Shareholder‐ Versus Stakeholder‐Focused Japanese Companies: Firm Characteristics and Accounting Valuation*
Bibliographic record
Abstract
Abstract Recent research has found that the value‐relevance of accounting variables depends not only on whether a country's accounting rules are code‐law oriented or common‐law oriented, but also on the reporting incentives created by the legal and business environment in which a firm operates. Therefore, for example, the earnings of firms in some countries with common‐law oriented rules but with code‐law incentives have more code‐law‐type characteristics. We further this research by examining whether this is true for firms facing the same accounting regime and institutional environment but different stakeholder‐related incentives. We find significant stakeholder‐related incentives across 23 Japanese firms listed in the United States and 23 Japanese firms not listed in the United States that are matched by industry and size. Although these firms face the same institutional environment and the same accounting regime, consistent with the differences in stakeholder‐related incentives, the earnings and book values of the firms listed in the more shareholder‐oriented U.S. markets have significantly more explanatory power for market value than those for firms not cross‐listed in the United States. These findings are unaffected by whether the reports are based on consolidated or parent‐only accounting or whether they are based on U.S. or Japanese GAAP, emphasizing the potential influence of reporting incentives at all levels on the effect of standardization, conversion, or harmonization of accounting methods globally.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".