His paper shares the findings from a study of the countries of Africa across a set of key socio-economic indicators, including life expectancy, birth and mortality rates, Education Index, Human Development Index, GDP per capita in PPP terms, unemployment rate, and healthcare spending per capita at PPP. The authors describe a set of interrelationships between the indicators via a correlation analysis. The paper provides a set of regression equations describing the dependence of life expectancy and the Human Development Index on a set of factors across several cluster groups. The authors’ findings from a cluster analysis of African countries across a set of key socio-economic indicators may be of practical and research significance for researchers studying economic and social development in the countries of Africa. Breaking the entire aggregate of countries down into several homogeneous groups helps improve the quality of economic analysis, more importantly the quality of forecasts into the future. It becomes a lot easier to work out other countries’ economic policy in respect of the countries under review if one examines not the entire aggregate as a whole but explores specific homogeneous groups of countries with similar socio-economic characteristics. This helps keep track of the dynamics of change in the cluster groups’ composition in the course of time, which can make it possible to detect straightaway a certain country acquiring whole new socio-economic characteristics and moving into a different cluster group with a higher or lower level of development.
Volume 11 | 08-Special Issue