China's provincial energy‐related carbon emissions‐economy nexus: A two‐stage framework based on decoupling analysis and panel vector autoregression

Abstract

China is transforming the growth model and speeding up industrial structural improvement and upgrading now and in the coming years, which means the slowdown of economic growth and more serious environmental costs in economic and social development would be the “New Normal.” As the world's largest energy consumer and carbon‐emitting country, China's emissions reduction commitments are crucial to global greenhouse gas emissions mitigation, so there is a profusion of research focused on China's economy‐environment nexus. Among which, the dynamic relationship of carbon emission and economic growth and its evolution combined the national, regional, provincial data have not been discussed thoroughly. This paper analyses the elasticity of economic performance of carbon emissions based on 30 Chinese provincial data from 2000 to 2016; furthermore, a panel vector autoregressive model is constructed to discuss the interactions of variables within environmental economic system. It is concluded that China is experiencing a turning point from weak decoupling to strong decoupling in recent years, and its economic performance of carbon emissions has been gradually improved with larger disparities among provinces though. Regression result confirms the role of the energy mix on carbon emissions, and it also indicates that the impact of most factors influencing that have been discussed in previous studies may not be direct, prominent, and for long term.

Decoupling analysis and peak prediction of carbon emission in less developed provinces: A case study of Sichuan province, China

“…However, as a municipality directly under the Central Government, Chongqing has a better policy background. The degree of decoupling in Chongqing is also in a relatively good state 56 . It is different from the development model in which developed cities gradually move closer to the service industry 52 .…”

“…The degree of decoupling in Chongqing is also in a relatively good state. 56 It is different from the development model in which developed cities gradually move closer to the service industry. 52 As an underdeveloped province, Sichuan province is in the initial stage of urban development.…”

Decoupling analysis and peak projection of manufacturing CO2 emissions from the perspective of investment

“…Moreover, there are also many existing studies about decoupling analysis on China's carbon emissions (see Table S2). A few studies focused on decoupling relationship between carbon emissions and economic growth in China (Jiang et al, 2018 ; Xu et al, 2021 ; Wu et al, 2019 ; Liang et al, 2019b ; Wu et al, 2018 ; Pan et al, 2019 ). Because some scholars (Xu et al, 2017 ; Liang et al, 2019a ; Jia et al, 2021 ; Chen et al, 2022 ) found that the impact of industry on the decoupling status of economic growth and carbon emissions was a decisive factor and Wang et al ( 2019 ) concluded only manufacturing sector presented the same trend with the entire industrial sector, manufacturing became the representative of the industrial study.…”

Green Financing as a Condition for Sustainable Economic Growth

“…The more distinctive features of the green economy are: a) low carbon and hydrocarbon emissions; b) preventing the degradation of ecological services and biodiversity; c) preservation and growth of natural capital; d) saving resources and energy efficiency; and e) increasing income and employment(Demirel et al., 2019; D'Orazio & Popoyan, 2019; Fatoki, 2019; Abid et al, 2019; Semin et al, 2019).Currently, various methods and indicators are used to assess sustainable development. For instance, the OECD calculates the decoupling coefficient, which reflects the relationship between economic growth and resource consumption or environmental pollution(Pan et al, 2019;Chien, 2020). In 1996, the UN Commission on Sustainable Development proposed the Sustainable Development Goals Index (SDG), which takes into account a significant number of indicators (over 240).…”