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Magnitude and evolution of gender and race contributions to earnings inequality across US regions

Author

Listed:
  • Frederic Chantreuil

    (TEPP - Travail, Emploi et Politiques Publiques - UPEM - Université Paris-Est Marne-la-Vallée - CNRS - Centre National de la Recherche Scientifique, UNC - Université de la Nouvelle-Calédonie, LARJE - Laboratoire de Recherches Juridique et Economique - UNC - Université de la Nouvelle-Calédonie)

  • Kévin Fourrey

    (LIRSA - Laboratoire interdisciplinaire de recherche en sciences de l'action - Cnam - Conservatoire National des Arts et Métiers [Cnam], CEET - Centre d'études de l'emploi et du travail - Cnam - Conservatoire National des Arts et Métiers [Cnam] - M.E.N.E.S.R. - Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche - Ministère du Travail, de l'Emploi et de la Santé, TEPP - Travail, Emploi et Politiques Publiques - UPEM - Université Paris-Est Marne-la-Vallée - CNRS - Centre National de la Recherche Scientifique)

  • Isabelle Lebon

    (TEPP - Travail, Emploi et Politiques Publiques - UPEM - Université Paris-Est Marne-la-Vallée - CNRS - Centre National de la Recherche Scientifique, CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

  • Thérèse Rebière

    (LIRSA - Laboratoire interdisciplinaire de recherche en sciences de l'action - Cnam - Conservatoire National des Arts et Métiers [Cnam], TEPP - Travail, Emploi et Politiques Publiques - UPEM - Université Paris-Est Marne-la-Vallée - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper studies individual characteristics of earnings inequality within the population of blacks and whites in the United States over the period 2005-2017. Beyond education and age serving as a proxy for professional experience, applying a new Shapley income decomposition methodology enables us to isolate and measure two discriminative factors in earnings differences: race and gender. We show that these two factors explain a significant share of total earnings inequality, as defined by the Gini index, for all the geographical administrative divisions used. Whatever the division, the share of earnings inequality associated with gender greatly exceeds that of race. While gender earnings inequality has fallen over time, inequality associated with race has tended to increase since 2010 and is stronger in the Southeast of the country. (C) 2020 University of Venice. Published by Elsevier Ltd. All rights reserved.

Suggested Citation

  • Frederic Chantreuil & Kévin Fourrey & Isabelle Lebon & Thérèse Rebière, 2021. "Magnitude and evolution of gender and race contributions to earnings inequality across US regions," Post-Print hal-03245932, HAL.
    • Handle: RePEc:hal:journl:hal-03245932
    DOI: 10.1016/j.rie.2020.11.001
    Note: View the original document on HAL open archive server: https://hal.science/hal-03245932v1
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    Cited by:

    1. Ernst Coupet & Ehab Yamani, 2022. "The impact of the coronavirus on African American unemployment: lessons from history," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 56(1), pages 1-18, December.

    More about this item

    Keywords

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    JEL classification:

    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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