黄金中游产品国际贸易网络演化特征研究
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摘要
黄金是中国战略性矿产资源之一,黄金中游产品国际贸易能反映产业链上下游国际供给关系及供给安全,战略意义重大。为了研究黄金中游产品国际贸易网络演化特征,本文利用2008～2017年的黄金中游产品国际贸易数据,基于复杂网络理论,构建了有向加权复杂网络模型,从贸易网络的整体结构特征、幂律分布特征、贸易枢纽国、核心国家识别等方面进行研究。结果显示,其贸易参与规模不断扩大,但贸易份额向少数国家集聚程度增加;美国、德国的贸易控制能力较强,处于贸易枢纽地位。通过研究,建议黄金中游产品贸易国通过观测美国、德国的黄金贸易趋势调整贸易量;瑞士、南非、美国是相关国家的首选贸易伙伴;澳大利亚、巴西和南非是拥有精加工能力但资源不足的国家建立贸易关系的首选。
Gold is one of China's strategic mineral resources,and its international trade is related to supply security and strategic importance.Through the international trade of gold midstream products,it can reflect the upstream and downstream international supply relationship of the industrial chain.In order to study the evolution characteristics of the international trade network of gold midstream products,this paper constructs a directed weighted complex network model based on the complex network theory using the international trade data of gold midstream products from 2008 to 2017.We conduct research on the overall structural characteristics of trade networks,power law distribution characteristics,trade hub countries,and identification of core countries.The results show that the scale of trade participation is expanding,but the trade share is increasing to a few countries.The United States and Germany have strong trade control capabilities and they are in the trade hub.We recommend that the gold midstream product trading countries adjust their trade volume by observing the gold trade trends between the two countries through the research.Switzerland,South Africa and the United States are the preferred trading partners of the countries concerned.Australia,Brazil and South Africa are the first choice for establishing trade relations in countries with fine processing capabilities but insufficient resources.
Gold is one of China's strategic mineral resources,and its international trade is related to supply security and strategic importance.Through the international trade of gold midstream products,it can reflect the upstream and downstream international supply relationship of the industrial chain.In order to study the evolution characteristics of the international trade network of gold midstream products,this paper constructs a directed weighted complex network model based on the complex network theory using the international trade data of gold midstream products from 2008 to 2017.We conduct research on the overall structural characteristics of trade networks,power law distribution characteristics,trade hub countries,and identification of core countries.The results show that the scale of trade participation is expanding,but the trade share is increasing to a few countries.The United States and Germany have strong trade control capabilities and they are in the trade hub.We recommend that the gold midstream product trading countries adjust their trade volume by observing the gold trade trends between the two countries through the research.Switzerland,South Africa and the United States are the preferred trading partners of the countries concerned.Australia,Brazil and South Africa are the first choice for establishing trade relations in countries with fine processing capabilities but insufficient resources.
引文
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[15]郝晓晴，安海忠，陈玉蓉，等．基于复杂网络的国际铁矿石贸易演变规律研究[J]．经济地理，2013,33(1):92-97.HAO Xiaoqing,AN Haizhong,CHEN Yurong,et al.Research on evolution of international iron ore trade based on complex network theory[J].Economic Geography,2013,33(1):92-97．
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[20]张丽佳，张丽丽，郝晓晴，等．基于复杂网络的国际铜矿石贸易演变规律研究[J]．中国矿业，2015,24(10):57-62.ZHANG Lijia,ZHANG Lili,HAO Xiaoqing,et al.Research into evolution of international copper ore trade based on complex network theory[J].China Mining Magazine,2015,24(10):57-62．
[21]史超亚，高湘昀，孙晓奇，等．复杂网络视角下的国际铝土矿贸易演化特征研究[J]．中国矿业，2018,27(1):57-62.SHI Chaoya,GAO Xiangyun,SUN Xiaoqi,et al.Study on the evolution characteristics of international bauxite trade from the perspective of complex network[J].China Mining Magazine,2018,27(1):57-62．
[22]FREEMAN L C.Centrality in social networks conceptual clarification[J].Social Networks,1978,1(3):215-239.
[2]杜方欣，张德生．基于混合Copula-GARCH模型的黄金与股票的相关性分析[J]．现代经济信息，2013(24):353-355.DU Fangxin,ZHANG Desheng.Correlation analysis of gold and stock based on mixed Copula-GARCH model[J].Modern Economic Information,2013(24):353-355．
[3]张清朵，刘玲．基于时变Copula函数的石油与黄金相关性研究[J]．现代商业，2015(9):250-251.ZHANG Qingduo,LIU Ling.Correlation between petroleum and gold based on time-varying Copula function[J].Modern Business,2015(9):250-251．
[4]李鹏远，申维．全球黄金供需格局变迁[J]．中国矿业，2014,23(S1):6-10.LI Pengyuan,SHEN Wei.The changes in the global gold supply and demand structure[J].China Mining Magazine,2014,23(S1):6-10．
[5]李鹏远，周平，唐金荣，等．中国黄金制造业用金需求趋势预测[J]．资源科学，2015,37(5):1030-1037.LI Pengyuan,ZHOU Ping,TANG Jinrong,et al.China gold fabrication demand prediction[J].Resources Science,2015,37(5):1030-1037．
[6]蒋先玲，王炳楠．国际黄金价格波动特征及影响因素研究---基于周期视角的分析[J]．价格理论与实践，2017(12):98-101.JIANG Xianling,WANG Bingnan.Study on the fluctuation characteristics of international gold price and factors based on cycle perspective[J].Price:Theory&Practice,2017(12):98-101．
[7]丁绪辉，高新雨，杨凯凯．国际黄金价格波动特征及风险防范研究---基于GARCH族模型的实证分析[J]．价格理论与实践，2014(7):72-74.DING Xuhui,GAO Xinyu,YANG Kaikai.International gold price volatility characteristics and risk prevention research:an empirical analysis based on GARCH family model[J].Price:Theory&Practice,2014(7):72-74．
[8]杨丽君，张坤．关于美元指数与黄金价格联动性研究---基于适应性预期的分析[J]．价格理论与实践，2016(11):94-97.YANG Lijun,ZHANG Kun.Research on the linkage between the dollar index and gold prices:based on adaptive expectations[J].Price:Theory&Practice,2016(11):94-97．
[9]BHADURI S,GHOSH D,GHOSH S.Fluctuation of USAgold price-revisited with chaos-based complex network method[J].Eprint arXiv,2016．
[10]WATTS D J,STROGATZ S H.Collective dynamics of smallworld networks[J].Nature,1998,393:440-442．
[11]BARABSI A L,JEONG H,NDA Z,et al.Evolution of the social network of scientific collaborations[J].Physica A:Statistical Mechanics and its Applications,2001,311(3-4):590-614．
[12]刘辉，申玉铭，王伟，等．北京金融服务业集群的网络特征及影响因素[J]．经济地理，2013,33(1):131-137.LIU Hui,SHEN Yuming,WANG Wei,et al.Research on the networks and factors for financial services industry:with the case study of Beijing finance street[J].Economic Geography,2013,33(1):131-137．
[13]李敬，陈澍，万广华，等．中国区域经济增长的空间关联及其解释---基于网络分析方法[J]．经济研究，2014(11):4-16.LI Jing,CHEN Shu,WAN Guanghua,et al.Study on the spatial correlation and explanation of regional economic growth in China[J].Economic Research Journal,2014(11):4-16．
[14]姜巍，高卫东，张敏．中国煤炭资源铁路流通网络结构特征及其演变[J]．经济地理，2013,33(1):98-104.JIANG Wei,GAO Weidong,ZHANG Min.China coal resource railway circulation networks structural characteristic and evolvement[J].Economic Geography,2013,33(1):98-104．
[15]郝晓晴，安海忠，陈玉蓉，等．基于复杂网络的国际铁矿石贸易演变规律研究[J]．经济地理，2013,33(1):92-97.HAO Xiaoqing,AN Haizhong,CHEN Yurong,et al.Research on evolution of international iron ore trade based on complex network theory[J].Economic Geography,2013,33(1):92-97．
[16]WANG Xibo,GE Jianping,WEI Wendong,et al.Spatial dynamics of the communities and the role of major countries in the international rare earths trade:a complex network analysis[J].Plos One,2016,11(5):e0154575．
[17]AN H Z,ZHONG W Q,CHEN Y R,et al.Features and evolution of international crude oil trade relationships:a tradingbased network analysis[J].Energy,2014,74(5):254-259．
[18]杨鑫，安海忠，高湘昀．国际天然气贸易关系网络结构特征研究：基于复杂网络理论[J]．资源与产业，2012,14(2):81-87.YANG Xin,AN Haizhong,GAO Xiangyun.Structural features of global gas trading relationship network based on complex network theory[J].Resources&Industries,2012,14(2):81-87．
[19]郝晓晴，安海忠，刘晓佳，等．主要矿产品国际贸易分析[J]．资源与产业，2013,15(6):18-34.HAO Xiaoqing,AN Haizhong,LIU Xiaojia,et al.Analysis on main mineral products in internationam trade[J].Resources&Industries,2013,15(6):18-34．
[20]张丽佳，张丽丽，郝晓晴，等．基于复杂网络的国际铜矿石贸易演变规律研究[J]．中国矿业，2015,24(10):57-62.ZHANG Lijia,ZHANG Lili,HAO Xiaoqing,et al.Research into evolution of international copper ore trade based on complex network theory[J].China Mining Magazine,2015,24(10):57-62．
[21]史超亚，高湘昀，孙晓奇，等．复杂网络视角下的国际铝土矿贸易演化特征研究[J]．中国矿业，2018,27(1):57-62.SHI Chaoya,GAO Xiangyun,SUN Xiaoqi,et al.Study on the evolution characteristics of international bauxite trade from the perspective of complex network[J].China Mining Magazine,2018,27(1):57-62．
[22]FREEMAN L C.Centrality in social networks conceptual clarification[J].Social Networks,1978,1(3):215-239.
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