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Measuring Employment Readiness for Hard-to-Place Individuals

Author

Listed:
  • Tranberg Bodilsen, Simon

    (Aarhus University)

  • Nielsen, Søren Albeck

    (Aarhus University)

  • Rosholm, Michael

    (Aarhus University)

Abstract

In an era characterized by population aging and economic challenges in welfare states across the world, sustaining these welfare systems requires a large workforce. Many individuals outside the labor market aspire to work but encounter a labyrinth of obstacles. While Public Employment Services employ Active Labor Market Policies, their effectiveness for this group remains uncertain. This study introduces the Employment Readiness Indicator Questionnaire (ERIQ), transcending traditional employment categories by assessing individuals' progress toward employment and measuring employment readiness for those labeled "hard-to-place". Integrating socially vulnerable clients into the labor market remains an unsolved challenge. ERIQ demonstrates impressive predictive abilities and points towards actionable recommendations by identifying malleable traits, such as social skills, coping strategies, goal orientation, and self-efficacy, that significantly impact employment readiness. ERIQ emerges as a valuable resource for policymakers and practitioners, advancing the goal of promoting labor market participation for socially vulnerable individuals.

Suggested Citation

  • Tranberg Bodilsen, Simon & Nielsen, Søren Albeck & Rosholm, Michael, 2023. "Measuring Employment Readiness for Hard-to-Place Individuals," IZA Discussion Papers 16626, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp16626
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    References listed on IDEAS

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    1. Takaya Saito & Marc Rehmsmeier, 2015. "The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
    2. Wright, Marvin N. & Ziegler, Andreas, 2017. "ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i01).
    3. Ronald W. McQuaid & Colin Lindsay, 2005. "The Concept of Employability," Urban Studies, Urban Studies Journal Limited, vol. 42(2), pages 197-219, February.
    4. Michael Rosholm & Simon Tranberg Bodilsen & Bastien Michel & Albeck Søren Nielsen, 2024. "Predictive risk modeling for child maltreatment detection and enhanced decision-making: Evidence from Danish administrative data," Post-Print hal-04743190, HAL.
    5. Rosholm, Michael & Staghøj, Jonas & Svarer, Michael & Hammer, Bo, 2006. "A Danish Profiling System," Nationaløkonomisk tidsskrift, Nationaløkonomisk Forening, vol. 2006(1), pages 209-229.
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    Cited by:

    1. Tshering Choki & Alvin Etang, 2025. "Understanding the Challenges and Constraints of Bhutanese Youth in Accessing Employment Opportunities," World Bank Publications - Reports 42646, The World Bank Group.

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    Keywords

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    JEL classification:

    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

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