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The Impact of Factor Market Distortion on the Efficiency of Technological Innovation: A Spatial Analysis

Author

Listed:
  • Qian Lu

    (School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Chao Hua

    (School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Jianjun Miao

    (School of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

Abstract

The growth of scientific and technological innovation in China is facing a bottleneck under the influence of domestic and foreign environments. The economic internal circulation policy of China may explore new driving forces for innovation from the perspective of optimizing the efficiency of production factor allocation. This research applies the provincial data from 2001 to 2017 to empirically investigate the spatial effects of factor market distortions on the efficiency of technological innovation. The DEA (Data envelopment analysis) model with variable returns to scale is exploited to measure the efficiency of technological innovation. The production function approach can be harnessed to measure labor market distortions and capital market distortions. The spatial correlation test results and the spatial econometric results regressed with three spatial weight matrices draw the following conclusions: (1) No matter how the spatial connection is established, the efficiency of the scientific and technological innovation in China shows a strong positive spatial correlation. (2) Labor market distortion and capital market distortion lead to low factor allocation efficiency, which inhibits the improvement of scientific and technological innovation efficiency. (3) When considering inter-regional economic connections, the inhibitory effect of factor market distortions on the efficiency of technological innovation shows spillover effects on surrounding areas. (4) Human capital and advanced industrial structure are conducive to the improvement of scientific and technological innovation efficiency. Optimizing the efficiency of factor market allocation can become a significant path for China to release new room for improvement in scientific and technological innovation.

Suggested Citation

  • Qian Lu & Chao Hua & Jianjun Miao, 2022. "The Impact of Factor Market Distortion on the Efficiency of Technological Innovation: A Spatial Analysis," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12064-:d:923716
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    References listed on IDEAS

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    1. Acharya, Viral & Xu, Zhaoxia, 2017. "Financial dependence and innovation: The case of public versus private firms," Journal of Financial Economics, Elsevier, vol. 124(2), pages 223-243.
    2. Tom Broekel, 2015. "Do Cooperative Research and Development (R&D) Subsidies Stimulate Regional Innovation Efficiency? Evidence from Germany," Regional Studies, Taylor & Francis Journals, vol. 49(7), pages 1087-1110, July.
    3. Junhong Bai, 2013. "On Regional Innovation Efficiency: Evidence from Panel Data of China's Different Provinces," Regional Studies, Taylor & Francis Journals, vol. 47(5), pages 773-788, May.
    4. Blind, Knut & Petersen, Sören S. & Riillo, Cesare A.F., 2017. "The impact of standards and regulation on innovation in uncertain markets," Research Policy, Elsevier, vol. 46(1), pages 249-264.
    5. Mourad Dakhli & Dirk De Clercq, 2004. "Human capital, social capital, and innovation: a multi-country study," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 16(2), pages 107-128, March.
    6. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-1039, December.
    7. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    8. Xiafei Chen & Zhiying Liu & Chaoliang Ma, 2017. "Chinese innovation-driving factors: regional structure, innovation effect, and economic development—empirical research based on panel data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(1), pages 43-68, July.
    9. Bhagwati, Jagdish N & Ramaswami, V K & Srinivasan, T N, 1969. "Domestic Distortions, Tariffs, and the Theory of Optimum Subsidy: Some Further Results," Journal of Political Economy, University of Chicago Press, vol. 77(6), pages 1005-1010, Nov./Dec..
    10. Ljungwall, Christer & Tingvall, Patrik Gustavsson, 2015. "Is China different? A meta-analysis of the growth-enhancing effect from R&D spending in China," China Economic Review, Elsevier, vol. 36(C), pages 272-278.
    11. Chen, Jian & Wang, Lingjun & Li, Yuanyuan, 2020. "Natural resources, urbanization and regional innovation capabilities," Resources Policy, Elsevier, vol. 66(C).
    12. Guan, JianCheng & Yam, Richard C.M., 2015. "Effects of government financial incentives on firms’ innovation performance in China: Evidences from Beijing in the 1990s," Research Policy, Elsevier, vol. 44(1), pages 273-282.
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