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Record W3124011337

Testing Russia's Virtual Economy

2001· preprint· en· W3124011337 on OpenAlexaff
Vlad Ivanenko

Bibliographic record

VenueRePEc: Research Papers in Economics · 2001
Typepreprint
Languageen
FieldSocial Sciences
TopicRussia and Soviet political economy
Canadian institutionsWestern University
Fundersnot available
KeywordsBarterEconomicsValue (mathematics)SubsidyDistribution (mathematics)EconomyMonetary economicsMarket economy
DOInot available

Abstract

fetched live from OpenAlex

In the aftermath of sovereign default of August 1998, the hypothesis of virtual economy in Russia developed by Gaddy and Ickes has gained popularity. The hypothesis states that the country has not moved towards free-market economy but developed a system of implicit price subsidization similar to what had existed before. Non-viable sectors that the state supported with subsidies before survive by over-pricing their output. Customers pass the bill back to the government by reducing their tax liabilities. We test the proposition that the distribution of the value-added across sectors is biased because of price distortions and estimate the distribution at world prices. The results support the claim that Russian price structure is different from the world level and three out of fifteen sectors, for which we construct price indices, become "value-destroying". We investigate the reasons behind price differentials and find that difference in processing and the use of barter explain a large part of it.

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)0.004
metaresearch head score (Gemma)0.020
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 score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
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 head0.063
GPT teacher head0.363
Teacher spread0.300 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

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