Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Personal Interview

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (StatsSA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa. Since 2008, StatsSA have produced an annual dataset based on the QLFS data, "Labour Market Dynamics in South Africa". The dataset is constructed using data from all all four QLFS datasets in the year. The dataset also includes a number of variables (including income) that are not available in any of the QLFS datasets from 2010.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population except for those in workers' hostels. However, persons living in private dwelling units within institutions are enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data

Sampling procedure

Each year the LMDSA is created by combining the QLFS waves for that year and then including some additional variables. The QLFS master frame for this LMDSA was based on the 2011 population census by Stas SA. The sampling is stratified by province, district, and geographic type (urban, traditional, farm). There are 3324 PSUs drawn each year, using probability proportional to size (PPS) sampling. In the second stage Dwelling Units (DUs) are systematically selected from PSUs. The 3324 PSU are split into four groups for the year, and at each quarter the DUs from the given group are replaced by substitute DUs from the same PSU or the next PSU on the list (in the same group). It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, two quarters and a new household moves in, the new household will be enumerated for two more quarters until the DU is rotated out. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (or unoccupied).

Mode of data collection

Computer Assisted Telephone Interview

Data appraisal

The statistical release notes that missing values were "generally imputed" for item non-response but provides no detail on how Statistics SA did so.

This dataset collection contains data from the South African General Household Survey (GHS) conducted annually by Statistics South Africa (Stats SA) from 2012 to 2022. The GHS is a critical tool for monitoring and evaluating various aspects of living conditions and service delivery across South African households.

Key Features:

Time Span: 2012 to 2022 Geographical Coverage: Nationwide, covering all provinces in South Africa Sample Size: Thousands of households each year Data Scope: The datasets include a wide range of variables such as employment status, education, health, housing, access to services, social grants, and more.

These datasets are invaluable for researchers, policymakers, and analysts interested in understanding socio-economic trends, evaluating public policies, or conducting longitudinal studies on living conditions in South Africa. They can be used for time series analysis, predictive modeling, and other data-driven inquiries.

Abstract

Censuses are principal means of collecting basic population and housing statistics required for social and economic development, policy interventions, their implementation and evaluation. The Post-Apartheid South African government has conducted four Censuses, in 1996, 2001, 2011 and 2022.

Geographic coverage

The South African Census 2022 has national coverage.

Analysis unit

Households and individuals

Universe

The South African Census 2022 covered every person present in South Africa on the Census reference night, midnight of 2-3 February 2022 including all de jure household members and residents of institutions.

Kind of data

Census/enumeration data

Sampling procedure

Census 2022 micro-data were sampled from the latest census data based on prescribed business requirements to ensure the generated estimates match the census population counts at local municipal level by age, sex, and population group. The Census 2022 Household record file and Person record file were used as a basis for the creation of the household and person sampling frame respectively. Households and household members in the in-scope households (records of the household questionnaire) formed part of the 10% sample. The municipal sample sizes for households were determined by taking 10% of the respective municipal measure of sizes. The household frame was implicitly stratified within each local municipality using household characteristics. Systematic samples of households were selected in each local municipality from the implicitly sorted household frame. The procedure used the allocated sample within each local municipality to produce the sample of households as well as the sampling weights, which are the inverse of the inclusion probabilities.

A Post-enumeration Survey (PES) is an independent sample survey that is conducted immediately after the completion of census enumeration to evaluate the coverage and content errors of the census. A sample of 840 sub-enumeration areas was selected across South Africa's nine provinces for the PES sampling frame. A mixed-mode data collection methodology was implemented to counteract the effects of the COVID19 pandemic. This was made possible by having integrated, digitally enabled survey processes with a geo-spatial information frame as a base.

Mode of data collection

Face-to-Face and Computer Assisted Personal and Telephone Interview

Research instrument

One questionnaire was used to capture the Census 2022 which included information on: 1. Households - particulars of the household (cover page of the household questionnaire) and household information sections of the household questionnaire. 2. Persons - particulars of the household member and person information sections of the household questionnaire. 3. Geography - geographic information associated with households and persons

A Post-Enumeration Survey was carried out after the census, which used a PES questionnaire.

Sampling error estimates

Coverage errors are a measure of how many persons or households were missed or counted more than once in the census. The final net coverage error rate relative to the final true population of 61,4 million persons is thus 31,1%. The final net coverage error rate relative to the final true population of 19,3 million households is 30,5%.

Content errors indicate the quality of key characteristics in the census. With respect to content errors, six variables were tested for consistency in terms of the responses that were recorded in the Census and the PES. The aggregated index of inconsistency was 7,5% for population group, 8,2% for sex, and 13,6% for age group, indicating a high level of agreement. The aggregated index of inconsistency for marital status was 23,0%, relationship to head of household was 34,8%, and country of birth was 42,3%, indicating moderate rates of agreement.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The QLFS uses a master sampling frame that is used by several household surveys conducted by Statistics South Africa. This wave of the QLFS is based on the 2013 master frame, which was created based on the 2011 census. There are 3324 PSUs in the master frame and roughly 33 000 dwelling units.

The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

For each quarter of the QLFS, a quarter of the sampled dwellings are rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. For more information see the statistical release.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire consists of the following sections: - Biographical information (marital status, education, etc.) - Economic activities for persons aged 15 years and older

As of 2022, South Africa's population increased and counted approximately 60.6 million inhabitants in total, of which the majority (roughly 49.1 million) were Black Africans. Individuals with an Indian or Asian background formed the smallest population group, counting approximately 1.56 million people overall. Looking at the population from a regional perspective, Gauteng (includes Johannesburg) is the smallest province of South Africa, though highly urbanized with a population of nearly 16 million people.

Increase in number of households

The total number of households increased annually between 2002 and 2022. Between this period, the number of households in South Africa grew by approximately 65 percent. Furthermore, households comprising two to three members were more common in urban areas (39.2 percent) than they were in rural areas (30.6 percent). Households with six or more people, on the other hand, amounted to 19.3 percent in rural areas, being roughly twice as common as those in urban areas.

Main sources of income

The majority of the households in South Africa had salaries or grants as a main source of income in 2019. Roughly 10.7 million drew their income from regular wages, whereas 7.9 million households received social grants paid by the government for citizens in need of state support.

As of 2023, South Africa's population increased and counted approximately 62.3 million inhabitants in total, of which the majority inhabited Gauteng, KwaZulu-Natal, and the Western-Eastern Cape. Gauteng (includes Johannesburg) is the smallest province in South Africa, though highly urbanized with a population of over 16 million people according to the estimates. Cape Town, on the other hand, is the largest city in South Africa with nearly 3.43 million inhabitants in the same year, whereas Durban counted 3.12 million citizens. However, looking at cities including municipalities, Johannesburg ranks first. High rate of young population South Africa has a substantial population of young people. In 2024, approximately 34.3 percent of the people were aged 19 years or younger. Those aged 60 or older, on the other hand, made-up over 10 percent of the total population. Distributing South African citizens by marital status, approximately half of the males and females were classified as single in 2021. Furthermore, 29.1 percent of the men were registered as married, whereas nearly 27 percent of the women walked down the aisle. Youth unemployment Youth unemployment fluctuated heavily between 2003 and 2022. In 2003, the unemployment rate stood at 36 percent, followed by a significant increase to 45.5 percent in 2010. However, it fluctuated again and as of 2022, over 51 percent of the youth were registered as unemployed. Furthermore, based on a survey conducted on the worries of South Africans, some 64 percent reported being worried about employment and the job market situation.

Description: Data presented as a spreadsheet; Provides Population estimates by population group, gender and age for South Africa since 2002.Linage: The data presented is extracted from Statistics South Africa (Stats SA) Mid-year population estimates (MYPE) trends as published on https://www.statssa.gov.za/Publication Date: 15 July 2022Contact person: Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Unemployment Rate in South Africa decreased to 31.90 percent in the third quarter of 2025 from 33.20 percent in the second quarter of 2025. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

In April 2018, StatsSA launched the Governance Public Safety and Justice Survey (GPSJS) in response to the need for standardised international reporting standards on governance and access to justice that are recommended by the SDGs, ShaSA and Agenda 2063. In compliance with these standards, Stats SA discontinued the separate publication of the Victims of Crime Survey (VCS) and incorporated it within the new GPSJS series. Therefore, the GPSJS represents the new source of microdata on the experience and prevalence of particular kinds of crime within South Africa. The GPSJS data can be used for research in the development of policies and strategies for governance, crime prevention, public safety and justice programmes with the main objectives of the survey being to:

• Provide information about the dynamics of crime from the perspective of households and the victims of crime. • Explore public perceptions of the activities of the police, prosecutors, courts and correctional services in the prevention of crime and victimisation; and • Provide complimentary data on the level of crime within South Africa in addition to the statistics published annually by the South African Police Service.

NOTE: The GPSJS is a continuation of the VCS series, which ended with VCS 2017/18. Therefore, the VCS 2018/19 can be exctracted from GPSJS 2018/19 and is comparable to previous VCS's only where questions remained the same. Please see Data Quality Notes for more infomation on comparability.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa, as well as residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks. It is only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data

Sampling procedure

The GPSJS 2022/23 uses the Master Sample (MS) sampling frame that has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys that have design requirements that are reasonably compatible with GPSJS. The GPSJS 2022/23 collection was drawn from the 2013 Master Sample. This master sample is based on information collected during Census 2011. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The Census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the master sample, since they covered the entire country and had other information that is crucial for stratification and creation of PSUs.

There are 3 324 primary sampling units (PSUs) in the master sample with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current master sample (3 324) reflect an 8,0% increase in the size of the master sample compared to the previous (2008) master sample (which had 3 080 PSUs). The larger master sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GPSJS estimates.

Mode of data collection

Computer Assisted Telephone Interview

Research instrument

The GPSJS questionnaire is based on international reporting standards of governance, public safety and justice defined by the SDGs.

Sections 1 to 3 of the questionnaire relate to household crimes. A proxy respondent (preferably head of the household or acting head of household) answered on behalf of the household. Section 4 to 9 of the questionnaire relate to crimes experienced by individuals and were asked of a household member who was selected using the birthday section method. This methodology selects an individual who is 16 years or older, whose birthday is soonest after the survey date.

Data appraisal

Comparability to VCS series:

While redesigning the VCS into the GPSJS, some questions were modified in order to align the series with international reporting demands (e.g. SDGs) and to improve the accuracy of victim reporting. This caused a break of series for affected questions, in particular questions on 12-month experience of crime. The question on 5-year experience of crime was not changed and hence there is no break of series. The 5-year trends can therefore be used as a proxy for the 12-month series as the two follow similar patterns. Similarity of shapes of the two series makes it possible to predict increase or decrease of crime during the past 12 months using the 5-year series.

Comparability to previous GPSJS series: To facilitate CATI data collection, the GPSJS 2019/20 sample was re-used and households that provided operational telephone numbers in 2019/20 were contacted and interviewed. The data is adjusted during the weighting process due to non-response from some households. The details of how the adjustment was done is contained in the metadata technical report. Given the change in the data survey mode of collection from CAPI to CATI, and the fact that the GPSJS 2020/21 estimates are not based on a full sample, comparisons with previous years should be made with caution.

Historical dataset showing South Africa hunger statistics by year from 2001 to 2022.

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

South Africa Population: Mid Year data was reported at 60,604,992.000 Person in 2022. This records an increase from the previous number of 59,964,917.000 Person for 2021. South Africa Population: Mid Year data is updated yearly, averaging 52,294,075.000 Person from Jun 2001 (Median) to 2022, with 22 observations. The data reached an all-time high of 60,604,992.000 Person in 2022 and a record low of 44,801,352.000 Person in 2001. South Africa Population: Mid Year data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.G003: Population: Mid Year: by Group, Age and Sex.

Historical dataset showing South Africa population density by year from 1961 to 2022.

As of 2022, just over 55 percent of all men in South Africa were classified as single, which was only a slightly larger rate compared to the almost 49 percent of females among the South African adult population. At 10.2 percent, however, women made up a noticeably larger percentage of widows compared to their male counterparts at only 2.7 percent.

Historical dataset showing South Africa healthcare spending per capita by year from 2000 to 2022.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Quarterly: average based on 3 monthly data points

Sampling procedure

Sample size:

South Africa ZA: Incidence of HIV: per 1,000 Uninfected Population data was reported at 3.150 Ratio in 2022. This records a decrease from the previous number of 3.390 Ratio for 2021. South Africa ZA: Incidence of HIV: per 1,000 Uninfected Population data is updated yearly, averaging 8.440 Ratio from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 12.730 Ratio in 1999 and a record low of 3.150 Ratio in 2022. South Africa ZA: Incidence of HIV: per 1,000 Uninfected Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Social: Health Statistics. Number of new HIV infections among uninfected populations expressed per 1,000 uninfected population in the year before the period.;UNAIDS estimates.;Weighted average;This is the Sustainable Development Goal indicator 3.3.1 [https://unstats.un.org/sdgs/metadata/].

Abstract

The DTS is a large-scale household survey aimed at collecting accurate statistics on the travel behaviour and expenditure of South African residents travelling within the borders of the country. Such information is crucial when determining the contribution of tourism to the South African economy, as well as helping with planning, marketing, policy formulation, and the regulation of tourism-related activities.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers’ hostels. The survey does not cover other collective living quarters such as students’ hostels, oldage homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data

Sampling procedure

The sample design for the DTS 2022 was based on a Master Sample (MS) that has been designed for all household surveys conducted by Statistics South Africa.

The Master Sample used a two-staged, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used. Stratification was done in two stages: Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2011 data were summarised at PSU level. The following variables were used for secondary stratification: household size, education, occupancy status, gender, industry and income.

Mode of data collection

Computer Assisted Telephone Interview

Historical dataset showing South Africa education spending by year from 1996 to 2022.