The paper investigates the prevalence of extreme poverty in a panel of 39 sub-Saharan African (SSA) countries over the period 2000–2018 while accounting for spillover effects.
The study adopts the recently developed spatial dependence-consistent, bias-corrected quasi-maximum likelihood (QML) estimators and the linear dynamic panel regression to control for the potential endogeneity in poverty and corruption spillovers.
The spatial model shows. consistently across all the specifications, that there is a substantial spillover effect of corruption and poverty across the region. Additionally, the study also found that investment in health and education is a significant determinant of poverty in the region. However, the effectiveness of these policy variables to reduce poverty declines in the face of corruption spillovers. More importantly, the empirical analysis shows that poverty does not only exhibit spatial spillovers but also has a persistent effect over time. The results, therefore, suggest that to reduce poverty in the region, sub-Saharan African governments must adopt spatially differentiated policies and programmes by working together to reduce unemployment and corruption in the region, and not the widely adopted spatially mute designs currently in place. The research and policy implications are discussed.
The study accounts for spatial dependency and spillover effects in the analysis of poverty and corruption in SSA
