创新驱动产业转型升级研究——基于中国1998-2016年省域面板数据
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摘要
为了探究创新驱动产业转型升级的作用机制,构建了创新投入与创新产出对产业转型升级内涵质量与外显效应的影响模型,并提出研究假设。基于中国1998-2016年省域面板数据,借助Eviews 9.0计量软件,采用固定效应模型进行实证研究。结果表明,所提出的研究假设均得到验证。创新产出对产业转型升级内涵质量具有积极影响,创新产出的各表征变量(专利授权数、技术市场合同成交金额、新产品销售收入)每增长1%,产业转型升级内涵质量的表征变量人均国内生产总值将提高0.014 8%～0.051 1%。创新投入对产业转型升级外显效应具有积极影响,创新投入的各表征变量(R&D经费内部支出、R&D人员全时当量)每增加1%,产业转型升级外显效应的表征变量产业结构层次系数将提高0.007 1%～0.010 5%。因此,创新能够驱动产业转型升级,但创新投入与创新产出对产业转型升级的影响机制并不相同。研究结果为创新驱动产业转型升级问题的研究提供了一个新的研究范式,对实施创新驱动发展战略、促进产业转型升级有借鉴意义。
In order to explore the mechanism of innovation driven industry transformation and upgrading, the influence model of innovation input and innovation output on the content quality and explicit effect of industry transformation and upgrading is constructed, and the relevant research hypotheses are put forward. Based on provincial panel data of 1998-2016 in China, the empirical study is conducted by adopting fixed effect model with Eviews 9.0. The research hypothesis proposed in this study has been verified. On the one hand, the positive effect of innovation output on the content quality of industry transformation and upgrading is significant. When every change in various characteristic indicators of innovation output(i.e., patent applications accepted, value of contract deals in technical markets, sales revenue of new products) goes up 1%, per capita GDP as the indicator of the content quality of industry transformation and upgrading will increase by 0.014 8%～0.051 1%. On the other hand, the positive effect of innovation input on the explicit effect of industry transformation and upgrading is significant. When every change in various characteristic indicators of innovation input(i.e., internal expenditure on R&D, full-time equivalent of R&D personnel) goes up 1%, the level coefficient of industrial structure adjustment as the indicator of the explicit effect of industry transformation and upgrading will increase by 0.007 1%～0.010 5%. Innovation can drive industrial transformation and upgrading, but the impact mechanism of innovation input and innovation output on industrial transformation and upgrading is not the same. The research results provide a new research paradigm for the study of noonvation-driven industrial transformation and upgrading and have reference significance for the implementation of innovation-driven development strategy to promote industrial transformation and upgrading.
In order to explore the mechanism of innovation driven industry transformation and upgrading, the influence model of innovation input and innovation output on the content quality and explicit effect of industry transformation and upgrading is constructed, and the relevant research hypotheses are put forward. Based on provincial panel data of 1998-2016 in China, the empirical study is conducted by adopting fixed effect model with Eviews 9.0. The research hypothesis proposed in this study has been verified. On the one hand, the positive effect of innovation output on the content quality of industry transformation and upgrading is significant. When every change in various characteristic indicators of innovation output(i.e., patent applications accepted, value of contract deals in technical markets, sales revenue of new products) goes up 1%, per capita GDP as the indicator of the content quality of industry transformation and upgrading will increase by 0.014 8%～0.051 1%. On the other hand, the positive effect of innovation input on the explicit effect of industry transformation and upgrading is significant. When every change in various characteristic indicators of innovation input(i.e., internal expenditure on R&D, full-time equivalent of R&D personnel) goes up 1%, the level coefficient of industrial structure adjustment as the indicator of the explicit effect of industry transformation and upgrading will increase by 0.007 1%～0.010 5%. Innovation can drive industrial transformation and upgrading, but the impact mechanism of innovation input and innovation output on industrial transformation and upgrading is not the same. The research results provide a new research paradigm for the study of noonvation-driven industrial transformation and upgrading and have reference significance for the implementation of innovation-driven development strategy to promote industrial transformation and upgrading.
引文
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[2]宋晶,陈劲.全球价值链升级下中国创新驱动发展战略的实施策略[J].技术经济,2016,35(5):6-9.SONG Jing,CHEN Jin.Implementation on innovation-driven development strategy of China under global value chain upgrading[J].Technology Economics,2016,35(5):6-9.
[3]白极星,周京奎.研发聚集、创新能力与产业转型升级---基于中国工业企业数据实证研究[J].科学决策,2017(1):1-17.BAI Jixing,ZHOU Jingkui.R&D agglomeration,innovation ability and industrial transformation and upgrading:Empirical research on China's industrial enterprise data based on 2005-2007[J].Scientific Decision Making,2017(1):1-17.
[4]BAUMOL W J.Macroeconomics of unbalanced growth:The anatomy of the urban crises[J].The American Economic Review,1967,57(3):415-426.
[5]MONTOBBIO F.An evolutionary model of industrial growth and structural change[J].Structural Change and Economic Dynamics,2002,13(4):387-414.
[6]纪玉俊,李超.创新驱动与产业升级---基于我国省际面板数据的空间计量检验[J].科学学研究,2015,33(11):1651-1659.JI Yujun,LI Chao.Innovation driving and industrial upgrading:The spatial econometric analysis based on China's provincial panel data[J].Studies in Science of Science,2015,33(11):1651-1659.
[7]蔡玉蓉,汪慧玲.创新投入对产业结构升级的影响机制研究---基于分位数回归的分析[J].经济问题探索,2018(1):138-146.
[8]BAPTISTA R,SWANN P.Do firms in clusters innovate more?[J].Research Policy,1998,27(5):525-540.
[9]霍远,王盛兰.产业创新与产业升级耦合协调发展的时空特征及驱动因素研究[J].商业经济研究,2018(16):175-178.
[10]陈生明,张亚斌,陈晓玲.技术选择、产业结构升级与经济增长---基于半参数空间面板向量自回归模型的研究[J].经济经纬,2017,34(5):87-92.CHEN Shengming,ZHANG Yabin,CHEN Xiaoling.Technology choice,upgrading of industrial structure and economic growth:Research based on semi-parameter spatial panel vector auto-regression model[J].Economic Survey,2017,34(5):87-92.
[11]高素英,钦彦祥,张烨.创新投入影响产业结构优化升级路径分析---基于本地效应与多元空间溢出效应[J].科技进步与对策,2017,34(19):60-67.GAO Suying,QIN Yanxiang,ZHANG Ye.An analysis of the effect of innovation input on industrial structure optimization and industrial upgrading:Based on local effects and pluralistic spatial spillover effects[J].Science&Technology Progress and Policy,2017,34(19):60-67.
[12]干春晖,郑若谷,余典范.中国产业结构变迁对经济增长和波动的影响[J].经济研究,2011,21(5):4-16.GAN Chunhui,ZHENG Ruogu,YU Dianfan.An empirical study on the effects of industrial structure on economic growth and fluctuations in China[J].Economic Research Journal,2011,21(5):4-16.
[13]金碚.工业的使命和价值---中国产业转型升级的理论逻辑[J].中国工业经济,2014(9):51-64.JIN Bei.The mission and value of industry:The theoretical logic of industrial transformation and upgrading in China[J].China Industrial Economics,2014(9):51-64.
[14]吴江.科技创新与产业转型研究[M].北京:经济管理出版社,2014.
[15]SCHUMPETER J.The Theory of Economic Development[M].Cambridge:Harvard University Press,1934.
[16]GRILICHES Z.Issues in assessing the contribution of research and development to productivity growth[J].The Bell Journal of Economics,1979,10(1):92-116.
[17]田晖,宋清.创新驱动能否促进智慧城市经济绿色发展---基于我国47个城市面板数据的实证分析[J].科技进步与对策,2018,35(24):6-12.TIAN Hui,SONG Qing.Does innovation-driven promote smart cities'green economic growth:Empirical analysis of panel data from 47cities in China[J].Science&Technology Progress and Policy,2018,35(24):6-12.
[18]张杰.进口对中国制造业企业专利活动的抑制效应研究[J].中国工业经济,2015(7):68-83.ZHANG Jie.Study on the inhibitory effect of imports on patent activities of China’s manufacturing enterprises[J].China Industrial Economics,2015(7):68-83.
[19]李小平,朱钟棣.国际贸易、R&D溢出和生产率增长[J].经济研究,2006(2):31-43.LI Xiaoping,ZHOU Zhongdi.International trade,R&D spillover and productivity development:Based on the analysis of Chinese industry's panel data[J].Economic Research Journal,2006(2):31-43.
[20]贾俊生,伦晓波,林树.金融发展、微观企业创新产出与经济增长---基于上市公司专利视角的实证分析[J].金融研究,2017(1):99-113.JIA Junsheng,LUN Xiaobo,LIN Shu.Financial development,corporation innovation and economic growth:Empirical analysis from the patent perspective[J].Journal of Financial Research,2017(1):99-113.
[21]李政,杨思莹.创新投入、产业结构与经济增长[J].求是学刊,2015,42(4):61-67.LI Zheng,YANG Siying.Innovation input,industrial structure and economic growth[J].Seeking Truth,2015,42(4):61-67.
[22]HU A G Z,PNG I P L.Patent rights and economic growth:Evidence from cross-country panels of manufacturing industries[J].Oxford Economic Papers,2013,65(3):675-698.
[23]张杰,高德步,夏胤磊.专利能否促进中国经济增长---基于中国专利资助政策视角的一个解释[J].中国工业经济,2016(1):83-98.ZHANG Jie,GAO Debu,XIA Yinlei.Do patents drive economic growth in China:An explanation based on government patent subsidy policy[J].China Industrial Economics,2016(1):83-98.
[24]张江雪.我国技术市场的发展状况及其经济效应研究[J].中国新技术新产品,2010(12):1-4.
[25]GREUNZ L.Industrial structure and innovation-evidence from European regions[J].Journal of Evolutionary Economics,2004,14(5):563-592.
[26]樊杰,刘汉初.“十三五”时期科技创新驱动对我国区域发展格局变化的影响与适应[J].经济地理,2016,36(1):1-9.FAN Jie,LIU Hanchu.Impacts and adaptation of China’s regional development pattern changes influenced by scientific and technological innovation driven during the Thirteenth National Five-year Plan period[J].Economic Geography,2016,36(1):1-9.
[27]LAWRENCE R M,TATUM J S.Energy possibilities:Rethinking alternatives and the choice-making process[J].The American Political Science Review,1996,90(2):440-441.
[28]王永进,张国峰.开发区生产率优势的来源:集聚效应还是选择效应?[J].经济研究,2016(7):58-71.WANG Yongjin,ZHANG Guofeng.Sources of productivity advantages of special economic zones:Agglomeration effect or selection effect?[J].Economic Research Journal,2016(7):58-71.
[29]李健.产权结构变迁和中国创新能力[J].中国科技论坛,2018(2):30-37.LI Jian.The structure change of property right and China's innovation capacity[J].Forum on Science and Technology in China,2018(2):30-37.
[30]冯智雨,戴万亮.辽宁省创新效率评估与创新驱动路径研究---基于DEA-Tobit模型[J].科技与管理,2017,19(5):16-20.FENG Zhiyu,DAI Wanliang.Research on innovation efficiency evaluation and innovation-driven path of Liaoning province:Based on DEA-Tobit model[J].Science-Technology and Management,2017,19(5);16-20.
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