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A Fuzzy clustering approach to the key sectors of the Spanish economy

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  • Barbara Diaz
  • Laura Moniche
  • Antonio Morillas

Abstract

The search for key sectors in an economy has been and still is one of the more recurrent themes in input-output analysis. When using clustering techniques, sectors can only belong to a group, having a particular performance. But, actually, the same sector could be important from different perspectives at the same time, to a different degree. So, a fuzzy clustering approach is needed. In this work we propose a multidimensional approach to classify the productive sectors of the Spanish input-output table for 1995, based on three groups of variables: those related to their productive integration, others measuring their specific weight in the economy and finally some showing their economic dynamic. We also incorporate into the analysis the technological level, which being a categorical variable presents special methodological problems. All these questions are tackled applying a robust and fuzzy clustering analysis, which gives as a result a classification of sectors illustrating the role that each one plays in the Spanish economy.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Economic Systems Research.

Volume (Year): 18 (2006)
Issue (Month): 3 ()
Pages: 299-318

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Handle: RePEc:taf:ecsysr:v:18:y:2006:i:3:p:299-318

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Related research

Keywords: Key sectors; fuzzy clustering; input-output analysis; Spanish economy;

References

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  1. 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.
  2. Erik Dietzenbacher, 2005. "More on multipliers," Journal of Regional Science, Wiley Blackwell, vol. 45(2), pages 421-426.
  3. Alex Hoen, 2002. "Identifying Linkages with a Cluster-based Methodology," Economic Systems Research, Taylor & Francis Journals, vol. 14(2), pages 131-146.
  4. Erik Dietzenbacher & Bart Los, 2002. "Externalities of R&D Expenditures," Economic Systems Research, Taylor & Francis Journals, vol. 14(4), pages 407-425.
  5. Johan Hauknes, . "Norwegian Input-Output Clusters and Innovation Patterns," STEP Report series 199815, The STEP Group, Studies in technology, innovation and economic policy.
  6. Chokri Dridi & Geoffrey J.D. Hewings, 2003. "Sectors associations and similarities in input-output systems: An application of dual scaling and fuzzy logic to Canada and the United States," The Annals of Regional Science, Springer, vol. 37(4), pages 629-656, December.
  7. Dietzenbacher, Erik, 1992. "The measurement of interindustry linkages : Key sectors in the Netherlands," Economic Modelling, Elsevier, vol. 9(4), pages 419-437, October.
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Citations

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Cited by:
  1. Matías Piaggio & Vicent Alcántara Escolano & Emilio Padilla, 2012. "Economic structure and key sectors analysis of greenhouse gas emissions in Uruguay," Working Papers wpdea1204, Department of Applied Economics at Universitat Autonoma of Barcelona.
  2. García Muñiz, Ana Salomé, 2013. "Input–output research in structural equivalence: Extracting paths and similarities," Economic Modelling, Elsevier, vol. 31(C), pages 796-803.
  3. João C. Lopes & Tanya Araújo & João Dias & João F. Amaral, 2010. "National industry cluster templates and the structure of industry output dynamics: a stochastic geometry approach," Working Papers Department of Economics 2010/20, ISEG - School of Economics and Management, Department of Economics, University of Lisbon.
  4. João Lopes, 2011. "Industrial Clustering and Sectoral Growth: a Network Dynamics Approach," ERSA conference papers ersa11p637, European Regional Science Association.

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