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Scarring Effects of Unemployment

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  • Nilsen, Øivind Anti

    () (Norwegian School of Economics)

  • Reiso, Katrine Holm

    () (Norwegian School of Economics)

Abstract

Using Norwegian individual register data of young workers, from the period 1986-2008, we analyse whether there are large and persistent negative relationships between unemployment and the risk of repeated unemployment and being out of labour force. A nearest-neighbour propensity score matching method is applied to make the treatment group (the unemployed) and the control group (the employed) as similar as possible. By tracking workers over a 10-year follow-up period, we find that unemployment has a negative effect on later labour market attachment. This is consistent with existing findings in the literature. The negative effects decrease over time. Using the bounding approach proposed by Rosenbaum (2002) to analyse the importance of unobserved variables, our results indicate that a relatively high level of unobserved selection bias could be present in the data before changing the inference. Thus, unemployment leaves young workers with long-term scars.

Suggested Citation

  • Nilsen, Øivind Anti & Reiso, Katrine Holm, 2011. "Scarring Effects of Unemployment," IZA Discussion Papers 6198, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp6198
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    Cited by:

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    2. Clark, Andrew E. & Lepinteur, Anthony, 2019. "The causes and consequences of early-adult unemployment: Evidence from cohort data," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 107-124.
    3. Luis Beccaria & Roxana Maurizio & Martin Trombetta & Gustavo Vázquez, 2016. "Una evaluación del efecto scarring en Argentina," Revista Desarrollo y Sociedad, Universidad de los Andes - CEDE, vol. 77, August.
    4. Marjan Petreski & Nikica Mojsoska-Blazevski & Marcelo Bergolo, 2017. "Labor-Market Scars When Youth Unemployment is Extremely High: Evidence from Macedonia," Eastern European Economics, Taylor & Francis Journals, vol. 55(2), pages 168-196, March.
    5. Schmillen, Achim & Umkehrer, Matthias, 2013. "The scars of youth : effects of early-career unemployment on future unemployment experience," IAB Discussion Paper 201306, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    6. Möller Joachim & Umkehrer Matthias, 2015. "Are there Long-Term Earnings Scars from Youth Unemployment in Germany?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 235(4-5), pages 474-498, August.
    7. Murray, Emily T. & Zaninotto, Paola & Fleischmann, Maria & Stafford, Mai & Carr, Ewan & Shelton, Nicola & Stansfeld, Stephen & Kuh, Diana & Head, Jenny, 2019. "Linking local labour market conditions across the life course to retirement age: Pathways of health, employment status, occupational class and educational achievement, using 60 years of the 1946 Briti," Social Science & Medicine, Elsevier, vol. 226(C), pages 113-122.
    8. Székely,Miguel & Karver,Jonathan George, 2015. "Youth out of school and out of work in Latin America : a cohort approach," Policy Research Working Paper Series 7421, The World Bank.
    9. Bofinger, Peter & Schnabel, Isabel & Feld, Lars P. & Schmidt, Christoph M. & Wieland, Volker, 2014. "Mehr Vertrauen in Marktprozesse. Jahresgutachten 2014/15," Annual Economic Reports / Jahresgutachten, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, volume 127, number 201415, September.

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    More about this item

    Keywords

    scarring; unemployment persistency; matching technique;

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • J65 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment Insurance; Severance Pay; Plant Closings
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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