MétaCan
Menu
Back to cohort
Record W2354988967

An Analysis of the Intermediate Target Choice of China's Monetary Policy

2007· article· en· W2354988967 on OpenAlexaboutno aff
Jianguo Liu

Bibliographic record

VenueHuadong Li-Gong Daxue xuebao · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEvaluation Methods in Various Fields
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsMonetary policyMoney supplyInflation (cosmology)Variance decomposition of forecast errorsMonetary economicsExchange rateVariance (accounting)Interest rateQuarter (Canadian coin)Granger causalityCausality (physics)Inflation targetingEconometricsMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Since 1996,our country has adopted money supply as the intermediate target of the monetary policy.Many scholars hold that money supply can not be acted as an effective intermediate target to influence the terminal target because it is not under well control,and should be substituted by other targets like interest rate,exchange rate,inflation rate,etc.This essay,therefore,would explore the effectiveness of these different targets,employing data from the 1st quarter of 1996 to the 4th quarter of 2006.We would utilize modern methodologies of econometrics like dynamic correlations coefficient,VAR model,variance decomposition,Granger causality analysis,etc.In the end,we reach a conclusion that currently our country should still adopt the money supply as the intermediate target of the 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)0.003
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.341
Teacher spread0.322 · 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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueHuadong Li-Gong Daxue xuebaoSame topicEvaluation Methods in Various FieldsFrench-language works237,207