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A stochastic independence approach for different measures of concentration and specialization

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  • HAEDO, Christian

    (CIDETI, University of Bologna, Argentina)

  • MOUCHART, Michel

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

Abstract

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," LIDAM Discussion Papers CORE 2012025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2012025
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    2. X. Ramos & D. Van De Gaer, 2012. "Empirical Approaches to Inequality of Opportunity: Principles, Measures, and Evidence," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/792, Ghent University, Faculty of Economics and Business Administration.
    3. Jacques Drèze & Erik Schokkaert, 2013. "Arrow’s theorem of the deductible: Moral hazard and stop-loss in health insurance," Journal of Risk and Uncertainty, Springer, vol. 47(2), pages 147-163, October.
    4. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," LIDAM Discussion Papers CORE 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. HAEDO, Christian & MOUCHART , Michel & ,, 2013. "Specialized agglomerations with areal data: model and detection," LIDAM Discussion Papers CORE 2013060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. CREMER, Helmuth & PESTIEAU, Pierre & PONTHIERE, Grégory, 2012. "The economics of long-term care: a survey," LIDAM Discussion Papers CORE 2012030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Thierry Bréchet & Yann Ménière & Pierre M. Picard, 2016. "The Clean Development Mechanism in a world carbon market," Canadian Journal of Economics, Canadian Economics Association, vol. 49(4), pages 1569-1598, November.
    8. Haedo, Christian & Mouchart, Michel, 2016. "Automatic biclustering of regions and sectors," LIDAM Discussion Papers ISBA 2016042, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

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