Zhou Pinglu, Ning Xiaoya, Huang Meiying, Zhou Ziyi, Shi Wei, Qin Ming
School of Economics, Lanzhou University, Lanzhou, 730000, China.
J Environ Manage. 2025 Sep;392:126749. doi: 10.1016/j.jenvman.2025.126749. Epub 2025 Aug 1.
Based on panel data from 270 prefecture-level cities in China from 2006 to 2021, this paper employs the Pilot Programme to Promote the Integration of Science and Technology (S&T) Finance as a quasi-natural experiment. A difference-in-differences (DID) model is applied to evaluate its impact on urban carbon reduction, spatial spillovers, and underlying mechanisms. The results show that the pilot programme significantly promotes carbon reduction and facilitates low-carbon urban transformation. These findings remain robust after a series of tests, including parallel trend tests, placebo tests, double machine learning, and PSM-DID, which address endogeneity concerns. The programme also generates positive spatial spillover effects on neighboring cities. Heterogeneity analysis reveals that its impact varies across cities, depending on development scale, environmental awareness, and human capital levels. Mechanism analysis reveals four key drivers of carbon reduction. These include factor agglomeration, technological innovation, structural transformation, and resource allocation.
基于2006年至2021年中国270个地级市的面板数据，本文将促进科技金融融合试点项目作为一项准自然实验。运用双重差分（DID）模型评估其对城市碳减排、空间溢出效应及潜在机制的影响。结果表明，该试点项目显著促进了碳减排，并推动了低碳城市转型。在进行了包括平行趋势检验、安慰剂检验、双重机器学习和倾向得分匹配法-双重差分（PSM-DID）等一系列解决内生性问题的检验后，这些结果依然稳健。该项目还对邻近城市产生了积极的空间溢出效应。异质性分析表明，其影响因城市的发展规模、环境意识和人力资本水平而异。机制分析揭示了碳减排的四个关键驱动因素，包括要素集聚、技术创新、结构转型和资源配置。
