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Record W3124474326 · doi:10.55016/ojs/sppp.v6i1.42420

Reform Proposals for Replenishing Retirement Savings

2013· article· en· W3124474326 on OpenAlexafffundabout
Jack Mintz, Thomas A. Wilson

Bibliographic record

VenueThe School of Public Policy Publications · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of TorontoUniversity of Calgary
FundersUniversity of TorontoUniversity of OxfordImperial Oil Limited
KeywordsPensionRevenueLabour economicsBusinessRetirement ageEconomicsDemographic economicsFinance

Abstract

fetched live from OpenAlex

The 2008-2009 economic crisis dealt a serious blow to Canadians’ retirement savings. While markets have since partially recovered, the ratio of Canadians’ household net-worth relative to disposable income still remains below where it was in 2007. So much wealth that workers had accumulated to prepare for retirement has been wiped away, while the years since 2008 that might have otherwise been spent compounding retirement savings have been spent, instead, on trying to recover losses in a low-interest-rate environment that has limited returns. With large waves of older workers approaching retirement age, and these future retirees projected to live longer than previous cohorts, Canada now faces the very realistic scenario that a significant number of people will reach retirement age without the funds they will need to provide a comfortable post-working-life income. Canadian policy-makers may not have the ability to restore that destroyed wealth. And with most governments already struggling to resolve serious deficits, the situation is not likely to be ameliorated with anything that requires additional spending, or that could reduce tax revenues. But there are policy reforms available that can help at least in better preparing the coming waves of retirees for a financially secure retirement. The reforms need not be far-reaching to have a meaningful impact. And they need not be costly, either. They can include a modest expansion of the Canada Pension Plan (CPP) to allow larger contributions — shared by employers and employees, or covered entirely by employees — that would, in turn, allow retiring workers to draw a larger maximum pension, rather than having to rely on the guaranteed income supplement (GIS). CPP contributions could also be made deductible from taxable income, like RRSP investments, to encourage workers to maximize contributions. To minimize an increase in payroll taxes, the eligibility age for CPP benefits could be increased to 67 years of age, similar to old-age security eligibility. Meanwhile, the tax treatment of group RRSPs — for which employer contributions are currently subject to payroll taxes — should be made the same as it is for defined-contribution registered pension plans (RPPs). There is also the option of increasing the age limit for RPP and RRSP contributions, from 71 to 75 years, to reflect the increase in life expectancies. RRSP contributions can be altered to allow lifetimeaveraging, allowing workers to take advantage of additional contribution room. Contribution limits on Tax-Free Savings Accounts should be increased as well. Policy-makers should also look at creating a capital-gains deferral account, to allow investors to sell off underperforming assets, without fear of triggering a tax bill, as long as they reinvest the proceeds. The freedom to unlock unwanted investments, and make better ones, will improve revenue prospects for investors and the government. Many of these reforms can be phased in gradually, to assess their effects on government revenue and savers’ behaviour. But they all appear to have the potential to encourage increased saving, without significantly harming long-term government revenue, helping Canadians better prepare for comfortable retirements, even after the serious wealth destruction that accompanied the recent economic crisis.

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)0.002
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.058
GPT teacher head0.344
Teacher spread0.286 · 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

Citations7
Published2013
Admission routes3
Has abstractyes

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