Seychelles had the largest Gross Domestic Product (GDP) per capita in Africa as of 2024. The value amounted to 21,630 U.S. dollars. Mauritius followed with around 12,330 U.S. dollars, whereas Gabon registered 8,840 U.S. dollars. GDP per capita is calculated by dividing a country’s GDP by its population, meaning that some of the largest economies are not ranked within the leading ten. Impact of COVID-19 on North Africa’s GDP When looking at the GDP growth rate in Africa in 2024, Libya had the largest estimated growth in Northern Africa, a value of 7.8 percent compared to the previous year. Niger and Senegal were at the top of the list with rates of 10.4 percent and 8.3 percent, respectively. During the COVID-19 pandemic, the impact on the economy was severe. The growth of the North African real GDP was estimated at minus 1.1 percent in 2020. However, estimations for 2022 looked much brighter, as it was set that the region would see a GDP growth of six percent, compared to four percent in 2021.
Contribution of Tourism Various countries in Africa are dependent on tourism, contributing to the economy. In 2023, travel and tourism were estimated to contribute 182.6 billion U.S. dollars, a clear increase from 96.5 in 2020 following COVID-19. As of 2024, South Africa, Mauritius, and Egypt led tourism in the continent according to the Travel & Tourism Development Index.

South Africa ZA: Income Share Held by Lowest 20% data was reported at 2.400 % in 2014. This records a decrease from the previous number of 2.500 % for 2010. South Africa ZA: Income Share Held by Lowest 20% data is updated yearly, averaging 2.600 % from Dec 1993 (Median) to 2014, with 7 observations. The data reached an all-time high of 3.100 % in 2000 and a record low of 2.400 % in 2014. South Africa ZA: Income Share Held by Lowest 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.

According to the latest governmental data from 2019, the Gini coefficient in South Africa was 0.65 points in 2015, with lesser inequality in income within the rural areas of the most southern country of Africa. The Gini index gives information on the distribution of income in a country. In an ideal situation in which incomes are perfectly distributed, the coefficient is equal to zero, whereas one represents the highest inequality situation.

South Africa had the world's highest inequality in income distribution. Furthermore, the first eight countries on the ranking are located in Sub-Saharan Africa, with an index over 50 points.

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.

In 2020, the total income in the agriculture and related services industry in South Africa amounted to almost 371 billion South African rand (around 23.62 billion U.S. dollars). Animals and animal products were the most lucrative product type with, nearly 152 billion South African rand (roughly 9.68 billion U.S. dollars). Horticultural crops and products followed at over 91 billion South African rand (some 5.79 billion U.S. dollars).

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.

In 2021, the total income from animals and animal products in South Africa reached over 159 billion South African rand (around 8.33 billion U.S. dollars). Compared to the previous year, this was an increase of 5.1 percent. Generally, the income earned from animals increased during the period reviewed. Overall, animals and products thereof generated the highest income in the agriculture and related services industry.

Introduction/objectivesMore than half of South Africa’s population lives in poverty, with significant health disparities across different regions. This study investigates the effects of regional poverty and historical economic factors on the efficacy of public health expenditure to understand how socioeconomic contexts influence overall public health outcomes.MethodsOur study utilized annual data from 2005 to 2019 for 9 provinces, drawing from the General Household Survey, Health Systems Trust database, and National Treasury’s Intergovernmental Fiscal Review. The primary health outcome was life expectancy at birth, while public health expenditure per capita was the main independent variable. We developed the Provincial Index of Multiple Deprivation to assess poverty, incorporating dimensions such as health, education, and living standards. We employed a two-way fixed effects model to examine the complex relationships between regional poverty, public health spending, and health outcomes.ResultsThe study found that poverty levels moderate the impact of public health spending on health outcomes, as evidenced by varying results across different provincial regions. Health outcomes in poorer provinces were less influenced by public health spending than wealthier regions. Additionally, the study established that income per capita, along with its lagged values and the lagged values of public health expenditure per capita, did not significantly affect health outcomes as measured by life expectancy.Conclusion/recommendationsThe impact of health expenditure in South Africa is influenced by regional poverty levels. To maximize the effectiveness of health spending, equitable, region-specific interventions tailored to address the unique health challenges of each area should be implemented.

Merchandise exports to low- and middle-income economies within region (% of total merchandise exports) in South Africa was reported at 28.31 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Merchandise exports to developing economies within region (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

Abstract

A comprehensive survey was conducted by Central Statistical Service (later Statistics South Africa) in October 1995 in order to determine the income and expenditure of households in South Africa. This survey shows the earnings and spendings of South African households and the pattern of household consumption. The survey covered the metropolitan, urban and rural areas of South Africa. The main purpose of the survey was to determine the average expenditure patterns of households in the different areas concerned. This survey forms the basis for the determination of the "basket" of consumer goods and services used for the calculation of the Consumer Price Index.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the survey includes households

Universe

The 1995 IES differed from previous household surveys of its kind in South Africa, since it was a countrywide survey covering metro, urban and rural areas, rather than a more limited sub-set of households in 12 major metro/urban areas of the country previously referred to. By extending the sample to include the whole country, a clearer indication of the life circumstances of all South Africans in all parts of the country could be inferred.

Kind of data

Sample survey data [ssd]

Sampling procedure

Two surveys, namely the CSS's annual October household survey (OHS) and the IES were run concurrently during October 1995. Information for the IES was obtained, as far as possible, from the same 30 000 households that were visited for the 1995 OHS. Altogether, 3 000 enumerator areas (EAs) were drawn for the sample, and ten households were visited in each EA. The sample was stratified by race, province, urban and non-urban area. The 1991 population census was used as a frame for drawing the sample, including estimates of the size of the population in the formerly independent TBVC (Transkei-Bophuthatswana-Venda-Ciskei) states.

More details on the sampling frame and sampling procedure are given in the report on the 1995 OHS, Living in South Africa (CSS, 1996).

Mode of data collection

Face-to-face [f2f]

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.

Abstract

A comprehensive survey was conducted by Central Statistical Service (later Statistics South Africa) in October 1995 in order to determine the income and expenditure of households in South Africa. This survey shows the earnings and spendings of South African households and the pattern of household consumption. The survey covered the metropolitan, urban and rural areas of South Africa. The main purpose of the survey was to determine the average expenditure patterns of households in the different areas concerned. This survey forms the basis for the determination of the "basket" of consumer goods and services used for the calculation of the Consumer Price Index. The 1995 IES differed from previous household surveys of its kind in South Africa, since it was a countrywide survey covering metro, urban and rural areas, rather than a more limited sub-set of households in 12 major metro/urban areas of the country covered by the 1990 IES.

Geographic coverage

The survey had national coverage

Analysis unit

Households and individuals

Universe

The 1995 IES differed from previous household surveys of its kind in South Africa, since it was a countrywide survey covering metro, urban and rural areas, rather than a more limited sub-set of households in 12 major metro/urban areas of the country previously referred to. By extending the sample to include the whole country, a clearer indication of the life circumstances of all South Africans in all parts of the country could be inferred.

Kind of data

Sample survey data

Sampling procedure

Two surveys, namely the CSS’s annual October household survey (OHS) and the IES were run concurrently during October 1995. Information for the IES was obtained, as far as possible, from the same 30 000 households that were visited for the 1995 OHS. Altogether, 3 000 enumerator areas (EAs) were drawn for the sample, and ten households were visited in each EA. The sample was stratified by race, province, urban and non-urban area. The 1991 population census was used as a frame for drawing the sample, including estimates of the size of the population in the formerly independent TBVC (Transkei-Bophuthatswana-Venda-Ciskei) states. More details on the sampling frame and sampling procedure are given in the report on the 1995 OHS, Living in South Africa (CSS, 1996).

Mode of data collection

Face-to-face [f2f]

In 2021, Southern Africa's richest ** percent held around ** percent of the total wealth. Furthermore, the richest one percent in the region held over ** percent. The other African regions had a slightly smaller share of wealth with the wealthiest people. For instance, in West Africa, the richest ** percent held close to ** percent of the wealth, while the richest one percent held ** percent. On the other hand. The poorest ** percent in all the regions held lower than ***** percent of the wealth.

Since 1970, net national incomes per capita have grown in each region of the world. North America has experienced the largest increase, growing from nearly 4,500 U.S. dollars per capita in 1970 to $57,300 per capita in 2021. Europe and Central Asia follow behind North America, growing from 1,200 dollars per capita in 1970 to 22,000 in 2021. Other regions such as Sub-Saharan Africa, the Middle East and North Africa, Latin America and the Caribbean, and South Asia have not grown as high, but their growth is still significant, with net national incomes per capita in 2021 growing to between 10 and 20 times their 1970 levels.

South Africa ZA: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data was reported at 19.476 % in 2016. This records an increase from the previous number of 19.079 % for 2015. South Africa ZA: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data is updated yearly, averaging 3.590 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 21.869 % in 2013 and a record low of 0.810 % in 1967. South Africa ZA: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region 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: Exports. Merchandise exports to low- and middle-income economies outside region are the sum of merchandise exports from the reporting economy to other low- and middle-income economies in other World Bank regions according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise exports 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;

Abstract

The National Income Dynamics Study (NIDS) is a face-to-face longitudinal survey of individuals living in South Africa as well as their households. The survey was designed to give effect to the dimensions of the well-being of South Africans, to be tracked over time. At the broadest level, these were: Wealth creation in terms of income and expenditure dynamics and asset endowments; Demographic dynamics as these relate to household composition and migration; Social heritage, including education and employment dynamics, the impact of life events (including positive and negative shocks), social capital and intergenerational developments;
Access to cash transfers and social services.

Dates: 2008 – ongoing. First 5 “waves” implemented by SALDRU.

Funding: The Presidency (2008 – 2013); The Department of Planning, Monitoring and Evaluation (2014 – Present).

SALDRU people: Murray Leibbrandt, Ingrid Woolard, Cecil Mlatsheni and Reza C. Daniels.

Coverage: Nationally representative of the South African population.

Initial Sample size (2008): Approximately 28 000 individuals.

Data: The survey’s questionnaires, technical documents and reports for Wave 1, Wave 2, Wave 3, Wave 4 and Wave 5 are available for download from DataFirst’s Open Data Portal. NIDS produces public release data, which is also available for download from DataFirst’s Open Data Portal and secure data, which can only be accessed through DataFirst’s Secure Research Data Centre.

Included sections: Household Living Standards; Household Composition and Structure; Mortality; Household Food and Non-food Spending and Consumption; Household Durable Goods, Household Net Assets; Agriculture; Demographics; Birth Histories and Children; Parents and Family Support; Labour Market Participation and Economic Activity; Income and Expenditure; Grants; Contributions Given and Received; Education; Health; Emotional Health; Household Decision-making; Wellbeing and Social Cohesion; Anthropometric Measurements; Personal Ownership and Debt.

Geographic coverage

The NIDS data is nationally representative. The survey began in 2008 with a nationally representative sample of over 28,000 individuals in 7,300 households across the country. The survey is repeated every two years with these same household members, who are called Continuing Sample Members (CSMs). The survey is designed to follow people who are CSMs, wherever they may be in SA at the time of interview. The NIDS data is therefore, by design, not representative provincially or at a lower level of geography (e.g. District Council).

Analysis unit

Households and individuals

Universe

The target population for NIDS was private households in all nine provinces of South Africa, and residents in workers' hostels, convents and monasteries. The frame excludes other collective living quarters, such as student hostels, old age homes, hospitals, prisons and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

NIDS is a national panel (longitudinal) survey which began with a sample of 28 000 South Africans. NIDS' cycles of data collection, referred to as "waves" were undertaken. In Wave 1 (2008), 400 Enumerator Areas, comprising of 7296 households were selected for inclusion in the NIDS sample. 300 fieldworkers spread out across all nine provinces of the country in search of the 28 226 people that formed part of these selected households; successfully interviewing 26 776 of these individuals during Wave 1.

In subsequent waves, the original sample members are tracked and re-interviewed. Anyone that they live with at the time is also interviewed. In Wave 2 (2010-2011) 28 537 individuals were interviewed; in Wave 3 (2012) 32 582 were interviewed; and in Wave 4 (2014-2015) 37 368 were interviewed. Data collection for Wave 5 took place in 2017 and included a sample "top-up" to increase the number of white, Indian and high income respondents who had experienced low baseline response rates in Wave 1 and higher attrition rates between Waves 1-4. During Wave 5, 39,434 individuals were successfully interviewed, of which, 2016 were from the "top-up" sample. The data for Wave 5 was released at the end of August 2018.

More information on NIDS sampling refer to NIDS Technical Paper Number 1 http://www.nids.uct.ac.za/publications/technical-papers/108-nids-technical-paper-no1/file

Mode of data collection

Face-to-face [f2f]

Abstract

In 1990 the Central Statistical Service of South Africa sponsored a household expenditure survey in a sub-set of households in 12 major metro/urban areas in the country. The aim of the survey was to obtain data on income and expenditure patterns of South African households on which the Consumer Price Index (CPS) and various other economic indicators could be based. The survey was conducted by Markdata, the fieldwork arm of the Human Sciences Research Council (HSRC). All population groups were enumerated but this dataset does not contain data files for the "white" population group.

Geographic coverage

The IES 1990 only collected data on expenditure from the 12 largest urban areas in the country, leaving out buying patters in small towns and rural areas. Areas enumerated were: Cape Peninsula, Port Elizabeth- Uitenhage, East London, Kimberley, Pietermaritz burg, Durban, Pretoria, Johannesburg, Witwatersrand (excl Jhb), Klerksdorp, Vaal Triangle, Orange Free State-Gold Fields, Bloemfontein.

Analysis unit

Households and individuals

Universe

The survey covered all household members in the selected areas

Kind of data

Sample survey data

Mode of data collection

Face-to-face [f2f]

Research instrument

Two survey instruments were provided in the IES 1990: A detailed "long" questionnaire and a "short" questionnaire without detailed classification of expenditure items. The "short" questionnaire was completed by two out of three households enumerated. The "short" and "long" questionnaires are identified separately in the variable q_type. "Long" questionnaires are indicated as questionnaire = 1 and "short' questionnaires as questionnaire = 2.

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.

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.