Auditor’s Downward Switch, Governance, and Accounting Conservatism
Bibliographic record
Abstract
This study demonstrates that the firms that switch from Big N auditors to non-Big N auditors use less accounting conservatism in the post-switch year relative to the year before switch. Our analyses further show that the decline in conservatism is mainly evident for the firms that switch to smaller non-Big N auditors, but not when the firms switch from Big N to second-tier national auditors, such as BDO Seidman and Grant Thornton (BDO/GT). In addition, we find that the firms experiencing switches from Big N to smaller non-Big N firms exhibit less accounting conservatism in the post-switch year when they have relatively weaker corporate governance. We also observe that both auditor resignation and auditor dismissal events lead to a significant decline in post-switch conservatism, especially among the firms with weaker governance mechanisms that experience switch to smaller non-Big N auditors. Furthermore, the smaller and younger firms with weaker governance adopt less conservatism in the post-switch period relative to the pre-switch period. Our findings complement prior research in this area and have policy implications that the quality of audits provided by smaller auditors may continue to remain a matter of concern in the post–Sarbanes–Oxley Act of 2002 (SOX) and post–Public Company Accounting Oversight Board (PCAOB) periods, especially when the firms have weaker governance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".