Compensation transparency and managerial opportunism: a study of supplemental retirement plans
Bibliographic record
Abstract
Abstract Existing research on managerial compensation is based primarily on optimal contracting and managerial hegemony theories. Under the optimal contracting theory, observed compensation contracts are optimally determined, aligning the interests of managers and shareholders. Under the managerial hegemony theory, observed compensation contracts deviate from the optimum because top managers with power over boards are able to influence their own pay. I argue that the impact of managerial power over boards on managerial pay, and hence the deviation of compensation contracts from the optimum, is contingent on the transparency of managerial compensation. Within this framework, I investigate the impact of supplemental executive retirement plans (SERPs)— historically the least transparent compensation component— on opportunistic decision making. An empirical analysis based on a time series sample of CEOs of S&P/TSX60 firms provides support of the compensation transparency theory. I find that SERP benefits are primarily driven by variables proxying for CEO power over the board, whereas more transparent compensation components are primarily driven by economic factors. The results also suggest that CEOs whose SERPs are contingent on firm performance appear to reduce firm R&D expenditures as they approach retirement. Both findings provide important contributions to existing research on the impact of managerial compensation on opportunistic decisions. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.000 | 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) | 0.001 | 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".