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Dynamic Impact of Technology and Finance on Green Technology Innovation Efficiency: Empirical Evidence from China’s Provinces

Author

Listed:
  • Yang Liu

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Yanlin Yang

    (Center for Economic Development Research and Center of Population, Resource & Environmental Economics Research, Wuhan University, Wuhan 430072, China)

  • Shuang Zheng

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Lei Xiao

    (Economics and Management School, Wuhan University, Wuhan 430072, China)

  • Hongjie Gao

    (School of Computer Science, Zhuhai College of Science and Technology, Zhuhai 519040, China)

  • Hechen Lu

    (School of Management, University of Science and Technology of China, Hefei 230026, China)

Abstract

In the new stage of global economic development, we hope to achieve both economic development and environmental improvement through green technology innovation. How to effectively obtain the support of technology and finance to green technology innovation is an issue worth studying. This paper constructed an improved super-SBM-DEA efficiency measurement model and combined it with the window analysis method to measure the green technology innovation efficiency (GTIE) of Chinese provinces from 2006 to 2018. Then, based on the PVAR model, the impulse response function and Monte Carlo simulation were used to study the dynamic impact of various variables of technology and finance on GTIE. Finally, the variance decomposition was used to explore the contribution degree of each variable of technology and finance to improving GTIE. The results revealed the following: (1) the average value of China’s provincial GTIE from 2006 to 2018 was 0.42, which is relatively low and shows a trend of volatility and rising. (2) From the impulse response results, it could be seen that various variables of technology and finance have always had a positive impact on GTIE. However, there are differences in the influence degree, shock effect, and dynamic transmission mechanism. (3) The results of the variance decomposition showed that government financial technology investment had the highest contribution to the improvement of GTIE, followed by bank technology credit, then by enterprise independent R&D investment, and finally venture capital. This paper offered a reference to developing countries with regard to improving their GTIE and studying the role of technology and finance.

Suggested Citation

  • Yang Liu & Yanlin Yang & Shuang Zheng & Lei Xiao & Hongjie Gao & Hechen Lu, 2022. "Dynamic Impact of Technology and Finance on Green Technology Innovation Efficiency: Empirical Evidence from China’s Provinces," IJERPH, MDPI, vol. 19(8), pages 1-17, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4764-:d:793981
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    Cited by:

    1. Chen Qian & Caiyao Xu & Fanbin Kong, 2022. "Spatio-Temporal Pattern of Green Agricultural Science and Technology Progress: A Case Study in Yangtze River Delta of China," IJERPH, MDPI, vol. 19(14), pages 1-13, July.
    2. Fei Wang & Zhi Dong & Jichang Dong, 2023. "Assessment of the Drivers and Effects of International Science and Technology Cooperation in Xinjiang in the Context of the Belt and Road Initiative," Sustainability, MDPI, vol. 15(2), pages 1-20, January.

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