Explore publications.

The efficient integration of young people into the global job market is fundamental to sustainable development, significantly impacting economic stability, social unity, and demographic benefits. This study examines the determinants of youth labour absorption across key economic sectors in South Africa. The study uses the autoregressive distributed lag (ARDL) model to analyse sector-specific time-series data. The empirical findings show that youth labour market outcomes are influenced by both macroeconomic and microeconomic factors, with varying effects across economic sectors. The identified key determinants of youth labour absorption include economic growth, skills levels, labour costs, capital- or labour-intensity, profitability, and investment. In the manufacturing sector, for example, a rising capital-to-labour ratio was identified as one of the key constraints on youth labour absorption, while relatively low labour costs supported youth labour absorption in the community and social services sector. These sector-specific insights highlight the necessity of differentiated policy responses. Accordingly, the study recommends targeted strategies to promote inclusive economic growth, bridge skills mismatches, and encourage investment in labour-intensive industries.

This study aims to examine the causes and impacts of unemployment in South Africa using data from the 2022 General Household Survey conducted by STATS SA. Specifically, it seeks to analyze the demographic and socio-economic factors influencing unemployment rates, explore the implications of unemployment on individuals and society, and identify policy implications for addressing this pressing issue. Unemployment remains a significant challenge in South Africa, with persistent high rates that disproportionately affect certain demographic groups. This study addresses the need for an in-depth analysis of unemployment dynamics, providing valuable insights into its causes, consequences, and potential policy interventions. The study utilizes data from the 2022 General Household Survey conducted by STATS SA, encompassing a total population of approximately 18738 households. The dataset offers comprehensive information on employment status, demographic characteristics, education levels, and household income. Employing the statistical software SPSS, employing a combination of descriptive statistics, cross-tabulation, and a binary logistic regression model, the research uncovers significant disparities across demographic groups, shedding light on the challenges faced by individuals at the household level and advocating for targeted policy interventions. Gender disparities emerge starkly, with female-headed households constituting 44% of the sample yet reporting lower employment rates (34.7%) compared to male-headed households (59.6%). Regression analysis confirms this trend, highlighting the gender-based hurdles in accessing employment opportunities. Furthermore, concerning trends in youth unemployment are revealed, with nearly 40% of individuals under 35 reported as unemployed. Regression analysis demonstrates a negative association between age and unemployment, emphasizing the need for targeted youth employment initiatives. Additionally, the study underscores the critical role of education in enhancing employment prospects, with higher levels of education associated with lower unemployment rates. Racial disparities in unemployment rates are also elucidated, with the Black/African population group facing the highest unemployment rate at 52.3%, significantly higher than the Asian/Indian (37.8%) and White (40.4%) population groups. Regression analysis confirms these disparities, necessitating targeted efforts to address structural barriers and promote racial equity in the labor market. The study recommends, implementing gender-sensitive employment policies, enhancing youth skills development programs, and promoting equitable access to education and training opportunities for all groups.