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Distance-based measures of spatial concentration: Introducing a relative density function

Author

Listed:
  • Gabriel Lang

    (MIA-Paris - Mathématiques et Informatique Appliquées - INRA - Institut National de la Recherche Agronomique - AgroParisTech)

  • Eric Marcon

    (UMR ECOFOG - Ecologie des forêts de Guyane - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - INRA - Institut National de la Recherche Agronomique - AgroParisTech - UG - Université de Guyane - CNRS - Centre National de la Recherche Scientifique - UA - Université des Antilles)

  • Florence Puech

    (RITM - Réseaux Innovation Territoires et Mondialisation - UP11 - Université Paris-Sud - Paris 11)

Abstract

For a decade, distance-based methods have been widely employed and constantly improved in the field of spatial economics. These methods are a very useful tool for accurately evaluating the spatial distribution of plants or retail stores, for example (Duranton and Overman, 2008). In this paper, we introduce a new distance-based statistical measure for evaluating the spatial concentration of economic activities. To our knowledge, the m function is the first relative density function to be proposed in the economics literature. This tool supplements the typology of distance-based methods recently drawn up by Marcon and Puech (2012). By considering several theoretical and empirical examples, we show the advantages and the limits of the m function for detecting spatial structures in economics.

Suggested Citation

  • Gabriel Lang & Eric Marcon & Florence Puech, 2020. "Distance-based measures of spatial concentration: Introducing a relative density function," Post-Print hal-01082178, HAL.
    • Handle: RePEc:hal:journl:hal-01082178
    DOI: 10.1007/s00168-019-00946-7
    Note: View the original document on HAL open archive server: https://hal.science/hal-01082178v4
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    References listed on IDEAS

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    1. Alfaro, Laura & Chen, Maggie Xiaoyang, 2014. "The global agglomeration of multinational firms," Journal of International Economics, Elsevier, vol. 94(2), pages 263-276.
    2. 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.
    3. Florent Bonneu & Christine Thomas-Agnan, 2015. "Measuring and Testing Spatial Mass Concentration with Micro-geographic Data," Spatial Economic Analysis, Taylor & Francis Journals, vol. 10(3), pages 289-316, September.
    4. Behrens, Kristian & Guillain, Rachel, 2017. "The determinants of coagglomeration: Evidence from functional employment patterns," CEPR Discussion Papers 11884, C.E.P.R. Discussion Papers.
    5. 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.
    6. 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, February.
    7. Giuseppe Arbia & Giuseppe Espa & Danny Quah, 2009. "A class of spatial econometric methods in the empirical analysis of clusters of firms in the space," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 81-103, Springer.
    8. 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.
    9. Giuseppe Arbia, 2001. "The role of spatial effects in the empirical analysis of regional concentration," Journal of Geographical Systems, Springer, vol. 3(3), pages 271-281, November.
    10. 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.
    11. Arbia, Giuseppe, 2016. "Spatial Econometrics: A Broad View," Foundations and Trends(R) in Econometrics, now publishers, vol. 8(3-4), pages 145-265, November.
    12. Zhou, Tingyu & Clapp, John M., 2015. "The location of new anchor stores within metropolitan areas," Regional Science and Urban Economics, Elsevier, vol. 50(C), pages 87-107.
    13. Eric Marcon & Florence Puech, 2010. "Measures of the geographic concentration of industries: improving distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 10(5), pages 745-762, September.
    14. 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.
    15. Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).
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    Cited by:

    1. A. Tidu & S. Usai & Frederick Guy, 2021. "Agglomeration in manufacturing and services: an experimental application of a distance-based measure to Sardinia," Working Paper CRENoS 202110, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Ludwig von Auer & Mark Trede, 2021. "Urbanization in Industrialized Countries: Appearances Are Deceptive," Research Papers in Economics 2021-04, University of Trier, Department of Economics.
    3. Yukio Sadahiro, 2022. "A method for evaluating the degree of spatial and temporal avoidance in spatial point patterns," Journal of Geographical Systems, Springer, vol. 24(2), pages 241-260, April.
    4. Sugam Agarwal & Smruti Ranjan Behera, 2022. "Geographical concentration of knowledge and technology-intensive industries in India: empirical evidence from establishment-level analysis," Indian Economic Review, Springer, vol. 57(2), pages 513-552, December.
    5. S. Usai & Frederick Guy & A. Tidu, 2022. "Measuring spatial dispersion: an experimental test on the M-index," Working Paper CRENoS 202206, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

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    More about this item

    Keywords

    Agglomeration; Aggregation; Spatial Concentration; Point Patterns; Economic Geography;
    All these keywords.

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