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Record W2166061160 · doi:10.34989/tr-80

Constraints on the Conduct of Canadian Monetary Policy in the 1990s: Dealing with Uncertainty in Financial Markets

2021· preprint· en· W2166061160 on OpenAlexaffabout
Mark Zelmer

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 policyFinancial marketEconomicsMonetary economicsFinancial economicsBusinessFinancial systemFinance

Abstract

fetched live from OpenAlex

Canada's economic performance in the first half of the 1990s was adversely affected by high premiums in interest rates that were brought on by political and economic uncertainties. The short-term output-inflation trade-off was worsened since these uncertainties weakened the value of the Canadian dollar at the same time as they raised domestic interest rates. In this environment, attempts by the Bank of Canada to ease monetary conditions were liable to be misinterpreted by the market as a sign of weakening commitment to inflation control. On several occasions, such fears led to sharp increases in interest rates. The first part of this report presents a simple theoretical model that shows the qualitative impact of the increased interest rate premiums on economic performance. Some evidence is presented that suggests high Canadian interest rate premiums were an important factor explaining the general weakness of economic activity. This is followed by a discussion of the tactical conduct of monetary policy when the need to build credibility often seemed to be in conflict with the desired easing of monetary conditions. Finally, the report describes steps that the Bank has taken to reduce uncertainty about how it conducts monetary policy.

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)0.005
metaresearch head score (Gemma)0.015
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.844

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0070.004
Scholarly communication0.0110.002
Open science0.0010.002
Research integrity0.0030.003
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 head0.105
GPT teacher head0.291
Teacher spread0.186 · 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

Citations14
Published2021
Admission routes2
Has abstractyes

Explore more

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