国际稀土永磁制成品贸易网络结构特征与依赖关系演化

Structural Characteristics and Dependency Relationship Evolution of the International Trade Network for Rare Earth Permanent Magnet Manufactured Products

摘要

稀土永磁制成品是支撑战略性产业的核心基础元件，其全球贸易格局与依赖关系深刻影响着各国的能源转型进程和科技竞争力。当前，全球稀土永磁制成品产能较为集中，贸易关系呈现非对称特征，同时地缘政治风险进一步加剧了供应链的不确定性。在此背景下，系统揭示国际稀土永磁制成品贸易网络的结构特征和国家间的贸易依赖关系，对于保障中国产业链供应链安全、优化产业布局以及制定精准的贸易政策具有重要意义。基于联合国商品贸易统计数据库，聚焦集成高性能稀土永磁材料的关键终端应用产品，构建2012—2024年国际稀土永磁制成品贸易网络。首先，运用复杂网络分析方法，从宏观整体拓扑结构和微观节点中心性2个维度，刻画网络的演化轨迹与节点地位的变迁。其次，引入鲁汶算法对网络进行凝聚子群划分，揭示贸易集团的动态重组与阵营化趋势。最后，构建贸易依赖指数，从依赖强度、拓扑结构及关键关系对3个层面，剖析国家间贸易依赖关系模式。研究发现：1）全球稀土永磁制成品贸易网络的互联性与效率显著提升，网络密度由0.222增至0.311，平均路径长度缩短至1.882，平均聚类系数相对较高，贸易网络呈现“小世界”特征。2）节点影响力格局发生重构，逐渐呈现多极化趋势。德国依托高端制造业基础始终稳居核心枢纽；中国度中心度先升后降，但仍处前列，不过其中介能力较弱，并非贸易流的关键桥梁；法国、意大利、巴西等后来居上，成为2024年新的关键中介节点；泰国等新兴市场的影响力显著上升，而美国的直接连接影响力相对减弱。3）网络中观结构经历了从效率优先到安全优先的转变，由地理邻近驱动的聚类演化为地缘政治导向的阵营化格局，形成了以中国为核心的全球南方子群与美欧主导的发达国家子群共存的格局。4）贸易依赖关系呈现中度依赖增强、高度依赖先增后降、低度依赖收缩的聚合趋势。核心依赖关系也从早期的资源—市场互补型，日益转向核心制造国之间的产业链协同型，并表现出显著的区域化收缩特征。针对上述发现，提出以下建议：实施枢纽强化和通道多元化战略，保障供应链畅通与安全；推动嵌入式协同和标准引领，深度融入并塑造高端产业链；深化南南合作和拓展第三极市场，构建更加平衡的贸易格局；聚焦核心技术突破和品牌化发展，巩固网络核心节点地位；建立健全供应链风险监测与多边协商机制，积极参与全球治理。

Abstract

Rare earth permanent magnet (REPM) manufactured products are core components of strategic industries, and their global trade patterns and dependencies strongly affect energy transitions and technological competitiveness. Global REPM production is concentrated; trade relations are asymmetric; and geopolitical risks increase supply chain uncertainty. Revealing the structure and dependency evolution of international REPM trade network is therefore important for China's supply chain security, industrial layout, and trade policy. Using UN Comtrade data and focusing on key end-use products incorporating high-performance REPM materials, this study builds an international REPM manufactured products trade network from 2012 to 2024. It first applies complex network analysis to characterize the network's evolution and shifts in node status through macro-level topology and micro-level centrality. It then uses the Louvain algorithm to identify cohesive subgroups, revealing trade bloc restructuring and bloc formation. Finally, it constructs a trade dependence index to analyze inter-country dependence patterns in terms of intensity, topology, and key relationship pairs. The results show that network connectivity and efficiency improved notably, with density rising from 0.222 to 0.311, average path length falling to 1.882, and relatively high clustering, indicating “small-world” features. Node influence has become more multipolar. Germany remains a core hub; China's degree centrality first rose then declined but remains high, though its intermediary capacity is weak; France, Italy and Brazil become new key intermediaries in 2024; Thailand's influence rises, while U.S. direct connectivity weakens. The meso-level structure shifts from efficiency-first to security-first, evolving from geographic clustering to geopolitically oriented blocs, with a China-centered global south subgroup coexisting with a U.S.-Europe-led developed-country subgroup. Dependence shows stronger moderate ties, high dependence rising then falling, and shrinking low dependence. Core ties shift from resource-market complementarity to industrial-chain synergy among major manufacturers, with marked regionalization. It is recommended that a strategy of hub strengthening and corridor diversification be implemented to ensure smooth and secure supply chains, that embedded collaboration and standard leadership be promoted to deeply integrate into and shape high-end industrial chains, that South-South cooperation be deepened and third-pole markets be expanded to build a more balanced trade pattern, that breakthroughs in core technologies and brand development be pursued to consolidate the position of core network nodes, and that supply chain risk monitoring and multilateral consultation mechanisms be established and improved to actively participate in global governance.

关键词

贸易网络 / 稀土制成品 / 依赖关系 / 网络分析

Key words

trade network / rare earth manufactured products / dependency relationships / network analysis

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基金资助

内蒙古自然科学基金面上项目(2025MS07034)