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.

South Africa Population: 15 to 64 Years: White data was reported at 2,978.591 Person th in Sep 2018. This records a decrease from the previous number of 2,987.055 Person th for Jun 2018. South Africa Population: 15 to 64 Years: White data is updated quarterly, averaging 3,143.298 Person th from Mar 2008 (Median) to Sep 2018, with 43 observations. The data reached an all-time high of 3,277.317 Person th in Mar 2008 and a record low of 2,978.591 Person th in Sep 2018. South Africa Population: 15 to 64 Years: White 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.G001: Population.

In 2022, women in South Africa represented 51.1 percent of the population. The majority of them were White South African, reaching 51.7 percent of the population. On the other hand, Indian/Asian women had a share of 48.9 percent.

Abstract

The 1970 South African Population 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.

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%

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.

In 2021, Black South Africans were the largest group in the country accessing the internet via a smartphone. Some ** percent of Black South Africans used a smartphone to go online, while the white population followed with nearly ** percent. Indian/Asian individuals, on the other hand, were the population group with the smallest share of internet access via a smartphone. In 2022, Black South Africans were the largest population group in the country, followed by the colored and white populations.

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).

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

As of the second quarter of 2024, nearly 3.83 million people in South Africa worked within the community and social services industry. The sector concentrated the highest number of employees, followed by the trade industry, which employed about 3.36 million people. A struggling labor market The South African labor market faces severe challenges and obstacles. In 2023, the country had the highest unemployment rate in Africa, with almost 30 percent of the labor force being jobless. In addition, only 40 percent of the population was employed in 2021. Indeed, South Africans were the most concerned globally about finding jobs and being unemployed. According to a survey, 64 percent of South African respondents reported being worried about unemployment as of September 2023. A highly unequal country South Africa is the most income-unequal country in the world, as it registered a Gini score of 63 in 2021. The major reasons for this inequality originate from the country’s infamous Apartheid regime and the failure of the job market to provide enough opportunities for its people. For example, the unemployment rate among Black South Africans was close to 37 percent, compared to eight percent for white South Africans. Furthermore, unemployment in the country was more widespread among individuals with a lower level of education. Specifically, in 2023, over 50 percent of the jobless South Africans had an education level lower than matric (grade 12).

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

Households and individuals

Universe

"White' South Africans, 18 years or older.

Kind of data

Sample survey data

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.

About this dataset

Context

The dataset tabulates the population of South Tucson by race. It includes the population of South Tucson across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of South Tucson across relevant racial categories.

Key observations

The percent distribution of South Tucson population by race (across all racial categories recognized by the U.S. Census Bureau): 45.89% are white, 3.40% are Black or African American, 19.39% are American Indian and Alaska Native, 0.13% are Asian, 16.52% are some other race and 14.67% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the South Tucson
• Population: The population of the racial category (excluding ethnicity) in the South Tucson is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of South Tucson total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for South Tucson Population by Race & Ethnicity. You can refer the same here

In 2021, a survey was conducted in South Africa about the distribution of instant messaging applications among different population groups. It found that LinkedIn users were predominantly Black. They made up a share of ** percent. Moreover, white South Africans made up about ** percent of the LinkedIn users in the country. In 2022, Black South Africans were the largest population group in the country, followed by the colored and white populations.

Graph and download economic data for Unemployment Rate - Black or African American (LNS14000006) from Jan 1972 to Aug 2025 about African-American, 16 years +, household survey, unemployment, rate, and USA.

In 2021, a survey was conducted in South Africa about the distribution of instant messaging applications among different population groups. It found that Instagram was predominately used by Black people. They made up a share of approximately ** percent. In 2022, Black South Africans were the largest population group in the country, followed by the colored and white populations.

As of 2023, the number of South Africans with and without medical aid coverage was highest among the Black African population group, with just over ************ and **********, respectively. However, this equates to only around ** percent of the total Black African population having coverage. The white population group followed, with *********** having coverage, which amounted to a share of almost ** percent.

In 2018, tertiary education attainment was highest among the White population in South Africa, with around ****, **** and *** percent of the individuals associated with Generation X, Millennials, and Born-free Millennials, respectively. Moreover, compared to the generation of Millennials, tertiary school completion was higher in all population groups in Generation X, except among Indians/Asians. Furthermore, the total share of Millennials who received a tertiary education (**** percent) was slightly lower than that of Generation X. However, the source indicates that a possible explanation to that is that some of the Millennials were still obtaining their higher education degrees.

Abstract

The KwaZulu-Natal Income Dynamics Study (KIDS) is a panel study that follows a random sample of households who lived in the South African province of KwaZulu-Natal (KZN) in 1993. These households and those who have split off from them were interviewed again in 1998 and 2004. This document summarizes the main features of the third wave of KIDS conducted in 2004.

Geographic coverage

The Province of Kwazulu-Natal

Analysis unit

individuals, communities

Universe

The sample covered on African and Indian Households.

Kind of data

Sample survey data [ssd]

Sampling procedure

Due to the geographic concentration of African and Indian households, KIDS-unlike the PSLSD-limits its scope to African and Indian households. In the KwaZulu-Natal province, Africans represent 85 percent of the population and Indians represent 12 percent. Compared with their representation nationally, White and Coloured people are underrepresented in KwaZulu-Natal. Effectively, the numbers of White and Coloureds in the KwaZulu-Natal sample are too small, and too geographically concentrated in a few clusters, to permit meaningful inference. The KIDS study has thus been limited to the first two population groups.

PSLSD was a survey of households. However, households are a complicated object to define, particularly in longitudinal studies. To transform KIDS from a single-round household survey into a longitudinal household panel study required a redefinition of the sampling unit. In 1998, a decision was made to follow the core household members with the intention of capturing the major decision makers within the household.

A household member is a core person if he/she satisfied any of the following criteria: - The self-declared head of household from the 1993 survey - A spouse/partner of the self-declared head of household (from the 1993 survey) - Lives in a three generation household and all of the following are true: - Child of the self-declared household head, son/daughter-in-law of the household head, or niece/nephew of self-declared head - At least 30 years old - Have at least one child living in household - Spouse/partner of person satisfying criterion.

Thus all heads of households and spouses of heads are automatically classified as core and, in some three-generation households, adult children are also included in this cateogry. In this way, we can see the 1993 survey as the baseline information for a random sample of dynasties. The efforts of the 1998 and 2004 surveyors to find the location of the 1993 core members can then be seen as a way to keep track of the 1993 dynasties.

In 2004, due to the aging of the core members and the high prevalence of HIV/AIDS in South Africa, the study was extended in a complementary way to track and interview the households of the children of the core or the next generation. These are sons and daughters of core members older than 18, who have established a "new" household since 1993 (labeled as "K"). By establishing a new household we mean that these children are now living away from their own parents with their own children, or with the children of their partner. Using the next generation to keep track of family "dynasties" provides a way of refreshing the panel and establishing a generational transition. In addition, due to our interest in the impact on children of the HIV/AIDS epidemic, the 2004 wave followed foster children to their new households. This group is defined as children aged less than 18 years old of core and next generation household members who no longer live with their parents i.e. no longer live in core or next generation households (labeled as "N"). As described in Appendix A, different questionnaire modules were administered in the core, next generation, and foster child households.

As the goal of the 2004 wave of KIDS was to find and interview the households of the children of the core and the foster children in addition to those of the regular core members, we had three ways in which we could contact the 1993 dynasties. In 1998, almost 84% of the 1993 dynasties were found as documented by May et al. (2000). From the 1132 dynasties interviewed in 1998, the 2004 wave found 841, yielding a response rate of 74%. Most of these dynasties were still composed of the original core members (760) however some of them were represented by the next generation of household members (K) or foster children (N).

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire containing the following sections:

Household Roster Household Services Food Spending and Consumption Non-Food Spending and Assets Remittances Household Income from Non-Employment Sources Economic Shocks, Agriculture Employment Health Social Capital and Trust Children Tests of Learning and Anthropometry

Response rate

In 1998, almost 84% of the 1993 dynasties were found as documented by May et al. (2000). From the 1132 dynasties interviewed in 1998, the 2004 wave found 841, yielding a response rate of 74%. Most of these dynasties were still composed of the original core members (760) however some of them were represented by the next generation of household members (K) or foster children (N).

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 South Africa’s yearly population growth has been fluctuating since 2013, with the growth rate dropping below the world average in 2024. The majority of people lived in the borders of Gauteng, the smallest of the nine provinces in terms of land area. The number of people residing there amounted to 16.6 million in 2023. Although the Western Cape was the third-largest province, the city of 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 fourth quarter of 2024, the unemployment rate reached close to 60 percent and 384 percent among people aged 15-24 and 25–34 years, respectively. In the same period, some 27 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 74.3 percent.

In 2023, **** percent of South Carolina residents were Black or African American. A further **** percent of the population were white, and * percent of South Carolina residents were of two or more races in that same year.