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Record W2021265906 · doi:10.3138/cpp.2013-009

Canadian Retirement Incomes: How Much Do Financial Market Returns Matter?

2014· article· en· W2021265906 on OpenAlexafffundvenueabout
Bonnie‐Jeanne MacDonald, Lars Osberg

Bibliographic record

VenueCanadian Public Policy · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsDalhousie University
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of TorontoSociety of Actuaries
KeywordsFinancial crisisStock marketFinancial marketPopulationPensionEconomicsBoomBaby boomOrder (exchange)Labour economicsFinanceDemographic economicsBusiness

Abstract

fetched live from OpenAlex

How much might poor financial market returns affect the financial well-being of Canadian seniors? We compare three scenarios: if Canadian financial markets (a) never experienced the financial crisis of 2008 (i.e., continued on their pre-2008 path); (b) experienced the crisis and return to historical trends; or (c) enter a new low normal of depressed stock market returns and continued low interest rates. Using a population microsimulation model, we model the first order impacts—that is, before behavioural responses such as delayed retirement or increased savings—on the retirement income flows of Baby Boom retirees. While annual income from private savings of the median Canadian baby-boom senior drops by over half in the event of continuing low financial market returns, median financial welfare drops by only just over a fifth. Rising social transfers and stable income sources (such as Canada/Quebec Pension Plan and implicit income from home ownership) partially shield Canadian seniors from financial market risk. Canadian research has long recognized that the Canadian social pension system protects poorer Canadian seniors from destitution. Our results indicate that it also helps shield the Canadian elderly population as a whole from financial market risk.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.009
GPT teacher head0.199
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2014
Admission routes4
Has abstractyes

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