Frühwirth-Schnatter, Sylvia Pamminger, Christoph Weber, Andrea Winter-Ebmer, Rudolf
Year of Publication:
NRN Working Paper, NRN: The Austrian Center for Labor Economics and the Analysis of the Welfare State No. 1409
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.
fertility timing of birth family gap Transition Data Markov Chain Monte Carlo Multinomial Logit Panel Data