Bibliographic record
Abstract
This paper examines the role of Social Security policy changes and the shift in pension plans — from annuity based retirement plans like Defined Benefit to account based plans like Defined Contribution — in explaining the recent increase in labor force participation of older workers. A structural retirement model of consumption, savings, Social Security, health insurance and pension plan heterogeneity is estimated using data from the Health and Retirement Study. The model captures key differences in pension wealth evolution across Defined Benefit and Defined Contribution pension plans and accounts for differences in out-of pocket medical spending across different health insurance groups. As a result, it produces variation in labor supply, both across different pension plan groups and health insurance types at older ages, as observed in the data. After controlling for any changes in the population age distribution and health insurance plans over time, model simulations indicate that changes in pension plan composition can explain 30.5 percent of the increase in labor force participation of the age group 65 to 69. Changes in Social Security normal retirement age and earnings test can each explain 19 and 45% of the increase in labor supply respectively for this age group.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".