中国城市能源效率测算

发布时间：2018-11-09 15:59

【摘要】：伴随着中国的快速城市化进程,能源消耗总量不断攀升,其中城市能源消耗量占到绝大比重,故科学测算与认清城市能源效率状况,对于制定合理的能源政策具有重要意义。借助多渠道的统计数据和细致的数据预处理,文章在以永续盘存法估算城市资本存量的基础上,借鉴Zhou等(2012)基于Shephard能源距离函数的能源效率定义,将劳动和资本的无效率从生产函数中分离出来,采用随机前沿分析(SFA)测算我国2001-2013年245个地级以上城市的全要素能源效率,并开展四大地区、南方北方、不同规模等级城市全要素能源效率的差异分析。结果显示,地级以上城市能源效率平均水平略高于0.6,能源效率排名前10位城市主要位于东部沿海地区,后10位城市则主要位于西部地区;四大地区、南方北方及不同规模等级城市的能源效率及变动趋势表现出明显差异,总体上都存在较大的节能潜力空间。
[Abstract]:With the rapid urbanization of China, the total amount of energy consumption is rising, among which the urban energy consumption accounts for the majority, so it is of great significance to scientifically estimate and recognize the energy efficiency of the city. With the help of multi-channel statistical data and meticulous data preprocessing, this paper uses Zhou et al. (2012) as reference for the definition of energy efficiency based on Shephard energy distance function on the basis of estimating urban capital stock by sustainable inventory method. The inefficient labor and capital are separated from the production function, and the total factor energy efficiency of 245 prefecture-level cities in China from 2001 to 2013 is estimated by using stochastic frontier analysis (SFA), and four major regions, the south and the north, are carried out. The difference analysis of energy efficiency of all factors in cities of different scale. The results show that the average level of energy efficiency of cities above the prefectural level is slightly higher than 0.6, the top 10 cities are mainly located in the eastern coastal areas, and the last 10 cities are mainly located in the western region. The energy efficiency and change trend of the four major regions, the north of the south and the cities of different scale are obviously different, and there is a great potential space for energy conservation in the whole.
【作者单位】：浙江工商大学统计与数学学院;浙江财经大学数据科学学院;
【基金】：国家自然科学基金面上项目(71373240) 教育部人文社科规划基金项目(13YJA630012);教育部人文社科重点研究基地浙江工商大学现代商贸研究中心和浙江省2011协同创新中心——现代商贸流通体系建设协同创新中心项目(15SMGK032) 浙江省“之江青年课题研究”项目(13ZJQN005YB) 浙江省高校人文社科重点研究基地(统计学)项目(1020XJ3314044G)
【分类号】：F206;F224

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