Financial Stress, Monetary Policy, and Economic Activity: A Nonlinear Approach
Bibliographic record
Abstract
This paper examines empirically whether financial stress conditions play a role as a nonlinear propagator of monetary policy shocks. This propagation takes the form of a threshold vector autoregression in which a regime change occurs if financial stress conditions cross a critical threshold. Using nonlinear analysis methods, we examine questions like: Does monetary policy have the same effect on the real economy in the low financial stress regime and high financial stress regime? Suppose that the economy be currently in a given financial stress regime, does monetary policy shock have a substantial effect on the transition probability from the given regime to another. As suggested among the findings in this paper, contractionary monetary shocks typically have a larger effect than expansionary monetary shocks, and large contractionary monetary shocks have larger effects on output in the high financial stress regime than do in low financial stress regime. Large contractionary monetary shocks increase the likelihood of being in the high financial stress regime. The authors would like to thank.... The authors also thank seminar participants at the Bank of Canada,... The views expressed in this paper are those of the authors. No responsibility for them should be attributed to the Bank of
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".