基于DEA和Malmquist指数的中国物流业全要素能源效率评价
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摘要
文章基于2006—2015年我国30个省份的省际面板数据,通过DEA模型和Malmquist指数,从静态和动态两个角度分析我国物流业全要素能源效率。研究发现,在静态角度:(1)我国物流业全要素能源效率还处于很低的水平仅为0.64,总体呈现出"东高、中次、西低"的现状;(2)通过对我国能源效率最低的云南省做投影分析发现,云南省的能源效率有75%的提升空间。在动态角度:(1)我国物流业全要素能源效率在这十年间呈现下降的趋势,下降了3.2%,主要原因是技术进步;(2)能源效率下降趋势呈现出"中快、西次、东慢"的现状;最后,对改善和提升我国物流业全要素能源效率提出了对策建议。
Based on the provincial panel data of 30 provinces from 2006 to 2015, this paper analyzes the total energy efficiency of logistics industry in China from static and dynamic perspectives through the DEA model and the Malmquist index. The studies show that, the static angle:(1) The energy efficiency of the logistics industry is still at a very low level, it is only 0.64 and decreases from east to west;(2) Through the projection analysis of the lowest energy efficiency in Yunnan Province, it is found that the energy efficiency of Yunnan province has 75% of the promotion space. The dynamic angle:(1) In the past ten years, the total factor energy efficiency of the logistics industry showed a downward trend and fell by which is 3.2%, which is mainly due to technological progress;(2) The downward trend of energy efficiency shows the status of "central fast, western and eastern slow". Finally, based on the above analysis, the article provides suggestions for improving the logistics industry total factor energy efficiency.
Based on the provincial panel data of 30 provinces from 2006 to 2015, this paper analyzes the total energy efficiency of logistics industry in China from static and dynamic perspectives through the DEA model and the Malmquist index. The studies show that, the static angle:(1) The energy efficiency of the logistics industry is still at a very low level, it is only 0.64 and decreases from east to west;(2) Through the projection analysis of the lowest energy efficiency in Yunnan Province, it is found that the energy efficiency of Yunnan province has 75% of the promotion space. The dynamic angle:(1) In the past ten years, the total factor energy efficiency of the logistics industry showed a downward trend and fell by which is 3.2%, which is mainly due to technological progress;(2) The downward trend of energy efficiency shows the status of "central fast, western and eastern slow". Finally, based on the above analysis, the article provides suggestions for improving the logistics industry total factor energy efficiency.
引文
[1]中华人民共和国国家统计局.中国统计年鉴2016[M].北京:中国统计出版社,2016.
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[4]曹翠珍,赵国浩.区域物流发展、经济增长与能源消费--基于中国省际面板数据的实证分析[J].财贸研究,2015(2):44-52.
[5]王富忠.城镇化发展视角下物流发展与能源消费研究[J].经济与管理研究,2015(3):100-103.
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[8]刘勇.物流业全要素能源效率评价及其影响因素分析[J].统计与决策,2014(1):66-68.
[9]吕荣胜,陈晓杰.我国物流行业全要素能源效率实证分析[J].商业研究,2014(2):51-56.
[10]张立国,李东,龚爱青.中国物流业全要素能源效率动态变动及区域差异分析[J].资源科学,2015(4):754-763.
[11]杨恺钧,毛博伟,胡菡.长江经济带物流业全要素能源效率--基于包含碳排放的SBM与GML指数模型[J].北京理工大学学报(社会科学版),2016(6):54-62.
[12]Aronsson H,Brodin M H.The environmental impact of changing logistics structures[J].International Journal of Logistics management,2006,17(3):394-415.
[13]Halldórssoná,Kovács G.The sustainable agenda and energy efficiency[J].International Journal of Physical Distribution&Logistics Management,2013,40(1/2):5-13.
[14]张竟轶,张竟成.基于三阶段DEA模型的我国物流效率综合研究[J].管理世界,2016(8):178-179.
[15]F?re R,Grosskopf S,Norris M.Productivity growth,technical progress,and efficiency change in industrialized countries:Reply[J].American Economic Review,1994,87(5):1040-1044.
[16]田刚,李南.中国物流业技术效率差异及其影响因素研究--基于省级面板数据的实证分析[J].科研管理,2011(7):34-44.
[17]刘秉镰,李清彬.中国城市全要素生产率的动态实证分析:1990-2006--基于DEA模型的Malmquist指数方法[J].南开经济研究,2009(3):139-152.
[18]邓学平,王旭,Ng A S F.我国物流企业生产效率与规模效率[J].系统工程理论与实践,2009(4):34-42.
[2]国家发展改革委.国家发展改革委国家能源局关于印发能源发展“十三五”规划的通知[EB/OL].(2016-12-26).http://www.ndrc.gov.cn/zcfb/zcfbtz/201701/t20170117_835278.html.
[3]洪帅,吕荣胜.物流产业发展与能源消费关系的实证研究[J].预测,2017(3):56-61.
[4]曹翠珍,赵国浩.区域物流发展、经济增长与能源消费--基于中国省际面板数据的实证分析[J].财贸研究,2015(2):44-52.
[5]王富忠.城镇化发展视角下物流发展与能源消费研究[J].经济与管理研究,2015(3):100-103.
[6]Mckinnon A C.Reducing energy consumption and emissions in the logistics sector[EB/OL].(2012-03-03).https://link.springer.com/chapter/10.1007%2F978-1-4471-2717-8_29.
[7]An H J,Searcy S W.Economic and energy evaluation of a logistics system based on biomass modules[J].Biomass&Bioenergy,2012,46(46):190-202.
[8]刘勇.物流业全要素能源效率评价及其影响因素分析[J].统计与决策,2014(1):66-68.
[9]吕荣胜,陈晓杰.我国物流行业全要素能源效率实证分析[J].商业研究,2014(2):51-56.
[10]张立国,李东,龚爱青.中国物流业全要素能源效率动态变动及区域差异分析[J].资源科学,2015(4):754-763.
[11]杨恺钧,毛博伟,胡菡.长江经济带物流业全要素能源效率--基于包含碳排放的SBM与GML指数模型[J].北京理工大学学报(社会科学版),2016(6):54-62.
[12]Aronsson H,Brodin M H.The environmental impact of changing logistics structures[J].International Journal of Logistics management,2006,17(3):394-415.
[13]Halldórssoná,Kovács G.The sustainable agenda and energy efficiency[J].International Journal of Physical Distribution&Logistics Management,2013,40(1/2):5-13.
[14]张竟轶,张竟成.基于三阶段DEA模型的我国物流效率综合研究[J].管理世界,2016(8):178-179.
[15]F?re R,Grosskopf S,Norris M.Productivity growth,technical progress,and efficiency change in industrialized countries:Reply[J].American Economic Review,1994,87(5):1040-1044.
[16]田刚,李南.中国物流业技术效率差异及其影响因素研究--基于省级面板数据的实证分析[J].科研管理,2011(7):34-44.
[17]刘秉镰,李清彬.中国城市全要素生产率的动态实证分析:1990-2006--基于DEA模型的Malmquist指数方法[J].南开经济研究,2009(3):139-152.
[18]邓学平,王旭,Ng A S F.我国物流企业生产效率与规模效率[J].系统工程理论与实践,2009(4):34-42.