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World Input-Output Network.

Cerina F, Zhu Z, Chessa A, Riccaboni M - PLoS ONE (2015)

Bottom Line: At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions.Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages.We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

View Article: PubMed Central - PubMed

Affiliation: Linkalab, Complex Systems Computational Laboratory, Cagliari, Italy; Department of Physics, Università degli Studi di Cagliari, Cagliari, Italy.

ABSTRACT
Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the global multi-regional input-output (GMRIO) tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION) and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

No MeSH data available.


Related in: MedlinePlus

Community detection and community core detection results in 2003.The economies are arranged by rows and the industries are arranged by columns. Each color represents a community detected, except that the black color indicates the isolated nodes with only self-loop. Within each community, the top 3 core economy-industry pairs are identified. The first place is with thick and solid border. The second place is with thick and dashed border. The third place is with border and texture.
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pone.0134025.g009: Community detection and community core detection results in 2003.The economies are arranged by rows and the industries are arranged by columns. Each color represents a community detected, except that the black color indicates the isolated nodes with only self-loop. Within each community, the top 3 core economy-industry pairs are identified. The first place is with thick and solid border. The second place is with thick and dashed border. The third place is with border and texture.

Mentions: Figs 8, 9, and 10 report the community detection results for the selected years 1995, 2003, and 2011, respectively (We perform the community detection for all available years (1995–2011). Results are available upon request.). The 40 countries in the WIOD are arranged by rows while the 35 industries are arranged by columns. Different colors indicate different communities detected. There are two interesting findings in our results. First, most communities were based on a single economy, i.e., the same color often goes through a single row. This echoes one of the features of the WION mentioned in Section 1, i.e., most of the inter-industrial activities are still restricted within the country border. Second, for all the three years selected, we always color the community involving Germany in red and put it on the top. As a result, our algorithm captures a growing Germany-centered input-output community. It is centered on Germany because the community core detection results below show that the cores of this red community are all within Germany. Since the WIOD monetary goods flows are based on undeflated current prices, one possible reason for the emergence of the German community is that the community members may have experienced significantly more inflation and/or exchange rate volatility than other regions in the world. Referring to the World Bank inflation data and the exchange rate data used in the WIOD, we show that this is hardly the case (see S1 Fig).


World Input-Output Network.

Cerina F, Zhu Z, Chessa A, Riccaboni M - PLoS ONE (2015)

Community detection and community core detection results in 2003.The economies are arranged by rows and the industries are arranged by columns. Each color represents a community detected, except that the black color indicates the isolated nodes with only self-loop. Within each community, the top 3 core economy-industry pairs are identified. The first place is with thick and solid border. The second place is with thick and dashed border. The third place is with border and texture.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4519177&req=5

pone.0134025.g009: Community detection and community core detection results in 2003.The economies are arranged by rows and the industries are arranged by columns. Each color represents a community detected, except that the black color indicates the isolated nodes with only self-loop. Within each community, the top 3 core economy-industry pairs are identified. The first place is with thick and solid border. The second place is with thick and dashed border. The third place is with border and texture.
Mentions: Figs 8, 9, and 10 report the community detection results for the selected years 1995, 2003, and 2011, respectively (We perform the community detection for all available years (1995–2011). Results are available upon request.). The 40 countries in the WIOD are arranged by rows while the 35 industries are arranged by columns. Different colors indicate different communities detected. There are two interesting findings in our results. First, most communities were based on a single economy, i.e., the same color often goes through a single row. This echoes one of the features of the WION mentioned in Section 1, i.e., most of the inter-industrial activities are still restricted within the country border. Second, for all the three years selected, we always color the community involving Germany in red and put it on the top. As a result, our algorithm captures a growing Germany-centered input-output community. It is centered on Germany because the community core detection results below show that the cores of this red community are all within Germany. Since the WIOD monetary goods flows are based on undeflated current prices, one possible reason for the emergence of the German community is that the community members may have experienced significantly more inflation and/or exchange rate volatility than other regions in the world. Referring to the World Bank inflation data and the exchange rate data used in the WIOD, we show that this is hardly the case (see S1 Fig).

Bottom Line: At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions.Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages.We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

View Article: PubMed Central - PubMed

Affiliation: Linkalab, Complex Systems Computational Laboratory, Cagliari, Italy; Department of Physics, Università degli Studi di Cagliari, Cagliari, Italy.

ABSTRACT
Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD) is one of the first efforts to construct the global multi-regional input-output (GMRIO) tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION) and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

No MeSH data available.


Related in: MedlinePlus