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本文运用基于非期望产出的SBM模型计算出2000—2011年我国29个省份及东、中、西部区域的煤炭、石油和燃气三种主要能源的生态全要素能源效率(ETFEE),在此基础上,通过面板Tobit回归模型实证分析我国区域结构能源效率的影响因素。实证研究表明:我国区域结构能源效率呈上升趋势。各省份之间煤炭和燃气ETFEE相差较大,石油ETFEE则趋于稳定。东部区域三种能源ETFEE较高;中部区域三种能源ETFEE波动幅度较大;西部区域石油ETFEE较高,但煤炭和燃气ETFEE较低。面板Tobit回归模型显示:经济增长水平、产业结构、能源产量、外贸进出口总额、能源工业投资和地理差异均会对我国区域结构能源效率产生积极或消极影响。依据这些影响因素,本文认为,通过优化调整地区和区域能源结构,实现区域经济增长向技术密集与资本密集的深度结构转变,加快能源产地区域的能源科研成果实际转化,鼓励利用区域贸易优势加强能源技术转移和扩散,可以有效提高我国区域结构能源效率。
In this paper, we use the SBM model based on the non-expected output to calculate the ETF of three major energy sources of coal, oil and gas in 29 provinces in China and the eastern, central and western regions from 2000 to 2011. Based on this, On the basis of panel Tobit regression model, this paper empirically analyzes the influencing factors of energy efficiency in China’s regional structure. Empirical studies show that: the energy efficiency of China’s regional structure is on the rise. Coal and gas ETFEE vary greatly among provinces, while oil ETFEE tends to be stable. The ETFEE of the three energy sources in the eastern region is relatively high; the ETFEEs of the three energy sources in the central region are more volatile; the ETFEEs of the western region are higher but the ETFEEs of the coal and gas are lower. Panel Tobit regression model shows that the level of economic growth, industrial structure, energy production, total foreign trade volume, investment in energy industry and geographical differences will all have positive or negative impact on the energy efficiency of China’s regional structure. Based on these influencing factors, this paper argues that through the optimization and adjustment of regional and regional energy structures, the transformation of regional economic growth from a technology-intensive to a capital-intensive deep-seated structure will be accelerated, and the actual conversion of energy research results in energy-producing areas will be accelerated. Encouraging the use of regional trade advantages and strengthening energy sources Technology transfer and proliferation can effectively improve the energy efficiency of China’s regional structure.