Estimation of the Taylor Rule for Canada Under Multiple Structural Changes
Bibliographic record
Abstract
The Taylor rule is estimated under the period 1963Q2 to 1999Q4 using Canadian data and the methodology proposed by Bai and Perron (1998) to estimate regression models with multiple endogenous breaks. Although monetary rules are notorious for suffering from structural instability, recent attempts at modeling it are only considering exogenous breaks which are imposed on the data generating process (e.g. Judd and Rudebusch, 1998; and Clarida, Galí and Gertler, 2000). We show that the monetary rule cannot be evaluated over this period without taking into account parameter instability and structural changes, re- flecting changes in monetary policy preferences. Infation is modeled as a Markov-Switching (MS) process to extract expectations, which we treat as the implicit infation target. To extract the potential level of output, we also use a MS process. Modeling the rule when allowance for two breaks is made (1978Q3 and 1988Q2) illustrates well the changing policy preferences of the Bank of Canada.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".