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<p>Higher temperatures are expected to impact globally on poverty and inequality, yet little cross-country analysis exists to quantify the effects. Here we analyse a panel dataset of subnational poverty in 130 countries covering the past decade and find that a 1 °C increase in temperature causes headcount poverty increases of 0.63–1.18 percentage points, using the daily poverty lines of US$2.15 (corresponding to 8.3% and 15.6% increases), and increases in the Gini inequality index of 1.3–1.9%. These poverty estimates equal a projected increase of global poor by 62.3–98.7 million people by 2030 compared with a scenario without climate change. Poorer countries—particularly those in Sub-Saharan Africa—are more vulnerable, as are countries with higher agriculture shares in the economy. Estimates at the subnational level are larger than those using the country-level data, indicating that aggregated analysis may underestimate climate change risks.</p>

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Impacts of global warming on subnational poverty and inequality

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月22日

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  • Hai-Anh H. Dang,
  • Stephane Hallegatte,
  • Minh Cong Nguyen,
  • Trong-Anh Trinh

摘要

Higher temperatures are expected to impact globally on poverty and inequality, yet little cross-country analysis exists to quantify the effects. Here we analyse a panel dataset of subnational poverty in 130 countries covering the past decade and find that a 1 °C increase in temperature causes headcount poverty increases of 0.63–1.18 percentage points, using the daily poverty lines of US$2.15 (corresponding to 8.3% and 15.6% increases), and increases in the Gini inequality index of 1.3–1.9%. These poverty estimates equal a projected increase of global poor by 62.3–98.7 million people by 2030 compared with a scenario without climate change. Poorer countries—particularly those in Sub-Saharan Africa—are more vulnerable, as are countries with higher agriculture shares in the economy. Estimates at the subnational level are larger than those using the country-level data, indicating that aggregated analysis may underestimate climate change risks.