Further Evidence on Asymmetry in the Impact of Oil Price on Exchange Rate and Stock Price in China using Daily Data
Bibliographic record
Abstract
The role of oil price on the macro-economy has been intensely researched. However, oil remains one of the most important energy sources for production. Concerning China, there are projections that the country’s energy consumption would have risen to 18 billion barrels per day in the next two decades. Given China’s heavy reliance on oil, we reexamine the impact of oil price on the US dollar-Renminbi rate and the Shanghai index using daily data from 4/01/2010 to 29/03/2021. In our analysis, we apply the Nonlinear ARDL technique in the presence of structural breaks and find that oil price has asymmetric impact on exchange rate and stock price in the short-run alone. However, the asymmetry is only in terms of magnitude and not in terms of effect direction. Oil price is found to appreciate the Renminbi vis-à-vis the US dollar and to increase stock price significantly both in the short-run. We find that accounting for structural breaks is necessary for cointegration in using oil price to explain both variables.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".