Research on the spatial effect and threshold effect of industrial structure upgrading on carbon emissions in China

Abstract

Based on panel data from 2000 to 2017 in 29 Chinese provinces, this paper analyzes the impact of industrial structure upgrading on carbon emissions by constructing a spatial panel model and a panel threshold model. The results show that (1) there is a significant spatial correlation between carbon emissions in Chinese provinces, and the carbon emissions of a province are affected by the carbon emissions of surrounding provinces; (2) in China, carbon emissions have a significant time lag feature, and current carbon emissions are largely affected by previous carbon emissions; (3) industrial structure upgrading can effectively promote carbon emission reductions in local areas, and the impact of industrial structure upgrading on carbon emissions has a significant threshold effect. With continued economic development, the promotion effect of industrial structure upgrading on carbon emission reductions will decrease slightly, but this carbon emission reduction effect is still significant. (4) In addition, there is a clear difference between the impact of energy consumption intensity and population size on carbon emissions in short and long terms. In the short term, the increase in energy consumption intensity and the expansion of population size not only increase the carbon emissions of a local area but also increase the carbon emissions of neighboring areas. In the long term, the impact of energy consumption intensity and population size on carbon emissions of neighboring areas will be weakened, but the promotion impact on carbon emissions in local areas will be strengthened.

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

“…and Zhang [ 52 , 55 ]. From the general rule of industrial structure evolution, the shift of industrial structure center of gravity from primary to tertiary industries is often accompanied by the gradual replacement of traditional industries by low-pollution, low-energy-consuming and high-value-added new industries, which not only improves factor production efficiency but also reduces energy consumption intensity, thus positively influencing the reduction of carbon emissions [ 13 , 14 , 20 ]. Therefore, it is recommended that Chinese provinces continue to accelerate the pace of industrial transformation and upgrading, promote the industrial structure in the direction of advanced development, encourage the transformation and upgrading of traditional industries, improve industrial efficiency, and strive to achieve low energy consumption and high output while accelerating the formation of knowledge- and technology-intensive industries such as strategic emerging industries and high-tech industries.…”

“…Industrial restructuring, together with more environmentally friendly and efficient energy-saving and emission-reduction technologies, can bring about advanced and new production technologies. The improvement of production technology and the increased technical content of products can effectively improve production efficiency, elevate energy efficiency, reduce factor inputs and pollution emissions per unit of output, and weaken the negative environmental externalities caused by production processes [ 13 , 14 ]. Therefore, industrial restructuring is one of the important means to achieve economic transformation and reduce carbon emissions [ 15 ].…”

Digital Economy and Environmental Quality: Insights from the Spatial Durbin Model

“…Therefore, whether the secondary or tertiary industry dominates the industrial structure is related to carbon dioxide emission intensity. This is calculated by the ratio of the tertiary industry to the secondary industry [ 61 ].…”

Fiscal decentralization, industrial structure upgrading and carbon emission: Evidence from China

“…The mediating effect showed that the upgrading of industrial structure could reduce carbon dioxide emissions by improving energy efficiency. In addition, some scholars believe that the impact of industrial structure upgrading on carbon emissions can not only promote regional carbon emission reduction, but also have a significant threshold effect (Li and Zhou, 2021). Wei and Zhang(2020) employed the panel smooth transition regression (PSTR) model to investigate the nonlinear effects of the upgrading of industrial structure and CO2 emissions in China.…”