中国区域能源效率及其影响因素分析——基于DEA-Malmquist模型

›› 2017 ›› Issue (06): 32-39.

中国区域能源效率及其影响因素分析——基于DEA-Malmquist模型

陈海跃

四川大学经济学院, 四川成都 610065

收稿日期:2017-06-25 出版日期:2017-11-15 发布日期:2018-01-11
作者简介:陈海跃(1975-),男,广东海丰人,四川大学经济学院博士研究生,中国南方电网深圳供电局工程师,研究方向为世界经济。

Analysis of Regional Energy Efficiency and Influencing Factors in China——Based on DEA-Malmquist model

CHEN Hai-yue

School of Economics, Sichuan University, Chengdu, Sichuan 610065, China

Received:2017-06-25 Online:2017-11-15 Published:2018-01-11

摘要/Abstract

摘要： 采用1995—2015年中国28个省（市、自治区）的面板数据，基于DEA模型和Malmquist指数法，对中国各省（市、自治区）能源效率的测度和的研究结果显示：从整体上看，1995—2015年间各地区能源效率和全要素能源生产率呈上升趋势；各地区能源效率和全要素能源生产率存在差异，四川等地区的能源效率位于前沿面上，而青海等地区能源效率一直较低；大多数地区的技术效率较高，表明各地区在提高管理技术水平，引进先进技术设备和生产管理优化方面保持着较高水平。

关键词: 能源效率, 全要素能源生产率, DEA模型, Malmquist指数

Abstract: Based on the panel data of 28 provinces (municipalities and autonomous regions) in China from 1995 to 2015, the results of the study on the energy efficiency of China's provinces based on the DEA model and the Malmquist index show that:On the whole, energy efficiency and total factor energy productivity in each region increased from 1995 to 2015; Energy efficiency and total factor energy productivity in different regions were different; Energy efficiency in many regions, such as Sichuan, were in the frontier, while energy efficiency in Qinghai was low. In most, the technical efficiency of the region is high, indicating that the region has maintained a high level in improving the management technology level, introducing advanced technology equipment and production management optimization.

Key words: energy efficiency, total factor energy productivity, DEA model, malmquist index

中图分类号:

F426
F224

陈海跃. 中国区域能源效率及其影响因素分析——基于DEA-Malmquist模型[J]. , 2017(06): 32-39.

CHEN Hai-yue. Analysis of Regional Energy Efficiency and Influencing Factors in China——Based on DEA-Malmquist model[J]. , 2017(06): 32-39.

参考文献

[1] 余江,叶林.资源约束、结构变动与经济增长——基于新古典经济增长模型的分析[J].经济评论,2008(2):22-24.

[2] 张建伟,杨志明.能源效率对中国经济增长的实证研究[J].山东社会科学,2013(10):22-24.

[3] 刘晓虹,江可申.环境规制、能源消费结构与雾霾——基于省级面板数据的分析[J].国土资源科技管理,2016(1):59-66.

[4] 张少华,蒋伟杰.能源效率测度方法:演变、争议与未来[J].数量经济技术经济研究,2016(7):3-24.

[5] 魏一鸣,廖华.能源效率的七类测度指标及其测度方法[J].中国软科学,2010(1):128-137.

[6] 廖华.能源效率的计量经济模型及其应用研究[D].北京:中国科学院科技政策与管理科学研究所,2008.

[7] Nagata Y.The Us/Japan Comparison of Energy Intensity,Estimating the Real Gap[J].Energy Policy,1997,25(7):683-691.

[8] Zhou P.,Ang B.W.,Wang H.Energy and CO₂ Emission Performance in Electricity Generation:A Non-radial Directional Distance Function Approach[J].European Journal of Operational Research,2012,221(3):625-635.

[9] Liang L,Wu J,Cook W D,et al.The DEA game cross-efficiency model and its Nash equilibrium[J].Operation Research,2008(56):1278-1288.

[10] 李莞婕,徐莉,葛涛.基于DEA-Malmquist指数的中部六省能源效率分析[J].科技和产业,2014(12):101-105+151.

[11] 屈小娥.中国省际全要素能源效率变动分解——基于Malmquist指数的实证研究[J].数量经济技术经济研究,2009(8):29-43.

[12] 杜江,杨文溥.基于面板随机前沿模型的R&D对工业行业生产率影响研究[J].统计与决策,2016(15):133-137.

[13] Charnes A.,Cooper W.W.,Rhodes E.Measuring the Efficiency of Decision Making Units[J].European Journal of Operational Research,1978,2(78):429-444.

[14] Banker R.D.,Chames A.,Cooper W.W.Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis[J].Management Science,1984,30(9):1078-1092.

[15] Tone Kaoru,M.Tsutsui.Dynamic DEA:Alacks-based Measure Approach[J].Omega,2010(38):145-156.

[16] F? re R.,Grosskopf S.,Tyteca D.An Activity Analysis Model of the Environmental Performance of Firms:Application to Fossil-fuel-fired Electric Utilities[J].Ecological Economics,1996,18(2):161-175.

[17] 程中华,李廉水,刘军.环境约束下技术进步对能源效率的影响[J].统计与信息论坛,2016(6):70-76.

[18] 杜江,杨文溥.制度环境与我国地区工业生产效率分析——基于面板随机前沿模型[J].宏观质量研究,2016,4(02):17-27.[2017-09-08].

[19] Boyd G A,Pang J X.Estimating the linkage between energy efficiency and productivity[J].Energy Policy,2000,28(5):289-296.