Cash flows, capital structure and shareholder value: Empirical evidence from Amman stock exchange
Bibliographic record
Abstract
The current study links the information contents of the three main financial statements in a balanced panel data model to empirically examine the effect of cash flows per share and capital structure on shareholder value. The results of the study are based on a sample of 270 firm-year observations from the Jordanian commercial banks and insurance companies that listed on Amman Stock Exchange (ASE) from 2011 to 2019. Based on the Fixed Effect Model (FEM) with Driscoll-Kraay standard errors, the empirical results show that cash flows from operating activities per share had a positive and significant relationship with shareholder value, whereas both the cash flows from investing and financing activities per share had negative but insignificant relationship with shareholders’ value. Results also show that capital structure had a negative but insignificant relationship with shareholder value. Finally, the results indicate that dividend per share had a positive and significant relationship with shareholder value. Accordingly, decision-makers should direct cash to efficient investment projects in order for cash outflows from investing activities to create value to shareholders and to generate positive cash flows from financing activities. Similarly, an appropriate capital structure should be selected to create value for shareholders.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".