|
|
|
| The Spatial-temporal Pattern and Dynamic Evolution of The Innovation Factors Agglomeration Capacity in China |
| Liu Shuai,Li Qi,Xu Xiaoyu,Qiao Zhilin |
| (School of Economics and Finance, Xi'an Jiaotong University, Xi'an 710061, China) |
|
|
|
|
Abstract This study takes industrial enterprises, research institutes, and universities as the main regional innovation subjects and studies the spatial-temporal pattern and dynamic evolution of their innovation factors agglomeration capacity based on the data collected from 30 provinces in China during 2000-2018.The Gini coefficient and spatial decomposition, exploratory spatial analysis, kernel density estimation, spatial Markov chain, and hidden Markov model are comprehensively used.Research finds that: (1) there is a small regional gap in the capacity of innovation factors agglomeration between industrial enterprises and universities.And the regional gap in the capacity of innovation factors agglomeration between scientific institutes is relatively large.(2) The regional disparity of innovation factors agglomeration capacity of three kinds of innovation subjects mainly comes from the disparity between non-adjacent regions’ innovation factors agglomeration capacity.The innovation factors agglomeration capacity of three kinds of innovation subjects shows positive spatial convergence, and their spatial distribution is characterized by different polarization phenomena and trends.(3) the innovation factors agglomeration capacity of industrial enterprises, research institutes, and universities have experienced three states in the sample period, which are high, medium, and low, respectively.The state transition of innovation factors agglomeration capacity shows the characteristics of path-dependence and space-dependence.
|
|
Received: 29 December 2020
|
|
|
|
|
|
| [1] GAGLIARDI L.Does skilled migration foster innovative performance? evidence from British local areas[J].Papers in Regional Science, 2015, 94(4):773-794.[2] OTSUKA A.Dynamics of agglomeration, accessibility, and total factor productivity: evidence from Japanese regions[J].Economics of Innovation and New Technology, 2017, 102(4):1-17.[3] 周璇, 陶长琪.要素空间集聚、制度质量对全要素生产率的影响研究[J].系统工程理论与实践, 2019, 39(4):1051-1066.[4] YANG C-H, LIN H-L, LI H-Y.Influences of production and R&D agglomeration on productivity: evidence from Chinese electronics firms[J].China Economic Review, 2013, 27:162-178.[5] 王钺, 刘秉镰.创新要素的流动为何如此重要——基于全要素生产率的视角[J].中国软科学, 2017,32(8):91-101.[6] 吴卫红, 董姗, 张爱美, 等.创新要素集聚对区域创新绩效的溢出效应研究——基于门槛值的分析[J].科技管理研究, 2020, 40(5):6-14.[7] 赖一飞, 覃冰洁, 雷慧, 等.“中三角”区域省份创新要素集聚与经济增长的关系研究[J].科技进步与对策, 2016, 33(23):32-39.[8] 余泳泽.创新要素集聚、政府支持与科技创新效率——基于省域数据的空间面板计量分析[J].经济评论, 2011,32(2):93-101.[9] BUZARD K, CARLINO G A, HUNT R M, et al.The agglomeration of American R&D labs[J].Journal of Urban Economics, 2017, 101:14-26.[10] 周锐波, 刘叶子, 杨卓文.中国城市创新能力的时空演化及溢出效应[J].经济地理, 2019, 39(4):85-92.[11] BARRIOS C, FLORES E, MARTíNEZ M .Club convergence in innovation activity across European regions[J].Papers in Regional Science, 2019, 98(4):1545-1565.[12] PI J, ZHANG P.Rural-urban human capital disparity and skilled-unskilled wage inequality in China[J].Review of Development Economics, 2018, 22(2):827-843.[13] 纪祥裕.金融地理影响了城市创新能力吗[J].产业经济研究, 2020(1):114-127.[14] 陆铭, 李鹏飞, 钟辉勇.发展与平衡的新时代——新中国70年的空间政治经济学[J].管理世界, 2019, 35(10):11-23，63，219.[15] 黄贤金, 卢芹莉.世界资源地理研究:中国资源地理学的现状、缺失与机遇[J].地理研究, 2016, 35(4):607-616.[16] SOO K T.Innovation across cities[J].Journal of Regional Science, 2018, 58(2):295-314.[17] YANG C-H, HUANG C-H.Agglomeration, ownership, and R&D activity: firm-level evidence from China's electronics industry[J].Empirical Economics, 2018, 54(4):1673-1696.[18] 赵建吉, 曾刚.创新的空间测度:数据与指标[J].经济地理, 2009, 29(8):1250-1255.[19] 郭庆宾, 张中华.长江中游城市群要素集聚能力的时空演变[J].地理学报, 2017, 72(10):1746-1761.[20] 余泳泽, 刘大勇.创新要素集聚与科技创新的空间外溢效应[J].科研管理, 2013, 34(1):46-54.[21] FUJITA M, THISSE J-F.Does geographical agglomeration foster economic growth? and who gains and loses from it[J].The Japanese Economic Review, 2003, 54(2):121-145.[22] 周茂, 李雨浓, 姚星, 等.人力资本扩张与中国城市制造业出口升级:来自高校扩招的证据[J].管理世界, 2019, 35(5):64-77，198-199.[23] 吴卫红, 杨婷, 张爱美.高校创新要素集聚对区域创新效率的溢出效应[J].科技进步与对策, 2018, 35(11):46-51.[24] BOSETTI V, CATTANEO C, VERDOLINI E.Migration of skilled workers and innovation: a European perspective[J].Journal of International Economics, 2015, 96(2):311-322.[25] TABUCHI T.Historical trends of agglomeration to the capital region and new economic geography[J].Regional Science and Urban Economics, 2014, 44:50-59.[26] FU Y, GABRIEL S A.Labor migration, human capital agglomeration and regional development in China[J].Regional Science and Urban Economics, 2012, 42(3):473-484.[27] VANDENBUSSCHE J, AGHION P, MEGHIR C.Growth, distance to frontier and composition of human capital[J].Journal of Economic Growth, 2006, 11(2):97-127.[28] 张玉昌.企业研发决策、要素配置与创新效率——基于企业微观科技活动数据[J].财经论丛, 2019,35(8):3-10.[29] 杨明海, 张红霞, 孙亚男.七大城市群创新能力的区域差距及其分布动态演进[J].数量经济技术经济研究, 2017, 34(3):21-39.[30] REY S J, SMITH R J.A spatial decomposition of the Gini coefficient[J].Letters in Spatial and Resource Sciences, 2013, 6(2):55-70.[31] 张志强.空间加权矩阵设置与空间面板参数估计效率[J].数量经济技术经济研究, 2014, 31(10):122-138.[32] 王元地, 陈凤珍, 李敏.我国科研机构专利许可的空间分布及流动网络分析[J].情报杂志, 2016, 35(1):57-63.[33] 中国社会科学院工业经济研究所课题组, 张其仔.“十四五”时期我国区域创新体系建设的重点任务和政策思路[J].经济管理, 2020, 42(8):5-16.[34] CHEN W, WEI X, XIAOGUO ZHU K.Engaging voluntary contributions in online communities: a hidden markov model[J].MIS Quarterly, 2018, 42(1):83-100.[35] 杨明海, 张红霞, 孙亚男, 等.中国八大综合经济区科技创新能力的区域差距及其影响因素研究[J].数量经济技术经济研究, 2018, 35(4):3-19.[36] GUASTELLA G, TIMPANO F.Knowledge, innovation, agglomeration and regional convergence in the EU: motivating place-based regional intervention[J].Review of Regional Research, 2016, 36(2):121-143. |
|
|
|
