Abstract
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.
Publisher
African - British Journals
Reference44 articles.
1. Babtunde S, Omotosho and Sani I. Doguwa (2012): Understanding the dynamics of Inflation in Nigeria; A GARCH Perspective. CBN Journal of Applied Statistics, Volume 3, NO.2 pp 51-74
2. Bala D. A. and Asemta J. O (2013): Exchange rate volatility in Nigeria: application of GARCH models with an exogenous break. CBN Journal of statistics 4(1)
3. Bala, D. A. & Takimoto, T. (2017). Stock markets volatility spill-overs during financial crises: A DCC-Multivariate GARCH with skewed-t density approach. Borsa Istanbul Review, 17(1), 25-48.
4. Bollerslev, T (1986). Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics, 31, 3, pp.307-327
5. Bollerslev, T (1990). Modelling the Coherence in short-Run Nominal Exchange Rates. A Multivariate Generalized ARCH Model. The Review of Economics and Statistics. Vol. 72, No.3, 498-505.