We analyze the multilayer architecture of the global input-output network using sectoral trade data (WIOD, 2016 release). With a focus on the mesoscale structure and related properties, our multilayer analysis takes into consideration the splitting into industry-based layers in order to catch more peculiar relationships between countries that cannot be detected from the analysis of the single-layer aggregated network. We can identify several large international communities in which some countries trade more intensively in some specific layers. However, interestingly, our results show that these clusters can restructure and evolve over time. In general, not only their internal composition changes, but the centrality rankings of the members inside are also reordered, industries from some countries diminishing their role and others from other countries growing importance. These changes in the large international clusters may reflect the outcomes and the dynamics of cooperation, partner selection and competition among industries and among countries in the global input-output network.

Bartesaghi, P., Clemente, G., Grassi, R., Luu, D. (2022). The multilayer architecture of the global input-output network and its properties. JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION, 204(December 2022), 304-341 [10.1016/j.jebo.2022.10.029].

The multilayer architecture of the global input-output network and its properties

Bartesaghi, Paolo
;
Grassi, Rosanna
;
2022

Abstract

We analyze the multilayer architecture of the global input-output network using sectoral trade data (WIOD, 2016 release). With a focus on the mesoscale structure and related properties, our multilayer analysis takes into consideration the splitting into industry-based layers in order to catch more peculiar relationships between countries that cannot be detected from the analysis of the single-layer aggregated network. We can identify several large international communities in which some countries trade more intensively in some specific layers. However, interestingly, our results show that these clusters can restructure and evolve over time. In general, not only their internal composition changes, but the centrality rankings of the members inside are also reordered, industries from some countries diminishing their role and others from other countries growing importance. These changes in the large international clusters may reflect the outcomes and the dynamics of cooperation, partner selection and competition among industries and among countries in the global input-output network.
Articolo in rivista - Articolo scientifico
Global trade; Input-output linkages; International trade clusters; Layer-layer interdependencies; Mesoscale structure; Multilayer architecture;
English
29-ott-2022
2022
204
December 2022
304
341
none
Bartesaghi, P., Clemente, G., Grassi, R., Luu, D. (2022). The multilayer architecture of the global input-output network and its properties. JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION, 204(December 2022), 304-341 [10.1016/j.jebo.2022.10.029].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/395890
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