IDEAS home Printed from https://ideas.repec.org/p/pum/wpaper/2012-02.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://repec.geographie.uni-marburg.de/pum/wpaper/wp0212.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. repec:hal:spmain:info:hdl:2441/9932 is not listed on IDEAS
    4. 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.
    5. 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.
    6. repec:hal:wpspec:info:hdl:2441/9932 is not listed on IDEAS
    7. 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.
    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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 115-168, Elsevier.
    3. Tobias Scholl & Thomas Brenner, 2011. "Testing for Clustering of Industries - Evidence from micro geographic data," Working Papers on Innovation and Space 2011-02, Philipps University Marburg, Department of Geography.
    4. Tobias Scholl & Thomas Brenner, 2015. "Optimizing distance-based methods for large data sets," Journal of Geographical Systems, Springer, vol. 17(4), pages 333-351, October.
    5. Marcon, Eric & Puech, Florence, 2017. "A typology of distance-based measures of spatial concentration," Regional Science and Urban Economics, Elsevier, vol. 62(C), pages 56-67.
    6. 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.
    7. Thi Xuan Thu Nguyen & Javier Revilla Diez, 2017. "Multinational enterprises and industrial spatial concentration patterns in the Red River Delta and Southeast Vietnam," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(1), pages 101-138, July.
    8. Billings, Stephen B. & Johnson, Erik B., 2012. "A non-parametric test for industrial specialization," Journal of Urban Economics, Elsevier, vol. 71(3), pages 312-331.
    9. Franz-Josef Bade & Eckhardt Bode & Eleonora Cutrini, 2015. "Spatial fragmentation of industries by functions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(1), pages 215-250, January.
    10. Eric Marcon & Florence Puech, 2012. "A typology of distance-based measures of spatial concentration," Working Papers halshs-00679993, HAL.
    11. Edilberto Tiago Almeida & Raul Mota Silveira Neto & Jaime Macedo Brito Bastos & Rubens Lopes Pereira Silva, 2021. "Location patterns of service activities in large metropolitan areas: the Case of São Paulo," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(2), pages 451-481, October.
    12. Oliver Falck & Michael Fritsch & Stephan Heblich, 2014. "Is industry location persistent over time? Evidence from coagglomeration patterns between new and incumbent firms in Germany," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 34(1), pages 1-21, February.
    13. Rawaa Laajimi & Julie Le Gallo & Saloua Benammou, 2020. "What Geographical Concentration of Industries in the Tunisian Sahel? Empirical Evidence Using Distance‐Based Measures," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 111(5), pages 738-757, December.
    14. Stephen Billings & Erik Johnson, 2012. "Localization and Co-Localization within an Urban Area," ERSA conference papers ersa12p569, European Regional Science Association.
    15. Eckhardt Bode & Franz-Josef Bade Bade & Eleonora Cutrini Cutrini, 2011. "Domestic and International Offshoring of Tasks," ERSA conference papers ersa11p1840, European Regional Science Association.
    16. Ehrl, Philipp, 2013. "Agglomeration economies with consistent productivity estimates," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 751-763.
    17. Kristian Behrens, 2016. "Agglomeration and clusters: Tools and insights from coagglomeration patterns," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(4), pages 1293-1339, November.
    18. Thomas Klier & Daniel McMillen, 2015. "Plant Location Patterns in the European Automobile Supplier Industry," Growth and Change, Wiley Blackwell, vol. 46(4), pages 558-573, December.
    19. Benjamin Goldman & Thomas H. Klier & Thomas Walstrum, 2016. "Evidence on the Within-Industry Agglomeration of R&D, Production, and Administrative Occupations," Working Paper Series WP-2016-20, Federal Reserve Bank of Chicago.
    20. Andreas Behr & Christoph Schiwy & Lucy Hong, 2023. "Do high local customer and supply densities foster firm growth? [Fördern hohe lokale Kunden- und Lieferantendichten das Unternehmenswachstum?]," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 43(2), pages 265-289, August.

    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)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pum:wpaper:2012-02. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Robert Csicsics (email available below). General contact details of provider: https://edirc.repec.org/data/vamarde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.