Hedge Fund Ownership, Board Composition and Dividend Policy in the Telecommunications Industry
Bibliographic record
Abstract
This paper examines the impact of hedge fund ownership, mutual fund ownership, board composition and large block ownership on the dividend policy of telecommunications firms. The paper is intended to test the agency cost hypothesis for dividends, in which dividends serve as a substitute control mechanism in circumstances in which shareholder control has been attenuated. The evidence suggests that hedge fund ownership serves as a substitute for dividends as a corporate control mechanism to alleviate agency problems. However, the same case cannot be made for mutual fund ownership. The evidence also suggests that board independence increases the likelihood and the magnitude of a dividend payout. Furthermore, the results also indicate that the joint presence of independent boards and large shareholdings reduces the likelihood of a dividend payment. The latter two results suggest that greater independent board representation provides an effective medium for shareholders to extract dividends as well as a complement to top shareholder concentration in relieving agency costs. Overall, the results provide ample support for an agency-theoretic explanation of dividends.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".