The Value of CEO Extraversion: Implications for CEO Pay and Firm Performance
Bibliographic record
Abstract
We study the effect of chief executive officer (CEO) extraversion on CEO pay. Integrating research on personality and career outcomes, we theorize that CEO’s pay and other career related outcomes will differ across more and less extraverted CEOs. We collected longitudinal data on a sample of 3,149 unique CEOs from 1,703 S&P 1500 firms from 2003 to 2013. To measure personality traits of CEOs, we used computerized text analysis on the language spoken by CEOs in the discussion portion of the quarterly earnings conference calls over a multi-year period (2003 to 2013). We find that, in comparison to less extraverted CEOs, more extraverted CEOs earn a significantly higher pay, they also earn higher relative pay vis-à-vis other top managers in the firm, and are also more likely to become first-time CEOs at a younger age. A one-unit increase in CEO extraversion is associated with a $233,260 increase in CEO’s total pay. Moreover, the effect of CEO extraversion on CEO pay is partially mediated by the size of CEO’s board network. Finally, consistent with the better fit explanation of the effect of CEO extraversion on CEO pay, we find that CEO extraversion has a positive impact on firm performance.
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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 | 0.016 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".