Canadian regional labour market evolutions: a long-run restrictions SVAR analysis
Bibliographic record
Abstract
Canada's high reliance on commodities can work against its constitutionally mandated goal of regional equity in economic development, while also inhibiting macroeconomic performance and limiting monetary policy effectiveness. Yet, flexible and integrated regional labour markets can help achieve both equity and macroeconomic goals. Therefore, this study examines the dynamics of Canadian provincial labour markets using a long-run restrictions structural vector autoregression (SVAR) model. Labour market fluctuations are decomposed into the parts arising from shocks to labour demand (new jobs), labour supply through migration (new people) and internal labour supply (original residents). The results suggest that demand innovations primarily underlie provincial labour market fluctuations. Despite significant geographic and language barriers that could impede their performance, there also is little overall evidence to suggest that provincial labour markets are more sluggish or less flexible than US state labour markets. Finally, original residents benefit slightly more from increased provincial labour demand compared to findings for US states.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".