Assessing Nigeria’s Resilience to Oil-price Volatility: Evidence from a Vector Autoregression of GDP Dynamics and Policy Buffers

Abstract

Aim: This study constructs a first-difference Vector Autoregression (VAR) model to analyze the dynamic interplay between global oil-price shocks and Nigeria’s real GDP over the period 1990–2023. Methodology: This study began by subjecting annual series of Brent crude prices and the World Bank’s GDP index to Augmented Dickey-Fuller and Phillips-Perron tests, confirming their integration of order one and justifying modeling in first differences. Optimal lag length is determined via Akaike, Schwarz, Hannan-Quinn, and FPE criteria, leading to a VAR(3) specification. Orthogonalized impulse-response functions reveal that a one-standard-deviation oil-price innovation yields a modest, transitory GDP response-peaking at approximately +0.9% in the second year and dissipating by year five-with all 95% confidence bands encompassing zero. Forecast-error variance decomposition further shows that oil-price shocks explain no more than 13% of GDP forecast variance at horizon ten, while endogenous dynamics dominate. Conversely, GDP innovations account for roughly 30% of oil-price variance after four years, underscoring limited feedback. Result: These findings corroborate rapid mean reversion documented in commodity-dependent economies and mirror evidence that oil revenues contribute marginally to output volatility. Conclusion: The paper concludes with policy prescriptions for rule-based stabilization funds, automatic fiscal triggers, and accelerated diversification into agriculture, manufacturing, and services to bolster macroeconomic resilience and sustain non-oil growth.