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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 development of urbanization in China,energy consumption is rising increasingly. Urban energy consumption accounts for the biggest proportion of total energy consumption. It is important to measure urban energy efficiency scientifically and accurately for reasonable energy policy making. From multiple channels,data are collected and carefully prepared.Then the perpetual inventory method is adopted to measure the urban capital stock. According to Zhou et al.( 2012) 's definition of energy efficiency based on Shephard energy distance function,the inefficiency of capital and labor is decomposed from the total production function. Based on urban capital stock,SFA is applied to measure the total factor energy efficiency of China's 245 cities from 2001 to 2013. Then urban total factor energy efficiency is compared among four regions,northern cities and southern cities,and city scales. Results show that the average of urban energy efficiency is slightly higher than 0. 6,the top 10 cities are mainly located in the eastern coastal region; the last 10 cities are mainly located in the western region. Urban energy efficiency among four regions,northern and southern cities,and five scales shows obvious differences. Overall,there is a great potentiality in energysaving for China's cities in the future.
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(1)受篇幅所限,未能将全部城市资本存量数据呈现,感兴趣的读者可向作者索取。
基本信息:
DOI：10.14134/j.cnki.cn33-1336/f.2016.07.009
中图分类号:F206;F224
引用信息:
[1]陈龙,李金昌,程开明.中国城市能源效率测算[J].商业经济与管理,2016,No.297(07):83-96.DOI:10.14134/j.cnki.cn33-1336/f.2016.07.009.
基金信息:
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)
2016-07-15
2016-07-15