The Determinants of Tax Revenues: Empirical Evidence From Jordan
Bibliographic record
Abstract
The purpose of this study is to identify the determinants of tax revenues (TXR) in Jordan. The study covered the period (1990-2019) and used ARDL Bound test for co-integration, ARDL Long Run form, and ARDL Error Correction regression to examine the study hypotheses. The results of the bound test and co-integration equation (CointEq1) shows that there exists a long run relationship between (INDUST, LPCI, FD, FAID, GE, OPEN) and (TXR) in Jordan. The analysis results revealed that per capita GDP, fiscal deficit and government expenditure have a positive significant impact on tax revenues in the short run and long run. While, Foreign aids has a negative significant impact on tax revenues. Industrial sector Value added and economic openness have a positive significant impact in the short run while having a positive insignificant impact on tax revenues in the long run. The results explore that per capita GDP, fiscal deficit, foreign aids and government expenditure are good determinants for tax revenues in the short run as well as in the long run, while industrial sector value added and economic openness are good determinants in the short run. The findings suggest a reduction in government expenditure due to the upward trend in the fiscal deficit and public debt, and the continued increase in (GE) leading to more internal and external imbalances.
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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 | 0.002 | 0.010 |
| 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 | 0.001 | 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".