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How unemployment scarring affects skilled young workers: evidence from a factorial survey of Swiss recruiters

Author

Listed:
  • Lulu P. Shi

    (University of Basel)

  • Christian Imdorf

    (Norwegian University of Science and Technology)

  • Robin Samuel

    (Université du Luxembourg, Maison des Sciences Humaines)

  • Stefan Sacchi

    (University of Bern)

Abstract

We ask how employers contribute to unemployment scarring in the recruitment process in the German-speaking part of Switzerland. By drawing on recruitment theories, we aim to better understand how recruiters assess different patterns of unemployment in a job candidate’s CV and how this affects the chances of young applicants being considered for a vacancy. We argue that in contexts with tight school-work linkage and highly standardised Vocational Education and Training systems, the detrimental effect of early unemployment depends on how well the applicant’s profile matches the requirements of the advertised position. To test this assumption, we surveyed Swiss recruiters who were seeking to fill positions during the time of data collection. We employed a factorial survey experiment that tested how the (un)employment trajectories in hypothetical young job applicants’ CV affected their chances of being considered for a real vacancy. Our results show that unemployment decreases the perceived suitability of an applicant for a specific job, which implies there is a scarring effect of unemployment that increases with the duration of being unemployed. But we also found that these effects are moderated by how well the applicant’s profile matches the job’s requirements. Overall, the worse the match between applicant’s profile and the job profile, the smaller are the scarring effects of unemployment. In sum, our findings contribute to the literature by revealing considerable heterogeneity in the scarring effects of unemployment. Our findings further suggest that the scarring effects of unemployment need to be studied with regard to country-specific institutional settings, the applicants’ previous education and employment experiences, and the job characteristics.

Suggested Citation

  • Lulu P. Shi & Christian Imdorf & Robin Samuel & Stefan Sacchi, 2018. "How unemployment scarring affects skilled young workers: evidence from a factorial survey of Swiss recruiters," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 52(1), pages 1-15, December.
  • Handle: RePEc:spr:jlabrs:v:52:y:2018:i:1:d:10.1186_s12651-018-0239-7
    DOI: 10.1186/s12651-018-0239-7
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    Cited by:

    1. Miroslav Štefánik & Katarína Karasová & Ivana Studená, 2020. "Can supporting workplace insertions of unemployed recent graduates improve their long-term employability?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 47(2), pages 245-265, May.
    2. Tamara Gutfleisch & Robin Samuel & Stefan Sacchi, 2021. "The application of factorial surveys to study recruiters’ hiring intentions: comparing designs based on hypothetical and real vacancies," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(3), pages 775-804, June.
    3. Jacobus Johannes de Jongh, 2019. "Understanding the Drivers of Long-Term Youth Unemployment: Micro-Level Evidence from South Africa," Proceedings of International Academic Conferences 9912297, International Institute of Social and Economic Sciences.
    4. Christian Imdorf & Matthias Pohlig, 2021. "La sélection sur le marché du travail selon les ruptures dans le parcours antérieur comparaison Suisse et Bulgarie," Post-Print halshs-03364147, HAL.

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    More about this item

    Keywords

    Recruitment; Youth unemployment; Scarring; Hiring; Factorial survey; Switzerland;
    All these keywords.

    JEL classification:

    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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