NAOMI/US A small-scale model of the U.S. economy
Bibliographic record
Abstract
This paper presents NAOMI/US (North American Open economy Macro-econometric Integrated model/US), the U.S. counterpart to NAOMI/Canada, developed with the objective of contributing to EAFD’s analytical and forecasting tools. It is a tractable system built around three main equations: IS curve, Phillips curve and monetary policy rule. The model exhibits a meaningful steady state, is forwardlooking and consistent with the structure of NAOMI/Canada. Despite its parsimony, it displays credible dynamics that are comparable to those from larger, more complex models. Ce papier introduit MIOAN/US (modèle Macro-économique Intégré de l'économie Ouverte de l'Amérique du Nord/US), la contrepartie américaine de MIOAN/Canada. Ce modèle a été développé dans l’objectif de contribuer aux outils d’analyse et de prévisions macroéconomiques relatifs à l’économie américaine de la division de l’analyse et de prévisions économiques. MIOAN/US est un modèle à attentes rationnelles qui repose essentiellement sur trois équations : une courbe IS, une courbe de Phillips et une règle de politique monétaire. Malgré sa parcimonie, les propriétés de simulation du modèle sont comparables à ceux des modèles plus complexes et plus détaillés.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".