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Record W2814120368 · doi:10.7441/joc.2018.02.08

THE CURRENT ACCOUNT AND OIL PRICE FLUCTUATIONS NEXUS IN NIGERIA

2018· article· en· W2814120368 on OpenAlexaboutno aff
Oluwole Oluniyi Adelokun, Olawunmi Omitogun

Bibliographic record

VenueJournal of Competitiveness · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsNexus (standard)Oil priceCurrent (fluid)EconomicsMonetary economicsMacroeconomicsPhysicsThermodynamicsComputer science

Abstract

fetched live from OpenAlex

Considering Nigeria as an oil dependent country, fluctuations in oil prices as a result of policy competition between OPEC and oil shale producing countries (such as the United States and Canada) in recent years has posed an impediment on the current account balances of Nigeria.This study investigates the relationship between oil price fluctuations and the current account balances in Nigeria.The study used a time series data sample from 1977 to 2015.The Autoregressive Distributed Lag (ARDL) was used to estimate the relationship between the current account and oil price fluctuations in the short-run and long-run.It was argued from the findings that in the short-run, the oil price had a positive but insignificant impact on the current account balances, while in the long-run, it impacted negatively, but was found to be a significant determinant of current account balances in the economy.Other variables such as population growth (POP), gross domestic product (GDP) and trade (T) had an insignificant relationship with the current account balances in the short-run, while in the long-run, only GDP and oil price (OP) were found to be significant determinants of the current account balances in the economy.The study, therefore, concludes that better performances of the current account balance in the Nigerian economy are a function of the stability in the oil price.From the findings, it was recommended that the economy should be tailored towards mitigating the shocks in oil price through considering alternative means of trade.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.252
Teacher spread0.234 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2018
Admission routes1
Has abstractyes

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