Ren Yayun, Xu Xiaohang, Yu Yantuan, Zhang Zhenhua
School of Economics, Guizhou University of Finance and Economics, Guiyang, 550025, China.
School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou, 510006, China.
Carbon Balance Manag. 2025 Jul 5;20(1):22. doi: 10.1186/s13021-025-00311-6.
Addressing the carbon co-benefits of policy tools requires simultaneous improvements in both the quantity and quality of carbon abatement to achieve long-term sustainability and equity. Driven by digital technologies and bolstered by green capital, the combination of the digital economy and green finance (DEGF) establishes an effective mechanism for attaining sustainable development goals. Treating the coordinated implementation of the National Big Data Comprehensive Pilot Zones (NBDCPZ) and Green Finance Reform and Innovation Pilot Zones (GFRIPZ) policies in China as a quasi-natural experiment, we identify the carbon co-benefits of DEGF using the Synthetic Control Method with penalized regression technique. Empirical findings show that DEGF significantly promotes simultaneous improvements in both the quantity and quality of carbon mitigation. These findings are robust across various validation tests, including time-placebo test, alternative model specification, and double machine learning algorithms. According to mechanisms analysis, improving green technological innovation and human capital level are the main channels that DEGF produces carbon co-benefits. The study provides China and other emerging economies seeking to promote sustainable development through digital-green integration with policy-relevant implications.
解决政策工具的碳协同效益需要同时提高碳减排的数量和质量，以实现长期的可持续性和公平性。在数字技术的推动下，并在绿色资本的支持下，数字经济与绿色金融（DEGF）的结合建立了实现可持续发展目标的有效机制。将中国国家大数据综合试验区（NBDCPZ）和绿色金融改革创新试验区（GFRIPZ）政策的协同实施视为一项准自然实验，我们使用带惩罚回归技术的合成控制法来识别数字经济与绿色金融的碳协同效益。实证结果表明，数字经济与绿色金融显著促进了碳减排在数量和质量上的同步提升。这些结果在各种验证测试中都是稳健的，包括时间安慰剂测试、替代模型设定和双重机器学习算法。根据机制分析，提高绿色技术创新和人力资本水平是数字经济与绿色金融产生碳协同效益的主要渠道。该研究为中国和其他寻求通过数字-绿色融合促进可持续发展的新兴经济体提供了与政策相关的启示。
