Internal Deficit–External Deficit Nexus in Africa: 1960-2012
Bibliographic record
Abstract
In this article, we have tested the causality correlation linking the internal deficit with the external deficit for a group of 15 African economies. Specifically, using causality analysis, we have tested the four possible causation linkages: (1) internal deficit causes external deficit, (2) there is bidirectional causality linking the two variables, (3) the two deficits are not causally related and (4) external deficits cause internal deficits. Using linear panel causality, this paper shows with heterogeneous Granger causality analysis that in five African countries, Côte d’Ivoire, Gambia, Morocco, Democratic Republic of Congo and Tunisia, external deficit Granger caused internal deficit. Two countries, Nigeria and Egypt, postulate causality from internal deficit to external deficit. While one country, South Africa, reveal a bidirectional causal link between internal deficit and external deficit. Monetary policies focused on the efficiency, as well as the exchange rate, will help to re-build, harmonize and control the budget policy in African countries.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".