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<p>This study provides a comprehensive review of Climate Policy Uncertainty (CPU)—the unpredictability surrounding changes in climate-related regulations. Although prior reviews in fields such as Environmental Policy Uncertainty (EPU) and green finance have provided valuable insights into policy-related risks, Climate Policy Uncertainty (CPU) remains insuf- ficiently examined as an independent research domain. To fill this gap, the study conducts an integrated bibliometric and systematic review of 1123 publications spanning 1976–2024, using the PRISMA protocol in conjunction with Biblioshiny and VOSviewer-based mapping. By combining quantitative bibliometric analysis with qualitative thematic synthesis, the review offers a multidimensional perspective on the evolution, geographic distribution, and dominant modeling approaches (e.g., GARCH-MIDAS, VAR, and wavelet methods) within CPU research. The findings reveal that CPU significantly affects macroeconomic stability, environmental regulation, asset pricing, and corporate decision-making. Despite increasing scholarly attention, the field remains fragmented and regionally imbalanced, with limited cross-disciplinary integration and insufficient focus on emerging topics such as AI-driven climate forecasting. In general, this review advances understanding of the economic and financial dimensions of CPU and provides a foundation for more coherent, globally inclusive, and adaptive climate policy research.</p>

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Climate policy uncertainty and its implications for sustainable development: a bibliometric and systematic review

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月12日

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  • Bibi Fiza Shah,
  • Hyder Ali

摘要

This study provides a comprehensive review of Climate Policy Uncertainty (CPU)—the unpredictability surrounding changes in climate-related regulations. Although prior reviews in fields such as Environmental Policy Uncertainty (EPU) and green finance have provided valuable insights into policy-related risks, Climate Policy Uncertainty (CPU) remains insuf- ficiently examined as an independent research domain. To fill this gap, the study conducts an integrated bibliometric and systematic review of 1123 publications spanning 1976–2024, using the PRISMA protocol in conjunction with Biblioshiny and VOSviewer-based mapping. By combining quantitative bibliometric analysis with qualitative thematic synthesis, the review offers a multidimensional perspective on the evolution, geographic distribution, and dominant modeling approaches (e.g., GARCH-MIDAS, VAR, and wavelet methods) within CPU research. The findings reveal that CPU significantly affects macroeconomic stability, environmental regulation, asset pricing, and corporate decision-making. Despite increasing scholarly attention, the field remains fragmented and regionally imbalanced, with limited cross-disciplinary integration and insufficient focus on emerging topics such as AI-driven climate forecasting. In general, this review advances understanding of the economic and financial dimensions of CPU and provides a foundation for more coherent, globally inclusive, and adaptive climate policy research.