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Which Sectors of a Modern Economy are most Central?

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  • Florian Blöchl
  • Fabian J. Theis
  • Fernando Vega-Redondo
  • Eric O'N. Fisher

Abstract

We analyze input-output matrices for a wide set of countries as weighted directed networks. These graphs contain only 47 nodes, but they are almost fully connected and many have nodes with strong self-loops. We apply two measures: random walk centrality and one based on count-betweenness. Our findings are intuitive. For example, in Luxembourg the most central sector is “Finance and Insurance” and the analog in Germany is “Wholesale and Retail Trade” or “Motor Vehicles”, according to the measure. Rankings of sectoral centrality vary by country. Some sectors are often highly central, while others never are. Hierarchical clustering reveals geographical proximity and similar development status.

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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 3175.

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Date of creation: 2010
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Handle: RePEc:ces:ceswps:_3175

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References

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  1. Vega-Redondo,Fernando, 2007. "Complex Social Networks," Cambridge Books, Cambridge University Press, number 9780521674096.
  2. Iori, G. & Masi, G. D. & Precup, O. V. & Gabbi, G. & Caldarelli, G., 2005. "A network analysis of the Italian oversight money market," Working Papers 05/05, Department of Economics, City University London.
  3. C. A. Hidalgo & B. Klinger & A. -L. Barabasi & R. Hausmann, 2007. "The Product Space Conditions the Development of Nations," Papers 0708.2090, arXiv.org.
  4. D. Garlaschelli & M. I. Loffredo, 2004. "Fitness-dependent topological properties of the World Trade Web," Papers cond-mat/0403051, arXiv.org, revised Oct 2004.
  5. Garlaschelli, Diego & Loffredo, Maria I., 2005. "Structure and evolution of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 138-144.
  6. Grassi, Rosanna, 2010. "Vertex centrality as a measure of information flow in Italian Corporate Board Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2455-2464.
  7. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906, September.
  8. Giorgio Fagiolo & Javier Reyes & Stefano Schiavo, 2008. "The World-Trade Web: Topological Properties, Dynamics, and Evolution," Sciences Po publications 2008/16, Sciences Po.
  9. Vega-Redondo,Fernando, 2007. "Complex Social Networks," Cambridge Books, Cambridge University Press, number 9780521857406.
  10. ten Raa,Thijs, 2006. "The Economics of Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521841795.
  11. Estrada, Ernesto & Higham, Desmond J. & Hatano, Naomichi, 2009. "Communicability betweenness in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 764-774.
  12. D. Garlaschelli & M. I. Loffredo, 2005. "Structure and Evolution of the World Trade Network," Papers physics/0502066, arXiv.org, revised May 2005.
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Cited by:
  1. Baskaran, Thushyanthan & Blöchl, Florian & Brück, Tilman & Theis, Fabian J., 2011. "The Heckscher-Ohlin model and the network structure of international trade," International Review of Economics & Finance, Elsevier, vol. 20(2), pages 135-145, April.

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