The existing oil import dependence index cannot exactly measure the economic cost or scales, and it is difficult to describe the economical aspect of oil security. To measure the foreign dependence of one country'...The existing oil import dependence index cannot exactly measure the economic cost or scales, and it is difficult to describe the economical aspect of oil security. To measure the foreign dependence of one country's economy and reflect its oil economic security, this paper defines the net oil import intensity as the ratio of net oil import cost to GDP. By using Divisia Index Decomposition, the change of net oil import intensity in five industrialized countries and five newly industrialized countries during 1971—2010 is decomposed into five factors: oil price, oil intensity, oil self-sufficiency, domestic price level and exchange rate. The result shows that the dominating factors are oil price and oil intensity; moreover, the newly industrialized countries have higher net oil import intensity than industrialized countries.展开更多
This paper quantifies a decomposition analysis of energy-related CO2 emissions in the industrial sectors of Shanghai over the period 1994-2007.The Log-Mean Divisia Index(LMDI) method is applied to this study in terms ...This paper quantifies a decomposition analysis of energy-related CO2 emissions in the industrial sectors of Shanghai over the period 1994-2007.The Log-Mean Divisia Index(LMDI) method is applied to this study in terms of six factors:labor force,labor mobility,gross labor productivity,energy intensity,fuel mix,and emission coefficient.In addition,the decoupling effect between industrial economic growth and CO2 emissions is analyzed to evaluate CO2 mitigation strategies for Shanghai.The results show that all labor productivity has the largest positive effect on CO2 emission changes in the industrial sectors,whereas labor mobility and energy intensity are the main components for decreasing CO2 emissions.Other factors have different effects on CO2 mitigation in different sub-periods.Although a relative decoupling of industrial CO2 emissions from the economic growth in Shanghai has been found,Shanghai should keep pace with the industrial CO2 emissions reduction by implementing low-carbon technology.These results have important policy implications:Plan C is the reasonable choice for Shanghai.展开更多
There has been considerable debate about the major factors responsible for the dramatic decline of China＇s energy intensity in the 1980s and 1990s. However, few detailed analysis has been done to explain the fluctuat...There has been considerable debate about the major factors responsible for the dramatic decline of China＇s energy intensity in the 1980s and 1990s. However, few detailed analysis has been done to explain the fluctuation in energy intensity during 2002-005. In this paper, we use the structural decomposition analysis （SDA） to decompose energy intensity into five determining factors： Energy input coefficient, technology coefficient （Leontief inverse coefficient）, final demands structure by product, final demands by category and final energy consumption coefficient. We then further decompose two coefficients, energy input coefficient and technology coefficient, into structure and real coefficient. Empirical study is carried out based on the energy-input-output tables from 1987 to 2005 in 2000 constant price. The results show that between 1987 and 2002, energy input structure accounts for most of the decline in energy intensity. However, the input structure and final demands structure by product explain the increase of the energy intensity between 2002 and 2005.展开更多
基金Supported by the National Natural Science Foundation of China(No.71273027 and No.71322306)
文摘The existing oil import dependence index cannot exactly measure the economic cost or scales, and it is difficult to describe the economical aspect of oil security. To measure the foreign dependence of one country's economy and reflect its oil economic security, this paper defines the net oil import intensity as the ratio of net oil import cost to GDP. By using Divisia Index Decomposition, the change of net oil import intensity in five industrialized countries and five newly industrialized countries during 1971—2010 is decomposed into five factors: oil price, oil intensity, oil self-sufficiency, domestic price level and exchange rate. The result shows that the dominating factors are oil price and oil intensity; moreover, the newly industrialized countries have higher net oil import intensity than industrialized countries.
基金the National Natural Science Foundation of China(Grant No.71173157)the State Key Program of the National Social Science Foundation of Ching (Grant No.11AZD102)
文摘This paper quantifies a decomposition analysis of energy-related CO2 emissions in the industrial sectors of Shanghai over the period 1994-2007.The Log-Mean Divisia Index(LMDI) method is applied to this study in terms of six factors:labor force,labor mobility,gross labor productivity,energy intensity,fuel mix,and emission coefficient.In addition,the decoupling effect between industrial economic growth and CO2 emissions is analyzed to evaluate CO2 mitigation strategies for Shanghai.The results show that all labor productivity has the largest positive effect on CO2 emission changes in the industrial sectors,whereas labor mobility and energy intensity are the main components for decreasing CO2 emissions.Other factors have different effects on CO2 mitigation in different sub-periods.Although a relative decoupling of industrial CO2 emissions from the economic growth in Shanghai has been found,Shanghai should keep pace with the industrial CO2 emissions reduction by implementing low-carbon technology.These results have important policy implications:Plan C is the reasonable choice for Shanghai.
基金supported by the National Natural Science Foundation of China under Grant Nos.70871108, 70810107020
文摘There has been considerable debate about the major factors responsible for the dramatic decline of China＇s energy intensity in the 1980s and 1990s. However, few detailed analysis has been done to explain the fluctuation in energy intensity during 2002-005. In this paper, we use the structural decomposition analysis （SDA） to decompose energy intensity into five determining factors： Energy input coefficient, technology coefficient （Leontief inverse coefficient）, final demands structure by product, final demands by category and final energy consumption coefficient. We then further decompose two coefficients, energy input coefficient and technology coefficient, into structure and real coefficient. Empirical study is carried out based on the energy-input-output tables from 1987 to 2005 in 2000 constant price. The results show that between 1987 and 2002, energy input structure accounts for most of the decline in energy intensity. However, the input structure and final demands structure by product explain the increase of the energy intensity between 2002 and 2005.
