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Record W2001227819 · doi:10.5539/ijef.v6n10p55

Study on Synergistic Fluctuation of Exchange Rate between Renminbi and New Taiwan Dollar

2014· article· en· W2001227819 on OpenAlexvenueno aff
Xiaoheng Cao, Wentung Lee, Yao-Hung Yang

Bibliographic record

VenueInternational Journal of Economics and Finance · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsRenminbiEconomicsCurrencyCointegrationExchange rateLiberian dollarMonetary economicsClearingGranger causalityInternational economicsInvestment (military)Us dollarError correction modelEconometricsFinance

Abstract

fetched live from OpenAlex

According to the methods such as Johansen Cointegration Test, Error Correction Model (ECM) and Granger Causality Test, the empirical result in this paper shows the launching of the “Cross-Strait Currency Clearing Mechanism” prominently increase long-term equilibrium, long/short-term interaction and lead-lag relationship of the exchange rate between Renminbi (RMB) and New Taiwan Dollar (TWD). To sum up, it is proved that implementation of Memorandum on Cross-strait Currency Clearing Cooperation and the policy of “Cross-Strait Currency Clearing Mechanism” remarkably multiplies a positive synergistic fluctuation of the exchange rate between cross-Strait currencies in causality. It is suggested that transaction in U.S. Dollars decrease and transaction in RMB increase for cross-Strait economy and trade, investment and fund dealings.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.088
GPT teacher head0.258
Teacher spread0.171 · 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
Published2014
Admission routes1
Has abstractyes

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