Hidden spatial inequalities in youth unemployment in Gauteng
Need for place-based interventions
Bibliographic Data
| ID | 13136621 |
|---|---|
| Authors | Thabiso Moeti (0000-0002-1313-9023, Human Sciences Research Council, corresponding author), Tholang Mokhele (0000-0002-9087-7951, Human Sciences Research Council), Emmanuel Fundisi (0000-0002-1609-1029, Human Sciences Research Council) |
| Year | 2026 |
| Volume | 8 |
| Publication date | 2026-02-18 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Human Dynamics (JOURNAL) |
| Journal identifiers | ISSN: 2673-2726 • E-ISSN: 2673-2726 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fhumd.2026.1761649 |
| OpenAlex | W7130386949 |
| Language | EN |
| References cited | 11 |
One of South Africa's most persistent socioeconomic challenges is youth unemployment with rates among young people consistently higher than the national average. This study examined the spatial variation of youth unemployment in Gauteng province using data from the Gauteng City-Region Observatory (GCRO) Quality of Life Survey 7 (2023/24). Geographically Weighted Regression (GWR) was used to show how the relationships between youth unemployment and significant socioeconomic factors vary across space, instead of assuming that these relationships are uniform across the province. Youth dissatisfaction with government job creation initiatives, educational attainment, perceived job difficulties in finding work, gender and living in informal dwellings are the main focus of the analysis. Significant spatial heterogeneity was noticed in the GWR results, with Ekurhuleni, Sedibeng and parts of City of Johannesburg showing stronger associations between youth unemployment and these factors. The determinants of youth unemployment are highly place-specific as indicated by the significant variation in local model performance across wards (local R 2 ranging from 0.39 to 0.77). These findings demonstrate that highly variable local factors influence youth unemployment in Gauteng and that place-based, spatially focused policy interventions are required rather than uniform, province-wide solutions
Government (linguistics · Inequality · Poverty · Psychological intervention · Public policy · Socioeconomic status · Spatial inequality · Unemployment · Youth unemployment · Regional Economics and Spatial Analysis · Spatial and Panel Data Analysis · Urban, Neighborhood, and Segregation Studies
| Highly cited | No |
|---|