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ARE SANCTIONS FOR LOSERS? A NETWORK STUDY OF TRADE SANCTIONS

A network study of trade sanctions
Authors: Telarico, Fabio Ashtar;

ARE SANCTIONS FOR LOSERS? A NETWORK STUDY OF TRADE SANCTIONS

Abstract

<p>Studies built on dependency and world-system theory using network approaches have showed that international trade is structured into clusters of ‘core’ and ‘peripheral’ countries performing distinct functions. However, few have used these methods to investigate how sanctions affect the position of the countries involved in the capitalist world-economy. Yet, this topic has acquired pressing relevance due to the emergence of economic warfare as a key geopolitical weapon since the 1950s. And even more so in light of the preeminent role that sanctions have played in the US and their allies’ response to the Russian-Ukrainian war. Applying several clustering techniques designed for complex and temporal networks, this paper shows that a shift in the pattern of commerce away from sanctioning countries and towards neutral/friendly ones. Additionally, there are suggestions that these shifts may lead to the creation of an alternative ‘core’ that interacts with the world-economy’s periphery bypassing traditional ‘core’ countries such as EU member States and the US.</p>

Keywords

FOS: Computer and information sciences, Blockmodeling, General Economics (econ.GN), Dynamic networks, [INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI], International trade, Iran, Russia, Methodology (stat.ME), FOS: Economics and business, World-system theory, Sanctions, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, Statistics - Methodology, Economics - General Economics

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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