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

  • 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 - Université de Guyane - CNRS - Centre National de la Recherche Scientifique)

  • Florence Puech

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

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    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.

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    Paper provided by HAL in its series Working Papers with number halshs-00372617.

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    Date of creation: 01 Apr 2009
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    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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    1. Pierre-Philippe Combes & Henry Overman, 2003. "The Spatial Distribution of Economic Activities in the European Union," CEP Discussion Papers dp0587, Centre for Economic Performance, LSE.
    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. Anthony Briant & Pierre-Philippe Combes & Miren Lafourcade, 2008. "Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?," PSE Working Papers halshs-00586029, HAL.
    4. C S Morphet, 1997. "A Statistical Method for the Identification of Spatial Clusters," Environment and Planning A, SAGE Publishing, vol. 29(6), pages 1039-1055, June.
    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. 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.
    7. Haaland, Jan I. & Kind, Hans Jarle & Ulltveit-Moe, Karen-Helene, 1999. "What Determines the Economic Geography of Europe?," CEPR Discussion Papers 2072, C.E.P.R. Discussion Papers.
    8. Ugo Fratesi, 2008. "Issues in the measurement of localization," Environment and Planning A, Pion Ltd, London, vol. 40(3), pages 733-758, March.
    9. Giuseppe Arbia & Giuseppe Espa & Danny Quah, 2007. "A class of spatial econometric methods in the empirical analysis of clusters of firms in the space," Department of Economics Working Papers 0705, Department of Economics, University of Trento, Italia.
    10. 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.
    11. Gilles Duranton & Henry G Overman, 2006. "Exploring the Detailed Location Patterns of UK Manufacturing Industries using Microgeographic Data," Working Papers tecipa-248, University of Toronto, Department of Economics.
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