Evolutionary analysis of the global rare earth trade networks

被引:34
作者
Yu, Guihai [1 ]
Xiong, Chao [1 ]
Xiao, Jianxiong [1 ]
He, Deyan [1 ]
Peng, Gang [2 ]
机构
[1] Guizhou Univ Finance & Econ Guiyang, Coll Big Data Stat, Guiyang 550025, Guizhou, Peoples R China
[2] Southwestern Univ Finance & Econ Chengdu, Sch Stat, Chengdu 611130, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
Global rare earth trade; Social network analysis; Global Moran index; TERGM; WORLD-TRADE; DYNAMICS; MODELS;
D O I
10.1016/j.amc.2022.127249
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This study used social network analysis, spatial measurement, and network statistical analysis to study the relationships among countries in the global rare earth trade. Using data on rare earth products from the UN Comtrade database, the global rare earth trade network and its evolving topological characteristics are analyzed for the period 1999-2020. Spatial correlation analysis using the global Moran index showed that countries tended to carry out rare earth trade with neighboring countries, and there were certain spatial aggregations in the trade patterns. A temporal exponential random graph model (TERGM) was used to analyze the influencing factors and evolution of the global rare earth trade, and network motif analysis was used to analyze the influence of network topology on the trading network structure. The results showed that the global rare earth trade model presented the following characteristics: trade from one core country to many other countries, reciprocity between trading countries, and trade around near neighboring rare earth-rich countries. Other factors, such as countries with the same GDP levels and World Trade Organization (WTO) member countries, influenced the global rare earth trade but not the formation of the rare earth trade network. In examining the temporal dependence of rare earth trade networks over a 22-year period, it was found that the linkages of rare earth trade networks among countries remained relatively stable, pointing to the long-term dependence of countries with scarce rare earth resources on resource-rich countries. (C) 2022 Elsevier Inc. All rights reserved.
引用
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页数:23
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共 27 条
  • [1] Dynamic Network Logistic Regression: A Logistic Choice Analysis of Inter- and Intra-Group Blog Citation Dynamics in the 2004 US Presidential Election
    Almquist, Zack W.
    Butts, Carter T.
    [J]. POLITICAL ANALYSIS, 2013, 21 (04) : 430 - 448
  • [2] Emergence of scaling in random networks
    Barabási, AL
    Albert, R
    [J]. SCIENCE, 1999, 286 (5439) : 509 - 512
  • [3] Complex Dependencies in the Alliance Network
    Cranmer, Skyler J.
    Desmarais, Bruce A.
    Menninga, Elizabeth J.
    [J]. CONFLICT MANAGEMENT AND PEACE SCIENCE, 2012, 29 (03) : 279 - 313
  • [4] Toward a Network Theory of Alliance Formation
    Cranmer, Skyler J.
    Desmarais, Bruce A.
    Kirkland, Justin H.
    [J]. INTERNATIONAL INTERACTIONS, 2012, 38 (03) : 295 - 324
  • [5] Dong J., 2021, REV EC MANAGEMENT, V37, P27
  • [6] On the topological properties of the world trade web: A weighted network analysis
    Fagiolo, Giorgio
    Reyes, Javier
    Schiavo, Stefano
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2008, 387 (15) : 3868 - 3873
  • [7] Structure and evolution of the world trade network
    Garlaschelli, D
    Loffredo, MI
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2005, 355 (01) : 138 - 144
  • [8] Discrete temporal models of social networks
    Hanneke, Steve
    Fu, Wenjie
    Xing, Eric P.
    [J]. ELECTRONIC JOURNAL OF STATISTICS, 2010, 4 : 585 - 605
  • [9] A separable model for dynamic networks
    Krivitsky, Pavel N.
    Handcock, Mark S.
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2014, 76 (01) : 29 - 46
  • [10] Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals
    Leifeld, Philip
    Cranmer, Skyler J.
    Desmarais, Bruce A.
    [J]. JOURNAL OF STATISTICAL SOFTWARE, 2018, 83 (06):