You get what you Pay for: The Effect of Top Executives’ Compensation on Advertising and R&D Spending Decisions and Stock Market Return
Bibliographic record
Abstract
Although there is literature on how top executives’ compensation influences general management decisions, relatively little is known about whether and how compensation influences advertising and research-and-development (R&D) spending decisions. This study addresses two questions. First, is there an incentive effect of long- versus short-term compensation on advertising and R&D spending? Second, is there a mediation effect of advertising and R&D spending on the relationship between long- versus short-term compensation and stock market return? The authors address these questions using a combination of ExecuComp, Compustat, and Center for Research in Security Prices data on 842 firms during the 1993–2005 period. They find that an increase in the equity to bonus compensation ratio is positively associated with an increase in advertising and R&D spending as a share of sales. Advertising and R&D spending as a share of sales also mediates the effect of equity to bonus ratio on stock market return. The authors discuss implications for top management seeking to mitigate myopic management of resources by employing compensation to incentivize a longer-term orientation for advertising and R&D spending to improve stock return.
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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 | 0.002 | 0.013 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".