Does CEOs Performance-based Compensation Waits on Shareholders? A Cross National Analysis
Bibliographic record
Abstract
The objective of the paper is to develop deeper insight into how the firm’s incentive systems are designed and, whether the CEOs compensation pay-to-performance schemes really align the incentives of executives and shareholders. Logit and Stepwise regressions on executive compensation data of 231 listed companies’ belongings to four countries from the Anglo-American and the Euro-continental corporate governance models over the period 2004-2008 show that pay-to-performance incentives serve likely shareholders as they tend to create value. Moreover, sensitivity analyses point out that their effects on the Long Term Total Shareholder Return (LTTRS) are far from unanimous. They often depend on the context in which they are planned and executed. More specifically, they are even large than the property rights are stripped, the institutional ownership is less restricted, the governance quality is better, the investor protection is high, and the legal system is common law one.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".