A Two Sector Small Open Economy Model. Which Inflation to Target
Bibliographic record
Abstract
This paper analyses welfare-improving monetary policy reaction functions in the context of a new-Keynesian small open economy model with a tradables and a non-tradables sector. The model is estimated for the case of Canada and used to evaluate the welfare gains of alternative specifications of the feedback nominal interest rate rule, in particular when allowing for different coefficients on the sectorial inflation rates. We find reasonable estimates for the deep parameters of the model , which include significant heterogeneity in the degree of price rigidity across sectors, as well as reasonable quantitative responses to sectorial and aggregate variables to local and foreign shocks. We find welfare gains in responding somehow more aggressively to aggregate inflation deviations from target than it has been the case in the last three decades and substantial welfare losses if the Bank of Canada aimed at stabilizing output more aggressively. But we find substantial further welfare gains of being more aggressive on imported inflation than on domestic sectors inflation since it is imports prices those that show a higher level of estimated stickiness
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".