The effect of the spatial heterogeneity of human capital structure on regional green total factor productivity

China’s rapid economic growth has resulted in resource consumption and environmental degradation. Only by improving green total factor productivity (GTFP) can China’s economic growth become stable and sustainable. Existing studies have demonstrated that total human capital can improve GTFP, but such studies have ignored the heterogeneous influence of human capital structure, and there is a lack research on how human capital structure affects GTFP spatially. Therefore, based on China’s provincial panel data from 2000 to 2018, this paper uses the Super-SBM-ML model to evaluate GTFP. The human capital is divided into that having academic education and that having only non-academic education, and then the spatial Dubin model is used to estimate the relationship between GTFP, academic education and non-academic education human capital. The empirical results show that different levels of human capital have different effects on GTFP. Some types of human capital (such as tertiary-level educational human capital) promote local GTFP, while other types (such as primary-level educational human capital) inhibit it. This indicates that local governments should optimize the human capital structure in order to promote green development. In addition, although there are effects of human capital on the spatial spillover of GTFP, those effects are not significant for some types of human capital, indicating that local circulation channels for human capital are not smooth, so it is necessary to improve local talent policies and strengthen regional cooperation and development so that human capital can promote the rapid development of a green economy. Finally, this paper proves that educational human capital can alter the impact on GTFP of technological progress, knowledge spillover, industrial upgrading and environmental regulation.