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THE TRANSMISSION OF MONETARY POLICY IN A MULTISECTOR ECONOMY*

2009· article· en· W2101472359 on OpenAlexaff
Hafedh Bouakez, Emanuela Cardia, Francisco J. Ruge‐Murcia

Bibliographic record

VenueInternational Economic Review · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversité de MontréalHEC Montréal
Fundersnot available
KeywordsEconomicsMonetary policyGeneral equilibrium theoryProduction (economics)Aggregate (composite)Investment (military)Monetary economicsCapital (architecture)MacroeconomicsEconometricsEconomy

Abstract

fetched live from OpenAlex

This article constructs and estimates a sticky‐price, Dynamic Stochastic General Equilibrium model with heterogeneous production sectors. Firms in different sectors vary in their price rigidity, production technology, and the combination of material and investment inputs. In particular, firms buy inputs from all sectors using the actual Input–Output Matrix and Capital Flow Table of the U.S. economy. By relaxing the standard assumption of symmetry, this model allows idiosyncratic sectoral dynamics in response to monetary policy shocks. The model is estimated by the Generalized Method of Moments using sectoral and aggregate U.S. time series.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.280
Teacher spread0.233 · 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 designTheoretical or conceptual
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

Citations160
Published2009
Admission routes1
Has abstractyes

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