26 datasets found
  1. Forecast of the global middle class population 2015-2030

    • statista.com
    Updated Jan 23, 2025
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    Statista (2025). Forecast of the global middle class population 2015-2030 [Dataset]. https://www.statista.com/statistics/255591/forecast-on-the-worldwide-middle-class-population-by-region/
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    Dataset updated
    Jan 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2017
    Area covered
    World
    Description

    By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 million in 2030.

    Worldwide wealth

    While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent of non-investable assets.

    The middle-class

    The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth to the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle-class.

  2. S

    South Africa ZA: Income Share Held by Third 20%

    • ceicdata.com
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    CEICdata.com, South Africa ZA: Income Share Held by Third 20% [Dataset]. https://www.ceicdata.com/en/south-africa/poverty/za-income-share-held-by-third-20
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1993 - Dec 1, 2014
    Area covered
    South Africa
    Description

    South Africa ZA: Income Share Held by Third 20% data was reported at 8.200 % in 2014. This records an increase from the previous number of 8.000 % for 2010. South Africa ZA: Income Share Held by Third 20% data is updated yearly, averaging 8.200 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 9.900 % in 2000 and a record low of 7.500 % in 2005. South Africa ZA: Income Share Held by Third 20% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

  3. Household disposable income per capita in South Africa 2004-2022

    • statista.com
    Updated Nov 14, 2023
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    Statista (2023). Household disposable income per capita in South Africa 2004-2022 [Dataset]. https://www.statista.com/statistics/874035/household-disposable-income-in-south-africa/
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    Dataset updated
    Nov 14, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    South Africa
    Description

    In 2022, South African households had an average disposable income of over 50,500 South African rand (approximately 2,738 U.S. dollars). This was slightly higher than the previous year where the average disposable income was 50,343 South African rand (around 2,725 U.S. dollars). Within the observed period, the disposable income of households in the country was highest in 2018 at 51,236 South African rand (about 2,773 U.S. dollars), while it was lowest in 2004.

  4. S

    South Africa ZA: Income Share Held by Highest 20%

    • ceicdata.com
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    CEICdata.com, South Africa ZA: Income Share Held by Highest 20% [Dataset]. https://www.ceicdata.com/en/south-africa/poverty/za-income-share-held-by-highest-20
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1993 - Dec 1, 2014
    Area covered
    South Africa
    Description

    South Africa ZA: Income Share Held by Highest 20% data was reported at 68.200 % in 2014. This records a decrease from the previous number of 68.900 % for 2010. South Africa ZA: Income Share Held by Highest 20% data is updated yearly, averaging 68.200 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 71.000 % in 2005 and a record low of 62.700 % in 2000. South Africa ZA: Income Share Held by Highest 20% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

  5. S

    South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods...

    • ceicdata.com
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    CEICdata.com, South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa [Dataset]. https://www.ceicdata.com/en/south-africa/imports/za-imports-low-and-middleincome-economies--of-total-goods-imports-middle-east--north-africa
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    South Africa
    Variables measured
    Merchandise Trade
    Description

    South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa data was reported at 0.280 % in 2016. This records a decrease from the previous number of 0.400 % for 2015. South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa data is updated yearly, averaging 4.068 % from Dec 1998 (Median) to 2016, with 19 observations. The data reached an all-time high of 5.552 % in 2008 and a record low of 0.280 % in 2016. South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa 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: Imports. Merchandise imports from low- and middle-income economies in Middle East and North Africa are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Middle East and North Africa region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

  6. Income per capita in Africa 2023, by country

    • statista.com
    Updated Sep 30, 2024
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    Statista (2024). Income per capita in Africa 2023, by country [Dataset]. https://www.statista.com/statistics/1290903/gross-national-income-per-capita-in-africa-by-country/
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    Dataset updated
    Sep 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Africa
    Description

    Seychelles recorded the highest Gross National Income (GNI) per capita in Africa as of 2023, at 16,940 U.S. dollars. The African island was, therefore, the only high-income country on the continent, according to the source's classification. Mauritius, Gabon, Botswana, Libya, South Africa, Equatorial Guinea, Algeria, and Namibia were defined as upper-middle-income economies, those with a GNI per capita between 4,516 U.S. dollars and 14,005 U.S. dollars. On the opposite, 20 African countries recorded a GNI per capita below 1,145 U.S. dollars, being thus classified as low-income economies. Among them, Burundi presented the lowest income per capita, some 230 U.S. dollars. Poverty and population growth in Africa Despite a few countries being in the high income and upper-middle countries classification, Africa had a significant number of people living under extreme poverty. However, this number is expected to decline gradually in the upcoming years, with experts forecasting that this number will decrease to almost 400 million individuals by 2030 from nearly 430 million in 2023, despite the continent currently having the highest population growth rate globally. African economic growth and prosperity In recent years, Africa showed significant growth in various industries, such as natural gas production, clean energy generation, and services exports. Furthermore, it is forecast that the GDP growth rate would reach 4.5 percent by 2027, keeping the overall positive trend of economic growth in the continent.

  7. S

    South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods...

    • ceicdata.com
    Updated May 15, 2018
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    South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific [Dataset]. https://www.ceicdata.com/en/south-africa/imports/za-imports-low-and-middleincome-economies--of-total-goods-imports-east-asia--pacific
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    Dataset updated
    May 15, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    South Africa
    Variables measured
    Merchandise Trade
    Description

    South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data was reported at 24.753 % in 2016. This records an increase from the previous number of 24.300 % for 2015. South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data is updated yearly, averaging 14.386 % from Dec 1998 (Median) to 2016, with 19 observations. The data reached an all-time high of 24.753 % in 2016 and a record low of 5.339 % in 1998. South Africa ZA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific 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: Imports. Merchandise imports from low- and middle-income economies in East Asia and Pacific are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the East Asia and Pacific region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

  8. T

    South Africa - Merchandise Exports To Developing Economies In Middle East &...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 2, 2017
    + more versions
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    TRADING ECONOMICS (2017). South Africa - Merchandise Exports To Developing Economies In Middle East & North Africa (% Of Total Merchandise Exports) [Dataset]. https://tradingeconomics.com/south-africa/merchandise-exports-to-developing-economies-in-middle-east--north-africa-percent-of-total-merchandise-exports-wb-data.html
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    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    Jun 2, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    South Africa
    Description

    Merchandise exports to low- and middle-income economies in Middle East & North Africa (% of total merchandise exports) in South Africa was reported at 0.35979 % in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Merchandise exports to developing economies in Middle East & North Africa (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

  9. Annual poverty rate in Southern Africa 2023, by country and income level

    • statista.com
    Updated Feb 21, 2025
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    Statista (2025). Annual poverty rate in Southern Africa 2023, by country and income level [Dataset]. https://www.statista.com/statistics/1551703/southern-africa-poverty-rate-by-country-and-income-level/
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    Dataset updated
    Feb 21, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Africa
    Description

    In 2023, the international poverty (based on 2017 purchasing power parities (PPPs)) and the lower-income poverty rate (3.65 U.S. dollars in 2017 PPP), was highest for Mozambique within the Southern Africa region, with 74.7 percent and 88.7 percent, respectively. However, the upper middle-income poverty rate was highest for Zambia, at 93 percent.

  10. South Africa ZA: Income Share Held by Second 20%

    • ceicdata.com
    Updated May 15, 2018
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    CEICdata.com (2018). South Africa ZA: Income Share Held by Second 20% [Dataset]. https://www.ceicdata.com/en/south-africa/poverty/za-income-share-held-by-second-20
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    Dataset updated
    May 15, 2018
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1993 - Dec 1, 2014
    Area covered
    South Africa
    Description

    South Africa ZA: Income Share Held by Second 20% data was reported at 4.800 % in 2014. This records an increase from the previous number of 4.700 % for 2010. South Africa ZA: Income Share Held by Second 20% data is updated yearly, averaging 4.900 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 5.600 % in 2000 and a record low of 4.700 % in 2010. South Africa ZA: Income Share Held by Second 20% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

  11. S

    South Africa ZA: Income Share Held by Highest 10%

    • ceicdata.com
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    CEICdata.com, South Africa ZA: Income Share Held by Highest 10% [Dataset]. https://www.ceicdata.com/en/south-africa/poverty/za-income-share-held-by-highest-10
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    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1993 - Dec 1, 2014
    Area covered
    South Africa
    Description

    South Africa ZA: Income Share Held by Highest 10% data was reported at 50.500 % in 2014. This records a decrease from the previous number of 51.300 % for 2010. South Africa ZA: Income Share Held by Highest 10% data is updated yearly, averaging 50.500 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 54.200 % in 2005 and a record low of 44.900 % in 2000. South Africa ZA: Income Share Held by Highest 10% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

  12. S

    South Africa ZA: Income Share Held by Lowest 10%

    • ceicdata.com
    Updated Mar 15, 2023
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    CEICdata.com (2023). South Africa ZA: Income Share Held by Lowest 10% [Dataset]. https://www.ceicdata.com/en/south-africa/poverty/za-income-share-held-by-lowest-10
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    Dataset updated
    Mar 15, 2023
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1993 - Dec 1, 2014
    Area covered
    South Africa
    Description

    South Africa ZA: Income Share Held by Lowest 10% data was reported at 0.900 % in 2014. This stayed constant from the previous number of 0.900 % for 2010. South Africa ZA: Income Share Held by Lowest 10% data is updated yearly, averaging 1.000 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 1.300 % in 2000 and a record low of 0.900 % in 2014. South Africa ZA: Income Share Held by Lowest 10% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

  13. T

    South Africa - Merchandise Exports To Developing Economies In Europe &...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 29, 2017
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    TRADING ECONOMICS (2017). South Africa - Merchandise Exports To Developing Economies In Europe & Central Asia (% Of Total Merchandise Exports) [Dataset]. https://tradingeconomics.com/south-africa/merchandise-exports-to-developing-economies-in-europe--central-asia-percent-of-total-merchandise-exports-wb-data.html
    Explore at:
    excel, json, csv, xmlAvailable download formats
    Dataset updated
    May 29, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    South Africa
    Description

    Merchandise exports to low- and middle-income economies in Europe & Central Asia (% of total merchandise exports) in South Africa was reported at 0.52772 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Merchandise exports to developing economies in Europe & Central Asia (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

  14. c

    The formal processes of inheritance in Johannesburg, South Africa 1900-2019

    • datacatalogue.cessda.eu
    Updated Mar 3, 2025
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    Bolt, M (2025). The formal processes of inheritance in Johannesburg, South Africa 1900-2019 [Dataset]. http://doi.org/10.5255/UKDA-SN-853806
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    Dataset updated
    Mar 3, 2025
    Dataset provided by
    University of Birmingham
    Authors
    Bolt, M
    Time period covered
    Jan 1, 2016 - Mar 11, 2019
    Area covered
    South Africa
    Variables measured
    Individual, Organization, Family, Household, Event/process, Text unit
    Measurement technique
    I conducted extensive ethnographic research within Johannesburg's inheritance system. This involved shadowing officials across different parts of the administration of deceased estates, and related expert practitioners. It involved sitting in on legal advice consultations held within on the site of government administration and in the offices of legal NGO ProBono.Org. It involved attending court hearings, in Johannesburg's the High Court and Magistrate's Court. It meant interviewing state and civil-society employees, as well people encountering the system as members of the public, both via processes of snowball sampling emerging out of research in the deceased estates process. Finally, with the benefit of ethnographic insight into the composition of deceased estates files, I conducted archival research to capture a large sample of files over Johannesburg's history and aggregate metrics such as regarding wealth accumulation, wealth transfer and kinship.
    Description

    This dataset results from an anthropological project investigating how will-making and the formal processes of inheritance shape the passing on of property and the making of socio-economic class in Johannesburg, South Africa. While the number of people making wills is rising, and will-making is a key focus of attempts to shape citizens as legally aware individual decision-makers, most people die intestate. Appeals to state processes have popular appeal as ways to seek official protection, despite popular awareness of limited state capacity. Family dynamics are often better enforced than the law. In post-apartheid South Africa, ending segregation meant including everyone in the same legal code, but this often enshrined the norms of the white elite. Intestate succession is seen as profound injustice because it prioritises nuclear family over kin group, and asset over patrimony, even as custom norms are often used to justify male control and marginalise widows. This is made more complicated by patchy regulation and enforcement. People’s unequal abilities to navigate the system, and even manipulate it, become central determinants of who benefits and whose version of kinship is counted. I conducted extensive ethnographic research within this system, shadowing officials and other expert practitioners; sitting in on legal advice consultations; attending court hearings; interviewing state and civil-society employees, as well people encountering the system as members of the public. This was complemented by archival research to enable the analysis of information in deceased estates files across time. The dataset consists of 1) anonymized example case studies from key Johannesburg Institutions – the Master’s Office (where deceased estates are processed), the High Court, the Magistrate’s Court, legal clinics – and from interviews with practitioners and members of the public; 2) an Excel database aggregating information about inheritance from around 500 deceased estates files over Johannesburg's history, along with an illustrative example of a deceased estates file and a document showing and explaining features of the original MS Access database.

    Since the end of apartheid, South Africa's black middle class has grown exponentially, as a new stratum of black citizens has moved into government and corporate employment. As more South Africans accumulate substantial property, its disbursement becomes a new terrain on which battles of kinship obligation are fought. This project approaches class reproduction through an ethnographic focus on wills and testaments: the processes through which they are made, and the disputes surrounding their execution. The result is an innovative lens that attends to the role of experts and bureaucrats in shaping the dynamics of class. It extends my interest in class reproduction, explored in my forthcoming book (CUP 2015) based on fieldwork in South Africa since 2006. In South Africa, as the post-apartheid black middle class ages and considers family futures, the project is especially timely. The project addresses key anthropological concerns. It combines political-economic (inequality) and cultural (lifestyle) perspectives on the middle class, and these with scholarship on state institutions. And it extends existing work on class and status reproduction by transcending generations. How do black middle-class South Africans pass on the property that shapes their kin's status and life chances? As will-making is promoted ever more widely, how do institutions that facilitate it inflect experiences of kinship and property before death forces the issue? How does this compare with the established white middle class? Within families, how are competing definitions of ownership, rights and entitlements judged? When expressions of future plans also become expressions of state regulation, how does this affect access to family property (e.g. township houses)? Who is included and excluded, in the bottleneck of bureaucracy and legal process? How and why are particular possessions valued? How are people's roles and entitlements constituted in the process? Amidst increasing inequality and precarity, how is will-making talked about? How have concerns about property and inheritance been reflected in the media? Given the South African black middle class's diverse history, how does will-making today compare with the past? Examining class reproduction over time means combining ethnographic and historical methods. For the former, I will begin with long-term observation in the Johannesburg High Court where disputes around wills are heard, and trace cases out from the formal probate process to fieldwork with individuals and families. Meanwhile, I will work with will consultants and lawyers, and interview judges, members of financial organisations, and the experts responsible for designing their online will templates. The former Dean of Law at Wits University (where I am a Research Associate) has expressed...

  15. c

    Explaining Population Trends in Cardiovascular Risk: South Africa and...

    • datacatalogue.cessda.eu
    • beta.ukdataservice.ac.uk
    Updated Mar 26, 2025
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    Adjaye-Gbewonyo, K; Cois, A (2025). Explaining Population Trends in Cardiovascular Risk: South Africa and England, 1998-2017 [Dataset]. http://doi.org/10.5255/UKDA-SN-857400
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    Dataset updated
    Mar 26, 2025
    Dataset provided by
    South African Medical Research Council
    University of Greenwich
    Authors
    Adjaye-Gbewonyo, K; Cois, A
    Area covered
    England, South Africa
    Variables measured
    Individual
    Measurement technique
    Data for South Africa were drawn from 11 nationally representative surveys that collected information on non-communicable diseases and risk factors and included blood pressure readings and anthropometric measurements. These include the three iterations of the South African Demographic and Health Survey (DHS), the five waves of the National Income Dynamics Study (NIDS) and the South African National Health and Nutrition Examination Survey (SANHANES), and the two waves of the Study on Global Ageing and Adult Health (SAGE). Together, the 11 surveys provided data for the period 1998 to 2017 covering nearly 156,000 individuals aged 15 years and older.Data for England come from 17 annual Health Surveys for England (HSE) conducted during the 20-year period spanning 1998 to 2017. These data cover over 168,000 individuals aged 16+ years, representing England’s adult population.
    Description

    The project, based at the University of Greenwich, UK and Stellenbosch University, South Africa, aimed to examine epidemiologic transitions by identifying and quantifying the drivers of change in CVD risk in the middle-income country of South Africa compared to the high-income nation of England. The project produced a harmonised dataset of national surveys measuring CVD risk factors in South Africa and England for others to use in future work. The harmonised dataset includes microdata from nationally-representative surveys in South Africa derived from the Demographic and Health Surveys, National Income Dynamics Study, South Africa National Health and Nutrition Examination Survey and Study on Global Ageing and Adult Health, covering 11 cross-sections and approximately 156,000 individuals aged 15+ years, representing South Africa’s adult population from 1998 to 2017.

    Data for England come from 17 Health Surveys for England (HSE) over the same time period, covering over 168,000 individuals aged 16+ years, representing England’s adult population.

    This study uses existing data to identify drivers of recent health transitions in South Africa compared to England. The global burden of non-communicable diseases (NCDs) on health is increasing. Cardiovascular diseases (CVD) in particular are the leading causes of death globally and often share characteristics with many major NCDs. Namely, they tend to increase with age and are influenced by behavioural factors such as diet, exercise and smoking. Risk factors for CVD are routinely measured in population surveys and thus provide an opportunity to study health transitions. Understanding the drivers of health transitions in countries that have not followed expected paths (eg, South Africa) compared to those that exemplified models of 'epidemiologic transition' (eg, England) can generate knowledge on where resources may best be directed to reduce the burden of disease. In the middle-income country of South Africa, CVD is the second leading cause of death after HIV/AIDS and tuberculosis (TB). Moreover, many of the known risk factors for NCDs like CVD are highly prevalent. Rates of hypertension are high, with recent estimates suggesting that over 40% of adults have high blood pressure. Around 60% of women and 30% of men over 15 are overweight in South Africa. In addition, excessive alcohol consumption, a risk factor for many chronic diseases, is high, with over 30% of men aged 15 and older having engaged in heavy episodic drinking within a 30-day period. Nevertheless, infectious diseases such as HIV/AIDS remain the leading cause of death, though many with HIV/AIDS and TB also have NCDs. In high-income countries like England, by contrast, NCDs such as CVD have been the leading causes of death since the mid-1900s. However, CVD and risk factors such as hypertension have been declining in recent decades due to increased prevention and treatment. The major drivers of change in disease burden have been attributed to factors including ageing, improved living standards, urbanisation, lifestyle change, and reduced infectious disease. Together, these changes are often referred to as the epidemiologic transition. However, recent research has questioned whether epidemiologic transition theory accurately describes the experience of many low- and middle-income countries or, in fact, of high-income nations such as England. Furthermore, few studies have empirically tested the relative contributions of demographic, behavioural, health and economic factors to trends in disease burden and risk, particularly on the African continent. In addition, many social and environmental factors are overlooked in this research. To address these gaps, our study will use population measurements of CVD risk derived from surveys in South Africa over nearly 20 years in order to examine whether and to what extent demographic, behavioural, environmental, medical, social and other factors contribute to recent health trends and transitions. We will compare these trends to those occurring in England over the same time period. Thus, this analysis seeks to illuminate the drivers of health transitions in a country which is assumed to still be 'transitioning' to a chronic disease profile but which continues to have a high infectious disease burden (South Africa) as compared to a country which is assumed to have already transitioned following epidemiological transition theory (England). The analysis will employ modelling techniques on pooled cross-sectional data to examine how various factors explain the variation in CVD risk over time in representative population samples from South Africa and England. The results of this analysis may help to identify some of the main contributors to recent changes in CVD risk in South Africa and England. Such information can be used to pinpoint potential areas for intervention, such as social policy and services, thereby helping to set priorities for governmental and...

  16. A scoping review exploring vocational rehabilitation interventions for...

    • zenodo.org
    bin, txt
    Updated Jun 5, 2022
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    Munyaradzi Chimara; Munyaradzi Chimara; Lana van Niekerk; Hester Maria van Biljon; Lana van Niekerk; Hester Maria van Biljon (2022). A scoping review exploring vocational rehabilitation interventions for mental health service users with chronic mental illness in low-income to upper-middle-income countries [Dataset]. http://doi.org/10.5061/dryad.0p2ngf23t
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    txt, binAvailable download formats
    Dataset updated
    Jun 5, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Munyaradzi Chimara; Munyaradzi Chimara; Lana van Niekerk; Hester Maria van Biljon; Lana van Niekerk; Hester Maria van Biljon
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Objective

    To synthesize research published on vocational rehabilitation (VR) interventions offered in institutions, by occupational therapists, to mental health service users (MHSUs) with chronic mental illness, in low-income to upper middle-income countries (L-UMIC).

    Design

    This scoping review used Arksey and O'Malley's methodological framework, the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) and Joanna Briggs scoping review guidelines.

    Data Sources

    We searched PsycInfo, EBSCOhost, HINARI, Google scholar, Medline, CINAHL, PubMed, Cochrane Library, Scopus, Science Direct and Wiley online library between 15 July and 31 August 2021.

    Eligibility Criteria

    Sources, published in English between 2011 and 2021, on institution-based VR in occupational therapy for MHSUs who had chronic mental illness in L-UMIC were included. We included primary studies of any design.

    Data extraction and synthesis

    Three reviewers used Mendeley to manage identified references, Rayyan for abstract and full text screening, and Microsoft Excel for data extraction. Data was sifted and sorted by key categories and themes.

    Results

    895 sources were identified, and their title and abstracts reviewed. 207 sources were included for full text screening. 12 articles from 4 countries (South Africa, India, Brazil & Kenya) were finally included. Types of VR intervention included supported employment, case management and prevocational skills training. Client centeredness, support and empowerment were the key VR principles identified. Teaching of illness self-management, job analysis and matching, job coaching, trial placement, and vocational guidance and counseling, were the main intervention strategies reported.

    Conclusions

    VR intervention in institutions for MHSUs in L-UMIC revealed the multidimensional uniqueness of individual MHSU's vocational ability, needs and contexts. The interventions allowed client-centered approaches that offer support, and empowerment beyond the boundaries of the institutions. Occupational therapists offering VR need to expand their interventions beyond their institutions to contexts where MHSUs are working or intending to work.

  17. Average price of avocados on markets in South Africa 2000-2019

    • statista.com
    Updated Apr 26, 2023
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    Statista (2023). Average price of avocados on markets in South Africa 2000-2019 [Dataset]. https://www.statista.com/statistics/1154816/sales-price-of-avocados-on-markets-in-south-africa/
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    Dataset updated
    Apr 26, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    South Africa
    Description

    As of 2018/2019, the average sales price for avocados on markets in South Africa was at 10,755 South African Rands per metric ton (roughly 658 U.S. dollars per metric ton), a decline in comparison to previous year. A general increasing trend can be recognized between 2000 and 2019, with several slight dips. Moreover, the upward tendency may be related to the growth of the middle class in South Africa, along with the higher income groups willing to pay more for products with value addition. Comprehensive promotions on the emphasis on eating healthy have probably also caused demand for avocados to increase.

  18. T

    South Sudan - Merchandise Exports To Developing Economies In Sub-Saharan...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Feb 5, 2020
    + more versions
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    TRADING ECONOMICS (2020). South Sudan - Merchandise Exports To Developing Economies In Sub-Saharan Africa (% Of Total Merchandise Exports) [Dataset]. https://tradingeconomics.com/south-sudan/merchandise-exports-to-developing-economies-in-sub-saharan-africa-percent-of-total-merchandise-exports-wb-data.html
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Feb 5, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    South Sudan
    Description

    Merchandise exports to low- and middle-income economies in Sub-Saharan Africa (% of total merchandise exports) in South Sudan was reported at 0.11094 % in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Sudan - Merchandise exports to developing economies in Sub-Saharan Africa (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

  19. f

    Table_3_Training a Fit-For-Purpose Rural Health Workforce for Low- and...

    • figshare.com
    bin
    Updated Jun 5, 2023
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    Karen Johnston; Monsie Guingona; Salwa Elsanousi; Jabu Mbokazi; Charlie Labarda; Fortunato L. Cristobal; Shambhu Upadhyay; Abu-Bakr Othman; Torres Woolley; Balkrishna Acharya; John C. Hogenbirk; Sarangan Ketheesan; Jonathan C. Craig; Andre-Jacques Neusy; Sarah Larkins (2023). Table_3_Training a Fit-For-Purpose Rural Health Workforce for Low- and Middle-Income Countries (LMICs): How Do Drivers and Enablers of Rural Practice Intention Differ Between Learners From LMICs and High Income Countries?.docx [Dataset]. http://doi.org/10.3389/fpubh.2020.582464.s003
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    Frontiers
    Authors
    Karen Johnston; Monsie Guingona; Salwa Elsanousi; Jabu Mbokazi; Charlie Labarda; Fortunato L. Cristobal; Shambhu Upadhyay; Abu-Bakr Othman; Torres Woolley; Balkrishna Acharya; John C. Hogenbirk; Sarangan Ketheesan; Jonathan C. Craig; Andre-Jacques Neusy; Sarah Larkins
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Equity in health outcomes for rural and remote populations in low- and middle-income countries (LMICs) is limited by a range of socio-economic, cultural and environmental determinants of health. Health professional education that is sensitive to local population needs and that attends to all elements of the rural pathway is vital to increase the proportion of the health workforce that practices in underserved rural and remote areas. The Training for Health Equity Network (THEnet) is a community-of-practice of 13 health professional education institutions with a focus on delivering socially accountable education to produce a fit-for-purpose health workforce. The THEnet Graduate Outcome Study is an international prospective cohort study with more than 6,000 learners from nine health professional schools in seven countries (including four LMICs; the Philippines, Sudan, South Africa and Nepal). Surveys of learners are administered at entry to and exit from medical school, and at years 1, 4, 7, and 10 thereafter. The association of learners' intention to practice in rural and other underserved areas, and a range of individual and institutional level variables at two time points—entry to and exit from the medical program, are examined and compared between country income settings. These findings are then triangulated with a sociocultural exploration of the structural relationships between educational and health service delivery ministries in each setting, status of postgraduate training for primary care, and current policy settings. This analysis confirmed the association of rural background with intention to practice in rural areas at both entry and exit. Intention to work abroad was greater for learners at entry, with a significant shift to an intention to work in-country for learners with entry and exit data. Learners at exit were more likely to intend a career in generalist disciplines than those at entry however lack of health policy and unclear career pathways limits the effectiveness of educational strategies in LMICs. This multi-national study of learners from medical schools with a social accountability mandate confirms that it is possible to produce a health workforce with a strong intent to practice in rural areas through attention to all aspects of the rural pathway.

  20. T

    South Sudan - Merchandise Exports To Developing Economies In Middle East &...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 6, 2020
    + more versions
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    TRADING ECONOMICS (2020). South Sudan - Merchandise Exports To Developing Economies In Middle East & North Africa (% Of Total Merchandise Exports) [Dataset]. https://tradingeconomics.com/south-sudan/merchandise-exports-to-developing-economies-in-middle-east--north-africa-percent-of-total-merchandise-exports-wb-data.html
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Mar 6, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    South Sudan
    Description

    Merchandise exports to low- and middle-income economies in Middle East & North Africa (% of total merchandise exports) in South Sudan was reported at 0.06035 % in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Sudan - Merchandise exports to developing economies in Middle East & North Africa (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

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Statista (2025). Forecast of the global middle class population 2015-2030 [Dataset]. https://www.statista.com/statistics/255591/forecast-on-the-worldwide-middle-class-population-by-region/
Organization logo

Forecast of the global middle class population 2015-2030

Explore at:
10 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jan 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2017
Area covered
World
Description

By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 million in 2030.

Worldwide wealth

While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent of non-investable assets.

The middle-class

The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth to the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle-class.

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