This paper uses an input-output table of China's provinces(2007-2016) to measure carbon emissions of these industries.It employs a Malmquist-Luenberger(ML) index with expected and undesired outputs,and an absolute...This paper uses an input-output table of China's provinces(2007-2016) to measure carbon emissions of these industries.It employs a Malmquist-Luenberger(ML) index with expected and undesired outputs,and an absolute β convergence and a conditional β convergence model,to conduct an in-depth analysis of dynamic changes and spatial convergence.Carbon emission efficiency of forest processing industries in 25 regions,including Shanghai,Chongqing,Zhejiang,and Jiangsu are increasing,whereas those of Tianjin,Liaoning,Heilongjiang,and Tibet are decreasing.The main contributing factors of carbon emission efficiency in three major regions vary over time.Further,carbon emission efficiency in the eastern,central,and western regions all have absolute β convergence and conditional β convergence,indicating that different regions are developing toward their own goals and industry,yet regions with lower efficiency are catching up with those where with more efficient strategies in place.Finally,this paper proposes according recommendations.展开更多
To measure the carbon emission efficiency of China’s pharmaceutical manufacturing industry, explore the factors affecting the carbon emission efficiency of China’s pharmaceutical manufacturing industry, and provide ...To measure the carbon emission efficiency of China’s pharmaceutical manufacturing industry, explore the factors affecting the carbon emission efficiency of China’s pharmaceutical manufacturing industry, and provide reference for improving the carbon emission efficiency of China’s pharmaceutical manufacturing industry and promoting the government to formulate macro policies. Based on the data of the pharmaceutical manufacturing industry in 30 provinces of China from 2010 to 2019, and based on the SBM model and ML (Malmquist-Luenberger) index model, the carbon emission efficiency of the pharmaceutical manufacturing industry was calculated and its dynamic change was investigated, and the Tobit model was further used to explore the influencing factors of the carbon emission efficiency of the pharmaceutical manufacturing industry. The carbon emission efficiency of China’s inter-provincial pharmaceutical manufacturing industry has steadily improved. The carbon emission efficiency of the eastern region is higher than that of the western region, and that of the western region is higher than that of the central region. The eastern region is dominated by technological progress, and there is room for improvement in technological efficiency. The central and western regions are dominated by technological efficiency. Compared with technological efficiency, technological progress needs to be further improved. Environmental regulation, industrial agglomeration and technological innovation level positively affect carbon emission efficiency, while foreign investment level has no significant impact on carbon emission efficiency.展开更多
文摘This paper uses an input-output table of China's provinces(2007-2016) to measure carbon emissions of these industries.It employs a Malmquist-Luenberger(ML) index with expected and undesired outputs,and an absolute β convergence and a conditional β convergence model,to conduct an in-depth analysis of dynamic changes and spatial convergence.Carbon emission efficiency of forest processing industries in 25 regions,including Shanghai,Chongqing,Zhejiang,and Jiangsu are increasing,whereas those of Tianjin,Liaoning,Heilongjiang,and Tibet are decreasing.The main contributing factors of carbon emission efficiency in three major regions vary over time.Further,carbon emission efficiency in the eastern,central,and western regions all have absolute β convergence and conditional β convergence,indicating that different regions are developing toward their own goals and industry,yet regions with lower efficiency are catching up with those where with more efficient strategies in place.Finally,this paper proposes according recommendations.
文摘To measure the carbon emission efficiency of China’s pharmaceutical manufacturing industry, explore the factors affecting the carbon emission efficiency of China’s pharmaceutical manufacturing industry, and provide reference for improving the carbon emission efficiency of China’s pharmaceutical manufacturing industry and promoting the government to formulate macro policies. Based on the data of the pharmaceutical manufacturing industry in 30 provinces of China from 2010 to 2019, and based on the SBM model and ML (Malmquist-Luenberger) index model, the carbon emission efficiency of the pharmaceutical manufacturing industry was calculated and its dynamic change was investigated, and the Tobit model was further used to explore the influencing factors of the carbon emission efficiency of the pharmaceutical manufacturing industry. The carbon emission efficiency of China’s inter-provincial pharmaceutical manufacturing industry has steadily improved. The carbon emission efficiency of the eastern region is higher than that of the western region, and that of the western region is higher than that of the central region. The eastern region is dominated by technological progress, and there is room for improvement in technological efficiency. The central and western regions are dominated by technological efficiency. Compared with technological efficiency, technological progress needs to be further improved. Environmental regulation, industrial agglomeration and technological innovation level positively affect carbon emission efficiency, while foreign investment level has no significant impact on carbon emission efficiency.
