Revenue, Trade and Welfare Effects Of the Comesa Free Trade Agreement on the Democratic Republic Of Congo
Bibliographic record
Abstract
Abstract The present research attempts to assess the likely revenue, trade and welfare implications of the Common Market for Eastern and Southern Africa (COMESA) Free Trade Agreement (FTA) on the DRC. The study adopts a partial equilibrium model as the methodological approach. The findings of the research reveal that the COMESA FTA will be beneficial to the DRC in terms of an increase in exports and consumer welfare gain. Moreover, The WITS-SMART simulation results indicate that trade will be created in the DRC as a result of the COMESA FTA. Notwithstanding the fact that trade creation will have a positive effect on welfare, as the Congolese consumers would benefit from lower prices, some local industries in the DRC may be threaten of closure due to the lack of competitiveness. In addition, the simultation results show that the country will experience a huge fiscal revenue loss due to the implementation of zero per cent tarrif rate on imports duty from the COMESA trading partners. Finally, the simultation results indicate that trade will be diverted from more efficient and low cost non-member states to high cost suppliers from the COMESA region. These findings shed light on policy implications.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".