Audit quality and the market value of cash: the role played by the Big 4 auditor in Latin America
Bibliographic record
Abstract
Abstract Despite the extensive discussion in the accounting literature regarding the importance of internal control for the proper allocation of corporate resources, little is known about the role of auditors as a governance mechanism in reducing agency costs related to cash resources. This study extends the literature that explores differences in audit quality by examining whether perceived audit quality, measured by the Big 4/non-Big 4 dichotomy, mitigates the value destruction associated with cash. To the extent that investors do not perceive Big 4 auditors, as opposed to non-Big 4 auditors, as effective in preventing the potential value destruction associated with cash holdings or enhancing the contribution of cash to firm value in Latin America, our article is the first to document that investors do not assign a statistically significant premium to the cash balances of Big 4 clients. The results hold after a series of robustness checks and additional analyses. Our article enriches the literature on audit quality, corporate governance and cash holdings by demonstrating no statistically significant influence of auditor choice on the value investors place on cash reserves in a weak legal environment, i.e., where minority shareholders are poorly protected. Our conclusions have important implications for investors and lenders looking to Latin America to diversify their investments, as our findings about audit quality can influence their investment decisions. This study also has practical implications for the debate concerning the role played by audit quality.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 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".