江苏省制造业集聚及地理格局演化
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摘要
文章运用区域基尼系数与空间自相关测度了江苏省2001-2016年制造业集聚与地理空间格局及演化。结果显示:江苏省制造业整体上呈现出先集聚后分散的"倒U型"趋势,三种类型行业集聚与分散变动趋势较为同步,资本密集型行业集聚程度高于技术密集型行业与劳动密集型行业;制造业地理格局存在空间正相关关系,同2001年相比,2016年劳动密集型与资本密集型行业空间正相关程度有所减小,技术密集型行业空间正相关程度有所增加;整合区域基尼系数与莫兰指数构建集聚—地理格局矩阵,可以将全部26个行业划分为集聚—集中、分散—集中、分散—离散和集聚—离散四种类型,2001-2016年,26个行业在矩阵中的分布由集中在中心交点附近区域向外扩散,由右向左移动是主要的特征。
This paper applies the regional Gini coefficient and the spatial autocorrelation to measure the pattern and evolution of manufacturing agglomeration and geographical space in Jiangsu province from 2001 to 2016. The results show that: The manufacturing industrial of Jiangsu province shows the trend of"inverted U type",which is dispersed after agglomeration,three types of industrial agglomeration and dispersed trend are more synchronized,and the concentration of capital-intensive industries is higher than that of technology-intensive and labor-intensive industries; The geographical pattern of manufacturing industry has a spatial positive correlation,compared with 2001,the labor-intensive and industry capital-intensive industries in 2016 have a decreasing positive spatial correlation,whereas the technology-intensive industries have an increasing positive spatial correlation;The integrated spatial Gini coefficient and the Morin index construct the aggregation-geographical pattern matrix,which can classify all 26 industries into four types: clusters-concentrated,decentralized-concentrated,decentralized-discrete and cluster-discrete. From 2001 to 2016,the distribution of 26 industries in the matrix spreads outward from the area near the center intersection,and the movement from right to left is the main feature.
This paper applies the regional Gini coefficient and the spatial autocorrelation to measure the pattern and evolution of manufacturing agglomeration and geographical space in Jiangsu province from 2001 to 2016. The results show that: The manufacturing industrial of Jiangsu province shows the trend of"inverted U type",which is dispersed after agglomeration,three types of industrial agglomeration and dispersed trend are more synchronized,and the concentration of capital-intensive industries is higher than that of technology-intensive and labor-intensive industries; The geographical pattern of manufacturing industry has a spatial positive correlation,compared with 2001,the labor-intensive and industry capital-intensive industries in 2016 have a decreasing positive spatial correlation,whereas the technology-intensive industries have an increasing positive spatial correlation;The integrated spatial Gini coefficient and the Morin index construct the aggregation-geographical pattern matrix,which can classify all 26 industries into four types: clusters-concentrated,decentralized-concentrated,decentralized-discrete and cluster-discrete. From 2001 to 2016,the distribution of 26 industries in the matrix spreads outward from the area near the center intersection,and the movement from right to left is the main feature.
引文
[1]李东光,郭凤城.产业集群与城市群协调发展对区域经济的影响[J].经济纵横,2011(8):40-43.
[2]唐松.基于非均衡发展理论的区域协调内涵诠释[J].经济经纬,2008(1):70-72.
[3]马歇尔.经济学原理[M].长沙:湖南文艺出版社,2012:1-10.
[4]RONALD H.COASE.The Nature of the Firm[J].Economic,1937(11):386-405.
[5]黄家明,方卫东.交易费用理论:从科斯到威廉姆森[J].合肥工业大学学报:社会科学版,2000(1):33-36.
[6]KRUGMAN P.Increasing Returns and Economic Geography[J].Journal of Political Economy,1991,99(3):483-499.
[7]KUEI H N,GRANT M,SEUNG B,et al.Trust,learning and a firm's involvement in industrial clusters:a conceptual framework[J].Competitiveness Review:An International Business Journal incorporating Journal of Global Competitiveness,2012,22(2):133-146.
[8]YOUNG J L.Characteristics of Tourism Industrial Clusters from Spatial Perspectives[J].International Journal of Tourism Sciences,2004,4(2):21-40.
[9]FRANK M,DIMITEIOS T,HUANG Q H.The development of industrial clusters and public policy[J].Entrepreneurship&Regional Development,2006,18(6):525-542.
[10]GUSTAVO B L.Internationalization of companies in industrial clusters:a study of medical,dental and hospital supply industries in Ribeir2o Preto-SP[J].REGE-Revista de Gest2o,2011,18(1):19-33.
[11]贺灿飞,谢秀珍.中国制造业地理集中与省区专业化[J].地理学报,2006(2):212-222.
[12]罗胤晨,谷人旭.1980-2011年中国制造业空间集聚格局及其演变趋势[J].经济地理,2014(7):82-89.
[13]贺灿飞,潘峰华.中国制造业地理集聚的成因与趋势[J].南方经济,2011(6):38-52.
[14]文东伟,冼国明.中国制造业产业集聚的程度及其演变趋势:1998-2009年[J].世界经济,2014(3):3-31
[15]靖学青.长三角地区制造业转移与集聚分析[J].南京社会科学,2010(3):9-13,21.
[16]李燕,贺灿飞.1998-2009年珠江三角洲制造业空间转移特征及其机制[J].地理科学进展,2013(5):777-787.
[17]马国霞,朱晓娟,田玉军.京津冀都市圈制造业产业链的空间集聚度分析[J].人文地理,2011(3):116-121.
[18]吕卫国,陈雯.江苏省制造业产业集群及其空间集聚特征[J].经济地理,2009(10):1677-1684.
[19]贺灿飞,朱晟君.制造业地理集聚的区域差异研究——江苏和安徽对比研究[J].地理科学,2008(6):715-721.
[20]韩玉刚,焦华富,郇恒飞.省际边缘区传统制造业集聚过程及动因分析——以安徽省宁国市耐磨铸件产业为例[J].经济地理,2011(7):1128-1133.
(1)从各地区占全省GDP比重看,2010年苏南地区为60 .18%,苏北地区为21.32%,2016年苏南地区下降为57 .228%,苏北地区上升为23.2%,地区间差距在缩小;但是从各地市平均产值来看,苏南地区为苏北地区的2.47倍,苏中地区产值也达到了苏北地区的1.41倍,区域间仍然存在着较大的差异。(2)本结果通过聚类分析法对计算出的全部区域基尼系数进行聚类分析后得到,聚类结果显示可以将研究区间全部行业处于0~1之间的区域基尼系数分为5个层次,分别为低度集聚[0,0.30)、中低度集聚[0.30,0.45)、中度集聚[0.45,0.65)、中高度集聚[0.65,0.78)和高度集聚[0.78,1],其中中等集聚层次的中点为0.55,所以取0.55为分界点。本部分划分标准是基于本研究需要而定,不构成作为其他研究划分标准的建议。
[2]唐松.基于非均衡发展理论的区域协调内涵诠释[J].经济经纬,2008(1):70-72.
[3]马歇尔.经济学原理[M].长沙:湖南文艺出版社,2012:1-10.
[4]RONALD H.COASE.The Nature of the Firm[J].Economic,1937(11):386-405.
[5]黄家明,方卫东.交易费用理论:从科斯到威廉姆森[J].合肥工业大学学报:社会科学版,2000(1):33-36.
[6]KRUGMAN P.Increasing Returns and Economic Geography[J].Journal of Political Economy,1991,99(3):483-499.
[7]KUEI H N,GRANT M,SEUNG B,et al.Trust,learning and a firm's involvement in industrial clusters:a conceptual framework[J].Competitiveness Review:An International Business Journal incorporating Journal of Global Competitiveness,2012,22(2):133-146.
[8]YOUNG J L.Characteristics of Tourism Industrial Clusters from Spatial Perspectives[J].International Journal of Tourism Sciences,2004,4(2):21-40.
[9]FRANK M,DIMITEIOS T,HUANG Q H.The development of industrial clusters and public policy[J].Entrepreneurship&Regional Development,2006,18(6):525-542.
[10]GUSTAVO B L.Internationalization of companies in industrial clusters:a study of medical,dental and hospital supply industries in Ribeir2o Preto-SP[J].REGE-Revista de Gest2o,2011,18(1):19-33.
[11]贺灿飞,谢秀珍.中国制造业地理集中与省区专业化[J].地理学报,2006(2):212-222.
[12]罗胤晨,谷人旭.1980-2011年中国制造业空间集聚格局及其演变趋势[J].经济地理,2014(7):82-89.
[13]贺灿飞,潘峰华.中国制造业地理集聚的成因与趋势[J].南方经济,2011(6):38-52.
[14]文东伟,冼国明.中国制造业产业集聚的程度及其演变趋势:1998-2009年[J].世界经济,2014(3):3-31
[15]靖学青.长三角地区制造业转移与集聚分析[J].南京社会科学,2010(3):9-13,21.
[16]李燕,贺灿飞.1998-2009年珠江三角洲制造业空间转移特征及其机制[J].地理科学进展,2013(5):777-787.
[17]马国霞,朱晓娟,田玉军.京津冀都市圈制造业产业链的空间集聚度分析[J].人文地理,2011(3):116-121.
[18]吕卫国,陈雯.江苏省制造业产业集群及其空间集聚特征[J].经济地理,2009(10):1677-1684.
[19]贺灿飞,朱晟君.制造业地理集聚的区域差异研究——江苏和安徽对比研究[J].地理科学,2008(6):715-721.
[20]韩玉刚,焦华富,郇恒飞.省际边缘区传统制造业集聚过程及动因分析——以安徽省宁国市耐磨铸件产业为例[J].经济地理,2011(7):1128-1133.
(1)从各地区占全省GDP比重看,2010年苏南地区为60 .18%,苏北地区为21.32%,2016年苏南地区下降为57 .228%,苏北地区上升为23.2%,地区间差距在缩小;但是从各地市平均产值来看,苏南地区为苏北地区的2.47倍,苏中地区产值也达到了苏北地区的1.41倍,区域间仍然存在着较大的差异。(2)本结果通过聚类分析法对计算出的全部区域基尼系数进行聚类分析后得到,聚类结果显示可以将研究区间全部行业处于0~1之间的区域基尼系数分为5个层次,分别为低度集聚[0,0.30)、中低度集聚[0.30,0.45)、中度集聚[0.45,0.65)、中高度集聚[0.65,0.78)和高度集聚[0.78,1],其中中等集聚层次的中点为0.55,所以取0.55为分界点。本部分划分标准是基于本研究需要而定,不构成作为其他研究划分标准的建议。