Dividend payout and executive compensation: theory and Canadian evidence
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.
Bibliographic record
Abstract
Purpose This paper seeks to present and test a model of the association between dividend payout and executive compensation. Design/methodology/approach The authors develop a model based on Bhattacharyya whereby managerial quality is unobservable to shareholders, and therefore first‐best contracts are not possible. In the second‐best world, compensation contracts motivate high quality managers to retain and invest firm earnings, while low quality managers are motivated to distribute income to shareholders. These hypotheses arising from the model are tested on data for Canadian firms' dividend payouts over the period 1993‐1995 using tobit regression analyses. Findings Consistent with the predictions of the Bhattacharyya model, the results show that, ceteris paribus , earnings retention (dividend payout) is positively (negatively) associated with executive compensation. These results hold when payout is defined as common dividends plus common share repurchases. Research limitations/implications The Canadian data provide only limited information on the components of executive compensation. A more useful test would be possible with more detailed information on, for example, salary, bonus, and benefits. Originality/value Several recent papers have documented an association between dividends and executive compensation. This paper presents and tests a model that provides a potential explanation for this link.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it