Abstract (may include machine translation)
Using Bayesian Markov chain clustering analysis we investigate career paths of Austrian women after their first birth. This data-driven method allows characterizing long-term career paths of mothers over up to 19 years by transitions between parental leave, non-employment and different forms of employment. We classify women into five cluster groups with very different long-run career trajectories after childbearing. We further model group membership with a multinomial specification within the finite mixture model. This approach gives insights into the determinants of long-run outcomes. In particular, giving birth at an older age appears to be associated with very diverse outcomes: it is related to higher odds of dropping out of the labour force, on the one hand, but also to higher odds of reaching a high wage career track, on the other hand.
Original language | English |
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Pages (from-to) | 707-725 |
Number of pages | 19 |
Journal | Journal of the Royal Statistical Society. Series A: Statistics in Society |
Volume | 179 |
Issue number | 3 |
DOIs | |
State | Published - 1 Jun 2016 |
Externally published | Yes |
Keywords
- Family gap
- Fertility
- Markov chain Monte Carlo methods
- Multinomial logit
- Panel data
- Timing of birth
- Transition data