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Record W2791490751 · doi:10.22158/jepf.v4n2p143

Do Financial Arrangement of the International Monetary Fund Has Impact on the Reduction of Government Spending, Evidence through Political Fiscal Cycles, the Case of Croatia

2018· article· en· W2791490751 on OpenAlexaboutno aff
Ivana Rukavina

Bibliographic record

VenueJournal of Economics and Public Finance · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policies and Political Economy
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment spendingEconomicsObligationGovernment (linguistics)PoliticsQuarter (Canadian coin)LimitingMonetary economicsFiscal policyEconomic policyPolitical scienceMarket economyWelfareLaw

Abstract

fetched live from OpenAlex

<p><em>This paper examines the regulatory role of the IMF on government spending through political fiscal cycles. According to theoretical views, the fiscal policy in the pre-election period reflects an increase in government spending or budget expenditures; in postelection period, it takes a restrictive course by reducing spending. In the presence of a contractual agreement with the IMF, the theory points to limiting and reducing the magnitude of government spending in the pre-election period. According to the research results in Croatia, there is an increase in government spending in the election quarter, and its decrease in the quarter after the election. On the other hand, the contractual arrangements with the IMF show significant reductions in government spending. When a country is under a contractual obligation with the IMF, it reduced the government spending in the pre-election period in relation to the period when it is not under a contractual obligation.</em></p>

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 score0.551
Threshold uncertainty score0.361

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.091
GPT teacher head0.276
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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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