Year: 2025
Type: article
Abstract: The growing disparity between the supply and demand of rare earth elements has become increasingly pronounced, and accurately forecasting China's future rare earth demand is crucial for the rational exploitation and utilization of formulating import and export strategies and national industrial polices. In this paper, grey correlation analysis was used to select rare earth prices, China's GDP and industrial structure from 2003 to 2023 as the main driving variables, and a combined model of ARMI-GM-BP neural network was constructed to predict China's rare earth demand from 2025 to 2035 by scenario analysis. The results show that the selected driving variables have a high correlation with China's rare earth demand, and the combined model has higher prediction accuracy than the single model. From 2025 to 2035, China's rare earth demand and imports are expected to continue to rise, however, the rate of growth is expected and decelerate. Under the three scenarios, the projected average demand for rare earth elements in China for the years 2025, 2030 and 2035 is 280000 tons, 420000 tons and 470000 tons, respectively. The average import dependence forecast for 2025—2035 is 24.96%. Accordingly, targeted policy recommendations are formulated.
Source: Chinese Rare Earths
Authors: Ming-gui ZHENG, Li LI, Ming YU
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4411110602