Abstract
Abstract
This study develops and applies a novel methodology for estimating state-level Gross Domestic Product (GDP) in Nigeria using satellite-recorded Nighttime Lights (NTL) data. Motivated by the absence of comprehensive subnational GDP statistics, the research integrates remote sensing and econometric modeling to provide spatially detailed insights into Nigeria’s economic dynamics. NTL intensity data, obtained from the Earth Observation Group, are combined with fixed effects panel regressions, β- and σ-convergence tests, and elasticity estimation to examine the relationship between luminosity and economic activity. Results reveal a strong, positive, and statistically significant correlation between NTL and GDP, with elasticity estimates of approximately 0.096 for growth rates and 0.207 for levels, and R² values up to 0.95 under fixed effects. The NTL-based GDP estimates broadly reproduce official state rankings and national aggregates, though systematic underestimation occurs in agriculturally oriented states and overestimation in highly illuminated but lower-output regions. Convergence analyses indicate both absolute and conditional convergence in per capita GDP, highlighting gradual regional equalization with structural heterogeneity. Findings confirm that while NTL is a valuable and cost-effective proxy for economic activity, it is not a perfect substitute - particularly for agriculture, informal sectors, and offshore production. The study recommends integrating NTL with other complementary indicators, developing state-specific adjustment factors and institutionalizing satellite-based monitoring within national statistical systems to enhance subnational economic tracking and evidence-based policymaking. Overall, the research demonstrates the practical viability of remote sensing as a tool for assessing and understanding regional economic performance in data-scarce environments.