Underemployment and unemployment in South Africa’s informal sector: a case study of Potchefstroom
The main aim of this study is to investigate the prevalence, type and probable effects of skills-related underemployment in the car-guarding, waste-picking and day-labouring informal sub-sectors of South Africa’s informal economy, using the town of Potchefstroom as a case study. The study also briefly investigates the prevalence of unemployment in the day-labouring sub-sector of Potchefstroom. The study focused on three informal sub-sectors of the informal economy of Potchefstroom; car-guarding, day-labouring and waste-picking. Cross-sectional data was collected for the periods 2014 to 2016 through survey questionnaires. A two-prong concurrent mixed method approach was used where the quantitative aspect of the analysis was aimed at determining the prevalence of skills-related underemployment as well as its probable significant relationship with the dependent variables of choice. The qualitative method was aimed at providing insights into the educational attainments of the respondents as well as the underlying reasons behind them, in order to further understand their entrance and continuation in the informal economy. Furthermore, the unemployment levels of day-labourers were investigated as well as variables that could possibly explain these levels in the Potchefstroom market. The results of the study found that there was a minimum prevalence of 48% skills-related underemployment across all three sub-sectors; the car-guarding sector having the highest incidence. Vocational overskilling was identified as the type of skills-related underemployment, which is present across all three sub-sectors. Furthermore, the results found that skills-related underemployment only has a significant relationship with the income of car-guards; the incomes of day-labourers and waste-pickers were not significantly associated with skills-related underemployment. The study also revealed that most of the respondents of the day-labouring sector had faced a 60% unemployment rate in the week of reference, whilst 25% had faced 100% unemployment in the week of reference. The qualitative analysis indicated that a vast majority of the respondents had very low levels of educational attainment.