Literature DB >> 34762254

How does anti-corruption affect enterprise green innovation in China's energy-intensive industries?

Xiude Chen1,2, Guocai Chen1, Miaoxin Lin1, Kai Tang3, Bin Ye4.   

Abstract

Rampant corruption exists in China's energy-intensive industries. However, we know little about the nexus of corruption and enterprise green innovation in China's energy-intensive industries. This paper discusses the impact of anti-corruption on enterprises' green innovation and its effect margin. Analyzing the panel data of Chinese listed enterprises in energy-intensive industries from 2009 to 2017, we find that anti-corruption played a positive role in stimulating enterprises' green innovation investments in energy-intensive industries. Then we adopt the instrumental variable approach and difference-in-differences model to alleviate the endogeneity problem. Moreover, we find that research and development investments from state-owned, high-tech enterprises and enterprises in the regions with more government intervention or weaker intellectual property protection were more prominent after the anti-corruption campaign. Finally, political connection played an intermediary role in this process, in which only the government-official political connection worked. Our results highlight the roles of enterprises' attributes and environmental characteristics as important factors in the relationship between anti-corruption and green innovation investments. Policymakers should enhance the control of corruption to boost green innovation in energy-intensive industries.
© 2021. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  Anti-corruption; China; Energy-intensive industries; Green innovation investments

Mesh:

Year:  2021        PMID: 34762254     DOI: 10.1007/s10653-021-01125-4

Source DB:  PubMed          Journal:  Environ Geochem Health        ISSN: 0269-4042            Impact factor:   4.898


  1 in total

1.  The Impact of Financial Deepening on Carbon Reductions in China: Evidence from City- and Enterprise-Level Data.

Authors:  Kai Tang; Qianbo Chen; Weijie Tan; Yi Jun Wu Feng
Journal:  Int J Environ Res Public Health       Date:  2022-09-09       Impact factor: 4.614

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.