A Panel Data Analysis of Jordan’s Foreign Trade: The Gravity Model Approach
Bibliographic record
Abstract
This study aims to identify the most important factors affecting the flow of Jordanian foreign trade, with its main trading partners for the period (1995-2016). To achieve this objective, the gravity model was adopted using a random effects model. The empirical findings show that Jordan’s foreign trade is positively determined by Jordan’s RGDP and dummy variable that used to capture the effect of a common border with Jordan. On the other side, distance and similarity index are found to be significant factors in influencing Jordanian foreign trade negatively. Finally, the study found that the RGDP of trade partner and bilateral real exchange rate are not statistically significant. empirical evidence linking bank customers’ participation in financial ads to their attitude. Managerially, this study informs bank managers regarding effective management of financial advert contents in order to influence bank customer’s attitude towards financial adverts.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 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".