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Record W3121387825

The Great Increase in Relative Volatility of Real Wages in the United States

2010· article· en· W3121387825 on OpenAlex
André Kurmann, Julien Champagne

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

VenueCahiers de recherche · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic theories and models
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsEconomicsDynamic stochastic general equilibriumVolatility (finance)WageGreat ModerationBusiness cycleReal wagesEconometricsCurrent Population SurveyRelative volatilityMonetary policyPopulationMonetary economicsLabour economicsMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper documents that over the past 25 years, aggregate hourly real wages in the United States have become substantially more volatile relative to output. We use micro-data from the Current Population Survey (CPS) to show that this increase in relative volatility is predominantly due to increases in the relative volatility of hourly wages across different groups of workers. Compositional changes, by contrast, account for at most 12% of the increase in relative wage volatility. Using a Dynamic Stochastic General Equilibrium (DSGE) model, we show that the observed increase in relative wage volatility is unlikely to come from changes outside of the labor market (e.g. smaller exogenous shocks or more aggressive monetary policy). By contrast, increased flexibility in wage setting is capable of accounting for a large fraction of the observed increase in relative wage volatility. At the same time, increased wage flexibility generates a substantial decrease in the magnitude of business cycle fluctuations, which suggests a promising new explanation for the Great Moderation.

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)0.009
metaresearch head score (Gemma)0.002
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 score0.030
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
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 integrity0.0000.001
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 head0.103
GPT teacher head0.302
Teacher spread0.199 · 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