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Record W2993997339 · doi:10.15353/rea.v12i2.1693

Interactions among Economic Ideas, Policies and Experience - The Establishment of Inflation Targeting in Canada, 1991-2001

2020· article· en· W2993997339 on OpenAlexaffvenueabout
David Laidler

Bibliographic record

VenueReview of Economic Analysis · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsWestern University
Fundersnot available
KeywordsEconomicsDepreciation (economics)Inflation (cosmology)Exchange rateInflation targetingMonetary policyPrice of stabilityUnemploymentVirtuous circle and vicious circleEconomic stabilityMacroeconomicsKeynesian economicsMonetary economicsInflation rateEconomic growth

Abstract

fetched live from OpenAlex

In Canada, targeting the inflation rate was intended as a temporary measure during a transition to price-level stability, but became a well-established monetary policy regime in its own right. This paper analyses the role of the interaction of economic ideas with the experience generated by their application to policy in bringing about this outcome. In the following account, changing beliefs about the stability or otherwise of ongoing inflation, the capacity of a flexible exchange rate to create a vicious circle of depreciation and rising domestic prices, are emphasised, while ideas about the natural unemployment rate and money growth in influencing economic outcomes are also discussed. Today’s standard theoretical approach to modelling inflation targeting arrived on the scene only as the Canadian regime was becoming well established.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.954

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0100.008
Scholarly communication0.0080.002
Open science0.0010.003
Research integrity0.0010.003
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 head0.023
GPT teacher head0.257
Teacher spread0.234 · 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 designQualitative
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

Citations5
Published2020
Admission routes3
Has abstractyes

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