The similarity of global value chains: A network-based measure

被引:8
作者
Zhu, Zhen [1 ,2 ]
Morrison, Greg [3 ]
Puliga, Michelangelo [1 ,4 ]
Chessa, Alessandro [1 ,4 ]
Riccaboni, Massimo [1 ,5 ]
机构
[1] IMT Sch Adv Studies Lucca, I-55100 Lucca, Italy
[2] Univ Greenwich, Dept Int Business & Econ, London SE10 9LS, England
[3] Univ Houston, Dept Phys, Houston, TX 77204 USA
[4] Linkalab, Cagliari, Italy
[5] Katholieke Univ Leuven, Dept Managerial Econ Strategy & Innovat, B-3000 Leuven, Belgium
关键词
networks; node similarity; input-output analysis; global value chains; vertical specialization; international trade;
D O I
10.1017/nws.2018.8
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
International trade has been increasingly organized in the form of global value chains (GVCs). In this paper, we provide a new method for comparing GVCs across countries and over time. First, we use the World Input-Output Database (WIOD) to construct both the upstream and the downstream global value networks. Second, we introduce a network-based measure of node similarity to compare the GVCs between any pair of countries for each sector and each year available in the WIOD. Our network-based similarity is a better measure for node comparison than the existing ones because it takes into account all the direct and indirect relationships between the country-sector pairs, is applicable to both directed and weighted networks with self-loops, and takes into account externally defined node attributes. As a result, our measure of similarity reveals the most intensive interactions among the GVCs across countries and over time. From 1995 to 2011, the average similarity between sectors and countries have clear increasing trends, which are temporarily interrupted by the recent economic crisis. This measure of the similarity of GVCs provides quantitative answers to important questions about dependency, sustainability, risk, and competition in the global production system.
引用
收藏
页码:607 / 632
页数:26
相关论文
共 55 条
  • [31] Vertex similarity in networks
    Leicht, EA
    Holme, P
    Newman, MEJ
    [J]. PHYSICAL REVIEW E, 2006, 73 (02)
  • [32] QUANTITATIVE INPUT AND OUTPUT RELATIONS IN THE ECONOMIC SYSTEM OF THE UNITED STATES
    Leontief, Wassily W.
    [J]. REVIEW OF ECONOMIC STATISTICS, 1936, 18 (03): : 105 - 125
  • [33] Lerner J, 2005, LECT NOTES COMPUT SC, V3418, P216
  • [34] Lloyd P. J, 2004, EMPIRICAL METHODS IN, P21
  • [35] HOW GLOBAL ARE GLOBAL VALUE CHAINS? A NEW APPROACH TO MEASURE INTERNATIONAL FRAGMENTATION
    Los, Bart
    Timmer, Marcel P.
    de Vries, Gaaitzen J.
    [J]. JOURNAL OF REGIONAL SCIENCE, 2015, 55 (01) : 66 - 92
  • [36] Link prediction in complex networks: A survey
    Lue, Linyuan
    Zhou, Tao
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2011, 390 (06) : 1150 - 1170
  • [37] Similarity index based on local paths for link prediction of complex networks
    Lue, Linyuan
    Jin, Ci-Hang
    Zhou, Tao
    [J]. PHYSICAL REVIEW E, 2009, 80 (04)
  • [38] New Directions in Globalization Indices
    Martens, Pim
    Caselli, Marco
    De Lombaerde, Philippe
    Figge, Lukas
    Scholte, Jan Aart
    [J]. GLOBALIZATIONS, 2015, 12 (02) : 217 - 228
  • [39] Miller R.E., 2009, INPUT OUTPUT ANAL FD
  • [40] Discovering Communities through Friendship
    Morrison, Greg
    Mahadevan, L.
    [J]. PLOS ONE, 2012, 7 (07):