img

QQ群聊

img

官方微信

高级检索

黄金科学技术 ›› 2023, Vol. 31 ›› Issue (5): 823-834.doi: 10.11872/j.issn.1005-2518.2023.05.041

• 采选技术与矿山管理 • 上一篇    下一篇

稀土产品全球贸易网络格局演化及其影响因素

廖秋敏1,2(),罗连英1()   

  1. 1.江西理工大学经济管理学院,江西 赣州 341000
    2.江西理工大学矿业贸易与投资研究中心,江西 赣州 341000
  • 收稿日期:2023-03-09 修回日期:2023-05-28 出版日期:2023-10-31 发布日期:2023-11-21
  • 通讯作者: 罗连英 E-mail:309144504@qq.com;3462230944@qq.com
  • 作者简介:廖秋敏(1980-),女,黑龙江齐齐哈尔人,博士,副教授,硕士生导师,从事国际贸易理论与政策、矿产品贸易方面的研究工作。309144504@qq.com
  • 基金资助:
    国家社会科学基金一般项目“稀土产品全球贸易网络格局演化与中国战略地位提升研究”(21BGL182)

Evolution of the Global Trade Network Pattern of Rare Earth Products and Its Influencing Factors

Qiumin LIAO1,2(),Lianying LUO1()   

  1. 1.School of Economics and Management,Jiangxi University of Science and Technology,Ganzhou 341000,Jiangxi,China
    2.Mining Trade and Investment Research Center,Jiangxi University of Science and Technology,Ganzhou 341000,Jiangxi,China
  • Received:2023-03-09 Revised:2023-05-28 Online:2023-10-31 Published:2023-11-21
  • Contact: Lianying LUO E-mail:309144504@qq.com;3462230944@qq.com

摘要:

为了探讨稀土产品贸易网络格局演化影响机制,选取2009—2020年54个主要国家(地区)7种稀土产品的国际贸易数据,运用社会网络分析方法分别从整体和个体层面对比分析了7种主要稀土产品贸易网络格局演化及个体结构特征,并运用指数随机图模型分析和解释了稀土产品贸易网络形成的基础机制。研究发现:(1)稀土矿、稀土氧化物、铈铁以及稀土永磁材料贸易网络的贸易联系趋于紧密,且所有稀土产品贸易网络具有较高的集团性和连通性,呈现出小世界特征,但是该特征趋于弱化;(2)稀土产品出口主要集中在少数稀土大国,稀土金属、铈化合物、稀土氧化物、铈铁和稀土铁合金贸易网络呈现明显的“富人俱乐部”现象;(3)核心国家相对固定,德国和中国均为核心国家,德国影响力优势趋于弱化,中国影响力有所提升;(4)互惠性、多连通性、传递闭合性、聚敛性和扩张性结构效应对7种稀土产品贸易网络演化具有显著的异质性影响。研究结果为我国缓解经贸摩擦、促进稀土国际经济合作提供了政策启示。

关键词: 稀土产品, 贸易网络, 社会网络分析, 格局演化, 影响因素, 指数随机图模型(ERGM)

Abstract:

Rare earths are listed as crisis minerals,key raw materials or strategic minerals by countries around the world.Taking the trade networks of main rare earth products as the research object,the research gets trade data of 7 kinds of rare earth products from 54 major countries(or regions) during the period of 2009—2020,and the evolution of 7 rare earth products trade networks was compared by social network analysis,and the basis of trade network formation mechanism was explained by using the Exponential Random Graph Model(ERGM) analysis method.The conclusions are as follows:(1)Trade network links of some rare earth products,such as rare earth mineral substances,compounds of rare-earth metals,Ferro-cerium and permanent magnet,are getting tight.While the overall structures of all the networks are still relatively loose.Trade networks of all rare earth products have a high community structure and connectivity,showing a small world property but gradually weakening.(2)In the trade networks of 7 rare earth products,it can be easily found that huge trade volumes are controlled by a few countries,with an obvious center-periphery phenomenon.Rich Club Phenomenon is significant in trade networks of rare earth metals,rare-earth compounds,cerium compounds,Ferro-cerium and Ferro-alloys.(3)Countries’ performance in Degree Centrality remain stable.Germany and China are both core countries,but Germany’s advantage is weakening while China strengthening.(4)Influences of mutualism,multi-connectivity,transitive closure,convergence and expansionary structural effects on trade network evolution of 7 rare earth products are significantly heterogeneous.The research results provide policy enlightenment for China to strengthen the strategic research and judgment of the new pattern and new situation of global rare earth product trade and alleviate economic and trade frictions.

Key words: rare earth products, trade network, social network analysis, pattern evolution, influencing factors, exponential random graph model(ERGM)

中图分类号: 

  • F742

表1

稀土产品名称及分类"

产业链产品编码产品名称
上游HS 253090代表海关编码前6位为253090的稀土产品,主要包括按重量计中重稀土总含量≥30%的稀土矿
中游HS 280530代表海关编码前6位为280530的稀土产品,主要包括稀土金属(不论是否互混合或熔合)、钪及钇
HS 284610代表海关编码前6位为284610的稀土产品,包括氧化铈、氢氧化铈、碳酸铈、氰化铈及铈的其他化合物
HS 284690代表海关编码前6位为284690的稀土产品,包括其他稀土金属、钪、钇及其混合物的化合物(铈除外)
下游HS 360690代表海关编码前6位为360690的稀土产品,主要包括铈铁合金
HS 720299

代表海关编码前6位为720299的稀土产品,包括按重量计中重稀土总含量≥30%的铁合金(按重量计稀土

元素总含量在10%以上)、稀土硅铁合金(按重量计稀土元素总含量在10%以上)、其他按重量计稀土元素

总含量在10%以上的铁合金

HS 850511代表海关编码前6位为850511的稀土产品,包括稀土永磁铁及稀土永磁体

表2

54个国家(地区)名单"

序号iso国名

所属

大洲

序号iso国名所属大洲
1ARE阿联酋亚洲28ITA意大利欧洲
2ARG阿根廷美洲29JPN日本亚洲
3AUS澳大利亚大洋洲30KAZ哈萨克斯坦亚洲
4AUT奥地利欧洲31KOR韩国亚洲
5BEL比利时欧洲32LUX卢森堡欧洲
6BRA巴西美洲33LVA拉脱维亚欧洲
7CAN加拿大美洲34MAC中国澳门亚洲
8CHE瑞士欧洲35MEX墨西哥美洲
9CHN中国亚洲36MKD北马其顿欧洲
10CZE捷克欧洲37MYS马来西亚亚洲
11DEU德国欧洲38NLD荷兰欧洲
12DNK丹麦欧洲39NOR挪威欧洲
13EGY埃及非洲40PHL菲律宾亚洲
14ESP西班牙欧洲41POL波兰欧洲
15EST爱沙尼亚欧洲42RUS俄罗斯欧洲
16FIN芬兰欧洲43SAU沙特阿拉伯亚洲
17FRA法国欧洲44SGP新加坡亚洲
18GBR英国欧洲45SVK斯洛伐克欧洲
19GRC希腊欧洲46SVN斯洛文尼亚欧洲
20HKG中国香港亚洲47SWE瑞典欧洲
21HRV克罗地亚欧洲48THA泰国亚洲
22HUN匈牙利欧洲49TUR土耳其亚洲
23IDN印尼亚洲50UKR乌克兰欧洲
24IND印度亚洲51USA美国美洲
25IRL爱尔兰欧洲52VNM越南亚洲
26IRN伊朗亚洲53ZAF南非非洲
27ISR以色列亚洲54ZMB赞比亚非洲

图1

2009—2020年7种稀土产品贸易网络整体网络密度指标演变"

表3

2009—2020年7种稀土产品贸易网络集聚系数及平均路径长度演变"

年份产品集聚系数

稀土矿

(HS 253090)

稀土金属

(HS 280530)

铈化合物

(HS 284610)

稀土氧化物

(HS 284690)

铈铁

(HS 360690)

稀土铁合金

(HS 720299)

稀土永磁材料

(HS 850511)

20090.600.620.560.640.520.510.67
20130.600.570.570.590.530.500.68
20170.630.590.580.600.550.500.71
20200.650.500.600.610.550.500.72
年份产品平均路径长度

稀土矿

(HS 253090)

稀土金属

(HS 280530)

铈化合物

(HS 284610)

稀土氧化物

(HS 284690)

铈铁

(HS 360690)

稀土铁合金

(HS 720299)

稀土永磁材料

(HS 850511)

20091.702.062.192.051.952.041.54
20131.692.311.981.982.012.111.52
20171.692.291.961.911.902.121.49
20201.662.401.961.811.942.031.44

表4

2009—2020年7种稀土产品贸易网络度数中心度指标前3名国家(地区)演变(稀土矿HS 253090)"

年份相对点出度相对点入度
排名国家指标值排名国家指标值
20091德国98.111德国64.15
2西班牙90.572美国56.60
3奥地利90.573英国52.83
20131德国94.341德国66.04
2荷兰90.572美国62.26
3奥地利88.683英国58.49
20171德国94.341德国67.92
2意大利86.792美国64.15
3波兰84.913中国62.26
20201德国94.341美国66.04
2荷兰92.452德国64.15
3意大利86.793中国58.49

图2

2020年7种稀土产品贸易网络度分布"

表5

2009—2020年7种稀土产品贸易网络点强度指标前3名国家(地区)演变(稀土矿:HS 253090)"

年份相对出强度相对入强度
排名国家指标值排名国家指标值
20091西班牙4.831中国3.06
2德国4.742德国2.32
3中国2.413法国2.22
20131澳大利亚2.931中国2.63
2中国1.992德国1.51
3美国1.863日本1.08
20171澳大利亚2.121中国2.13
2美国0.352马来西亚0.20
3中国0.243德国0.14
20201澳大利亚2.021中国2.09
2中国0.322美国0.23
3荷兰0.283德国0.18

图3

2009—2020年7种稀土产品贸易网络中主要国家中介中心度演变(稀土矿和稀土金属)"

表6

指数随机图模型的变量介绍"

统计项对应变量图形变量解释
内生性结构变量(弧)edges网络中边的基础效应,相当于截距项
互惠性mutual网络中的互惠结构对稀土产品全球贸易网络的影响
聚敛性gwidegree网络中的“星型”聚敛结构对稀土产品全球贸易网络的影响
积极性gwodegree网络中的“星型”发散结构对稀土产品全球贸易网络的影响
传递性gwesp网络中的传递闭合结构对稀土产品全球贸易网络的影响
多连通性gwdsp网络中的多连通结构对稀土产品全球贸易网络的影响
节点属性变量发送者属性lnGDP经济体的经济发展水平、人口规模和经济制度对其发送稀土产品贸易网络关系的影响
lnpop
lnEFI
接收者属性lnGDP经济体的经济发展水平、人口规模和经济制度对其接收稀土产品贸易网络关系的影响
lnpop
lnEFI
嵌入性网络协变量距离网络lndist经济体间的地理距离、宗教关系、语言关系、接壤关系或贸易协定关系对稀土产品贸易网络的影响
宗教网络relig
语言网络comlang
接壤网络border
贸易协定RTA

表7

2020年7种稀土产品ERGM的回归结果(2%的贸易额阈值)"

网络统计量模型1模型2模型3模型4模型5模型6模型7
稀土矿稀土金属铈化合物稀土氧化物铈铁稀土铁合金稀土永磁材料
边(弧)edges-46.01***-36.15***-31.64***-32.78***-42.91***-23.56***-53.45***
(3.73)(7.47)(5.48)(4.36)(4.85)(3.57)(4.34)
内生性结构效应mutual0.15-0.14-0.69*-0.260.150.250.56***
(0.16)(0.35)(0.31)(0.24)(0.19)(0.23)(0.17)
gwesp0.060.44***0.94***1.53***0.65***0.75***-0.42
(0.19)(0.13)(0.14)(0.19)(0.13)(0.13)(0.37)
gwdsp-0.15***-0.01-0.03-0.05**-0.10***-0.09***-0.12**
(0.02)(0.03)(0.02)(0.02)(0.02)(0.02)(0.04)
gwideg3.94*1.59*3.33***3.50***4.32***2.90***5.75
(1.54)(0.73)(0.82)(0.81)(1.07)(0.76)(3.71)
gwodeg-0.95-2.04***-1.48**0.72-0.51-0.79-2.95
(0.90)(0.50)(0.51)(0.62)(0.51)(0.49)(2.02)
发送者属性lnGDP0.64***0.42**0.24**0.43***0.19**0.20**0.96***
(0.08)(0.15)(0.09)(0.09)(0.07)(0.07)(0.08)
lnpop0.15*0.110.070.010.30***0.21**0.19*
(0.07)(0.13)(0.08)(0.07)(0.07)(0.06)(0.08)
lnEFI1.50**1.961.020.753.77***-0.032.62***
(0.48)(1.08)(0.73)(0.60)(0.66)(0.54)(0.64)
接收者属性lnGDP0.21*0.66**0.030.010.47***0.220.20*
(0.08)(0.21)(0.14)(0.11)(0.10)(0.11)(0.09)
lnpop0.50***-0.060.50***0.38***-0.010.24*0.49***
(0.08)(0.16)(0.13)(0.10)(0.10)(0.10)(0.08)
lnEFI3.24***-0.122.27*2.00*2.09**1.343.79***
(0.60)(1.25)(1.03)(0.83)(0.77)(0.84)(0.64)
网络协变量lndist-1.03***-0.66***-0.46***-0.40***-0.92***-0.56***-1.06***
(0.08)(0.12)(0.09)(0.08)(0.09)(0.08)(0.08)
relig0.65**-0.350.07-0.220.74***0.53**0.82***
(0.21)(0.40)(0.27)(0.25)(0.22)(0.20)(0.23)
comlang-0.410.330.290.27-0.29-0.08-0.07
(0.18)(0.23)(0.18)(0.15)(0.18)(0.19)(0.19)
border1.51***0.350.181.24***0.72*1.24***0.77
(0.39)(0.35)(0.33)(0.31)(0.29)(0.26)(0.44)
RTA0.26*0.190.28*0.31*0.090.130.44***
(0.11)(0.18)(0.13)(0.12)(0.11)(0.12)(0.11)
Chen Z H, An H Z, An F,et al,2018.Structural risk evaluation of global gas trade by a network-based dynamics simulation model[J].Energy,159:457-471.
Dong D, Gao X Y, Sun X Q,et al,2018.Factors affecting the formation of copper international trade community:Based on resource dependence and network theory[J].Resources Policy,57:167-185.
Gao Fengping, Zhang Pu, Liu Dacheng,et al,2019.The rare earths global market updates and the rare earths industry master plan of the united states and its allies[J].Journal of International Trade,(7):63-81.
Hou W Y, Liu H F, Wang H,et al,2018.Structure and patterns of the international rare earths trade:A complex network analysis[J].Resources Policy,55:133-142.
Ji Qidi, Liu Weidong, Chen Wei,et al,2021.Structure of global copper-containing products trade network based on industrial chain perspective[J].Scientia Geographica Sinica,41(1):44-54.
Li Hangfei, Wei Shaobin,2022.A study on spatial-temporal pattern evolution of global rare earth trade network and China’s status change[J].World Regional Studies: 1-16[2023-10-10]..
Li Qi, Zheng Minggui, Luo Yuwen,2022.Research on China’s rare earth trade security(1992—2018)—Based on complex network analysis method[J].Chinese Rare Earths,43(1):147-158.
Li Huajiao, An Haizhong, Qi Yajie,et al,2020.Trade and competitiveness structure of China’s advantageous mineral resources based on the international trade network of industrial chain:A case study of tungsten[J].Resources Science,42(8):1504-1514.
Liu Jianwei,2022.Strategic competition and rebuilding of the U.S.rare earth industrial chain[J].Pacific Journal,30(12):52-63.
Liu Luxin,2021.Changes and prospects of U. S. science and technology strategy[J].Contemporary International Relations,(10):37-45.
Ma Yuan, Gong Yuanyuan,2021.Deconstruction of energy trade network situation and influencing factors in “Silk Road Economic Belt”:Based on social network analysis[J].International Business,(4):101-119.
Ma Yuan, Lei Huifang,2019.Simulation of energy trade network evolution and connectivity effect of countries along the Silk Road Economic Belt[J].Journal of Statistics and Information,34(9):92-102.
Ma Yuan, Xu Lili,2017.Natural gas trade network of countries along the “Belt and Road”[J].World Economy Studies,(3):109-122,136.
Peng Peng, Cheng Shifen, Yang Yu,et al,2021.Research on characteristics and evolution of global LNG transportation network[J].Geographical Research,40(2):373-386.
Wang W Y, Li Z F, Cheng X,2019.Evolution of the global coal trade network:A complex network analysis[J].Resources Policy,62:496-506.
Wang X B, Yao M T, Li J S,et al,2019.Global embodied rare earths flows and the out flow paths of China’s embodied rare earths:Combining multi-regional input-output analysis with the complex network approach[J].Journal of Cleaner Production,216:435-445.
Wu Yiding, Peng Zilong, Lai Dan,et al,2023.Exploring international rare earth industry landscape changes and China’s strategic responses[J].Bulletin of Chinese Academy of Sciences,38(2):255-264.
Xi X, Zhou J S, Gao X Y,et al,2019.Impact of changes in crude oil trade network patterns on national economy[J].Energy Economics,84:104490.
Xia Qifan, Du Debin,2022.Evolution of energy trade structure in the 21st Century Maritime Silk Road and its trade relations with China[J].Geographical Research,41(7):1797-1813.
Xia X H, Chen B, Wu X D,et al,2017.Coal use for world economy:Provision and transfer network by multi-region input-output analysis[J].Journal of Cleaner Production,143:125-144.
Xu Shuitai, Ma Caiwei, Zhu Wenxing,2022.Study on the structure and evolution of rare earth trade network along the Belt and Road[J].Gold Science and Technology,30(2):196-208.
Xu Helian, Sun Tianyang, Cheng Lihong,2015.Trade patterns and influence factors of high-end manufacturing on “One Belt and One Road”[J].Finance and Trade Economics,(12):74-88.
Yu Yu, Ma Daipeng, Wang Xianmei,2022.International trade network resilience for products in the whole industrial chain of iron ore resources[J].Resources Science,44(10):2006-2021.
Zhang Hong, Ding Hao, Zhang Lijun,et al,2020.Global natural gas trade pattern evolution and development of China’s natural gas importing paths[J].Areal Research and Development,39(6):1-5.
Zhong W Q, Dai T, Wang G S,et al,2018.Structure of international iron flow:Based on substance flow analysis and complex network[J].Resources,Conservation and Recycling,136:345-354.
Zhu Kongchao, Zhao Yuan, Xia Siyou,et al,2023.Evolution of the petroleum products trade network of countries along the “Belt and Road”[J].World Regional Studies,32(6):1-13.
Zhu Kongchao, Zhao Yuan, Yao Yabing,et al,2022.Global rare earth import competition pattern and prediction for potential trade links[J].Resources Science,44(1):70-84.
Zhuang Delin, Li Jiahao, Chen Ziruo,et al,2022.The dynamic change of global rare earth trade network and its impact mechanism:From the perspective of industrial chain[J].Scientia Geographica Sinica,42(11):1900-1911.
高风平,张璞,刘大成,等,2019.国际稀土市场新格局与中国稀土产业战略选择[J].国际贸易问题,(7):63-81.
计启迪,刘卫东,陈伟,等,2021.基于产业链的全球铜贸易网络结构研究[J].地理科学,41(1):44-54.
李航飞,魏少彬,2022.全球稀土贸易网络时空格局演化与中国地位变迁研究[J].世界地理研究: 1-16[2023-10-10]..
李华姣,安海忠,齐亚杰,等,2020.基于产业链国际贸易网络的中国优势矿产资源全球贸易格局和竞争力——以钨为例[J].资源科学,42(8):1504-1514.
李期,郑明贵,罗宇文,2022.中国稀土贸易安全研究(1992—2018)——基于复杂网络分析方法[J].稀土,43(1):147-158.
刘建伟,2022.大国战略竞争背景下美国稀土产业链的重建及其影响[J].太平洋学报,30(12):52-63.
刘露馨,2021.美国科技战略的变革及前景[J].现代国际关系,(10):37-45.
马远,宫圆圆,2021.“丝绸之路经济带”能源贸易网络态势解构及影响因素——基于社会网络分析法[J].国际商务(对外经济贸易大学学报),(4):101-119.
马远,雷会妨,2019.丝绸之路经济带沿线国家能源贸易网络演化及互联互通效应模拟[J].统计与信息论坛,34(9):92-102.
马远,徐俐俐,2017.“一带一路”沿线国家天然气贸易网络结构及影响因素[J].世界经济研究,(3):109-122,136.
彭澎,程诗奋,杨宇,等,2021.全球液化天然气运输网络特征及其演化[J].地理研究,40(2):373-386.
吴一丁,彭子龙,赖丹,等,2023.稀土产业链全球格局现状、趋势预判及应对战略研究[J].中国科学院院刊,38(2):255-264.
夏启繁,杜德斌,2022.21世纪海上丝绸之路能源贸易结构及与中国的贸易关系演变[J].地理研究,41(7):1797-1813.
徐水太,马彩薇,朱文兴,2022.“一带一路”稀土贸易网络结构及演化研究[J].黄金科学技术,30(2):196-208.
许和连,孙天阳,成丽红,2015.“一带一路”高端制造业贸易格局及影响因素研究——基于复杂网络的指数随机图分析[J].财贸经济,(12):74-88.
于娱,马代鹏,王贤梅,2022.国际铁矿资源全产业链产品的贸易网络韧性[J].资源科学,44(10):2006-2021.
张宏,丁昊,张力钧,等,2020.全球天然气贸易格局及中国天然气进口路径研究[J].地域研究与开发,39(6):1-5.
祝孔超,赵媛,夏四友,等,2023.“一带一路”沿线国家石油产品贸易网络演化分析[J].世界地理研究,32(6):1-13.
祝孔超,赵媛,姚亚兵,等,2022.全球稀土进口竞争格局分析及潜在贸易联系预测[J].资源科学,44(1):70-84.
庄德林,李嘉豪,陈紫若,等,2022.全球稀土贸易网络的动态演变与影响机制——基于产业链的视角[J].地理科学,42(11):1900-1911.
[1] 易璐, 李云云, 郑明贵, 谢柳燕. 全球铝土矿贸易格局演化及中国贸易特征[J]. 黄金科学技术, 2024, 32(5): 926-938.
[2] 张帅, 赵鑫, 彭祥玉, 王宇斌, 桂婉婷, 田家怡. 基于双隐含层BP神经网络的某金矿回收率预测研究[J]. 黄金科学技术, 2024, 32(1): 170-178.
[3] 叶前林, 马继越. 全球稀土贸易格局演化及竞合关系研究[J]. 黄金科学技术, 2024, 32(1): 144-159.
[4] 王开彬, 刘钦, 王洪涛. 压力型锚索锚固段荷载传递特征及影响因素研究[J]. 黄金科学技术, 2024, 32(1): 123-131.
[5] 许云美, 袁利伟, 龙皓楠. 干堆尾矿库稳定性影响因素的敏感性分析[J]. 黄金科学技术, 2023, 31(6): 1014-1022.
[6] 张国栋, 刘佳, 马凤山, 李光, 郭捷. 三山岛金矿海底开采井下沉降特点及影响因素浅析[J]. 黄金科学技术, 2023, 31(5): 785-793.
[7] 何玉龙, 刘佳, 马凤山, 李光, 郭捷. 三山岛金矿地面沉降特征及原因分析[J]. 黄金科学技术, 2023, 31(4): 605-612.
[8] 黄锴强,徐水太,薛飞. 基于ISM和ANP的废弃稀土矿山治理效果影响因素分析[J]. 黄金科学技术, 2021, 29(2): 306-314.
[9] 李淑琴,陈晓吾,牟长贤. 原子荧光光谱法测定化探样品中As、Sb、Bi的影响因素[J]. 黄金科学技术, 2013, 21(6): 78-81.
[10] 李勇, 宋卫东, 岳发强, 张锐, 张平顺. 模糊综合评判方法在矿山产量优化中的应用[J]. J4, 2003, 11(3): 35-38.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!