Financial Stress, Monetary Policy, and Economic Activity, Working paper
Bibliographic record
Abstract
This paper examines empirically whether financial stress conditions play a role as a non-linear propagator of monetary policy shocks in Canada. The model used is a threshold vector autoregression in which a regime change occurs if financial stress conditions cross a critical threshold. Using the financial stress index developed by Illing and Liu (2006) as a measure of the Canadian financial stress conditions, the authors examine questions such as: Do con-tractionary and expansionary monetary policy shocks have symmetric effects? Does monetary policy have the same effect on the real economy in the low financial stress regime and in the high financial stress regime? Suppose that the economy be currently in a given financial stress regime, do monetary policy shocks have a substantial effect on the transition probability from the given regime to the other? The empirical findings reveal that (i)contractionary monetary shocks typically have a larger effect on output than expansionary monetary shocks; (ii) the effects of large and small shocks are approximately proportional; (iii) contractionary monetary shocks have larger effects on output in the low financial stress regime than in the high financial stress regime; (iv)large contractionary monetary shocks increase the likelihood of moving to, or remaining in, the high financial stress regime.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".