Is Real Earnings Smoothing Harmful? Evidence from Firm‐Specific Stock Price Crash Risk
Bibliographic record
Abstract
Abstract This study examines whether and when real earnings smoothing influences firm‐specific stock price crash risk. Using a sample of U.S. public firms for the years 1993 through 2014, we find real earnings smoothing to be positively associated with firm‐specific stock price crash risk. This finding is consistent with the view that real earnings smoothing helps managers withhold bad news, keep poor‐performing projects, conceal resource diversion, and engage in ineffective risk management, which increases crash risk. Further, we find a stronger relation between crash risk and real earnings smoothing when firm uncertainty is higher, product market competition is lower, and balance sheet constraint is higher. Overall, our study suggests that real earnings smoothing destroys shareholder value in that it increases stock price crash risk.
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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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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".