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Environmental Kuznets Curve Hypothesis on CO2 Emissions: Evidence for China.
- Source :
- Journal of Risk & Financial Management; Mar2021, Vol. 14 Issue 3, p1-16, 16p
- Publication Year :
- 2021
-
Abstract
- China is the largest CO<subscript>2</subscript> emitter in the world, and it shared 28% of the global CO<subscript>2</subscript> emissions in 2017. According to the Paris Agreement, it is estimated that China's CO<subscript>2</subscript> emissions will reach its peak by 2030. However, whether or not the CO<subscript>2</subscript> emissions in China will rise again from its peak is still unknown. If the emission level continues to increase, the Chinese policymakers might have to introduce a severe CO<subscript>2</subscript> reduction policy. The aim of this paper is to conduct an empirical analysis on the long-standing relationship between CO<subscript>2</subscript> emissions and income while controlling energy consumption, trade openness, and urbanization. The autoregressive distributed lag (ARDL) model and the bounds test were adopted in evaluating the validity of the Environmental Kuznets Curve (EKC) hypothesis. The quantile regression was also used as an inference approach. The study reveals two major findings: first, instead of the conventional U-shaped EKC hypothesis, there is the N-shaped relationship between CO<subscript>2</subscript> emissions and real gross domestic product (GDP) per capita in the long run. Second, a positive effect of energy consumption and a negative effect of urbanization on CO<subscript>2</subscript> emissions, in the long run, are also estimated. Quantitatively, if energy consumption rises by 1%, then CO<subscript>2</subscript> emissions will increase by 0.9% in the long run. Therefore, the findings suggest that a breakthrough, in terms of policymaking and energy innovation under China's specific socioeconomic and political circumstances, are required for future decades. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19118066
- Volume :
- 14
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Journal of Risk & Financial Management
- Publication Type :
- Academic Journal
- Accession number :
- 149538642
- Full Text :
- https://doi.org/10.3390/jrfm14030093