More RRBs, Please! Why Ottawa Should Issue More Inflation-Indexed Bonds
Bibliographic record
Abstract
Financial instruments indexed to the general price level are of great potential use to borrowers and lenders alike. But up until recently, they have been relatively scarce – in part because private borrowers dislike offering protection against inflation that they do not control. Since the early 1980s, several developed-country governments have begun issuing price-level-linked bonds, and these bonds now constitute a large share of some countries’ total debt issue. This study argues that Canada’s federal government, which began issuing real-return bonds (RRBs) in 1991, should issue more RRBs of more types than it currently plans to do. Issuing more RRBs would not only better satisfy existing demand from investors, it has the potential to spur the development of other price-indexed instruments. Experience elsewhere suggests that more federal RRBs could encourage other entities to issue price-indexed debt, and would let intermediaries provide such products as inflation-linked annuities, thus providing more Canadian savers with protection against intentional or accidental inflation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.041 | 0.029 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".