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Record W2896690520 · doi:10.1002/ijfe.1691

Do demographics affect monetary policy transmission in Canada?

2018· article· en· W2896690520 on OpenAlexaffabout
Jeremy Kronick, Steve Ambler

Bibliographic record

VenueInternational Journal of Finance & Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsEsri (Canada)Université du Québec à MontréalOntario Brain Institute
Fundersnot available
KeywordsEconomicsDemographicsMonetary policyInflation (cosmology)Monetary economicsAffect (linguistics)Financial crisisInflation targetingPanel dataDependency ratioMacroeconomicsEconometricsDemography

Abstract

fetched live from OpenAlex

Abstract Using a panel of macroeconomic data for Canada and its 10 provinces, we estimate the dynamic effects of monetary policy shocks from the mid‐1980s until the present. We then relate the change in the impact of these shocks to macroeconomic factors including demographics, specifically changes in the old age dependency ratio. We find that the inflation‐targeting regime has had an ambiguous effect on the impact of monetary policy shocks in Canada. On the other hand, changing demographics have unambiguously reduced the impact of monetary policy shocks. This can help to explain tepid inflation since the financial crisis and could eventually undermine the effectiveness of Canada's inflation targeting regime.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.937

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.241
Teacher spread0.209 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations10
Published2018
Admission routes2
Has abstractyes

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