中部地区承接国际产业转移效率及驱动机理研究 ——基于超效率DEA 模型和面板回归分析

doi:10.11870/cjlyzyyhj201707003

长江流域资源与环境 >> 2017, Vol. 26 >> Issue (07): 973-.doi: 10.11870/cjlyzyyhj201707003

中部地区承接国际产业转移效率及驱动机理研究 ——基于超效率DEA 模型和面板回归分析

陈万旭 , 李江风, 朱丽君

1.中国地质大学（武汉）公共管理学院，湖北武汉 430074； 2.中国地质大学（武汉）国土资源部法律评价工程重点实验室，湖北武汉 430074

出版日期:2017-07-20

STUDY ON THE EFFICIENCY AND DRIVING MECHANISM OF UNDERTAKING INTERNATIONAL INDUSTRY TRANSFER IN CENTRAL CHINA：BASED ON THE SUPEREFFICIENCY DEA AND PANEL REGRESSIVE ANALYSIS

CHEN Wanxu1,2, LI Jiangfeng1,2, ZHU Lijun1

1.School of Public Administration of China University of Geosciences, Wuhan 430074, China；2.Key Laboratory of Legal Assessment Project，Ministry of Land and Resources，Wuhan 430074，China

Online:2017-07-20

摘要/Abstract

摘要： 为研究我国中部6省近15a承接国际产业转移成效，探索提高承接国际产业转移水平路径，从投入产出角度构建了承接国际产业转移效率测度指标体系，采用EMS31软件测度了我国中部6省80个地级单元2000~2014年承接国际产业转移效率的时空分异特征，结合GeoDa095i软件分析了中部地区承接国际产业转移效率的时空分异格局及空间关联性；在分析影响承接国际产业转移效率机制的基础上，采用固定效应模型对我国中部6省承接国际产业转移效率的影响因素进行定量分析。结果表明：（1） 2000~2014年间处于DEA有效的地市数量逐渐增加，处于波动上升的地市有52个，呈现下降趋势的有28个，省会城市及其周边地区DEA效率值相对高于其他地区；（2）中部地区承接国际产业转移效率空间分异显著，具有明显的空间群聚效应；（3）产业支撑因子、产业吸引因子、产业发展因子对中部地区承接国际产业转移效率影响较为显著，而产业鉴别因子影响相对较弱。影响因素回归系数由大到小分别为二、三产业从业人员比重、客运总量、职工平均工资、人均GDP、年末金融机构存款余额研究与试验发展(R&D)经费支出。基于研究结果对中部地区承接国际产业转移提出了相应对策建议。关键词：国际产业转移；超效率DEA；面板估计；空间分析；中部地区

Abstract: In order to study the consequence of undertaking international industrial transfer by six provinces of central China for nearly 15 years and explore how to improve the level to undertake international industrial transfer, this paper builds a measurement index system about the efficiency of undertaking international industrial transfer, from the angle of inputoutput. The time and space differentiation characteristics from 2000 to 2014 about the efficiency of 80 regional units of the six provinces in central China are measured by EMS3.1 software. The time and space differentiation pattern and space correlation are analyzed by GeoDa095i software. Based on analyzing the mechanism of influencing the efficiency of undertaking international industrial transfer, using stata130 software and adopting the fixed effects model, this paper makes quantitative analysis of the influencing factors of efficiency. Results show that: (1) From 2000 to 2014, the number of cities in the effective value of DEA gradually increases; the number of cities on the rise are 52, the number of cities showing a trend of decline are 28, and DEA efficiency value of the provincial capital city and its surrounding areas is relatively higher than that of other regions; (2) Spatial differentiation of the central region’s efficiency of undertaking international industrial transfer is obvious and it has a clear spatial cluster effect; (3) Industry supporting factor, industry attracting factor and industry developing factor have great influences on the efficiency of the central region to undertake international industry transfer, and the influence of industry identifying factor is relatively weak. The regression coefficients of influencing factors ranked from to small are the employee proportion of second and third industry, passenger volume, worker’s average wage, per capita GDP, the balance of financial institutions at the end of year, and research and development (R&D) spending. Based on the results, some corresponding countermeasures and suggestions are put forward for the central region to improve undertaking international industrial transfer. Key words： international industrial transfer; superDEA model; penal estimate; spatial analysis; central region in China

陈万旭,李江风, 朱丽君. 中部地区承接国际产业转移效率及驱动机理研究 ——基于超效率DEA 模型和面板回归分析[J]. 长江流域资源与环境, 2017, 26(07): 973-.

CHEN Wanxu1,2, LI Jiangfeng1,2, ZHU Lijun1. STUDY ON THE EFFICIENCY AND DRIVING MECHANISM OF UNDERTAKING INTERNATIONAL INDUSTRY TRANSFER IN CENTRAL CHINA：BASED ON THE SUPEREFFICIENCY DEA AND PANEL REGRESSIVE ANALYSIS[J]. RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN, 2017, 26(07): 973-.

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