Back to Search
Start Over
Carbon intensity reduction assessment of renewable energy technology innovation in China: A panel data model with cross-section dependence and slope heterogeneity.
- Source :
-
Renewable & Sustainable Energy Reviews . Jan2021, Vol. 135, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- Climate change and global warming have become severe environmental issues of global concern, and many countries have promulgated renewable energy development planning to achieve the targets of carbon emission reduction and sustainable development. Accelerating the development of renewable energy technology innovation is one of the major measures to stimulate the utilization of renewable resources. This paper analyzes the impact of renewable energy technology innovation on carbon intensity in 30 Chinese provinces from 2000 to 2015. Using the recent panel estimation methods that take cross-section dependence and slope heterogeneity into account, the results show that for every 1% increase in the innovation level of renewable energy technology, carbon intensity was significantly reduced by 0.051%. Specifically, renewable energy technology innovation does not affect carbon intensity in the short term. But in the long term, the influences are negative and significant. Moreover, the environmental benefits are most evident in eastern China, while there is no significant influence on the western regions. Finally, this paper provides some policy implications to further discuss the impetus of renewable energy technology innovation. • Renewable energy technology innovation can significantly reduce carbon intensity. • The influences of renewable energy technology innovation will change over time. • There exist differences in the innovation effects in different Chinese regions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13640321
- Volume :
- 135
- Database :
- Academic Search Index
- Journal :
- Renewable & Sustainable Energy Reviews
- Publication Type :
- Academic Journal
- Accession number :
- 147020014
- Full Text :
- https://doi.org/10.1016/j.rser.2020.110157