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

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 GHS is a household survey that has been executed annually by Stats SA since 2002. The survey in its present form was instituted as a result of the need identified by the Government of South Africa to determine the level of development in the country and the performance of programmes and projects on a regular basis. The survey was specifically designed to measure multiple facets of the living conditions of South African households, as well as the quality of service delivery in a number of key service sectors. The GHS covers six broad areas, namely: education, health, social development, housing, household access to services and facilities, food security and agriculture.

Geographic coverage

The nine provinces of South Africa

Analysis unit

Households 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, old-age 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

Données échantillonées [ssd]

Sampling procedure

The sample design for the GHS 2011 was based on a master sample (MS) that was originally designed for the QLFS and was used for the first time for the GHS in 2008. This master sample is shared by the Quarterly Labour Force Surveys (QLFS), General Household Survey (GHS), Living Conditions Survey (LCS), Domestic Tourism Survey and the Income and Expenditure Surveys (IES).

The master sample used a two-stage, 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 and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income.

Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: · Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs); · EAs with fewer than 25 DUs were excluded; · EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; · Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and · Informal PSUs were segmented.

A Randomised Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

For more Information on sampling please view technical notes in the statistical release

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire covers five core areas of importance with sections on education, health, non-remunerated trips undertaken by the household, housing, and household access to services and facilities. These are covered in four sections, each focusing on a particular aspect. Depending on the need for additional information, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed.

Contents of the GHS questionnaire - Cover page: Household information, response details, field staff information, result codes, etc. - Flap: Demographic information (name, sex, age, population group, etc.) - Section 1: Biographical information (education, health, disability, welfare) - Section 2: Economic activities - Section 3:Household information (type of dwelling, ownership of dwelling, electricity, water and sanitation,environmental issues, services, transport, etc.) - Section 4: Food security, income and expenditure (food supply, agriculture, expenditure, etc.)

Response rate

The national response rate for the survey was 94,2%.

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.

Data presented as a spreadsheet; Provides Electricity generated and available for distribution in South Africa since 2000.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: 5/6/2025Data source: Electricity generated and available for distribution(202503), Stats SA, published 6 May 2025contact person: Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

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

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

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 33000 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

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

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]

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

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

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

Abstract

Objectives: Providing data for reviewing existing policies and programmes addressing both human rights and development challenges as well as promoting inclusion of persons with disabilities.

Reference Period: 9 to 31 October 2011

Periodicity of Data Collection: Every 10 years

Geographic coverage

Whole country

Analysis unit

Individuals

Universe

Population groups: Persons in age group 15-64

Total population covered: 15% on the sample

Economic activities: All economic activities

Sectors covered: All sectors

Labor force status: Employed persons, unemployed persons, persons outside labour force

Status in Employment: Employees, employers, own-account workers, contributing family workers

Establishments: NR

Other limitations: No

Classifications: Level of education, sex, age, type of disability, level of disability, province, population group

Cross-classification: Employed by degree of difficulty in the six functional domains and by sex, population group), geography type. Distribution of population by disability status, sex and labour market status.

Kind of data

Census/enumeration data [cen]

Frequency of data collection

Periodicity of Data collection: Every 10 years

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

Abstract

This cumulative dataset contains statistics on mortality and causes of death in South Africa covering the period 1997-2015. The mortality and causes of death dataset are part of a regular series published by Stats SA, based on data collected through the civil registration system. The first dataset in the series is the separately available dataset Recorded Deaths 1996.

The main objective of this dataset is to outline emerging trends and differentials in mortality by selected socio-demographic and geographic characteristics for deaths that occurred in the registered year and over time. Reliable mortality statistics, are the cornerstone of national health information systems, and are necessary for population health assessment, health policy and service planning; and programme evaluation. They are essential for studying the occurrence and distribution of health-related events, their determinants and management of related health problems. These data are particularly critical for monitoring the Sustainable Development Goals (SDGs) and Agenda 2063 which share the same goal for a high standard of living and quality of life, sound health and well-being for all and at all ages. Mortality statistics are also required for assessing the impact of non-communicable diseases (NCD's), emerging infectious diseases, injuries and natural disasters.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

This dataset is based on information on mortality and causes of death from the South African civil registration system. It covers all death notification forms from the Department of Home Affairs for deaths that occurred in 1997-2015, that reached Stats SA during the 2016/2017 processing phase.

Kind of data

Administrative records data [adm]

Mode of data collection

Other [oth]

Research instrument

The registration of deaths is captured using two instruments: form BI-1663 and form DHA-1663 (Notification/Register of death/stillbirth).

Data appraisal

This cumulative dataset is part of a regular series published by Stats SA and includes all previous rounds in the series (excluding Recorded Deaths 1996). Stats SA only includes one variable to classify the occupation group of the deceased (OccupationGrp) in the current round (1997-2017). Prior to 2016, Stats SA included both occupation group (OccupationGrp) and industry classification (Industry) in all previous rounds. Therefore, DataFirst has made the 1997-2015 cumulative round available as a separately downloadable dataset which includes both occupation group and industry classification of the deceased spanning the years 1997-2015.

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:

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]

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

This dataset contains statistics on deaths in South Africa in 2014. The registration of deaths in South Africa is regulated by the Births and Deaths Registration Act, 51 of 1992. The South African Department of Home Affairs (DHA) is responsible for the registration of deaths in South Africa. The data is collected with two instruments: The death register and the medical certificate in respect of death. The staff of the DHA Registrar of Deaths section fills in the former while the medical practitioner attending to the death completes the latter. Causes of death are coded by the Department of Home Affairs according to the tenth revision of the International Classification of Diseases (ICD-10) ICD-10, as required by the World Health Organization for their member countries. The data is used by the Department of Home Affairs to update the Population Register. The forms are sent to Statistics South Africa (Stats SA) for their use for statistical purposes. From the two forms sent to Stats SA, the following data items of the deceased are extracted: place of residence, place of death, date of death, month and year of registration, sex, marital status, occupation, underlying cause of death, whether or not the death was certified by a medical practitioner, and whether or not the deceased died in a health institution or nursing home. From 1991 death notifications do not require data on population group, and therefore this dataset includes death data for all population groups. This dataset excludes 2014 deaths that were not registered, and late registrations which would not have been available to Stats SA in time for the production of the dataset.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The data covers all deaths that occurred in 2014 which were registered at the Department of Home Affairs in South Africa.

Kind of data

Administrative records data [adm]

Mode of data collection

Other [oth]

Research instrument

The data is collected with two instruments: The death register and the medical certificate in respect of death.

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: 01 April 2024 Contact Person: Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Abstract

Stats SA conducted the October Household Survey (OHS) annually from 1994 to 1999, based on a probability sample of a large number of households ranging from 16 000 to 30 000 households each year (depending on availability of funding). This survey was discontinued in 1999 due to the reprioritisation of surveys in the face of financial constraints. February 2000 saw the birth of the Labour Force Survey (LFS), which is a biannual survey conducted by Stats SA in March and September of each year. The LFS covers some areas previously covered by the OHS, but not all, since it is a specialised survey principally designed to measure the dynamics in the labour market. The September LFS each year does include a section designed to measure social indicators such as access to infrastructure, but again this section does not go into as much depth as the OHS used to. A need was therefore identified by our users for a regular survey designed specifically to measure the level of development and the performance of government programmes and projects. The General Household Survey (GHS) was developed for this purpose. While the survey replaces the October Household Survey (OHS), the indicators measured in the 13 nodal areas identified for the Integrated Rural Development Strategy (IRSD) formed the basis for the subject matter of the survey. The first round of the GHS was conducted in July 2002 and the second round in July 2003.

Geographic coverage

The scope of the General Household Survey 2003 was national coverage.

Analysis unit

The units of anaylsis for the General Household Survey 2003 are individuals and households.

Universe

The survey covered 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 students' hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

For the GHS 2003 a multi-stage stratified sample was drawn using probability proportional to size principles.

The sample was drawn from the master sample, which Statistics South Africa uses to draw samples for its regular household surveys. The master sample is drawn from the database of enumeration areas (EAs) established during the demarcation phase of Census 1996. As part of the master sample, small EAs consisting of fewer than 100 households are combined with adjacent EAs to form primary sampling units (PSUs) of at least 100 households, to allow for repeated sampling of dwelling units within each PSU. The sampling procedure for the master sample involves explicit stratification by province and within each province, by urban and non-urban areas. Within each stratum, the sample was allocated disproportionately. A PPS sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 000 PSUs were selected. In each selected PSU a systematic sample of ten dwelling units was drawn, thus, resulting in approximately 30 000 dwelling units. All households in the sampled dwelling units were enumerated. The master sample is divided into five independent clusters. In order to avoid respondent fatigue (the LFS is a rotating panel survey which is conducted twice yearly), the GHS sample uses a different cluster from the LFS clusters.

Mode of data collection

Face-to-face [f2f]

Research instrument

The GHS 2003 questionnaire collected data on: Household characteristics: Dwelling type, home ownership, access to water and sanitation facilities, access to services, transport, household assets, land ownership, agricultural production Individuals' characteristics: demographic characteristics, relationship to household head, marital status, language, education, employment, income, health, disability, access to social services, mortality. Women's characteristics: fertility

Response rate

Response codes Number of responses % Completed 26 469 84.7 Non-contact 897 2.9 Refusal 645 2.1 Partly completed 18 0.1 Unusable information 1 0.0 Vacant 1 510 4.8 Listing error 246 0.8 Other 1 447 4.6 Total 31 233 100.0

Description: Data presented as a spreadsheet; Provides PPI in South Africa since 2012.Artefact Type: Dataset (non-spatial)Lineage: The data presented is extracted from Statistics South Africa (Stats SA) Producer Price Index (PPI) trends as published on https://www.statssa.gov.za/Publication Date: 26 June 2025Data Sources / Layers: Excel - PPI New series from 2013(202505), Stats SA, published 26 June 2025Contact Person Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za