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Regional characteristics of industrial energy efficiency in China: application of stochastic frontier analysis method

机译:中国工业能源效率的区域特征:随机前沿分析方法的应用

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摘要

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 technology 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.
机译:本文使用总因子能效(TFEE)分析了中国的区域工业能效。东部地区的能源效率最高,中部和西部分别排名第二和第三。但是,发现从1998年到2006年,所有地区的工业能源效率都有所提高。这一结果与每个地区的经济发展水平是一致的。中国所有省份的产业尚未处于前沿效率位置,因此,要以前沿为目标,应相应调整其技术水平和生产工艺。与传统的能源效率相比,能源强度的倒数(定义为实际输出与能量输入的比率)被视为单因素能源效率(SFEE)指数。尽管每个地区的TFEE等级没有改变,但每个省的等级不同。比较结果还表明,投入(劳动力,资本存量和能源)之间的替代对生产产出的影响很大。如果将能源作为生产中的单一输入,则SFEE分数可能会被高估。最后,我们使用Tobit模型确定了影响工业能源效率的决定性因素。结果表明,人均国内生产总值的增长,港澳台地区和海外投资的工业总产值的百分比,能源价格以及对工业的科技活动的投资可能是增加的原因。工业能源效率的驱动力。但是,重工业的增加将导致工业能源效率下降。

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