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How do Automation and Offshorability Influence Unemployment Duration and Subsequent Job Quality?

Author

Listed:
  • Schmidpeter, Bernhard

    (Institute for Social and Economic Research, University of Essex)

  • Winter-Ebmer, Rudolf

    (Christian Doppler Laboratory Aging, Health and the Labor Market, JKU Linz and IHS, Institut for Advanced Studies, Vienna and IZA, Bonn and CEPR, London and CReAM, London)

Abstract

We analyze the effect of automation and offshorability on unemployment duration and post-unemployment outcomes such as wages and employment stability. Our rich administrative data allow us to evaluate the importance of providing unemployment training in this context. Employing a multivariate mixed proportional hazard model to deal with selectivity, we find that both the routine content in tasks as well as the probability of off-shoring negatively affects the re-employment possibilities. Labor market training is helping workers to ameliorate these negative effects and is remarkably on the spot. For workers who find re-employment, our results show that offshorability (but not automation) affects future job duration and wages positively. Our analysis reveals interesting differences by gender.

Suggested Citation

  • Schmidpeter, Bernhard & Winter-Ebmer, Rudolf, 2018. "How do Automation and Offshorability Influence Unemployment Duration and Subsequent Job Quality?," Economics Series 343, Institute for Advanced Studies.
    • Handle: RePEc:ihs:ihsesp:343
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    File URL: https://irihs.ihs.ac.at/id/eprint/4721
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    References listed on IDEAS

    as
    1. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    2. Alan S. Blinder & Alan B. Krueger, 2013. "Alternative Measures of Offshorability: A Survey Approach," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 97-128.
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    Cited by:

    1. Grigoli, Francesco & Koczan, Zsoka & Topalova, Petia, 2020. "Automation and labor force participation in advanced economies: Macro and micro evidence," European Economic Review, Elsevier, vol. 126(C).
    2. Schmidpeter, Bernhard & Winter-Ebmer, Rudolf, 2021. "Automation, unemployment, and the role of labor market training," European Economic Review, Elsevier, vol. 137(C).
    3. Brunello, Giorgio & Wruuck, Patricia, 2019. "Skill Shortages and Skill Mismatch in Europe: A Review of the Literature," IZA Discussion Papers 12346, IZA Network @ LISER.
    4. Malo, Miguel & Cueto, Begoña, 2019. "Do old and new labour market risks overlap? Automation, offshorability, and non-standard employment," MPRA Paper 95058, University Library of Munich, Germany.
    5. Xin, Baogui & Ye, Xiaopu, 2024. "Robotics applications, inclusive employment and income disparity," Technology in Society, Elsevier, vol. 78(C).
    6. Katharina Dengler & Katrin Hohmeyer & Cordula Zabel, 2021. "Welfare recipients’ transition into employment and employment stability in Germany," LABOUR, CEIS, vol. 35(4), pages 450-484, December.
    7. Brunello, Giorgio & Wruuck, Patricia & Maurin, Laurent, 2019. "Skill shortages and skill mismatch in Europe: A review of the literature," EIB Working Papers 2019/05, European Investment Bank (EIB).

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    Keywords

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    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • F66 - International Economics - - Economic Impacts of Globalization - - - Labor

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