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
  • [1] The Network Origins of Aggregate Fluctuations
    Acemoglu, Daron
    Carvalho, Vasco M.
    Ozdaglar, Asuman
    Tahbaz-Salehi, Alireza
    [J]. ECONOMETRICA, 2012, 80 (05) : 1977 - 2016
  • [2] Statistical mechanics of complex networks
    Albert, R
    Barabási, AL
    [J]. REVIEWS OF MODERN PHYSICS, 2002, 74 (01) : 47 - 97
  • [3] Amador J., 2014, J ECON SURV, V30, P278
  • [4] Supply-chain Trade: A Portrait of Global Patterns and Several Testable Hypotheses
    Baldwin, Richard
    Lopez-Gonzalez, Javier
    [J]. WORLD ECONOMY, 2015, 38 (11) : 1682 - 1721
  • [5] Spiders and snakes: Offshoring and agglomeration in the global economy
    Baldwin, Richard
    Venables, Anthony J.
    [J]. JOURNAL OF INTERNATIONAL ECONOMICS, 2013, 90 (02) : 245 - 254
  • [6] Vertex centralities in input-output networks reveal the structure of modern economies
    Bloechl, Florian
    Theis, Fabian J.
    Vega-Redondo, Fernando
    Fisher, Eric O'N
    [J]. PHYSICAL REVIEW E, 2011, 83 (04)
  • [7] A measure of similarity between graph vertices: Applications to synonym extraction and web searching
    Blondel, VD
    Gajardo, A
    Heymans, M
    Senellart, P
    Van Dooren, P
    [J]. SIAM REVIEW, 2004, 46 (04) : 647 - 666
  • [8] Reconstructing a credit network
    Caldarelli, Guido
    Chessa, Alessandro
    Gabrielli, Andrea
    Pammolli, Fabio
    Puliga, Michelangelo
    [J]. NATURE PHYSICS, 2013, 9 (03) : 125 - 126
  • [9] World Input-Output Network
    Cerina, Federica
    Zhu, Zhen
    Chessa, Alessandro
    Riccaboni, Massimo
    [J]. PLOS ONE, 2015, 10 (07):
  • [10] An Elementary Theory of Global Supply Chains
    Costinot, Arnaud
    Vogel, Jonathan
    Wang, Su
    [J]. REVIEW OF ECONOMIC STUDIES, 2013, 80 (01) : 109 - 144