Maternity Leave and Paternity Leave: Evidence on the Economic Impact of Legislative Changes in High-Income Countries
Bibliographic record
Abstract
Abstract Labor market policies for expecting and new mothers emerged at the turn of the 19th century. The main motivation for these policies was to ensure the health of mothers and their newborn children. With increased female labor market participation, the focus has gradually shifted to the effects that parental leave policies have on women’s labor market outcomes and gender equality. Proponents of extending parental leave rights for mothers in terms of duration, benefits, and job protection have argued that this will support mothers’ labor market attachment and allow them to take time off from work after childbirth and then safely return to their pre-birth jobs. Others have noted that extended maternity leave can work as a double-edged sword for mothers: If young women are likely to spend months, or even years, on leave, employers are likely to take that into consideration when hiring and promoting their employees. These policies may therefore end up adversely affecting women’s labor market outcomes. This has led to an increased focus on activating fathers to take parental leave, and in 2019, the European Parliament approved a directive requiring member states to ensure at least 2 months of earmarked paternity leave. The literature on parental leave has proliferated during the past two decades. The increased number of studies on the topic has brought forth some consistent findings. First, the introduction of short maternity leave is beneficial for both maternal and child health and for mothers’ labor market outcomes. Second, there appear to be negligible benefits from a leave extending beyond 6 months in terms of health outcomes and children’s long-term outcomes. Furthermore, longer leaves have little, or even adverse, influence on mothers’ labor market outcomes. However, evidence suggests that there may be underlying heterogeneous effects from extended leave among different socioeconomic groups. The literature on the effect of earmarked paternity leave indicates that these policies are effective in increasing fathers’ leave-taking and involvement in child care. However, the evidence on the influence of paternity leave on gender equality in the labor market remains scarce and is somewhat mixed. Finally, recent studies that focus on the effect of parental leave policies for firms find that in general, firms are able to compensate for lost labor when their employees go on leave. However, if firms face constraints when replacing employees, it could negatively influence their performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".