Improving energy efficiency is regarded as a key path to tackling global warming and achieving the Sustainable Development Goals(SDGs).In 2020,the energy consumption of the world's ten major energy-consuming count...Improving energy efficiency is regarded as a key path to tackling global warming and achieving the Sustainable Development Goals(SDGs).In 2020,the energy consumption of the world's ten major energy-consuming countries accounted for 66.8%of the global total.This paper applied data envelopment analysis(DEA)to calculate these ten major energyconsuming countries'total-factor energy efficiency(TFEE)at national and sectoral levels from 2001-2020,and explored the infuencing factors of total-factor energy efficiency with the Tobit regression model.The results showed significant difference in the ten countries'energy efficiency.The United States and Germany topped the list for total-factor energy efficiency,while China and India were at the bottom.Meanwhile,the energy efficiency of the industrial subsector has increased significantly over the past two decades,while that of the other subsectors has been relatively fat.The industrial structure upgrading,per capita GDP,energy consumption structure,and foreign direct investment had significant impacts on energy efficiency with national heterogeneity.Energy consumption structure and GDP per capita were determinative factors of energy efficiency.展开更多
Using 1995-2006 panel data for 210 cities,this article firstly measures total factor energy efficiency for Chinese cities with constant return to scale data envelopment analysis model,and then describes the features o...Using 1995-2006 panel data for 210 cities,this article firstly measures total factor energy efficiency for Chinese cities with constant return to scale data envelopment analysis model,and then describes the features of regional differences.The results show that the changing trend displays four "reversed U" shapes.A turning point of widening gap occurred among cities in 2000 and there was a certain convergence among four regions.Urban energy efficiency level is unstable.Cities with low efficiency and high energy input will be the focus of energy-saving and reducing emissions.According to Tobit model,resource endowment,temperature,industrial structure,technology level and variety of policy factors should be treated differently in different situations.展开更多
The study on the enterprise＇s energy efficiency is one of the most important fields of energy efficiency research. Most studies used DEA and aggregate data to estimate the energy efficiency of enterprises. In this st...The study on the enterprise＇s energy efficiency is one of the most important fields of energy efficiency research. Most studies used DEA and aggregate data to estimate the energy efficiency of enterprises. In this study, based on Cobb-Douglas production function, we make a SFA model which takes the energy input and CO2 emission into account. By using the SFA model, we calculate the refineries＇ total-factor energy efficiency with Sinopec refineries＇ micro-data from 2004 to 2009. Meanwhile, we do empirical study on the factors which influence the energy efficiency. In the last, we put forward some advices so as to improve energy efficiency.展开更多
This paper analyzed regional industrial energy efficiency in China with Total-Factor Energy Efficiency （TFEE）. The East region has the best energy efficiency and the Central and the West regions stand as the second ...This paper analyzed regional industrial energy efficiency in China with Total-Factor Energy Efficiency （TFEE）. The East region has the best energy efficiency and the Central and the West regions stand as the second and the third respectively. However, it is found that industrial energy efficiency of all regions increased from 1998 to 2006. This result is consistent with level of economic development of every region. The industries of all provinces in China are not yet at the frontier efficiency position, therefore, to the frontier as target, their technol- ogy levels and production processes should be adjusted accordingly. Compared with the conventional energy efficiency, the inverse of energy intensity, which is defined as the ratio of actual output to energy input, is regarded as Single-Factor Energy Efficiency （SFEE） index. Although TFEE ranks are not changed for each region, they are different for each province. The comparative result also shows that the substitution among inputs （labor, capital stock, and energy） to produce the output is significant. The SFEE scores could be over-estimated if energy is taken as the single input in the production. Finally, we identified determining factors affecting industrial energy efficiency using Tobit model. The results indicate that an increase of per capita Gross Domestic Product （GDP）, the percentage of output value of industry invested by Hong Kong, Macao, Taiwan and abroad, energy price and investment of scientific and technological activities for industry could be possible contributors and drivers to the industrial energy efficiency. However, increasing of heavy industry will lead to worse industrial energy efficiency.展开更多
基金supported by the National Natural Science Foundation of China (Nos.71761147001 and 42030707)the International Partnership Program by the Chinese Academy of Sciences (No.121311KYSB20190029)the Fundamental Research Fund for the Central Universities (No.20720210083)。
文摘Improving energy efficiency is regarded as a key path to tackling global warming and achieving the Sustainable Development Goals(SDGs).In 2020,the energy consumption of the world's ten major energy-consuming countries accounted for 66.8%of the global total.This paper applied data envelopment analysis(DEA)to calculate these ten major energyconsuming countries'total-factor energy efficiency(TFEE)at national and sectoral levels from 2001-2020,and explored the infuencing factors of total-factor energy efficiency with the Tobit regression model.The results showed significant difference in the ten countries'energy efficiency.The United States and Germany topped the list for total-factor energy efficiency,while China and India were at the bottom.Meanwhile,the energy efficiency of the industrial subsector has increased significantly over the past two decades,while that of the other subsectors has been relatively fat.The industrial structure upgrading,per capita GDP,energy consumption structure,and foreign direct investment had significant impacts on energy efficiency with national heterogeneity.Energy consumption structure and GDP per capita were determinative factors of energy efficiency.
基金provided by the major issues of philosophy and social science research projects of Chinese Ministry of Education(Project no.:09JZD0019)
文摘Using 1995-2006 panel data for 210 cities,this article firstly measures total factor energy efficiency for Chinese cities with constant return to scale data envelopment analysis model,and then describes the features of regional differences.The results show that the changing trend displays four "reversed U" shapes.A turning point of widening gap occurred among cities in 2000 and there was a certain convergence among four regions.Urban energy efficiency level is unstable.Cities with low efficiency and high energy input will be the focus of energy-saving and reducing emissions.According to Tobit model,resource endowment,temperature,industrial structure,technology level and variety of policy factors should be treated differently in different situations.
文摘The study on the enterprise＇s energy efficiency is one of the most important fields of energy efficiency research. Most studies used DEA and aggregate data to estimate the energy efficiency of enterprises. In this study, based on Cobb-Douglas production function, we make a SFA model which takes the energy input and CO2 emission into account. By using the SFA model, we calculate the refineries＇ total-factor energy efficiency with Sinopec refineries＇ micro-data from 2004 to 2009. Meanwhile, we do empirical study on the factors which influence the energy efficiency. In the last, we put forward some advices so as to improve energy efficiency.
文摘This paper analyzed regional industrial energy efficiency in China with Total-Factor Energy Efficiency （TFEE）. The East region has the best energy efficiency and the Central and the West regions stand as the second and the third respectively. However, it is found that industrial energy efficiency of all regions increased from 1998 to 2006. This result is consistent with level of economic development of every region. The industries of all provinces in China are not yet at the frontier efficiency position, therefore, to the frontier as target, their technol- ogy levels and production processes should be adjusted accordingly. Compared with the conventional energy efficiency, the inverse of energy intensity, which is defined as the ratio of actual output to energy input, is regarded as Single-Factor Energy Efficiency （SFEE） index. Although TFEE ranks are not changed for each region, they are different for each province. The comparative result also shows that the substitution among inputs （labor, capital stock, and energy） to produce the output is significant. The SFEE scores could be over-estimated if energy is taken as the single input in the production. Finally, we identified determining factors affecting industrial energy efficiency using Tobit model. The results indicate that an increase of per capita Gross Domestic Product （GDP）, the percentage of output value of industry invested by Hong Kong, Macao, Taiwan and abroad, energy price and investment of scientific and technological activities for industry could be possible contributors and drivers to the industrial energy efficiency. However, increasing of heavy industry will lead to worse industrial energy efficiency.
