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Record W2904257202 · doi:10.1017/s147474721800029x

The long-term effects of employer-sponsored pension plans on non-workplace returns on investments

2018· article· en· W2904257202 on OpenAlex
Derek Messacar, René Morissette

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Pensions Economics and Finance · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsStatistics CanadaMemorial University of Newfoundland
Fundersnot available
KeywordsPensionAsset allocationInvestment (military)EconomicsAsset (computer security)Term (time)BusinessActuarial scienceLabour economicsFinancePortfolio

Abstract

fetched live from OpenAlex

Abstract What is the effect of having an employer-sponsored pension plan (EPP) on financial performance in non-workplace investments? This paper offers new insight into this unresolved empirical issue using administrative data on more than 345,000 tax filers from Canada. The paper makes two key contributions. First, an approach for inferring relative returns on investments is developed based on a longitudinal analysis of saving flow-of-funds and wealth data related to the use of the tax-free savings account (TFSA). The analysis shows that there is substantial heterogeneity in asset balances across individuals with equivalent saving histories. Second, having an EPP is shown to raise the average return on investment in other tax-preferred saving plans, albeit by a modest amount of approximately 0.50–1.25% over 5 years since the TFSA was introduced. This result is robust to augmenting the analysis to an instrumental variables approach, exploiting variation in the availability of EPPs across cohorts by sex and industry of employment.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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