Trade Intensity, Fiscal Integration and Income Inequality in ECOWAS
Bibliographic record
Abstract
Abstract This paper analyzes the income inequality effect of economic integration in ECOWAS by decomposing economic integration into two dimensions: trade and fiscal integration approximated respectively by trade intensity and fiscal convergence. For robustness purposes, we use different metrics for each dimension. We also consider the introduction in the region of the growth and convergence pact in the analysis of fiscal integration effect on income inequality. The analysis covers the period 1990–2018. For the empirical evidence, the generalized method of moment is used. The results obtained are robust and reveal that improving regional economic integration has a reducing effect on income inequality. Taken individually, trade integration and fiscal integration contribute to reducing income inequality. However, taken together, the reducing effect of economic integration on income inequality is more pronounced. Besides, the results indicate that fiscal integration has more contributed to the reduction of income inequality since the introduction of the first fiscal convergence pact in the region in 2000 than before. For reducing income inequality, our analysis recommends to ECOWAS countries to take steps to remove barriers to regional trade on the one hand, and on the other hand, to converge together on the fiscal front.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".