When will China's industrial carbon emissions peak? Evidence from machine learning.

The manufacture of products in the industrial sector is the principal source of carbon emissions. To slow the progression of global warming and advance low-carbon economic development, it is essential to develop methods for accurately predicting carbon emissions from industrial sources and imposing reasonable controls on those emissions. We select a support vector machine to predict industrial carbon emissions from 2021 to 2040 by comparing the predictive power of the BP (backpropagation) neural network and the support vector machine. To reduce noise in the input variables for BP neural network and support vector machine models, we use a random forest technique to filter the factors affecting industrial carbon emissions. The statistical results suggest that BP's neural network is insufficiently adaptable to small sample sizes, has a relatively high error rate, and produces inconsistent predictions of industrial carbon emissions. The support vector machine produces excellent fitting results for tiny sample data, with projected values of industrial carbon dioxide emissions that are astonishingly close to the actual values. In 2030, carbon emissions from the industrial sector will have reached their maximum level.

What drives the green transformation of enterprises? A case of carbon emissions trading pilot policy in China.

As an important policy instrument to achieve greenhouse gas emission reduction, carbon emissions trading has also promoted the green transformation of enterprises while achieving carbon reduction targets. This study uses the implementation of the Chinese carbon emissions trading pilot policy (CETPP) as a quasi-natural experiment and analyzes the impacts of the CETPP on the green transformation of enterprises with the difference-in-differences (DID) method based on a sample of 297 listed Chinese A-share high-energy-consuming enterprises. The result findings show that CETPP can significantly promote the green transformation of enterprises. The heterogeneity analysis also reveals that CETPP has differential effects on enterprises belonging to different industries, which is caused by the fact that enterprises in different industries differ significantly in their green transformation paths and modes. Moreover, CETPP has a significant facilitating effect on the green transformation of non-state-owned enterprises compared to state-owned enterprises. Finally, marketization and enterprise social responsibility are two major mechanisms for the CETPP to promote the green transformation of enterprises. Our findings reveal that policymakers should further deepen the dynamic management of carbon emission allowances and guide enterprises to actively undertake social responsibility, thus leveraging the market regulation mechanism to promote the green transformation of enterprises.

Can new energy demonstration city policy reduce carbon emissions? A quasi-natural experiment from China.

Against achieving carbon peaking by 2030 and carbon neutrality by 2060 context in China, the new energy demonstration city policy (NEDCP) has a crucial function to perform in promoting resource utilization efficiency, building the green development policy system, and facilitating carbon emission reduction. However, existing research has rarely investigated the contribution of NEDCP on carbon reduction. To investigate the policy effect of NEDCP, the differences-in-differences (DID) model is introduced to quantify the influence of NEDCP on carbon reduction, taking a statistical sample of 285 Chinese cities over the period 2005-2017 on the basis of exploring the intrinsic mechanism of NEDCP on carbon emissions. The statistical results reveal that NEDCP significantly inhibits carbon emissions. NEDCP's dampening impact on carbon reduction is more pronounced in the eastern area but not in other areas. City size and resource endowment heterogeneity results suggest that NEDCP significantly inhibits the output of carbon emissions in non-resource-based and large cities but insignificantly in resource-based and small- and medium-sized cities. Finally, we conclude that policy-makers should not only broaden the scope of NEDCP implementation continuously but also design relevant policy combination tools following the basic characteristics of each city to provide institutional guarantees for achieving carbon emission reduction.

Can carbon emission trading pilot policy drive industrial structure low-carbon restructuring: new evidence from China.

Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals.

The impact of local government competition and green technology innovation on economic low-carbon transition: new insights from China.

The government-led Chinese economic development system determines that local government competition is a significant factor affecting the economic low-carbon transition. Driving an economic development mode with green technology innovation as the core is the critical path to realizing an economic low-carbon transition. Consequently, it is of significant practical relevance to investigate the impact of local government competition and green technology innovation on the economic low-carbon transition under the government-led Chinese economic development system. This paper systematically explores the nexus between green technology innovation and economic low-carbon transition in terms of local government competition perspective using the system generalized method of moments, panel threshold model, and geographically weighted regression on the basis of a dataset of 30 provincial administrative areas in China from a period of 2006-2019. The results indicate that green technology innovation significantly promotes the economic low-carbon transition. Local government competition not only significantly dampens the economic low-carbon transition but also considerably inhibits the positive effect of green technology innovation on the economic low-carbon transition. A significant N-shaped association is evident between green technology innovation and the economic low-carbon transition when green technology innovation is applied as a threshold, while such association is insignificant when local government competition is used as a threshold. Compared with high-competition intensity areas, green technology innovation promotes economic low-carbon transition weaker in low- competition intensity areas, while local government competition inhibits economic low-carbon transition stronger. However, local government competition significantly inhibits the positive effect of green technology innovation on the economic low-carbon transition in low-competition intensity areas, while insignificant in high-competition intensity areas. The geographically weighted regression technique as a whole also verified the above results. Therefore, policymakers should not only increase research and development investment in green technologies, but also develop a regionally linked low-carbon emission reduction system to avoid ineffective competition among governments to facilitate the earlier fulfillment of the "dual carbon" goal.