FDI, technological progress, and green total factor energy productivity: evidence from 281 prefecture cities in China

This paper uses the slack-based measure-Malmquist-Luenberger (SBM-ML) method to calculate green total factor energy productivity (GTFEP), constructs a dynamic panel data model to analyse the impact of foreign direct investment (FDI) and technological progress (TP) on GTFEP, and further verifies robustness through heterogeneity tests, quantile regression and a dynamic spatial Durbin model. The main results of this study show that from a national perspective, GTFEP has the characteristics of accumulation and sustainability, and the GTFEP value is positively affected by the value in the previous period. FDI, TP and their interaction term can all contribute significantly to GTFEP, and the effect of FDI in promoting GTFEP through TP is very obvious. The regional heterogeneity test shows that FDI can play a significant role only in the central region, and resource-based city policy can improve GTFEP to a certain extent. The results of quantile regression show that there is a dynamic process of the marginal effects of FDI and TP on GTFEP. The empirical results of the dynamic spatial Durbin model show that the results are still robust after considering spatial factors. Finally, corresponding policy implications are proposed based on the empirical conclusions.