CEO power, corporate social responsibility, and firm value: a test of agency theory
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore whether firms with powerful chief executive officers (CEOs) tend to invest (more) in corporate social responsibility (CSR) activities as the over-investment hypothesis based on classical agency theory predicts. Design/methodology/approach This paper tests an alternative hypothesis that if CSR investment is indeed an agency cost like the over-investment hypothesis suggests, then those activities may destroy firm value. Findings Using CEO pay slice (Bebchuk et al. , 2011), CEO tenure, and CEO duality to measure CEO power, the authors show that CEO power is negatively correlated with firm’s choice to engage in CSR and with the level of CSR activities in the firm. Furthermore, the results suggest that CSR activities are in fact value enhancing in that as firms engage in more CSR activities their value increases. Originality/value The first paper to study CEO power and CSR and their impact on firm value.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".