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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.

Marriage, despite its evolving role in society, has for generations played a fundamental role in shaping social relations. This paper examines household income by gender and the marital status of the head of household, with a focus on assessing the average total incomes for these different groups. The significance of household income in determining a household's poverty status cannot be overstated. While the use of multidimensional measures of poverty, such as the Multidimensional Poverty Index (MPI) and other household resources, has increased, it remains true that these measures are directly influenced by the household's income level. Therefore, household income continues to be the primary determinant of poverty. Analyzing income dynamics by gender provides insight into broader household issues, such as gender relations and the significance of marital status in the 21st century. The study employed Ordinary Least Squares (OLS) regression and descriptive analysis to derive the results. The findings indicate that married individuals have higher household incomes compared to all other groups. Notably, never-married single females have the lowest income among these groups. The analysis also reveals that, on average, males have higher incomes than females within the same marital status categories. These results confirm that both gender and marital status continue to influence household income levels. The policy implication is that, while marriage cannot be regulated, gender disparities can be addressed to ensure that individuals with the same qualifications and experience receive equal pay. To address these disparities, it is recommended that policies focus on promoting equal pay for equal work and enhancing women's economic empowerment, particularly for vulnerable groups. Supporting cohabiting households through legal and financial protections will also contribute to improved economic stability. These measures aim to reduce income disparities associated with gender and marital status, ultimately fostering greater social equity and economic growth.

Marriage, despite its evolving role in society, has for generations played a fundamental role in shaping social relations. This paper examines household income by gender and the marital status of the head of household, with a focus on assessing the average total incomes for these different groups. The significance of household income in determining a household's poverty status cannot be overstated. While the use of multidimensional measures of poverty, such as the Multidimensional Poverty Index (MPI) and other household resources, has increased, it remains true that these measures are directly influenced by the household's income level. Therefore, household income continues to be the primary determinant of poverty. Analyzing income dynamics by gender provides insight into broader household issues, such as gender relations and the significance of marital status in the 21st century. The study employed Ordinary Least Squares (OLS) regression and descriptive analysis to derive the results. The findings indicate that married individuals have higher household incomes compared to all other groups. Notably, never-married single females have the lowest income among these groups. The analysis also reveals that, on average, males have higher incomes than females within the same marital status categories. These results confirm that both gender and marital status continue to influence household income levels. The policy implication is that, while marriage cannot be regulated, gender disparities can be addressed to ensure that individuals with the same qualifications and experience receive equal pay. To address these disparities, it is recommended that policies focus on promoting equal pay for equal work and enhancing women's economic empowerment, particularly for vulnerable groups. Supporting cohabiting households through legal and financial protections will also contribute to improved economic stability. These measures aim to reduce income disparities associated with gender and marital status, ultimately fostering greater social equity and economic growth.

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.