Panel Data Approach of the Firm’s Value Determinants: Evidence from the Jordanian Industrial Firms
Bibliographic record
Abstract
<p class="zhengwen">This study aimed to investigate the main determinants of the industrial firms' value in developing countries namely Jordan. To achieve this goal all 77 ASE listed industrial firms for the period from 2000 to 2014 were utilized resulting in 974 firm-year observations. Twelve firm specific variables, namely, firm's size; firm's age; firm's risk level; firm's sales revenue; firm's operating cost; firm's tax rate; firm's net margin; firm's capital expenditure; firm's book value; firm's earning per share; firm's dividend per share and firm's pay-out ratio, were tested as a possible determinates of the firm's value. After testing for Multicollinearity and Heteroscedasticity the result of the unbalanced panel data Multi-regression model approach shows that the joint effect of the twelve potential determinants interprets about 37% of the variation in the value of the Jordanian industrial firms listed at ASE (R-squares = 0.3682), therefore, firm's in developing countries like Jordan should concentrate on these specific variables of the firms in order to improve the value and thus the wealth of the shareholders<strong>. </strong></p>Another finding of the study is that the firm's risk level and tax rate are not statistically significant drivers of the Jordanian industrial firm's value. The findings of the effect of firm's risk level and tax rate on the firm's value were contrary with Tiwari Ranjit et al (2015) and Rappaport (1998) respectively.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.001 |
| 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".