Digital Financial Inclusion and Urban Economic Resilience in China: Evidence from a Double Machine Learning Approach

Strengthening urban economic resilience is critical for sustaining stable economic growth amid frequent external shocks and ongoing structural economic transformation in China. As a core financial paradigm in the digital era, digital financial inclusion (DFI) requires systematic examination of its long-term macroeconomic stabilization effects. This study investigates the effect of DFI on urban economic resilience, explores its underlying transmission mechanisms, and determines heterogeneous effects across regional and urban characteristics. Based on panel data of 334 prefecture-level-and-above cities in China from 2011 to 2023, this study constructs a multi-dimensional urban economic resilience capacity index that reflects cities’ latent systemic capacity to resist, recover, adapt, and transform in response to exogenous shocks. Employing a double machine learning (DML) framework to address potential nonlinearities and complex functional relationships, this study provides robust empirical evidence of a positive relationship between DFI and urban economic resilience. The exploration of transmission mechanisms indicates that technological innovation, industrial structure upgrading, and consumption upgrading serve as potential paths. Heterogeneity analyses further indicate that the resilience-boosting effects of DFI vary across geographic regions, DFI dimensions, urban attributes and policy contexts, being notably larger in eastern, non-resource-based, core, and “Broadband China” pilot cities. These findings yield targeted policy implications, emphasizing the need for regionally differentiated DFI strategies and a balanced development paradigm between empowerment efficiency and risk governance. This study offers critical empirical insights and a reliable reference for leveraging DFI to foster high-quality, shock-resistant, and sustainable urban economic development.