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Cluster Analysis using Microgreographic data

Author

Listed:
  • Federico Pablo-Marti
  • Josep Maria Arauzo-Carod
Abstract
In this paper we try to identify manufacturing and service clusters in Spain, using data from Mercantile Registers of 2006. The proposed methodology partially follows contributions of Duranton and Overman (2005), Brenner (2003 and 2004) and Ellison and Glaser (1997), but departing from them we improve such approaches by several ways. In order to sum up, we can detail our approach and divide it into five stages. Firstly, we divide space into homogeneous cells. Secondly, we create industry specific maps departing from firms' georeferenced data. Thirdly, we create multiple random industry specific maps under two conditions: i) total number of firms at each industry remains constant and ii) total number of firms at each cell remains constant. Fourthly, we compare the observed spatial distribution of firms with random simulations of such distribution and we check if there is some kind of concentration compared to the random distribution. Fifthly, for each industry we map the areas where the concentration of firms is significantly higher than expected. Previous scheme allows us to identify real clusters (of different shapes and sizes) for all range of manufacturing and service activities and to use this information to design public policies related to such industries. Keywords: cluster analysis, geographic data, microeconomics, regional economics.

Suggested Citation

  • Federico Pablo-Marti & Josep Maria Arauzo-Carod, 2011. "Cluster Analysis using Microgreographic data," ERSA conference papers ersa11p284, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa11p284
    as

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    References listed on IDEAS

    as
    1. Rafael Boix, 2008. "Los distritos industriales en la Europa Mediterránea: los mapas de Italia y España," Working Papers wpdea0804, Department of Applied Economics at Universitat Autonoma of Barcelona.
    2. Vittorio Galletto & Rafael Boix, 2008. "Marshallian Industrial Districts in Spain," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2008(3), pages 29-52.
    3. Lambert, Dayton M. & McNamara, Kevin T. & Garrett, Megan I., 2006. "An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(1), pages 1-17, April.
    4. Thomas Brenner, 2006. "Identification of Local Industrial Clusters in Germany," Regional Studies, Taylor & Francis Journals, vol. 40(9), pages 991-1004.
    5. Gilles Duranton & Henry G. Overman, 2008. "Exploring The Detailed Location Patterns Of U.K. Manufacturing Industries Using Microgeographic Data," Journal of Regional Science, Wiley Blackwell, vol. 48(1), pages 213-243, February.
    6. Josep Maria Arauzo Carod & Miguel C. ManjÛn AntolÌn, 2004. "Firm Size and Geographical Aggregation: An Empirical Appraisal in Industrial Location," Small Business Economics, Springer, vol. 22(3_4), pages 299-312, April.
    7. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    8. Wagner, Alfred, 1891. "Marshall's Principles of Economics," History of Economic Thought Articles, McMaster University Archive for the History of Economic Thought, vol. 5, pages 319-338.
    9. Josep‐Maria Arauzo‐Carod, 2008. "Industrial Location At A Local Level: Comments On The Territorial Level Of The Analysis," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 99(2), pages 193-208, April.
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    Keywords

    cluster analysis; geographic data; microeconomics; regional economics.;
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