Earnings Management to Avoid Financial Distress and Improve Profitability: Evidence from Jordan
Bibliographic record
Abstract
Due to unstable economic and political conditions, many companies in the Middle East are undergoing various financial distress and decline in profitability. This paper examines the role of earnings management to avoid financial distress and improve profitability in 58 industrial corporations listed on Amman Stock Exchange for a period of 2011 to 2016, which constitutes 89% of the whole population. The total number of observations is 413 for the entire study period. The study uses a cross-sectional Jones model that was modified by (Kothari, Leone, and Wasley, 2005); to measuring discretionary accruals that used as a proxy for earnings management.The empirical results indicate that earning management is not affected by the Altman’s Z-score index, but it has a positive relationship with debt to equity ratio. This study also shows a positive relationship between earnings per share, returns on equity, and earnings management. Regarding the control variable, we found a negative relationship between cash flow from operation and discretionary accruals.
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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 | 0.001 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".