The Intra-EU Value Chain: An Approach to Its Economic Dimension and Environmental Impact

Abstract

This paper aims to analyze the economic dimension and environmental impact of intra-EU value-added generation linked to global value chains (GVCs) through input-output analysis. For this purpose, information has been collected from TiVA (Trade in Value Added, OECD) and Eora databases for the years 2005 and 2015. From an economic perspective, the results point to a strengthening of the value-added generated within Factory Europe. From an environmental perspective, all EU28 members have reduced their exports-related impacts in intensity-emissions terms, but not all of them in the same degree. An approach to the environmental Kuznets curve (EKC) has also been carried out through a panel data model. The results show a positive impact of the participation in intra-EU value chain (Factory Europe) on CO2 emissions per capita. Further, an inverted U-shaped curve for CO2 emissions is found for the period 2005–15. In this sense, European economies with lower development levels (many Eastern and Southern countries) seem to be still on the rising segment of the curve, while the more developed ones seem to be on the decreasing segment. These results highlight the need to design global monitoring and prevention mechanisms to tackle growing environmental challenges and the need to incorporate specific actions associated with the GVCs activity.

Africa Countries’ Energy Efficiency: Evidence from a Directional Distance Function Approach

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Trade and Embodied CO2 Emissions: Analysis from a Global Input–Output Perspective

“…Carbon dioxide emissions from China–Brazil trade had maintained a steady growth, and China was a net carbon dioxide emitter [ 11 ]. European economies with lower development levels (many Eastern and Southern countries) seemed to be still on the rising trend of carbon emission, while the more developed ones seemed to be on the decreasing trend of carbon emission between 2005 and 2015 [ 12 ]. Chinese scholars constructed a spatial correlation network of net carbon transfer in global trade including 185 countries (regions) in 2000 and 2015 and used multi-dimensional network measurement indicators to comprehensively examine the characteristics of change of the global trade embodied carbon emission network and the role and functional characteristics of the network sectors [ 13 , 14 ].…”