我国高技术产业间技术创新效率溢出效应——基于GVAR模型的研究

摘要/Abstract

摘要： 本文采用全局向量自回归（GVAR）模型，在测算中国9个高技术产业1997—2016年技术创新效率的基础上，研究我国高技术产业间技术创新效率的溢出效应。实证研究发现：（1）我国高技术产业间的技术创新效率溢出效应存在差异性，即一个产业技术创新效率对另一个产业溢出效应的大小与这两个产业反过来的影响是不一样的，甚至会出现正向促进作用和逆向竞争关系。（2）医药制造业和通信设备制造业技术创新效率几乎对其他产业的技术创新效率都产生了正向溢出效应，而医疗设备及器械制造业对其他产业的技术创新效率产生了负向溢出效应，即竞争效应。因此，有必要发挥医药制造业和通信设备制造业在技术创新效率方面的引领促进作用，拉动其他高技术产业共同发展，提高整个高技术产业的技术创新效率，促进产业结构转型升级。

关键词: 高技术产业, 技术创新效率, 溢出效应

Abstract: This paper adopts the Global Vector Autoregressive (GVAR) model to study the spillover effects of technological innovation efficiency among China's high-tech industries on the basis of measuring the technological innovation efficiency of nine high-tech industries in China from 1997 to 2016. The empirical results show that:(1) The spillover effect of technological innovation efficiency among high-tech industries in China is different, that is, the spillover effect of technological innovation efficiency in one industry on another industry is different from the reverse effect of the two industries, and there may even be a positive promotion effect and reverse competition relationship. (2) The technological innovation efficiency of pharmaceutical manufacturing and communication equipment manufacturing almost has a positive spillover effect on the technological innovation efficiency of other industries, while the medical equipment and device manufacturing almost has a negative spillover effect on the technological innovation efficiency of other industries, namely the competitive effect. Therefore, it is necessary to give play to the leading and promoting role of pharmaceutical manufacturing industry and communication equipment manufacturing industry in technological innovation efficiency, to promote the mutual development of other high-tech industries, to improve the technological innovation efficiency of the whole high-tech industries, and to promote the transformation and upgrading of industrial structure.

Key words: high-tech industry, technological innovation efficiency, spillover effects

杨友才, 耿璐璐, 史倩姿. 我国高技术产业间技术创新效率溢出效应——基于GVAR模型的研究[J]. 管理评论, 2020, 32(6): 138-149.

Yang Youcai, Geng Lulu, Shi Qianzi. Spillover Effects of Technological Innovation Efficiency among High-tech Industries in China——Based on GVAR Model[J]. Management Review, 2020, 32(6): 138-149.

参考文献

[1] 黄少安. 发展目标与经济增长动力[J]. 中国高校社会科学, 2016,(1):15-17
[2] 王俊松,颜燕,胡曙虹. 中国城市技术创新能力的空间特征及影响因素——基于空间面板数据模型的研究[J]. 地理科学, 2017,37(1):11-18
[3] Arrow K. J. The Economic Implications of Learning by Doing[J]. Review of Economic Studies, 1971,29(3):155-173
[4] Romer P. M. Increasing Returns and Long-Run Growth[J]. Journal of Political Economy, 1986,94(5):1002-1037
[5] Lucas R. E. On the Mechanics of Economic Development[J]. Journal of Monetary Economics, 1988,22(1):3-42
[6] 魏新颖,王宏伟,徐海龙. 高技术产业技术创新的空间关联与溢出效应[J]. 经济问题探索, 2019,(10):155-164
[7] 肖仁桥,钱丽,陈忠卫. 中国高技术产业创新效率及其影响因素研究[J]. 管理科学, 2012,25(5):85-98
[8] 陈凯华,官建成,寇明婷. 中国高技术产业"高产出、低效益"的症结与对策研究——基于技术创新效率角度的探索[J]. 管理评论, 2012,24(4):53-66
[9] 刘树林,姜新蓬,余谦. 中国高技术产业技术创新三阶段特征及其演变[J]. 数量经济技术经济研究, 2015,32(7):104-116
[10] 冯宗宪,丁梦. 本土技术转移对省际高新技术产业创新效率影响的实证分析[J]. 统计与决策, 2018,34(22):108-111
[11] 康淑娟. 基于产业异质性解构我国高技术产业创新价值链[J]. 软科学, 2017,31(7):1-5
[12] Salim A., Razavi M. R., Afsharimofrad M., et al. Foreign Direct Investment and Technology Spillover in Iran:The Role of Technological Capabilities of Subsidiaries[J]. Technological Forecasting & Social Change, 2015,122(9):207-214
[13] 沙文兵,孙君. FDI知识溢出对中国高技术产业创新能力的影响——基于分产业面板数据的检验[J]. 经济学家, 2010,(11):75-79
[14] 王敏. 我国高技术产业技术创新的溢出效应研究[D]. 武汉大学硕士学位论文, 2014
[15] 邱士雷,王子龙,杨琬琨. 高技术产业创新能力的空间集聚效应分析[J]. 研究与发展管理, 2018,30(6):132-141
[16] 闫军印,侯孟阳,梁波. 我国矿产资源型产业技术创新溢出效应实证分析[J]. 中国矿业, 2016,25(12):5-11
[17] Koukouritakis M., Papadopoulos A. P., Yannopoulos A. Linkages between the Eurozone and the South-Eastern European Countries:A Global VAR Analysis[J]. Economic Modelling, 2015,48(8):129-154
[18] 周银香,吕徐莹. 中国碳排放的经济规模、结构及技术效应——基于33个国家GVAR模型的实证分析[J]. 国际贸易问题, 2017,(8):96-107
[19] Ong S. L, Sato K. Regional or Global Shock? A Global VAR Analysis of Asian Economic and Financial Integration[J]. The North American Journal of Economics and Finance, 2018,46(11):232-248
[20] Chen P., Semmler W. Financial Stress, Regime Switching and Spillover Effects:Evidence from a Multi-regime Global VAR Model[J]. Journal of Economic Dynamics & Control, 2018,91(6):318-348
[21] 张永安,鲁明明. 高技术制造业创新效率评价及要素投入差异性研究[J]. 科技进步与对策, 2019,36(16):51-57
[22] 王明亮,余芬. 我国电子及通信设备制造业创新效率实证分析[J]. 科技管理研究, 2018,38(7):85-92
[23] 洪嵩. 政府R&D资助企业R&D投入与高技术产业创新效率的关系研究[D]. 中国科学技术大学博士论文, 2015
[24] 叶丹,黄庆华. 区域创新环境对高技术产业创新效率的影响研究——基于DEA-Malmquist方法[J]. 宏观经济研究, 2017,(8):132-140
[25] 耿鹏,赵昕东. 基于GVAR模型的产业内生联系与外生冲击分析[J]. 数量经济技术经济研究, 2009,(12):32-45
[26] Pesaran M. H., Shin Y. Generalized Impulse Response Analysis in Linear Multivariate Models[J]. Economic Letters, 1998,58(1):17-29
[27] Pesaran M. H., Schuermann T. and Weiner S. M. Modeling Regional Interdependencies Using a Global Erro r-Correcting Macroeconometric Model. Joumal of Business & Economic Statistics, 2004,22(2):129-162