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Record W4311791371 · doi:10.3390/jrfm15120608

Stability and Growth Pact: Too Young to Die, Too Old to Rock ‘n’ Roll

2022· article· en· W4311791371 on OpenAlexvenueno aff
Patroklos Patsoulis, Marios Psychalis, Georgios A. Deirmentzoglou

Bibliographic record

VenueJournal of risk and financial management · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsnot available
Fundersnot available
KeywordsStability and Growth PactEconomicsMonetary economicsConvergence (economics)Economic and monetary unionMoral hazardGovernment (linguistics)MacroeconomicsFiscal policyDebtGovernment debtMonetary policySpillover effectFiscal unionGovernment spendingInternational economicsEconomic policyWelfareEuropean unionMarket economyMember states

Abstract

fetched live from OpenAlex

This paper discusses the future of the Stability and Growth Pact (hereafter SGP). Although Neoclassical economic models argue that strict fiscal and monetary rules minimize moral hazard and crowding out, in practice many governments adopt fiscal expansion (in recent years in the form of non-standard monetary measures) to mitigate market failures, consequently rethinking monetary rules and targets. Government spending and countercyclical policies are essential tools for soothing business cycles and other market failures. To this end, we empirically test whether current and past forms of the SGP have led to greater convergence, while we critically assess and investigate a possible SGP reform. By adopting more flexible rules, in terms of government spending and fiscal expansion, the Economic and Monetary Union (hereafter EMU) could yield multiple positive spillover effects in long-term economic growth under specific terms and conditions, such as green conditionalities. We conclude that to mitigate the triple crisis threat (economic, environmental and health), what is mostly needed are reforms in the form of fiscal federalism, such as common debt issuance (Eurobonds) that enhance the ability of the EMU to tackle the consequences of the aforementioned crises.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.716
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.195
Teacher spread0.183 · 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 teacher head, 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
Published2022
Admission routes1
Has abstractyes

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