Scholarlink

<p>This study explored how changes in the frequency of billion-dollar weather disasters over time influenced the number of climate policies adopted by U.S. states from 2010 to 2023. Using fixed effects negative binomial (FE-NB) regression, panel data was analyzed to assess the relationship between billion-dollar weather disaster occurrence and policy adoption while controlling for social (state population), economic (GDP), and political (state trifecta status) factors. The model included potential time-lag effects at one and two-year intervals. Analysis revealed that mean billion-dollar weather disaster and mean climate policy adoption counts increased over time at the state level. Billion-dollar weather disaster count was a statistically significant predictor of climate policy count. States that experienced a higher incidence of billion-dollar weather disasters tended to adopt more climate policies within the subsequent year. State population and Democratic legislative control significantly influenced climate policy adoption rates.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Evidence on the relationship between billion-dollar weather disasters and state-level climate policy adoption in the United States

  • 期刊论文

  • 发表日期：

    2025年12月22日

查看全文
  • Jennifer A. da Rosa

摘要

This study explored how changes in the frequency of billion-dollar weather disasters over time influenced the number of climate policies adopted by U.S. states from 2010 to 2023. Using fixed effects negative binomial (FE-NB) regression, panel data was analyzed to assess the relationship between billion-dollar weather disaster occurrence and policy adoption while controlling for social (state population), economic (GDP), and political (state trifecta status) factors. The model included potential time-lag effects at one and two-year intervals. Analysis revealed that mean billion-dollar weather disaster and mean climate policy adoption counts increased over time at the state level. Billion-dollar weather disaster count was a statistically significant predictor of climate policy count. States that experienced a higher incidence of billion-dollar weather disasters tended to adopt more climate policies within the subsequent year. State population and Democratic legislative control significantly influenced climate policy adoption rates.