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Labour-Market Outcomes of Older Workers in the Netherlands: Measuring Job Prospects Using the Occupational Age Structure

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Abstract

This paper analyses changes in job opportunities of older workers in the Netherlands in the period 1996–2010. The standard human capital model predicts that, as a result of human capital obsolescence, mobility becomes more costly when workers become older. We measure and interpret how changing job opportunities across 96 occupations affect different age and skill groups. Older workers end up in shrinking occupations, in occupations with a lower share of high-skilled workers, in occupations facing a higher threat of offshoring tasks abroad, more focus on routine-intensive tasks and less rewarding job content. This process is not only observed for the oldest group of workers, but for workers aged 40 and above. Observing older workers in declining occupations is to a large extent a market outcome, but declining job opportunities in terms of less satisfying working conditions and job tasks and content could potentially raise incentives to retire early.

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Notes

  1. In the Dutch policy discussion De Economist has contributed to the discussion of future labour-market developments in Europe with among others a special issue labelled “ageing workforces” in 2011 (Vandenberghe 2011) and Van Ours (2009) for an analysis of declining productivity when workers become older. See Broer (2001), Bettendorf et al. (2011) and Heijdra and Mierau (2011) for assessments of the sustainability of the welfare state.

  2. Deelen (2012) presents wage-tenure profiles for Dutch workers in the period 1999–2005. Using administrative data, she finds that these profiles are relatively steep compared to other countries. Also industries with high returns to tenure appear to have a high share of older workers and low levels of job mobility. Borghans et al. (2007) obtain that high wage growth is related to low job flows for older workers in the Netherlands.

  3. Bartel and Sicherman (1993), Peracchi and Welch (1994) and Ahituv and Zeira (2005) argued that problems to cope with technological change and new technologies adequately, might force older workers to leave employment and push them into early retirement or unemployment.

  4. See e.g. Euwals et al. (2009), De Hek and Van Vuuren (2010) and Van Ours and Stoeldraijer (2011) for reviews of the theoretical and empirical literature.

  5. See e.g., Borghans and Ter Weel (2006) and Akcomak et al. (2011) for a recent analysis for the Netherlands and Acemoglu and Autor (2011) for an overview of the literature.

  6. Heckman and Scheinkman (1987), Gathmann and Schönberg (2010) and Acemoglu and Autor (2011) develop more general models of task bundles.

  7. Lazear (2009) and Gathmann and Schönberg (2010) develop this argument in more detail.

  8. These are ISCO 348, 521, 614, 700, 711, 732, 733, 744, 800, 811, 813, 816, 822 and 834. If we in addition exclude those occupations whose cells contain less than 100 workers (212, 230, 613, 615, 812, 814 and 820) the results remain similar.

  9. The assumption is that German and Dutch occupations are similar with respect to the inputs used to construct this variable.

  10. The regression coefficient is significant at the 1 % level.

    Fig. 3
    figure 3

    Changes (1996–2010) in the average age composition of occupations and employment shares

    Full size image

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Authors and Affiliations

  1. CPB Netherlands Bureau for Economic Policy Analysis, The Hague, The Netherlands

    Nicole Bosch & Bas ter Weel

  2. Maastricht University, Maastricht, The Netherlands

    Bas ter Weel

Authors
  1. Nicole Bosch
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  2. Bas ter Weel
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Correspondence to Bas ter Weel.

Additional information

We would like to thank a referee of this journal, Lex Borghans, Rob Euwals, Paul de Beer, Jan van Ours and Trudie Schils for comments on an earlier draft of this paper and Andrea Jaeger for excellent research assistance.

Appendix

Appendix

This appendix presents background information on the data sources we have used to construct the variables used in the analysis. Table 4 documents the variables and the way in which they are constructed. The final column shows the data source. Table 5 presents descriptive statistics of the variables.

Table 5 Descriptive statistics
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Bosch, N., ter Weel, B. Labour-Market Outcomes of Older Workers in the Netherlands: Measuring Job Prospects Using the Occupational Age Structure. De Economist 161, 199–218 (2013). https://doi.org/10.1007/s10645-013-9202-8

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