Bref aperçu d’un modèle à forme réduite de prévision de la dépense nationale brute au Canada
Bibliographic record
Abstract
This paper presents a critical evaluation of a St-Louis type monetarist reduced-form model for Canada. The model centres on two equations estimated over the 1957-1977 sample period. An expenditure equation relates the growth of nominal GNE to the rate of monetary expansion and to changes in autonomous expenditure. The split between real growth and inflation is modelled through a simple Phillips curve with adaptive expectations. The dynamic properties of the model are discussed, and illustrated with simulations of alternative monetary growth paths. The analysis reveals some disturbing characteristics of this type of model. For instance, the responses of GNE to money supply changes or to price shocks are not symmetrical though both represent the same shock to real money supply. The price response to a monetary shock, while more plausible than in most large macroeconomic models, remains inadequate since increased monetary expansion results in higher real money supply accompanying higher inflation. The author nevertheless leaves the impression that reduced form models are a useful starting point for econometric research; their limitations are only an invitation to further refinements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".