Do Firms Mimic Industry Leaders’ Accounting? Evidence from Financial Statement Comparability
Bibliographic record
Abstract
ABSTRACT Following management theory on organizational legitimacy, we predict that managers mimic the accounting of industry-leading companies to gain legitimacy. Such demand for legitimacy is expected to be greater for new managers because stakeholders are more uncertain about the managers’ ability. Using a sample of CEO turnovers, we find that a firm increases financial statement comparability with industry leaders after the new CEO assumes office. This relation is stronger when (1) new managers lack executive experience at larger firms, are younger, or belong to an underrepresented group (i.e., are female or nonwhite); (2) networks that facilitate imitation are more intense, such as when firms and peers are located in the same metropolitan statistical area (MSA) and when they share auditors or blockholders; and (3) firms’ operating environments are more volatile. These findings support the idea that CEOs’ demand for legitimacy leads to more comparable accounting. Data Availability: Data are available from the public sources cited in the text.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.009 |
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; both teacher heads agree on what is shown here.
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".