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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

Empirical counter-cumulative distribution functions of in-strength, out-strength, and total-strength for selected years.For the selected years 1995, 2003, and 2011, the first row has the in-strength distributions while the second row and the third row have the out-strength and total-strength distributions respectively. The observed data are in black circles while the green curve is the fitted log-normal distribution.
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pone.0134025.g007: Empirical counter-cumulative distribution functions of in-strength, out-strength, and total-strength for selected years.For the selected years 1995, 2003, and 2011, the first row has the in-strength distributions while the second row and the third row have the out-strength and total-strength distributions respectively. The observed data are in black circles while the green curve is the fitted log-normal distribution.

Mentions: We further take into account the edge weights and examine the strength distributions of the WION. Fig 7 shows the in-strength, out-strength, and total-strength distributions for the years 1995, 2003, and 2011. We perform Gabaix-Ibragimov test [35, 36] to see if the tails of the distributions are Pareto but find no significant power-law tails. Moreover, like the previous studies at the national level [12], the strength distributions can be well approximated by the log-normal distributions.


World Input-Output Network.

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

Empirical counter-cumulative distribution functions of in-strength, out-strength, and total-strength for selected years.For the selected years 1995, 2003, and 2011, the first row has the in-strength distributions while the second row and the third row have the out-strength and total-strength distributions respectively. The observed data are in black circles while the green curve is the fitted log-normal distribution.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0134025.g007: Empirical counter-cumulative distribution functions of in-strength, out-strength, and total-strength for selected years.For the selected years 1995, 2003, and 2011, the first row has the in-strength distributions while the second row and the third row have the out-strength and total-strength distributions respectively. The observed data are in black circles while the green curve is the fitted log-normal distribution.
Mentions: We further take into account the edge weights and examine the strength distributions of the WION. Fig 7 shows the in-strength, out-strength, and total-strength distributions for the years 1995, 2003, and 2011. We perform Gabaix-Ibragimov test [35, 36] to see if the tails of the distributions are Pareto but find no significant power-law tails. Moreover, like the previous studies at the national level [12], the strength distributions can be well approximated by the log-normal distributions.

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