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Is decoupling embodied carbon emissions from economic output in Sino-US trade possible?

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Abstract Trade boosts economic growth, but it increases carbon emissions embodied in trade. To achieve economic growth through trade without increasing carbon emissions, it is essential to determine the driving… Click to show full abstract

Abstract Trade boosts economic growth, but it increases carbon emissions embodied in trade. To achieve economic growth through trade without increasing carbon emissions, it is essential to determine the driving factors of economic growth and carbon emissions embodied in trade. This study uses the multi-regional input–output (MRIO), Tapio decoupling model, and structural decomposition analysis (SDA) to investigate the decoupling of carbon emissions embodied in the Sino-US trade and their driving factors. The results show that, first, the decoupling of carbon emissions embodied in China's exports to the US is relatively invariable and gradually improving. By contrast, the decoupling of carbon emissions embodied in the US exports to China is variable. Second, the effect of the intermediate product structure on carbon emissions embodied in the US export to China is higher than that of China's export to the US. Third, 5 industries in China that export to the US were in a strong decoupling state from 2013 to 2014, whereas knowledge-intensive manufacturing and service industries in the US that exports to China were in the best decoupling state. Fourth, the driving factors of carbon emissions embodied in trade between China's export to the US and the US export to China is similar, although the degrees of these drivers are different. This study does not only focus on the decoupling of carbon emissions embodied in the Sino-US trade but also provides a research framework for the decoupling of carbon emissions embodied in global trade, especially trade between developing and developed countries.

Keywords: sino trade; decoupling carbon; carbon emissions; emissions embodied; trade

Journal Title: Technological Forecasting and Social Change
Year Published: 2021

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