Future scenarios for the cost of capital of energy technologies linked to the Shared Socioeconomic Pathways

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a comprehensive dataset and methodology for incorporating cost of capital into energy system models, enabling more accurate scenario analysis.

🏢実務担当者:Useful for corporate strategists and investors to assess financing conditions for energy projects under different socioeconomic and policy scenarios.

🏛政策担当者:Helps policymakers understand how supportive policies can reduce capital costs and accelerate clean energy deployment.

The cost of capital is an important input for power sector and energy system models, used widely across industry, academia and government to explore future decarbonisation scenarios. Scenario modelling plays an important role in providing technical insights for stakeholders on the implications of future policy, technological and socioeconomic change on the global energy and climate system. Despite its importance for the competitiveness of energy technologies, the cost of capital (CoC) has received limited treatment in scenario modelling, due to uncertainties over the future evolution of interest rates, country risk factors and technological maturities. Here, we present global scenarios of the CoC for energy projects, covering 188 countries from 2025 to 2100 and linked directly to the Shared Socioeconomic Pathways. We estimate the CoC for five technology maturity levels, linked to the IEA’s extended Technology Readiness Level benchmarks, enabling stakeholders to explore the effects of technological development on the CoC within models. To provide a wide basis for modelling efforts, we also incorporate the effects of supportive policy environments on financing conditions.Uncertainty is treated through providing upper and lower bound scenario estimates alongside the central case, based on historical ranges. The data are global in scope but with national and technology specificity, covers the years 2025 through to 2100, and span over 800,000 datapoints across 186 countries, five technology maturities and two policy conditions. The database addresses the limited empirical data on cost of capital available and enables enables modellers to select and compare the impact of different scenarions on model outcomes. The estimation model builds on a number of peer-reviewed studies that have verified it to real-world conditions through stakeholder engagement, expert elicitation and benchmarking to empirical data. Estimates for the cost of capital across scenarios with country, technology maturity and policy condition specificity across all combinations are available in a wide format in SSP_WACC_SCENARIOS_UNCERTAINTY_WIDE.csv for low, central and high scenario estimates. The LONG csv files contain specific estimates for given technology maturity level for the central case in the format "SSP_WACC_SCENARIOS_CENTRAL_TECHNOLOGY_LONG", with more detailed information on the underlying drivers of the cost of capital than is included in the wide file (e.g., breakdown into the cost of debt, cost of equity and underlying components).

• openalex https://doi.org/10.5281/zenodo.19449137first seen 2026-05-05 19:11:40