A spatial effect study on digital economy affecting the green total factor productivity in the Yangtze River Economic Belt

Impacts of industrial agglomeration on the energy consumption structure's low-carbon transition process: A spatial and nonlinear perspective

Based on panel data collected from 2003 to 2020 across 30 provinces in China, the paper employs the spatial vector angle method and spatial Durbin model to investigate industrial agglomeration's nonlinear and spatial spillover effects on the energy consumption structure's low-carbon transition process (Lct). The results indicate the following: First, the influence of industrial agglomeration on Lct exhibits an inverted U-shaped pattern. As the degree of industrial agglomeration expands, its effect on Lct shifts from positive to negative. Second, industrial agglomeration demonstrates spatial spillover effects. It promotes the improvement of Lct in neighboring provinces through agglomeration effects. However, the continuous expansion of industrial agglomeration inhibits the improvement of Lct in neighboring provinces through congestion effects. Third, the heterogeneity test finds that industrial agglomeration has a significant role in promoting Lct in the samples of eastern region, but this effect is not significant in the samples of western and middle regions.

Can digitalization effectively promote green energy efficiency? The linear and nonlinear relationship analysis

In light of the integration of digitalization and the energy revolution, digitalization can be integrated into the energy industry to develop energy-saving technologies and improve resource allocation efficiency. On the basis of 2013-2019 Chinese provincial panel data, this paper measures the level of green energy efficiency based on the super-EBM-DEA model and analyzes the linear relationship, nonlinear relationship, and potential mechanism between digitalization and green energy efficiency. The findings indicate that (1) overall, both China's digitalization and green energy efficiency formed a steady upward trajectory during the sample period. Digitalization showed a spatial characteristic of extending and spreading from the eastern region to the central and western regions. Green energy efficiency was characterized by obvious regional heterogeneity. (2) Progress in digitalization has a significant driving effect on green energy efficiency. Subdimensional analysis shows that this driving effect mainly comes from digital development and digital transactions. (3) The impact of digitalization on green energy efficiency presents a threshold effect of economic agglomeration (with a threshold of 0.0257 and a marginally increasing, positive driving trend) and population agglomeration (with a threshold of 4.2750 and a marginally decreasing, positive driving trend). (4) Decomposing changes in green energy efficiency into scale efficiency and pure technical efficiency, this study shows that pure technical efficiency gains due to digitalization are the main driver of green energy efficiency improvements. Finally, some specific policy recommendations are proposed.

Digital economy and carbon emission: The coupling effects of the economy in Qinghai region of China

This study provides an in-depth analysis of the complex relationship between the digital economy and carbon emissions, fully drawing on essential principles of environmental economics, coupled economics, and sustainable development theory. Focusing on the Qinghai region in the western province of China, the study employs highly sophisticated methods such as multiple regression analysis and system dynamics modeling to reveal the multidimensional coupling effects between digital economy development and carbon emission dynamics. The study's results clearly show that in the Qinghai region of China, the booming growth of the digital economy is related to carbon emissions. Of particular interest, the study finds that this relationship exhibits a high degree of complexity and non-linearity and evolves gradually over time. Initially, the rapid expansion of the digital economy, accompanied by high energy consumption and increased carbon emissions, posed a significant challenge to environmental protection. However, a clear inverted "U"-shaped relationship has emerged as the digital economy evolves. This key inflection point signals a shift in the landscape as the digital economy begins to deliver some ecological benefits, potentially reducing the trend of carbon emissions in the future. The findings of this study go beyond simple causality and reveal a complex and evolving dynamic relationship between the digital economy and carbon emissions. Through such insights, this study provides a solid academic foundation and carefully constructs actionable policy recommendations to drive sustainable development. These insights apply to the Qinghai region of China and provide valuable references and lessons for other areas facing similar challenges.

The impact of the digital economy on low-carbon innovation in the Yangtze River Delta region

This study narrows its focus to the Yangtze River Delta, an important region in China known for its advancements in both digital economy and low-carbon technology. In contrast to previous studies, we also examine the heterogeneous effects between central and non-central cities, as well as the role of local financial development, when analyzing the impact of the digital economy on low-carbon innovation. Based on the data of 41 cities from 2011 to 2019, we find a significant direct promoting effect of the digital economy on low-carbon innovation. Furthermore, the development of the digital economy indirectly enhances low-carbon innovation through local financial development. The heterogeneous analysis reveals a positive impact of the digital economy on low-carbon innovation in both central and non-central cities, with a stronger effect observed in non-central cities. These findings suggest several policy recommendations, including promoting digital economy and finance, green finance, and fostering regional integration in the Yangtze River Delta.

Study on the coupling coordination development of China's multidimensional digital economy and industrial carbon emission efficiency

Exploring the coupling coordination between China's digital economy (DE) and industrial carbon emission efficiency (ICEE) is of great significance for achieving sustainable development goals. In the study, a multidimensional indicator system was established to evaluate DE, and spatiotemporal analysis and network analysis methods were used to reveal the dynamic evolution characteristics of DE and ICEE. The coupling coordination model and convergence model were adopted to explore the development trend of coupling coordination between DE and ICEE. The results show that the ICEE and DE in various provinces of China exhibit obvious spatial heterogeneity and spillover effects. Currently, the coupling coordination degree between the development of China's DE and ICEE has reached the level of primary coordination or above. The coupling coordination degree between DE and ICEE in the eastern, central, and northeastern regions has reached an intermediate level or above, with the highest degree in the eastern region. The fluctuation of China's ICEE has consistent σ-convergence and β-convergence, and the convergence effect is higher with the introduction of the DE than without it. The condition β-convergence result indicates that underdeveloped regions can narrow the gap between their ICEE and that of developed regions by utilizing their resource endowments, industrial structure, human capital, and other conditions, improving emission reduction measures and policies. This study provides a certain reference for the green and low-carbon development of industry in China and other developing countries in the digital economy era.

A novel evaluation system of green development level in the Three Gorges Reservoir Area and its spatial-temporal pattern

Evaluating the green development level (GDL) of a region will accelerate its economic transformation and promote ecological civilization. From the perspective of complex system, this study explores the green development level (GDL) of the Three Gorges Reservoir Area (TGRA) by constructing a novel and ecology-oriented evaluation system. The system is three-dimensional including indicators of environmental protection and utilization, green economy development, social harmony and prosperity. Resource elements are highly valued; inclusive society is fully considered. Overall entropy method and expert scoring method are integrated to assess the GDL of 26 regions in the TGRA from 2000 to 2020; the temporal and spatial characteristics of the GDL are examined through exploratory spatial data analysis (ESDA). The results show that (1) the GDL of the TGRA is at a medium level with the score fluctuating from 0.3 to 0.4 and the ecological protection with weight of 0.37 contributes greatly to the GDL. (2) Despite the high degree of coupling coordination, the complex ecosystem in the TGRA remains at a low level of coordinated development. (3) The GDL in the middle part of the TGRA is the highest, followed by the upper part and the lower part, and the gap is narrowing. (4) The global spatial correlation of the GDL is not obvious. The spatial spillover effect is not significant and clusters only appear in the upper part and the lower part. Finally, some reasonable suggestions are put forward for improving the GDL.

Can the digital economy development achieve the effect of pollution reduction? Evidence from Chinese Cities

As a new economic form, the digital economy is not only empowering new impetus to economic growth, but also reshaping specific business forms of economical operation. Therefore, we conducted an empirical test to verify the impact and mechanism of pollution reduction in the digital economy, based on the panel data of 280 prefecture-level cities in China from 2011 to 2019. The results show that, first the development of the digital economy indeed has the positive effect of realizing pollution reduction. The results of mediating effect test indicate the influence mechanism mainly rely on promoting the upgrading of industrial structure (structural effect) and upgrading the level of green technology innovation (technical effect). Second, the results of regional heterogeneity analysis show that the emission reduction effect of digital economy development on four pollutants is characterized by weakness in the east and strong in the west in regional distribution. Third, the development of digital economy has a threshold effect on the level of economic development to achieve its pollution reduction effect. Further identification of the threshold effect indicates that the higher the level of economic development, the better in emission reduction effect.

Exploring the Mechanism of the Impact of Green Finance and Digital Economy on China's Green Total Factor Productivity

In the context of the "double cycle," promoting the development of a green economy is an important goal for China's high-quality economic development in the digital age. This paper uses data from 30 provinces (municipalities and autonomous regions) in China during the 2006-2019 period using the Compiled Green Finance Index (GF) and Digital Economy Index (DE). The interrelationship between green finance, digital economy and green total factor productivity (GTFP) is empirically tested by conducting multiple regressions on panel data from 2006-2019 to perform an empirical analysis. Based on this, further analysis was performed with the threshold model. This study found that green finance and digital economy can contribute well to green total factor productivity, but the combination of the two does not have a good effect on green total factor productivity. Further study found that the green finance and digital economy's contribution to green total factor productivity is mainly derived from technological progress. The regression results based on the panel threshold model show that the more underdeveloped the digital economy is in certain regions, the stronger the role of green finance in promoting efficiency improvement. Therefore, policymakers should formulate differentiated green financial policies according to the level of development of the digital economy and give play to the role of green finance and the digital economy in promoting green total factor productivity.