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Record W4412501602 · doi:10.17016/2380-7172.3856

The International Role of the U.S. Dollar – 2025 Edition

2025· article· en· W4412501602 on OpenAlexaboutno aff
Carol C. Bertaut, Bastian von Beschwitz, Stephanie E. Curcuru

Bibliographic record

VenueFEDS Notes · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsLiberian dollarEconomicsPolitical sciencePsychologyFinance

Abstract

fetched live from OpenAlex

A key function of a currency is as a store of value which can be saved and retrieved in the future without a significant loss of purchasing power. One measure of confidence in a currency as a store of value is its usage in official foreign exchange reserves. As shown in Figure 2, the U.S. dollar comprised 58 percent of disclosed global official foreign reserves in 2024 and far surpassed all other currencies including the euro (20 percent), Japanese yen (6 percent), British pound (5 percent), and the Chinese renminbi (2 percent). The dollar share has declined from its peak of 72 percent of reserves in 2001, as foreign reserve managers have added to their portfolios a wide range of smaller currencies, including the Australian and Canadian dollars (IMF COFER). Even with this decline, the dollar remains by far the dominant reserve currency and only returned to about the share it had in 1995. Notably, it is basically unchanged since 2022, when it accounted for 58 percent of reserves, suggesting that U.S. sanctions on Russia following the invasion of Ukraine have not led to fears of dollar "weaponization" causing a notable reallocation of reserves out of dollars.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0080.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0440.031

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 head0.011
GPT teacher head0.221
Teacher spread0.209 · 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 designNot applicable
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

Citations9
Published2025
Admission routes1
Has abstractyes

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