Abstract
The primary objective of this research paper was to investigate the determinants of poverty in South Africa in the aftermath of the Covid-19 pandemic. To accomplish this, the study employed data from STATS SA collected in 2021, calculating the poverty status of households based on the national poverty line, and generating a binary variable comprising two categories: poor and non-poor. The research employed descriptive, cross-tabulation analysis and binary logistic regression models to ascertain the associations between selected independent variables (gender, age, household size, population group income, and province) and the dependent variable (poverty status). The findings demonstrated that 62% of the households surveyed were living below the upper-bound poverty line, with 49% classified as poor based on the lower-bound poverty line. Furthermore, the regression analysis revealed that gender, age, and income were significant predictors of poverty status, with females, younger household heads, and those with lower incomes being more likely to be poor. The paper concludes with a set of recommendations for the South African government to mitigate poverty, such as investing in education and skills development, promoting job creation, expanding social protection programs, and enhancing access to fundamental services such as water and sanitation.
Publisher
Center for Strategic Studies in Business and Finance SSBFNET
Subject
General Earth and Planetary Sciences,General Environmental Science
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