THE EFFECTS OF SINGLE MOTHERS' WELFARE USE AND EMPLOYMENT DECISIONS ON CHILDREN'S COGNITIVE DEVELOPMENT
Bibliographic record
Abstract
We examine the effects of single mothers' welfare use and employment decisions on children's short‐run cognitive development, as measured by their preschool standardized math test scores. We control for three mechanisms through which these decisions might affect children's outcomes: direct monetary benefits, parental time invested in the child, and nonpecuniary benefits from in‐kind transfer programs such as Medicaid. We employ a correction function approach and control for state‐fixed effects to address the endogenous nature of welfare participation and employment decisions. Our estimates suggest that although each additional quarter of either mother's employment or welfare use results in only a small increase in a child's standardized math test score, the total effects after several quarters are sizable. We allow mothers' decisions to have varying effects on attainment by children's observed innate ability and by the intensity of welfare use and employment. A child who has the mean level of observed innate ability with a mother who simultaneously worked and used welfare in all 20 quarters after childbirth experiences an 8.25 standardized‐point increase in standardized scores. The positive impact is more pronounced for the more disadvantaged children, who tend to be born to mothers with low Armed Forces Qualification Test scores, or have lower birth weights. We also examine the effects using timing of employment and welfare use, as well as children's maturity and gender. (JEL I3, J13, J22)
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".