Do Government Budget Deficits Raise Bond Yields? Evidence from Canada
Bibliographic record
Abstract
This study applies quarterly data from 2013 through 2022 to a loanable funds framework to determine whether there is recent evidence that higher deficits and debt (both as a percentage of GDP) elevate the real yield on 10-year Canadian Treasury bonds. The study period is unique in that includes several quarters during which the COVID-19 pandemic was hampering the Canadian economy. Issues caused by the pandemic led the Canadian federal government to boost its spending by 70 % through $100 billion spending packages like the Canada Emergency Wage Subsidy and the Canada Emergency Response Benefit. Results from an autoregressive two-stage least squares regression suggest that larger Canadian federal government budget deficits and a higher debt-to-GDP ratio both elevated the real yield on 10-year Canadian government bonds. Other results indicate that the COVID-19 pandemic had its own positive impact on the real yield, potentially adding to any crowding out problems associated with higher real interest rates in Canada.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.010 |
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".