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Record W1591534703 · doi:10.6277/ter.2003.314.2

Re-examining the Sources of Real Exchange Rate Fluctuations: A Rational Expectations Structural VAR Approach

2003· article· en· W1591534703 on OpenAlexaboutno aff
Hsiu‐Yun Lee, Kenneth S. Lin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsExchange rateEconomicsRational expectationsExplanatory powerShock (circulatory)EconometricsForeign exchangeMonetary economicsForeign exchange marketVector autoregression

Abstract

fetched live from OpenAlex

To explicitly take into account market expectations for real exchange rate fluctuations, this paper proposes a rational expectations structural VAR (RE-SVAR) method to decompose structural shocks. An exogenous shock not only has effects on real exchange rates directly, but also has indirect effects through the change in predictions for other fundamental variables. The RE-SVAR method imposes all these direct and indirect channels to decompose the sources of real exchange rate fluctuations. We find that the over-identifying restrictions implied by our model cannot be rejected for Canada, France, Italy, and Japan. Our results also indicate that private expenditure shocks are the most important source of real exchange rate variations for France and Italy, monetary shocks are most important for Canada, and foreign price shocks are most important in the long run for Japan. Moreover, supply shocks have a small but significant explanatory power fot real exchange rate variations only in France.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.111
GPT teacher head0.249
Teacher spread0.138 · 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 designSimulation or modeling
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

Citations2
Published2003
Admission routes1
Has abstractyes

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