An Investigation Of Investors’ Use Of Reported Cash Flow And Accrual Information For Eight Countries
Bibliographic record
Abstract
Using 1995 through 1999 data from the United States and seven other countries with different sets of national accounting standards (Canada, France, Germany, Hong Kong, Japan, Malaysia, and the United Kingdom), we test whether the cash flow component of earnings is more persistent than the accrual component, and then whether the relative persistence of these two earnings components is reflected in stock market returns. Using the Mishkin model employed by Sloan (1996) to test the data for each of the countries, we find that, while reported cash flows are significantly more persistent than accruals in each of the eight accounting regimes, Canadian companies are the only ones for which the pricing of equity securities is clearly efficient with regard to cash flow and accrual information. While there is some evidence for this stock market efficiency for the UK and German companies, it is not conclusive. For firms from France, Hong Kong, Japan, Malaysia, and the United States, the differences observed between the persistence of cash flows and accruals are not reflected in stock prices.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".