The Doug Purvis Memorial Lecture—Monetary/Fiscal Policy Mix and Financial Stability: The Medium Term Is Still the Message
Bibliographic record
Abstract
Financial stability risks have become topical in the wake of the global financial crisis and the subsequent extended period of very low interest rates. This paper investigates the significance of the mix of monetary and fiscal policies for financial stability through counterfactual simulations of three key historical episodes, using the Bank's main policy model, ToTEM (Terms-of-Trade Economic Model). The paper finds that there is an intimate relationship between the monetary/fiscal policy mix and the dynamics of both private sector and public sector debt accumulation. No attempt is made to develop criteria for policy mix optimization, since it is clear from the model simulations that the appropriate policy mix is highly state-dependent. This finding points to the need for a coherent framework for weighing the relative financial and macroeconomic consequences of accumulating public sector versus private sector debt. Furthermore, the analysis suggests that there are potential benefits to ex ante monetary/fiscal policy coordination, and that Canada's policy framework—where the monetary and fiscal authorities jointly agree on an inflation target while enshrining central bank operational independence—represents an elegant coordinating mechanism.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".