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Record W3125248746

Income Security and Stability During Retirement in Canada

2008· preprint· en· W3125248746 on OpenAlexaboutno aff
Sebastien Larochelle-Côté, John Myles, Garnett Picot

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typepreprint
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsPensionDemographic economicsPovertyEconomicsEconomic inequalityIncome distributionHousehold incomeInequalityLabour economicsGeographyEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

Post-war policies and subsequent debates had two policy targets: reducing old-age poverty and enhancing income security for the “average worker” after retirement. While we know a lot about the first issue, the second has received less attention as a result of data limitations. We take advantage of unique longitudinal data based on Canadian tax files (the LAD) to examine income replacement rates of older Canadians relative to their economic status when they were in their mid-fifties. In 2005, the replacement income of retired individuals in their mid-seventies who were in the middle of the income distribution at age 55 (in the early 1980s) was between 70 and 80 percent of their previous incomes some 20 years earlier This figure is at the high end of the range (65 to 75 percent) that experts generally consider “adequate” for middle-income retirees to maintain their pre-retirement living standards. However, we also show that there is considerable variation in replacement rates. By age 75, about a quarter of middle-income persons had retirement incomes of less than 60 percent of the income they were receiving in their mid-fifties, a result of differential access to private pension income. We also ask whether income replacement rates have been rising or falling among more recent cohorts of retirees but find little change. Finally, we report results about the stability of incomes in the retirement years. We conclude that year to year instability in family income declines for both high and low income earners as they age, largely because of the stabilizing effect of public pension income sources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.638

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.006
Science and technology studies0.0080.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.138
GPT teacher head0.393
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicRetirement, Disability, and EmploymentFrench-language works237,207