Highlighting Determinants of Financial Performance of the Jordanian Financial Sector: Panel Data Approach
Bibliographic record
Abstract
This study was aimed at identifying the main determinants of financial performance in Jordanian financial sector over 2005-2016 periods. Profitability ratio (return on equity) was used as a proxy of financial performance measurement. Meanwhile, firms’ specific variables, macroeconomic variables and non-economic factors were used as explanation variables. Panel data set for four sub-sectors of financial sector over the above period were used. Pooled OLS, Fixed effect, random effects techniques with Heteroskedasticity and Serial Correlation Robust Standard Error estimation methods were employed. The empirical results showed that liquidity and leverage were the key determinants of financial performance while risk, macroeconomic factors and non-economic factors do not affect the financial performance of financial sector in Amman Stock Exchange. Therefore, the results conclude that financial performance is mainly driven by firm specific factors (company characteristics). Thus, a sound financial performance can be obtained by giving attention to firm specific variables.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".