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Age Biased Technical and Organisational Change, Training and Employment Prospects of Older Workers

Author

Listed:
  • Behaghel, Luc

    () (Paris School of Economics)

  • Caroli, Eve

    () (Université Paris-Dauphine)

  • Roger, Muriel

    () (INRA-CORELA)

Abstract

We analyse the role of training in mitigating the negative impact of technical and organizational changes on the employment prospects of older workers. Using a panel of French firms in the late 1990s, we first estimate wage bill share equations for different age groups. Consistently with what is found in the literature, we find that adopting new technologies and innovative work practices negatively affects the wage bill share of older workers. In contrast, training older workers more than average increases their share in the wage bill in the next period. So, training contributes to offset the negative impact of ICT and innovative work practices. However, it does not reduce the age bias associated with these innovative devices: the interaction terms between training and ICT/innovative work practices are either insignificant or negative. As a second step, we estimate the impact of ICT, innovative work practices and training on employment flows by age group in the next period. We get similar results to those obtained with wage bill shares. Overall, training appears to have a positive impact on the employability of older workers, but it offers limited prospects to dampen the age bias associated with new technologies and innovative work practices.

Suggested Citation

  • Behaghel, Luc & Caroli, Eve & Roger, Muriel, 2011. "Age Biased Technical and Organisational Change, Training and Employment Prospects of Older Workers," IZA Discussion Papers 5544, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp5544
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    References listed on IDEAS

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    Cited by:

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    2. Sotiris Blanas, 2019. "The distinct effects of information technologies and communication technologies on the age-skill composition of labour demand," Working Paper Research 365, National Bank of Belgium.
    3. Fries, Jan, 2014. "Age and skill bias of trade liberalisation? Heterogeneous employment effects of EU Eastern Enlargement," ZEW Discussion Papers 14-113, ZEW - Leibniz Centre for European Economic Research.
    4. Sandulli, Francesco D. & Baker, Paul M.A. & López-Sánchez, José I., 2013. "Can small and medium enterprises benefit from skill-biased technological change?," Journal of Business Research, Elsevier, vol. 66(10), pages 1976-1982.
    5. Erling Barth & James C. Davis & Richard B. Freeman & Kristina McElheran, 2020. "Twisting the Demand Curve: Digitalization and the Older Workforce," Working Papers 20-37, Center for Economic Studies, U.S. Census Bureau.
    6. Alex Coad, 2018. "Firm age: a survey," Journal of Evolutionary Economics, Springer, vol. 28(1), pages 13-43, January.
    7. Campaner, Annika & Heywood, John S. & Jirjahn, Uwe, 2018. "Flexible Work Organization and Employer Provided Training: Evidence from German Linked Employer-Employee Data," IZA Discussion Papers 11696, Institute of Labor Economics (IZA).
    8. Jorge Calero & Álvaro Choi, 2015. "The distribution of skills among the European adult population and unemployment: a comparative approach," Working Papers 2015/35, Institut d'Economia de Barcelona (IEB).
    9. Boockmann, Bernhard & Fries, Jan & Göbel, Christian, 2018. "Specific measures for older employees and late career employment," The Journal of the Economics of Ageing, Elsevier, vol. 12(C), pages 159-174.
    10. Anne Sonnet & Hilde Olsen & Thomas Manfredi, 2014. "Towards More Inclusive Ageing and Employment Policies: The Lessons from France, The Netherlands, Norway and Switzerland," De Economist, Springer, vol. 162(4), pages 315-339, December.
    11. Grillitsch, Markus & Schubert, Torben & Srholec, Martin, 2016. "Knowledge diversity and firm growth: Searching for a missing link," Papers in Innovation Studies 2016/13, Lund University, CIRCLE - Center for Innovation Research.
    12. Guerrazzi, Marco, 2014. "Workforce ageing and the training propensity of Italian firms: cross-sectional evidence from the INDACO survey," MPRA Paper 56826, University Library of Munich, Germany.
    13. Yashiro, Naomitsu & Kyyrä, Tomi & Hwang, Hyunjeong & Tuomala, Juha, 2020. "Technology, Labour Market Institutions and Early Retirement: Evidence from Finland," IZA Discussion Papers 13990, Institute of Labor Economics (IZA).
    14. Torben Schubert & Martin Andersson, 2015. "Old is gold? The effects of employee age on innovation and the moderating effects of employment turnover," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 24(1-2), pages 95-113, March.

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    More about this item

    Keywords

    training; organizational change; technical change; older workers;

    JEL classification:

    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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