Corporate Governance and Fair Value Accounting: An International Perspective
Bibliographic record
Abstract
The overall objective of this dissertation is to investigate the interface between both firm- and country-level corporate governance mechanisms and fair value accounting for a sample of international financial institutions in the post-financial crisis period. In order to meet this objective, I conduct two studies investigating different aspects of the fair value hierarchy and the role of corporate governance. \n \n\tThe first study investigates the impact of firm- and country-level corporate governance mechanisms on the relevance and reliability of the estimates provided by the fair value hierarchy. This is examined for a sample of publicly listed banks from Canada and the European Union and extends the scant literature on the interface between corporate governance and fair value accounting. The results show that, contrary to prior research, investors do not consider level 3 fair value estimates to be reliable enough to be incorporated into firm value and thus, are not value relevant. Further testing, however, reveals that corporate governance mechanisms act in such a manner as to increase the perceived reliability of level 3 fair value estimates such that investors do consider them to be value relevant. Moreover, the results suggest that, in the context of value relevance decisions, firm- and country-level governance mechanisms act as substitutes for one another. \n \n\tThe second study investigates the potential for the fair value hierarchy to act as an alternative vehicle for earnings management in banks, and the role that firm- and country-level corporate governance plays in impacting the relationship between two competing earnings management methods. Extant earnings management literature on financial institutions focuses on the use of the loan loss provision to manage earnings. However, the recent change in accounting standards towards fair value accounting has provided an alternative vehicle for earnings management, specifically through level 2 and level 3 fair value measurements. The results show that level 2 fair values do not appear to be a viable tool to manage earnings. However, after accounting for the effect of either firm- or country-level corporate governance, the results suggest that level 3 fair values can act as an alternative earnings management tool. Managers faced with high (low) governance report lower (higher) levels of discretionary loan loss provisions as the proportion of level 3 assets increases. Moreover, additional analyses provide preliminary results suggesting that, in the context of earnings management, firm- and country-level governance mechanisms act as complements for one another.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".