Finances of the Nation: The Global Financial Cycle and Canadian Bond Markets—Implications for Provincial Borrowers
Bibliographic record
Abstract
This article examines implications of the global financial cycle for Canada's public sector borrowers, with a particular emphasis on the borrowing conditions of Canadian provinces. It makes three broad points. First, even relative to other advanced economies, Canada, and the government of Canada in particular, has done well by the global financial cycle. In a world of trade imbalances and uncertainty, investors need safe assets, and Canada's wealth, political stability, and open capital markets have made government of Canada bonds a natural haven. Second, the provinces have also done well by the global financial cycle, but their bonds are riskier and less liquid than government of Canada debt, which explains why their spreads tend to increase with global volatility, and why, if volatility becomes too severe, the provinces occasionally struggle to borrow. Volatility-related premiums are lower among provinces with relatively large and liquid pools of debt, and higher—if the volatility is associated with a significant drop in oil prices—among oil-producing provinces. Third, the global financial cycle is evolving, and one of the most important developments is the growing vulnerability of central governments. Sovereign bond yields no longer reliably fall in the face of adverse conditions, and in some cases they even increase. These developments appear to stem from a combination of technical factors and growing concerns about sovereign credit risk, particularly in the United States. They also represent a fundamental shift in the pricing of traditionally safe assets and expose the government of Canada and provinces to a number of unknown risks.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".