产业空间集聚影响因素实证分析——基于广东省制造业的面板数据回归模型  

The Empirical Analysis on the Influencing Factors of Industrial Spatial Agglomeration——Based on the Panel Data Regression Model of Guangdong Manufacturing

作　　者：吴波亮 王韬 WU Boliang;WANG Tao(CEPREI,Guangzhou 511370,China)

机构地区：[1]工业和信息化部电子第五研究所,广东广州511370

出　　处：《电子产品可靠性与环境试验》2021年第6期73-79,共7页Electronic Product Reliability and Environmental Testing

摘　　要：利用正态分布和产业聚集指数CIP方法,对2012—2019年广东省制造业28个行业空间集聚水平进行测量,并运用面板数据回归模型进行制造业空间集聚影响因素分析。研究表明:广东省制造业空间集聚水平总体较高,4个行业高度集聚,10个行业相对集中;21个地市集聚了各具特色的优势产业,但广州、深圳、佛山、东莞等珠三角核心城市是产业空间集聚的重要区域;政府投资、资本禀赋、劳动密集度、行业发展前景和行业规模成为影响广东省制造业产业集聚的重要因素。在此基础上,提出了促进广东省制造业空间集聚的建议对策。The spatial agglomeration level of 28 manufacturing industries in Guangdong province from 2012 to 2019 is measured by the normal distribution and the industrial agglomeration index CIP method, and the factors affecting the spatial agglomeration of the manufacturing industry are analyzed by using the panel data regression model. The research shows that the level of spatial agglomeration of manufacturing industry in Guangdong province is generally high, 4 industries are highly concentrated, and 10 industries are relatively concentrated.21 cities gather their own distinctive and advantageous industries, but the core cities of the Pearl River Delta such as Guangzhou, Shenzhen, Foshan, and Dongguan are important areas for industrial spatial agglomeration. Government investment, capital endowment, labor intensity, industry development prospects and industry scale have become important factors affecting the agglomeration of manufacturing industries in Guangdong province. On this basis, the countermeasures to promote the spatial agglomeration of manufacturing industries in Guangdong province are put forward.

关 键 词：制造业 产业空间集聚 面板数据回归模型 建议对策 

分 类 号：F269.23[经济管理—国民经济]