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Record W2103703399 · doi:10.1017/s1365100513000084

HOW DO INTERNATIONAL STOCK MARKETS RESPOND TO OIL DEMAND AND SUPPLY SHOCKS?

2013· article· en· W2103703399 on OpenAlexaboutno aff
Jochen Güntner

Bibliographic record

VenueMacroeconomic Dynamics · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsStock (firearms)Oil supplyOil priceStock market crashMonetary economicsAggregate demandStock marketDemand shockFinancial economicsMonetary policy

Abstract

fetched live from OpenAlex

Building on Kilian and Park's (2009) structural VAR analysis of the effects of oil demand and supply shocks on the U.S. stock market, this paper focuses on the differences and commonalities of stock price responses in oil exporting and importing economies in 1974–2011. Structural oil price shocks add to our understanding of the 2008 stock market crash. I find that unexpected reductions in world oil supply do not affect stock returns in any of six OECD countries. Although an increase in global aggregate demand consistently raises oil prices and cumulative real stock returns, the effect is more persistent for oil exporters. Other, e.g., precautionary oil demand shocks have a detrimental impact on stock markets in oil-importing countries, a statistically insignificant effect for Canada, and a significantly positive effect for Norway. Oil price shocks account for a larger share of the variation in aggregate international stock returns than in national stock returns.

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)0.005
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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

Citations89
Published2013
Admission routes1
Has abstractyes

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