Market Competition, Downward-Sticky Pay, and Stock Returns: Lessons from South Korea
Bibliographic record
Abstract
This study examines whether market competition reduces managerial slack under downward-sticky CEO pay schemes, thus mitigating the potentially negative link between downward-sticky pay and shareholder’s value. Using data on the Korean product market, which has been dominated by business conglomerates known as ‘chaebols’, we first find that downward-sticky pay is prevalent in underperforming firms and affects shareholder value negatively. Then, we find that a higher level of market competition alleviates the value-deteriorating effect of downward-sticky pay. Overall, the findings from our study imply that market competition as an external mechanism of corporate governance threatens still highly paid CEOs with worsening performance and motivates them implicitly to work harder. Together with a need for shareholders’ influence on downward-sticky pay, this study sheds light on the importance of market competition regimes in developing countries where legal protection for shareholders and internal governance structures are weak.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".