Are dividends disappearing and is the life-cycle theory of dividends relevant to Canadian stock market?
Bibliographic record
Abstract
We investigated the dividend payout policy of the companies listed in the Canadian stock market to establish the relevancy of life-cycle theory of dividends among the sample stocks. While investigating whether dividend is disappearing in the Canadian stock market, we analyzed the proportion of firms paying cash dividends as in Fama and French (2001) and the aggregate real dividends paid by industrial firms as in DeAngelo, DeAngelo and Skinner (2004). Our sample ranges from 182 firm-years data in 1997 and to 999 firm-years in 2007. For the life-cycle theory of dividends, we also estimate a firm’s stage in its financial life cycle by the amount of its retained earnings as in DeAngelo, DeAngelo and Stulz (2006). Our findings indicate that proportion of dividend paying firms to total firms is on a decline but the aggregate real dividends of dividends payers is increasing. Our findings support the view provided by DeAngelo et. al. (2004) that dividends in Canadian listed firms are not disappearing. In addition, we report a positive and statistically significant relationship between the probability that a firm pays dividends and its earned/contributed capital mix, thus supporting the life-cycle theory of dividends.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".