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Frühwirth-Schnatter, Sylvia
Pamminger, Christoph
Weber, Andrea
Winter-Ebmer, Rudolf
Year of Publication: 
Series/Report no.: 
Working Paper, Department of Economics, Johannes Kepler University of Linz 1408
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, thus, classify women into five cluster-groups with very different long-run career costs of childbearing. We model group membership with a multinomial specification within the finite mixture model. This approach gives insights into the determinants of the long-run family gap. Giving birth late in life may lead very diverse outcomes: on the one hand, it increases the odds to drop out of labor force, and on the other hand, it increases the odds to reach a high-wage career track.
timing of birth
family gap
Transition Data
Markov Chain Monte Carlo
Multinomial Logit
Panel Data
Document Type: 
Working Paper

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