On the Nexus of Monetary Policy and Financial Stability: Recent Developments and Research
Bibliographic record
Abstract
Because financial and macroeconomic conditions are tightly interconnected, financial stability considerations are an important element of any monetary policy framework. Yet, the circumstances under which it would be appropriate for the Bank to use monetary policy to lean against financial risks need to be more fully specified (Côté 2014). The extent to which financial stability concerns should be taken into account by monetary policy will be a priority topic of research at the Bank for the renewal of the inflation-control target agreement in 2016. This paper reviews four considerations of interest, taking stock of key domestic and international developments and knowledge gained over the past few years: (i) Canada and other countries have made significant progress in the implementation of micro- and macroprudential regulatory reforms, and limited existing research finds that most of these policies were effective in reducing the potential need for leaning by monetary policy; (ii) the effectiveness of the monetary policy transmission mechanism depends on the state of the financial system, implying that financial system conditions need to be taken into account by monetary policy; (iii) although exceptionally low interest rates and other forms of monetary stimulus are sometimes needed to support growth and achieve inflation-target mandates, they may lead to excessive risk-taking activities and therefore contribute to the buildup of financial imbalances; and (iv) coordination of monetary and macroprudential policies for dealing with imbalances may, in some circumstances, be beneficial. The paper concludes by identifying future areas of research to further clarify the role of monetary policy in addressing financial stability risks.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".