相关实验视频
发行绿色债券和碳排放:因果机器学习能否为前性政策决策提供信息?
1Insititue for Risk Management and Insurance Innovation, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States.
Environmental science & technology
|November 14, 2025
概括
市政绿色债券减少了当地碳排放,特别是在有更多中小企业的县里. 这些环境融资工具在时间和空间上显示出不同的影响,每二氧化碳的减排成本为192美元.
科学领域:
- 环境金融 环境金融
- 应用经济学应用经济学
- 城市可持续性 城市可持续性
背景情况:
- 绿色债券为环境项目提供资金,但它们对当地碳排放的影响尚未得到充分证实.
- 市政当局需要有关绿色债券影响的细节数据,以便明智作出决策.
研究的目的:
- 调查美国市政绿色债券发行对当地碳排放的因果关系.
- 分析减排的空间和时间变化.
- 确定影响绿色债券有效性的社会经济因素.
主要方法:
- 在双偏的机器学习框架中使用因果森林模型.
- 分析了2009-2019年美国市政绿色债券数据.
- 根据当地社会经济条件进行控制,以隔离绿色债券的影响.
主要成果:
- 绿色债券发行在减少碳排放方面表现出了相当大的空间和时间异质性.
- 观察到最大的排放减少是在特定的县,并随着时间的推移而增加.
- 暗示的碳减排成本估计为每CO2的192美元.
- 有较高中小企业集中度的县份显示出减排效益最强.
结论:
- 市政绿色债券通常会减少碳排放,尽管规模因当地经济和基础设施特征而异.
- 这些发现为市政绿色融资的有效性提供了关键证据.
- 结果对政策实施和预测环境结果有影响,特别是对新发行人来说.
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