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基于贸易增加值分解框架,结合社会网络分析法,文章构建了全球制造业增加值贸易网络,探究了其整体结构及动态演化趋势,并实证检验了网络特征对全球价值链(GVC)分工的影响。研究发现:(1)全球贸易网络聚集度逐渐增强,制造业及高技术制造业的贸易重心逐渐向东亚转移。(2)贸易网络特征能够显著提升GVC分工水平。具体来看,网络出度中心度对GVC分工的提升效应在中低技术制造业和发展中国家更强,主要对前向参与GVC分工产生影响;而网络入度中心度的提升效应在高技术制造业和发达国家更强,主要对后向参与GVC分工产生影响;网络联系强度在发达国家作用更强;网络异质性在中低技术制造业、发展中国家更明显;金融危机爆发显著削弱了网络联系强度对GVC分工的提升效应。(3)贸易网络特征主要通过竞争效应、产业关联效应和规模经济效应三个渠道来促进GVC分工水平提升。文章为中国扩大高水平对外开放,实现价值链跃升提供了实证支持和政策参考。
Abstract:Based on the trade value-added decomposition framework and the Social Network Analysis(SNA), this paper systematically constructs a comprehensive global manufacturing value-added trade network. We further explore its structure and dynamic evolution trends, empirically assessing the influence of network characteristics on the participation of Global Value Chain(GVC). We find that, firstly, there has been a noticeable trend towards the concentration of trade networks, with the center of manufacturing and high-tech manufacturing network gradually moving toward East Asia.Secondly, the attributes of trade networks have a substantial influence on the extent of GVC participation. In particular, the impact of network outdegree centrality exhibits a more pronounced enhancing effect on GVC in low-tech, medium-tech manufacturing and developing countries, which predominantly affects GVC forward participation. However, the impact of network in-degree centrality is stronger in high-tech manufacturing and developed countries, which primarily affects GVC backward participation. The network strength exerts a stronger influence in developed countries,while network heterogeneity is more obvious in non-high-tech manufacturing and developing countries. Furthermore, after the financial crisis outbreak, there is a notable weakening effect of network strength on GVC participation. Thirdly, the attributes of trade networks facilitate involvement in GVC participation mainly through three channels as competition effect, industrial linkage effect and scale effect. This article provides empirical support and policy insights to guide China′s efforts in expanding high-level openness and achieving advancements in GVC.
[1] Acemoglu D,Akcigit U,Kerr W.Networks and the macroeconomy:an empirical exploration[J].NBER Macroeconomics Annual,2016,30(1):273-335.
[2] Bernard A B,Moxnes A,Saito Y U.Production networks,geography,and firm performance[J].Journal of Political Economy,2019,127(2):639-688.
[3] Burt R S.Structural holes[M].Cambridge,MA:Harvard University Press,1992.
[4] Dachs B,Kinkel S,J?ger A.Bringing it all back home?Backshoring of manufacturing activities and the adoption of Industry 4.0 technologies[J].Journal of World Business,2019,54(6):101017.
[5] De Benedictis L,Tajoli L.The world trade network[J].The World Economy,2011,34(8):1417-1454.
[6] Fagiolo G,Reyes J,Schiavo S.The evolution of the world trade web:a weighted-network analysis[J].Journal of Evolutionary Economics,2010,20(4):479-514.
[7] Fally T,Hillberry R.A Coasian model of international production chains[J].Journal of International Economics,2018,114:299-315.
[8] Freeman L C,Roeder D,Mulholland R R.Centrality in social networks:II.Experimental results[J].Social networks,1979,2(2):119-141.
[9] Gancia G,Ponzetto G A M,Ventura J.A theory of economic unions[J].Journal of Monetary Economics,2020,109:107-127.
[10] Garlaschelli D,Loffredo M I.Structure and evolution of the world trade network[J].Physica A:Statistical Mechanics and its Applications,2005,355(1):138-144.
[11] Kano L,Tsang E W K,Yeung H W.Global value chains:A review of the multi-disciplinary literature[J].Journal of International Business Studies,2020,51(4):577-622.
[12] Koopman R,Powers W,WANG Z,et al.Give credit where credit is due:Tracing value added in global production chains[R].National Bureau of Economic Research,2010,No.16426.
[13] Koopman R,WANG Z,WEI S J.Tracing value-added and double counting in gross exports[J].American Economic Review,2014,104(2):459-494.
[14] Robert R C,Noguera G.A portrait of trade in value-added over four decades[J].Review of Economics and Statistics,2017,99(5):896-911.
[15] Serrano M A,Boguňá M.Topology of the world trade web[J].Physical Review E,2003,68(1):015101.
[16] Vasco M,Tahbaz-Salehi A.Production networks:A primer[J].Annual Review of Economics,2019,11:635-663.
[17] WANG Z,WEI S J,ZHU K.Quantifying international production sharing at the bilateral and sector levels[R].National Bureau of Economic Research,No.19677,2013.
[18] WANG Z,WEI S J,YU X,et al.Characterizing global value chains:Production length and upstreamness[R].National Bureau of Economic Research,No.23261,2017a.
[19] WANG Z,WEI S J,YU X,et al.Measures of participation in global value chains and global business cycles[R].National Bureau of Economic Research,No.23222,2017b.
[20] 成丽红,孙天阳.战略性产业贸易网络的结构特征及演化模式[J].科学学研究,2021,39(12):2140-2148.
[21] 邓慧慧,徐昊,王强.数字经济与全球制造业增加值贸易网络演进[J].统计研究,2023,40(5):3-19.
[22] 高鹏,岳书敬.全球价值链嵌入是否降低了中国产业部门隐含碳——兼论产业数字化的调节效应[J].国际贸易问题,2022(7):53-67.
[23] 耿伟,吴雪洁,叶品良.数字服务贸易网络对出口国内增加值的影响——来自跨国数据的经验证据[J].国际贸易问题,2022(12):90-110.
[24] 贺胜兵,许宸昊,周华蓉.“一带一路”工业机器人贸易网络特征及演化机制 [J].中国软科学,2023(6):43-55.
[25] 黄海刚,毋偲奇.高等教育在全球价值链攀升中的贡献研究[J].复旦教育论坛,2022,20(3):20-27.
[26] 黄祖南,郑正喜.复杂产业网络度中心性研究 [J].统计研究,2021,38(5):147-160.
[27] 江艇.因果推断经验研究中的中介效应与调节效应[J].中国工业经济,2022(5):100-120.
[28] 江小涓,孟丽君.内循环为主、外循环赋能与更高水平双循环——国际经验与中国实践 [J].管理世界,2021,37 (1):1-19.
[29] 刘景卿,于佳雯,车维汉.FDI流动与全球价值链分工变化——基于社会网络分析的视角[J].财经研究,2019,45(3):100-113.
[30] 刘林青,闫小斐,杨理斯等.国际贸易依赖网络的演化及内生机制研究[J].中国工业经济,2021(2):98-116.
[31] 刘梦,戴翔.经济增长中“净出口”作用如何被低估?——基于传统方法的修正、再测算与比较研究[J].南开经济研究,2020(2):49-67.
[32] 刘敏,薛伟贤,陈莎.“一带一路”贸易网络能否促进各国全球价值链地位提升[J].管理评论,2022,34(12):49-59.
[33] 吕越,毛诗丝.欧盟参与全球价值链分工的现状及决定因素分析[J].欧洲研究,2020,38(2):81-103;7.
[34] 吕越,尉亚宁.全球价值链下的企业贸易网络和出口国内附加值[J].世界经济,2020,43(12):50-75.
[35] 吕越,谷玮,尉亚宁等.人工智能与全球价值链网络深化[J].数量经济技术经济研究,2023,40(1):128-151.
[36] 吕延方,方若楠,王冬.全球数字服务贸易网络的拓扑结构特征及影响机制 [J].数量经济技术经济研究,2021,38 (10):128-147.
[37] 马淑琴,童银节,邵宇佳.中间品贸易、最终品贸易与国际经济周期联动性研究——来自世界与中国的经验证据[J].国际经贸探索,2019,35(7):4-20.
[38] 马述忠,任婉婉,吴国杰.一国农产品贸易网络特征及其对全球价值链分工的影响——基于社会网络分析视角[J].管理世界,2016(3):60-72.
[39] 苏冬蔚,陈纯纯,许振国,等.商业银行社会网络与微型金融可持续发展[J].经济研究,2017,52(2):140-155.
[40] 苏庆义,高凌云.全球价值链分工位置及其演进规律[J].统计研究,2015,32(12):38-45.
[41] 汪莉,邵雨卉,汪亚楠.网络结构与银行效率:基于时变“银行—股东”网络的研究[J].经济研究,2021,56(12):60-76.
[42] 王直,魏尚进,祝坤福.总贸易核算法:官方贸易统计与全球价值链的度量[J].中国社会科学,2015(9):108-127;205-206.
[43] 吴迪.全球价值链重构背景下我国实现高水平对外开放的战略选择[J].经济学家,2023(2):15-24.
[44] 许朝凯,刘宏曼.国际贸易网络演化与中国出口韧性提升[J].世界经济研究,2023(6):100-114;136.
[45] 许和连,成丽红,孙天阳.离岸服务外包网络与服务业全球价值链提升[J].世界经济,2018,41(6):77-101.
[46] 杨蕙馨,孙芹,王海花.知识网络动态性对高校协同创新绩效的影响研究:合作网络的调节作用[J].经济与管理研究,2022,43(10):68-80.
[47] 钟祖昌,余佩璇,肖宵等.高技术产品出口贸易网络构建对一国或地区全球价值链分工位置的影响研究:基于社会网络分析的视角[J].管理评论,2022,34(3):127-140.
(1)由于全球价值链分工指数和差异性指数存在趋近于0的情况,本文按照ln(1+变量值)的方法处理。
(2)限于篇幅,稳健性检验的实证结果未在文中展示,备索。
基本信息:
DOI:10.13516/j.cnki.wes.2024.08.003
中图分类号:F414
引用信息:
[1]石建勋,陈亚楠.增加值视角下全球制造业贸易网络特征与价值链分工水平提升[J].世界经济研究,2024,No.366(08):44-59+136.DOI:10.13516/j.cnki.wes.2024.08.003.
基金信息:
国家社会科学基金重大专项课题项目资助(项目编号:21VGQ005); 国家自然科学基金项目“基于双重价值链视角的中国高技术产业竞争优势重构研究”(项目编号:71972063)