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Record W4206377351 · doi:10.32479/ijeep.12528

The Indirect Effects of Oil Price on Consumption Through Assets

2022· article· en· W4206377351 on OpenAlexaboutno aff
Seyedeh Fatemeh Razmi, Leila Torki, Seyed Mohammad Javad Razmi, Ehsan Mohaghegh Dowlatabadi

Bibliographic record

VenueInternational Journal of Energy Economics and Policy · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsConsumption (sociology)Stock (firearms)Vector autoregressionAsset (computer security)Shock (circulatory)Oil priceQuarter (Canadian coin)Monetary economicsWealth effectCrude oilEconometricsFinancial economicsMonetary policy

Abstract

fetched live from OpenAlex

This research considers how oil price can indirectly affect consumption through asset prices of stock and house. Using the theory of consumption wealth effect, this research shows that, unexpectedly, a rise in oil price would lead to increase in consumption. The research uses the data of three OECD countries of France, Canada and the United States from quarter 1st 1997 to quarter 3rd 2017 and vector autoregression model. Empirical results prove that a positive shock to oil price has a positive indirect effect on consumptions of France and Canada via both asset prices. The indirect effect of oil price on US consumption only exists through stock price. The duration of indirect effect of oil price on consumption depends on dependency of consumption to asset prices in each country.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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 designSimulation or modeling
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

Citations9
Published2022
Admission routes1
Has abstractyes

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