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Record W1522546273 · doi:10.3386/w19019

Offshore jurisdictions (including Cyprus), corruption money laundering and Russian round-trip investment

2013· report· en· W1522546273 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNational Bureau of Economic Research · 2013
Typereport
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsWestern University
Fundersnot available
KeywordsMoney launderingLanguage changeInvestment (military)BusinessReal estateForeign direct investmentSubmarine pipelineEconomyFinancial systemFinanceMonetary economicsEconomicsPolitical scienceEngineeringMacroeconomicsLawPolitics

Abstract

fetched live from OpenAlex

In this paper we analyze the link between corruption money laundering and round-trip investment via offshore jurisdictions utilizing Russian firm-level data. In particular we empirically explore location strategies of round-trip investors (namely, from Cyprus and British Virgin Islands) across Russia and compare them with the benchmark group of genuine foreign investors in Russia. We further study the determinants of the fraction of round-trip investment in total foreign investment in Russian regions. We find that round-trip investors tend to locate in more corrupt Russian regions than their genuine foreign counterparts and the fraction of round-trip investment is also significantly higher in corrupt regions. Taking into account that a large fraction of round-trip investment in Russia is concentrated in real estate and financial sectors, our results point to the conclusion that there is a strong link between round-trip investment and corruption money laundering.

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.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.497
GPT teacher head0.535
Teacher spread0.038 · 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