Clean Technologies and Environmental Policy

, Volume 21, Issue 9, pp 1739–1749 | Cite as

Do the coupling effects of environmental regulation and R&D subsidies work in the development of green innovation? Empirical evidence from China

  • Sumin HuEmail author
  • Shulin Liu
Original Paper


Global environmental problems will require the development of new technologies. How will green technology-related public policy affect this process? By exploiting an economic assessing model of green technical innovation efficiency, this paper examines the impact of two different environmental policies (environmental regulation and government subsidy) and their interaction on green technical innovation. The analysis was conducted by collecting innovation-related data on 30 provinces in China over the period 2006–2016. It was found that there are dramatic regional differences in green innovation efficiency in China. The average efficiency in the eastern region is about 0.8, followed by the western region, the central region and the north-eastern region, with 0.4, 0.2 and 0.2, respectively. During the sample period, there was a statistically significant effect of the coupling of the two policy instruments on the innovative efficiency of green technology of China, which is − 0.01. Regulatory policies have a remarkable incentive influence on the performance of green innovation in the central region (0.5) but a restraining effect on the eastern region (− 0.9). R&D subsidies play an essential role in inducing green technology only in the central region (0.2). The paper concludes that both regulative policy and governmental subsidies have failed to achieve the goal of promoting green innovation development in China.

Graphic abstract

These two figures show the average regional efficiency of the two types of innovation with or without environment-related factors using innovation-related data on a panel of 30 provinces in China over the period 2006–2016.


Environmental regulation R&D subsidy Green innovative efficiency China’s provinces 



We would like to acknowledge support from Prof. Qian Yu and Dr. Haoqiang Wu for their comments on earlier drafts of this paper, as well as seminar participants at Wuhan University of Technology during the initial writing of this paper. And our special thanks to Mr. Rui Lin for his company and assisting in collecting panel data.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of EconomicsWuhan University of TechnologyWuhanChina

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