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Record W2470643014 · doi:10.1080/08911916.2016.1185318

Does U.S. Pressure Lead to Changes in China’s Exchange Rate?

2016· article· en· W2470643014 on OpenAlexaff
Paul Bowles, Baotai Wang

Bibliographic record

VenueInternational Journal of Political Economy · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsRenminbiGranger causalityChinaEconomicsLiberian dollarExchange rateMonetary economicsVector autoregressionInternational economicsUs dollarLead (geology)Political scienceEconometricsLawFinance

Abstract

fetched live from OpenAlex

:The role of external political pressure in the appreciation of the Chinese renminbi against the U.S. dollar since 2005 has been the subject of debate. While Chinese authorities maintain that only domestic considerations have played a role, whether the appreciation has also been the result of the exercise of international monetary power by the United States has been examined using three different approaches. The results have been contradictory with the weight of studies finding against U.S. pressure having an effect on the exchange rate. In this article, we use Granger causality tests to reexamine the issue using data from 2000–2014. We find evidence that U.S. pressure does Granger-cause renminbi appreciation. We also examine whether U.S. pressure causes the changes in China’s export tax rebates. We find no evidence for this.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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 teacher head, not a consensus.

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

Citations7
Published2016
Admission routes1
Has abstractyes

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