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April 16, 20260 citationsOpen Access

The Adaptation Imperative: Climate Change and Sovereign Credit Risk

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MBM. BurkeKMK. MohaddesMRM. Raissi

Key Points

  • This research investigates the impact of climate change on sovereign credit ratings and borrowing costs using updated climate scenarios.
  • Integrated income-loss estimates from Mohaddes and Raissi into the IMF's Q-CRAFT framework.
  • Applied a Random Forest emulator to predict future credit rating trajectories.
  • Utilized CDS-spread mapping to convert rating changes into borrowing cost effects.
  • Conducted Monte Carlo simulations to assess tail risks and cross-country variations.
  • Under high-emission scenarios, sovereign ratings may drop by up to 2.8 notches, increasing borrowing costs by 30 basis points.
  • Paris-aligned scenarios show negligible impacts on ratings.
  • Tail risks could lead to downgrades of up to six notches by 2100.
  • Emerging economies exposed to climate-related disasters may experience downgrades of 1–3 notches by 2050.

Abstract

This paper examines how climate change affects sovereign credit ratings and borrowing costs under the latest IPCC climate scenarios. We integrate country-specific income-loss estimates from Mohaddes and Raissi (2025) into the IMF’s Q-CRAFT macro-fiscal framework and apply a Random Forest emulator to predict rating trajectories. We also use the CDS-spread mapping from Aizenman et al. (2013) to translate these rating changes into borrowing-cost effects. Results show negligible rating impacts under the Paris-aligned scenario but significant downgrades (up to 2.8 notches) and increases in borrowing costs (30 basis points) under high-emission, slow-adaptation pathways by 2100 for the G20 countries. Monte Carlo simulations highlight substantial tail risks and cross-country heterogeneity, with tail outcomes producing downgrades of up to six notches by century end. We further extend the analysis to unrated economies and incorporate acute physical risks from climate-related natural disasters, using DIGNAD to estimate their cumulative GDP effects over 30 years and feeding these into the Q-CRAFT and the Random Forest emulator to project ratings. Disaster exposure can induce 1–3 notch downgrades by 2050 for highly vulnerable emerging economies.

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Cite This Study

Burke et al. (2026) studied this question.

synapsesocial.com/papers/69e07e582f7e8953b7cbf576https://doi.org/10.17863/cam.129389
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