Do U.S. Firms Have the Best Corporate Governance? A Cross-Country Examination of the Relation between Corporate Governance and Shareholder Wealth
Bibliographic record
Abstract
We compare the governance of foreign firms to the governance of similar U.S. firms.Using an index of firm governance attributes, we find that, on average, foreign firms have worse governance than matching U.S. firms.Roughly 8% of foreign firms have better governance than comparable U.S. firms.The majority of these firms are either in the U.K. or in Canada.When we define a firm's governance gap as the difference between the quality of its governance and the governance of a comparable U.S. firm, we find that the value of foreign firms increases with the governance gap.This result suggests that firms are rewarded by the markets for having better governance than their U.S. peers.It is therefore not the case that foreign firms are better off simply mimicking the governance of comparable U.S. firms.Among the individual governance attributes considered, we find that firms with board and audit committee independence are valued more.In contrast, other attributes, such as the separation of the chairman of the board and of the CEO functions, do not appear to be associated with higher shareholder wealth.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".