The Impact of Resource Endowment on the Sustainable Improvement of Rural Project Quality: Causal Inference Based on Dual Machine Learning

Resource endowment serves as the foundational condition and strategic pillar for the sustainable improvement of rural project quality, determining the capacity for sustainable development. Clarifying the intrinsic mechanisms through which resource endowment influences the sustainable improvement of rural project quality not only demystifies the “black box” of resource conversion but also reshapes the project development paradigm centered on endowment matching. Based on panel data from 30 provinces in China spanning from 2015 to 2024, this paper empirically examines the impact of resource endowment on the sustainable improvement of rural project quality using a double machine learning model. The results indicate that resource endowment has significant promoting effect. Furthermore, the baseline regression results remain robust after various robustness checks, including adjustment to the research sample, reestablishment of machine learning model, and endogeneity tests involving the introduction of instrumental variable and lagged core variable. Mechanism analysis indicates that resource endowment primarily achieves promoting effect through government attention. Heterogeneity analysis indicates that the impact of resource endowment varies depending on geographic location and the type of project. The SHAP method is also employed to reveal the key factors driving the sustainable improvement of rural project quality in resource endowment.