Geopolitical risks and mineral-driven renewable energy generation in China: A decomposed analysis

Minerals are critical in manufacturing and handling renewable energy technologies, including solar photovoltaics (PV), wind turbines, electric vehicles (EVs), and power storage batteries. However, mineral mining and the supply-related risky situations stunt the mineral import flows of the renewable energy-producing countries. Given this, we scrutinize the role of the decomposed measures of geopolitical risks in the mineral import demand and this demand-driven renewable energy generation in China, covering monthly data from 1996 to 2020. We employ the quantile autoregressive distributed lag (QARDL) technique for measuring the co-integrating association among the variables across different quantiles. We find a significant effect of the decomposed measures of the geopolitical risks on the mineral import and mineral import-augmented renewable energy generation mainly at the extreme quantiles under long memory. In particular, geopolitical risks 'threats' and 'narrow' parameters negatively affect where the geopolitical risks 'acts' and 'broad' measures positively influence mineral import demand and this demand-driven renewable energy generation in China. Furthermore, we legitimize our findings across the quantile on quantile (QQ) regression technique. Moreover, our investigation outcome is beneficial for elevating mineral-driven renewable energy generation by preventing geopolitical risks in the context of China.