IDEAS home Printed from https://ideas.repec.org/p/trr/wpaper/201613.html

Classifying Industries Into Types of Relative Concentration

Author

Listed:
  • Ludwig von Auer
  • Andranik Stepanyan
  • Mark Trede

Abstract

When some industries are overrepresented in urban areas (urban concentration), some other industries must be overrepresented in rural areas (rural concentration). Existing measures of concentration do not distinguish between these different types of concentration. Instead, they rank industries according to their degree of concentration. However, knowing the concentration type is important, when investigating the forces of agglomeration that shape the geographical distribution of an industry. Therefore, the present paper proposes a new statistical approach that classifies each industry into one of seven different geographical patterns, five of which represent different types of concentration. The statistical identification of each industry’s geographical pattern is based on two Goodman-Kruskal rank correlation coefficients. The power of our approach is illustrated by German employment data on 613 different industries in 412 regions.

Suggested Citation

  • Ludwig von Auer & Andranik Stepanyan & Mark Trede, 2016. "Classifying Industries Into Types of Relative Concentration," Research Papers in Economics 2016-13, University of Trier, Department of Economics.
    • Handle: RePEc:trr:wpaper:201613
    as

    Download full text from publisher

    File URL: http://www.uni-trier.de/fileadmin/fb4/prof/VWL/EWF/Research_Papers/2016-13.pdf
    File Function: First version, 2016
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Eric Marcon & Florence Puech, 2003. "Evaluating the geographic concentration of industries using distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 3(4), pages 409-428, October.
    3. Gilles Duranton & Henry G. Overman, 2005. "Testing for Localization Using Micro-Geographic Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(4), pages 1077-1106.
    4. Miren Lafourcade & Jacques-François Thisse, 2008. "New economic geography: A guide to transport analysis," Working Papers halshs-00586878, HAL.
    5. Maurel, Francoise & Sedillot, Beatrice, 1999. "A measure of the geographic concentration in french manufacturing industries," Regional Science and Urban Economics, Elsevier, vol. 29(5), pages 575-604, September.
    6. Pierre-Philippe Combes & Thierry Mayer & Jacques-François Thisse, 2008. "Economic Geography: The Integration of Regions and Nations," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00311000, HAL.
    7. Devereux, Michael P. & Griffith, Rachel & Simpson, Helen, 2004. "The geographic distribution of production activity in the UK," Regional Science and Urban Economics, Elsevier, vol. 34(5), pages 533-564, September.
    8. Frank Bickenbach & Eckhardt Bode, 2008. "Disproportionality Measures of Concentration, Specialization, and Localization," International Regional Science Review, , vol. 31(4), pages 359-388, October.
    9. Eric Marcon & Florence Puech, 2012. "A typology of distance-based measures of spatial concentration," Working Papers halshs-00679993, HAL.
    Full references (including those not matched with items on IDEAS)

    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. Andranik Stepanyan & Ludwig von Auer & Mark Trede, 2015. "Regional Concentration and Confidence Regions," ERSA conference papers ersa15p564, European Regional Science Association.
    2. Roy Cerqueti & Eleonora Cutrini, 2024. "Testing for Localization with Entropy-Based Measures," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 173(1), pages 227-247, May.
    3. HAEDO, Christian & MOUCHART, Michel, 2012. "A stochastic independence approach for different measures of concentration and specialization," LIDAM Discussion Papers CORE 2012025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Cutrini, Eleonora, 2009. "Using entropy measures to disentangle regional from national localization patterns," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 243-250, March.
    5. Di Giacinto, Valter & Pagnini, Marcello, 2011. "Local and global agglomeration patterns: Two econometrics-based indicators," Regional Science and Urban Economics, Elsevier, vol. 41(3), pages 266-280, May.
    6. 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.
    7. Nakajima, Kentaro & Saito, Yukiko Umeno & Uesugi, Iichiro, 2012. "Measuring economic localization: Evidence from Japanese firm-level data," Journal of the Japanese and International Economies, Elsevier, vol. 26(2), pages 201-220.
    8. Maria Dav? & Isidora Barbaccia, 2015. "Measuring agglomeration by spatial effects: a proposal," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2015(1), pages 44-70.
    9. Lafourcade, Miren & Mion, Giordano, 2007. "Concentration, agglomeration and the size of plants," Regional Science and Urban Economics, Elsevier, vol. 37(1), pages 46-68, January.
    10. Valter Di Giacinto & Marcello Pagnini, 2008. "Agglomeration within and between regions: Two econometric based indicators," Temi di discussione (Economic working papers) 674, Bank of Italy, Economic Research and International Relations Area.
    11. Karsten Rusche & Uwe Kies & Andreas Schulte, 2011. "Measuring spatial co-agglomeration patterns by extending ESDA techniques," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 31(1), pages 11-25, June.
    12. Olga Alonso-Villar, 2011. "Measuring concentration: Lorenz curves and their decompositions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(2), pages 451-475, October.
    13. Gabriel Lang & Eric Marcon & Florence Puech, 2020. "Distance-based measures of spatial concentration: introducing a relative density function," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 243-265, April.
    14. Marta R. Casanova & Vicente Orts & José M. Albert, 2017. "Sectoral scope and colocalisation of Spanish manufacturing industries," Journal of Geographical Systems, Springer, vol. 19(1), pages 65-92, January.
    15. Barlet, M. & Briant, A. & Crusson, L., 2013. "Location patterns of service industries in France: A distance-based approach," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 338-351.
    16. Behrens, Kristian & Bougna, Théophile, 2015. "An anatomy of the geographical concentration of Canadian manufacturing industries," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 47-69.
    17. Giulio Cainelli & Roberto Ganau & Yuting Jiang, 2020. "Detecting space–time agglomeration processes over the Great Recession using firm-level micro-geographic data," Journal of Geographical Systems, Springer, vol. 22(4), pages 419-445, October.
    18. Lu, Jiangyong & Tao, Zhigang, 2009. "Trends and determinants of China's industrial agglomeration," Journal of Urban Economics, Elsevier, vol. 65(2), pages 167-180, March.
    19. Bagoulla, Corinne & Péridy, Nicolas, 2011. "Market access and the other determinants of North–South manufacturing location choice: An application to the Euro-Mediterranean area," Economic Systems, Elsevier, vol. 35(4), pages 537-561.
    20. Briant, A. & Combes, P.-P. & Lafourcade, M., 2010. "Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?," Journal of Urban Economics, Elsevier, vol. 67(3), pages 287-302, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - 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:trr:wpaper:201613. 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: Matthias Neuenkirch (email available below). General contact details of provider: https://edirc.repec.org/data/petride.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.