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Occupational Mobility in Europe: Extent, Determinants and Consequences

Abstract

We examine occupational mobility and its link to wage mobility across a large number of EU countries using worker-level micro data. In doing so, we document the extent, the individual-level determinants and the consequences of occupational mobility in terms of wage outcomes and structural change across the EU. In addition, we identify potential explanations for the observed cross-country variation. Our results show that on average, 3% of European workers change their occupation per year, and that the extent of occupational mobility differs strongly by country. Individual characteristics play an important role for person-specific occupational mobility, but have little explanatory power for differences between countries. Occupational mobility is strongly associated with earnings mobility, and occupation movers are more likely than job movers to experience a downward rather than an upward earnings transition; by contrast, changing occupation voluntarily is more often followed by an upward wage transition. As opposed to composition effects, employment protection legislation seems to play an important role for explaining cross-country differences in occupational mobility through its impact on overall job mobility.

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Notes

  1. 1.

    Wage transitions refer to transitions between deciles of the distribution of earnings from paid labour. The terms “wage transitions” and “earnings transitions” are used interchangeably in the article.

  2. 2.

    Note that—as indicated in the introduction—we choose this time period for our analysis because there is a break in the ISCO classification in 2011, and because we aim at focusing on a recent period of relative economic stability.

  3. 3.

    We thus exclude self-employment from the analysis as is standard in the literature (e.g. Kambourov and Manovskii 2008, Longhy and Brynin 2010, Lalé 2012, Groes et al. 2015, as well as Carrillo-Tudela et al. 2016).

  4. 4.

    Distinguishing between changes of employers and changes within the same firm is not possible, however.

  5. 5.

    All EU averages are unweighted averages of the country values in the overall sample. The values for each country are calculated using individual weights in order to be representative for the country’s population.

  6. 6.

    For the 1-digit level of occupational codes, the average is somewhat lower (2.5%), which means that the large majority of occupational changes at the 2-digit level go along with a change at the 1-digit level. These figures indicate that a relatively large share of occupational changes in our sample reflect a vertical, rather than a horizontal, change when changing their job and occupation. Our figures are furthermore of a similar magnitude as those in Lalé (2012) who reports mobility rates for the 1- and the 2-digit-level of slightly below and above 4%, respectively.

  7. 7.

    This is in line with the finding by Carrillo-Tudela et al (2016) for the UK that about 50% of all job changes are accompanied by an occupational change.

  8. 8.

    This figure is in line with the result of net mobility amounting to 1% in France (Lalé 2012), but lower than figures for the US (Kambourov and Manovskii 2008) and the UK (Carrillo-Tudela et al. 2016), where net mobility was found to be 4.5% and 12%, respectively. Apart from different time horizons, also sample restrictions might be reasons for diverging results.

  9. 9.

    In a robustness test, we apply as an alternative measure of wage mobility absolute changes in deflated earnings that are larger than 5% compared to the previous year’s individual earnings and define such changes as upward or downward mobility. This measure has the advantage that it is not affected by the degree of inequality prevailing in a specific country. The results (available from the authors upon request) are very close to our main measure.

  10. 10.

    The magnitude of this number should not be overinterpreted as it is a consequence of defining wage transitions as transitions across deciles of the wage distribution. Rather, it should be regarded as an indicator of the probability that a wage change is zero or relatively small.

  11. 11.

    Note that this could be partly driven by the selection of risk-averse workers into full-time jobs, as part-time jobs (which are excluded from this part of the analysis) make up an important share of employees in the Netherlands.

  12. 12.

    The contrary argument is not necessarily true, however: Overlapping confidence intervals do not always imply that the difference between two values is not significantly different, as long as each of the two values is not included in the confidence interval for the other.

  13. 13.

    Data source: Visser (2016).

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Acknowledgements

This paper is based on the project “Permeability of European Labour Markets” which was carried out by RWI for the Bertelsmann Foundation. We thank Joscha Schwarzwälder from the Bertelsmann Foundation for his support at various stages of the project. The authors are grateful to Julia Bredtmann, Sandra Schaffner, an anonymous referee and participants of the EALE 2018 Conference, the 5th European User Conference for EU-Microdata, the International Workshop on “Income Mobility, Economic Insecurity and Vulnerability for Different Generations of Europeans” at the University of Alcalá and a seminar at RWI for helpful comments and suggestions.

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Correspondence to Ronald Bachmann.

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Appendix

Appendix

See Table 5 and Fig. 11.

Table 5 1- and 2-digit ISCO-08 codes
Fig. 11
figure11

Predicted values for the probability of occupational change

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Bachmann, R., Bechara, P. & Vonnahme, C. Occupational Mobility in Europe: Extent, Determinants and Consequences. De Economist 168, 79–108 (2020). https://doi.org/10.1007/s10645-019-09355-9

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Keywords

  • Occupational mobility
  • Job mobility
  • Wage mobility
  • European labour markets
  • EU-SILC

JEL Classification

  • J62
  • J63
  • P52