Bibliographic record
Abstract
This study describes a semi-structural New-Keynesian Quarterly Projection Model (QPM) for the WAEMU zone. In the context of a fixed exchange rate regime and relatively tight capital controls, the central bank for the WAEMU monetary union (Banque Centrale des États de l’Afrique de l’Ouest, BCEAO) can exert some influence on the domestic money markets and interest rates. We adjusted the canonical version of a New Keynesian semi-structural Quarterly Projection Model (QPM) to capture that feature and other aspects specific to the BCEAO monetary policy framework, including an implicit foreign exchange reserve target. The model, which is parametrized though and mix of calibration and Bayesian estimation techniques, displays dynamic properties for the main variables in response to various shocks that are in line with theoretical priors and empirical evidence. Medium-term forecasts considering the Covid-19 pandemic produce sensible results when compared with forecast produced by a standard VAR. Moments computed from artificial data generated with the model match well those observed in the data. Overall, the model displays desirable analytical properties and sensible data-matching and forecasting capabilities and could, therefore, be used by the BCEAO to identify relevant shocks, map their propagation into the WAEMU regional economy, and better support its monetary policy decisions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".