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Vivid EU ETS model

Vivid Economics EU Emissions Trading System model

ClimateClimateemissionsMarket Stability ReserveMSRTradingEU ETS

overview

ClimateClimateemissionsMarket Stability ReserveMSRTradingEU ETS

main purpose

The model represents the EU Emissions Trading System, as a competitive market where firms can optimise their holdings of emissions allowances over time. It returns a series of equilibrium prices, banking, and emissions within the EU ETS scope on an annual basis.

summary

The Vivid EU ETS model was created by Vivid Economics to model the EU ETS, for the purpose of modelling the functioning of the Market Stability Reserve of the EU ETS (the MSR). The model builds on the modelling approach from Quemin and Trotignon (2019) [1] that is calibrated to represent the average EU ETS compliance entity.

The model considers the EU ETS as a competitive market where firms can bank emissions allowances. The model is dynamic as the number of banked allowances from a given year will affect the total supply of allowances in the subsequent year. Firms are required to surrender allowances for compliance each year that match their emissions and bank any remaining allowances that they hold across years. Solving the model returns a series of equilibrium prices, banking, and emissions within the EU ETS scope on an annual basis.

The model has been used to assess MSR options for the Impact Assessment of the EU ETS review.

[1] Quemin S and Trotignon R (2019) – “Emissions trading with rolling horizons”. Centre for Climate Change Economics and Policy Working Paper 348/Grantham Research Institute on Climate Change and the Environment Working Paper 316. London: London School of Economics and Political Science

model type

ownership

Third-party ownership (commercial companies, Member States, other organisations, …)
Vivid Economics

licence

Licence type:
Non-Free Software licence

details on model structure and approach

The representative firm in the model minimises its abatement cost with rolling horizons and limited foresight. In the model, the firm faces the problem of choosing emissions and abatement over a given time horizon. The firm takes into account its baseline emissions forecast and supply of allowances for the next 10 years (more precisely, the firm decides on emissions in year t after making forecasts of up to year t+9). Baseline emissions in this model are a theoretical construct to represent the emissions in absence of a carbon price. The supply of allowances is determined by the EU ETS cap and augmented by MSR dynamics. The difference between the baseline emissions and the supply of allowances over this time horizon determines the total abatement required from the firm, thus entering its optimisation problem as a budget constraint. The firm minimises the net present value of abatement costs over these X years given this budget constraint and a given interest rate (in addition, there is a borrowing constraint in which the firm can only borrow allowances up to the number of free allocations in the subsequent year. However, this constraint is not binding over the time period in 2020-2030). Limited foresight of the firm means that its forecast of baseline emissions may deviate from the actual baseline emissions. Shocks to the system will affect the firm’s expectations and therefore its optimal choice of emissions and abatement. Finally, equilibrium prices are calculated by mapping the firm’s abatement to a marginal abatement cost curve.

The model is the best-in-class representation of the MSR available in the literature. This includes explicit representation of MSR intakes, releases, corresponding thresholds, the invalidation mechanism, and the calculation of total number of allowances in circulation in the EU ETS (TNAC) on an annual basis. In particular, the model captures the fact that the TNAC for a given year is reported in May in the subsequent year, then affecting auction volumes from September to August. Given the rules-based nature of the MSR, some other models in the literature estimate the TNAC simply by taking an exogenous emissions pathway as given. However, the advantage of optimisation models such as the one used in this assessment is that the emissions pathway is endogenous to the given policy design. In other words, changes in policy parameters will affect the perceived scarcity of emissions allowances and therefore the firm’s behaviour on emissions and abatement. For instance, a higher MSR intake rate should represent a tightening of future allowance supply and therefore reduce emissions today and increase TNAC. The model used in this assessment, adapted from Quemin and Trotignon (2019) [1], is able to model this while capturing realistic aspects of firm behaviour – limited foresight and rolling horizons, as noted above. These aspects of firm behaviour are taken from the latest academic literature and provides an additional perspective to explore the impact of the MSR.

[1] Quemin S and Trotignon R (2019) – “Emissions trading with rolling horizons”. Centre for Climate Change Economics and Policy Working Paper 348/Grantham Research Institute on Climate Change and the Environment Working Paper 316. London: London School of Economics and Political Science

model inputs

  • Baseline emissions
  • Marginal Abatement Cost Curve
  • Interest Rate
  • Anticipation Period
  • Growth rates
  • Assumptions on future EU ETS scope

model outputs

  • MSR intakes
  • Total number of allowances in circulation
  • Emissions
  • Equilibrium carbon prices
  • Auctioned volumes
  • Auction revenues

model spatial-temporal resolution and extent

ParameterDescription
Spatial Extent/Country Coverage
EU Member states 27EFTA countries
The model works at the aggregated level of the EU ETS, i.a. the EU + EEA Member States
Spatial Resolution
World-regions (supranational)
Temporal Extent
Medium-term (5 to 15 years)
Temporal Resolution
Years