single-jc.php

JACIII Vol.22 No.4 pp. 437-447
doi: 10.20965/jaciii.2018.p0437
(2018)

Paper:

Research on Innovation Knowledge Spillover Effect of China’s High-Tech Industry R&D-Base on Multidimensional Spatial Weight Matrices

Xiuwu Zhang* and Chengkun Liu**,†

*School of Statistics, Huaqiao University
No.668 Jimei Avenue, Jimei District, Xiamen 361021, China

**School of Economics and Finance, Huaqiao University
No.269, Chenghua North Road, Fengze District, Quanzhou 362021, China

Corresponding author

Received:
May 22, 2017
Accepted:
December 24, 2017
Published:
July 20, 2018
Keywords:
high-tech industry, spillover effect, spatial econometric model
Abstract

Based on the panel data of R&D activities of the provincial high-tech industry in China from 1998 to 2014, this paper adopts the spatial weight matrix of different dimensions including geographical distance, technical distance, economic distance, proximity distance, and human capital distance, to construct a spatial econometric model to analyze the knowledge spillover effects of R&D activities through both local and transnational routes. The results show that in the case of spatial auto-correlation of the dependent variables, the results of the spatial panel model are more accurate and reliable than those obtained by the conventional panel model. The spatial coefficients of the spatial econometric model based on five different spatial weight matrices are all very significant, and there is a clear spatial correlation between the R&D activities of high-tech industries in different regions. Labor input and exports have a positive impact on innovation output, but the introduction of technology will hinder independent innovation in China’s high-tech industry, and the impact of capital investment to innovation output is uncertain, as it closely relates to the set of models. In addition, the space knowledge spillover effect through the local approach is larger than that produced by the transnational route.

Cite this article as:
X. Zhang and C. Liu, “Research on Innovation Knowledge Spillover Effect of China’s High-Tech Industry R&D-Base on Multidimensional Spatial Weight Matrices,” J. Adv. Comput. Intell. Intell. Inform., Vol.22, No.4, pp. 437-447, 2018.
Data files:
References
  1. [1] D. T. Coe and E. Helpman, “International R&D spillovers,” Europe Economic Review, Vol.39, No.5, pp. 859-887,1995.
  2. [2] D. T. Coe, E. Helpman, and A. W. Hoffmaister, “International R&D spillovers and institutions,” European Economic Review, Vol.53, No.7, pp. 723-741,2009.
  3. [3] M. Ali, U. Cantner, and I. Roy, “Knowledge spillovers through FDI and trade : the moderating role of quality-adjusted human capital,” J. Evol. Econ., Vol.26, No.4, pp. 837-868, 2016.
  4. [4] M. Lin and Y. K. Kwan, “FDI technology spillovers, geography, and spatial diffusion,” Int. Review of Economics and Finance, Vol.43, pp. 257-274, 2016.
  5. [5] Q. Wang, “Multidimensional Proximity and Regional Knowledge Spillover of High-tech Industry in China-A Spatial Panel Data Analysis,” Science Research, Vol.31, No.7, pp. 1068-1076, 2013.
  6. [6] X. Wei and H. Wang, “Research on Productivity and Spillover Effect of High-tech Industry in China-Empirical Analysis Based on Provincial Panel Data,” Technical Economics and Management Research, Vol.4, pp. 116-121, 2017.
  7. [7] J. Li and Y. He, “Impact of Knowledge Spillover on Regional Innovation Performance Based on Spatial Correlation Perspectives – A Case Study of Provincial Panel Data,” Research and Development Management, Vol.29, No.1, pp. 42-54, 2017.
  8. [8] Y. Jeon, B. I. Park, and P. N. Ghauri, “Foreign direct investment spillover effects in China: Are they different across industries with different technological levels?,” China Economic Review, Vol.26, pp. 105-117, 2013.
  9. [9] Q. Liu and L. D. Qiu, “Intermediate input imports and innovations: Evidence from Chinese firms’patent filings,” J. of Int. Economics, Vol.103, pp. 166-183, 2016.
  10. [10] G. Ren and F. Meng, “Comparative Study on R&D Spillover between High-tech Industry and Traditional Industry – From the Perspective of Economic Weight Distance,” Soft Science, Vol.29, No.1, pp. 29-32, 2015.
  11. [11] J. Chen, L. Meng, and Q. Wang, “Absorptive Capacity, Threshold Effect of FDI Technology Spillover and Domestic Productivity Growth-Empirical Analysis Based on China’s High-tech Industry,” Industrial Technology Economy, Vol.10, pp. 121-128, 2015.
  12. [12] Y. Zhang and F. Zhao, “Research on the Impact of International Technology Spillovers and Absorptive Capacity on Independent Innovation in High-tech Industries,” Financial Research, Vol.43, No.3, pp. 94-106, 2017.
  13. [13] Z. Griliches, “Issues in Assessing the Contribution of Research and Development to Productivity Growth,” Bell J. of Economics, Vol.10, pp. 92-116, 1979.
  14. [14] A. B. Jaffe, “Technology Opportunity and Spillovers of R&D: Evidence from Firm’s Patents,Profits, and Market Value,” The American Economic Review, Vol.76, No.5, pp. 984-1001, 1986.
  15. [15] L. Anselin, “Spatial Econometrics: Methods and Models,” Kluwer Academic Publishers, 1988.
  16. [16] G. Yang and M. Yang, “Spatial Correlation Effect of Total Factor Productivity in China: An Empirical Study-Based on Static and Dynamic Spatial Panel Model,” J. of Economic Geography, Vol.33, No.11, pp. 122-129, 2013.
  17. [17] U. Kaiser, “Measuring Knowledge Spillovers in Manufacturing and Services: An Empirical Assessment of Alternative Approaches,” J. of Research Policy, Vol.31, pp. 125-144, 2002.
  18. [18] L. Anselin, A. Varga, and Z. Acs, “Local Geographic Spillovers Between University Research and High Technology Innovation,” J. of Urban Economics, Vol.42, pp. 422-448, 1995.
  19. [19] G. Xiang, P. Zhu, and Z. Zhang, “A Study on the Spillover Effects of R&D in China’s High-tech Industry-From the Perspective of Two Dimensions of Local and Transnational,” J. of Shanghai Economic Research, Vol.9, pp. 19-29, 2012.
  20. [20] J. Li, Q. Tan, and J. Bai, “Spatial Metrological Analysis of Regional Innovation Production in China -An Empirical Study Based on Static and Dynamic Spatial Panel Model,” J. of the World Manage, Vol.7, pp. 43-55, 2010.
  21. [21] M. Deng and Z. Qian, “China’s inter-provincial Knowledge Stock, Knowledge Production and Knowledge of Space Spillovers,” J. of of Quantitative Economic and Technical Economic Research, Vol.5, pp. 42-53, 2009.
  22. [22] Y. Wu, “Research on the Application of Spatial Econometric Model in Provincial R&D and Innovation,” J. of of Quantitative Economic and Technical Economic Research, Vol.5, pp. 74-85, 2006.
  23. [23] I. Cockburn and Z. Griliches, “Industry Effects and Appropriability Measures in the Stock Market’s Valuation of R&D and Patents,” The American Economic Review, Vol.5, pp. 419-423, 1988.
  24. [24] K. Chen and J. Guan, “A Study on the Crux and Countermeasure of ‘High Output and Low Efficiency’ of China’s High-tech Industry-Based on the Exploration of Technological Innovation Efficiency,” J. of Manage Comments, Vol.24, No.4, pp. 53-66, 2012.
  25. [25] B. H. Baltagi, S. H. Song, and W. Koh, “Testing Panel Data Regression Models with Spatial Error Correlation,” J. of Econometrics, Vol.117, No.1, pp. 123-150, 2003.
  26. [26] M. Kapoor, H. H. Kelejian, and I. R. Prucha, “Panel Data Model with Spatially Correlated Error Compents,” J. of Econometrics, Vol.140, No.1, pp. 97-130, 2007.
  27. [27] L. Yao and G. Gu, “Regional Technological Innovation, Spatial Overflow and Regional High-tech Industry,” China Science and Technology Forum, Vol.1, pp. 91-95, 2015.
  28. [28] C. Zhou, “Knowledge Spillover and China’s High-tech Industry Innovation,” Economic Latitude and Longitude, Vol.33, No.3, pp. 78-83, 2016.
  29. [29] H. Zhao and S. Wang, “Analysis on the Knowledge Spillover Effect of High Technology Industry in China,” Technology and Management, Vol.19, No.3, pp. 36-40, 2017.
  30. [30] Z. Li, R. Chi, and C. Millman, “Impact of Technology Import and Export Trade on Independent of R&D: An Empirical Study of Zhejiang High-tech Industry,” Science Research, Vol.28, No.10, pp. 1495-1501, 2010.
  31. [31] B. Han et al., “Multidimensional Proximity and Regional Knowledge Spillover: Empirical Analysis Based on Chinese High-tech Industry Panel Data from 2000 to 2014,” Industrial Economic Forum, Vol.3, No.5, pp. 510-523, 2016.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on Oct. 17, 2018