Simulation of China’s Carbon Emission based on Influencing Factors

China is one of the world’s largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China’s carbon emissions by constructing a system dynamics model of China’s carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China’s carbon emissions. The contribution rates of the five factors to China’s carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China’s carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China’s carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small

An Analysis of Agricultural Production Efficiency of Yangtze River Economic Belt Based on a Three-Stage DEA Malmquist Model

The Yangtze River Economic Belt (YREB) is a major national strategic development area in China, and the development of the YREB will greatly promote the development of the entirety China, so research on its agricultural production efficiency is also of great significance. This paper is committed to studying the agricultural production efficiency of 11 provinces in the YREB and adopts a combination of the Data Envelopment Analysis (DEA) model and the Malmquist index to make a dynamic and static analysis on the YREB’s agricultural production efficiency from 2010 to 2019. Then, a three-stage DEA Malmquist model that eliminates the factors of random interference and management inefficiency is compared to a model without elimination. The results show that the adjusted technological efficiency changes, technological progress, and total factor productivity increased by −0.1%, 0.24%, and 0.22%, respectively. When comparing these values to the pre-adjustment values, the results indicate that the effect of environmental variables cannot be ignored when studying the agricultural production efficiency of the YREB. At the same time, the differences in the agricultural production efficiency in the YREB are reasonably explained, and feasible suggestions are put forward

Impact of Industrial Structure Upgrading on Green Total Factor Productivity in the Yangtze River Economic Belt

The Yangtze River economic belt is an inland river economic belt with international influence composed of 11 provinces and municipalities in the Yangtze River Basin. This paper uses the super-efficiency model to calculate the green total factor productivity of 11 provinces and municipalities in the Yangtze River economic belt (YREB). Then we establish a model to study the impact of industrial structure upgrading, industrial structure rationalization, and environmental regulation on green total factor productivity (GTFP). Empirical analysis shows that the industrial structure upgrading and environmental regulation have a significant impact on GTFP and show regional characteristics. The more developed the economy and the higher the industrial structure, the greater the impact of upgrading and environmental regulation on GTFP. Compared with other control variables, the urbanization rate impacts GTFP, followed by regional economic development

The Impact of Innovation-Driven Strategy on High-Quality Economic Development: Evidence from China

It is of great significance to study the impact of innovation-driven strategy on high-quality development. This paper investigates the relationship between the economic development quality index (EDQI) and the innovation-driven index (IDI) using the entropy method based on China’s macroeconomic data from 2000 to 2019. It examines the impacts of innovation-driven strategy on the economy using systematic cluster analysis and the impact of innovation on economic development quality through regression analyses. Results of empirical analyses illustrate that the innovation-driven strategy of China has played an important role in the quality of economic development. Still, the lack of hard innovation leads to primary and secondary industries’ insufficient development quality. Different innovation indicators have different effects, and the overall efficiency of financial research funds is insufficient. Further, the results also show that the positive role of innovation-driven strategy is mainly realized through high-tech markets in China. Therefore, R&D investment should focus on high-tech industries or fields related to the national economic lifeline or strategic industries, such as environmental protection, microchips, and high-end instruments industries in China. This paper attempts to study the effect of China’s innovation-driven strategy on the quality of economic development to provide reference experience for developing countries’ sustainable economic development

Simulation of China’s Carbon Emission based on Influencing Factors

China is one of the world’s largest energy consumers and carbon emitters, and the situation of carbon emission reduction is serious. This paper forecasts the future trend of China’s carbon emissions by constructing a system dynamics model of China’s carbon emissions. The results show that China cannot fulfill its commitment to peak its carbon emissions in 2030 as scheduled. Secondly, the Logarithmic Mean Divisia Index model (LMDI) was used to analyze the influencing factors of China’s carbon emissions. The contribution rates of the five factors to China’s carbon emissions are as follows: economic development (226.30%), technological innovation (−105.92%), industrial structure (−26.55%), population scale (11.44%) and energy structure (−5.28%). Finally, this paper formulates five carbon emission reduction paths according to the size and direction of various factors that affect China’s carbon emissions. The paths of carbon emission reduction were simulated by using the system dynamics model of China’s carbon emissions. It is found that technological innovation is the key pathway for China to realize its commitment to carbon emission reduction. Slowing economic growth will delay the arrival time of peak carbon emissions and increase the intensity of carbon emissions. Optimizing the industrial structure, reducing the population scale and adjusting the energy structure can reduce the peak and carbon emissions in China, but the effect is small

Influence of Green Finance on Ecological Environment Quality in Yangtze River Delta

Along with the development of society and the deepening contradiction between economic growth and natural resources, green finance has attracted more and more attention. As an area of great strategic significance in China’s modernization, the development of green finance can improve the quality of its ecological environment and find new economic growth points for it. Based on the index system of pressure state response and while considering the scientific nature and desirability of the indicators, this paper selects 12 indicators to construct an index system of eco-environmental quality. It uses the entropy method to calculate the level of eco-environmental quality. Then, three control variables are selected, and the difference-in-difference model is used for empirical analysis. It is found that green finance positively affects the ecological environment quality of the Yangtze River Delta. In addition, the level of opening to the outside world and the level of economic development also have a positive effect on the quality of the ecological environment to a certain extent. Still, the impact of industrial structure on it is negative. Therefore, this paper puts forward some suggestions for strengthening the disclosure of green financial information, paying attention to the concept of green development and strengthening regional cooperation and exchange to promote the development of green finance further and promote the coordination of economic development and ecological protection in the Yangtze River Delta