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Record W1546460735 · doi:10.34989/swp-2001-27

The Monetary Transmission Mechanism at the Sectoral Level

2021· preprint· en· W1546460735 on OpenAlexaffabout
Jean Farès, Gabriel Srour

Bibliographic record

VenueRePEc: Research Papers in Economics · 2021
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of Canada
Fundersnot available
KeywordsMonetary transmission mechanismMechanism (biology)EconomicsTransmission (telecommunications)Production (economics)Monetary economicsSimple (philosophy)Vector autoregressionMacroeconomicsMonetary policyEconometricsComputer scienceCredit channelInflation targeting

Abstract

fetched live from OpenAlex

This paper relies on simple vector autoregressions to investigate the monetary transmission mechanism in broad sectors of the Canadian economy. Two types of disaggregation are considered: one at the level of final expenditures, and one at the level of production. At the level of final expenditures, it is found that a monetary contraction affects exports relatively quickly, and it affects investment much more substantially than the consumption of goods, while it does not seem to affect services. Not surprisingly, durables respond much more substantially than semi-durables to a monetary contraction, while non-durables do not respond significantly. At the level of production, following a monetary contraction, construction reaches the trough of the cycle first, although, cumulatively, manufacturing reacts twice as strongly. The response of the service sector is significant, but it lags manufacturing.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.670

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.136
GPT teacher head0.297
Teacher spread0.161 · 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 designSimulation or modeling
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

Citations20
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueRePEc: Research Papers in EconomicsSame topicMonetary Policy and Economic ImpactFrench-language works237,207