MULTIVARIATE ANALYSIS OF ENERGY AS DRIVERS OF GROSS DOMESTIC PRODUCT (GDP) IN NIGERIA (2000–2022).

This study investigates the impact of energy-related variables on Nigeria's gross domestic product (GDP) from 2000 to 2022 using multivariate techniques.Specifically, it applies Principal Component Analysis (PCA) to reduce dimensionality across 33 variables spanning energy consumption, CO₂ emissions, and renewable electricity generation.The suitability of PCA was confirmed by a Kaiser-Meyer-Olkin (KMO) measure of 0.67 and a significant Bartlett's Test (p < 0.001).Two principal components explained approximately 81% of total variance.Component 1 captured industrial and fossil-based energy usage, while Component 2 represented environmental and renewable energy dynamics.A multiple linear regression of these components against GDP showed that both significantly predicted economic growth (R² = 0.954, p < 0.001), with Component 1 having a stronger influence.The findings underscore the importance of optimizing energy policy to support economic growth while transitioning to cleaner energy systems.Recommendations include strengthening investment in renewable energy and improving energy efficiency for industrial sectors.