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Record W1974095295 · doi:10.5539/ijef.v5n2p102

The Analysis of Inflation Rate Dynamic in Central and South-Eastern Europe’s States in the Context of The EU Accession

2013· article· en· W1974095295 on OpenAlexvenueno aff
Ovidiu Stoica, Monica Damian

Bibliographic record

VenueInternational Journal of Economics and Finance · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsAccessionEconomicsContext (archaeology)Inflation (cosmology)International economicsEuropean unionMonetary economicsRelative priceInflation rateInternational tradeMonetary policyGeography

Abstract

fetched live from OpenAlex

In the year 2004 ten states from Central and South-Eastern Europe joined the European Union. The majority of them have registered a significant consumer price increase in the year 2004. The goal of this paper is to examine the fundamental factors that have influenced inflation rate after EU accession and to analyse the causes of the inflation differential in EU member states which acceded in 2004. The impact of EU accession was different in analysed countries, the increasing of inflation rate in accession year being determined by the adoption of the Common Agricultural Policy, the harmonization of the structure and rates of indirect taxes, the introduction of the Common Customs Policy, the free movement of goods, the free movement of capital and the expected inflation. From the analyses we have done, we have remarked that the main cause of inflation differential has been the oil price on the international market, because of the different degree of dependence on oil import of these countries, but also on the different weight of electricity, gases and other fuels in the consumer basket.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.228
Teacher spread0.202 · 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 designObservational
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

Citations3
Published2013
Admission routes1
Has abstractyes

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