Abstract
The poor in Sub-Saharan Africa (SSA) are in a worse predicament than their counterparts in other regions. The goal of this study was to establish the key drivers of poverty in SSA by looking at how economic variables affect growth and poverty. Data from ten SSA nations—upper-middle-income countries (UMIC), lower-middle-income countries (LMIC), and low-income countries (LIC)—were analyzed based on historical values from 2015 to 2019. From the six economic variables studied, the best model reveals that 78% of the differences in poverty can be accounted for using a methodical, statistical approach. Poverty and unemployment rates have a substantial positive relationship (p = 0.001662). The gross domestic product (GDP) growth rate and poverty have a slight link, which is significant at the 10% level (p = 0.067) but is not a significant contributor to poverty alleviation. The secondary school enrolment rate has no bearing on poverty variation (p = 0.33). Increased GDP does not necessarily correspond to poverty reduction. Unemployment, on the other hand, is a major contributor to poverty in the region. Moreover, education (secondary school ennoblement) plays a less important role in reducing poverty, whereas per capita personal consumer spending and GDP growth rate have a bigger impact on poverty reduction. The proposed theoretical and numerical model works on general indicators and trends; it does not guarantee that people in the UMIC, LMIC, and LIC countries may not fall below the international poverty line ($1.90 per day). The poverty rates are predicted to climb by more than 2% by 2030, postponing poverty elimination in the SSA region by almost five years. This signifies that more than half of the SSA population will remain poor.
Funder
University of the Free State
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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