Transition Risk under Uncertain Climate Policy
不確実な気候政策下における移行リスク (AI 翻訳)
Azaribrahim Rabhi, Mohammed Salah Chiadmi, Rajae Aboulaïch
🤖 gxceed AI 要約
日本語
本論文は、政策不確実性の下での気候移行リスクの経済・金融への影響を分析。NGFSシナリオに基づく確率的枠組みを用い、モンテカルロシミュレーションにより移行確率と気候調整リスク指標を推定。化石燃料電源は脆弱、再生可能エネルギーは強靱であることを示し、投資家と政策立案者への示唆を提供。
English
This paper analyzes the economic and financial implications of climate transition risk under policy uncertainty. Using stochastic modeling calibrated on NGFS scenarios and Monte Carlo simulations, it estimates transition probabilities and climate-adjusted risk indicators (Climate VaR and ES). Results show fossil-based electricity is highly vulnerable, while renewables are resilient, offering insights for investors and policymakers.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
本論文はNGFSシナリオを用いた包括的な枠組みを提供し、日本の金融機関や企業が気候移行リスクを評価する際の参考となる。政策不確実性の定量化は、日本のGX政策やSSBJ開示におけるシナリオ分析の高度化に寄与する。
In the global GX context
This paper provides a robust stochastic framework for transition risk under policy uncertainty, directly relevant to global climate disclosure standards (TCFD, ISSB) and stress-testing practices. Its findings on sectoral vulnerability inform both investment strategies and regulatory approaches to climate risk management.
👥 読者別の含意
🔬研究者:Novel stochastic model integrating policy regime shifts and physical climate feedbacks, applicable to transition risk research.
🏢実務担当者:Monte Carlo framework can be adapted for corporate scenario analysis and climate-adjusted risk metrics.
🏛政策担当者:Highlights importance of credible, stable climate policy to reduce transition uncertainty and financial fragility.
📄 Abstract（原文）
This paper analyzes the economic and financial implications of climate transition risk under policy uncertainty, with a particular emphasis on the energy sector. A stochastic modeling framework is developed to capture the dynamic evolution of climate policy regimes, calibrated on NGFS transition scenarios. The model incorporates both the probability of regime shifts and their financial consequences, highlighting how regulatory adjustments respond to the accumulation of physical climate stress and transmit shocks across energy sub-sectors. By employing Monte Carlo simulations, we estimate the likelihood of different transitions and derive climate-adjusted risk indicators., including Climate Value at Risk (VaR) and Climate Expected Shortfall (ES), for both fossil fuel and renewable energy sectors. Results show a clear structural division.: Once ambitious policy regimes come into play, transition trajectories find stability, leading to a reduction in transition probabilities as climate signals are mitigated.. The fossil-based electricity sector appears as highly vulnerable to adverse financial shocks, while renewable energy sector proves relative resilience, even in extreme scenarios. These findings highlight the crucial importance of considering policy uncertainty when making strategic investment decisions and managing financial risks. The proposed framework offers a practical tool, beneficial for both investors and policymakers, to execute forward-looking stress tests and to reallocate assets in response to emerging climate commitments.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.37394/23207.2026.23.31first seen 2026-05-23 05:00:29 · last seen 2026-05-27 04:31:12
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