Bibliographic record
Abstract
This paper studies the effects of health shocks on the demand for health insurance and annuities, precautionary saving, and the welfare implications of public policies in a simple life-cycle model.I show that when the health shock simultaneously increases health expenses and reduces longevity, the following results can be obtained via closed-form solutions.First, utility-maximizing agents would neither fully insure their uncertain health expenses nor fully annuitize their wealth, even in the absence of market frictions and bequest motives.Second, the effect of uncertain health expenses on precautionary saving may be smaller than what has been found in previous studies.Under certain conditions, uncertain health expenses may even reduce precautionary saving.Third, mandatory health insurance (e.g.public health insurance) tends to benefit the poor more, while mandatory annuitization (e.g.public pension) is more likely to favor the rich.A simple numerical application of the model to the US long term care (LTC) insurance market suggests that the simultaneous effect of health shock on health expenses and longevity is a quantitatively important reason why agents (especially the rich) do not purchase more private LTC insurance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 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".