A HEALTH PRODUCTION MODEL WITH ENDOGENOUS RETIREMENT
Why this work is in the frame
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Bibliographic record
Abstract
We formulate a stylized structural model of health, wealth accumulation and retirement decisions building on the human capital framework of health and derive analytic solutions for the time paths of consumption, health, health investment, savings and retirement. We argue that the literature has been unnecessarily restrictive in assuming that health is always at the 'optimal' health level. Exploring the properties of corner solutions, we find that advances in population health decrease the retirement age, whereas at the same time, individuals retire when their health has deteriorated. This potentially explains why retirees point to deteriorating health as an important reason for early retirement, whereas retirement ages have continued to fall in the developed world, despite continued improvements in population health and mortality. In our model, workers with higher human capital invest more in health and, because they stay healthier, retire later than those with lower human capital whose health deteriorates faster.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it