Retirement Income Security and Well-Being in Canada
Bibliographic record
Abstract
A large international literature has documented the labor market distortions associated with social security benefits for near-retirees.In this paper, we investigate the 'other side' of social security programs, seeking to document improvements in wellbeing arising from the provision of public pensions.To the extent households adjust their savings and employment behavior to account for enhanced retirement benefits, the positive impact of the benefits may be crowded out.We proceed by using the large variation across birth cohorts in income security entitlements in Canada that arise from reforms to the programs over the past 35 years.This variation allows us to explore the effects of benefits on elderly well-being while controlling for other factors that affect well-being over time and by age.We examine measures of income, consumption, poverty, and happiness.For income, we find large increases in income corresponding to retirement benefit increases, suggesting little crowd out.Consumption also shows increases, although smaller in magnitude than for income.We find larger retirement benefits diminish income poverty rates, but have no discernable impact on consumption poverty measures.This could indicate smoothing of consumption through savings or other mechanisms.Finally, our limited happiness measures show no definitive effect.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".