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Industrial Clustering and Sectoral Growth: a Network Dynamics Approach

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  • João Lopes

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Abstract

Cluster analysis has been widely used in an Input-Output framework, with the main objective of uncover the structure of production, in order to better identify which sectors are strongly connected with each other and choose the key sectors of a national or regional economy. There are many empirical studies determining potential clusters from interindustry flows directly, or from their corresponding technical (demand) or market (supply) coefficients, most of them applying multivariate statistical techniques. In this paper we follow a different strategy. Since it is expected that strongly (interindustry) connected sectors share a similar growth and development path, we will try to uncover clusters from sectoral dynamics, by applying a stochastic geometry technique, based on the yearly distances of industry outputs. An application is made, comparing these growth based cluster templates with interindustry based ones, using Portuguese input-output data. Identifying regional clusters and its dynamics can be a useful extension of the methods proposed in this paper.

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Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa11p637.

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Date of creation: Sep 2011
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Handle: RePEc:wiw:wiwrsa:ersa11p637

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  1. Sedef Akg�Ng�R & Nese Kumral & Aykut Lenger, 2003. "National Industry Clusters and Regional Specializations in Turkey," European Planning Studies, Taylor & Francis Journals, vol. 11(6), pages 647-669, September.
  2. R. Vilela Mendes & Tanya Ara\'{u}jo & Francisco Lou\c{c}\~{a}, 2002. "Reconstructing an economic space from a market metric," Papers cond-mat/0211108, arXiv.org.
  3. Frederic Rychen & Jean-Benoit Zimmermann, 2008. "Clusters in the Global Knowledge-based Economy: Knowledge Gatekeepers and Temporary Proximity," Regional Studies, Taylor & Francis Journals, vol. 42(6), pages 767-776.
  4. Fidel Aroche-Reyes, 2003. "A qualitative input-output method to find basic economic structures," Economics of Governance, Springer, vol. 82(4), pages 581-590, November.
  5. Sara Cruz & Aurora Teixeira, 2010. "The Evolution of the Cluster Literature: Shedding Light on the Regional Studies-Regional Science Debate," Regional Studies, Taylor & Francis Journals, vol. 44(9), pages 1263-1288.
  6. Barbara Diaz & Laura Moniche & Antonio Morillas, 2006. "A Fuzzy clustering approach to the key sectors of the Spanish economy," Economic Systems Research, Taylor & Francis Journals, vol. 18(3), pages 299-318.
  7. Edward Feser & Edward Bergman, 2000. "National Industry Cluster Templates: A Framework for Applied Regional Cluster Analysis," Regional Studies, Taylor & Francis Journals, vol. 34(1), pages 1-19.
  8. Alex Hoen, 2002. "Identifying Linkages with a Cluster-based Methodology," Economic Systems Research, Taylor & Francis Journals, vol. 14(2), pages 131-146.
  9. Vilela Mendes, R. & Araújo, Tanya & Louçã, Francisco, 2003. "Reconstructing an economic space from a market metric," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 635-650.
  10. Christina Kelton & Margaret Pasquale & Robert Rebelein, 2007. "Using the North American Industry Classification System (NAICS) to Identify National Industry Cluster Templates for Applied Regional Analysis," Regional Studies, Taylor & Francis Journals, vol. 42(3), pages 305-321.
  11. Antonio Morillas & Barbara Diaz, 2008. "Key Sectors, Industrial Clustering and Multivariate Outliers," Economic Systems Research, Taylor & Francis Journals, vol. 20(1), pages 57-73.
  12. Mirko Titze & Matthias Brachert & Alexander Kubis, 2008. "The Identification of Regional Industrial Clusters Using Qualitative Input-Output Analysis," IWH Discussion Papers 13, Halle Institute for Economic Research.
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