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Record W7074146467

Problems and challenges of Avramović stabilization program quarter of a century later

2022· article· en· W7074146467 on OpenAlexaboutno aff

Bibliographic record

VenueSCIndeks · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSerbianIndependence (probability theory)GovernorPosition (finance)Monetary policyQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Avramović accepted a position of a governor of Central bank of Yugoslavia (at that time, consisted of Republic of Serbia and Republic of Montenegro) in 1994. He has successfully executed one of the most effective anti-inflation programs in an adverse financial environment and without international support. This paper deals with some of the basic problems Avramović has faced twenty five years ago, most of which have left visible consequences up to present day. They still nowadays present important weaknesses of Serbian monetary and financial system. First of those problems is low institutional independence of Serbian central bank. Second problem Avramović was facing was lack of confidence in the banking system. Third problem Avramović was facing at the time of his Program was lack of confidence in the local currency. These features, although less pronounced, still remain a burden for Serbian financial system. They increase lending risks, weaken monetary policy tools, and decrease rates of growth to this day. Keywords: Anti-inflation program, Dragoslav Avramović, Dollarization, Monetary policy, Central bank independence. JEL: E58, G28, G21, N14.

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)0.006
metaresearch head score (Gemma)0.007
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0040.003
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.053
GPT teacher head0.205
Teacher spread0.151 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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