Monetary aggregates as indicators of economic activity in Canada: empirical evidence
Bibliographic record
Abstract
Empirical evidence linking monetary aggregates to variables such as inflation and economic growth has weakened over the past two decades. In this study we re‐examine these relationships by creating composite monetary aggregates that switch among existing monetary aggregates, using quarterly data over the sample 1971–99. Overall, composite monetary aggregates appear to be useful in explaining or forecasting short‐run movements in GDP growth and inflation. Also, the most successful composite monetary aggregates produce switch dates that overlap with the introduction of financial innovations. These subsequently prompted the Bank of Canada to revise or introduce new monetary aggregates. JEL Classification: E51, E52, C52, C53 Les agrégats monétaires en tant qu'indicateurs de l'activitééconomique: résultats empiriques. Les résultats empiriques jaugeant les liens entre les agrégats monétaires et des variables telles que l'inflation et la croissance économique montrent que ces liens se sont affaiblis au cours des deux dernières décennies. Ce mémoire examine ces relations en créant des agrégats monétaires composites qui se déplacent entre les agrégats usuels selon certains critères statistiques. L'étude utilise des données trimestrielles pour la période 1971–99. Dans l'ensemble, les agrégats monétaires composites semblent plus utiles pour expliquer ou prévoir les mouvements à court terme dans le niveau de croissance du PIB et de l'inflation. De plus, les agrégats monétaires composites qui ont le plus de succès suggèrent des moments de déplacement qui correspondent à des discontinuités marquant la mise en place d'innovations financières. Celles‐ci ont entraîné la Banque du Canada à reviser les agrégats monétaires usuels ou à en suggérer de nouveaux.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".