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Record W1551883340

The Pension Fund Advantage: Are Canadians Overpaying Their Mutual Funds?

2008· article· en· W1551883340 on OpenAlexaboutno aff
Rob Bauer, Luc Kicken

Bibliographic record

VenueSSRN Electronic Journal · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMutual fundPensionClosed-end fundFund of fundsIncome fundBusinessOpen-end fundPassive managementFund administrationFinanceFixed incomeTarget date fundSample (material)Global assets under managementShareholderInvestment (military)Institutional investorDifferential (mechanical device)Manager of managers fundCorporate governanceBond
DOInot available

Abstract

fetched live from OpenAlex

The institutional structure through which individuals accumulate retirement savings is an important issue. Ideally, it is expert and low-cost. This article compares the cost-effectiveness of the pension fund structure with the mutual fund structure. The authors hypothesize that the pension fund structure provides investment management services at lower cost because most mutual funds are conflicted between providing good financial results for their clients and good financial results for their shareholders. Specifically, they compare the investment performance of a sample of domestic fixed income portfolios of Canadian pension funds with those of a sample of Canadian fixed income mutual funds. They find an average performance differential of 1.8 percent per annum in favor of pension funds. This performance gap is approximately equal to the average cost differential between the two approaches. They conclude that high mutual fund fees significantly reduce the net returns of mutual fund investors.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.215
Teacher spread0.200 · 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 designObservational
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

Citations5
Published2008
Admission routes1
Has abstractyes

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