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Record W2946525269 · doi:10.1111/ecin.12841

THE SHIFTS IN LEAD‐LAG PROPERTIES OF THE U.S. BUSINESS CYCLE

2019· article· en· W2946525269 on OpenAlex
Joshua Brault, Hashmat Khan

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

VenueEconomic Inquiry · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsCarleton University
Fundersnot available
KeywordsBusiness cycleLaggingEconomicsLagCounterfactual thinkingProductivityUnemploymentEconometricsUnemployment rateLead (geology)Okun's lawMonetary economicsMacroeconomicsMathematicsComputer science

Abstract

fetched live from OpenAlex

We document shifts in the lead‐lag properties of the U.S. business cycle since the mid‐1980s. Specifically, (1) the well‐known inverted leading indicator property of real interest rates has completely vanished; (2) labor productivity switched from positively leading to negatively lagging output and labor inputs over the cycle; and (3) the unemployment rate shifted from lagging productivity negatively to leading positively. Many contemporary business cycle models produce counterfactual cross‐correlations revealing that popular frictions and shocks provide an incomplete account of business cycle comovement. Determining the underlying sources of these shifts in the lead‐lag properties and their consequences for macroeconomic forecasts is therefore a promising direction for future research. ( JEL E24, E32, E43)

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.998

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.072
GPT teacher head0.216
Teacher spread0.144 · 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