Joint Effects of Principles-Based versus Rules-Based Standards and Auditor Type in Constraining Financial Managers’ Aggressive Reporting
Bibliographic record
Abstract
ABSTRACT: Managers sometimes implement accounting standards (such as the lease standard) opportunistically to move debt off balance sheet. Regulators and standard-setters are considering the adoption of principles-based accounting standards to reduce such opportunism. We report the results of an experiment in which experienced financial managers, with incentives to structure a transaction off balance sheet, take a reporting position on how a lease is to be reported. We manipulate the type of accounting standards (principles-based, rules-based) and the type of auditor (principles-oriented, rules-oriented, or client-oriented). Results show that for a rules-based standard, auditor-type does not influence participants’ propensity to report the transaction off balance sheet. However, for a principles-based standard, auditor-type matters in that this propensity is lowest when the auditor is principles-oriented as opposed to rules- or client-oriented. Our results suggest that a move toward more principles-based standards is likely to result in improved financial reporting quality only when there is a corresponding shift in auditors’ mindsets toward being more principles-oriented.
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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 | 0.020 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".