Sustainable retirement income for the socialite, the gardener, and the uninsured
Bibliographic record
Abstract
This paper advances the literature on the sustainability of retirement income by making consumption a stochastic variable instead of a constant real value, as previous papers have done. The paper continues to make the rate of return and date of death stochastic variables, as Milevsky and Robinson (2000, 2005) do. The sustainability of retirement income depends on the nature of the lifestyle that the retiree chooses. The difference in shortfall probabilities or risk of ruin between the variable cases and the fixed consumption case is significant, and so the adviser needs to take this into account. The difference in shortfall probabilities between making consumption a nonconstant but deterministic amount, and making it also stochastic, is not as important, because it does not reduce risk enough to make more aggressive consumption rates secure. Finally, making consumption correlated with the rate of return, which implies the family adjusts consumption as its wealth changes, reduces shortfall probabilities to a moderate extent. In general, an initial consumption of more than 4% of initial wealth is not sustainable for any likely set of conditions. In the very best case, an initial consumption rate of 6% is sustainable, but we think that case will fit very few people.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".