Should the CEO Pay Ratio be Regulated
Bibliographic record
Abstract
Starting from January 2017, all publicly listed firms in the United States are required to disclose a pay ratio of annual CEO compensation to the median employee compensation (Pay Ratio). Opponents of this legislation have argued that this additional Pay Ratio disclosure would simply add to the costs of compliance without providing any new information to the market over and above the existing CEO Pay Slice variable, known as the ratio of CEO’s pay to top five executives’ compensation. Using hand-collected data, this paper finds that both variables are related to CEO power, but the Pay Ratio variable provides new and additional information over and above the Pay Slice variable. Furthermore, the Pay Ratio variable is more informative about the agency costs excessive CEO power imposes on shareholders. The cost of capital increases significantly as Pay Ratio increases and Pay Ratio dominates and eliminates the explanatory power of Pay Slice. Our empirical finding suggests that to understand the costs imposed on shareholders by excessive CEO power, we also need to pay attention to the Pay Ratio variable.
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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 | 0.018 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".