A number of scholars (Bronfman, 2014; Kane, 2008; Bici Rodrigue, Kneebone, and Reeves, 2016) have explored various ways to measure poverty through a multidimensional lens, yet such studies have seldom concentrated on the Sub-Saharan African region. Sida (2017) identifies essential aspects like access to opportunities and resources as vital elements of poverty, while Bici and Çela (2017) underscore the pivotal role of education. Similarly, Rodrigue, Kneebone, and Reeves (2016) stress the importance of healthcare access and employment status as integral to understanding poverty's complexity. These differing perspectives highlight the absence of a unified framework for defining the dimensions of poverty. Given recent global and local developments, such as the COVID-19 pandemic, ongoing conflict in Israel, severe power outages, and rising unemployment, there is a pressing need for updated, context-specific research, especially focused on the realities in South Africa. This paper aims to focus on socioeconomic and macroeconomic dimensions of poverty, including financial inclusion, that mainly affect South Africa namely. The main variables taken into consideration are standard of living, inequality, unemployment, education, health, interest rates and inflation and financial inclusion. One of the most significant findings of this study is the undervalued but critical role of financial inclusion in influencing multiple dimensions of poverty, especially education and employment. Policies aimed at enhancing access to affordable credit, mobile banking, insurance, and financial literacy, particularly in rural and informal communities, should be mainstreamed into the country’s broader poverty alleviation agenda. Future studies should include psychological and sociological impacts of poverty, including dignity, mental health, and social exclusion. They should also include Intra-household deprivations, especially how gender, age, or disability may influence the way poverty is experienced. Such approaches would provide richer, context-sensitive data and allow for intersectional analysis of poverty dynamics.
Thulo et al. (Thu,) studied this question.