Environmental asymmetries in global value chains: The case of the European automotive sector
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Elsevier
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The European automotive sector is deeply integrated in the EU regional value chain. Each EU member show differences their economic and environmental performance. While central European countries perform more advanced, higher-value and lower-emission tasks, eastern economies specialize in manufacturing and have a higher share of exports from an environmental perspective. However, the environmental effects resulting from automotive production, as well as the distinctions among European economies based on their development levels, remain unexplored. Similarly, the implications of participation in global value chains (GVCs) in this context have not been examined. Therefore, the aim of this paper is to analyze the Environmental Kuznets Curve and the Pollution Haven/Halo Hypothesis in the case of the EU28 automotive sector under a value-added approach. The multi-regional input-output methodology along with a panel data estimation was used to verify the hypotheses. The results verify an inverted-N shape curve for the Kuznets hypothesis. Nevertheless, the results show no evidence of compliance with the haven or halo hypotheses. Moreover, participation in GVCs implies higher environmental impacts. Based on these findings, some policy recommendations are proposed to enhance the sector's circularity and optimize material use throughout the production chain
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Journal of Cleaner Production, Volume 449, 2024, 141606
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https://doi.org/10.1016/j.jclepro.2024.141606Sponsors
This research has been supported by the ICEDE research group, to which the authors belong, Galician Competitive Research Group ED431C 2022/15 financed by Xunta de Galicia and project “REVALEC” REFERENCE PID2022 141162NB-I00 Financed by MCIN/AEI/ 10.13039/501100011033/EFRD, EU
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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by nc-nd/4.0/)
© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by nc-nd/4.0/)








