Economic Growth in Sub-Saharan Africa: An Analysis of the Technical Efficiency of Natural Resource Rent and Institutions Based on a Copula Stochastic Frontier Model

This study employs a copula-based stochastic frontier modeling (copula-SFM) framework to empirically assess resource-rich countries’ efficiency in utilizing resource rent within Sub-Saharan Africa. The primary objective is to provide robust scientific evidence to aid these nations in maximizing their mineral resource utilization. Model selection criteria, specifically the Bayesian Information Criterion (BIC) and Akaike Information Criterion (AIC), identify the Normal copula-SFM as the superior choice. The findings emphasize the pivotal role of government effectiveness and population growth as strong, positive determinants of per capita income in the selected countries. In terms of average technical efficiency (TE) scores, Equatorial Guinea leads the rankings with an impressive score of 0.9907, while Tanzania trails with the lowest average TE score of 0.8177. These results underscore the potential for enhancing resource-rich countries’ economic performance through effective governance and managing population growth.