April 2017 Annual Reassessment of Potential Output Growth in Canada
Bibliographic record
Abstract
This note summarizes the Bank of Canada’s annual reassessment of potential output growth, conducted for the April 2017 Monetary Policy Report. Potential output growth is projected to increase from 1.3 per cent in 2017 to 1.6 per cent by 2020. The lower estimate for potential output growth in the near term (relative to the 2016 assessment) largely reflects distinctly weak business investment over 2015 and 2016, as well as reallocation costs associated with the adjustment to lower oil prices. However, potential output growth improves throughout the projection as investment is expected to pick up, with an increasing share in productivity-enhancing machinery and equipment. Population aging will act as a drag on potential output growth, with a small offset coming from higher levels of immigration. An analysis of alternative scenarios suggests a range of potential output growth from ±0.3 percentage points in 2017 to ±0.5 percentage points in 2020.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".