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Record W3124900929 · doi:10.5539/ibr.v9n8p84

Appreciation Pressures and Real Depreciation: The Experience with the Swiss Franc-Euro Exchange Rate Floor

2016· article· en· W3124900929 on OpenAlexvenueno aff
Tobias F. Rötheli

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsDepreciation (economics)Exchange rateEconomicsCurrencyDeflationMonetary economicsProductivityInternational economicsMacroeconomicsMonetary policyMicroeconomics

Abstract

fetched live from OpenAlex

We study the course of the Swiss price level during the recent episode where Switzerland enforced a floor on the Swiss Franc exchange rate relative to the Euro. Given the strong nominal upward pressure on the Swiss currency the introduced limit of 1.20 Francs per Euro led to a quasi-fixed exchange rate from 2011 until early 2015. This measure was specifically aimed at helping the firms of the Swiss export sector to compete internationally. A further reason for imposing this floor was the Swiss National Bank’s concern with deflationary pressures. Interestingly, it turned out that during the episode with a quasi-fixed exchange rate the Swiss price level came under downward pressure. We offer an analysis that helps to understand this depreciation of the Swiss currency in real terms which in fact contributed to the exchange rate floor being eventually abandoned. The article thus clarifies some intricate mechanisms affecting the choice of exchange rate policies which are so important for firms in the export sector. As a theoretical contribution (complementing the well-known Balassa-Samuelson analysis) the article presents a computable equilibrium model that explains real exchange rate variations with diverging trends in the productivity growth of the non-traded goods sectors of economies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.046

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 studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.122
GPT teacher head0.310
Teacher spread0.189 · 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
Published2016
Admission routes1
Has abstractyes

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Same venueInternational Business Research→Same topicMonetary Policy and Economic Impact→French-language works237,207→