Measuring accessibility of government housing programmes
City regions like Gauteng provide a range of services that contribute to improving quality of life, such as schools, shops, hospitals and clinics, parks and public transport. However, in order to make a difference, these services need to be accessible to potential users. To enhance liveability, cities such as Melbourne, Australia, are pursuing the ‘20 minute city’ where people can access most of the things they need within a 20-minute walk, cycle or public transport trip. Although a range of factors - such as overall city size, density and zoning practices - contributes to achieving high accessibility, the proximity of housing to services, opportunities and public transport is perhaps the most important determinant.
Government housing programmes in Gauteng have been widely criticised for being poorly located and entrenching inequitable and unsustainable spatial forms (e.g. Haferburg, 2013; Landman 2010). However, there is limited research assessing whether those who live in such settlements are within easy reach of the services they need, compared to those who live elsewhere.
The June 2019 Map of the Month uses the Quality of Life V (2017/18) survey data to explore various elements of accessibility for residents of Gauteng and, in particular, people living within government housing programmes.
The maps present an Accessibility Index that has been developed by combining 13 access-related questions from QoL V (2017/18) to give an overall sense of access. This index focuses primarily on whether QoL respondents in particular areas are able to access goods and services, rather than how proximate areas are to work opportunities or other parts of the province.
Table 1 provides a listing of the questions included in the Accessibility Index. These questions have been combined into a single score, scaled out of 10, where 10 indicates the highest accessibility. The lower the score, the fewer the services easily reachable from where the respondent lives. The higher the score, the more likely it is that the respondent can quickly and easily access the goods, services and opportunities that they need.
The overall Accessibility score for the province is 5.1 out of 10, which indicates that Gauteng has a moderate level of overall accessibility, and a significant proportion of people in the province do not live within easy access of services. However, this figure is highly differentiated across space and settlement types.
In our analysis, we organise the average Index scores into the following categories: ‘very low’ (index score < 2), ‘low’ (index score 2 - 4), ‘moderate’ (index score 4 - 6), ‘high’ (index score 6 - 8), and ‘very high’ (index score >8). Map 1 shows the results of the accessibility index by ward (2016), using these categories from 'very low' to 'very high' accessibility. It is notable that although some 17% of respondents fall into the ‘very high’ accessibility category, no ward’s average falls into this category (hence its absence from the maps). The map shows that Johannesburg and Ekurhuleni have the highest accessibility in overall terms, neither of which have any wards with ‘very low’ accessibility. However, each municipality in the province has pockets of both higher and lower accessibility. Of concern is the large proportion of wards in Midvaal (50%), Merafong (34%) and Rand West (31%) that have ‘low’ or ‘very low’ accessibility.
Map 1 shows that areas within the urban core (e.g. Pretoria CBD, Vanderbijl Park, Sandton and Johannesburg CBD) have high accessibility, whereas those areas that are further away often have lower accessibility (e.g. Winterveld and Walkerville). Of particular interest are adjacent wards that have very different accessibility scores. For example, in eastern edge of Rand West, there are a number of high accessibility wards that are adjacent to wards with very low accessibility.
Figure 1 compares the average Accessibility Index score for respondents located within government housing programmes, informal settlements and the rest of Gauteng. This analysis focuses on all residents regardless of their tenure status, or housing type (i.e. the respondents within government housing developments might not be living in a government subsidised dwelling). This graph demonstrates that although people located within government housing programmes have lower access than the ‘rest of Gauteng’, they have substantially better access than people living in informal settlements.
Map 1 shows the location of government housing programmes (2014)* by shading them in white. These areas are the primary focus of Map 2.
Map 2 focuses on those QoL V (2017/18) respondents who live within the areas identified as government housing programmes, where there is a sample of more than 15 respondents within each settlement area (again these respondents might not be living in government subsidised housing, but are nonetheless living within government housing programme areas). There is a large number of housing programmes in Gauteng that had fewer than 15 respondents in the QoL V (2017/18) survey. Map 2 shows the results for 82 settlements out of the 467 housing programmes listed in the 2014 provincial dataset.
The average Accessibility Index score was calculated for each applicable housing programme and grouped into our set of index categories, from ‘very high to 'very low'. Tshwaing Village, near Winterveld in Tshwane, is the housing programme with the lowest accessibility index score of 0.9. Nguni Hostel, in central Ekurhuleni, has the highest score on the Index at 6.9 out of 10. No housing programme achieved an accessibility index of 8 or above - 'very high' access - thus this highest category has been excluded from the map. These results are mapped onto Gauteng's urban land use footprint.
Map 2 clearly shows significant differences in accessibility across different government housing programmes. These differences are likely due to a number of different factors. Respondents in settlements such as Winterveld and Savanna City, located far from the urban core, may have lower accessibility scores because of their relatively peripheral location. On the other hand, accessibility scores may reflect what has actually been developed inside different settlements. Higher accessibility may be a function of older areas having had more time for services to be developed compared to newer developments. It is likely that over time accessibility to goods and services improves for newer developments.
Despite the common belief that government housing developments are poorly located, many of the programmes in this map are located in wards that have moderate to high accessibility. Nonetheless, there are many other programmes that are indeed located within wards where accessibility is low or very low. Interestingly, the Accessibility Index score within housing programmes does not necessarily correlate with that of wards in which they are located. For example, Cosmo City and Zonkizizwe have high accessibility, but the wards in which they fall have only moderate accessibility. In contrast, Savanna City falls within a ward with low accessibility, but people within the housing development have very low accessibility.
Poor accessibility has knock-on impacts on the time and cost of accessing services and opportunities. For people living within government housing programme areas, there is a correlation between improved accessibility, and higher ‘satisfaction with life as a whole’ and higher ‘satisfaction with the amount of money available to respondents’.
Although the Accessibility Index does not specifically focus on access to work and economic opportunities, the results correlate strongly with commuting time to work and to look for work. Figure 2 shows that the higher the Accessibility Index score the greater the likelihood of spending 30 mins or less commuting to work or to look for work. The graph highlights that although the overall Accessibility Index is higher for those within government housing programmes than people living in informal settlements, respondents in informal settlements are more likely to get to work in a shorter time than people in government housing programmes.
There have been tense debates around how the government in Gauteng should respond to the existing and growing need for housing, particularly for the poor and those living informally (Ballard, 2017). Many people have critiqued the housing programmes in the province because of their location with regards to work opportunities (Budlender and Royston, 2016). In GCRO’s May 2015 Map of the Month, we mapped the location of planned mega housing projects in Gauteng in comparison to where businesses and unemployed people are concentrated. This June 2019 Map of the Month contributes to these debates by providing more nuanced empirical evidence regarding access. Additional analysis that dives deeper into the commuting time and distance across Gauteng and by people living within government housing programmes would further enhance this research.
* Spatial distribution of government housing programmes as at 2014, obtained from Gauteng Provincial Government. This dataset includes housing projects that have been developed, are under construction and that are in the planning phases. This is the most current comprehensive list for Gauteng we have been able to obtain. It is possible that a number of the projects listed in this dataset are no longer planned to be taken forward.
Ballard, Richard (2017), “Prefix as Policy: Megaprojects as South Africa’s Big Idea for Human Settlements”, Transformation: Critical Perspectives on Southern Africa Vol 95, No 1, pages i–xviii.
Budlender, Josh and Royston, Lauren (2016), “Edged out: Spatial mismatch and spatial justice in South Africa’s main urban areas”, Socio-economic rights institute of South Africa (SERI). Available online.
Haferburg, Christoph (2013), “Townships of To-Morrow? Cosmo City and Inclusive Visions for Post-Apartheid Urban Futures”, Habitat International Vol 39, No Supplement C, pages 261–268.
Landman, Karina (2010), “A Home Close to Opportunities in South Africa: Top down Vision or Bottom up Demand?”, Town and Regional Planning Vol 56, No 0, pages 8-17–17.