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Nonlinear effects of climate risks on climate-sensitive sectors

Author

Listed:
  • Wenqiang Zhu

    (Southeast University
    Southeast University)

  • Shouwei Li

    (Southeast University
    Southeast University)

Abstract

The urgency of recognizing the substantial impacts of climate risks on economic and financial systems is increasingly emphasized among regulators and investors. By constructing the news-based climate physical risk (CPR), climate transition risk (CTR), and climate policy uncertainty (CPU) indexes for China, we adopt TVP-VAR-SV models and apply it to various economic sectors in a climate-sensitive scenario. We obtain this result that the significant heterogeneity of climate risk exposures and its different effects on climate-sensitive sectors. CPR emphasizes the immediate effect of operating and bankruptcy costs, thus not causing large variations across sectors. The differences in CTR exposure among these sectors are largely influenced by energy transition and climate policy. In addition, climate policy timing matters. CPU shock shows that a disorderly and ambitious climate policy could have adverse consequences for economic sectors over time approximation, especially for the related sectors within the energy chain. Noticeably, the response in the finance sector illustrates that the transition to low-carbon finance could also have net positive effects. Therefore, our results provide important implications for the low-carbon actors dealing with a ‘green’ or a ‘brown’ investing and transition strategy in China’s “carbon peak, carbon neutrality” target.

Suggested Citation

  • Wenqiang Zhu & Shouwei Li, 2024. "Nonlinear effects of climate risks on climate-sensitive sectors," Economic Change and Restructuring, Springer, vol. 57(5), pages 1-31, October.
  • Handle: RePEc:kap:ecopln:v:57:y:2024:i:5:d:10.1007_s10644-024-09751-5
    DOI: 10.1007/s10644-024-09751-5
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    More about this item

    Keywords

    Climate physical risk; Climate transition risk; Climate policy uncertainty; Climate-sensitive sectors;
    All these keywords.

    JEL classification:

    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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