article · African Journal of Mathematics and Statistics Studies
An investigation into Nigeria crude oil production and price volatility assessed the stationarity and positive definiteness of multivariate time series data. Testing confirmed the stationarity of the series. Several multivariate autoregressive conditional heteroscedasticity models were fitted to crude oil price and production volatilities, with the MARCH [p (3,1)] specification emerging as the best performer according to model selection criteria. The analysis confirms a mutual interaction and bilateral causality between oil production levels and market prices. Shocks in oil prices consistently correlate with significant fluctuations in production volumes, leading to disruptions in national economic development. To mitigate these adverse impacts, proactive strategies are suggested to maintain stable crude oil output during periods of international market instability.
Crude oil revenue plays a critical role in resource-dependent economies. Demonstrating that oil price shocks drive domestic production swings helps explain how global market instability disrupts national economic planning. Understanding the two-way relationship between price and output provides an empirical basis for designing policies aimed at cushioning economic growth against volatile international commodity markets.
The statistical modelling could inform macroeconomic forecasting tools, treasury risk management frameworks, and energy sector planning used by central banks, energy ministries, or economic analysts. The work remains at an early, theoretical stage of econometric modelling, as the abstract describes model fitting and statistical tests rather than an operational forecasting platform, validated policy toolkit, or commercial software product.
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Modelling of Nigeria's Crude Oil Production and Price Volatilities was the major focus of this paper. The paper investigated the stationarity of the multivariate time series positive definiteness property, and the results revealed the stationarity of the multivariate time series. Special classes of MARCH and MGARCH models were fitted to the crude oil price and production volatilities, and MARCH [p (3,1)] outperformed other models with the aid of model selection criteria. The research has established interaction and interdependence between the two macroeconomic variables and has also revealed bilateral causality between crude oil production and price. This further substantiates the fact that every regime of oil price shock is tantamount to high variability in production, which, in effect, causes a setback in the economic development of the affected country. Hence, this paper proposes proactive measures that can always guarantee stability in crude oil production whenever the country experiences instability in the oil price in the international market.
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DOI: 10.52589/ajmss-l4fi9dw6
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