The Relationship Between Earnings Management and Inventory Management in Emerging Markets: The Case of Moroccan Companies Listed on the Casablanca Stock Exchange
Bibliographic record
Abstract
This study examines how inventory management influences accrual-based earnings management in emerging markets. Specifically, it analyzes the effect of three inventory performance indicators—Inventory Turnover Ratio (ITR), Inventory Service Level (ISL), and Inventory Coverage Rate (ICR)—on discretionary accruals (AVDA), measured as the absolute value of discretionary accruals estimated using the Kothari model. The Moroccan context offers a relevant setting due to the scarcity of research linking operational supply-chain metrics to financial reporting practices in emerging economies. The empirical analysis relies on 321 firm-year observations from 41 non-financial companies listed on the Casablanca Stock Exchange between 2016 and 2023. A panel fixed-effects regression model is employed to assess the association between inventory indicators and AVDA. Results show a significant negative relationship between ISL and discretionary accruals, while ITR and ICR exhibit no significant effects. These findings indicate that higher inventory service reliability is associated with reduced earnings management, highlighting the governance role of inventory-related SCM practices in Morocco.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".