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Record W1600563511

Estimating the Cost of Equity for Canadian and U.S. Firms

2007· article· en· W1600563511 on OpenAlexvenueaboutno aff
Lorie Zorn

Bibliographic record

VenueBank of Canada review · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCost of equityEquity (law)EnforcementEquity capital marketsEconomicsEquity riskFinanceSample (material)Private equity firmInvestment (military)Basis pointClub dealBusinessPublic economicsCost of capitalPrivate equityInterest rateMarket economyPolitical scienceIncentive
DOInot available

Abstract

fetched live from OpenAlex

Financing costs are important for both firms and the economy, affecting investment decisions and, ultimately, economic growth. Despite concern among policy-makers that the cost of equity financing may be higher in Canada than in the United States, empirical evidence supporting this view is mixed. Yet Canadian firms may not undertake as many projects that could potentially enhance growth if the cost of equity financing in Canada is relatively high. The article summarizes research by Jonathan Witmer and Lorie Zorn on the influences on the cost of equity in Canada and the United States, using an updated methodology that controls for firm characteristics and aggregate-level factors. In their sample, the cost of equity was 30-50 basis points higher in Canada over 1988 to 2006 but appears to have dropped in the post-1997 period. The results have policy implications related to such factors as firm size, disclosure, and securities regulation and enforcement.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.338

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.008
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.257
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2007
Admission routes2
Has abstractyes

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