Audit Profession Development and Bank Loan Contracting
Bibliographic record
Abstract
SUMMARY This study examines the relation between country-level audit profession development (APD) and bank loan contracting around the world. Using a sample of bank loan data from 35 countries, we find that stronger APD is associated with more favorable loan terms, such as lower loan spreads, fewer covenants, and larger loan amounts. These effects are stronger in countries with a weaker rule of law. We also find that stronger APD attracts significantly more lenders participating in loans and more foreign lenders leading loans. A breakdown of APD into three subcategories, namely, auditor education, auditor independence and liability, and auditor oversight, reveals that all three influence various contracting terms. We also provide evidence that stronger APD is associated with a higher degree of timely loss recognition. Collectively, our findings show that APD improves bank loan contracting terms. Data Availability: Data are publicly available from the sources mentioned in the manuscript. JEL Classification: F34; K20; M41; M42.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".