Description: data presented as a spreadsheet; Provides an overview of the labour force participation rate across all provinces and metros in South Africa since 2008.Linage: The data presented is extracted from Statistics South Africa (Stats SA) Quarterly Labour Force Survey (QLFS) trends as published on https://www.statssa.gov.za/Publication Date: 14 May 2024Data Sources: QLFS Trends 2008-2024Q1, Stats SA, published ‎14 ‎May ‎2024Contact Person: Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

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

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

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

The survey had 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 [ssd]

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).

For more information see the statistical release that accompanies the data.

Mode of data collection

Face-to-face [f2f]

Description: Data presented as a spreadsheet; Provides an overview of the labour force participation rate across all provinces and metros in South Africa since 2008.Artefact Type: Dataset (non-spatial)Lineage: The data presented is extracted from Statistics South Africa (Stats SA) Quarterly Labour Force Survey (QLFS) trends as published on https://www.statssa.gov.za/Publication Date 13 May 2025Data Sources / Layers QLFS Trends 2008-2025Q1, Stats SA, published 13 May 2025Contact Person Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

DescriptionData presented as a spreadsheet; Provides Population estimates by gender and age across all provinces in South Africa since 2002.Artefact TypeDataset (non-spatial)LineageThe 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 Date28 July 2025Data Sources / LayersExcel - Provincial projection by sex and age (2002-2025)_web, Stats SA, published 28 July 2025Contact PersonElize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Sources: Stats SA (www.statssa.gov.za), *SAPS (www.saps.gov.za).

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 is a countrywide household-based survey which collects data on two types of crimes, namely, vehicle hijacking and home robbery. Business robbery is not covered by the survey. The survey includes information on victimisation experienced by individuals and households and their perspectives on community responses to crime. Additionally, the survey data includes information on legitimacy, voice, equity and discrimination. Therefore, GPSJS data can be used for research in the development of policies and strategies for governance, crime prevention, public safety and justice programmes. The main objectives of the survey are 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.

• 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

The survey has 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 [ssd]

Sampling procedure

The GPSJS 2020/21 uses the master sample (MS) sampling frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys having design requirements that are reasonably compatible with GPSJS. The GPSJS 2020/21 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 [cati]

Research instrument

The GPSJS 2020/21 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.

Data on hostel standards of living in South Africa. Source: StatsSA Superweb, 2018 http://superweb.statssa.gov.za/webapi/jsf/login.xhtml?invalidSession=true&reason=Session+not+established

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

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 [ssd]

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 Telephone 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

This dataset includes imputation for missing data in key variables in the ten percent sample of the 2001 South African Census. Researchers at the Centre for the Analysis of South African Social Policy (CASASP) at the University of Oxford used sequential multiple regression techniques to impute income, education, age, gender, population group, occupation and employment status in the dataset. The main focus of the work was to impute income where it was missing or recorded as zero. The imputed results are similar to previous imputation work on the 2001 South African Census, including the single ‘hot-deck’ imputation carried out by Statistics South Africa.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Geographic coverage

National

Analysis unit

Units of analysis in the survey were households and individuals

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Abstract

The CPI is a current social and economic indicator constructed to measure changes over time in the general level of prices of consumer goods and services that households acquire, use, or pay for. The index measures changes in consumer prices over time by measuring the cost of purchasing a fixed basket of consumer goods and services of constant quality and similar characteristics. The products in the basket are selected to be representative of households' expenditure during a specific year. Such an index is called a fixed-basket price index. Changes in the index reflect the effects of price changes on the cost of achieving a constant standard of living.

The South African CPI has three equally important objectives: 1. To measure inflation in the economy so that macroeconomic policy is based on comprehensive and up-to-date price information. 2. To measure changes in the cost of living of South African households to promote equity in measures taken to adjust wages, grants, service agreements and contracts. 3. To provide a deflator for consumer expenditure in the national accounts and other economic data, to compute volume (as opposed to nominal) estimates.

In compiling the South African CPI, Stats SA largely follows the methodology guidelines in the 2020 Consumer Price Index Manual: Concepts and Methods published jointly by the International Monetary Fund, International Labour Organization, Statistical Office of the European Union, United Nations Economic Commission for Europe, Organisation for Economic Co-operation and Development, and World Bank.

Kind of data

Time-Series

Description: Data presented as a spreadsheet; Provides Population estimates by 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

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:

Geographic coverage

National

Analysis unit

Units of analysis in the survey were households and individuals

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Descriptiondata presented as spreadsheet; Provides an overview of the official unemployment rate by narrow definition across all provinces and metros in South Africa since 2008.Artefact TypeDataset (non-spatial)LineageThe data presented is extracted from Statistics South Africa (Stats SA) Quarterly Labour Force Survey (QLFS) trends as published on https://www.statssa.gov.za/Publication Date13 May 2025Data Sources / LayersQLFS Trends 2008-2025Q1, Stats SA, published 13 May 2025Terms of useNo special restrictions or limitations on using the item's content have been provided Contact PersonElize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Abstract

The Survey of Activities of Young People (SAYP) is a household-based survey that collects data on the activities of young people aged 7-17 years who live in South Africa. The survey covers involvement of children in market production activities, production for own final consumption, household chores as well as activities that children engaged in at school. Statistics South Africa collects SAYP information as part of the module of the Quarterly Labour Force Survey (QLFS) every four years. This information is gathered from respondents who are members of households living in dwellings that have been selected to take part in the QLFS and have children aged 7-17 years.

The aim of the first survey (SAYP 1999) was to collect information on childrens economic activities, including paid and unpaid work. All subsequent survey's (SAYP 2010, 2015 and 2019) are intended to provide updated information on the economic activities of children, including an analysis of child labour in South Africa. The specific objectives of the SAYP are to understand the extent of childrent's involvement in economic activities, provide information for the formulation of an informed policy to combat child labour within the country and to monitor the South African Child Programme of Action (CLPA) and Sustainable Development Goal (SDG'S).

Geographic coverage

The survey has national coverage.

Analysis unit

Households and individuals

Universe

The SAYP covers children aged 7-17 years resident in a household. The survey excluded all people in prison, patients in hospitals, people residing in boarding houses and hotels, and boarding schools. Any single person households were screened out in all areas before the sample was drawn. Families living in hostels were treated as households.

Kind of data

Sample survey data

Sampling procedure

The Survey of Activities of Young People (SAYP) comprised two stages. The first stage involved identifying households with children aged 7-17 years during the Quarterly Labour Force Survey (QLFS) data collection that took place in the third quarter of 2019 (Q3:2019). The second stage involved a follow-up interview with children in those households to establish what kind of activities they were involved in and several other aspects related to the activities they engaged in.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SAYP collected data in two phases using one questionnaire.

The first phase questionnaire covered the following topics: Living conditions of the household, including the type of dwelling, fuels used for cooking, lighting and heating,water source for domestic use, land ownership,tenure and cultivation; demographic information on members of the household, both adults and children. Questions covered the age, gender and population group of each household member, their marital status, their relationships to each other, and their levels of education; migration details; household income; school attendance of children aged 5 -17 years; information on economic and non-economic activities of children aged 5-17 years in the 12 months prior to the survey

The second phase questionnaire was administered to the sampled sub-set of households in which at least one child was involved in some form of work in the year prior to the interview. It covered activities of children in much more detail than in phase one, and the work situation of related adults in the household. Both adults and children were asked to respond.

Data presented as a spreadsheet; Provides Electricity generated and available for distribution in South Africa since 2002.Linage: The data presented is extracted from Statistics South Africa (Stats SA) Electricity generated and available for distribution trends as published on https://www.statssa.gov.za/Publication Date: 04 July 2024Data sources: Excel - Electricity generated and available for distribution(202405), Stats SA, published 4 July 2024Contact Person: Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Abstract

The October Household Survey (OHS) of 1995 is the second official survey undertaken by Statistics South Africa (Stats SA) with the specific aim of making data available for the South African government's Reconstruction and Development Programme (RDP). Data collected includes population data, particulars of dwellings and data on services and on perceived quality of life.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the survey are households and individuals

Universe

The survey covered households and household members in households in the nine provinces of South Africa

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 30 000 households was drawn in 3 000 enumerator areas (EA's) (that is 10 households per Enumerator Area). A two stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirement of probability sampling. The sample was based on the 1991 Population Census enumerator areas. The sampled population excluded all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent). The sample was explicitly stratified by province, Magisterial District, Urban/rural and Population group. The allocated number of EA's was systematically selected with probability proportional to size in each stratum The measure of size was the estimated number of people. In each EA, a systematic sample of 10 households was drawn.

Mode of data collection

Face-to-face [f2f]

Analysis unit

Woman, Birth, Child, Birth, Man, Household Member

Universe

Women age 15-49, Births, Children age 0-4, Men age 15-59, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: National Department of Health (NDoH) [South Africa], Statistics South Africa (Stats SA), South African Medical Research Council (SAMRC), and ICF.

SAMPLE UNIT: Woman SAMPLE SIZE: 8514

SAMPLE UNIT: Birth SAMPLE SIZE: 14144

SAMPLE UNIT: Child SAMPLE SIZE: 3548

SAMPLE UNIT: Man SAMPLE SIZE: 3618

SAMPLE UNIT: Member SAMPLE SIZE: 38850

Mode of data collection

Face-to-face [f2f]