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Research on the Impact of Government R&D Funding on Regional Innovation Quality: Analysis of Spatial Durbin Model Based on 283 Cities in China

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  • Jing Li
  • Xinlu Wu
  • Baogui Xin

Abstract

Based on the perspective of the regional innovation system, this study constructs an analytical framework for the influence of government R&D funding on regional innovation quality and uses 283 Chinese cities as research samples to empirically test the influence of government R&D funding methods such as subsidies and tax preferences on regional innovation quality by the spatial Durbin model. According to the study, China’s regional innovation quality has a positive spatial correlation. Subsidies can improve regional innovation quality, which is mainly realized by increasing the input of innovation resources from local direct innovation subjects, attracting the inflow of innovation resources from neighboring areas, and increasing the innovation support from local indirect innovation subjects. Besides, spatial competition for subsidies makes it beneficial to improve the regional innovation quality in neighboring regions, while the promotion effect of tax preferences is not significant. When considering the heterogeneity of the city location and administrative hierarchy, it shows that the government R&D funding cannot improve the innovation quality of the Eastern cities and higher-administrative-hierarchy cities, while it can improve that of the Middle and Western cities and general-administrative-hierarchy cities. Furthermore, government R&D funding widens the gap of regional innovation quality, which may be related to the existing “insufficient intervention†and “excessive intervention†of government R&D funding. This study provides insights into the implementation of R&D funding by the government to promote the development of regional innovation quality.

Suggested Citation

  • Jing Li & Xinlu Wu & Baogui Xin, 2021. "Research on the Impact of Government R&D Funding on Regional Innovation Quality: Analysis of Spatial Durbin Model Based on 283 Cities in China," Complexity, Hindawi, vol. 2021, pages 1-20, July.
    • Handle: RePEc:hin:complx:2217588
    DOI: 10.1155/2021/2217588
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    Cited by:

    1. Yabin Yu & Qian Xu, 2022. "Influencing Factors of Enterprise R&D Investment: Post-Subsidy, Sustainability, and Heterogeneity," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    2. Li, Beili & Fan, Xu & Li, Jianjiang, 2024. "Natural resource dependence and government-guided social forces participation in R&D investment: An analysis of the resource curse hypothesis," Resources Policy, Elsevier, vol. 89(C).
    3. Pu, Xiaohong & Zeng, Ming & Zhang, Weike, 2023. "Corporate sustainable development driven by high-quality innovation: Does fiscal decentralization really matter?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 273-289.
    4. Guoyuan Han & Zhilin Zhang, 2022. "Regional innovation paths selection in complex environments of China: A configurational perspective," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2598-2606, September.

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