共有社会経済経路に連動したエネルギー技術の資本コストの将来シナリオ

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

🔬研究者:エネルギーシステムモデルに資本コストの内生的・国別・技術別変動を組み込むための基盤データを提供する。

🏢実務担当者:自社の脱炭素投資の割引率やIRR評価に、SSP連動の資本コストシナリオを適用できる。

🏛政策担当者:政策環境の強弱が資本コストに与える影響を定量化し、脱炭素投資を促す政策設計の根拠となり得る。

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 ( FOAK, Early Commercial, Scaling, Commercial, Mature ), 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 ( Strong/Weak, in the Policy Maturity column). Uncertainty is treated through providing upper ( "High" ) and lower bound scenario ( "Low" ) estimates alongside the central case ( "Central" ), based on historical ranges in the equity risk premium and risk-free rates. 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 188 countries, five technology maturities and two policy conditions. The database addresses the limited empirical data on cost of capital available and enables modellers to select and compare the impact of different scenarios 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). We have also included a breakdown of the country risk premium trajectories under (i) our regression using GDP per capita against a number of controls and (ii) a regression using GDP per capita and a lagged country risk factor into a separate file, to aid with applications for other modelling studies, named "SSP_WACC_SCENARIOS_COUNTRY_RISKS_LONG.csv". We also include in the evolution of the country default spread using the main regression (no lagged formulation) in SSP_WACC_SCENARIOS_COUNTRY_DEFAULT_SPREAD_WIDE.csv". A pre-print of the methodology can be found at: https://www.researchsquare.com/article/rs-9348818/v1. 

• Zenodo https://zenodo.org/records/22796912first seen 2026-09-18 04:11:06 · last seen 2026-09-21 04:14:24