Beyond earnings: do EBITDA reporting and governance matter for market participants?
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 formally disclosing an earnings before interests, taxes, depreciation, and amortization (EBITDA) number reduces the information asymmetry between managers and investors beyond the release of GAAP earnings. The paper also assess if EBITDA disclosure enhances the value relevance and the predictive ability of earnings. Design/methodology/approach The authors explore the interface between GAAP and non-GAAP reporting as well as the impact of corporate governance on the quality of non-GAAP measures. Findings Results suggest that EBITDA reporting is associated with greater analyst following and with less information asymmetry. The authors also document that EBITDA reporting enhances the positive relationship between earnings and stock pricing as well as future cash flows. Moreover, it appears that corporate governance substitutes for EBITDA reporting for stock markets. Hence, EBITDA helps market participants to better assess earnings valuation when a firm’s governance is weak. Inversely, when governance is strong, releasing EBITDA information has a much smaller impact on the earnings-stock price relation. Originality/value The authors revisit the issue of how corporate governance relates with earnings quality by considering the potentially confounding effect of EBITDA reporting; it appears that such reporting substitutes for governance in moderating the relation between governance and earnings quality.
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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 | 0.001 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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