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Energy Economics
Article . 2022
License: taverne
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Energy Economics
Article . 2022 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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How would GVCs participation affect carbon intensity in the “Belt and Road Initiative” countries?

Authors: Shi, Qiaoling; Shan, Yuli; Zhong, Chao; Cao, Ye; Xue, Rui;

How would GVCs participation affect carbon intensity in the “Belt and Road Initiative” countries?

Abstract

Participating in global value chains (GVCs) brings great economic and ecological benefits in Belt and Road Initiative (BRI) countries. By combining the multi-region input-output analyses with regression models, this study examines the impact of GVCs participation on carbon intensity in BRI countries during 2005–2016. Results show that: most BRI countries are located in backward GVCs positions, and carbon intensity presents a decreasing trend. Heterogeneity analysis indicates that, forward (backward) GVCs participation mode is negatively (positively) associated with carbon intensity changes in BRI countries. Both forward and backward participation modes have greater impacts on BRI developing than that of developed countries. With the deepening of forward linkages, BRI developing countries could reduce greater carbon intensity than all global developing countries.Further analysis shows that technological innovation and industrial upgrading effects of forward mode play greater impacts on decreasing carbon intensity than that of backward mode. Taken together, BRI countries can strengthen cooperation in climate governance and promote synergy to reduce carbon intensity. In addition, it is necessary to seek a breakthrough in GVCs position to realize the function of environmental governance. Advancing technological innovation and upgrading industrial structure are also effective ways to reduce carbon intensity.

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Keywords

Carbon intensity, Impact mechanism, Forward and backward participation mode, Global value chains, The Belt and Road Initiative countries

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Top 10%
Top 1%
hybrid