创新要素集聚对区域创新绩效的非线性边际效应演化分析
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摘要
要素集聚可能存在正负两方面的外部性,充分发挥创新要素集聚的正外部性,对于提升区域创新绩效尤为重要。基于2005—2015年中国省级面板数据,测算了当前各省创新要素集聚水平,运用投影寻踪模型和随机前沿分析技术测算了分省创新绩效,探讨了创新要素集聚对创新绩效的非线性边际效应及其在创新绩效不同分布下的演化特征。研究结果表明:各地区的创新绩效存在较大差异,东部地区的创新绩效明显高于中西部地区,考察期内全国整体创新绩效先降后升,呈现出U型趋势;创新要素集聚与创新绩效存在显著的倒U型关系,且创新要素在不同创新水平下的最优集聚度不同,随着创新绩效的提高,两类创新要素的最优集聚规模整体上呈现出下降趋势。在上述研究结论的基础上,提出相应的政策建议。
Elements cluster may have both positive and negative externality,giving full play to positive externality of innovation elements cluster is especially important to improve the regional innovation performance.Based on Chinese provincial panel data during 2005-2015 to measure the innovation elements cluster levels and provincial innovation efficiency through Projection Pursuit Model and Stochastic Frontier Analysis,furtherly,discussed the nonlinear marginal effects of innovation elements cluster on regional innovation performance and its evolving feature under the regional innovation performance's different distribution.The study shows that:there are big gaps in regional innovation performance,and the innovation performances of eastern regions are better than that of central and western regions,the innovation performance goes up after dropping as a whole during the investigated period,presenting U Shape;the relationship between innovation elements cluster and regional innovation performance presenting Inverted U Shape,the innovation elements' optimum clustering levels differ greatly as the innovation performance are different,with the improvement of innovation performance,the optimum clustering levels of two innovation elements present a downward trend as a whole.Based on the conclusions above,some relevant political suggestions were presented.
Elements cluster may have both positive and negative externality,giving full play to positive externality of innovation elements cluster is especially important to improve the regional innovation performance.Based on Chinese provincial panel data during 2005-2015 to measure the innovation elements cluster levels and provincial innovation efficiency through Projection Pursuit Model and Stochastic Frontier Analysis,furtherly,discussed the nonlinear marginal effects of innovation elements cluster on regional innovation performance and its evolving feature under the regional innovation performance's different distribution.The study shows that:there are big gaps in regional innovation performance,and the innovation performances of eastern regions are better than that of central and western regions,the innovation performance goes up after dropping as a whole during the investigated period,presenting U Shape;the relationship between innovation elements cluster and regional innovation performance presenting Inverted U Shape,the innovation elements' optimum clustering levels differ greatly as the innovation performance are different,with the improvement of innovation performance,the optimum clustering levels of two innovation elements present a downward trend as a whole.Based on the conclusions above,some relevant political suggestions were presented.
引文
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[2]Jin H,Wentao Y U,Guo X,et al.Creative Industries Agglomeration,Regional Innovation and Productivity Growth in China[J].Chinese Geographical Science,2014,24(2).
[3]马子量,郭志仪.城市化发展中的产业升级:集聚推动、溢出效应与空间衰减——基于西北地区的空间计量[J].统计与信息论坛,2016(2).
[4]沈能,赵增耀,周晶晶.生产要素拥挤与最优集聚度识别——行业异质性的视角[J].中国工业经济,2014(5).
[5]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).
[6]Cong H,Zou D.Research on the Mechanism and Spatial-Temporal Differentiation of the Coupling Coordination Development Based on Industrial Cluster Agglomeration[J].Cluster Computing,2017(9).
[7]陶长琪,周璇.环境规制、要素集聚与全要素生产率的门槛效应研究[J].当代财经,2015(1).
[8]Su Y S,Chen J.Introduction to Regional Innovation Systems in East Asia[J].Technological Forecasting&Social Change,2015,100(1).
[9]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(2).
[10]邹文杰.研发要素集聚、投入强度与研发效率——基于空间异质性的视角[J].科学学研究,2015,33(3).
[11]吴延兵.中国哪种所有制类型企业最具创新性?[J].世界经济,2012(6).
[12]Kontolaimou A,Giotopoulos I,Tsakanikas A.A Typology of European Countries Based on Innovation Efficiency and Technology Gaps:The Role of Early-Stage Entrepreneurship[J].Economic Modelling,2016,52(B).
[13]赖永剑.基于潜类别随机前沿的区域创新效率及其影响因素分析[J].统计与信息论坛,2014(10).
[14]Carayannis E G,Grigoroudis E,Goletsis Y.A Multilevel and Multistage Efficiency Evaluation of Innovation Systems:A Multiobjective DEA Approach[J].Expert Systems with Applications,2016,62(C).
[15]郝金磊,董原.西部地区企业科技创新效率研究[J].西安财经学院学报,2017,30(2).
[16]卓乘风,邓峰,白洋,艾麦提江·阿布都哈力克.丝绸之路经济带区域创新与区域信息化的耦合协调性分析[J].科技管理研究,2017(4).
[17]刘和东.国内市场规模与创新要素集聚的虹吸效应研究[J].科学学与科学技术管理,2013(7).
[18]戴魁早,刘友金.要素市场扭曲如何影响创新绩效[J].世界经济,2016(11).
[19]Greene W H.On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model[J].Econometrica,1981,49(2).
[20]王鹏,曾坤.创新环境因素对区域创新效率影响的空间计量研究[J].贵州财经大学学报,2015(2).