Sub-Saharan African Countries’ Dependence on the External Inflation: Empirical Evidence Using Copulas
Bibliographic record
Abstract
The purpose of this study is to estimate the dependence between the inflation, given by the Consumer Price Index (CPI), in part of the Sub-Saharan African (SSA) countries with the CPI observed in the Euro Monetary Zone (EMZ) countries. To achieve this goal, we adopted the empirical methodology of Copulas, which was used in the analysis of the CPI, in bivariate models context. The results were controlled by the countries which adopted fixed and flexible exchange rate regimes. They suggest that the CPI in the sampled countries which adopted fixed exchange rate regimes, as Sao Tome and Principe, Benin, the countries of the West African Economic and the Monetary Union (WAEMU), Burkina Faso, Ivory Coast and Togo had more significant dependence relationship with the Euro. On the other hand, the countries which adopted flexible exchange rate regimes as Cape Verde, Burkina Faso, Guinea-Bissau, Mali, Senegal and Togo presented dependence on upper tail of the distribution, i.e., for the periods of increasing in the CPI. Maybe, it means that those countries had inelastic demands for tradable goods coming from the EMZ countries. We conclude that the imported inflation is an important issue to be considered by the policy makers of developing countries such as the studied, mainly for those which adopted fixed regimes, eventually change to flexible exchange regimes.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".