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“一带一路”省市制造业全要素生产率的变化及其影响因素——基于2006—2016年经验数据的分析 被引量:4

CHANGES AND FACTORS OF TOTAL FACTOR PRODUCTIVITY OF PROVINCIAL MANUFACTURING INDUSTRY ALONG“THE BELT AND ROAD”:ANALYSIS OF EMPIRICAL DATA FROM 2006 TO 2016
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摘要 采用超效率DEA模型和Malmquist指数计算2006—2016年我国"一带一路"沿线各省(市、自治区)制造业全要素生产率,从空间维度和时间维度讨论全要素生产率的区域差异和动态规律,并对全要素生产率变化进行分解,探究其变化的内在来源和驱动因素,以准确把握制造业全要素生产率的空间差异和演变特征。研究表明:"一带一路"沿线制造业的全要素生产率呈"U"型变化趋势,资源配置效率得到有效改善;"一带一路"区域内制造业的全要素生产率具有区域异质性,东南沿海省(市)高,其次是东北、西南,最低的是西北地区;技术进步是驱动制造业全要素生产率变化的重要因素,研发投入、专利申请数量、新产品销售收入和"一带一路"政策对全要素生产率均存在显著正向影响。 This paper uses DEA and Malmquist index to calculate the total factor productivities of manufacturing industry along“the Belt and Road”from 2006 to 2016,and discusses their regional differences and dynamic rules from temporal and spatial dimensions.Decomposition of total factor productivity is performed to explore the source and drives of its internal changes so as to precisely study the spatial difference and evolution of total factor productivity of manufacturing industry.The total factor productivity of manufacturing industry along“the Belt and Road”shows a U-shaped changing trend which suggests an improved resource allocation efficiency,and is of regional heterogeneity,high in southeastern coast area,followed by northeastern and southwestern area,and then by northwestern area.Technical advances play a key role in increasing the total factor productivity,and research and development input,patent counts,new products revenue and“the Belt and Road”policies are positively related to the total factor productivity.
作者 王琴 刘冬辉 孟令杰 WANG Qin;LIU Donghui;MENG Lingjie(School of Economics and Management,Nanjing University of Science and Technology,Nanjing 210094,China;School of Economics,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
出处 《资源与产业》 2021年第4期70-77,共8页 Resources & Industries
基金 江苏高校哲社重点项目(2017ZDIXM127) 江苏省社科基金专项课题(17ZTB014)。
关键词 “一带一路” 全要素生产率 研发投入 专利数量 超效率DEA模型 MALMQUIST指数 “the Belt and Road” total factor productivity research and development input patent counts super efficient DEA model Malmquist index
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