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Spatial Localization in Manufacturing: A Cross-Country Analysis

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This paper employs a homogenous firms database to investigate industry localization in European countries. More specifically, we compare, across industries and countries, the predictions of two of the most popular localization indices, i.e., the Ellison and Glaeser index (Ellison and Glaeser, 1997) and the Duranton and Overman index (Duranton and Overman, 2005). We find that, independently from the index used, localization is a pervasive phenomenon in all countries studied, but the degree of localization is very uneven across industries in each country. Furthermore, we find that the two indices significantly diverge in predicting the intensity of the forces generating localization within each industry. Finally, we perform a crosssectoral analysis of localized industries. We show that, in all countries, localized sectors are mainly "traditional" sectors (like jewelery, wine, and textiles) and sectors where scale economies are important. However, once one controls for countries' industrial structures science-based sectors turn out to be the most localized ones.
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  • Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2009. "Spatial Localization in Manufacturing: A Cross-Country Analysis," Documents de Travail de l'OFCE 2009-07, Observatoire Francais des Conjonctures Economiques (OFCE).
    • Handle: RePEc:fce:doctra:0907
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    Cited by:

    1. 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.
    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. José M. Albert Ortiz & Francisco M. Gasca Sánchez & Miguel A. Flores Segovia, 2018. "Patrones de localización espacial de las manufacturas mexicanas: análisis con la técnica de patrones de puntos espaciales\Spatial location patterns of Mexican manufacturing: Analysis using the tech," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 33(2), pages 253-282.
    4. 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.
    5. 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.
    6. Wolfgang Dauth & Michaela Fuchs & Anne Otto, 2018. "Long‐run processes of geographical concentration and dispersion: Evidence from Germany," Papers in Regional Science, Wiley Blackwell, vol. 97(3), pages 569-593, August.
    7. Steven Brakman & Harry Garretsen & Zhao Zhao, 2017. "Spatial concentration of manufacturing firms in China," Papers in Regional Science, Wiley Blackwell, vol. 96, pages 179-205, March.
    8. Kofanov, D. & Mikhailova, T., 2015. "Geographical Concentration of Soviet Industries: A Comparative Analysis," Journal of the New Economic Association, New Economic Association, vol. 28(4), pages 112-141.
    9. Davidson Natalia & Kislyak Nadezhda & Vorobyev Pavel, 2010. "Spatial Ñoncentration and Firm Performance in Russia," EERC Working Paper Series 10/05e, EERC Research Network, Russia and CIS.
    10. 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.
    11. 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.
    12. 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.
    13. Gu Jiafeng, 2014. "Spatial Dynamics, Vocational Education and Chinese Economic Growth," Journal of Systems Science and Information, De Gruyter, vol. 2(5), pages 385-400, October.

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    More about this item

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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