Benchmark Interest Rates When the Government is Risky
Bibliographic record
Abstract
Since the Global Financial Crisis, rates on interest rate swaps have fallen below maturity matched U.S. Treasury rates across different maturities. Swap rates represent future uncollateralized borrowing between banks. Treasuries should be expensive and produce yields that are lower than those of maturity matched swap rates, as they are deemed to have superior liquidity and to be safe, so this is a surprising development. We show, by no-arbitrage, that the U.S. sovereign default risk explains the negative swap spreads over Treasuries. This view is supported by a quantitative equilibrium model that jointly accounts for macroeconomic fundamentals and the term structures of interest and U.S. credit default swap rates. We account for interbank credit risk, liquidity effects, and cost of collateralization in the model. Thus, the sovereign risk explanation complements others based on frictions such as balance sheet constraints, convenience yield, and hedging demand.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".