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An Analysis of Copper Consumption in China Using a Multivariate Approach Grounded in Life Cycle Assessment
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DOI：10.1007/s13132-026-03405-9.png)
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Abstract
En 中文
This paper investigates how knowledge spillovers, innovation in extraction and processing technologies impact copper demand and long-term supply security in China from 2000 to 2022 using a multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) framework. Copper is a critical mineral for the energy transition, especially in knowledge-intensive sectors driven by technological change such as renewable energy deployment, electrification, and low-carbon infrastructure. The analysis includes GDP per capita, mineral rents, carbon dioxide emissions, renewable energy consumption and electricity output, regulatory quality, trade, and renewable energy capacity to capture the dynamic co-movement of these variables. The results reveal strong time-varying correlations, revealing that copper consumption is significantly determined by economic growth by 0.03%, an increase in electricity output by 1% increases copper consumption by 62%. Conversely, a rise in trade increases copper consumption by 3.34%. The enhancement of regulatory quality leads to a 49% increase in copper consumption. Structural break tests identify major shifts in 2008 and 2013, reflecting macroeconomic disruptions. Based on the estimated relationships, China’s copper consumption is projected to reach approximately 17.4 million tons by 2030, representing a 27.4% increase. Overall, the findings highlight copper’s central role in China’s energy transition and the growing importance of innovation-driven demand dynamics.
Keywords:
Copper consumption forecasting
Energy transition
Structural breaks
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