Green technology innovation and regional carbon emissions: analysis based on heterogeneous treatment effect modeling.

Abstract

The impact of green technology innovation on regional carbon emissions has been a contentious issue in academic research. In this study, we attempt to analyze the influence of green technology innovation on regional carbon emissions using panel data from 28 Chinese provinces for the period of 2007-2020. Utilizing a heterogeneous treatment effect model, we systematically examine the effects of green technology innovation on regional carbon emissions. Firstly, we conduct a feature selection analysis on the factors influencing regional carbon emissions using causal inference methods based on machine learning. Subsequently, we explore the conditional and marginal treatment effects of green technology innovation on regional carbon emissions using the heterogeneous treatment effect model. Finally, we investigate the dynamic effects of green technology innovation on regional carbon emissions across different periods. Empirical results indicate that firstly, green technology innovation indirectly reduces regional carbon emissions by promoting energy efficiency improvement; secondly, the impact of green technology innovation on carbon emissions exhibits significant regional heterogeneity, with the largest effect observed in the eastern region, followed by the western region and the smallest effect in the central region; thirdly, at a significance level of 5%, green technology innovation has a direct inhibitory effect on carbon emissions in certain regions.