中国高端制造业的全球贸易网络格局及其影响因素分析
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摘要
随着新一轮科技革命与全球产业格局重塑,解构发达国家与中国高端制造业的空间网络格局变化,判断不同时期中国在全球的高端制造业贸易网络地位,分析中国高端制造业网络的影响因素具有十分重要的现实意义。运用网络分析法可视化全球高端制造业空间贸易关联网络拓扑形态和关键特征,通过QAP分析贸易网络影响因素。结果表明:①全球高端制造业贸易网络呈现典型整体贸易网络结构特征,网络密度和互惠性高,联系紧密并保持良好的互通性,贸易活动较频繁;②整体网加权点强度测度表明中国在贸易网络呈现较频繁的贸易活动,并逐渐迈入网络贸易规模前列的空间格局;③个体网结构洞分析表明中国在网络中仍表现出较强的依赖性,贸易行为受其它节点的限制,中国还未成为全球高端制造业贸易网络的"织网者";④工业增加值和地理相邻等因素对全球高端制造业贸易具有统计上的显著性影响。
With the new round of scientific and technological revolution and the global industrial structure remodeling, it has strong significance to deconstruct the spatial network pattern between China's high-end manufacturing industry and developed countries, judge China's position as a global high-end manufacturing trade network in different periods, and analyze China's high-end manufacturing network. The social network analysis method is used to visualize the topological form and key features of spatial trade associated network in the global advanced manufacturing, and its influencing factors are analyzed through QAP. The results show that: 1) The global high-end manufacturing trade network presents the characteristics of a typical overall trade network structure with high network density and reciprocity, close contact and good interoperability, and frequent trade activities; 2) The weighted directional intensity measurement of the whole network indicates that China presents more frequent trade activities in the trade network and gradually enters the forefront of the spatial pattern; 3) Individual network structure hole analysis shows that China still shows stronger dependence in the network, and trade behavior is restricted by other nodes, so China has not yet become the "spinner" of the global advanced manufacturing trade network; 4) Factors such as industrial added value and geographical proximity have statistically significant effects on global advanced manufacturing trade.
With the new round of scientific and technological revolution and the global industrial structure remodeling, it has strong significance to deconstruct the spatial network pattern between China's high-end manufacturing industry and developed countries, judge China's position as a global high-end manufacturing trade network in different periods, and analyze China's high-end manufacturing network. The social network analysis method is used to visualize the topological form and key features of spatial trade associated network in the global advanced manufacturing, and its influencing factors are analyzed through QAP. The results show that: 1) The global high-end manufacturing trade network presents the characteristics of a typical overall trade network structure with high network density and reciprocity, close contact and good interoperability, and frequent trade activities; 2) The weighted directional intensity measurement of the whole network indicates that China presents more frequent trade activities in the trade network and gradually enters the forefront of the spatial pattern; 3) Individual network structure hole analysis shows that China still shows stronger dependence in the network, and trade behavior is restricted by other nodes, so China has not yet become the "spinner" of the global advanced manufacturing trade network; 4) Factors such as industrial added value and geographical proximity have statistically significant effects on global advanced manufacturing trade.
引文
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[12]Serrano M A,Boguna M.Topology of the world trade web[J].Physical Review E Statistical Nonlinear&Soft Matter Physics2003(68):634-646.
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(1)根据OECD认定的25个发达国家,分别为澳大利亚、奥地利、比利时、加拿大、中国、丹麦、芬兰、法国、德国、希腊、冰岛、爱尔兰、意大利、日本、卢森堡、荷兰、新西兰、挪威、葡萄牙、韩国、新加坡、西班牙、瑞士、瑞典、英国、美国。
[2]段文奇,刘宝全,季建华.国际贸易网络拓扑结构的演化[J].系统工程理论与实践,2008(10):71-81.
[3]Fagiolo G,Reyes J,Schiavo S.On the topological properties of the world trade web:A weighted network analysis[J].Physics AStatistical Mechanics&Its Applications,2008(387):3 868-3 873.
[4]Barigozzi M,Fagiolo G,Garlaschelli D.Multinetwork of international trade:a commodity-specific analysis[J].Physical Review E Statistical Nonlinear&Soft Matter Physics,2010,81(4Pt 2):046 104.
[5]Nicholas G.The Case for Regional Policies[J].Scottish Journal of Political Economy,2013,60:481-491.
[6]陈银飞.2000-2009年世界贸易格局的社会网络分析[J].国际贸易问题,2011(11):31-41.
[7]王开,靳玉英.全球FTA网络形成机制研究[J].财贸经济,2013(9):103-111.
[8]辛娜,袁红林.全球价值链嵌入与全球高端制造业网络地位:基于增加值贸易视角[J].改革,2019(3):61-71.
[9]罗仕龙,龚凯,邢欣,等.基于社会网络分析法的国际贸易网络结构及演化研究[J].中国管理科学,2016(12):698-702.
[10]许和连,孙天阳,成丽红.“一带一路”高端制造业贸易格局及影响因素研究[J].财贸经济,2015(12):74-87.
[11]赵国钦,万方.世界贸易网络演化及其解释——基于网络分析方法[J].宏观经济研究,2016(4):151-157.
[12]Serrano M A,Boguna M.Topology of the world trade web[J].Physical Review E Statistical Nonlinear&Soft Matter Physics2003(68):634-646.
[13]Newman M,Girvan M.Finding and evaluating community structure in networks[J].Physical Review,2004,69(2):26113.
[14]Freeman L C.A set of measures of centrality based on betweenness[J].Sociometry,1977,40(1):35-41.
(1)根据OECD认定的25个发达国家,分别为澳大利亚、奥地利、比利时、加拿大、中国、丹麦、芬兰、法国、德国、希腊、冰岛、爱尔兰、意大利、日本、卢森堡、荷兰、新西兰、挪威、葡萄牙、韩国、新加坡、西班牙、瑞士、瑞典、英国、美国。