OIL PRICE BEHAVIOUR, EXCHANGE RATE MOVEMENT AND THE COVID-19 PANDEMIC IN NIGERIA: ANALYSIS OF THE FIRST THREE QUARTERS OF 2020
Bibliographic record
Abstract
This paper evaluates the response of oil price and exchange rate to the corona virus pandemic shock aside from the link between oil price and exchange rate for the first three quarters of 2020 in Nigeria. The theoretical framework emanates from the informal approach and the terms of trade channels. Using VAR cointegration approach, results show existence of long run relationship among the oil price, exchange rate movement and the corona virus indicators based on Max-Eigen and Trace test statistic. End of first quarter oil price, discharge rate and fatality rate negatively relate with current exchange rate. First quarter exchange rate and fatality rate positively relates to oil price behaviour in the third quarter while end of first quarter discharge rate increase fosters oil price decline. First quarter spread rate increase gradually reduces oil demand and the price in the third quarter. All corona virus indicators and exchange rate variable Granger Cause current oil price. Diversification is key to widen export base and increase foreign exchange and stability. Policy measures to sustain the economy in the post COVID-19 and beyond are necessary for long term development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".