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Record W4308887533 · doi:10.1080/1540496x.2022.2119804

Oceans Apart? China and Other Systemically Important Economies

2022· article· en· W4308887533 on OpenAlexaff
Hongyi Chen, Pierre L. Siklos

Bibliographic record

VenueEmerging Markets Finance and Trade · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsWilfrid Laurier UniversityBalsillie School of International Affairs
Fundersnot available
KeywordsChinaEconomicsBusinessEconomyEconomic geographyGeography

Abstract

fetched live from OpenAlex

China has been considered a systemically important economy for at least a decade. As policymakers worldwide grapple with sluggish growth there is relatively little evidence about whether the G4, which consists of the US, the Eurozone, Japan, and includes China, as a block contributes to global economic performance in a manner that is not possible when China is left out or treated exogenously. We estimate a series of panel factor and standard VARs because these are well suited to exploit cross-country links. We estimate the relative impact of domestic and global factors on these four economies. First, it is essential to treat China in a model of the G4, on a level playing field with the US, the Eurozone, and Japan to better understand how shocks among these economies interact with each other. Second, we find that domestic and global shocks can reinforce each other. Indeed, global monetary shocks explain up to 60% of variation in commodity demand and real economic conditions. We also report that there is a trade-off between domestic monetary and financial conditions. We recommend that policymakers to reexamine the potential benefits from greater policy cooperation.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.018
GPT teacher head0.189
Teacher spread0.170 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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