Bibliographic record
Abstract
In the wake of Arab world crisis that already causes oil supply disruptions and oil price increases, the present dissertation records and sheds light to the main historical oil prices shocks from the 1970s till nowadays and the main determinants of oil prices and economic growth. With the ultimate purpose being the examination of the much debated effect of oil price on the economic growth, we test and analyze the existence and the type -bidirectional or unidirectional, short-term or long-term- of this relation and the degree of influence for the main industrialized G7 countries (the USA, the UK, Italy, France, Germany, Japan and Canada) during the 1990-2007 period (quarterly basis data). The Augmented Dickey Fuller Unit Root Test is used in order to prove if the time series variables (GDP and oil prices) are stationary or non- stationary, the Johansen approach is used for tracing or not cointergration, the Error Correction Model (VEC) in case of cointegration existence while on the occasion that no cointergration is proved, we use Granger Causality test. The empirical results mainly suggest the existence of a relation- albeit different but with some common characteristics across the G7 countries. In all countries except for Canada, there is cointegration between oil prices and GDP in the long-term. In all countries except for Canada there is bidirectional relation in the long-term. In Germany, France, Italy and Japan the relation between oil prices and GDP is negative. In Germany the relation is unidirectional in the short-term where the oil prices affect the GDP. In the UK and in Japan there is unidirectional relation in the short-term where the GDP affects oil prices. In Canada, the UK and in the USA the relation is shown positive. In the case of Canada there is unidirectional relation where the GDP influences oil prices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".