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Emission reduction target, complexity and industrial performance.
- Source :
-
Journal of Environmental Management . Apr2020, Vol. 260, pN.PAG-N.PAG. 1p. - Publication Year :
- 2020
-
Abstract
- To tackle climate change, Chinese government has applied an array of mitigating measures to reduce CO2 emissions. During the 11th Five-year Plan, Chinese government set the emission reduction target policy to reduce energy consumption per unit of gross domestic product (GDP) by 20%. This paper attempts to estimate the effect of this emission reduction target policy on industrial performance from complexity perspective. The result shows more complex industrial structure is related to less coal consumption. In general, emission reduction target policy has a negative effect on the probability of branching into new industries and lower the productivity and profitability of a given industry. However, this negative effect is weaker for more complex industries. Only for industries with very high complexity, emission reduction target policy can improve the performance of an industry rather than exerting a negative effect. Our finding not only helps to design a more effective policy to achieve industrial development strategy, but also provides a potential way to achieve economic growth while reduce the emission of greenhouse gases at the same time. • We investigate the impact of Emission reduction target policy(ERT) on industrial performance from complexity perspective. • We apply the method of reflection to calculate the Economic Complexity of provinces and Industry Complexity of industries. • More complex industrial structure contributes to the coal consumption reduction. • ERT has negative effects on the probability of branching into new industries, lowers the productivity and profitability of a given industry. • ERT has weaker negative effects for more complex industries. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03014797
- Volume :
- 260
- Database :
- Academic Search Index
- Journal :
- Journal of Environmental Management
- Publication Type :
- Academic Journal
- Accession number :
- 141829346
- Full Text :
- https://doi.org/10.1016/j.jenvman.2020.110148