Dynamics between global value chain participation, CO2 emissions, and economic growth: Evidence from a panel vector autoregression model

Jing Wang, Dan Rickman and Yihua Yu ()

Energy Economics, 2022, vol. 109, issue C

Abstract: Resolving the conflict between economic growth and CO2 reduction is critical for sustainable growth. Increasing integration into global value chains (GVCs) is an inevitable trend for countries to develop their international markets. However, the dynamic relationships between GVC participation, CO2emissions, and economic growth have not been fully clarified. This study analyzes these relationships and the underlying mechanisms using a panel vector autoregressive model approach with data for 63 countries and regions from 2005 to 2015. The major findings are: (1) GVC participation promotes environmentally-friendly growth in the long run by increasing per capita gross domestic product (GDP) and reducing per capita CO2 emissions. (2) GVC participation increases as per capita CO2 emissions increase; it decreases as per capita GDP grows. (3) These relationships vary by industry and income. The variation of GVC participation in high-CO2 emission industries explains a large proportion of the variation in per capita CO2emissions, and in high value-added industries, GVC variation explains a large proportion of the variation in per capita GDP. Further, high-income countries benefit more from GVC participation compared to low-income countries. An important policy recommendation is that countries should actively participate in GVCs to promote sustainable growth.

Keywords: global value chain participation; CO2 emission; economic growth; panel vector autoregressive model; sustainable growth; global warming (search for similar items in EconPapers)
JEL-codes: F23 G14 O40 O44 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:109:y:2022:i:c:s0140988322001414

DOI: 10.1016/j.eneco.2022.105965

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