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Record W2966259400 · doi:10.33423/jabe.v21i4.2137

Are Economic Uncertainty Expectations Rational?

2019· article· en· W2966259400 on OpenAlexvenueno aff
Priti Verma, Rahul Verma

Bibliographic record

VenueJournal of Applied Business and Economics · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsRational expectationsIrrational numberStock (firearms)Financial economicsAsset (computer security)Capital asset pricing modelCurrencyMacroeconomics

Abstract

fetched live from OpenAlex

This study analyzes whether expectations about uncertainty of the global and U.S. economy emanate from the natural dynamics of the U.S. based rational economic fundamentals, or stem from irrational outlook not attributable to any known risk factors. The findings suggest that both the U.S. and the global economic uncertainty expectations are significantly driven by the U.S. economy and stock market related rational factors namely, economic growth, economic risk premium and excess returns. The three Fama and French factors have significant impact on the U.S. economic uncertainty expectations but insignificant role for global economic uncertainty expectations. Foreign currency movements play a significant role for the global economic uncertainty. The impact of the rational factors is higher for the U.S. economic uncertainty expectations than on the global economic uncertainty expectations. Lastly, there exists a positive feedback effect of the U.S. and global and economic uncertainty expectations. Overall, to a significant extent, the expectations of the U.S. economic uncertainty are well captured by the risk factors suggested in the asset pricing literature.

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)0.002
metaresearch head score (Gemma)0.022
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0030.004
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.200
Teacher spread0.185 · 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
Published2019
Admission routes1
Has abstractyes

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