Background
Participatory approaches have been argued to bring a more diverse range of views into the ΙΑΜ process, by building a better understanding of the social context and supporting more inclusive decision-making. In IAM COMPACT, we have designed a Policy Response Mechanism (PRM), a co-creation process that facilitates collaboration among modelling teams and with stakeholders. The PRM dynamically responds to changing policy priorities, aiming for policy relevance, knowledge exchange, and enhanced trust, by providing different layers of inputs and making modelling socially/politically realistic. Stakeholder engagement in IAM COMPACT is organised into themes (for stakeholders within the EU) and regions (for stakeholders outside the EU). The themes and regions were collaboratively determined within the project, with Bruegel coordinating the process. For the themes, the aim was to have a broad enough coverage to capture a range of issues, but also sufficiently selective to lead a clear research agenda later in the project.
Overall, 23 questions emerged from high-level exchanges with policy stakeholders (forming the Policy Steering Groups), which we grouped into proposals for seven modelling studies. These proposals were in turn grouped into four overreaching themes and discussed with a wider policy audience (forming the Core Working Groups) selected on geographical and sectoral criteria. The consultative process helped us evaluate the relevance of policy issues, refine the scope of research questions, and establish a balanced group of stakeholders to participate. We conducted one workshop under each theme alongside the corresponding core working group to consult stakeholders on our scenario design and co-define desired outputs as well as a key set of joint input assumptions.
This study is part of the theme Global Effects, which considers trade and macroeconomic issues and their effects on European decarbonisation. During the workshop conducted under this theme, we sought feedback on the scenario design, inputs, and projections of two proposed modelling studies. Following an in-depth discussion on uncertainty factors and how these may play out, the 20 participating stakeholders—among others from DG Trade, DG ECFIN, the European Central Bank, and the National Bank of Belgium—were asked to also fill out a survey on how perceived costs may evolve for different technologies and countries around the world. The study presented here looked at how regionally and technologically differentiated cost of capital projections could affect decarbonisation pathways in Europe and around the world.
Cost of capital evolution
We drew experts’ insights on how much investment risks may change for a set of technologies by 2050 in high-, middle-, and low-income countries, considering finance and policy derisking or divestment mechanisms that may play out, to determine the final risk percentage change. Figure 1 shows a representation of baseline and future aggregated WACC values by region and technology for each scenario.
Figure 1: Baseline and projections of WACC values per scenario and windfall profits. WACC values aggregated by aggregated region and technology (fossil fuels, renewables, nuclear, CCS, and green hydrogen), (a) in the baseline year; (b) in 2050 based on the survey results (Sv, Sv-F, Sv-NF scenarios); (c) and in 2050 for the Frag scenario. Scenarios are explained in Table A1.
Scenario design
We designed four alternative futures, in terms of cost-of-capital projections. The first explicitly reflects the results of the survey (scenario Sv in the figures below). Seeing how our experts’ responses showed two tendences in terms of cost-of-capital projections across technologies, namely increased risk of fossil-fuel investments and derisking of renewable energy technologies, we disaggregated these trends and formulated two more futures. The following table describes the cost of capital trajectories and assumptions for each modelled scenario.
Scenario name |
WACC trends and climate policies assumptions |
B-NDC |
Based on 2030 emission targets pledged in NDCs submitted or announced by June 2023, capturing all mitigation ambition updates during and after COP26 in Glasgow, implemented on top of current policies. In model regions with current policies exceeding NDC mitigation targets, no additional emission constraints are applied; emissions reductions are therefore never less ambitious than implied in current policies. Empirical WACC values are used and kept fixed for the entire time horizon. |
B-LTT |
For regions that have expressed an LTT—e.g., net-zero commitments or other targets for 2050 or later—emission constraints linearly decline from 2030 levels from the NDC target towards the LTT. For regions without LTTs, post-2030 the applied policy targets are maintained as minimum levels beyond 2030 to avoid backtracking of achieved policies. Empirical WACC values are fixed for the entire time horizon. |
Sv |
Empirical WACC values are used as baseline (2020), while future WACC values change for all technologies linearly in 2018-2050, according to our survey results. Carbon prices are taken from B-NDC. |
Sv-F |
Empirical WACC values are used as baseline (2020), while future WACC values for fossil fuels increase linearly in 2018-2050, according to our survey results. Carbon prices are taken from B-NDC. |
Sv-NF |
Empirical WACC values are used as baseline (2020), while future WACC values for RES, green H2, hydro, and CCS decrease, and those for biomass and nuclear increase linearly in 2018-2050, according to survey results. Carbon prices are taken from B-NDC. |
Frag |
Empirical WACC values are used as baseline (2020), while future WACC values of high-income countries further diverge from those in LMICs, linearly in 2018-2050: for high-income countries (incl. China), WACC values converge to the 25th percentile of the average baseline empirical WACC value per technology; for LMICs, WACC values converge to the 75th percentile of the average baseline empirical WACC value per technology. Carbon prices are taken from B-NDC. |