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      Environmental Kuznets Curve Hypothesis on CO2 Emissions: Evidence for China

      Journal of Risk and Financial Management
      MDPI AG

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          Abstract

          China is the largest CO2 emitter in the world, and it shared 28% of the global CO2 emissions in 2017. According to the Paris Agreement, it is estimated that China’s CO2 emissions will reach its peak by 2030. However, whether or not the CO2 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 CO2 reduction policy. The aim of this paper is to conduct an empirical analysis on the long-standing relationship between CO2 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 CO2 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 CO2 emissions, in the long run, are also estimated. Quantitatively, if energy consumption rises by 1%, then CO2 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.

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          Regression Quantiles

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            Bounds testing approaches to the analysis of level relationships

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              Economic Growth and the Environment

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                Author and article information

                Journal
                Journal of Risk and Financial Management
                JRFM
                MDPI AG
                1911-8074
                March 2021
                February 26 2021
                : 14
                : 3
                : 93
                Article
                10.3390/jrfm14030093
                8f32a547-cae6-4348-b65c-13c32d305938
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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