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.

In the second quarter of 2024, the unemployment rate among Black South Africans was 36.9 percent, marking a year-on-year change of 0.8 percent compared to the second quarter of 2023. On the other hand, the unemployment rate among white South Africans was 7.9 percent in the second quarter of 2024, with a 0.5 percent year-on-year change. Unemployment prevalent among youth and women The unemployment rate is the share of the labor force population that is unemployed, while the labor force includes individuals who are employed as well as those who are unemployed but looking for work. South Africa is struggling to absorb its youth into the job market. For instance, the unemployment rate among young South Africans aged 15-24 years reached a staggering 60.7 percent in the second quarter of 2023. Furthermore, women had higher unemployment rates than men. Since the start of 2016, the unemployment rate of women has been consistently more than that of men, reaching close to 36 percent compared to 30 percent, respectively. A new minimum wage and most paying jobs      In South Africa, a new minimum hourly wage went into effect on March 1, 2022. The minimum salary reached 23.19 South African rand per hour (1.44 U.S. dollars per hour), up from 21.69 South African rand per hour (1.35 U.S. dollars per hour) in 2021. In addition, the preponderance of employed South Africans worked between 40 and 45 hours weekly in 2021. Individuals holding Executive Management and Change Management jobs were the highest paid in the country, with salaries averaging 74,000 U.S. dollars per year.

Abstract

The 1970 South African Population Census was an enumeration of the population and housing in South Africa.The census collected data on dwellings and individuals' demographic, migration, family and employment details.

Geographic coverage

National coverage of the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal, and the so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, Kwandebele, Transkei and Bophuthatswana.

Analysis unit

The units of analysis for the South African Census 1970 were households and individuals

Universe

The South African population census of 1970 covered all de jure household members (usual residents) of South Africa and the "national states".

The Census was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night were enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were not enumerated and included in the figures. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census/enumeration data [cen]

Sampling procedure

The 1970 Census was a full count for Whites, Coloureds and Asians, and a 5% sample for Blacks (Africans)

Sampling deviation

The country was divided into 400 census districts for the 1970 Census. In most cases the boundaries of the census districts corresponded with those of the magisterial districts. However, in some cases the boundaries did not correspond, particularly in the areas in and around the "National States". This was to facilitate the administration of the census and to make it easier to exclude figures of the "National states" from provincial totals.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1970 Population Census of the Republic of South Africa questionnaires were: Form 01, to be completed by "Whites, Coloured and Asiatics" Form 02, to be completed by "Bantu" Form 03, for families, households and dwellings

Form 01 collected data on relationship to household head, population group, sex, age, marital status, place of birth, and citizenship, as well as usual place of residence, home language, religion, level of education and income. Employment data collected included occupation, employment status and industry type.

Form 02 collected data for African South Africans on relationship to household head, sex, age, marital status, fertility, place of birth, home language and literacy, religion and level of education. Employment data collected included occupation, employment status and industry type.

Form 03 collected household data, including data on dwelling type, building material of dwelling walls, number of rooms and age of the dwelling. Data on home ownership. Data was also collected on the number and sex of household members and their relationship to the household head. Data on household heads included their population group, age and marital status. Income data was also collected, for husbands and wives. Data on home ownership, household size and domestic workers was also collected, but for Urban households only.

According to a survey conducted in 2021, Black South Africans were the largest group accessing the internet, with a share of 70.3 percent. Moreover, white and colored people followed, with shares reaching around 16 percent and nine percent, respectively. In 2022, Black South Africans were the largest population group in the country, followed by the colored and white populations.

South Africa Population: Mid Year: White: Male: 70 to 74 Years data was reported at 105,238.000 Person in 2018. This records an increase from the previous number of 95,344.570 Person for 2017. South Africa Population: Mid Year: White: Male: 70 to 74 Years data is updated yearly, averaging 78,333.668 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 105,238.000 Person in 2018 and a record low of 55,969.000 Person in 2001. South Africa Population: Mid Year: White: Male: 70 to 74 Years 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.

Geographic coverage

The 1985 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

The 1985 Census dataset contains 9 data files. These refer to Development Regions demarcated by the South African Government according to their socio-economic conditions and development needs. These Development Regions are labeled A to J (there is no Region I, presumably because Statistics SA felt an "I" could be confused with the number 1). The 9 data files in the 1985 Census dataset refer to the following areas:

DEV REGION AREA COVERED A Western Cape Province including Walvis Bay B Northern Cape C Orange Free State and Qwaqwa D Eastern Cape/Border E Natal and Kwazulu F Eastern Transvaal, KaNgwane and part of the Simdlangentsha district of Kwazulu G Northern Transvaal, Lebowa and Gazankulu H PWV area, Moutse and KwaNdebele J Western Transvaal

Analysis unit

The units of analysis under observation in the South African census 1985 are households and individuals

Universe

The South African census 1985 census covered the provinces of the Cape, the Orange Free State, Transvaal, and Nata and the so-called National States of KwaZulu, Kangwane, Gazankulu, Lebowa, Qwaqwa, and Kwandebele. The 1985 South African census excluded the areas of the Transkei, Bophutatswana, Ciskei, and Venda.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Although the census was meant to cover all residents of the so called white areas of South Africa, in 88 areas door-to-door surveys were not possible and the population in these areas was enumerated by means of a sample survey conducted by the Human Sciences Research Council.

Mode of data collection

Face-to-face [f2f]

Research instrument

The1985 population census questionnaire was administered to each household and collected information on household and area type, and information on household members, including relationship within household, sex, age, marital status, population group, birthplace, country of citizenship, level of education, occupation, identity of employer and the nature of economic activities

Data appraisal

UNDER-ENUMERATION: The following under-enumeration figures have been calculated for the 1985 census. Estimated percentage distribution of undercount by race according to the HSRC: Percent undercount
Whites 7.6%
Blacks in the “RSA” 20.4% Blacks in the “National States” 15.1% Coloureds 1.0% Asians 4.6%

Abstract

The principal purpose of this explorative telephone survey was to collect information on attitudes of white South Africans towards the Truth and Reconciliation Commission (TRC) and related topics at the beginning of its public hearings in April-May 1996.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the survey were households and individuals

Universe

"White' South Africans, 18 years or older.

Kind of data

Sample survey data [ssd]

Sampling procedure

A random sample of adult (18+) white South African households with a telephone (1996: 89%) was derived from a complete set of the latest edition of official Telkom phone books. The "next-birthday-method" was used for intra-household respondent selection (the respondent in the household is selected randomly by interviewing that member of the household, whose birthday is next). Black, Indian and Coloured respondents were excluded through an introductory question.

Mode of data collection

Face-to-face [f2f]

Response rate

A maximum of six contact attempts were made at different times to speak to the selected respondent. The response rate was 56 Percent. See Theissen (1997, Chapter 4) for further details.

As of 2024, South Africa's population increased, counting approximately 63 million inhabitants. Of these, roughly 27.5 million were aged 0-24, while 654,000 people were 80 years or older. Gauteng and Cape Town are the most populated Although South Africa’s yearly population growth has been dropping since 2013, the growth rate still stood above the world average in 2021. That year, the global population increase reached 0.94 percent, while for South Africa, the rise was 1.23 percent. The majority of the people lived in the borders of Gauteng, the smallest of the nine provinces in land area. The number of people residing there amounted to 15.9 million in 2021. Although Western Cape was the third-largest province, one of it cities, Cape Town, had the highest number of inhabitants in the country, at 3.4 million. An underemployed younger population South Africa has a large population under 14, who will be looking for job opportunities in the future. However, the country's labor market has had difficulty integrating these youngsters. Specifically, as of the third quarter of 2022, the unemployment rate reached close to 60 percent and 42.9 percent among people aged 15-24 and 25-34 years, respectively. In the same period, some 25 percent of the individuals between 15 and 24 years were economically active, while the labor force participation rate was higher among people aged 25 to 34, at 71.2 percent.

Abstract

The purpose of this study was to explore the relationship between truth acceptance and reconciliation among South Africans during and since the political transition from Apartheid to democracy. The study investigated the extent to which South Africans participated in the Truth and Reconciliation Commission and the degree to which they were "reconciled." The Truth and Reconciliation Commission (TRC) was based on the Promotion of National Unity and Reconciliation Act of 1995. The TRC investigated past gross human rights violations and granted amnesty to individuals in exchange for full and public disclosure of information related to these crimes. The hypothesis that truth acceptance leads to reconciliation was tested in this research. Data were collected through a systematic survey of South Africans. Nearly all relevant segments of the South African population were included in the sample, as well as representative subsamples of at least 250 respondents of most major racial/ethnic/linguistic groups.

Questions about the TRC investigated respondent awareness, knowledge, and approval of the activities of the TRC. Respondents were asked for their opinions on the effectiveness of the TRC in its efforts to provide a true and unbiased account of South Africa's history and in awarding compensation to those who suffered abuses under the Apartheid regime. Other questions included those eliciting respondents views on the importance of revealing the truth about the past and achieving racial reconciliation.

Geographic coverage

The Survey of Truth and Reconciliation in South Africa, 2000-2001 had national coverage.

Analysis unit

Individuals

Universe

The universe under investigation included all South Africans aged 18+.

Kind of data

Sample survey data

Sampling procedure

The area probability sample included a primary sample of South Africans of all races and a boost sample of white South Africans. Representative subsamples of at least 250 respondents of most major racial, ethnic, and linguistic groups were also included.

The sampling was divided into two parts – a primary sample, including South Africans of all races, and a boost sample of white South Africans. In the main sample, 3,139 interviews were completed. The Boost Sample was composed only of white South Africans, with a control for language (English versus Afrikaans). A total of 588 additional whites was interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the Survey of Truth and Reconciliation in South Africa, 2000-2001 includes individual characteristics, respondent awareness, knowledge, and approval of the activities of the TRC, how important it was for respondents to find out the truth about the past and achieve racial reconciliation.

Response rate

The overall response rate for the survey was approximately 87 percent (after treating “break-offs” as unsuccessful interviews). The main reason for failing to complete the interview was inability to contact the respondent; refusal to be interviewed accounted for approximately 27 percent of the failed interviews. From the response rate alone, the representativeness of the sample seems assured. Such a high rate of response can be attributed to the general willingness of the South African population to be interviewed, the large number of call-backs we employed, and the use of an incentive for participating in the interview (the incentive was a magnetic torch (flashlight), with which the respondents were quite pleased).

Abstract

The 1980 South African Population Census was a count of all persons present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980). The purpose of the population census was to collect, process and disseminate detailed statistics on population size, composition and distribution at small area level. The 1980 South African Population Census contains data collected on HOUSEHOLDS: household goods and dwelling characteristics as well as employment of domestic workers; INDIVIDUALS: population group, citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities

Geographic coverage

The 1980 census covered the so-called white areas of South Africa, i.e. the areas in the former four provinces of the Cape, the Orange Free State, Transvaal, and Natal. It also covered areas in the following so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, and Kwandebele. The 1980 South African census excluded the areas of the Transkei and Bophuthatswana. A census data file for Bophuthatswana was released with the final South African Census 1980 dataset.

Analysis unit

The units of analysis of the 1980 census includes households, individuals and institutions

Universe

The 1980 South African census covered all household members (usual residents).

The 1980 South African Population Census was enumerated on a de facto basis, that is, according to the place where persons were located during the census. All persons who were present on Republic of South African territory during census night (i.e. at midnight between 6 and 7 May 1980) were enumerated and included in the data. Visitors from abroad who were present in the RSA on holiday or business on the night of the census, as well as foreigners (and their families) who were studying or economically active, were not enumerated and included in the figures. Likewise, members of the Diplomatic and Consular Corps of foreign countries were not included. However, the South African personnel linked to the foreign missions including domestic workers were enumerated. Crews and passengers of ships were also not enumerated, unless they were normally resident in the Republic of South Africa. Residents of the RSA who were absent from the night were as far as possible enumerated on their return and included in the region where they normally resided. Personnel of the South African Government stationed abroad and their families were, however enumerated. Such persons were included in the Transvaal (Pretoria).

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1980 Population Census questionnaire was administered to all household members and covered household goods and dwelling characteristics, and employment of domestic workers. Questions concerning individuals included those on citizenship/nationality, marital status, fertility and infant mortality, education, employment, religion, language and disabilities, as well as mode of transport used and participation in sport and other recreational activities.

The following questions appear in the questionnaire but the corresponding data has not been included in the data set: PART C: PARTICULARS OF DWELLING: 2. How many separate families (i) Number of families (ii) Number of non-family persons (iii) total number of occupants [i.e. persons in families shown against (i) plus persons shown against 3. Persons employed by household Full-time, Part-time (a) How many persons are employed as domestics by you? (Include garden workers) (b) Total cash wages paid to above –mentioned persons for April 1980 4. Ownership – Do not answer this question if your dwelling is on a farm. (i) Own dwelling – (Including hire-purchase, sectional title property or property of wife): (a) Is the dwelling Fully paid Partly paid-off (b) If partly paid-off, state monthly repayment (include housing subsidy, but exclude insurance. (ii) Rented or occupied free dwelling : (a) Is the dwelling occupied free, rented furnished, rented unfurnished (b) If rented, state monthly rent (c) Is the dwelling owned by the employer? (d) Does it belong to the state, SA Railways, a provincial administration, a divisional council, or a municipality or other local authority? PART D: PARTICULARS OF THE FAMILY 1. Number of members in the family 2. Occupation. (Nature of work done) (a) Head of family (b) Wife 3. Annual income of head of family and wife. Annual income of: Head, Wife (if applicable)

Abstract

An omnibus survey is done quarterly and its purpose is to give clients an opportunity to participate in a national survey at low cost. A number of clients’ questions are combined into one questionnaire. This questionnaire is usually administered to probability sample of about 2200 respondents in the whole country (South Africa). The 1996 February omnibus consisted of two separate samples of 2200 each – one sample having a yellow questionnaire and the other sample having a pink questionnaire. The February/March 1996 omnibus survey was undertaken over the period 27 February to 24 March 1996. The data from this survey was available in May 1996. The fieldwork was done on a countrywide basis including all nine provinces.

Geographic coverage

National coverage

Analysis unit

Units of analysis in the survey included individuals

Universe

The universe included all household residents 18 years old or older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The South African population of persons 18 years and older was stratified according to: Province (Western Cape, Eastern Cape, Northern Cape, Orange Free State, Natal/KwaZulu, Eastern Transvaal, PWV, North Western Province, Northern Transvaal) Socio-economic classification: Rural areas in former self-governing and TBVC states Squatter areas in former non-white urban (metro and non- metro areas) Hostels and hotels Former urban areas for coloureds Former urban areas for a Asians Former urban areas for blacks Former urban (non- metro) areas for whites Former urban (metro) areas for whites Rural areas, excluding the former self-governing and TBVC states

The sample allocation to these strata was done roughly proportional to the adjusted 1991 populatio n census figures with a few exceptions, among which was to ensure a minimal provincial total of 120. Multistage stratified cluster (probability) sampling was used to draw the respondents with the adjusted 1991 population census figures as measure of size. Census enumerator areas and similar areas were used as the clusters in the pen-ultimate sampling stage, from which an equal number, viz. one or two by four households were drawn. All clusters were drawn with probability proportional to size, whilst households were drawn from the final clusters with equal probability (systematically). Respondents were drawn at random from qualifying household members. In addition, population of live-in domestic workers was sampled in relation to their residence in already drawn households.

Mode of data collection

Face-to-face [f2f]

South Africa Population: Mid Year: White: Male: 20 to 24 Years data was reported at 128,124.000 Person in 2018. This records a decrease from the previous number of 133,602.152 Person for 2017. South Africa Population: Mid Year: White: Male: 20 to 24 Years data is updated yearly, averaging 167,038.201 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 179,008.715 Person in 2005 and a record low of 128,124.000 Person in 2018. South Africa Population: Mid Year: White: Male: 20 to 24 Years 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.

South Africa Population: Mid Year: White: Male: 60 to 64 Years data was reported at 138,340.000 Person in 2018. This records an increase from the previous number of 134,849.595 Person for 2017. South Africa Population: Mid Year: White: Male: 60 to 64 Years data is updated yearly, averaging 131,671.338 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 138,340.000 Person in 2018 and a record low of 112,762.389 Person in 2002. South Africa Population: Mid Year: White: Male: 60 to 64 Years 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.

South Africa Population: Mid Year: White: Female: 10 to 14 Years data was reported at 123,340.000 Person in 2018. This records an increase from the previous number of 122,386.453 Person for 2017. South Africa Population: Mid Year: White: Female: 10 to 14 Years data is updated yearly, averaging 134,804.608 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 164,730.463 Person in 2002 and a record low of 119,214.598 Person in 2015. South Africa Population: Mid Year: White: Female: 10 to 14 Years 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.

In the fourth quarter of 2023, the labor force participation rate among Black South Africans reached over 59 percent, marking a year-on-year change of two percent compared to the fourth quarter of 2022. However, the participation rate of the labor force among Indian/Asian South Africans dropped from about 61 percent in the previous year to 58 percent.

Abstract

The information collected in household surveys, such as this one, is used to describe and understand the living conditions and experiences of South Africans. Often, however, different surveys use different sample areas and interview different households, making it difficult to know whether the living standards or circumstances of particular households have improved. The aim of this survey is to determine whether or not there have been any changes in the socio-economic conditions of those households interviewed in 1993. This information will be used to understand the dynamics of household behaviour over time.

Geographic coverage

The survey covered households in KwaZulu-Natal Province, on the east coast of South Africa

Analysis unit

Units of analysis in the Kwazulu Natal Income Dynamics Study 1993-1998 are households and individuals

Universe

The Kwazulu Natal Income Dynamics Study 1993-1998 covered all household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 1993 sample was selected using a two-stage self-weighting design. In the first stage, clusters were chosen with probability proportional to size from census enumerator subdistricts (ESD) or approximate equivalents where an ESD was not available. In the second stage, all households in each chosen cluster were enumerated and a random sample of them selected. (See PSLSD, 1994, for further details.)

In 1993, the KwaZulu-Natal portion of the PSLSD sample was designed to be representative at the provincial level, conditional on the accuracy of the 1991 census and other information used for the sampling frame, and contained households of all races. It was decided not to re-survey the small number of white and coloured households in 1998, however. While there were minor advantages to retaining these groups, the relatively small number of households in each group (112 white households and 53 coloured) would have precluded most comparative ethnic analyses. Moreover, the households in these ethnic groups were entirely located in a small number of clusters (due to the general lack of spatial integration of the population), undermining their representativeness. As a result, the 1998 sample includes only African and Indian households.

Mode of data collection

Face-to-face [f2f]

South Africa Population: Mid Year: White: Male: 55 to 59 Years data was reported at 147,081.000 Person in 2018. This records a decrease from the previous number of 148,044.549 Person for 2017. South Africa Population: Mid Year: White: Male: 55 to 59 Years data is updated yearly, averaging 144,709.988 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 149,241.000 Person in 2001 and a record low of 136,138.481 Person in 2002. South Africa Population: Mid Year: White: Male: 55 to 59 Years 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.

As of 2022, the number of South Africans with and without medical aid coverage was highest among the Black African population group, with 4.8 million and 4.5 million, respectively. However, this equates to only around 10 percent of the total Black African population having coverage. The white population group followed, with 3.1 million having coverage, which amounted to a share of almost 72 percent.

South Africa Exports of sugar confectionery (including white chocolate), not containing cocoa to Central African Republic was US$1 during 2021, according to the United Nations COMTRADE database on international trade.

Abstract

The National Income Dynamics Study (NIDS) is a face-to-face longitudinal survey of individuals living in South Africa as well as their households. The survey was designed to give effect to the dimensions of the well-being of South Africans, to be tracked over time. At the broadest level, these were: Wealth creation in terms of income and expenditure dynamics and asset endowments; Demographic dynamics as these relate to household composition and migration; Social heritage, including education and employment dynamics, the impact of life events (including positive and negative shocks), social capital and intergenerational developments;
Access to cash transfers and social services.

Dates: 2008 – ongoing. First 5 “waves” implemented by SALDRU.

Funding: The Presidency (2008 – 2013); The Department of Planning, Monitoring and Evaluation (2014 – Present).

SALDRU people: Murray Leibbrandt, Ingrid Woolard, Cecil Mlatsheni and Reza C. Daniels.

Coverage: Nationally representative of the South African population.

Initial Sample size (2008): Approximately 28 000 individuals.

Data: The survey’s questionnaires, technical documents and reports for Wave 1, Wave 2, Wave 3, Wave 4 and Wave 5 are available for download from DataFirst’s Open Data Portal. NIDS produces public release data, which is also available for download from DataFirst’s Open Data Portal and secure data, which can only be accessed through DataFirst’s Secure Research Data Centre.

Included sections: Household Living Standards; Household Composition and Structure; Mortality; Household Food and Non-food Spending and Consumption; Household Durable Goods, Household Net Assets; Agriculture; Demographics; Birth Histories and Children; Parents and Family Support; Labour Market Participation and Economic Activity; Income and Expenditure; Grants; Contributions Given and Received; Education; Health; Emotional Health; Household Decision-making; Wellbeing and Social Cohesion; Anthropometric Measurements; Personal Ownership and Debt.

Geographic coverage

The NIDS data is nationally representative. The survey began in 2008 with a nationally representative sample of over 28,000 individuals in 7,300 households across the country. The survey is repeated every two years with these same household members, who are called Continuing Sample Members (CSMs). The survey is designed to follow people who are CSMs, wherever they may be in SA at the time of interview. The NIDS data is therefore, by design, not representative provincially or at a lower level of geography (e.g. District Council).

Analysis unit

Households and individuals

Universe

The target population for NIDS was private households in all nine provinces of South Africa, and residents in workers' hostels, convents and monasteries. The frame excludes other collective living quarters, such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

NIDS is a national panel (longitudinal) survey which began with a sample of 28 000 South Africans. NIDS' cycles of data collection, referred to as "waves" were undertaken. In Wave 1 (2008), 400 Enumerator Areas, comprising of 7296 households were selected for inclusion in the NIDS sample. 300 fieldworkers spread out across all nine provinces of the country in search of the 28 226 people that formed part of these selected households; successfully interviewing 26 776 of these individuals during Wave 1.

In subsequent waves, the original sample members are tracked and re-interviewed. Anyone that they live with at the time is also interviewed. In Wave 2 (2010-2011) 28 537 individuals were interviewed; in Wave 3 (2012) 32 582 were interviewed; and in Wave 4 (2014-2015) 37 368 were interviewed. Data collection for Wave 5 took place in 2017 and included a sample "top-up" to increase the number of white, Indian and high income respondents who had experienced low baseline response rates in Wave 1 and higher attrition rates between Waves 1-4. During Wave 5, 39,434 individuals were successfully interviewed, of which, 2016 were from the "top-up" sample. The data for Wave 5 was released at the end of August 2018.

More information on NIDS sampling refer to NIDS Technical Paper Number 1 http://www.nids.uct.ac.za/publications/technical-papers/108-nids-technical-paper-no1/file

Mode of data collection

Face-to-face [f2f]