The Valuation‐relevance of Earnings and Cash Flows: an International Perspective
Bibliographic record
Abstract
We investigate which variable, earnings or cash flows, provides greater information for equity valuation within the United States, the United Kingdom, Canada, Germany, and Japan. We regress returns on earnings and cash flow metrics. We generally find earnings developed in three Anglo‐Saxon countries—where capital is traditionally raised in public markets and reporting rules are unencumbered by taxation requirements—to have greater explanatory power for stock returns than cash flow metrics. Conversely, in two non‐Anglo‐Saxon countries—where capital is traditionally raised from private sources—earnings are generally not superior to cash flows for equity valuation, except in Japan, non‐consolidated sample. While sensitivity analyses generally support the conclusions of our primary tests, in some of the additional analyses, earnings were superior to cash flows for samples from all countries. As expected, in all countries earnings have incremental information content over cash flows in explaining returns. Collectively, our findings provide two contributions. First, we generalize the findings of prior US research by showing that earnings are more important than cash flows for equity valuation in other Anglo‐Saxon countries. Second and more importantly, our findings demonstrate that the superiority of earnings over cash flows is not universal. Rather, it depends on the national reporting regime and attendant institutional factors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".