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Record W2995023294 · doi:10.3386/w26583

The U.S. Public Debt Valuation Puzzle

2019· report· en· W2995023294 on OpenAlexaff
Zhengyang Jiang, Hanno Lustig, Stijn Van Nieuwerburgh, Mindy Z. Xiaolan

Bibliographic record

VenueNational Bureau of Economic Research · 2019
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsKellogg's (Canada)
FundersNational Science Foundation
KeywordsValuation (finance)DebtEconomicsMonetary economicsEconometricsActuarial scienceFinancial economicsFinance

Abstract

fetched live from OpenAlex

The government budget constraint ties the market value of government debt to the expected risk-adjusted present discounted value of fiscal surpluses. We find evidence that U.S. Treasury investors fail to impose this no-arbitrage restriction in the U.S. Both cyclical and long-run dynamics of tax revenues and government spending make the surplus claim risky. In a realistic asset pricing model, this risk in surpluses creates a large gap between the market value of debt and its fundamental value, the PDV of surpluses, suggesting that U.S. Treasurys may be mispriced.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.510
GPT teacher head0.492
Teacher spread0.018 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations68
Published2019
Admission routes1
Has abstractyes

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