An empirical study of the relationship between the busy outside directors and indicators of ESG performance
Bibliographic record
Abstract
In this article, we analyse whether the management structure of a company plays a role in the sustainability of companies. More specifically, we study the impact of occupied outside directors, outside directors sitting on several boards of directors, on the environmental, social and governance (ESG) performance of the company. We collect information about board characteristics, information about the board and management from MSCI ESG Research and financial information from Compustat. The study collects data based on panel data, which ranges from 2014 to 2020. The final sample consists of 550 US companies over a five-year period and contains 3850 firm-year observations. The study finds a positive relationship between busy outside directors and ESG performance. Busy outside directors have a positive impact not only on the overall ESG score, but also on individual ESG components. The environmental score is most affected by busy external directors, while the governance score appears to be little affected. Contrary to the theory that busy outside directors are overly engaged and degrade the fixed value, the findings support the theory that busy outside directors improve a company's sustainability performance because of their engagement, experience and the ESG 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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".