The nexus between fossil energy markets and the effect of the COVID-19 pandemic on clustering structures
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.
Bibliographic record
Abstract
The main purpose of this paper is to analyze price returns series to investigate causality between international fossil energy markets and the effect of the COVID-19 pandemic on their clustering structures. The sample period covers August 1993 to June 2023. The empirical results from Granger causality applied to tests show ( i ) no evidence of causality in both directions between Australian coal and Brent, and between Dubai crude oil and Australian coal, ( ii ) evidene of 52 unidirectional causal relationships across international fossil energy markets, and ( iii ) evidence of bidirectional causality between US gasoline and Brent, South African coal and Australian coal, Indonesian natural gas and Australian coal, Russian natural gas and Australian coal, and between South African coal and Russian natural gas. Besides, results from agglomerative hierarchical clustering show that the COVID-19 pandemic affected the structures in the clusters in fossil energy markets and increased the similarity between them. Overall, we provide insights about the connectedness and clustering among major international fossil energy markets to highlight important system dynamics that could be helpful for policy makers, traders and investors.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it