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Measures of the Geographic Concentration of Industries: Improving Distance-Based Methods

Author

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  • Eric Marcon

    () (ECOFOG - Ecologie des forêts de Guyane - CIRAD - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - INRA - Institut National de la Recherche Agronomique - UAG - Université des Antilles et de la Guyane - AgroParisTech - CNRS - Centre National de la Recherche Scientifique)

  • Florence Puech

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

Abstract

This study introduces two new measures of spatial concentration. The proposed M functions constitute an extension to Ripley's functions (Ripley, 1976, 1977). They allow the evaluation of the relative geographic concentration and co-location of industries in a non-homogeneous spatial framework. Some rigorous comparisons with similar recently developed tools prove the relevance of the M functions in the field of spatial economics.

Suggested Citation

  • Eric Marcon & Florence Puech, 2009. "Measures of the Geographic Concentration of Industries: Improving Distance-Based Methods," Working Papers halshs-00372617, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00372617
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00372617
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    References listed on IDEAS

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    1. Ugo Fratesi, 2008. "Issues in the Measurement of Localization," Environment and Planning A, , vol. 40(3), pages 733-758, March.
    2. Gilles Duranton & Henry G. Overman, 2005. "Testing for Localization Using Micro-Geographic Data," Review of Economic Studies, Oxford University Press, vol. 72(4), pages 1077-1106.
    3. 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.
    4. Haaland, J.I. & Kind, H.J. & knarvik, K.H.M. & Torstensson, J., 1998. "What Determines the Economic Geography of Europe?," Papers 19/98, Norwegian School of Economics and Business Administration-.
    5. Tomoya Mori & Koji Nishikimi & Tony E. Smith, 2005. "A Divergence Statistic for Industrial Localization," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 635-651, November.
    6. 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.
    7. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics,in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171 Elsevier.
    8. Combes, Pierre-Philippe & Overman, Henry G., 2004. "The spatial distribution of economic activities in the European Union," Handbook of Regional and Urban Economics,in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 64, pages 2845-2909 Elsevier.
    9. Giuseppe Arbia & Giuseppe Espa & Danny Quah, 2008. "A class of spatial econometric methods in the empirical analysis of clusters of firms in the space," Empirical Economics, Springer, vol. 34(1), pages 81-103, February.
    10. C S Morphet, 1997. "A Statistical Method for the Identification of Spatial Clusters," Environment and Planning A, , vol. 29(6), pages 1039-1055, June.
    11. 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.
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    Cited by:

    1. Pablo Jensen & Julien Michel, 2011. "Measuring spatial dispersion: exact results on the variance of random spatial distributions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(1), pages 81-110, August.
    2. Arbia, G. & Espa, G. & Giuliani, D. & Mazzitelli, A., 2012. "Clusters of firms in an inhomogeneous space: The high-tech industries in Milan," Economic Modelling, Elsevier, vol. 29(1), pages 3-11.
    3. Catini, Roberto & Karamshuk, Dmytro & Penner, Orion & Riccaboni, Massimo, 2015. "Identifying geographic clusters: A network analytic approach," Research Policy, Elsevier, vol. 44(9), pages 1749-1762.
    4. repec:bla:presci:v:95:y:2016:i:4:p:903-910 is not listed on IDEAS

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    Keywords

    Geographic concentration; Distance-based methods; Ripley's K function; M function;

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