我国省域创新产出的空间特征和时空演化——基于探索性空间数据分析的实证

以我国31个省域作为空间观测单元,以专利申请受理数作为创新产出的衡量指标,对我国1997～2008年期间省域创新产出的空间分布进行了探索性空间数据分析(ESDA)。通过计算区位基尼系数和集中度指数,发现我国的创新活动显示了相当高水平的空间集中,并且这种集中程度在过去的十多年里表现出了稳定的增长趋势;对全局的Moran’s I统计分析表明:省际创新活动之间存在着显著的空间自相关(空间依赖性),证明了知识溢出的存在性和空间局限性;对局部的Moran’s I分析进一步揭示了省际创新活动水平的相关模式,Moran散点图刻画了创新活动的空间集聚模式及其时空演变态势。研究结果说明经过十几年的发展,我国省域创新活动的地域性特征十分显著。

Spatial characteristics and dynamic changes of provincial innovation output in China:An investigation using the ESDA

Innovation activities in each region not only depend on their own characteristics,but also on those of the regions that form the neighborhood to which it belongs.Regional spillover as a spatial interaction is important in explaining agglomeration,innovation and regional growth.A great deal of literature has deeply dealt with the issue from a spatial perspective since the 1990s,especially in the context of urban and regional studies.Unfortunately,the traditional approaches to regional innovation suppose that each region is independent from others.This paper uses spatial statistical techniques to establish the statistical relations among data according to the geographical locations.It aims to understand the spatial dependence and autocorrelation related to geographical locations.Using the methods of exploratory spatial data analysis(ESDA) and spatial analysis software,this paper analyzes the spatial distribution of innovation outputs,measured by the number of patient applications,throughout 31 Chinese provinces from 1997 to 2008.The visual patent distribution plot has shown the distribution of innovation outputs at the provincial level and its spatial dynamic changes.A significantly high level of spatial concentration of innovation outputs among Chinese provinces has been captured by the computed spatial Gini coefficient and the Concentration Ratio,and the concentration level has increased steadily over the past 10 years.The analysis using the Moran’s I statistics gives the strong evidence of spatial autocorrelation in innovation activities among provinces,while the concentration pattern of innovation activities among provinces and its changes over time have been revealed by using the local Moran’s I and the Moran scatter plot,which indicate the clustering nature of the spatial distribution of provincial innovation activities.Spatial Gini coefficient and Moran’s I index have indicated that innovation activities of Chinese provinces are not randomly distributed.Our findings suggest that innovation activities are spatially differentiated among Chinese provinces over the 10 years,and innovation activities at the provincial level are highly localized.This study can provide a scientific basis for the intuitive expression of the spatial correlation of innovation outputs among provinces,and puts forward that the spatial statistical analysis could present some references valuable for analyzing spatial structure and patterns and policy-making.