ASSET PRICES AND MONETARY POLICY: A CANADIAN PERSPECTIVE ON THE ISSUES
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The issue addressed in this article is the extent to which monetary policy in Canada should respond to asset-price bubbles. The article concludes that maintaining low and stable consumer price inflation is the best contribution that monetary policy can make to promoting economic and financial stability, even when the economy experiences asset-price bubbles. In extreme circumstances--when an asset-price bubble is well identified and likely to have significant costs to the economy when it bursts--monetary policy might better maintain low and stable consumer price inflation by leaning against a particular bubble even though it may mean that inflation deviates temporarily from its target. Such a strategy might reduce the risk that a crash in asset prices could lead to a recession and to inflation markedly below target in the longer run. The circumstances where this strategy is possible will be rare because economists are far from being able to determine consistently and reliably when leaning against a particular bubble is likely to do more harm than good. Housing-price bubbles should be a greater concern for Canadian monetary policy than equity-price bubbles, since rising housing prices are more likely to reflect excessively easy domestic credit conditions than are equity prices, which are largely determined in global markets.
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.
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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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 it