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The local distribution of in-work poverty and sectoral employment: an analysis of local dynamics in Italy

Author

Listed:
  • Giovanni Tonutti

    (Scuola Normale Superiore
    World Bank Group)

  • Andrea Garnero

    (OECD
    Institute of Labor Economics IZA)

  • Gaia Bertarelli

    (Ca’Foscari University of Venice)

  • Monica Pratesi

    (Italian National Institute of Statistic ISTAT
    University of Pisa)

Abstract

In-work poverty has risen to become a key feature of European societies. In 2017, the percentage of workers at risk of low pay in Italy reached an estimated 25% and the issue rose to the forefront of the public and political debate. Yet, due to data limitations, few studies analysed the local distribution of this phenomenon and investigated the macro-determinants associated with its rise. By applying Small Area Estimates (SAE) to EU-SILC data we obtain a novel map of the distribution of in-work poverty in Italy, defined as the share of workers at risk of low pay (AROLP) between 2008 and 2017. The unit of analysis of Local Labour Systems, a non-administrative unit based on commuter flows, highlights the deepening of Italian dualism between Northern and Southern areas, as well as rising within-region wage inequality. By means of a panel fixed-effects model linking estimates of AROLP with data on local sectoral employment, we observe that growth in low-skill sectors such as agriculture is associated with increases in AROLP incidence. On the contrary trends of low pay are negatively associated with the growth of manufacturing and construction sectors, and jobs in non-market services, such as public sector jobs. In addition, variations in overall employment represent the strongest predictor for dynamics of low-pay incidence.

Suggested Citation

  • Giovanni Tonutti & Andrea Garnero & Gaia Bertarelli & Monica Pratesi, 2024. "The local distribution of in-work poverty and sectoral employment: an analysis of local dynamics in Italy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 973-998, July.
  • Handle: RePEc:spr:stmapp:v:33:y:2024:i:3:d:10.1007_s10260-024-00756-y
    DOI: 10.1007/s10260-024-00756-y
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    References listed on IDEAS

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