Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Face-to-face [f2f]

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus version numbers of files within a dataset may not match.

This edition of the Abstract of Agricultural Statistics contains South African agricultural statistics of major importance that were available up to December 2017. The "Abstract" contains meaningful information on, inter alia, field crops, horticulture, livestock, important indicators and the contribution of agriculture.

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (StatsSA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa. Since 2008, StatsSA have produced an annual dataset based on the QLFS data, "Labour Market Dynamics in South Africa". The dataset is constructed using data from all all four QLFS datasets in the year. The dataset also includes a number of variables (including income) that are not available in any of the QLFS datasets from 2010.

Geographic coverage

The survey had national coverage.

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population except for those in workers' hostels. However, persons living in private dwelling units within institutions are enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

Each year the LMDSA is created by combining the QLFS waves for that year and then including some additional variables. The QLFS master frame for this LMDSA was based on the 2011 population census by Stas SA. The sampling is stratified by province, district, and geographic type (urban, traditional, farm).

There are 3324 PSUs drawn each year, using probability proportional to size (PPS) sampling. In the second stage Dwelling Units (DUs) are systematically selected from PSUs. The 3324 PSU are split into four groups for the year, and at each quarter the DUs from the given group are replaced by substitute DUs from the same PSU or the next PSU on the list (in the same group). It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, two quarters and a new household moves in, the new household will be enumerated for two more quarters until the DU is rotated out. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (or unoccupied).

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

Mode of data collection

Face-to-face [f2f]

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Quarterly Labour Force Survey (QLFS) uses a master sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household surveys that have reasonably compatible design requirement as the QLFS. The 2013 master sample is based on information collected during the 2011 population Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the master sample since they covered the entire country and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the master sample with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current master sample (3 324) reflects an 8,0% increase in the size of the master sample compared to the previous (2007) master sample (which had 3 080 PSUs). The larger master sample of PSUs was selected to improve the precision (smaller CVs) of the QLFS estimates.

The master sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are:urban, tribal and farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro. It is divided equally into four sub-groups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one (1) to four (4) and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.

There are a number of aspects in which the 2013 version of the master sample differs from the 2007 version. In particular, the number of primary sample units increased. Mining strata were also introduced which serves to improve the efficiency of estimates relating to employment in mining. The number of geo-types was reduced from 4 to 3 while the new master sample allows for the publication of estimates of the labour market at metro level. The master sample was also adjusted Given the change in the provincial distribution of the South African population between 2001 and 2011. There was also an 8% increase in the sample size of the master sample of PSUs to improve the precision of the QLFS estimates. The sample size increased most notable in Gauteng, the Eastern Cape and KwaZulu-Natal. For more details on the differences between the two master samples please consult the section 8 (technical notes) of the QLFS 2015 Q3 release document (P0211).

From the master sample frame, the QLFS takes draws exmploying a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The primary stratification occurred at provincial, metro/non-metro, mining and geography type while the secondary strata were created within the primary strata based on the demographic and socio-economic characteristics of the population.

For each quarter of the QLFS, a ¼ of the sampled dwellings is rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. Thus, sampled dwellings are expected to remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, two quarters and a new household moves in, the new household will be enumerated for the next two quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (or unoccupied).

Mode of data collection

Face-to-face [f2f]

Abstract

The General Household Survey (GHS) has been used as an instrument to track the progress of development since 2002 when it was first introduced . It is an annual household survey specifically designed to measure the living circumstances of South African households. The GHS collects data on education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Geographic coverage

National

Analysis unit

Households

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Face-to-face [f2f]

Data appraisal

Please note that DataFirst provides versioning at dataset and file level. Revised files have new version numbers. Files that are not revised retain their original version numbers. Changes to any of the data files will result in the dataset having a new version number. Thus, version numbers of files within a dataset may not match.

South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data was reported at 531,545.000 Person in 2018. This records a decrease from the previous number of 568,062.743 Person for 2017. South Africa Population: Mid Year: Eastern Cape: 20 to 24 Years data is updated yearly, averaging 620,146.947 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 671,734.772 Person in 2009 and a record low of 482,541.064 Person in 2001. South Africa Population: Mid Year: Eastern Cape: 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.G004: Population: Mid Year: by Province, Age and Sex.

Abstract

The Volunteer Activities Survey (VAS) is a household-based survey conducted by Statistics South Africa (Stats SA). The VAS collects information on the volunteer activities of individuals aged 15 years and older in South Africa. The respondents were selected from households who took part in the second quarter Quarterly Labour Force Survey (QLFS). Volunteer activities covers unpaid non-compulsory work; that is, the time individuals give without pay to activities performed either through an organisation or directly for others outside their own household.

Data on volunteering provides important infomation on skills application, social network development, social capital and quality of life outcomes. The main aim of the survey is to provide information on the scale of volunteer work and bring into view the sizeable part of the labour force that is invisible in existing labour statistics. The objectives of the VAS are:

• To collect reliable data about people who are involved in volunteer activities. • To identify organisation-based and direct volunteering. • To give a profile of those engaged in volunteer activities. • To estimate the economic value of volunteer work.

Stats SA conducted the first Volunteer Activities Survey (VAS 2010) in the second quarter of 2010 and the second (VAS 2014) in the second quarter of 2014. VAS 2018 is the third survey in the series which was conducted in the second quarter of 2018.

Geographic coverage

The survey has national coverage

Analysis unit

Households and individuals

Universe

The target population of the survey consists of individuals aged 15 years and older who live in South Africa and who are members of households living in dwellings that have been selected to take part in the second quarter Quarterly Labour Force Survey (QLFS).

Kind of data

Sample survey data

Sampling procedure

The Quarterly Labour Force Survey (QLFS) sample frame was used for data collection in the VAS. The sample for the QLFS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The frame was developed as a general purpose household survey frame that can be used by all other household surveys irrespective of the sample size requirement of the survey. The sample is based on information collected by Statistics SA during the 2001 Population Census and is designed to be representative at the provincial level and within provinces at the metro/non-metro level. Within the metros, the sample is further distributed by geography type. The four geography types are: urban formal, urban informal, farms and tribal land.

Mode of data collection

Face-to-face [f2f]

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.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Quarterly: average based on 3 monthly data points

Sampling procedure

Sample size:

Abstract

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The QLFS sample covers the non-institutional population of South Africa with one exception. The only institutional subpopulation included in the QLFS sample are individuals in worker's hostels. Persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Quarterly Labour Force Survey (QLFS) uses a master sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household surveys that have reasonably compatible design requirement as the QLFS. The 2013 master sample is based on information collected during the 2011 population Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the master sample since they covered the entire country and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the master sample with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current master sample (3 324) reflects an 8,0% increase in the size of the master sample compared to the previous (2007) master sample (which had 3 080 PSUs). The larger master sample of PSUs was selected to improve the precision (smaller CVs) of the QLFS estimates.

The master sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are:urban, tribal and farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro. It is divided equally into four sub-groups or panels called rotation groups. The rotation groups are designed in such a way that each of these groups has the same distribution pattern as that which is observed in the whole sample. They are numbered from one (1) to four (4) and these numbers also correspond to the quarters of the year in which the sample will be rotated for the particular group.

There are a number of aspects in which the 2013 version of the master sample differs from the 2007 version. In particular, the number of primary sample units increased. Mining strata were also introduced which serves to improve the efficiency of estimates relating to employment in mining. The number of geo-types was reduced from 4 to 3 while the new master sample allows for the publication of estimates of the labour market at metro level. The master sample was also adjusted Given the change in the provincial distribution of the South African population between 2001 and 2011. There was also an 8% increase in the sample size of the master sample of PSUs to improve the precision of the QLFS estimates. The sample size increased most notable in Gauteng, the Eastern Cape and KwaZulu-Natal. For more details on the differences between the two master samples please consult the section 8 (technical notes) of the QLFS 2015 Q3 release document (P0211).

From the master sample frame, the QLFS takes draws exmploying a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. The primary stratification occurred at provincial, metro/non-metro, mining and geography type while the secondary strata were created within the primary strata based on the demographic and socio-economic characteristics of the population.

For each quarter of the QLFS, a ¼ of the sampled dwellings is rotated out of the sample. These dwellings are replaced by new dwellings from the same PSU or the next PSU on the list. Thus, sampled dwellings are expected to remain in the sample for four consecutive quarters. It should be noted that the sampling unit is the dwelling, and the unit of observation is the household. Therefore, if a household moves out of a dwelling after being in the sample for, two quarters and a new household moves in, the new household will be enumerated for the next two quarters. If no household moves into the sampled dwelling, the dwelling will be classified as vacant (or unoccupied).

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consists of five section: Section 1: Biographical information (marital status, language, migration, education, training, literacy, etc.) Section 2: Economic activities for persons aged 15 years and older Section 3: Unemployment and economic inactivity for persons aged 15 years and older Section 4: Main work activities in the last week for persons aged 15 years and older Section 5: Earnings in the main job for employees, employers and own-account workers aged 15 years and older

The Quarterly Labour Force Survey (QLFS) is a household-based sample survey conducted by Statistics South Africa (Stats SA). It collects data on the labour market activities of individuals aged 15 years or older who live in South Africa.

South Africa Population: Mid Year: Eastern Cape: Male: 35 to 39 Years data was reported at 196,782.000 Person in 2018. This records an increase from the previous number of 191,078.367 Person for 2017. South Africa Population: Mid Year: Eastern Cape: Male: 35 to 39 Years data is updated yearly, averaging 155,979.321 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 196,782.000 Person in 2018 and a record low of 133,930.894 Person in 2001. South Africa Population: Mid Year: Eastern Cape: Male: 35 to 39 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.G004: Population: Mid Year: by Province, Age and Sex.

In the third quarter of 2023, consumers in South Africa spent an estimated 3.07 trillion South African rand in total, which demonstrates a continuous decline from the first quarter of 2023. The coronavirus pandemic had a noticeable impact on the wallets of South African consumers: during the second quarter of 2020, the household consumer spending amounted to about 2.4 trillion South African Rand.

Unemployment Rate in South Africa decreased to 31.90 percent in the third quarter of 2025 from 33.20 percent in the second quarter of 2025. This dataset provides - South Africa Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

As of 2018, the languages most commonly spoken by individuals inside of South African households were isiZulu at 25.3 percent, isiXhosa at 14.8 percent and Afrikaans at 12.2 percent respectively. While English only accounts for the sixth most common language spoken inside of South African households at 8.1 percent, it is the second-most prevalent language spoken outside of homes, at 16.6 percent.

As of 2022, the majority of companies in South Africa (** percent) planned to implement multimedia content strategy as a company tool in the next twelve months. The second favorite tool that year was social media analytics, as 46 percent confirmed to have planned to use it in the upcoming year. This represented a decline in the share of companies who favored this tool in 2021, when 54 percent chose it as their favorite. Nevertheless, both multimedia content and social media analytics have been companies' favorite tools since 2018.

Abstract

In April 2018, StatsSA launched the Governance Public Safety and Justice Survey (GPSJS) in response to the need for standardised international reporting standards on governance and access to justice that are recommended by the SDGs, ShaSA and Agenda 2063. In compliance with these standards, Stats SA discontinued the separate publication of the Victims of Crime Survey (VCS) and incorporated it within the new GPSJS series. Therefore, the GPSJS represents the new source of microdata on the experience and prevalence of particular kinds of crime within South Africa.

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

• Provide information about the dynamics of crime from the perspective of households and the victims of crime.

• Explore public perceptions of the activities of the police, prosecutors, courts and correctional services in the prevention of crime and victimisation.

• Provide complimentary data on the level of crime within South Africa in addition to the statistics published annually by the South African Police Service.

NOTE: The GPSJS is a continuation of the VCS series, which ended with VCS 2017/18. Therefore, the VCS 2018/19 can be exctracted from GPSJS 2018/19 and is comparable to previous VCS's only where questions remained the same. Please see Data Quality Notes for more infomation on comparability.

Geographic coverage

The survey has national coverage.

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa, as well as residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks. It is only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data

Sampling procedure

GPSJS 2018/19 uses a Master Sample of 2013 (MS 2013) which has been designed as a general-purpose household survey frame for all Stats SA household surveys. MS 2013 is based on a stratified two-stage design with probability proportional to size (PPS) sampling of primary sampling units (PSUs) in the first stage, and systematic sampling of dwelling units (DUs) in the second stage. The MS has 3 324 PSUs and it has been divided into four rotation groups. Thus, each rotation group has 831 PSUs.

The selected 3 324 PSUs were sent to Geography division for the creation of the up-to-date DU frame to be used in the selection of the dwelling unit sample. There were three conceptually split PSUs (as per MS design) in the MS PSUs based on GIF information. This resulted in 3 324 PSUs, but on the ground they are represented by 3 321 unique PSUs. Out of the 3 324 PSUs, 3 313 PSUs had dwelling units to sample from while no sample could be drawn from 11 PSUs. The dwelling units were selected using the systematic sampling method with a specified sample take of around 10 DUs per PSU. A total of 27 071 DUs were sampled.

MS 2013 is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

Mode of data collection

Face-to-face [f2f]

Research instrument

The GPSJS 2018/19 questionnaire is based on international reporting standards of governance, public safety and justice defined by the SDGs.

Sections 1 to 3 of the questionnaire relate to household crimes. A proxy respondent (preferably head of the household or acting head of household) answered on behalf of the household. Section 4 to 9 of the questionnaire relate to crimes experienced by individuals and were asked of a household member who was selected using the birthday section method. This methodology selects an individual who is 16 years or older, whose birthday is soonest after the survey date.

Data appraisal

Comparability to VCS series:

While redesigning the VCS into the GPSJS, some questions were modified in order to align the series with international reporting demands (e.g. SDGs) and to improve the accuracy of victim reporting. This caused a break of series for affected questions, in particular questions on 12-month experience of crime. The question on 5-year experience of crime was not changed and hence there is no break of series. The 5-year trends can therefore be used as a proxy for the 12-month series as the two follow similar patterns. Similarity of shapes of the two series makes it possible to predict increase or decrease of crime during the past 12 months using the 5-year series.

Abstract

The Victims of Crime Survey (VCS) is a countrywide household-based survey which collects data on the prevalence of particular kinds of crime within South Africa. The survey includes information on victimisation experienced by individuals and households and their perspectives on community responses to crime. Therefore, VCS data can be used for research in the development of policies and strategies for crime prevention and public safety and education programmes. Statistics South Africa (StatsSA) conducted its first VCS in 1998. Following the VCS 1998, victims surveys were conducted by the Institute for Security Studies (ISS). Since 2011, StatsSA began conducting an annual collection of the VCS as a source of information on crime in South Africa. The main objectives of the survey are to:

• Provide information about the dynamics of crime from the perspective of households and the victims of crime.

• Explore public perceptions of the activities of the police, prosecutors, courts and correctional services in the prevention of crime and victimisation.

• Provide complimentary data on the level of crime within South Africa in addition to the statistics published annually by the South African Police Service.

NOTE: The VCS 2017/18 is the eighth and final release in the collection and is comparable to the new Governance Public Safety and Justice Survey (GPSJS). In April 2018, StatsSA launched the GPSJS in response to the need for standardised international reporting standards on governance and access to justice that are recommended by the SDGs, ShaSA and Agenda 2063. In compliance with these standards, Stats SA has discontinued separate publication of the VCS and rather incorporated it within the new GPSJS series. Therefore, VCS 2017/18 represents the final separate release of the series and all subsequent VCS series can be extracted from the GPSJS series (i.e. VCS 2018/19 is contained within GPSJS 2018/19).

Geographic coverage

The survey has national coverage.

Analysis unit

Households and individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data

Sampling procedure

VCS 2017/2018 uses a Master Sample frame which has been developed as a general-purpose household survey frame that can be used by other Stats SA household-based surveys. VCS 2017/2018 collection was based on the Stats SA 2013 Master Sample. This Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample. There are 3 324 primary sampling units (PSUs) in the Master Sample with an expected sample of approximately 33 000 dwelling units (DUs).The number of PSUs in the current Master Sample (3 324) reflects an 8,0% increase in the size of the Master Sample compared to the previous Master Sample (based on the 2001 Census which had 3 080 PSUs). The updating of the Master Sample as compared to previous VCSs is expected to improve the precision of statistical estimates.

The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

Mode of data collection

Face-to-face [f2f]

Research instrument

The VCS 2017/18 questionnaire was based on the questionnaires used in the International Crime Victim Survey (ICVS) and previous VOCSs conducted by the Institute for Security Studies (ISS) and Statistics SA.

Sections 10 to 20 of the questionnaire relate to household crimes. A proxy respondent (preferably head of the household or acting head of household) answered on behalf of the household. Section 21 to 28 of the questionnaire about crimes on individuals were asked of a household member who was selected using the birthday section method. This methodology selects an individual who is 16 years or older, whose birthday is soonest after the survey date.

Data appraisal

Comparability:

Prior to 2014/2015, VOCS respondents were asked about their crime-related experiences in the previous calendar year, but since 2014/15 VCS changed to a Continuous Data Collection (CDC) method. In this data collection method, respondents were interviewed on a rolling basis over the course of a year and asked about crime experienced in the 12 months prior to the interview. As a result of this, the victimisation experiences reported by respondents interviewed in a period of 12 months relate to a broader span of 23 months.

The VCS 2017/18 is comparable to all previous VCSs iin that several questions have remained unchanged over time. Where possible, it was generally indicated in the report. Additionally, the VCS 2017/18 is the last before VCS became incorproated into a broader survey called the GPSJS. The change to the surveys will likely cause some comparability issues going forward beyond 2018.

Metadata: There is an error in the SSA published metadata, which incorrectly states that the survey was designed with 3080 PSUs. The survey was designed with 3324 PSUs.

South Africa Population: Mid Year: Eastern Cape: Male: 30 to 34 Years data was reported at 242,435.000 Person in 2018. This records an increase from the previous number of 238,308.846 Person for 2017. South Africa Population: Mid Year: Eastern Cape: Male: 30 to 34 Years data is updated yearly, averaging 183,708.440 Person from Jun 2001 (Median) to 2018, with 18 observations. The data reached an all-time high of 242,435.000 Person in 2018 and a record low of 148,367.490 Person in 2001. South Africa Population: Mid Year: Eastern Cape: Male: 30 to 34 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.G004: Population: Mid Year: by Province, Age and Sex.

Google's Android dominates the mobile operating system market in South Africa. Android had a market share of over ** percent as of October 2025, with Apple's iOS claiming around **** percent.