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A stochastic independence approach for different measures of concentration and specialization


  • HAEDO, Christian

    (CIDETI, University of Bologna, Argentina)

  • MOUCHART, Michel

    () (Université catholique de Louvain, CORE & ISBA, B-1348 Louvain-la-Neuve, Belgium)


From data in the form of a two-way contingency table “Regions _ Sectors”, the concepts of specialization and concentration, built from the analysis of conditional distributions or profiles, is based on discrepancies among distributions: between profiles and a uniform distribution for absolute concepts; between profiles and the corresponding marginal distribution for the relative concepts; or between the joint distribution and the product of the marginal distributions for the global concept. This paper provides an extensive numerical analysis of measures derived from this approach and from other approaches used in the literature and shows that while the different measures under consideration display rather similar numerical behaviours, differences of ranking call for a particular care when interpreting the numerical results.

Suggested Citation

  • HAEDO, Christian & MOUCHART, Michel, 2012. "A stochastic independence approach for different measures of concentration and specialization," CORE Discussion Papers 2012025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2012025

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    References listed on IDEAS

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    Cited by:

    1. 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.


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