Heterogeneous impacts of digital economy on tourism: a causal forest analysis from China

This study explores the heterogeneous effects of digital economy on tourism, exploiting the Broadband China Program as a quasi-natural experiment. Using a panel dataset comprising 295 Chinese cities from 2005 to 2019, we apply a staggered difference-in-differences strategy to identify average treatment effects and a causal forest method to uncover treatment heterogeneity. The policy increased tourism arrivals by 24.0% and revenue by 25.7%, primarily through enhanced informatization, industry integration, and innovation capacity. Benefits are concentrated in cities with advanced transportation, abundant tourism resources, higher network stock, and greater technology input. Importance factor analysis identifies government support, industrial structure, economic activity, and openness as critical drivers of policy effectiveness. Quantile estimates reveal larger effects in cities with higher tourism capacity, suggesting a risk of widening regional disparities. Spatial analysis confirms positive spillovers in neighboring cities within 300 km. These findings underscore the need for localized digital strategies.