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The impact of government subsidies on green innovation performance in new energy enterprises: A digital transformation perspective

Author

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  • Duan, Yu
  • Xi, Bin
  • Xu, Xin
  • Xuan, Siyuan

Abstract

This paper selects data from A-share listed companies in China's new energy industry from 2007 to 2021 and constructs a fixed-effects negative binomial regression model to examine the impact of government subsidies on corporate green innovation performance and its mechanism. It further investigates the moderating effects of digital transformation and environmental regulation. The research finds that government subsidies significantly enhance corporate green innovation performance, and this conclusion remains valid after a series of robustness tests. Both corporate digital transformation and environmental regulation amplify the positive effect of government subsidies on green innovation performance. Meanwhile, the impact of government subsidies on green innovation performance varies with the nature of corporate ownership, industry characteristics, and company size. In non-state-owned, high-tech, and non-heavy pollution enterprises, the enhancing effect of government subsidies on green innovation performance is more pronounced. Mechanism tests show that government subsidies improve corporate innovation performance by enhancing technological integration capability, easing financing constraints, and increasing innovation input capacity. This paper provides new evidence on the factors influencing green innovation performance in new energy enterprises, offering significant insights into how government subsidies enhance green innovation performance in the new energy sector.

Suggested Citation

  • Duan, Yu & Xi, Bin & Xu, Xin & Xuan, Siyuan, 2024. "The impact of government subsidies on green innovation performance in new energy enterprises: A digital transformation perspective," International Review of Economics & Finance, Elsevier, vol. 94(C).
  • Handle: RePEc:eee:reveco:v:94:y:2024:i:c:s1059056024004064
    DOI: 10.1016/j.iref.2024.103414
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