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Record W2807858166 · doi:10.3138/cpp.2017-038

Individual Financial Returns from Quebec Pension Plan Reform Options: Analyzing Proposals to Renew a Second-Pillar Retirement Income Program

2018· article· en· W2807858166 on OpenAlexaffvenueabout
David Boisclair, Guy Lacroix, Steeve Marchand, Pierre‐Carl Michaud

Bibliographic record

VenueCanadian Public Policy · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsCenter for Interuniversity Research and Analysis on OrganizationsUniversité LavalHEC Montréal
Fundersnot available
KeywordsEarningsPensionYield (engineering)Government (linguistics)Income taxEconomicsLife expectancyRate of returnPillarLabour economicsFinancePublic economicsEngineering

Abstract

fetched live from OpenAlex

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.147
GPT teacher head0.396
Teacher spread0.249 · 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 teacher head, not a consensus.

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

Citations6
Published2018
Admission routes3
Has abstractyes

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