The performance and robustness of simple monetary policy rules in models of the Canadian economy
Bibliographic record
Abstract
Abstract. In this paper, we evaluate seven simple monetary policy rules in a wide range of models of the Canadian economy. Our results indicate that none of the seven simple policy rules we examined is robust to model uncertainty, in that no single rule performs well in all models. In fact, our results show that the performance of some of the simple rules, particularly rules with interest rate smoothing and rules with a high coefficient on the inflation gap, can substantially deviate from that of the optimal rule and can even be unstable in some models. Furthermore, we find that “open‐economy” rules do not perform well in many models. We find that adding an exchange rate term to a simple policy rule often increases the value of the policy‐maker's loss function. Although it is not robust, we find that a simple nominal Taylor‐type rule that has a coefficient of 2 on the inflation gap and 0.5 on the output gap outperforms the other simple rules in a certain class of models. However, even in those models, the loss‐function value of this simple rule can be substantially higher than that of the optimal or base‐case rule. JEL classification: E52, E58
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".