江苏省县域创新产出空间计量经济分析

摘要/Abstract

摘要： 以专利授权量来表征创新产出，运用标准差、变异系数、空间自相关和空间计量经济模型等方法对1986-2014年江苏省县域创新产出的差异演变及影响因素进行研究。结果表明：（1）江苏省县域创新产出发展具有明显的不均衡性，2012年以后，江苏省县域创新产出的绝对差异和相对差异都呈下降趋势。（2）南京市区的创新产出，在九五时期之后呈弱化趋势，苏州市区、昆山市、无锡市区等苏南地区创新产出提升较快。（3）江苏省县域创新产出在苏南、苏中、苏北三大地带的创新产出梯度递减，呈南高北低的空间格局。（4）苏北地区的大部分县域“低-低”集聚，并有向苏中地区扩散的趋势，“高-高”集聚的县域较少，主要集中在苏南地区。（5）空间交互作用是江苏省县域创新产出差异的重要原因。（6）区域创新环境、科技政策对县域创新产出具有显著影响。（7）在具体因素方面，表征经济基础、研发投入、科技人才、传统基础设施、通讯基础设施及FDI的回归系数相差不大，大多在0.090上下波动，其中国际互联网用户数的系数最大，达到0.094，而科技政策的回归系数较小，仅为0.012。

关键词: 创新产出, 县域, 差异演变, 空间自相关, 空间计量经济分析

Abstract: At present, the spatial spillover of innovation output is mostly carried out at the provincial and municipal scales, but the research at county scale is less. In this paper, representing innovation output by patent licensing, the standard deviation, coefficient of variation, spatial autocorrelation and spatial econometric model were employed to study the differences of innovation output in counties of Jiangsu Province from 1986 to 2014. The results show as follows: (1)Before 2006, the absolute difference innovative output among counties of Jiangsu Province increased slowly, then rapidly widening, increased from 268.42 in 2006 to 7045.6 in 2012. The relative difference reached its highest of 2.91 in 2000, after that it began to decline. The relative difference fluctuated from time to times, but it showed downward trend overall. (2)The innovation output of Nanjing City showed a weakening trend during the Ninth Five-Year Plan. Innovation output in Suzhou City, Kunshan City, Wuxi City and South of Jiangsu Province were increasing rapidly. (3)The innovation output in counties of south Jiangsu, middle Jiangsu and north Jiangsu declined in gradient, and it showed the spatial pattern of high in north and low in south. (4)Most of the counties in north Jiangsu showed the "low-low" gathering and had a tendency to spread to middle Jiangsu. The counties of the "high-high" gathering were few and mainly concentrated in south Jiangsu. (5)Moran's I of the innovation output in the counties of Jiangsu province was 0.477, normal statistic Z-value was 4.794, and spatial interaction terms of coefficient was 0.609, so it shows that spatial interaction is the important reason for innovation output difference. (6)Regional innovation environment, science and technology policy had significant impacts on the county's innovative output, according to the regression coefficients which were 0.529 and 0.110, respectively. (7)In specific factors, there was no difference of regression coefficients between economic basis, R&D investment, R&D personnel, traditional infrastructure, communications infrastructure and FDI, which were 0.092, 0.09, 0.091, 0.089, 0.094 and 0.089, respectively. However, regression coefficient of science and technology policy was very small, which was only 0.012. To a certain extent, this study reveals the mechanism for the formation of innovation output difference, which has a revelation to explore the difference of county innovation output.

Key words: innovation output, county, differential evolution, spatial autocorrelation, Spatial Econometric analysis

中图分类号:

F127

张建伟, 窦攀烽, 张永凯, 苗长虹. 江苏省县域创新产出空间计量经济分析[J]. 干旱区地理, 2017, 40(1): 222-229.

ZHANG Jian-wei, DOU Pan-feng, ZHANG Yong-kai, MIAO Chang-Hong. Spatial econometric analysis of innovation output of Jiangsu Province in terms of county scale[J]. , 2017, 40(1): 222-229.

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