Scalable shift‐share analysis: Novel framework and application to France

Jean-François Ruault () and Yves Schaeffer ()
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Jean-François Ruault: UR LESSEM - Laboratoire des EcoSystèmes et des Sociétés en Montagne - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Fédération OSUG - Observatoire des Sciences de l'Univers de Grenoble - UGA - Université Grenoble Alpes, LVMT - Laboratoire Ville, Mobilité, Transport - ENPC - École nationale des ponts et chaussées - Université Gustave Eiffel
Yves Schaeffer: UR LESSEM - Laboratoire des EcoSystèmes et des Sociétés en Montagne - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Fédération OSUG - Observatoire des Sciences de l'Univers de Grenoble - UGA - Université Grenoble Alpes

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Abstract: The shift‐share analysis (SSA) of regional employment growth disparities aims at disentangling the effects of regional differences in industry mix and industrial competitiveness. Yet, the spatial concentration of industry is a blindspot of this approach. We generalize the SSA to encompass this salient feature of the economic geography. Besides, industry emergence and catastrophic growth events—booming or collapsing industries—are integrated in our framework. This novel method is applied to study regional disparities in manufacturing employment growth in France in a dynamic way over a 22‐year period at a fine geographical level.

Keywords: dynamic shift‐share analysis; France; manufacturing; regional employment growth; regional inequality (search for similar items in EconPapers)
Date: 2020-12
Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-02929570v1
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Published in Papers in Regional Science, 2020, 99 (6), pp.1667-1690. ⟨10.1111/pirs.12558⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02929570

DOI: 10.1111/pirs.12558

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