Bibliographic record
Abstract
This study examines the behaviour of monetary policy in Canada over the last 40 years using a Markov-switching VAR model of the macroeconomy. The Markov-switching estimates capture three continuous regimes that are interpreted as the ‘surprise’ regime from 1972Q1 to 1982Q2, the ‘recovery’ regime from 1982Q3 to 1991Q3 and the ‘target’ regime from 1991Q4 to 2014Q4. Monetary policy multipliers for the output gap are greater than one for all three regimes, suggesting that the central bank does not accommodate any expected changes in inflation over the long-run due to the domestic relationship between the output gap and future inflation. The long-run multipliers for inflation are equal to one in the surprise and recovery regimes, indicating that monetary policy also responds to offset inflation shocks. Overall, the policy multipliers and impulse response functions indicate a proactive central bank that responds systematically to movements in the output gap in order to control expected future inflation and to inflation surprises in the three regimes. The regime-dependent behaviour of monetary policy indicates a central bank pursuing an implicit form of inflation targeting as a means of achieving a nominal anchor for policy. The implicit inflation targets are consistent with historical episodes of inflation in Canada over the past 40 years.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".