Impact of low-carbon development on urban employment based on a dynamic spatial Durbin model

Dynamic spatial econometric models have increasingly become a popular tool for investigating how green development policies influence employment outcomes. Among them, the dynamic spatial Durbin model has become a mainstream method because it captures both time-lag effects and spatial externalities. However, existing studies generally lack a clear understanding of the spatiotemporal transmission paths of employment impacts, especially overlooking the potential feedback mechanisms from the low-carbon development level of neighboring cities. This study employs panel data covering 285 prefecture-level cities and above in China between 2005 and 2022, incorporates double-lag terms to improve dynamic fitting, and systematically explores the direct effects, spatial spillovers, and mechanisms of low-carbon development on urban employment. A Dynamic Spatial Durbin Model is constructed to conduct a comprehensive analysis. The empirical results show that under the one-period lag specification, low-carbon development significantly promotes urban employment, with a short-run direct effect of 0.072 and a short-run spatial spillover effect of 0.047. In the long run, the direct effect rises to 0.143 and the spatial spillover effect increases to 0.101. Under the two-period lag specification, the long-run direct and indirect effects remain significant at 0.158 and 0.095, respectively, indicating that the employment gains of low-carbon transition are cumulative over time and extend across neighboring cities. These findings provide a quantitative foundation for improving regional coordinated employment policies in the context of green urban transformation and offer a generalizable analytical framework for identifying the spatiotemporal linkage effects of environmental policies.