Author(s):	Sylvia Frühwirth-Schnatter, Christoph Pamminger, Andrea Weber, Rudolf Winter-Ebmer
Publication Date:	September 2014
Keyword(s):	family gap, fertility, Markov Chain Monte Carlo, Multinomial Logit, Panel Data, timing of birth, Transition Data
JEL(s):	J13
Programme Areas:	Labour Economics
Link to this Page:	cepr.org/active/publications/discussion_papers/dp.php?dpno=10132

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.