@article{409,
author = "O.B. Akanbi and K.A. Alobaloke",
abstract = "As a result of the adverse macroeconomic effect of oil price fluctuations on welfare, fiscal budgeting, trade performance, international competitiveness and the whole economy, oil prices remain a subject of utmost concern and interest to policy makers. Therefore, the need to investigate predictors of oil price measures arises. The model averaging methods considered uncertainty as part of the model selections, and includes information from all candidate models. Thus, this study investigated the main predictors for Nigerian Oil prices using the Bayesian and Dynamic Model Averaging (BMA, DMA) Techniques. The study considered sixteen (16) predictors cutting across oil and financial sectors of the Nigerian economy. The results for both model techniques showed that refinery capacity and the exchange rate are the main potential determinants of oil prices in Nigeria. These predictors can be considered as the leaders of the modelling procession over the selected periods.",
issn = "23942894",
journal = "IJASM",
keywords = "Bayesian Model Averaging;Dynamic Model Averaging;Oil Price;Exchange Rate",
month = "September",
number = "5",
pages = "52-60",
title = "{M}odelling {O}il {P}rice in {N}igeria {U}sing {BMA} and {DMA} {T}echniques",
volume = "10",
year = "2023",
}