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The structure of economic connections between industries: non-scaling behaviour

Author

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  • Camila C.S. Caiado
  • Paul Ormerod

Abstract

There is considerable evidence of the existence of scaling behaviour (power law relationships) in a number of aspects of economic activity. Here, we examine the evidence on the connections between different industrial sectors, in terms of the value of output which each industry sells to each of the others, and the value of output which the others sell to it. Information on these connections between industries is available in the input-output tables in the national economic accounts. We analyse a database in which activity in the UK economy is disaggregated into 123 separate industries. We find that although the statistical distributions of the connections are highly non-Gaussian, there are marked departures from scaling behaviour, whether in the distribution of the connections from each individual industry to all the others, or in the distribution of connections from all industries into each individual one.

Suggested Citation

  • Camila C.S. Caiado & Paul Ormerod, 2012. "The structure of economic connections between industries: non-scaling behaviour," International Journal of Complexity in Leadership and Management, Inderscience Enterprises Ltd, vol. 2(1/2), pages 39-51.
  • Handle: RePEc:ids:ijclma:v:2:y:2012:i:1/2:p:39-51
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    References listed on IDEAS

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    1. Konno, Tomohiko, 2008. "Network Structure of Japanese Firms Hierarchy and Degree Correlation: Analysis from 800,000 Firms," Economics Discussion Papers 2008-39, Kiel Institute for the World Economy (IfW Kiel).
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    3. Cook, William & Ormerod, Paul, 2003. "Power law distribution of the frequency of demises of US firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 207-212.
    4. Takaaki Ohnishi & Hideki Takayasu & Misako Takayasu, 2010. "Network motifs in an inter-firm network," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(2), pages 171-180, December.
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