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Comment réduire la fracture spatiale ? Une application en Ile-de-France

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  • Nathalie Georges
  • Yannick L'Horty
  • Florent Sari

Abstract

Nous estimons sur des données communales franciliennes un modèle à erreurs spatialement corrélées afin d'expliquer les disparités spatiales de durées de chômage. Nous mobilisons des indicateurs représentatifs du dynamisme de l'emploi local, du mésappariement entre la localisation des emplois et des demandeurs d'emplois, du mésappariement entre les compétences demandées par les entreprises et celles offertes par les demandeurs d'emplois, de la ségrégation résidentielle et du logement. Nous utilisons des méthodes qui permettent d'évaluer la portée de chacune de ces explications et de déterminer lesquelles sont les plus importantes à considérer du point de vue de la décision publique. Les résultats montrent que les efforts devraient être accentués sur les problèmes de mésappariement en termes de compétences et de localisation géographique des demandeurs d'emplois.
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Suggested Citation

  • Nathalie Georges & Yannick L'Horty & Florent Sari, 2012. "Comment réduire la fracture spatiale ? Une application en Ile-de-France," TEPP Research Report 2012-07, TEPP.
  • Handle: RePEc:tep:tepprr:rr12-07
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    Cited by:

    1. Frédéric Gavrel & Nathalie Georges & Yannick L’Horty & Isabelle Lebon, 2015. "Inadéquation des qualifications et fracture spatiale," Economie & Prévision, La Documentation Française, vol. 0(1), pages 1-16.
    2. Yannick L'Horty & Florent Sari, 2011. "Pourquoi tant de chômeurs à Paris ?," TEPP Research Report 2011-11, TEPP.
    3. Emilie Bourdu & Olivier Bouba-Olga, 2012. "Évaluation d'impact d'un nouveau service public de formation professionnelle," Post-Print hal-00613021, HAL.
    4. Jean-Michel Floch, 2017. "Standards of living and segregation in twelve French metropolises," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 497-498, pages 73-96.

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