Is One Head Better Than Two? Dual Leadership and Firm Performance During the <scp>COVID</scp>‐19 Crisis
Bibliographic record
Abstract
We provide novel evidence on the value of combined CEO and board chair positions (CEO duality) for firms during the COVID‐19 pandemic in 2020. Based on 4,840 firm‐quarter observations from 1,210 unique firms in the US, we show that CEO duality firms outperformed non‐duality firms by a 0.58% margin in quarterly return on assets in 2020, which is equivalent to an incremental annual net profit of US$164 million. A difference‐in‐difference estimation confirms that the benefit of CEO duality is observed only in the COVID‐19 crisis period. Our main finding is robust to potential endogeneity concerns and alternative performance measures. Additional analyses show that the positive impact of CEO duality stems from the mechanisms of operating cost savings and working capital optimization during the crisis. Our finding underscores the benefit of CEO duality when economic uncertainty is high and a speedy decision is important.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".