Working Paper: CEPR ID: DP10132
Authors: Sylvia Frühwirth-Schnatter; Christoph Pamminger; Andrea Weber; Rudolf Winter-Ebmer
Abstract: 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.
Keywords: family gap; fertility; Markov chain Monte Carlo; multinomial logit; panel data; timing of birth; transition data
JEL Codes: J13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| early childbearing (J13) | higher likelihood of returning to work quickly (J22) |
| early childbearing (J13) | moving towards high-paying jobs (J62) |
| giving birth late (J19) | increase likelihood of dropping out of the labor force (J63) |
| giving birth late (J19) | enhance chances of entering a high-wage career track (J24) |
| age at first birth (J13) | labor market outcomes (J48) |
| older mothers (J19) | more likely to end up in high-wage clusters (J69) |
| older mothers (J19) | more likely to end up out of the labor force (J69) |