Bibliographic record
Abstract
Starting with the UK in 1981, many of the industrialized countries have issued long-term bonds whose principal value is indexed to the rate of inflation. One of the benefits that economists predicted from issuing such bonds is that the difference between the yield on indexed and nominal bonds would be an indicator of the market’s expectations of inflation. This could be a useful guide for central banks in judging the success of their monetary policy in stabilizing the inflation rate. This paper examines the data from Canada, which began issuing indexed (“real return”) bonds in 1991. It is found that it is possible to explain the relationship between real and nominal bonds with very small residuals, using a moving average of historical inflation and the US bond yield as explanatory variables. The implication is that expectations in the nominal bond market are adaptive rather than forward looking. Therefore, while we are able to infer the market’s expectations of inflation with a high degree of precision, this is not actually very useful as a guide to monetary policy or predicting future inflation. 1By contrast, with regular bonds there is a higher nominal bond yield which attempts to account for the depreciation of the real value of the principal due to inflation. The annual interest payments are the same each year, which means that the real value of the payments diminishes each year when there is inflation. Borrowing costs are front end loaded, which creates an especially high burden on capital intensive projects in periods when there is high inflation and high nominal bond yields. 2The Canadian Government refers to them as “real return bonds. ” There are four issues
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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) | 0.000 | 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) | 0.115 | 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; 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".