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Record W2922526533 · doi:10.1002/ijfe.1692

Crude oil price shocks, monetary policy, and China's economy

2018· article· en· W2922526533 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Finance & Economics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversity of Windsor
FundersChina Scholarship CouncilFundamental Research Funds for the Central UniversitiesCentral South UniversityMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsEconomicsMonetary policyChinaMonetary economicsOil priceInflation (cosmology)Crude oilShort runVector autoregressionMacroeconomics

Abstract

fetched live from OpenAlex

Abstract This paper develops a time‐varying parameter vector autoregressive model to examine the dynamic effects of crude oil prices and monetary policy on China's economy during January 1996 to June 2017. The empirical results indicate that (a) in general, international crude oil price shocks have positive effect on China's economic growth and inflation in the short run, but the long‐run effect appears diverse; (b) China's monetary policy shocks have positive effect on the economic growth and inflation overall; specifically, an increase in monetary supply can partly offset crude oil prices' negative effect on China's economic growth; (c) China's monetary policy has positive effect on crude oil prices and plays an important role in the relationship between crude oil price shocks and economy; and (d) during the recent global financial crisis, crude oil price shocks produce greater negative effect on China's economic growth, whereas the long‐run effect of monetary policy on China's economic growth proves weaker, compared with other periods.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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