Quality of audit and cost stickiness empirical evidence from emerging markets
Bibliographic record
Abstract
This study aims to present further evidence of cost stickiness by employing Selling, General, and Administrative (SG&A) costs. It also provides empirical evidence on the effect of audit committee meetings and audit quality on cost stickiness. The study used data from listed companies on the Saudi Arabian stock exchange during 2015–2019. Based on pooled panel data regression, the study proves that the SG&A costs are sticky. The results show the level of SG&A costs increases more with an increase in sales revenue (activity) while it decreases less with an equivalent reduction in sales revenue (activity). Also, this study finds that the frequency of audit committee meetings decreases the magnitude stickiness of SG&A costs, which supports the view that frequent meetings of AC significantly enhance its overseeing function and effectiveness. The study further reveals that audit quality “by BIG4 audit firms” is not related to reduced cost stickiness. This result implies that there is no difference in CS between companies audited by BIG4 or by non-BIG4. In general, the research highlights the importance of AC diligence (i.e., meetings) in improving its effectiveness and controlling management’s discretions affecting the cost structure in the context of sticky cost behavior.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".