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De-facto Gaps in Social Protection for Standard and Non-standard Workers: An Approach for Monitoring the Accessibility and Levels of Income Support

Author

Listed:
  • Immervoll, Herwig

    (OECD, Paris)

  • Fernandez, Rodrigo

    (OECD)

  • Hyee, Raphaela

    (OECD)

  • Lee, Jongmi

    (OECD)

  • Pacifico, Daniele

    (OECD)

Abstract

Social protection systems play a key stabilising role for individuals and societies, especially in the recent context of heightened uncertainties. Income stabilisation and related social policy objectives hinge on the extent to which social protection is accessible for those requiring support. This paper proposes a new empirical approach for quantifying the accessibility and value of income transfers following an earnings loss. It first presents a methodology for assessing support levels for jobless individuals in specific circumstances that allows for comparisons across countries and over time. It then illustrates the approach using longitudinal survey data in 16 OECD countries. The illustration focusses on differences in entitlements between people who were in "standard" and "non-standard" employment prior to joblessness. Results show that, prior to the COVID pandemic, income support gaps between standard and non-standard workers were often sizeable. For instance, in Korea, job losers with prior standard employment were nearly twice as likely to receive income support as otherwise similar individuals with a history of non-standard work. Gaps were also large in Italy and Portugal. By contrast, gaps were statistically insignificant in Australia, Austria, Belgium, Germany, Hungary and the United Kingdom. As these latter countries follow very different social protection strategies, results suggest that limiting support gaps for non-standard workers is achievable with different policy designs and targeting mechanisms.

Suggested Citation

  • Immervoll, Herwig & Fernandez, Rodrigo & Hyee, Raphaela & Lee, Jongmi & Pacifico, Daniele, 2022. "De-facto Gaps in Social Protection for Standard and Non-standard Workers: An Approach for Monitoring the Accessibility and Levels of Income Support," IZA Discussion Papers 15289, IZA Network @ LISER.
  • Handle: RePEc:iza:izadps:dp15289
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    References listed on IDEAS

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    1. Tim Bulman & Daniele Pacifico & Mauro Pisu & Olga Rastrigina, 2019. "Tax and benefit reforms to support employment and inclusiveness and address poverty in Italy," OECD Economics Department Working Papers 1580, OECD Publishing.
    2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
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    Cited by:

    1. Gouzoulis, Giorgos & Iliopoulos, Panagiotis & Galanis, Giorgos, 2022. "EU-induced Financialisation and Its Impact on the Greek Wage Share, 1999-2021," GLO Discussion Paper Series 1209, Global Labor Organization (GLO).
    2. Eichhorst, Werner & Krause-Pilatus, Annabelle & Dolls, Mathias & Lay, Max, 2024. "Crisis Resilience of European Welfare States: The Role of Multiple Layers of Protection," IZA Discussion Papers 17463, IZA Network @ LISER.

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    Keywords

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    JEL classification:

    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • J65 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment Insurance; Severance Pay; Plant Closings
    • H55 - Public Economics - - National Government Expenditures and Related Policies - - - Social Security and Public Pensions
    • H53 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Welfare Programs
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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