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Record W3123435116 · doi:10.5089/9781513511061.001

Sub-National Government’s Risk Premia: Does Fiscal Performance Matter?

2015· preprint· en· W3123435116 on OpenAlex
Sergio Sola, Geremia Palomba

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIMF Working Paper · 2015
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsnot available
Fundersnot available
KeywordsRisk premiumGovernment (linguistics)IncentiveCapital marketCentral governmentEconomicsMonetary economicsGovernment debtBusinessFiscal policyFinanceMarket economyLocal governmentPolitical science

Abstract

fetched live from OpenAlex

This paper examines the determinants of sub-national governments risk premia using secondary market data for U.S., Canada, Australia and Germany. It finds that, as for central governments, fiscal fundamentals matter in the pricing of risk premia, and sub-national governments with higher public debt and larger deficits pay higher premia. However, this relationship is not uniform across countries. Market pricing mechanisms are less effective in presence of explicit or implicit guarantees from the central government. Specifically, we show that in pricing risk premia of sub-national governments, markets are less responsive to fiscal fundamental when sub-national governments depend on high transfers from the central government, i.e., when there is some form of implicit guarantee from the center. Using primary market data, the paper also looks at whether transfer dependency from the central government influences sub-national governments’ incentive to access markets. We show that high transfer dependency lowers the probability of sub-national governments to borrow on capital markets.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.645
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.030
GPT teacher head0.223
Teacher spread0.193 · 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