Description: data presented as a spreadsheet; Provides an overview of the labour force participation rate across all provinces and metros in South Africa since 2008.Linage: The data presented is extracted from Statistics South Africa (Stats SA) Quarterly Labour Force Survey (QLFS) trends as published on https://www.statssa.gov.za/Publication Date: 14 May 2024Data Sources: QLFS Trends 2008-2024Q1, Stats SA, published ‎14 ‎May ‎2024Contact Person: Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Data presented as a spreadsheet; Provides Electricity generated and available for distribution in South Africa since 2002.Linage:The data presented is extracted from Statistics South Africa (Stats SA) Electricity generated and available for distribution trends as published on https://www.statssa.gov.za/Publication Date:04 July 2024Data sources:Excel - Electricity generated and available for distribution(202405), Stats SA, published 4 July 2024Contact Person:Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

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 data can be used for research in the development of policies and strategies for governance, crime prevention, public safety and justice programmes with the main objectives of the survey being 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; and • 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

The GPSJS 2022/23 uses the Master Sample (MS) sampling frame that has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys that have design requirements that are reasonably compatible with GPSJS. The GPSJS 2022/23 collection was drawn from the 2013 Master Sample. This master sample is based on information collected during Census 2011. 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 GPSJS estimates.

Mode of data collection

Computer Assisted Telephone Interview

Research instrument

The GPSJS 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.

Comparability to previous GPSJS series: To facilitate CATI data collection, the GPSJS 2019/20 sample was re-used and households that provided operational telephone numbers in 2019/20 were contacted and interviewed. The data is adjusted during the weighting process due to non-response from some households. The details of how the adjustment was done is contained in the metadata technical report. Given the change in the data survey mode of collection from CAPI to CATI, and the fact that the GPSJS 2020/21 estimates are not based on a full sample, comparisons with previous years should be made with caution.

Abstract

In October 2001, South Africans were enumerated to collect information on persons and households throughout the country, using a uniform methodology. Household data collected included data on each household and each person present in the household on Census night, as well as data on services available to the household. Data on household residents, and residents of hostels and the other types of collective living quarters was also captured, as well as data on individuals who spent census night in institutions and hotels.

Geographic coverage

The South African Census 2001 has national coverage.

Analysis unit

The units of analysis for the South Africa Census 2001 were households and individuals

Universe

The South African Census 2001 covered every person present in South Africa on Census Night, 9-10 October 2001 including all de jure household members and residents of institutions.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The data in the South African Census 2001 dataset is a 10% unit level sample drawn from Census 2001 as follows: 1) Households: • A 10% sample of households in housing units, and • A 10% sample of collective living quarters (both institutional and non-institutional) and the homeless.

2) Persons: • A sample consisting of all persons in the households and collective living quarters, and the homeless, drawn for the samples described above

3) Mortality: • A sample consisting of all mortality information for the households in housing units drawn in the 10% sample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were administered for the South African Census 2001, questionnaire A (for persons in households), questionnaire B (for persons in institutions) and questionnaire C (for institutions). The Household questionnaire covered household characteristics, such as dwellling type, home ownership, household assets, access to services and energy sources. A component of the questionnaire captures fertility data. Both the household and persons in institutions questionnaires collected data on individuals' characteristics, including age, population group, language, religion, citizenship, migration, mortality and disability, as well as means of travel. Economic characteristics of individuals included employment activities and data on unemployment.

Cleaning operations

The following publication can be consulted for a detailed account of the editing undertaken for the South African Census 2001: Computer editing specifications / Statistics South Africa. Pretoria: Statistics South Africa, 2003 369p. [Report No. 03-02-43 (2001)]. ISBN 0-621-34566-0.

Data appraisal

As part of the quality check for Census 2001, a Post-Enumeration Survey (PES) was conducted in November 2001, approximately one month after the census. Fieldworkers re-visited a scientifically selected sample of almost 1% of the census enumeration areas, to do an independent recount. The published census results are adjusted for undercount according to the findings of the PES. In addition to the check on coverage, the PES also involved an independent re-measurement of the basic characteristics of the population. Details on this process are available in the publication:

Statistics South Africa. 2004. Census 2001: post-enumeration survey: results and methodology. Report no. 03-02-17 (2001).

"Online news websites and apps / ePaper" and "Podcasts" are the top two answers among South African consumers in our survey on the subject of "Most used publishing media services".The survey was conducted online among 2,030 respondents in South Africa, in 2024.

Abstract

The Marriages and Divorces (MD) dataset is one of three primary sources of of marriage and divorce statistics in South Africa. Unlike the other two sources (population censuses and household sample surveys), the MD dataset is compiled from administrative data and based on continuous recording (i.e. from civil registration systems and administrative records). Statistics South Africa (Stats SA) regularly publishes a series of data on marriages and divorces, with the first dataset in the series begining in 2006. The most recent dataset in the series is MD 2022.

Marriage data: Data on marriages for citizens and permanent residents are obtained from registered marriage records that are collected through the civil registration systems of the Department of Home Affairs (DHA). South Africa recognises three types of marriages by law: civil marriages, customary marriages and civil unions. Before 2008, marriage data only covered civil marriages. The registration of customary marriages and civil unions began in 2003 and 2007 respectively. However from 2008 onwards, Stats SA began publishing available data on customary marriages and civil unions.

Divorce data: Data on divorces are obtained from various regional courts that deal with divorce matters. The data are based on successful divorce cases that have been issued with a decree of divorce by the Department of Justice and Constitutional Development (DoJCD). Divorce cases come from marriages that were registered in different years as well as divorce cases that were filed in different years but whose divorce decrees were granted in the relevant year of collection.

NOTE: although both the data on marriages and divorces are collected in the same year, the data sets are not linked to each other.

Geographic coverage

The data has national coverage.

Analysis unit

Individuals

Universe

The data covers all civil marriages, civil unions and customary marriages that were recorded by the Department of Home Affairs and all divorce applications that were granted by the Department of Justice and Constitutional Development in 2022 in South Africa.

Kind of data

Administrative records

Mode of data collection

Other

Data presented as a spreadsheet; Provides CPI for Food across all provinces in South Africa since 2008.Linage: The data presented is extracted from Statistics South Africa (Stats SA) Consumer Price Index (CPI) trends as published on https://www.statssa.gov.za/Publication Date: 23 October 2024Data Sources:Excel - CPI (COICOP) from January 2008 (202409), Stats SA, published 23 October 2024Contact Person:Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

South Africa ZA: Death Rate: Crude: per 1000 People data was reported at 9.793 Ratio in 2016. This records a decrease from the previous number of 10.102 Ratio for 2015. South Africa ZA: Death Rate: Crude: per 1000 People data is updated yearly, averaging 11.455 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 14.815 Ratio in 1960 and a record low of 8.199 Ratio in 1991. South Africa ZA: Death Rate: Crude: per 1000 People 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. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

As of March 2020, the Consumer Price Index (CPI) in South Africa, an economic indicator providing information on the change of prices over time, was measured at 119.6 points regarding books, newspapers and stationery. This is symbolizing an increase of 5.8 points from the previous year.

South Africa ZA: Prevalence of Undernourishment: % of Population data was reported at 4.600 % in 2015. This records an increase from the previous number of 4.000 % for 2014. South Africa ZA: Prevalence of Undernourishment: % of Population data is updated yearly, averaging 4.200 % from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 4.700 % in 2000 and a record low of 3.600 % in 2012. South Africa ZA: Prevalence of Undernourishment: % 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: Health Statistics. Population below minimum level of dietary energy consumption (also referred to as prevalence of undernourishment) shows the percentage of the population whose food intake is insufficient to meet dietary energy requirements continuously. Data showing as 5 may signify a prevalence of undernourishment below 5%.; ; Food and Agriculture Organization (http://www.fao.org/publications/en/).; Weighted average;

According to the source, the number of employees of the publishing company Planeta SA in Spain peaked in the year 2016 with 492 employees. From then on the number of employees has been fluctuating with the lowest point being in 2017 with 441 employees and the highest point again in 2019 with 483.

United States AHE: sa: PW: Information: Newspaper Publishers data was reported at 27.640 USD in Nov 2022. This records an increase from the previous number of 27.170 USD for Oct 2022. United States AHE: sa: PW: Information: Newspaper Publishers data is updated monthly, averaging 18.760 USD from Jan 2003 (Median) to Nov 2022, with 239 observations. The data reached an all-time high of 27.640 USD in Nov 2022 and a record low of 15.070 USD in Jan 2003. United States AHE: sa: PW: Information: Newspaper Publishers data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G071: Current Employment Statistics Survey: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

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.

Students and Courses and Apprentices and Trainees: These statistics cover administrative data sets on student enrolments and qualifications attained with approximately 2 million students enrolling on vocation education and training in Australia each year, 400,000 graduates each year, and around 400,000 people in training as part of an apprenticeship or traineeships. Demographic information on students as well as the qualification they are training in and where the training took place are included. Courses are classified by intended occupation on completion, and field of study. Student Outcomes Survey: In addition a graduate destination survey is run capturing information on the quality of training, occupations before and after training, salary, and further education. Under data tab each collection appears and can be selected individually for information excel files and publications, under data data are three resources, Vocstats datacubes, VET Students by Industry, VET Graduates outcomes, salaries and jobs. http://www.ncver.edu.au For an overview of the statistics please see the following publication https://www.ncver.edu.au/publications/publications/all-publications/statistical-standard-software/avetmiss-data-element-definitions-edition-2.2# Datasets to be attributed to National Centre for Vocational Education Research (NCVER). https://www.ncver.edu.au/ Register for VOCSTATS by visiting the website (http://www.ncver.edu.au/wps/portal/vetdataportal/data/menu/vocstats)

Description: data presented as spreadsheet; Provides an overview of the official unemployment rate by narrow definition across all provinces and metros in South Africa since 2008.Linage: The data presented is extracted from Statistics South Africa (Stats SA) Quarterly Labour Force Survey (QLFS) trends as published on https://www.statssa.gov.za/Publication Date: 14 May 2024Data Sources: QLFS Trends 2008-2024Q1, Stats SA, published ‎14 ‎May ‎2024Contact Person: Elize van der Berg, Department of the Premier, Elize.VanDerBerg@westerncape.gov.za

Graph and download economic data for All Employees, Publishing Industries (CES5051100001) from Jan 1990 to Feb 2025 about printing, information, establishment survey, employment, industry, and USA.

Avg Weekly Earnings: sa: IF: Publishing Industries (PI) data was reported at 2,281.050 USD in Jan 2025. This records an increase from the previous number of 2,248.850 USD for Dec 2024. Avg Weekly Earnings: sa: IF: Publishing Industries (PI) data is updated monthly, averaging 1,538.630 USD from Mar 2006 (Median) to Jan 2025, with 227 observations. The data reached an all-time high of 2,308.280 USD in Oct 2024 and a record low of 1,005.260 USD in Apr 2006. Avg Weekly Earnings: sa: IF: Publishing Industries (PI) data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G065: Current Employment Statistics Survey: Average Weekly Earnings: Seasonally Adjusted.

United States AHE: sa: PW: Information: Publishing Industries, Except Internet data was reported at 44.270 USD in Nov 2022. This records an increase from the previous number of 43.780 USD for Oct 2022. United States AHE: sa: PW: Information: Publishing Industries, Except Internet data is updated monthly, averaging 30.470 USD from Jan 2003 (Median) to Nov 2022, with 239 observations. The data reached an all-time high of 44.270 USD in Nov 2022 and a record low of 21.570 USD in Mar 2003. United States AHE: sa: PW: Information: Publishing Industries, Except Internet data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G071: Current Employment Statistics Survey: Average Hourly Earnings: Production Workers: Seasonally Adjusted.

Data.SA publishing organisations site analytics 2016

This statistic shows the distribution of employees of the publishing company Planeta SA in Spain from 2010 to 2017, by type of contract. In 2017, all people employed by the Spanish publishing company had a permanent contract.