Stakeholder orientation and accounting conservatism: Evidence from state-level constituency statutes
Bibliographic record
Abstract
• The adoption of state-level constituency statutes leads to a significant decrease in accounting conservatism. • The adoption effect is stronger for firms with greater agency conflicts between shareholders and nonfinancial stakeholders. • The adoption effect is stronger for firms with lower demand for conservatism from shareholders and debtholders. • The adoption of the statutes increases corporate policies that are more friendly to employees, customers, and suppliers. We find that the staggered adoption of state-level constituency statutes leads to a significant decrease in accounting conservatism. Constituency statutes allow directors to consider stakeholder interests when making business decisions, thereby increasing firms’ stakeholder orientation. As firms shift attention to stakeholder interests, stakeholders become less concerned about shareholder expropriation and thus demand less conservatism. Cross-sectional analyses show stronger effects for firms with greater agency conflict between shareholders and nonfinancial stakeholders (i.e., customers, suppliers, and employees) and for firms where shareholders and debtholders have lower demand for conservatism. In additional analyses, we find that the adoption of constituency statutes does allow firms to implement corporate policies that are more friendly to their employees, customers, and suppliers. We also show that the effect of constituency statutes on conservatism still holds when the statutes only cover nonfinancial stakeholders (but not debtholders).
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".