Digital Infrastructure and Industrial Green Innovation in China: An Empirical Study on Efficiency Measurement and Impact Assessment
Abstract
As emerging economies navigate the global “twin transition”, decoupling industrial growth from environmental degradation has become an urgent imperative. This study investigates the fundamental role of digital infrastructure in driving Industrial Green Innovation Efficiency (IGIE). Utilizing panel data from 30 Chinese provinces spanning 2012 to 2022, we first measure the environment-adjusted IGIE employing a three-stage global SBM-DEA model to mitigate external environmental interferences and statistical noise. Subsequently, a two-way fixed-effects model, fortified by a Bartik-type instrumental variable (IV-2SLS) approach, is constructed to identify causal impacts. The descriptive results reveal that China’s overall IGIE exhibits a fluctuating upward trajectory, although absolute efficiency levels remain low. Furthermore, significant regional variations characterize the national landscape, manifesting as Eastern leadership, Central catch-up, Western improvement, and Northeastern volatility. Crucially, empirical baseline estimations confirm that digital infrastructure exerts a robust positive effect on IGIE. Mechanism analyses further demonstrate that this efficiency enhancement is primarily driven by the promotion of digital inclusive finance and localized technological diffusion. These findings theoretically enrich the understanding of digital empowerment and provide a practical blueprint for policymakers globally to formulate targeted infrastructure investments and differentiated regional transformation strategies.