Does government intervention affect CO2 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 CO2 emission reduction. Therefore, based on the nightlight data to calculate the CO2 emissions of 268 cities in China from 2005 to 2017, this study deeply explores the impact and transmission mechanism of PSA on CO2 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 CO2 emissions under different degrees of government intervention. The results reveal that: (1) Generally, China's CO2 emissions are path-dependent in the time dimension, showing a "snowball effect." PSA significantly inhibits CO2 emissions, but heterogeneous influences exist in different regions, time nodes, and sub-industries; (2) PSA can indirectly curb CO2 emissions through economies of scale, technological innovation, and industrial structure upgrading. (3) The impact of PSA on China's CO2 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 CO2 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.

Does the opening of high-speed railways improve urban livability? Evidence from a quasi-natural experiment in China

With the spread of “urban disease”, urban livability has aroused common concern in academic circles at home and abroad. High-speed railway opening is substantially affecting the development of cities. Based on the data of 271 cities in China from 2005 to 2018, this paper applies the entropy method to calculate urban livability level, and then the difference-in-differences (DID) model and mediatory effect model are constructed to test the impact and mechanism of high-speed railway (HSR) opening on urban livability. The findings show that: (1) Overall, HSR opening has significantly improved urban livability by 13.04%. After alleviating the endogenous problem and conducting a series of robustness tests, the conclusions are still valid. (2) Mechanism analysis indicates that HSR opening improves urban livability by promoting economic growth, talent agglomeration and industrial structure upgrading. Among them, the industrial structure upgrading effect is the strongest, followed by talent agglomeration and economic growth. (3) The heterogeneity analysis shows that the promotion effect of HSR opening on urban livability is more significant in the central and western regions and large-sized cities. Accordingly, the feasible path to improve urban livability through HSR opening is proposed. Finally, in the face of the impact of the COVID-19 pandemic on the world economy, more channels to enhance urban livability are expected to cope with the future “the global talent war”.