Companies' ethical certification and their attractiveness to institutional investors: An intermediate signaling perspective
Bibliographic record
Abstract
Abstract Our research investigates how the inclusion of a company on an independent ethics index affects its attractiveness to institutional investors. Using a sample of 864 U.S. firms over the 2010–2018 period, we find that institutional investors significantly increase their holdings in companies in the quarter that they are included on the ethics index and maintain larger holdings in the four quarters following the inclusion on the Ethisphere list relative to pre‐inclusion period, with dedicated institutional investors being more swayed to invest than transient investors. This paper adds to the emerging literature on intermediate signaling by showing that a firm's inclusion on an ethics index reduces information asymmetry with institutional investors. Our evidence suggests that public companies should effectively, rather than ceremonially, adopt sound governance structures and invest in socially responsible activities, as these actions can increase their likelihood of being included on ethics indices. By doing so, these firms send credible signals about their ethical compass, granting them access to valuable institutional investments.
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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 | 0.012 | 0.013 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".