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Record W3123394104 · doi:10.3386/w26429

Benchmark Interest Rates When the Government is Risky

2019· preprint· en· W3123394104 on OpenAlexaff
Patrick Augustin, Mikhail Chernov, Lukas Schmid, Dongho Song

Bibliographic record

VenueNational Bureau of Economic Research · 2019
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsMcGill University
Fundersnot available
KeywordsCollateralized debt obligationInterest rateInterest rate swapSwap (finance)Credit default swapEconomicsMonetary economicsMarket liquiditySovereign defaultCredit derivativeTreasuryCredit riskRisk premiumLiquidity premiumMaturity (psychological)Credit default swap indexFinancial crisisCollateralSovereigntyLiquidity riskCredit valuation adjustmentFinanceSovereign debtMacroeconomics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.748
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.341
GPT teacher head0.444
Teacher spread0.102 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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