Forecasts in IPO Prospectuses: The Effect of Corporate Governance on Earnings Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Prior research suggests that managers may use earnings management to meet voluntary earnings forecasts. We document the extent of earnings management undertaken within Canadian Initial Public Offerings (IPOs) and study the extent to which companies with better corporate governance systems are less likely to use earnings management to achieve their earnings forecasts. In addition, we test other factors that differentiate forecasting from non‐forecasting firms, and assess the impact of forecasting and corporate governance on future cash flow prediction. We find that firms with better corporate governance are less likely to include a voluntary earnings forecast in their IPO prospectus. In addition, we find that while IPO firms use accruals management to meet forecasts; the informativeness of the discretionary accruals depends on whether or not the firm would have missed its forecast without the use of discretionary accruals.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it