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Record W3123923117

Fiscal Risk in a Monetary Union

2008· preprint· en· W3123923117 on OpenAlexaff
Betty C. Daniel, Christos Shiamptanis

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFiscal unionFiscal policyEconomicsMaastricht TreatyDebtMonetary economicsMonetary policyEuropean debt crisisInsolvencyGovernment debtEuropean unionMacroeconomicsEconomic policyInternational economicsFinanceEuropean integration
DOInot available

Abstract

fetched live from OpenAlex

A country entering a monetary union gives up the right to determine its own monetary policy. Individual fiscal authorities promise passive fiscal policy, allowing the central monetary authority to use active monetary policy. Since a government, which can print its own money, can honor its nominal debt unconditionally, entrance into a monetary union raises new issues of potential fiscal insolvency. When there is an upper bound on the magnitude of the surplus and stochastic shocks to the surplus, a government can find itself in a position in which it cannot borrow to continue with its desired passive fiscal policy. This paper considers the risk of a fiscal financial crisis in a monetary union under alternative assumptions about how the fiscal authority would respond. The response affects the timing and probability of a crisis. We consider both outright default and policy switching, whereby the fiscal authority in crisis switches to active fiscal policy and the monetary authority switches to passive monetary policy. We apply the model to estimate fiscal risk in the European Monetary Union. Using panel estimates of the parameters in the surplus rule and initial values for government debt and the primary surplus, we simulate fiscal risk under the two alternative fiscal responses to a crisis. We find that countries with initial values bound by the Maastricht Treaty limits are safe, while countries like Italy and Greece, in which debt has strayed far above these limits, might not be.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.041
GPT teacher head0.280
Teacher spread0.239 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicFiscal Policies and Political EconomyFrench-language works237,207