Abstract
The optimal allocation of the labor force through population mobility is a critical determinant of the synergistic economy, society, and environment, with substantial implications for Green Total Factor Productivity (GTFP). This study employs panel data from 2011 to 2020 encompassing 30 Chinese provinces, to measure the GTFP using the SBM-DDF model. We then investigated the network association characteristics of GTFP across provinces through social network analysis. Furthermore, fixed- and moderating-effects models are applied to empirically examine the impact of population mobility on GTFP, as well as the moderating roles of technological progress, financial development, and digital inclusive finance. These results indicate that China's GTFP exhibits spatial clustering and regional disparities, with western and eastern regions being the primary sources and destinations of green resource flows, respectively. Population mobility enhances national GTFP, a finding that remains robust across several endogeneity and robustness tests. However, this effect is heterogeneous; it is significant in destination regions, eastern and western regions, and the post-industrialization stage, but negligible elsewhere. Furthermore, the moderating effect analysis shows that technological progress amplifies this relationship both nationally and in destination areas. Additionally, financial development strengthens the effect in destination regions, whereas digital inclusive finance strengthens the effect in origin regions. Recognizing population mobility as a globally pervasive phenomenon, this study highlights its functional role and advances our understanding of its relationship with sustainable development.