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Causality Links between Consumer and Producer Prices: Some Empirical Evidence

2002· article· en· W4254284282 on OpenAlexaboutno aff
Guglielmo Maria Caporale, Margarita Katsimi, Nikitas Pittis

Bibliographic record

VenueSouthern Economic Journal · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsCausality (physics)EconomicsEconometricsInferenceMonetary transmission mechanismTransmission (telecommunications)Empirical evidenceMechanism (biology)Causal inferenceMonetary policyMacroeconomicsMonetary economicsComputer scienceTelecommunicationsCredit channelInflation targeting

Abstract

fetched live from OpenAlex

This paper reexamines the relationship between consumer and producer prices in the G7 countries (United States, Canada, Germany, France, Italy, United Kingdom, and Japan), and it improves on the existing literature in two ways. First, it takes into account causality links arising from the transmission mechanism of monetary policy, which are generally overlooked. Second, it employs the causality testing method for unstable systems recently introduced by Toda and Yamamato (1995), which results in standard asymptotics, thereby obtaining valid statistical inference. The empirical results are consistent with the conventional wisdom according to which there is unidirectional causality running from producer to consumer prices, bidirectional causality (or even no significant links) only being found when the causality links reflecting the monetary transmission mechanism are ignored.

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)0.004
metaresearch head score (Gemma)0.038
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 score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.286
GPT teacher head0.291
Teacher spread0.005 · 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

Citations24
Published2002
Admission routes1
Has abstractyes

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