Housing & services

Housing type

Author/s: Katharine Hall
Date: January 2024

Definition

This indicator shows the number and share of children living in formal, informal and traditional housing. For the purposes of the indicator, “formal” housing is considered a proxy for adequate housing and consists of: dwellings or brick structures on separate stands; flats or apartments; town/cluster/semi-detached houses; units in retirement villages; rooms or flatlets on larger properties provided they are built with sturdy materials. “Informal” housing consists of: informal dwellings or shacks in backyards or informal settlements; dwellings or houses/flats/rooms in backyards built of iron, wood or other non-durable materials; and caravans or tents. “Traditional” housing is defined as a “traditional dwelling/hut/structure made of traditional materials” situated in a rural area.

Data

Data Source

Statistics South Africa (2003 - 2023) General Household Survey 2002 - 2022. Pretoria, Cape Town: Statistics South Africa.
Analysis by Katharine Hall, Children’s Institute, University of Cape Town.

Notes

Children are defined as persons aged 0 – 17 years.
Population numbers have been rounded off to the nearest thousand.
Sample surveys are always subject to error, and the proportions simply reflect the mid-point of a possible range. The confidence intervals (CIs) indicate the reliability of the estimate at the 95% level. This means that, if independent samples were repeatedly taken from the same population, we would expect the proportion to lie between upper and lower bounds of the CI 95% of the time. The wider the CI, the more uncertain the proportion. Where CIs overlap for different sub-populations or time periods we cannot be sure that there is a real difference in the proportion, even if the mid-points differ. CIs are represented in the bar graphs by vertical lines at the top of each bar.

What do the numbers tell us?

Children’s right to adequate housing means that they should not have to live in informal dwellings. One of the seven elements of adequate housing identified by the UN Committee on Economic, Social and Cultural Rights is that it must be “habitable”. To be habitable, houses should have enough space to prevent overcrowding, and should be built in a way that ensures physical safety and protection from the weather.

Formal brick houses that meet the state’s standards for quality housing could be considered “habitable housing”, whereas informal dwellings such as shacks in informal settlements and backyards would not be considered habitable or adequate. Informal housing in backyards and informal settlements make up the bulk of the housing backlog in South Africa. “Traditional” housing in rural areas cannot necessarily be assumed to be inadequate. Some traditional dwellings are more habitable than new subsidy houses – they can be more spacious and better insulated, for example.

Access to services is another element of “adequate housing”. Children living in formal areas are more likely to have services on site than those living in informal or traditional dwellings. They are also more likely to live closer to facilities like schools, libraries, clinics and hospitals than those living in informal settlements or rural areas. Children living in informal settlements are more exposed to hazards such as shack fires and paraffin poisoning.

The environmental hazards associated with informal housing are exacerbated for very young children. The distribution of children in informal dwellings is slightly skewed towards younger children and babies: 42% of children in informal housing are in the 0 – 5-year age group.

In 2018, nearly 1.7 million children (9%) in South Africa lived in backyard dwellings or shacks in informal settlements. The number of children in informal housing has declined slightly from 2.3 million (13%) in 2002. The provinces with the highest shares of informally-housed children are the Western Cape (with 17% of children in that province informally housed), Gauteng (14%), North West and Free State (each with 13% of children living in informal housing). The Eastern Cape and KwaZulu-Natal have by far the largest shares of children living in traditional dwellings (30% and 19% respectively).

The distribution of children in formal, informal and traditional housing has remained fairly constant since 2002. But racial inequalities persist. Almost all White children (99%) live in formal housing, compared with only 81% of African children. Access to formal housing increases with income. Ninety-five percent of children in the wealthiest 20% of households live in formal dwellings, compared with 77% of children in the poorest quintile.

1 Office of the United Nations High Commissioner for Human Rights (1991) The Right to Adequate Housing (art.11 (1)): 13/12/91. CESCR General Comment 4. Geneva: United Nations.

Technical notes

South Africa’s housing policy has no clear or consistent definition of adequate housing since ‘adequate’ includes a range of attributes. Some of these are very technical, for instance minimum standards relating to the quality and size of the dwelling, type of wall and roof materials, provision of services, etc. There are also qualitative descriptors of ‘adequate’ housing, which refer to things like “reasonable living space and privacy” (RDP ²) as well as “habitability, accessibility, location and cultural adequacy” (National Housing Code). However, the main attribute used to determine the housing backlog is the type of dwelling.

The GHS instructs the fieldworker to record dwelling type for the main dwelling as well as any other dwelling that belongs to the household but is situated elsewhere. Only the main dwelling type is used in this indicator.

Strengths and limitations of the data

The numbers are derived from the General Household Survey, a multi-purpose annual survey conducted by the national statistical agency, Statistics South Africa, to collect information on a range of topics from households in the country’s nine provinces. The survey uses a sample of 30,000 households. These are drawn from Census enumeration areas using multi-stage stratified sampling and probability proportional to size principles. The resulting estimates should be representative of all households in South Africa.

The GHS sample consists of households and does not cover other collective institutionalised living-quarters such as boarding schools, orphanages, students’ hostels, old-age homes, hospitals, prisons, military barracks and workers’ hostels. These exclusions should not have a noticeable impact on the findings in respect of children.

Changes in sample frame and stratification
The sample design for the 2015 GHS was based on a master sample that was designed in 2013 as a general purpose sampling frame to be used for all Stats SA household-based surveys. The same master sample is shared by the GHS, the Quarterly Labour Force Survey, the Living Conditions Survey and the Income and Expenditure Survey. The 2013 master sample is based on information collected during the 2011 population census. The previous master sample for the GHS was used for the first time in 2008, and the one before that in 2004. These again differed from the master sample used in the first two years of the GHS: 2002 and 2003. Thus there have been four different sampling frames during the 14-year history of the annual GHS, with the changes occurring in 2004, 2008 and 2013. In addition, there have been changes in the method of stratification over the years. These changes could compromise comparability across iterations of the survey to some extent, although it is common practice to use the GHS for longitudinal monitoring and many of the official trend analyses are drawn from this survey.

Weights
Person and household weights are provided by Stats SA and are applied in Children Count analyses to give estimates at the provincial and national levels. The GHS weights are derived from Stats SA’s mid-year population estimates. The population estimates are based on a model that is revised from time to time when it is possible to calibrate the population model to larger population surveys (such as the Community Survey) or to census data.

In 2013, Stats SA revised the demographic model to produce a new series of mid-year population estimates. The 2013 model drew on the 2011 census (along with vital registration, antenatal and other administrative data) but was a “smoothed” model that did not mimic the unusual shape of the age distribution found in the census. The results of the 2011 census were initially questioned because it seemed to over-count children in the 0 – 4 age group and under-count children in the 4 – 14-year group.

The 2013 model was used to adjust the benchmarking for all previous GHS data sets, which were re-released with the revised population weights by Stats SA, and was still used to calculate weights for the GHS up to and including 2015, even though it is now known that the mid-year population estimates on which the weights are based are incorrect. All the Children Count indicators were re-analysed retrospectively, using the revised weights provided by Stats SA, based on the 2013 model. The estimates are therefore comparable over the period 2002 to 2015. The revised weights particularly affected estimates for the years 2002 – 2007.

It is now thought that the fertility rates recorded in the 2011 population census may have been an accurate reflection of recent trends, with an unexplained upswing in fertility around 2009 after which fertility rates declined gradually. Similar patterns were found in the vital registration data as more births were reported retrospectively to the Department of Home Affairs, and in administrative data from schools, compiled by the Department of Basic Education. In effect, this means that there may be more children in South Africa than appear from the analyses presented in these analyses, where we have applied weights based on a model that it is now known to be inaccurate.

Disaggregation
Statistics South Africa suggests caution when attempting to interpret data generated at low level disaggregation. The population estimates are benchmarked at the national level in terms of age, sex and population group while at provincial level, benchmarking is by population group only. This could mean that estimates derived from any further disaggregation of the provincial data below the population group may not be robust enough.

Reporting error
Error may be present due to the methodology used, i.e. the questionnaire is administered to only one respondent in the household who is expected to provide information about all other members of the household. Not all respondents will have accurate information about all children in the household. In instances where the respondent did not or could not provide an answer, this was recorded as “unspecified” (no response) or “don’t know” (the respondent stated that they didn’t know the answer).

For more information on the methods of the General Household Survey, see the metadata for the respective survey years, available on Nesstar or DataFirst