Economic growth in Sub-Saharan Africa: analysis of technical efficiency of natural resource rent and institutions based on a Copula Stochastic Frontier model

Abstract

This thesis employs a copula-based stochastic frontier modeling (copula-SFM) framework to empirically assess the efficiency of resource-rich countries 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. It was discovered that the countries that have effectively managed their resource wealth avoided the resource curse through a three-pronged strategy. These countries pursued economic diversification, de-linked government expenditure from revenue, and invested surplus revenue for the benefit of future generations. It is recommended that low performing countries enhance their performance by accelerating diversification and increasing private sector participation by creating a favorable environment for business and innovation. They are also encouraged to digitalize and expand internet access, which can open new markets and harness the region's inherent dynamism and creativity.