Mapping social assistance in Gauteng

Introduction

South Africa's social assistance programme is the largest on the African continent. It plays a significant role in mitigating the impact of poverty and income inequality through supporting the livelihoods of vulnerable, qualifying households (Mackett, 2020; Satumba et al., 2017).

Nationally, the percentage of households receiving grants increased from 30.8% in 2003 to 52.4% in 2020, following the introduction of the Social Relief of Distress (SRD) grant. It declined slightly to 50% in 2023 (StatsSA, 2024). Similarly, successive iterations of GCRO’s Quality of Life Surveys show a consistent increase in grant receipt over the last decade and a half. In QoL II (2011), 30% of respondents indicated that they live in a grant-receiving household. This figure increased to 48% in QoL 6 (2020/21), following the introduction of the SRD grant. In the QoL 7 (2023/24) survey, 50% of respondents indicated that at least one member of their household receives a social grant of any type (Modiba et al., 2024).

Using data from the QoL 7 (2023/24) survey, this Map of the Month examines the spatial distribution of households receiving any type of grant in Gauteng. Although half of respondents live in households where at least one member accesses a grant, the data reveals significant spatial variation in the concentrations of grant-receiving households across the province. These patterns illuminate the continued spatial variation in the location of poverty and vulnerability in our still highly unequal province.

A deeper analysis of the gendered dimension of social assistance reveals how patterns of grant receipt reflect structural gender inequalities. The proportion of female-headed households receiving grants is significantly higher than male-headed households across all municipalities and race groups. These disparities are particularly pronounced in low-income, peripheral areas. Although there are a number of intersecting factors that contribute to gendered patterns of grant receipt, the Map of the Month focuses on two critical points: the design of certain grants and their relationship to social expectations surrounding care work, and the barriers that women face in the labour market. The analysis has implications for any redesign of the existing social grant architectures, and for how social assistance ought to articulate with broader welfare programmes targeting social vulnerability of women.

The distribution of social grants across Gauteng

Social grants are currently distributed through a means tested system, primarily targeting caregivers of children, persons with disabilities and the elderly. Additionally, the Social Relief of Distress (SRD) grant was dramatically expanded after the Covid-19 pandemic to target unemployed individuals of working age (Modiba et al., 2024). In QoL 7 (2023/24), 31.6% of respondents indicated that they were receiving this grant. Although grant receipt has increased, the proportion of respondents living in households that solely rely on a social grant as their income has decreased from 18% in 2015/16 to 2% in 2023/24 (Mushongera et al., 2024). This suggests that while more households are accessing grants, they are increasingly being used as supplementary rather than primary income sources.

Figure 1 shows the spatial variability of households receiving social grants across the province by mapping the percentage of respondents in each ward who indicated that at least one of the members of their household received a social grant. It indicates significant variation in the spatial concentration of grant receipt. Because household and personal income are key factors used in means testing for grants, the spatial pattern of social grant receipt closely mirrors that of household income across the province. This pattern reflects deeply entrenched spatial inequalities where income levels are highest in the core of the province and lowest at the peripheries (Mushongera et al., 2024). Accordingly, social grant receipt reaches higher levels (frequently higher than 60%) in peripheral areas of the province, while remaining lower (less than 20%) in the central metropolitan areas where income levels and concentrations of economic activity are highest.

Wards with very high proportions (over 60%) of grant-receiving households are concentrated in specific areas: the southern parts of the City of Johannesburg (Soweto and Orange Farm), the northern parts of the City of Tshwane (Hammanskraal, Soshanguve, Mamelodi and Bronkhorstspruit), and the southern parts of the City of Ekurhuleni (Katlehong and Vosloorus). In Emfuleni and Lesedi, almost all wards have more than 40% of respondents living in households accessing grants. In Lesedi, this distribution ranges from 40.6% to 73.5%, while in Emfuleni, with the exception of wards surrounding Vanderbijlpark, grant receipt ranges from 40.4% to 91.5%. A large proportion of wards in the central corridor of Emfuleni have more than 60% of respondents living in grant-receiving households.

Figure 1: Distribution of grant-receiving households in Gauteng. Source: GCRO QoL 7 (2023/24) Survey.

Figure 2 provides a breakdown of grant-receiving households across municipalities. The municipalities with the lowest rates of grant receipt are Midvaal (45.5%), the City of Tshwane (48.1%), and the City of Johannesburg (48.4%). The municipalities with the highest rates of grant receipt are Emfuleni (64.9%), Merafong (54.4%), and Lesedi (54.2%). Emfuleni in particular stands out, with grant receipt rates 14.9% above the provincial average.

Figure 2: Distribution of grant-receiving households across municipalities in Gauteng. Source: GCRO QoL 7 (2023/24) Survey.

Household income per capita levels are particularly low across wards in Emfuleni, Merafong and Lesedi, ranging between R796 - R5 638 per month (Mushongera et al., 2024). Additionally, the survey reveals that these municipalities also have the highest proportions of households living on incomes below the food-poverty line (set at R760). In Emfuleni 22% of respondents live in households below the food-poverty line, followed by 20% in Lesedi, and 18% in Merafong (Mushongera et al., 2024). Notably, the City of Tshwane has a lower proportion of households receiving grants, but 19% of respondents live in households below the food-poverty line. The household income per capita levels within the northern parts of the City of Tshwane, where the highest levels of grant-receiving households are concentrated, also fall within the range of R796 - R5 638 per month (Ibid).

The patterns observed across the province indicate that while grants serve as crucial poverty alleviation mechanisms, they also reflect the deeper spatial inequalities that characterise income distribution across the province. The concentration of grant receipt in peripheral and low-income areas is a stark reminder of how economic vulnerability remains geographically concentrated in Gauteng.

Gender and social grant receipt in Gauteng

This section explores the gendered character of social grants, and contributes to literature on the feminised nature of social grant receipt in South Africa. The analysis compares patterns of grant receipt between female- and male-headed households, as well as households headed by both spouses/partners. QoL 7 (2023/24) data indicates that 37.9% of respondents live in female-headed households, 60% live in male-headed households, and 2.1% live in households headed by both spouses or partners. Of the respondents living in female-headed households, 64.7% reported that a household member receives a grant compared to 41.5% in male-headed households and 41.4% where both spouses/partners are household heads. This represents a considerable 23 percentage point difference in grant receipt rates between female- and male-headed households.

Figure 3 shows the distribution of social grants by the race and gender of household heads. Across all population groups, female-headed households reported higher percentages of grant receipt than male-headed households, though the magnitude of this difference varies by race. Black African and coloured female-headed households show much higher overall grant receipt rates, at 67.6% and 66.3% respectively, compared to Indian/Asian and white female-headed households, at 35.5% and 34.6% respectively. The difference in levels of grant receipt for female- and male-headed households is largest among coloured households (24.1%), followed by black African households (22.3%). Indian/Asian and white households reported the smallest differences (14.2% and 10.4%, respectively).

Figure 3: The distribution of social grants by household head and race. Source: GCRO QoL 7 (2023/24) Survey.

Figures 4 and 5 compare the spatial variability of grant distribution across female- and male-headed households across the province (households headed by both spouses/partners are excluded due to the small sample size per ward). While very few wards show over 80% grant receipt when examining all households in the province, isolating female-headed households reveals a pattern with much higher intensities of grant receipt in specific areas.

Figures 4 and 5: Comparison of the distribution of female- vs. male-headed grant-receiving households per ward in Gauteng. Source: GCRO QoL 7 (2023/24) Survey.

The contrast between the two maps is striking: grant receipt across wards for male-headed households (Figure 5) is more evenly distributed, with most falling in the 20% to 60% range per ward. In contrast, female-headed households (Figure 4) display a more extreme differentiation, with a much higher number of wards falling in the ranges above 60% per ward. The maps show that the gendered differences in grant receipt are amplified in peripheral areas, and the female-headed distribution mirrors the core-periphery economic pattern in Gauteng more starkly. This suggests that female-headed households may be disproportionately impacted by these patterns of spatial inequality.

Figure 6 shows the distribution of social grants across municipalities and by gender of the household head. As noted above, Emfuleni, Merafong and Lesedi have the highest proportions of households receiving grants. These municipalities also have the highest proportion of female-headed households receiving grants (at 77.7%, 73.2% and 70.4% respectively). Although households headed by both spouses/partners make up a minority in the province, these households access grants at higher rates than female- and male-headed households in Merafong, the City of Tshwane and the Midvaal (at 79%, 63.6% and 63.5% respectively).

Figure 6: Distribution of social grants across municipalities by household head. Source: GCRO QoL 7 (2023/24) Survey.

Two notable factors shape these gendered differences in grant receipt. Firstly, while certain grants like the Child Support Grant (CSG) are designed to be gender neutral, they become feminised in their implementation. The CSG is child-focused and has taken on a “feminised character (…) due to the prevailing social expectation that women should assume the primary caregiver role for children” (Kasan, 2024: 22). While this does not necessarily mean that female-headed households will automatically receive more grants, the distinct characteristics of female-headed households influence these patterns. For instance, female-headed households in Gauteng are more likely to be single-parent homes. According to the QoL 7 (2023/24) survey, 39% of grant-receiving female-headed households are single-parent homes compared to 34% for non-grant-receiving households. Only 7.5% of grant-receiving male-headed households, and 4.2% of non-grant-receiving households, are single-parent homes.

Secondly, structural gendered inequalities not only place the burden of care predominantly on women, but also limit women's participation in the labour market and result in lower income levels for female-headed households (Institute for Economic Justice, 2022). Data from the QoL 7 (2023/24) survey indicates that female-headed households experience higher levels of food insecurity than male-headed households, with 24% of female-headed households facing food insecurity compared to 12% of male-headed households (Mushongera et al., 2024). Additionally, female-headed households earn 50% less than male-headed households with average household income levels of R7 662 and R15 131, respectively (Ibid).

Conclusion

This Map of the Month reveals how expansive the social assistance programme is in Gauteng, but also the geographical variability in the proportion of households depending on social grants for income support. The pattern reflects the geography of spatial and economic inequality in the province. The gendered dimensions of grant receipt further highlight how multiple forms of inequality intersect to shape vulnerability in households. While social grants play a critical role in buffering households against the severe impacts of poverty, they cannot alone address the structural inequalities that households face.

The research has implications for how we think about broader social assistance reforms, including consideration of the Universal Basic Income Guarantee (UBIG), alongside strengthened social care infrastructure to address the root causes of vulnerabilities created by economic, spatial and gender inequalities. For example, the UBIG, without the “imposed eligibility criteria to exclude certain groups” (Institute for Economic Justice, 2022), will need to carefully consider the gendered nature of grant receipt in the current social assistance framework. We also need to carefully consider how social grant support ought to exist alongside a more developed and gender sensitive social welfare system that prioritises the provision of “high quality and widely accessible social care, and quality public services” (Kasan, 2024: 22) in order to fully support the intended developmental benefits of social grants.

References

Institute for Economic Justice (2022). Universal Basic Income Guarantee Factsheet Series: How a UBIG Can Advance Gender Justice and Social Cohesion. https://www.iej.org.za/wp-content/uploads/2022/12/IEJ-UBIG-5-fact-sheet-web.pdf

Kasan, J. (2024). Mapping South Africa’s Care Regime: Pathways to a care focused social policy. Economies of Care Working Paper Series #2. Institute for Economic Justice. https://iej.org.za/wp-content/uploads/2024/11/IEJ-CareEconomy2.pdf

Mackett, O. (2020). Social Grants as a Tool for Poverty Reduction in South Africa? A Longitudinal Analysis Using the NIDS Survey. African Studies Quarterly. 19(1). https://journals.flvc.org/ASQ/article/view/136019/140438

Modiba, M., Hassen, E-K, Labuschagne, H., Masinga, K., Radebe, M., Taldi, M., Erasmus, L., Nemavunde, M., Fani, N., Masango, B. and Machika, C. (2024). Inclusive Economies: Findings from the GCRO's Quality of Life Survey 7 (2023/24). GCRO Data Brief 20, October 2024. https://doi.org/10.36634/BNCK6336

Mushongera, D., Ndagurwa, P., Miles-Timotheus, S. and Hamann, C. (2024). Poverty and inequality: Findings from the GCRO's Quality of Life Survey 7 (2023/24). GCRO Data Brief 13, October 2024. https://doi.org/10.36634/HBXF9126

Ndagurwa, P., Naidoo, L. and Miles-Timotheus, S. (2023). The distribution of male-headed and female-headed households in Gauteng. Map of the Month. Gauteng City-Region Observatory. March 2023. https://doi.org/10.36634/TJJG2755

Satumba, T., Bayat, A. and Mohamed, S. (2017). The Impact of Social Grants on Poverty Reduction in South Africa. Journal of Economics, 8(1), 33-49. http://krepublishers.com/02-Journals/JE/JE-08-0-000-17-Web/JE-08-1-000-17-Abst-PDF/JE-08-1-033-17-250-Bayat-A/JE-08-1-033-17-250-Bayat-A-Tx[4].pmd.pdf

StatsSA (Statistics South Africa). (2024). General Household Survey 2023 [Statistical Release P0318]. Pretoria: Statistics South Africa. https://www.statssa.gov.za/publications/P0318/P03182023.pdf

Inputs, edits, and comments: Graeme Götz, Ebrahim-Khalil Hassen, Mamokete Modiba, Jason Bell, Dr Laven Naidoo, Dr Samkelisiwe Khanyile, and Christian Hamann

Suggested citation: Sango, A. (2025). Mapping Social Assistance in Gauteng. GCRO Map of the Month, Gauteng City-Region Observatory, May 2025. https://doi.org/10.36634/GERE9006.