Does proximity to corporate headquarters enhance directors' monitoring effectiveness? A look at financial reporting quality
Bibliographic record
Abstract
Abstract Research question/issue In this study, using a unique Canadian setting that relies on a principle‐based corporate oversight environment and that has access to a large pool of U.S. directors, we investigate how directors' proximity to a firm's headquarters influences its financial reporting quality. Research findings/insights Our results show that financial reporting quality is higher for firms whose boards (audit committees) consist of a greater proportion of independent directors who reside close to a firm's headquarters than for firms whose boards consist of directors who are more geographically dispersed. However, among nonlocal directors, the effect of nonlocal domestic directors on financial reporting quality is similar to the effect of local directors. In contrast, compared with local directors, the presence of U.S. directors has a negative impact on financial reporting quality. Theoretical/academic implications Our results suggest that directors' proximity to corporate headquarters extends beyond geographical proximity and also reflects directors' familiarity with a firm's institutional environment. Institutional familiarity helps domestic nonlocal directors reduce information costs associated with low geographical proximity, thus providing them with access to a wider range of information sources and enhancing their monitoring ability, at least for financial reporting. In contrast, foreign directors face information costs arising from both low geographical proximity and less familiarity with the institutional environment. Practitioner/policy implications Firms should take into consideration the consequences of nominating nonlocal directors on the monitoring of financial reporting quality. In addition, regulators should take a more comprehensive approach if they impose regulations such as board diversity initiatives, as regulatory pressures often imply appointing directors farther away from headquarters.
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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 | 0.007 | 0.052 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".