Canadian Retirement Incomes: How Much Do Financial Market Returns Matter?
Bibliographic record
Abstract
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.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".