能源经济环境模型为能源经济环境综合评价及宏观政策影响等研究提供了重要的分析手段。本文分析了能源经济环境模型中广泛应用的三种能源经济环境模型,C G E模型、技术模型和混合模型。依据文献资料,重点分析了模型发展方向,涵盖了诸多...能源经济环境模型为能源经济环境综合评价及宏观政策影响等研究提供了重要的分析手段。本文分析了能源经济环境模型中广泛应用的三种能源经济环境模型,C G E模型、技术模型和混合模型。依据文献资料,重点分析了模型发展方向,涵盖了诸多层面,如开发综合评价模型、细化重要部门、处理不确定性问题等。最终将基本模型能力建设的强化工作提了出来,积极融入国际间合作。展开更多
Mountain regions play an increasingly essential role in global sustainable development, and the related sustainable development issues have attracted increasing attention. There are obvious vertical spatial differenti...Mountain regions play an increasingly essential role in global sustainable development, and the related sustainable development issues have attracted increasing attention. There are obvious vertical spatial differentiation phenomena in both natural and socio-eeonomic fields with altitude being a key factor affecting the economic development of mountain regions. However, the exact influence of altitude is still unknown. Based on the county scale, this paper used the gravitational potential energy model to evaluate the effects of altitude on economic development in China. The results indicate that the high-altitude areas were the depression areas of county economic development, and county economic density showed a decreasing trend with the increase of altitude. County economic density respectively decreased by 0.10%, 0.04% and 0.02% with every 1% increase in altitude in 2000, 2005 and 2010. Here we demonstrate that high altitude has negative effect on county economy, although the negative effect presented a downward trend. The results also showed that increasing capital and labor investments could reduce the negative effect of high altitude on county economy. In 2010, with every 1% increase in capital and labor density, county economic density increased by 0.62% and 0.83%, respectively. The effects of altitude were the results of multidimensional factors. The fundamental approach to reduce the negative effects of high altitude is to combine the ecological environment and resources to develop characteristic industries. The construction of infrastructure should be strengthened, which can promote the occurrence of the contra-flow of people, logistics and capital, and promote the balanced development of county economy.展开更多
The efficient use of water resources directly affects environmental, social, and economic development; therefore, it has a significant impact on urban populations. A slacks-based measure for data envelopment analysis ...The efficient use of water resources directly affects environmental, social, and economic development; therefore, it has a significant impact on urban populations. A slacks-based measure for data envelopment analysis （SBM-DEA） has been widely used in energy efficiency and environmental efficiency analyses in recent years. Based on this model, data from 316 cities were examined and a category method was employed involving three different sorting techniques to empirically evaluate the efficiency of urban water re- source utilization in China between 2000 and 2012. The overall efficiency （OE） of urban water resource utilization in China was initially low, but has improved over the past decade. The scale efficiency （SE） was higher than the pure technological efficiency （PTE）; PTE is a major determining factor of OE, and has had an increasingly significant effect. The efficiency of water resource utilization varied ac- cording to the region, urban scale, and economic function. The OE score for the eastern China was higher than for the rest of the region, and the OE score for the western China was higher than for the central China. The OE score for urban water resource utilization has improved with urban expansion, except in the case of small cities. The SE showed an inverted U-shaped＇ trend with increasing urban expansion. The OE of urban water utilization in comprehensive functional cities was greater than in economic specialization cities, and was greater in heavy industry specialization cities than in other specialization cities. This study contributes to the field of urban water resource management by examining variations in efficiency with urban ~ezle展开更多
In this paper, the author uses super-efficiency DEA model to measure the national and regional energy efficiency in China; using spatial econometric model and from the perspective of geo-spatial spillover, the author ...In this paper, the author uses super-efficiency DEA model to measure the national and regional energy efficiency in China; using spatial econometric model and from the perspective of geo-spatial spillover, the author interprets the spatial characteristies of energy efficiency and extracts the main factors that influ- ence the regional energy efficiency. The analysis results show that： （1） the national and regional energy efficiency is consistent with inverted U-shaped curve, and the nationwide energy efficiency gap is increasing; （2） energy efficiency has the obvious effect of the spatial external effect, and when the government makes energy saving strategies, inter-regional energy cooperation and the prolif- eration of advanced production technology should be given more priority; （3） energy efficiency has significant negative correlation with government intervention, industrial structure, ownership structure, the energy consumption structure, and resource endowments, and has positive correlation with the degree of opening-up and energy price.展开更多
Economic policy and energy policy are two major factors of energy consumption and carbon emissions. The economic factor is external and energy supply structure and efficiency are intrinsic factors. Based on a carbon e...Economic policy and energy policy are two major factors of energy consumption and carbon emissions. The economic factor is external and energy supply structure and efficiency are intrinsic factors. Based on a carbon emissions completely decomposed analysis model, the logarithmic mean Divisia Index （LMDI） system analyzes the impact of carbon emission changes and the contribution rate in China from 1995 to 2010. The decomposition factors include four parts： economies of scale, structure effect, energy intensity effect and carbon intensity effects. Model results show that the contribution rate of the four effects is different and from 1995 to 2010 the greatest factors impacting increases in carbon emissions were economic development （contribution rate of 155%） and industrial structure change （contribution rate of 10.6%）. The reduction in carbon emissions was mainly the result of a decline in energy intensity （contribution rate of -63.7%）. The increase in carbon emissions in recent years is the result of changes in major economies of scale with 168.2% contribution rate, changes in carbon intensity （contribution rate of 4%） and industrial restructuring （contribution rate of 1.3%） have also contributed to increasing carbon emissions. Energy intensity declined only played a role in reducing carbon emissions （contribution rate -73.5%）. These results suggest that China needs to rethink industrial policy and energy development measures, strengthen future energy saving and emission mitigation policies and strengthen investment in low-carbon energy technologies and policy support.展开更多
文摘能源经济环境模型为能源经济环境综合评价及宏观政策影响等研究提供了重要的分析手段。本文分析了能源经济环境模型中广泛应用的三种能源经济环境模型,C G E模型、技术模型和混合模型。依据文献资料,重点分析了模型发展方向,涵盖了诸多层面,如开发综合评价模型、细化重要部门、处理不确定性问题等。最终将基本模型能力建设的强化工作提了出来,积极融入国际间合作。
基金funded by the National Natural Science Foundation of China (Grants No.41571523)the National Science and Technology Support Program (Grant No.2014BAC05B01)the National Key Basic Research and Development Program of China (973 Program) (Grant No.2013CBA01808)
文摘Mountain regions play an increasingly essential role in global sustainable development, and the related sustainable development issues have attracted increasing attention. There are obvious vertical spatial differentiation phenomena in both natural and socio-eeonomic fields with altitude being a key factor affecting the economic development of mountain regions. However, the exact influence of altitude is still unknown. Based on the county scale, this paper used the gravitational potential energy model to evaluate the effects of altitude on economic development in China. The results indicate that the high-altitude areas were the depression areas of county economic development, and county economic density showed a decreasing trend with the increase of altitude. County economic density respectively decreased by 0.10%, 0.04% and 0.02% with every 1% increase in altitude in 2000, 2005 and 2010. Here we demonstrate that high altitude has negative effect on county economy, although the negative effect presented a downward trend. The results also showed that increasing capital and labor investments could reduce the negative effect of high altitude on county economy. In 2010, with every 1% increase in capital and labor density, county economic density increased by 0.62% and 0.83%, respectively. The effects of altitude were the results of multidimensional factors. The fundamental approach to reduce the negative effects of high altitude is to combine the ecological environment and resources to develop characteristic industries. The construction of infrastructure should be strengthened, which can promote the occurrence of the contra-flow of people, logistics and capital, and promote the balanced development of county economy.
基金Key Research Program of Chinese Academy of Sciences(No.KZZD-EW-06-03-03)
文摘The efficient use of water resources directly affects environmental, social, and economic development; therefore, it has a significant impact on urban populations. A slacks-based measure for data envelopment analysis （SBM-DEA） has been widely used in energy efficiency and environmental efficiency analyses in recent years. Based on this model, data from 316 cities were examined and a category method was employed involving three different sorting techniques to empirically evaluate the efficiency of urban water re- source utilization in China between 2000 and 2012. The overall efficiency （OE） of urban water resource utilization in China was initially low, but has improved over the past decade. The scale efficiency （SE） was higher than the pure technological efficiency （PTE）; PTE is a major determining factor of OE, and has had an increasingly significant effect. The efficiency of water resource utilization varied ac- cording to the region, urban scale, and economic function. The OE score for the eastern China was higher than for the rest of the region, and the OE score for the western China was higher than for the central China. The OE score for urban water resource utilization has improved with urban expansion, except in the case of small cities. The SE showed an inverted U-shaped＇ trend with increasing urban expansion. The OE of urban water utilization in comprehensive functional cities was greater than in economic specialization cities, and was greater in heavy industry specialization cities than in other specialization cities. This study contributes to the field of urban water resource management by examining variations in efficiency with urban ~ezle
基金Interim research result of 2009 Planned Projectof Social Sciences of Fujian Province (Grant No.:2009B062)
文摘In this paper, the author uses super-efficiency DEA model to measure the national and regional energy efficiency in China; using spatial econometric model and from the perspective of geo-spatial spillover, the author interprets the spatial characteristies of energy efficiency and extracts the main factors that influ- ence the regional energy efficiency. The analysis results show that： （1） the national and regional energy efficiency is consistent with inverted U-shaped curve, and the nationwide energy efficiency gap is increasing; （2） energy efficiency has the obvious effect of the spatial external effect, and when the government makes energy saving strategies, inter-regional energy cooperation and the prolif- eration of advanced production technology should be given more priority; （3） energy efficiency has significant negative correlation with government intervention, industrial structure, ownership structure, the energy consumption structure, and resource endowments, and has positive correlation with the degree of opening-up and energy price.
基金National Basic Research Program of China(No.2012CB955801)
文摘Economic policy and energy policy are two major factors of energy consumption and carbon emissions. The economic factor is external and energy supply structure and efficiency are intrinsic factors. Based on a carbon emissions completely decomposed analysis model, the logarithmic mean Divisia Index （LMDI） system analyzes the impact of carbon emission changes and the contribution rate in China from 1995 to 2010. The decomposition factors include four parts： economies of scale, structure effect, energy intensity effect and carbon intensity effects. Model results show that the contribution rate of the four effects is different and from 1995 to 2010 the greatest factors impacting increases in carbon emissions were economic development （contribution rate of 155%） and industrial structure change （contribution rate of 10.6%）. The reduction in carbon emissions was mainly the result of a decline in energy intensity （contribution rate of -63.7%）. The increase in carbon emissions in recent years is the result of changes in major economies of scale with 168.2% contribution rate, changes in carbon intensity （contribution rate of 4%） and industrial restructuring （contribution rate of 1.3%） have also contributed to increasing carbon emissions. Energy intensity declined only played a role in reducing carbon emissions （contribution rate -73.5%）. These results suggest that China needs to rethink industrial policy and energy development measures, strengthen future energy saving and emission mitigation policies and strengthen investment in low-carbon energy technologies and policy support.
