The Cost of Living Longer: Projections of the Effects of Prospective Mortality Improvement on Economic Support Ratios for Eighteen More Advanced Economies
Bibliographic record
Abstract
The aims of this paper are threefold; (1) to forecast mortality for a wide range of more developed countries from 2010-2050; (2) to project the effects of the forecast mortality patterns on economic support ratios assuming continuation of current fertility, migration and labour force participation; and 3) to calculate changes to labour force participation which would offset these effects. The mortality forecasts are prepared for fourteen countries using the Poisson Common Factor Model proposed by Li (2013). The mortality forecasts show that the projected gains in life expectancy are greatest in Japan, Australia and East-Central Europe, and are least in Netherlands, North America and Sweden, and correlate negatively with fertility and migration levels. The support ratios are projected to fall most over the period to 2050 in Japan, East-Central and Southern Europe, and least in Sweden and Australia. However, except for Poland, some recovery in support ratios is projected for the East-Central and Southern European countries post 2050. Using the valuation method of Parr and Guest (2014), the largest percentage increases in labour force participation needed to counterbalance the projected effects of mortality improvement are for Japan, Poland and the Czech Republic, and the smallest increases for the USA, Canada, Netherlands and Sweden. The dependency of the estimated effects of mortality improvement on support ratios and the initial age structure and the assumed levels of fertility, migration and labour force participation is discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".