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Does High Involvement Management Make You Work Longer? Insights from Linked Survey and Register Data

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Listed:
  • Böckerman, Petri

    (University of Jyväskylä)

  • Bryson, Alex

    (University College London)

  • Ilmakunnas, Ilari

    (Finnish Centre for Pensions)

  • Ilmakunnas, Pekka

    (Aalto University)

Abstract

The management practices employers deploy may affect the utility workers derive from their jobs, potentially affecting the types of jobs they enter and also their propensity to exit the workforce. Ours is the first paper to assess whether employers' use of high involvement management (HIM) practices may influence workers' retirement intentions. Using linked survey and register data to analyze different combinations of HIM, we find that information sharing and employer-provided training lead to intentions to retire later among those who are close to the official retirement age in Finland.

Suggested Citation

  • Böckerman, Petri & Bryson, Alex & Ilmakunnas, Ilari & Ilmakunnas, Pekka, 2024. "Does High Involvement Management Make You Work Longer? Insights from Linked Survey and Register Data," IZA Discussion Papers 16827, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp16827
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    References listed on IDEAS

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    1. Petri Böckerman & Alex Bryson & Pekka Ilmakunnas, 2013. "Does high involvement management lead to higher pay?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(4), pages 861-885, October.
    2. Ilmakunnas, Pekka & Ilmakunnas, Seija, 2018. "Health and retirement age: Comparison of expectations and actual retirement," MPRA Paper 102618, University Library of Munich, Germany.
    3. Böckerman, Petri & Bryson, Alex & Ilmakunnas, Pekka, 2012. "Does high involvement management improve worker wellbeing?," Journal of Economic Behavior & Organization, Elsevier, vol. 84(2), pages 660-680.
    4. Frank Erp & Niels Vermeer & Daniel Vuuren, 2014. "Non-financial Determinants of Retirement: A Literature Review," De Economist, Springer, vol. 162(2), pages 167-191, June.
    5. Słoczyński, Tymon & Wooldridge, Jeffrey M., 2018. "A General Double Robustness Result For Estimating Average Treatment Effects," Econometric Theory, Cambridge University Press, vol. 34(1), pages 112-133, February.
    6. 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.
    7. Ludivine Martin & Uyen T. Nguyen-Thi & Caroline Mothe, 2021. "Human resource practices, perceived employability and turnover intention: does age matter?," Applied Economics, Taylor & Francis Journals, vol. 53(28), pages 3306-3320, June.
    8. Kosuke Imai & Marc Ratkovic, 2014. "Covariate balancing propensity score," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 243-263, January.
    9. Alex Bryson & John Forth & Helen Gray & Lucy Stokes, 2020. "Does Employing Older Workers Affect Workplace Performance?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 59(4), pages 532-562, October.
    10. Peter Browne & Ewan Carr & Maria Fleischmann & Baowen Xue & Stephen A. Stansfeld, 2019. "The relationship between workplace psychosocial environment and retirement intentions and actual retirement: a systematic review," European Journal of Ageing, Springer, vol. 16(1), pages 73-82, March.
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    More about this item

    Keywords

    retirement; high involvement management; information sharing; training;
    All these keywords.

    JEL classification:

    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • J32 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Nonwage Labor Costs and Benefits; Retirement Plans; Private Pensions

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