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Impact of government-guided funds on firms’ new quality productivity

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  • Li, Yinxia
  • Wang, Yu
  • Zhang, Ying

Abstract

New quality productivity is a core driver of China’s high-quality development and economic transformation, and its formation mechanisms and policy support pathways have attracted increasing scholarly and policy attention. Using a sample of A-share listed firms from 2009 to 2024, this study examines the impact of government-guided funds on firms’ new quality productivity. The results reveal that government-guided funds significantly enhance new quality productivity, with the effect strengthening over time and remaining robust across multiple tests. The mechanism operates through alleviating financing constraints and improving corporate governance. Heterogeneity analysis shows that the effect is more pronounced for high-tech firms and in regions with lower market and financial development, reflecting the policy orientation of “targeted empowerment and filling market gaps.” The findings provide theoretical foundations and policy implications for optimizing government-guided funds’ effectiveness and advancing technological innovation and high-quality development.

Suggested Citation

  • Li, Yinxia & Wang, Yu & Zhang, Ying, 2026. "Impact of government-guided funds on firms’ new quality productivity," Finance Research Letters, Elsevier, vol. 89(C).
  • Handle: RePEc:eee:finlet:v:89:y:2026:i:c:s1544612325025966
    DOI: 10.1016/j.frl.2025.109347
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    1. Hall, Bronwyn H. & Mairesse, Jacques & Mohnen, Pierre, 2010. "Measuring the Returns to R&D," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 1033-1082, Elsevier.
    2. Shao, Yanmin & Chen, Zhongfei, 2022. "Can government subsidies promote the green technology innovation transformation? Evidence from Chinese listed companies," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 716-727.
    3. Myers, Stewart C. & Majluf, Nicholas S., 1984. "Corporate financing and investment decisions when firms have information that investors do not have," Journal of Financial Economics, Elsevier, vol. 13(2), pages 187-221, June.
    4. Liang, Lin & Li, Yan, 2023. "How does government support promote digital economy development in China? The mediating role of regional innovation ecosystem resilience," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    5. Maty Konte & Godsway Korku Tetteh, 2023. "Mobile money, traditional financial services and firm productivity in Africa," Small Business Economics, Springer, vol. 60(2), pages 745-769, February.
    6. Li, Guangyu & Zhang, Jun & Wang, Yiming & Zhao, Zijian, 2024. "Can government-guided funds promote corporate technology innovation? Evidence from the new energy automobile industry," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    7. Hainmueller, Jens, 2012. "Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies," Political Analysis, Cambridge University Press, vol. 20(1), pages 25-46, January.
    8. Song, Yan & Xiu, Yifan & Zhao, Mengyang & Tian, Ye & Wang, Jingyuan, 2024. "Intellectual property protection and enterprise innovation: Evidence from China," Finance Research Letters, Elsevier, vol. 62(PB).
    9. Sun, Zhaoyang & Rao, Meng & Yao, Baoshuai & Ci, Huifang & Li, Zongrun & Feng, Chao, 2025. "Driving enterprise new quality productivity: The role of big data tax collection," International Review of Financial Analysis, Elsevier, vol. 103(C).
    10. Nicholas Bloom & John Van Reenen, 2007. "Measuring and Explaining Management Practices Across Firms and Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1351-1408.
    11. Sun, Wenqi & Zhao, Yuanjun & Sun, Lu, 2020. "Big Data Analytics for Venture Capital Application:Towards Innovation Performance Improvement," International Journal of Information Management, Elsevier, vol. 50(C), pages 557-565.
    12. Chen, Baodong & Pan, Qiao & Wu, Shuai, 2024. "Can government guided funds alleviate corporate financing constraints? Evidence from China," Finance Research Letters, Elsevier, vol. 66(C).
    13. Hao, Panpan & Wang, Yuchen & Fan, Liyan, 2025. "Government-guided fund, social resources, and corporate green innovation," International Review of Financial Analysis, Elsevier, vol. 98(C).
    14. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    15. Stiglitz, Joseph E, 1989. "Markets, Market Failures, and Development," American Economic Review, American Economic Association, vol. 79(2), pages 197-203, May.
    16. Du, Juntao & Shen, Zhiyang & Song, Malin & Zhang, Linda, 2023. "Nexus between digital transformation and energy technology innovation: An empirical test of A-share listed enterprises," Energy Economics, Elsevier, vol. 120(C).
    17. Pan, Wenrong & Xie, Tao & Wang, Zhuwang & Ma, Lisha, 2022. "Digital economy: An innovation driver for total factor productivity," Journal of Business Research, Elsevier, vol. 139(C), pages 303-311.
    18. Liu, Yi & He, Zhengchu, 2024. "Synergistic industrial agglomeration, new quality productive forces and high-quality development of the manufacturing industry," International Review of Economics & Finance, Elsevier, vol. 94(C).
    19. Nikolov, Boris & Schmid, Lukas & Steri, Roberto, 2021. "The Sources of Financing Constraints," Journal of Financial Economics, Elsevier, vol. 139(2), pages 478-501.
    20. Zhuo, Chengfeng & Chen, Jin, 2023. "Can digital transformation overcome the enterprise innovation dilemma: Effect, mechanism and effective boundary," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    21. Zhong, Meirui & Lu, Qiaolin & He, Ruifang, 2022. "The heterogeneous effects of industrial policy on technological innovation: Evidence from China's new metal material industry and micro-data," Resources Policy, Elsevier, vol. 79(C).
    22. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    23. Liu, Xiangjun & Liu, Ding, 2025. "How green finance drives new-quality productivity from the perspective of Chinese modernization," Finance Research Letters, Elsevier, vol. 82(C).
    24. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
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