Individual Financial Returns from Quebec Pension Plan Reform Options: Analyzing Proposals to Renew a Second-Pillar Retirement Income Program
Bibliographic record
Abstract
We use simulation methods and a detailed tax calculator to analyze the likely effects of two recent proposals aimed at reforming the Quebec Pension Plan (QPP): the federal proposal, eventually implemented throughout Canada, and the Quebec government's December 2016 proposal. Accounting for education-adjusted life expectancy, earnings variability over the course of a career, and their interactions with the tax code and retirement income system, we find that internal rates of return (IRRs) for new QPP contributions are similar under both reforms for individuals with lifetime average annual earnings of more than $40,000. Both reforms yield substantial IRRs for low-income individuals. Although the Quebec proposal offers higher IRRs for individuals earning less than $40,000, the federal proposal yields greater present value benefits for these same individuals. We show that if new QPP benefits were exempted from the Guaranteed Income Supplement (GIS) clawback, and provided that the working income tax benefit and GIS were not enhanced, the two reforms would yield similar IRRs for individuals with average earnings of more than $15,000. The QPP reform would thus better focus on the middle-income earners originally targeted by reform advocates.
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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 | 0.010 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".