Men, Women, and Capital: Estimating Substitution Patterns Using a Size and Gender-Dependent Childcare Policy in Chile
Bibliographic record
Abstract
This paper uses a policy implemented in Chile that obliges firms to fully fund childcare costs for their female employees, but only if they hire more than 19 women. Using plant level data from manufacturing firms, we first show that this policy has had a substantially detrimental impact on the hiring of women above that threshold, in particular since the policy has become more binding, in industrial sectors that hire fewer women and in larger firms. We then use the response of firms to study whether women workers are more or less complementary to capital than men. We find that firms that avoid the legislation by having just below 20 female workers are significantly more capital intensive than firms just above the threshold. This suggests that firms that want to avoid being subject to the regulation replace women with capital but in such a way that the capital to men ratio increases. We use our estimates to calibrate a production function and find that our results are consistent with a framework where women are weakly substitutes with capital (while men are complementary) in this emerging economy’s manufacturing sector. This does not seem to be driven by a change in skill composition of the workforce. We also find some evidence of other changes: average wages and total workforce are lower for firms who hire 20 women than those who hire just below that threshold but labor productivity is unaltered. PRELIMINARY, PLEASE DO NOT CITE ∗We thank comments from seminar participants at IADB, PUC Chile and Toronto. All remaining errors are our own. †Pontificia Universidad Catolica de Chile ‡Pontificia Universidad Catolica de Chile. §Pontificia Universidad Catolica de Chile and FinanceUC.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".