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Detecting Spatial Clustering Using a Firm-Level Index

Author

Listed:
  • Tobias Scholl

    (Schumpeter Center for Clusters, Entrepreneurship and Innnovation, University of Frankfurt)

  • Thomas Brenner

    (Working Group on Economic Geography and Location Research, Philipps University Marburg)

Abstract

We present a new statistical method that detects industrial clusters at a firm level. The proposed method does not divide space into subunits whereby it is not affected by the Modifiable Areal Unit Problem (MAUP). Our metric differs both in its calculation and interpretation from existing distance-based metrics and shows four central properties that enable its meaningful usage for cluster analysis. The method fulfills all five criteria for a test of localization proposed by Duranton and Overman (2005).

Suggested Citation

  • Tobias Scholl & Thomas Brenner, 2013. "Detecting Spatial Clustering Using a Firm-Level Index," Working Papers on Innovation and Space 2012-02, Philipps University Marburg, Department of Geography.
    • Handle: RePEc:pum:wpaper:2012-02
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    References listed on IDEAS

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    1. Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2013. "Spatial Localization in Manufacturing: A Cross-Country Analysis," Regional Studies, Taylor & Francis Journals, vol. 47(9), pages 1534-1554, October.
    2. repec:hal:wpspec:info:hdl:2441/9932 is not listed on IDEAS
    3. Glenn Ellison & Edward L. Glaeser & William R. Kerr, 2010. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," American Economic Review, American Economic Association, vol. 100(3), pages 1195-1213, June.
    4. Harvey J. Miller, 2010. "The Data Avalanche Is Here. Shouldn’T We Be Digging?," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 181-201, February.
    5. repec:hal:spmain:info:hdl:2441/9932 is not listed on IDEAS
    6. Hyun-Ju Koh & Nadine Riedel, 2009. "Assessing the Localization Pattern of German Manufacturing & Service Industries - A Distance Based Approach," Working Papers 0913, Oxford University Centre for Business Taxation.
    7. Thomas Klier & Daniel P. McMillen, 2008. "Evolving Agglomeration In The U.S. Auto Supplier Industry," Journal of Regional Science, Wiley Blackwell, vol. 48(1), pages 245-267, February.
    8. Reinhold Kosfeld & Hans-Friedrich Eckey & Jørgen Lauridsen, 2011. "Spatial point pattern analysis and industry concentration," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(2), pages 311-328, October.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Tobias Scholl & Thomas Brenner, 2013. "Optimizing Distance-Based Methods for Big Data Analysis," Working Papers on Innovation and Space 2013-09, Philipps University Marburg, Department of Geography.
    2. Tobias Scholl & Thomas Brenner & Martin Wendel, 2016. "Evolving localization patterns of company foundationsEvidence from the German MST-industry," Journal of Evolutionary Economics, Springer, vol. 26(5), pages 1067-1087, December.

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    More about this item

    Keywords

    Spatial concentration; localization; clusters; MAUP; distance†based measures;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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