Climate]
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OSORIO, Sebastian, RAUDE, Marie, FERRARI, Albert, HEINRICH, Lea, BORGHESI, Simone, Comparison of ex-ante modelling assessments of emissions trading - 2023, EUI, RSC, Policy Brief, 2023/24, Florence School of Regulation, LIFE COASE - Collaborative Observatory for ASsessment of the EU ETS, [Climate] - https://hdl.handle.net/1814/76436
Abstract
- This policy brief synthesises the results from the first annual workshop on ex-ante assessment of emissions trading. It focuses on models assessing the schemes in the EU, UK, China, California, and Québec.
- At a time when emissions trading systems (ETSs) are increasing in number and face similar issues, only a few comparisons of ex-ante models exist.
- The models show considerable heterogeneity. The differences stem from the specific aim, design, scope, ambition and maturity of each market modelled.
- Regarding modelling assumptions, there is an overall reliance of models on Marginal Abatement Cost Curves (MACCs) and a strong impact of parameters such as the discount rate on the assessments.
- In terms of predicted prices, an overall increasing trend is observed across jurisdictions, with predicted prices of non-EU ETSs remaining at a lower level than EU prices. This divergence is due to uncertainty regarding abatement costs, scope, maturity, and overlapping policies.
- There is a growing interest in capturing market imperfections and investor behaviour. Evaluation of carbon leakage, which still requires extensive modelling work, is also identified as relevant future model extensions.
- There is a need for discussion on model comparison to include industry feedback, share experiences and improve the robustness of modelling assumptions. - Closing the loop between the policy process and modelling work is necessary to enhance the predictability of carbon markets and to showcase the consequences of different policy and design choices. Models may also be useful to attribute certain effects to either ETS policies or other policies. This can ultimately improve our understanding of carbon markets in an increasingly dynamic policy landscape.