Audit Quality and Financial Reporting Quality of Quoted Manufacturing Firms in Nigeria
Bibliographic record
Abstract
The quality of financial reports has been a contemporary discuss in accounting and finance literature as it is capable of helping investors or the users of financial statement to make timely and informed economic decision. Financial statement should portray features like relevance, faithful understandability and timeliness. The reporting quality from literature is seen not to possess the relevant qualities as expected which has become worrisome for investors and stakeholders. The study investigated the effect of audit quality on the financial reporting quality of quoted manufacturing firms listed in Nigeria, employing a survey research design. The population of interest consisted of 250 auditors and accountants, with a sample size of 201 selected using the Taro Yamane Formula and purposive sampling. Data were gathered through a well-structured questionnaire and analyzed using both descriptive and inferential statistics. Findings revealed that audit quality had a significant impact on the relevance of financial reports (Adj. R² = 0.766; F = 99.565; p = 0.00) and also notably influenced the faithful representation of financial reports (Adj. R² = 0.598; F = 47.930; p = 0.00). The study concluded that audit quality plays a critical role in enhancing the financial reporting quality of listed manufacturing firms in Nigeria. The study recommended that management should prioritize the presentation of financial reports to improve their relevance to users. Keywords: Audit Quality, Financial Reporting, Financial Statement, Faithful Representation, Relevance, Understandability
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".