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Record W4399365654 · doi:10.3390/jrfm17060235

Financial Fragility and Public Social Spending: Unraveling the Endogenous Nexus

2024· article· en· W4399365654 on OpenAlexvenueno aff
Dionysios Kyriakopoulos, John Yfantopoulos, Theodoros V. Stamatopoulos

Bibliographic record

VenueJournal of risk and financial management · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)Financial fragilityFragilityEconomicsPublic financeBusinessFinancial crisisMacroeconomicsChemistry

Abstract

fetched live from OpenAlex

This article provides both stylized facts and estimations of the endogenous nexus of the financial fragility hypothesis (FFH) with public social spending (PSS) for a paradigmatic Eurozone member country. The sample period 1995–2022 includes three major economic crises, the global financial crisis 2007–2009, the European debt crisis 2010–2015 and the COVID-19 pandemic one in 2020–2022. Within the context of the financialization literature, this paper is founded, for the first time, as far as we know, on the “financial fragility hypothesis”, combining the effects of both Minsky’s “financial instability”, as it has been extended for open economies, and the “Eurozone fragility one”. Similar to the relevant literature, the findings show that the PSS is associated, in a long-term steady state (cointegration), with the financial fragility process, starting, firstly, from the hedge-financing structure with high profitability of firms, when PSS decreases; secondly, to hyper-speculative financing with risky options, supported by bank credit and openness, indebtedness or discretionary fiscal policy, when PSS rises; thirdly, to the hyper-speculative or even Ponzi financing structures with over-indebtedness (leverage) from the global capital market, inflated asset prices and internationalized fragility, when PSS also rises, and so on. Our conclusion validates Minsky’s famous saying, “stability breeds instability”, also in the architecturally incomplete Eurozone. Policy implications are straightforward and discussed.

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)0.003
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 score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.221
Teacher spread0.185 · 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
Published2024
Admission routes1
Has abstractyes

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