A causal inference for digital infrastructure construction and green innovation using double machine learning

During global digital transformation, advancing digital infrastructure has emerged as a catalyst for green development in China. Leveraging the Broadband China Pilot policy as a quasi-natural experiment for digital infrastructure construction, this study employs double machine learning models and panel data of 285 Chinese cities from 2010 to 2022 to evaluate the policy’s impact on urban green innovation. Results demonstrate that digital infrastructure development significantly enhances both the quantity and quality of urban green innovation. These findings withstand robustness checks, including sample adjustments and model respecification. Mechanistic analyses reveal that digital infrastructure facilitates innovators’ access to environmental, technological, and market-related information, enabling more targeted and cost-effective green innovation. Heterogeneity analyses indicate a stronger policy effect on high-quality green innovation in eastern, western, and non-resource-dependent cities. This study provides critical insights for leveraging digital infrastructure to advance sustainable economic development through green innovation.