Human development measures create a better picture of how a population is developing on average than income measures such as GDP per capita can. This includes considering inequalities within this measure. The data shows that the inclusion of inequality lowers the general human development level of a nation, and that improving the value of the Inequality Adjusted Human Development Index lends itself to the notion of inclusive growth. This dissertation analyses the relative importance of corruption, foreign aid and digital infrastructure in explaining the Human Development Index and Inequality-Adjusted Human Development Index values of 28 nations in Sub-Saharan Africa between 2010 and 2017. Using principal component analysis, a set of digital infrastructure variables are reduced for use in a 2SLS Fixed Effects regression model to account for omitted variables and simultaneity. The results reveal that digital infrastructure in all its forms has the potential to become a tool to help increase inclusive development across the continent, whilst corruption reduction also has a positive effect on both measures. Foreign aid, however does not have a significant impact upon either measure during the period assessed. The analysis also supports the notion that poor data availability has a detrimental impact upon the breadth and depth of research that can be conducted in this field. The recommendations as a result of this analysis include increased investment into all aspects of digital infrastructure in order to support inclusive human development and improve the capacity for future research and policy decisions.
PLEASE NOTE: You must be a member of the University of Lincoln to be able to view this dissertation. Please log in here.