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When the Weather Turns Risky: Climate Shocks and U.S. State-Level Credit Risk

Author

Listed:
  • Abeeb Olaniran

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Xin Sheng

    (Lord Ashcroft International Business School, Anglia Ruskin University, Chelmsford, United Kingdom.)

  • Oguzhan Cepni

    (Ostim Technical University, Ankara, Turkiye; University of Edinburgh Business School, Centre for Business, Climate Change, and Sustainability; Department of Economics, Copenhagen Business School, Denmark)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

Abstract

Climate-related risks have become an increasingly important source of market disruption, with potential implications for credit markets. As such, this study examines whether and how climate risks influence credit risk, as measured by credit default swap (CDS) spreads. Using a U.S. state-level climate risk measure and a local projections framework, we analyze both linear and asymmetric effects of climate shocks on CDS spreads. The linear results provide strong evidence that climate shocks exert a positive and statistically significant impact on credit risk, with findings robust across multiple CDS tenors. Within a nonlinear framework, where climate risk serves as a regime-switching variable, we uncover asymmetric responses of CDS spreads across different maturities and term structures. Overall, the findings offer valuable insights for market participants, including investors and financial institutions.

Suggested Citation

  • Abeeb Olaniran & Xin Sheng & Oguzhan Cepni & Rangan Gupta, 2026. "When the Weather Turns Risky: Climate Shocks and U.S. State-Level Credit Risk," Working Papers 202604, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202604
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    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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