中国城市全要素生产率的时空演变与影响因素研究——来自35个主要城市2000～2014年的经验证据

发布时间：2018-05-14 18:42

本文选题：城市 + 全要素生产率　；参考：《学习与实践》2017年05期

【摘要】：2000年以来中国城市全要素生产率整体水平提升2.6%,技术效率的改善是城市全要素生产率提升的主要动因,而技术变化起着负面作用。信息基础设施、人力资本、制造业集聚、经济密度和对外开放可以显著提升全要素生产率总体水平,政府干预具有较强的阻碍作用;有利于全要素生产率改善的因素对直辖市的作用程度普遍较高,对省会城市的影响程度较弱;东部地区和东北地区的城市受信息基础设施、教育、医疗和制造业集聚的正面影响最大,对中部地区和西部地区城市全要素生产率提升作用最大的分别是科技支出和经济密度。未来提升中国城市全要素生产率水平需要创新驱动促进城市经济转型升级,完善城市基础设施,实现制造业和服务业"双集聚",提升城市外向型经济水平和质量,强化政府在城市经济发展中的服务职能。
[Abstract]:Since 2000, the overall level of urban total factor productivity (TFP) in China has increased 2.6%. The improvement of technical efficiency is the main cause of TFP, and technological change plays a negative role. Information infrastructure, human capital, manufacturing agglomeration, economic density and opening to the outside world can significantly improve the overall level of total factor productivity, government intervention has a strong hindrance; The factors conducive to the improvement of total factor productivity (TFP) generally play a higher role in municipalities directly under the Central Government than in provincial capitals. Cities in the eastern and northeast regions are exposed to information infrastructure and education. The positive effect of medical treatment and manufacturing agglomeration is the biggest, and the biggest effect on urban total factor productivity in central region and western region is science and technology expenditure and economic density, respectively. In order to improve the level of total factor productivity of Chinese cities in the future, it is necessary to promote the transformation and upgrading of urban economy, improve urban infrastructure, realize the "dual agglomeration" of manufacturing and service industries, and promote the level and quality of export-oriented economy. Strengthen the service function of the government in the development of urban economy.
【作者单位】：武汉大学经济与管理学院;
【基金】：江汉大学武汉研究院开放性课题“武汉市经济转型升级与经济总量倍增战略研究”(jhunwyy2015101) 湖北省区域创新能力检测与分析软科学研究基地2016年度开放基金资助项目“湖北省地级市争创国家级创新型试点城市研究”(HBQY2016Y09)
【分类号】：F299.2

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