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Record W4404690918 · doi:10.1515/snde-2023-0108

Monetary Policy Uncertainty in the United States and Investment Sentiment in Advanced Economies

2024· article· en· W4404690918 on OpenAlex
Nahiyan Faisal Azad, Apostolos Serletis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueStudies in Nonlinear Dynamics and Econometrics · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEconomicsInvestment (military)Monetary policyMacroeconomicsPolitical science

Abstract

fetched live from OpenAlex

Abstract How does uncertainty originating from the future path taken by monetary policy enacted by the Federal Reserve in the United States affect the business confidence in other advanced economies? Does US monetary policy uncertainty affect economic activity in the United States and in Canada, France, Germany, Italy, Japan, and the United Kingdom. Motivated to answer these questions, we use monthly data and a bivariate GARCH-in-Mean VAR model. We also use a multivariate structural VAR model and a different measure of US monetary policy uncertainty, achieving identification by a combination of short-run and long-run restrictions. Our evidence shows that US monetary policy uncertainty, irrespective of how it is measured, has negative effects on the business confidence and output in the advanced G7 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.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
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 head0.032
GPT teacher head0.278
Teacher spread0.246 · 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