The Hidden Resources of Women Working Longer: Evidence from Linked Survey-Administrative Data
Bibliographic record
Abstract
Despite women’s increased labor force attachment over the lifecycle, household surveys such as the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) do not show increases in retirement income (pensions, 401(k)s, IRAs) for women at older ages. We use linked survey-administrative data to demonstrate that retirement incomes are considerably underreported in the CPS ASEC and that women’s economic progress at older ages has been substantially understated over the last quarter century. Specifically, the CPS ASEC shows median household income for women age 65-69 rose 21 percent since the late 1980s, while the administrative records show an increase of 58 percent. Survey biases in women’s own incomes appear largest for women with the longest work histories. We also exploit the panel dimension of our data to follow a cohort of women and their spouses (if present) as they transition into retirement in recent years. In contrast to previous work, we find that most women do not experience noticeable drops in income up to five years after claiming social security, with retirement income playing an important role in maintaining their overall standard of living. Our results pose a challenge to the literature on the “retirement consumption puzzle” and suggest total income replacement rates are high for recent retirees.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
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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 | 0.012 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".