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Record W3189001139 · doi:10.1093/ej/ueab019

Uncertainty, Wages and the Business Cycle

2021· article· en· W3189001139 on OpenAlex

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.

Bibliographic record

VenueThe Economic Journal · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of CanadaHEC Montréal
Fundersnot available
KeywordsEconomicsBusiness cycleWageRecessionConstraint (computer-aided design)EconometricsGreat recessionProfit (economics)Matching (statistics)Flexibility (engineering)Risk premiumMonetary economicsLabour economicsMacroeconomicsMicroeconomicsMathematics

Abstract

fetched live from OpenAlex

Abstract We show that limited wage flexibility in economic downturns generates strong and state-dependent amplification of uncertainty shocks. It also explains the cyclical behaviour of empirical measures of uncertainty. In the presence of matching frictions, an occasionally binding constraint on downward wage adjustment enhances the concavity of firms’ hiring rule, resulting in an endogenous profit risk-premium. In turn, higher uncertainty increases the profit risk-premium when the economy operates close to the wage constraint, deepening a recession. Non-linear local projections and vector autoregression estimates support the model predictions. In addition, we show that measured uncertainty rises in a recession even without uncertainty shocks.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.212
Teacher spread0.174 · 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