The association between CEO incentive rewards and 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
Purpose – The purpose of this paper is to investigate whether or not there is a link between CEO incentive-based compensation and earnings management and to examine how institutional environment's features influence such link. Design/methodology/approach – To test the predictions, the authors use a panel of 1,500 American, Canadian, British, and French firm-year observation over the period 2004-2008. Findings – The authors find a significant association between earnings management and CEO incentive-based compensation. Moreover, the analysis provides evidence that institutional factors are strong determinants of this association. Specifically, the results show that firms from countries within the Anglo-American corporate governance model, which provides greater protection of shareholder rights, ensures strict enforcement of law, and scores high on board oversight, tend to have lower level of earnings management. The analysis shows however, that beside the formal corporate governance quality, it is relevant to consider weaker shareholder protection and lower law enforcement indexes to explain earnings management in firms from countries within the Euro-Continental corporate governance model. Originality/value – This paper is the first to provide insights regarding the extent to which CEO incentive rewards imply management discretion and to indicate how much institutional features matter. The analysis contributes to two distinct strands of research. It extends prior research on the association between executive compensation and earnings management and adds to the literature demonstrating a relationship between institutional factors and financial decisions.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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