MétaCan
Menu
Back to cohort
Record W2370969256

Open-economy Exchange Rate Regime and Macroeconomic Policy Options——Case of Canada

2011· article· en· W2370969256 on OpenAlexaboutno aff
Wang Ying-gui

Bibliographic record

VenueTechnoeconomics & Management Research · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsExchange rateMonetary policyEconomicsExchange-rate regimeFiscal policyMonetary economicsInflation targetingFloating exchange rateShock (circulatory)Inflation (cosmology)MacroeconomicsInternational economicsEconomic policy
DOInot available

Abstract

fetched live from OpenAlex

Since Canada is a resources economy,the movements of Canadian dollar exchange rates are subject to changes in prices of commodities and crude oil on global markets and are beyond the zone of influence of domestic monetary policy.Independnet floating or fixed peg? That is the question.After two trials,the Government of Canada chose without any more hesitation independent floating,and eventually divorced exchange rate policy from monetary policy,giving greater autonomy to the Bank of Canada,who can focus on creating a low-inflation environment.Meanwhile,the federal government tried hard to foster a favourable environment for the exchange rate policy by clearly defining and the policy goals of monetary policy and fiscal ploicy and mixing appropriately the two major policy instruments,thereby laying a solid foundation for sustainability of the rate regime and economic growth.The paper focuses on the Canadian flexible exchange rate regime,examines aspects of Canadian fiscal policy,monetary policy and their interactions,and pays close attention to the role of the floating exchange rate regime as a shock absorber.

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)0.002
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.470

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0090.003
Scholarly communication0.0070.002
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.084
GPT teacher head0.365
Teacher spread0.281 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueTechnoeconomics & Management ResearchSame topicCanadian Policy and GovernanceFrench-language works237,207