Descriptive statistics.

This study delves into the impact of digital inclusive finance on environmental pollution, with a specific focus on air pollution. Utilizing data from 265 Chinese cities, advanced econometric methods such as the bi-directional fixed effects model, threshold model, spatial Durbin model, and multi-period difference-in-differences model are employed, incorporating a variety of control variables. The empirical findings indicate that digital inclusive finance significantly reduces air pollution. This mechanism chiefly operates through enhancing public environmental consciousness and fostering green technological innovation. The study also uncovers the spatial spillover effect and non-linear characteristics of digital inclusive finance on air pollution, along with its interactive effects with specific policies (e.g., smart city pilot policies and the “major protection, no major development" initiative). Moreover, heterogeneity analysis reveals regional variations in the environmental effects of digital inclusive finance. These insights provide a novel perspective on the relationship between financial technology and environmental protection and offer crucial guidance for policymaking.

本研究聚焦于数字普惠金融对环境污染的影响，且以空气污染为具体研究对象。研究采用中国265个城市的面板数据，运用双向固定效应模型、门槛模型、空间杜宾模型以及多期双重差分模型等高级计量经济学方法，并纳入多类控制变量。实证结果表明，数字普惠金融可显著降低空气污染水平。其作用机制主要通过提升公众环保意识与推动绿色技术创新得以实现。本研究还揭示了数字普惠金融对空气污染的空间溢出效应与非线性特征，以及其与智慧城市试点政策、"共抓大保护、不搞大开发"战略的交互效应。此外，异质性分析揭示了数字普惠金融环境效应的区域异质性。本研究为金融科技与环境保护之间的关联提供了全新视角，同时为政策制定提供了重要参考依据。