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Betweenness centrality for similarity-weight network and its application to measuring industrial sectors’ pivotability on the global value chain

Lizhi Xing, Xianlei Dong, Jun Guan and Xiaoyong Qiao

Physica A: Statistical Mechanics and its Applications, 2019, vol. 516, issue C, 19-36

Abstract: This paper focuses on measuring the globally and nationally economic system’s connectedness and industrial sector’s function on the Global Value Chain (GVC), as reinforcements to the present studies on international trade. Firstly, we reconsidered the length-related and position-related measures in literatures about vertical specialization from the perspective of econophysics. Secondly, we redefined the inter-country and inter-sector propagating process of intermediate goods and proposed the concept of Strongest Relevance Path Length (SRPL) based on Revised Floyd–Warshall Algorithm (RFWA), which is the basis of new measurement. Thirdly, we introduced Average and Maximum Strongest Relevance Degree (ASRD and MSRD) to measure the connectedness and compactness of network respectively. Fourthly, enlightened by betweenness centrality, we introduced SRPL-based index to measure industrial sectors’ Pivotability in transferring intermediate goods Fifthly, these indices were applied to the empirical analysis of the economic system by physical statistics. Finally, through cascading failure analysis, we found that both ASRD and MSRD reflecting the overall performance of propagating process of intermediate goods are vulnerable to those sectors with high pivotability.

Keywords: Global value chain; Inter-country input–output table; Floyd–Warshall algorithm; Betweenness centrality; Pivotability (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:516:y:2019:i:c:p:19-36

DOI: 10.1016/j.physa.2018.10.004

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