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Record W2033881396 · doi:10.1108/ijmf-03-2012-0040

Canadian corporate payout policy

2013· article· en· W2033881396 on OpenAlexaffabout
H. Kent Baker, Bin Chang, Shantanu Dutta, Samir Saadi

Bibliographic record

VenueInternational Journal of Managerial Finance · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsQueen's UniversityOntario Tech University
Fundersnot available
KeywordsDividendEarningsDividend payout ratioProfitability indexBusinessMonetary economicsCash flowIncentiveCashEconomicsDividend policyFinance

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to examine cash dividends and stock repurchases in Canada from 1988 to 2006 and their relationship with earnings. Design/methodology/approach The study uses logistic regressions to examine the likelihood of paying dividends and the timing of repurchases and OLS regressions to examine the level of payout. Findings The fraction of dividend‐paying firms declines from 1988 to 2001 and then slightly rebounds until the end of the sample period in 2006. Firm size, profitability, investment opportunities, and catering incentives explain the likelihood of paying dividends. Unlike US firms, Canadian repurchase‐only firms do not become important payers in terms of either the percentage of firms or the level of payout. Dividend‐only firms pay out significant amounts of cash. Firms with both regular dividends and regular repurchases pay out the largest amount. The payout of different groups of payers is determined by their earnings. Testing firms with both regular dividends and regular repurchases reveals that earnings, undervaluation, and availability of cash explains the timing of repurchases but earnings mainly explains the level of repurchases. Research limitations/implications Canadian data are unavailable after 2006, which precludes investigating the potential implications of the financial crisis beginning in 2007. Originality/value This is the first paper to analyze the evolution of the relationship between payout and earnings in Canada.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.211
Teacher spread0.197 · 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

Citations13
Published2013
Admission routes2
Has abstractyes

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