The retirement incentive effects of Canada's Income Security programs
Bibliographic record
Abstract
Abstract Canada has a large Income Security system for retirement that provides significant and widely varying disincentives to work at older ages. We provide an empirical analysis of the retirement incentives of the Canadian Income Security system using a new administrative database. We find that the work disincentives inherent in the Canadian Income Security system have significant impacts on retirement. This suggests that program reform can play a role in responses to fiscal pressures. We also demonstrate the importance of controlling for lifetime earnings in retirement models. Specifications without these controls overestimate the effects of the Income Security system. JEL Classification: H55, J26 Les effets d’incitation à la retraite des programmes de la sécurité du revenu au Canada Le Canada a un important système de sécurité du revenu après retraite qui crée des désincitations importantes et diverses au travail pour les gens d’un âge avancé. Les auteurs donnent des résultats d’une analyse empirique de ces incitations en utilisant certaines données administratives nouvelles. Il semble que ces désincitations au travailont un impact significatif sur les décisions de retraite. Voilà qui suggère qu’une réforme des programmes peut avoir un impact important sur les réactions aux pressions fiscales. On montre aussi que la prise en compte des revenus tout au long de lavie active a une grande importance dans les modèles de retraite. Il est clair que toutes les spécifications de modèles qui ne prennent pas en compte ces facteurs tendent à sur‐estimer les effets des programmes de la sécurité du revenu.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".