South Africa's immigrant population has undergone noticeable changes in recent decades, with the total number reaching approximately 2.4 million in 2022. Interestingly, while the overall immigrant population has grown, the number of immigrants who are South African citizens has steadily declined since 2001. This shift in citizenship status among immigrants reflects broader trends in migration patterns and policies in the region. Demographic shifts and origins of immigrants The composition of South Africa's immigrant population has evolved, with Zimbabwe emerging as the primary source country in 2022, accounting for 48.5 percent of immigrants. Mozambique and Lesotho followed, contributing 20 percent and nearly 11 percent, respectively. The median age of immigrants has also increased slightly, reaching 34 years for men and 33 years for women in 2022, up from 31 and 30 years in 2011. These demographic changes highlight the dynamic nature of migration flows in the region. Regional context and refugee populations South Africa's immigration trends are part of a larger pattern of population movements across Sub-Saharan Africa. The region has experienced a significant increase in refugee populations, with nearly eight million refugees recorded in 2023, a substantial rise from 2.2 million in 2010. While South Africa remains an important destination for immigrants, other countries in the region, such as Uganda, Sudan, and Ethiopia, host large numbers of refugees. Uganda, in particular, has emerged as the African country with the largest refugee population, sheltering nearly 1.5 million individuals as of 2023.

As of November 2023, the number of foreign travelers arriving in South Africa added up to almost 1.02 million. Compared to the previous month, this represented an increase of 1.5 percent. Due to the coronavirus (COVID-19) lockdown which was first introduced in March 2020, the number of foreigners travelling to South Africa dropped significantly to 29.3 thousand. Moreover, the number of foreigners departing from South Africa was slightly lower, as it amounted to around 201.8 thousand as of July 2021.

South Africa ZA: Net Migration data was reported at 300,000.000 Person in 2017. This records a decrease from the previous number of 806,500.000 Person for 2012. South Africa ZA: Net Migration data is updated yearly, averaging 263,300.000 Person from Dec 1962 (Median) to 2017, with 12 observations. The data reached an all-time high of 806,500.000 Person in 2012 and a record low of -129,050.000 Person in 1987. South Africa ZA: Net Migration data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Population and Urbanization Statistics. Net migration is the net total of migrants during the period, that is, the total number of immigrants less the annual number of emigrants, including both citizens and noncitizens. Data are five-year estimates.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Sum;

In 2020, South Africa hosted approximately **** million international migrants. The vast majority were from Zimbabwe, amounting to roughly *** thousand people. The neighboring country Mozambique was the origin of around *** thousand migrants, while *** thousand held Lesotho's nationality, which is an enclave within South Africa.

Abstract

The Human Sciences Research Council (HSRC) carried out the Migration and Remittances Survey in South Africa for the World Bank in collaboration with the African Development Bank. The primary mandate of the HSRC in this project was to come up with a migration database that includes both immigrants and emigrants. The specific activities included: · A household survey with a view of producing a detailed demographic/economic database of immigrants, emigrants and non migrants · The collation and preparation of a data set based on the survey · The production of basic primary statistics for the analysis of migration and remittance behaviour in South Africa.

Like many other African countries, South Africa lacks reliable census or other data on migrants (immigrants and emigrants), and on flows of resources that accompanies movement of people. This is so because a large proportion of African immigrants are in the country undocumented. A special effort was therefore made to design a household survey that would cover sufficient numbers and proportions of immigrants, and still conform to the principles of probability sampling. The approach that was followed gives a representative picture of migration in 2 provinces, Limpopo and Gauteng, which should be reflective of migration behaviour and its impacts in South Africa.

Geographic coverage

Two provinces: Gauteng and Limpopo

Limpopo is the main corridor for migration from African countries to the north of South Africa while Gauteng is the main port of entry as it has the largest airport in Africa. Gauteng is a destination for internal and international migrants because it has three large metropolitan cities with a great economic potential and reputation for offering employment, accommodations and access to many different opportunities within a distance of 56 km. These two provinces therefore were expected to accommodate most African migrants in South Africa, co-existing with a large host population.

Analysis unit

• Household
• Individual

Universe

The target group consists of households in all communities. The survey will be conducted among metro and non-metro households. Non-metro households include those in: - small towns, - secondary cities, - peri-urban settlements and - deep rural areas. From each selected household, one adult respondent will be selected to participate in the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Migration data for South Africa are available for 2007 only at the level of local governments or municipalities from the 2007 Census; for smaller areas called "sub places" (SPs) only as recently as the 2001 census, and for the desired EAs only back so far as the Census of 1996. In sum, there was no single source that provided recent data on the five types of migrants of principal interest at the level of the Enumeration Area, which was the area for which data were needed to draw the sample since it was going to be necessary to identify migrant and non-migrant households in the sample areas in order to oversample those with migrants for interview.

In an attempt to overcome the data limitations referred to above, it was necessary to adopt a novel approach to the design of the sample for the World Bank's household migration survey in South Africa, to identify EAs with a high probability of finding immigrants and those with a low probability. This required the combined use of the three sources of data described above. The starting point was the CS 2007 survey, which provided data on migration at a local government level, classifying each local government cluster in terms of migration level, taking into account the types of migrants identified. The researchers then spatially zoomed in from these clusters to the so-called sub-places (SPs) from the 2001 Census to classifying SP clusters by migration level. Finally, the 1996 Census data were used to zoom in even further down to the EA level, using the 1996 census data on migration levels of various typed, to identify the final level of clusters for the survey, namely the spatially small EAs (each typically containing about 200 households, and hence amenable to the listing operation in the field).

A higher score or weight was attached to the 2007 Community Survey municipality-level (MN) data than to the Census 2001 sub-place (SP) data, which in turn was given a greater weight than the 1996 enumerator area (EA) data. The latter was derived exclusively from the Census 1996 EA data, but has then been reallocated to the 2001 EAs proportional to geographical size. Although these weights are purely arbitrary since it was composed from different sources, they give an indication of the relevant importance attached to the different migrant categories. These weighted migrant proportions (secondary strata), therefore constituted the second level of clusters for sampling purposes.

In addition, a system of weighting or scoring the different persons by migrant type was applied to ensure that the likelihood of finding migrants would be optimised. As part of this procedure, recent migrants (who had migrated in the preceding five years) received a higher score than lifetime migrants (who had not migrated during the preceding five years). Similarly, a higher score was attached to international immigrants (both recent and lifetime, who had come to SA from abroad) than to internal migrants (who had only moved within SA's borders). A greater weight also applied to inter-provincial (internal) than to intra-provincial migrants (who only moved within the same South African province).

How the three data sources were combined to provide overall scores for EA can be briefly described. First, in each of the two provinces, all local government units were given migration scores according to the numbers or relative proportions of the population classified in the various categories of migrants (with non-migrants given a score of 1.0. Migrants were assigned higher scores according to their priority, with international migrants given higher scores than internal migrants and recent migrants higher scores than lifetime migrants. Then within the local governments, sub-places were assigned scores assigned on the basis of inter vs. intra-provincial migrants using the 2001 census data. Each SP area in a local government was thus assigned a value which was the product of its local government score (the same for all SPs in the local government) and its own SP score. The third and final stage was to develop relative migration scores for all the EAs from the 1996 census by similarly weighting the proportions of migrants (and non-migrants, assigned always 1.0) of each type. The the final migration score for an EA is the product of its own EA score from 1996, the SP score of which it is a part (assigned to all the EAs within the SP), and the local government score from the 2007 survey.

Based on all the above principles the set of weights or scores was developed.

In sum, we multiplied the proportion of populations of each migrant type, or their incidence, by the appropriate final corresponding EA scores for persons of each type in the EA (based on multiplying the three weights together), to obtain the overall score for each EA. This takes into account the distribution of persons in the EA according to migration status in 1996, the SP score of the EA in 2001, and the local government score (in which the EA is located) from 2007. Finally, all EAs in each province were then classified into quartiles, prior to sampling from the quartiles.

From the EAs so classified, the sampling took the form of selecting EAs, i.e., primary sampling units (PSUs, which in this case are also Ultimate Sampling Units, since this is a single stage sample), according to their classification into quartiles. The proportions selected from each quartile are based on the range of EA-level scores which are assumed to reflect weighted probabilities of finding desired migrants in each EA. To enhance the likelihood of finding migrants, much higher proportions of EAs were selected into the sample from the quartiles with the higher scores compared to the lower scores (disproportionate sampling). The decision on the most appropriate categorisations was informed by the observed migration levels in the two provinces of the study area during 2007, 2001 and 1996, analysed at the lowest spatial level for which migration data was available in each case.

Because of the differences in their characteristics it was decided that the provinces of Gauteng and Limpopo should each be regarded as an explicit stratum for sampling purposes. These two provinces therefore represented the primary explicit strata. It was decided to select an equal number of EAs from these two primary strata.

The migration-level categories referred to above were treated as secondary explicit strata to ensure optimal coverage of each in the sample. The distribution of migration levels was then used to draw EAs in such a way that greater preference could be given to areas with higher proportions of migrants in general, but especially immigrants (note the relative scores assigned to each type of person above). The proportion of EAs selected into the sample from the quartiles draws upon the relative mean weighted migrant scores (referred to as proportions) found below the table, but this is a coincidence and not necessary, as any disproportionate sampling of EAs from the quartiles could be done, since it would be rectified in the weighting at the end for the analysis.

The resultant proportions of migrants then led to the following proportional allocation of sampled EAs (Quartile 1: 5 per cent (instead of 25% as in an equal distribution), Quartile 2: 15 per cent (instead

United States Gross Sales by Foreigners: South Africa: US Corp Stocks data was reported at 247.000 USD mn in May 2018. This records a decrease from the previous number of 265.000 USD mn for Apr 2018. United States Gross Sales by Foreigners: South Africa: US Corp Stocks data is updated monthly, averaging 16.000 USD mn from Oct 1976 (Median) to May 2018, with 500 observations. The data reached an all-time high of 437.000 USD mn in Oct 2014 and a record low of 0.000 USD mn in Dec 1994. United States Gross Sales by Foreigners: South Africa: US Corp Stocks data remains active status in CEIC and is reported by US Department of Treasury. The data is categorized under Global Database’s USA – Table US.Z038: Foreign Purchases and Sales in Long Term Securities: African Countries.

In 2022, the percentage distribution of immigrants in South Africa was highest among the Black/African population group, with around 82 percent. White migrants followed, with a share of about 10 percent. Since 2001, the portion of Black/African immigrants in the country has made notable increases, whereas the remaining population groups have mostly experienced decreases.

As of November 2023, the number of foreign travelers departing from South Africa amounted to around 881 housand. Compared to the previous month, this represented an increase from roughly 846.9 thousand. Moreover, the number of foreigners arriving in South Africa was higher, as it reached over 1.01 million as of November 2023.

South Africa ZA: International Migrant Stock: % of Population data was reported at 5.767 % in 2015. This records an increase from the previous number of 3.764 % for 2010. South Africa ZA: International Migrant Stock: % of Population data is updated yearly, averaging 2.834 % from Dec 1990 (Median) to 2015, with 6 observations. The data reached an all-time high of 5.767 % in 2015 and a record low of 2.231 % in 2000. South Africa ZA: International Migrant Stock: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Population and Urbanization Statistics. International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.; ; United Nations Population Division, Trends in Total Migrant Stock: 2008 Revision.; Weighted average;

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.

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 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 so-called National States of Ciskei, KwaZulu, Gazankulu, Lebowa, Qwaqwa, Kangwane, and Kwandebele. The 1980 South African census excluded the "independent states" of Bophuthatswana, Transkei, and Venda. A census data file for Bophuthatswana was released with the final South African Census 1980 dataset.

Analysis unit

Households and individuals

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

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 employed as domestics (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)

There were ****** international students in South Africa as of 2019. Compared to the preceding year, this was a drop of ***** students. During the period under review, the number of foreign students in the country declined significantly in 2012 to close to ****** from over ****** in the previous year.

In 2022, the largest percentage distribution of immigrants in South Africa were residing in the Gauteng province, with just over 50 percent. The Western Cape followed, with a share of almost 16 percent. This is mostly due to better economic activities in these provinces, and more job opportunities.

Japan Number of Foreign Residents: Republic of South Africa data was reported at 873.000 Person in Dec 2017. This records an increase from the previous number of 834.000 Person for Jun 2017. Japan Number of Foreign Residents: Republic of South Africa data is updated semiannually, averaging 623.000 Person from Dec 2012 (Median) to Dec 2017, with 11 observations. The data reached an all-time high of 873.000 Person in Dec 2017 and a record low of 534.000 Person in Jun 2013. Japan Number of Foreign Residents: Republic of South Africa data remains active status in CEIC and is reported by Ministry of Justice. The data is categorized under Global Database’s Japan – Table JP.G008: Foreign Resident Statistics.

Abstract

The population census conducted in South Africa in 1985 covered the whole of South Africa, but excluded the "Homelands" of Transkei, Bophutatswana, Ciskei, and Venda. This dataset is the full census, as opposed to the 10% sample datasets provided by Statistics South Africa from 1996 onwards.

Geographic coverage

The 1985 census covered the so-called white areas of South Africa - the provinces of the Cape, the Orange Free State, Transvaal, and Natal - 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.

The 1985 Census dataset has 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

All persons who were present on Republic of South African territory during census night were enumerated. 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 enumerated but not included in the final data. 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

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 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).

Foreign Direct Investment in South Africa increased by 11700 ZAR Billion in the first quarter of 2025. This dataset provides - South Africa Foreign Direct Investment- actual values, historical data, forecast, chart, statistics, economic calendar and news.

South Africa Number of Local Branches of Foreign Banks data was reported at 17.000 Number in Feb 2020. This stayed constant from the previous number of 17.000 Number for Jan 2020. South Africa Number of Local Branches of Foreign Banks data is updated monthly, averaging 15.000 Number from Jan 2016 (Median) to Feb 2020, with 50 observations. The data reached an all-time high of 17.000 Number in Feb 2020 and a record low of 15.000 Number in Aug 2019. South Africa Number of Local Branches of Foreign Banks data remains active status in CEIC and is reported by South African Reserve Bank. The data is categorized under Global Database’s South Africa – Table ZA.KB019: Number of Banks.

Abstract

The 1991 South African population census was an enumeration of the population and housing in South Africa.The census collected data on dwellings and individuals' demographic, family and employment details.

Geographic coverage

The South African Census 1991 covered the whole of South Africa. The "homelands" of Transkei, Bophuthatswana, Venda and Ciskei were enumerated separately and the dataset contains data files for Bophuthatswana, Venda and Ciskei. The dataset does not include a data file for the Transkei.

Analysis unit

The units of analysis under observation in the South African census 1991 are households and individuals

Universe

The 1991 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 7 and 8 March 1991) were therefore 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 enumerated and included in the figures. The Diplomatic and Consular Corps of foreign countries were not included. Crews and passengers of ships were also not enumerated, except those who were present at the harbours of the RSA on census night. Similarly, residents of the RSA who were absent from the night were not enumerated. 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 deviation

As a result of the unplanned and unstructured nature of certain residential areas, as well as the inaccessibility of certain areas during the preparations for the enumeration of census, comprehensive door-to-door surveys were not possible. The Human Sciences Research Council had to enumerate these areas by means of sample surveys. 88 areas country-wide were enumerated on this basis.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1991 Population Census questionnaire covered particulars of households: dwelling type, ownership type, type of area (rural/urban) and particulars of individuals: relationship within household, sex, age, marital status, population group, birthplace, citizenship, duration of residency, religion, education level, language, literacy,employment status, occupation, economic sector and income.

africa albania alemania algeria ambos-sexos ame_rica-central-y-caribe ame_rica-del-norte ame_rica-del-sur america an_o andorra angola arabia-saudi arabia-saudi_ argelia argentina armenia asia australia austria bangladesh be_lgica belaru_s belarus belgium benin bolivia born-abroad born-in-spain bosnia-and-herzegovina bosnia-y-herzegovina both-sexes brasil brazil bulgaria burkina-faso cabo-verde cameroon cameru_n canada canada_ central-america-and-caribbean chile china chipre colombia communities comunidades congo continuous-register-statistics corea costa-de-marfil costa-rica country-of-birth croacia croatia cuba cyprus czech-republic democratic-republic-of-congo denmark dinamarca dominica dominican-republic ecuador egipto egypt el-salvador equatorial-guinea eslovenia espan_ol-extranjero estadi_stica-del-padro_n-continuo estadi_sticas estados-unidos-de-ame_rica estonia ethiope etiopi_a eu_27_2020_ europe females filipinas finland finlandia foreign-nationality france francia gambia georgia germany ghana grecia greece green-cape guatemala guinea guinea-bissau guinea-ecuatorial hombres honduras hungary hungri_a iceland india indonesia ira_n iran iraq ireland irlanda islandia israel italia italy ivory-coast japan japo_n jordan jordania kazajsta_n kazajstan kenia korea latvia lebanon letonia li_bano liberia liechtenstein lithuania lituania luxembourg luxemburgo macedonia-del-norte males mali malta marruecos mauritania me_xico mexico moldavia morocco mujeres nacidos-en-el-extranjero nacidos-en-espan_a nacionalidad-espan_ola nacionalidad-extranjera nepal new-zealand nicaragua nigeria non-european-community_27_2020_ north-america north-macedonia noruega norway nueva-zelanda oceania pai_s-de-nacimiento pai_ses-africanos pai_ses-americanos pai_ses-asia_ticos pai_ses-bajos pai_ses-de-oceani_a pai_ses-europeos pai_ses-europeos-no-ue_27_2020_ pakista_n pakistan panama panama_ paraguay peru peru_ philippines poland polonia portugal reino-unido repu_blica-checa repu_blica-democra_tica-del-congo repu_blica-dominicana repu_blica-eslovaca rest-of-africa rest-of-asia rest-of-central-america-and-caribbean rest-of-european-nationalities rest-of-oceania rest-of-south-america resto-de-ame_rica-central-y-caribe resto-de-ame_rica-del-sur resto-de-pai_ses-africanos resto-de-pai_ses-asia_ticos resto-de-pai_ses-de-oceani_a resto-de-pai_ses-europeos romania rumani_a rusia russia senegal serbia serbia-and-montenegro_former-yugoslavia_ serbia-y-montenegro-_antigua-yugoslavia_ sex sexo sierra-leona sierra-leone siria slovenia south-africa south-america spanish-foreigner spanish-nationality statistics suda_frica suecia suiza sweden switzerland syria tailandia thailand the-netherlands the-slovak-republic togo total total-poblacio_n total-population tu_nez tunisia turkey turqui_a ucrania ukraine unio_n-europea-_27_2020_ united-kingdom united-states-of-america uruguay venezuela vietnam year