Journal of Public Economics · 2025 · Robert Germeshausen、Sven Heim、Ulrich J. Wagner
中文摘要
气候变化减缓和能源安全等社会目标的兴起,要求可再生电力装机容量快速增长,然而当此类技术产生负向本地外部性时,公民的支持便面临考验。我们估计了风力涡轮机部署对产品市场与政治市场中可再生电力显示性偏好细粒度测度的影响。我们采用工具变量(IV)设计处理涡轮机选址潜在的内生性问题,该设计利用了补贴引致的盈利能力准实验变异。我们发现,风力涡轮机在本地显著降低了公民的支持度,但这一效应随距选址地点距离的增加而迅速消退。基于研究结果,我们评估了旨在增强公民对可再生能源支持的政策工具。• 背景挑战:尽管社会目标要求快速扩大可再生能源(如风电),但噪声污染或视觉干扰等负外部性会引发当地反对。• 实证方法:本研究采用工具变量(IV)策略处理风力涡轮机选址的内生性问题,利用补贴所致盈利能力差异形成的准实验变异。• 主要发现:风力涡轮机部署降低了当地对可再生电力的支持,这一点在消费者(产品)市场和政治市场中均有体现。• 政策含义:研究结果为旨在提高公众对可再生能源接受度的政策设计提供了依据,强调需要就风力涡轮机的负向本地外部性给予经济补偿。
Abstract
The rise of societal goals like climate change mitigation and energy security calls for rapid capacity growth in renewable electricity sources, yet citizens’ support is put to a test when such technologies emit negative local externalities. We estimate the impact of wind turbine deployment on granular measures of revealed preferences for renewable electricity in product and political markets. We address potentially endogenous siting of turbines with an IV design that exploits quasi-experimental variation in profitability induced by subsidies. We find that wind turbines significantly reduce citizens’ support locally, but this effect quickly fades with distance from the site. We assess policy instruments for enhancing citizens’ support for renewable energy in light of our results. • Contextual Challenge : While societal goals demand rapid expansion of renewable energy (e.g., wind power), local opposition arises due to negative externalities like noise pollution or visual disruption. • Empirical Approach : The study uses an instrumental variables (IV) strategy to address endogeneity in wind turbine siting, leveraging quasi-experimental variations from subsidy-driven profitability differences. • Key Finding : Wind turbine deployment reduces local support for renewable electricity, as observed in both consumer (product) and political markets. • Policy Implications : Results inform the design of policies aimed at boosting public acceptance of renewable energy, emphasizing the need for financial compensation for negative local externalities of wind turbines.