Does Cash Flows Useful in Predicting the Company’s Financial Health? Empirical Validation by Panel Cointegration Tests
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Bibliographic record
Abstract
Abstract The aim of this article is to test the usefulness of cash flows as a measure of companies' financial health. Our approach is different from the previous studies which have animated the debate on the comparison of the explanatory power between accrual and cash-flow. Indeed, we use current developments in cointegration tests on non-stationary dynamic panel data to test the existence of a long-run equilibrium relationship between a ratio based on cash flows (i.e., operating cash flow to total assets ratio) and four financial ratios based on accounting data, namely: working capital to total assets ratio, asset turnover ratio, return on assets ratio, and debt-assets ratio. These four financial ratios are commonly known as relevant indicators regarding the company's financial health regarding its liquidity, operational efficiency profitability, and solvency. Precisely, the panel unit root tests (Im, Pesaran, and Shin (2003)) and the panel cointegration tests (Pedroni (2004)) are applied on a sample of 150 American firms over the period 2010-2017. Our main results led to conclude that the cash flow has an informational content and a significant explanatory power in the prediction of the company’s financial health. We provide some explanations for these findings which are supported by a robustness analysis using panel error correction models (PECM). JEL classification numbers: G30, G33, L25, M10. Keywords: Cash flows, Accruals, Financial health, Explanatory power, Panel cointegration tests.
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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 | 0.000 |
| 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 | 0.000 | 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