Regional green economy efficiency and population aging in China: An empirical data envelopment analysis – Tobit model approach

This study presents an indicator system to assess the green economy efficiency of China's provinces and explores its relationship with population aging. Based on panel data covering 30 provincial-level regions from 2000 to 2020, a slacks-based measure–Data Envelopment Analysis (SBM–DEA) model is employed to evaluate green economy efficiency, followed by a Tobit regression model to examine the influence of demographic aging on regional performance. The results reveal three key findings: (1) At the national level, GEE shows an overall declining trend, with pronounced spatial disparities. The Eastern region consistently outperformed others, while the Western and Northeastern regions lagged behind. (2) Population aging exhibits a statistically significant positive effect on GEE. Robustness checks confirm the stability of this result. (3) Mechanism analysis suggests that aging primarily improves economic output efficiency rather than environmental performance, reflecting productivity gains through labor substitution, automation, and the expansion of knowledge- and service-based industries. (4) Clear regional heterogeneity is observed: in the Eastern region, the relationship follows a U-shaped pattern; in the Central region, a stable positive correlation persists; while in the Western and Northeastern regions, an inverted U-shaped trajectory emerges. These findings underscore the need for regionally differentiated policies that integrate demographic realities with green development strategies, ensuring that aging populations contribute to both economic productivity and environmental sustainability. The study provides evidence to support differentiated population and environmental strategies aimed at promoting a sustainable, low-carbon economy in China.