The Dynamics Between Dividends, Financing and Investments: Evidence From Jordanian Companies
Bibliographic record
Abstract
Dividend decisions, Financing decisions and Investment decisions are three very imperative decisions taken by a firm. The effect of these decisions is on the performance of the firm which subsequently effects the valuation of the firm. These decisions in a firm are also influenced by the growth and status of the respective economy.The current research attempts to analyze the dynamics between these three major decision areas and also assess their relationship with the market value of the firm. These dynamics are further tested against the economic growth of the respective economy. Annual data for 50 companies from Jordanian economy for the time period 2007-2018 is used to achieve the objective. Basic and advanced statistical techniques such as regression analysis and Vector Auto Regression (VAR) have been used in the study. The sample involved 50 Jordanian companies.The study found that the value of the firm is affected by three key decisions (value drivers) of dividend, investment and financing and this effect is best measured at a lag of two years. Also the combined effect of the three value drivers is more than standalone effect.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".