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Record W2265095336

Резервні вимоги та прогнозування грошового мультиплікатора: досвід Канади

2006· article· en· W2265095336 on OpenAlexaboutno aff
Kam Hon Chu

Bibliographic record

VenueElectronic Sumy State University Institutional Repository (Sumy State University) · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsExcess reservesReserve requirementMonetary policyArgument (complex analysis)Multiplier (economics)Bank reservesMonetary economicsCentral bankMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

An argument against abolishing legal reserve requirements is that money multipliers would become more volatile and unpredictable in the absence of reserve requirements, thus impairing the central bank’s effectiveness in controlling money aggregates. This study examines the Canadian experience during 1970-2004, where a zero reserve requirement regime has become fully effective since June 1994. The findings show that all money multipliers, except the M1 multiplier, under this current regime have become less volatile than before. Furthermore, short- and medium-term ex ante forecasts based on the Holt-Winters exponential smoothing model indicate that the money multipliers have not become apparently more unpredictable. Overall, the findings do not lend strong support to the monetary control argument for reserve requirements. Доказом, який свідчить не на користь скасування норм обов’язкових резервів, є те, що за відсутності резервних вимог грошові мультиплікатори можуть стати більш волатильними та непередбачуваними, що в свою чергу послабить ефективне контролювання грошових мас з боку центрального банку. У даній роботі вивчається досвід Канади протягом 1970-2004 рр., коли, починаючи вже з червня 1974 року, режим так званих нульових резервних вимог став цілком ефективним. Результати дослідження вказують на те, що всі грошові мультиплікатори, за винятком мультиплікатора М1, в умовах нинішнього режиму стали менш волатильними, ніж були раніше. Крім того, коротко- та довгострокові попередні прогнозування, базовані на моделі експоненційного згладжування Холта-Вінтерса, говорять, що грошові мультиплікатори не стали більш непередбачуваними. Загалом отримані висновки не дають змоги підтвердити доказ грошово-кредитного регулювання для резервних вимог.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.007
GPT teacher head0.162
Teacher spread0.155 · 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 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

Citations0
Published2006
Admission routes1
Has abstractyes

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