MétaCan
Menu
Back to cohort

Taylor Rules and the Euro

2011· article· en· W1684088702 on OpenAlexaboutno aff
Tanya Molodtsova, Alex Nikolsko‐Rzhevskyy, David H. Papell

Bibliographic record

VenueJournal of money credit and banking · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPredictabilityTaylor ruleEconomicsInflation (cosmology)Output gapExchange rateEconometricsQuarter (Canadian coin)Liberian dollarUs dollarUnemploymentReal interest rateSample (material)Interest rateMonetary policyMonetary economicsMacroeconomicsCentral bankFinanceStatisticsMathematics

Abstract

fetched live from OpenAlex

This article uses real‐time data to show that inflation and either the output gap or unemployment, variables which normally enter central banks’ Taylor rules, can provide evidence of out‐of‐sample predictability for the U.S. dollar/euro exchange rate from 1999 to 2007. The strongest evidence is found for specifications that constrain the coefficients on inflation and real economic activity to be the same for the United States and the Euro Area, do not incorporate interest rate smoothing, and do not include the real exchange rate in the forecasting regression. Evidence of predictability is found with both one‐quarter‐ahead and longer‐horizon forecasts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

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

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 head0.083
GPT teacher head0.210
Teacher spread0.127 · 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.

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

Citations74
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueJournal of money credit and bankingSame topicMonetary Policy and Economic ImpactFrench-language works237,207