Discovering preferential patterns in sectoral trade networks
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Author(s)
Cingolani, I
Piccardi, C
Tajoli, L
Type
Journal Article
Abstract
We analyze the patterns of import/export bilateral relations, with the aim of assessing the relevance and shape of preferentiality in countries trade decisions. Preferentiality here is defined as the tendency to concentrate trade on one or few partners. With this purpose, we adopt a systemic approach through the use of the tools of complex network analysis. In particular, we apply a pattern detection approach based on community and pseudocommunity analysis, in order to highlight the groups of countries within which most of members trade occur. The method is applied to two intra-industry trade networks consisting of 221 countries, relative to the low-tech Textiles and Textile Articles and the high-tech Electronics sectors for the year 2006, to look at the structure of world trade before the start of the international financial crisis. It turns out that the two networks display some similarities and some differences in preferential trade patterns: they both include few significant communities that define narrow sets of countries trading with each other as preferential destinations markets or supply sources, and they are characterized by the presence of similar hierarchical structures, led by the largest economies. But there are also distinctive features due to the characteristics of the industries examined, in which the organization of production and the destination markets are different. Overall, the extent of preferentiality and partner selection at the sector level confirm the relevance of international trade costs still today, inducing countries to seek the highest efficiency in their trade patterns.
Date Issued
2015-10-20
Date Acceptance
2015-10-02
Citation
PLOS One, 2015, 10 (10)
ISSN
1932-6203
Publisher
Public Library of Science
Journal / Book Title
PLOS One
Volume
10
Issue
10
Copyright Statement
© 2015 Cingolani et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
credited.
License URL
Identifier
PII: PONE-D-15-31302
Subjects
General Science & Technology
MD Multidisciplinary
Publication Status
Published
Article Number
e0140951