Does government intervention affect CO(2) emission reduction effect of producer service agglomeration? Empirical analysis based on spatial Durbin model and dynamic threshold model

Achieving carbon peak and carbon neutrality is an inherent requirement for countries to promote green recovery and transformation of the global economy after the COVID-19 pandemic. As “a smoke-free industry,” producer services agglomeration (PSA) may have significant impacts on CO(2) emission reduction. Therefore, based on the nightlight data to calculate the CO(2) emissions of 268 cities in China from 2005 to 2017, this study deeply explores the impact and transmission mechanism of PSA on CO(2) emissions by constructing dynamic spatial Durbin model and intermediary effect model. Furthermore, the dynamic threshold model is used to analyze the nonlinear characteristics between PSA and CO(2) emissions under different degrees of government intervention. The results reveal that: (1) Generally, China’s CO(2) emissions are path-dependent in the time dimension, showing a “snowball effect.” PSA significantly inhibits CO(2) emissions, but heterogeneous influences exist in different regions, time nodes, and sub-industries; (2) PSA can indirectly curb CO(2) emissions through economies of scale, technological innovation, and industrial structure upgrading. (3) The impact of PSA on China’s CO(2) emissions has an obvious double threshold effect under different degree of government intervention. Accordingly, the Chinese government should increase the support for producer services, dynamically adjust industrial policies, take a moderate intervention, and strengthen market-oriented reform to reduce CO(2) emissions. This study opens up a new path for the low-carbon economic development and environmental sustainability, and also fills in the theoretical gaps on these issues. The findings and implications will offer instructive guideline for early achieving carbon peak and carbon neutrality.