ORIGINAL RESEARCH article
Front. Hum. Dyn.
Sec. Population, Environment and Development
Hidden Spatial Inequalities in Youth Unemployment in Gauteng: ImplicationsNeed for Place-Based PolicyInterventions Exploring the Spatial Variation of Youth Unemployment in Gauteng Using Geographically Weighted Regression
Provisionally accepted
- Human Sciences Research Council, Pretoria, South Africa
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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). and Geographically Weighted Regression (GWR). Geographically Weighted Regression (GWR)GWR iswas 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. To examine how the relationships between youth unemployment and selected socioeconomic factors vary across space, Geographically Weighted Regression (GWR) was applied. Ordinary Least Squares (OLS) regression first showed significant global correlations between youth unemployment and several variables, while the use of GWR was justified after diagnostics tests verified spatial non-stationarity. Significant spatial heterogeneity was seen noticed in the GWR results, with Ekurhuleni, Sedibeng and parts of City of Johannesburg showing stronger associations between youth unemployment and these factorsselected variables. The determinants of youth unemployment are highly place-specific as indicated by the significant variation in local model performance across wards (Llocal R2 values showed that the model's explanatory power varied across wards, 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. Dissatisfaction with government initiatives and job search difficulties showed the strongest spatial relationships with youth unemployment according to local bivariate analysis. The findings emphasize the necessity for policy measures that are spatially focused and address the distinct local characteristics affecting youth unemployment.
Keywords: Gauteng5, GCRO Quality of Life Survey3, Geographically weighted regression2, Local bivariate relatioship4, Youth Unemployment1
Received: 05 Dec 2025; Accepted: 30 Jan 2026.
Copyright: © 2026 Moeti, Mokhele and Fundisi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Thabiso Moeti
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