The average monthly salary for South Africans who were employed in the formal non-agricultural sector was just over 26,800 South African rands (comparable to roughly 1,500 U.S. dollars) in November 2023, which represented a yearly increase of tw0 percent. During the period under review, the overall growth trend was positive, with the earnings increasing by 24.4 percent from 21,500 South African rands (approximately 1,180 U.S. dollars) in November 2018. Minimum wage and highest-paid professions Starting in March 2023, the minimum hourly wage in the country increased to 25.42 South African rands (comparable to 1.40 U.S. dollars), which represented an increase of 9.6 percent from 23.19 South African rands (1.27 U.S. dollars) per hour in the preceding year. On the other hand, professionals in executive and change management positions were paid the highest salaries in South Africa, with an average of 74,000 U.S. dollars yearly. Individuals with jobs in retail, trade, and craft followed, receiving an average of 66,000 U.S. dollars per annum. Highest unemployment among Black South Africans In 2022, the unemployment rate in South Africa was nearly 30 percent following an increasing trend since 2008. The rate was highest among Black South Africans reaching as high as 36.8 percent in the second quarter of 2023. Moreover, Colored South Africans followed with around 22 percent, while white South Africans had a much lower unemployment rate of over 7 percent.
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.
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.
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South Africa ZA: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 23.500 % in 2014. This stayed constant from the previous number of 23.500 % for 2010. South Africa ZA: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 23.500 % from Dec 1993 (Median) to 2014, with 6 observations. The data reached an all-time high of 25.500 % in 2000 and a record low of 20.300 % in 2005. South Africa ZA: Proportion of People Living Below 50 Percent Of Median Income: % 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: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).
The Income and Expenditure Survey is conducted every five years in South Africa.The main purpose of the survey is to determine the average expenditure patterns of households in different areas of the country. 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 survey had national coverage
Units of analysis in the survey are households
The survey covered private dwellings, workers' hostels, residential hotels, and nurses' and doctors' quarters, but excluded hospitals and clinics, hotels and guest houses, prisons, schools and student hostels and old-age homes.
Sample survey data [ssd]
The sampling frame for the IES 2010/2011 was obtained from Statistics South Africa’s Master Sample (MS) based on the 2001 Population Census enumeration areas (EAs). The scope of the Master Sample (MS) is national coverage of all households in South Africa and the target population consists of all qualifying persons and households in the country. In summary, it has been designed to cover all households living in private dwelling units and workers living in workers’ quarters in the country. The IES 2010/2011 sample is based on an extended sample of 3 254 PSUs, which consists of the 3 080 PSUs in the Master Sample and a supplement of 174 urban PSUs selected from the PSU frame. The IES sample file contained 31 419 sampled dwelling units (DUs). The 31 419 sampled DUs consist of 31 007 DUs sampled from the 3 080 design PSUs in the Master Sample and 412 DUs from the supplemented 174 urban PSUs. In the case of multiple households at a sampled DU, all households in the DU were included.
Face-to-face [f2f]
There were four modules in the household questionnaire with eighteen subsections. The first module collected general household data and data on household members. Modules 2 to 4 collected data on consumption expenditure, household finances and income. The diary was a booklet in which the respondent recorded weekly expenditure data. A household completed a different diary for each week of the survey period.
From the 31 419 dwelling units sampled across South Africa, 33 420 households were identified. Out of these, there was a sample realisation of 27 665 (82,8%) households, with the remaining 5 755 (17,2%) households being classified as out of scope.
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Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in South Tucson. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for South Tucson median household income by race. You can refer the same here
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South Africa Number of Households: Black African: by Income: Salaries, Wages or Commission data was reported at 8,288.000 Unit th in 2017. This records a decrease from the previous number of 8,595.000 Unit th for 2016. South Africa Number of Households: Black African: by Income: Salaries, Wages or Commission data is updated yearly, averaging 7,519.000 Unit th from Jul 2009 (Median) to 2017, with 9 observations. The data reached an all-time high of 8,595.000 Unit th in 2016 and a record low of 6,436.000 Unit th in 2009. South Africa Number of Households: Black African: by Income: Salaries, Wages or Commission data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.H007: Number of Households: by Income.
As of 2024, Morocco had the highest average monthly salaries in Africa. Employees in the country earned around 2,030 U.S. dollars per month. South Africa and Tunisia followed, with average monthly salaries amounting to 2,026 U.S. dollars and 1,348 U.S. dollars, respectively.
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Adjusted net national income per capita (annual % growth) in South Africa was reported at 5.2024 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Adjusted net national income per capita (annual % growth) - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.
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Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in South Coffeyville. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for South Coffeyville median household income by race. You can refer the same here
This map shows the purchasing power per capita in South Africa in 2023, in a multiscale map (Country, Province, District, Municipality, Main Place, Sub Place, and Small Area). Nationally, the purchasing power per capita is 62,579 South African rand. Purchasing Power describes the disposable income (income without taxes and social security contributions, including received transfer payments) of a certain area's population. The figures are in South African rand (ZAR) per capita.The pop-up is configured to show the following information at each geography level:Purchasing power per capitaPurchasing power per capita by various categoriesCount of households by income quintilesThe source of this data is Michael Bauer Research. The vintage of the data is 2023. This item was last updated in October, 2023 and is updated every 12-18 months as new annual figures are offered.Additional Esri Resources:Esri DemographicsThis item is for visualization purposes only and cannot be exported or used in analysis.We would love to hear from you. If you have any feedback regarding this item or Esri Demographics, please let us know.Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.
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South Africa Number of Households: Black African: by Income: Remittances data was reported at 2,343.000 Unit th in 2017. This records a decrease from the previous number of 2,476.000 Unit th for 2016. South Africa Number of Households: Black African: by Income: Remittances data is updated yearly, averaging 2,195.000 Unit th from Jul 2009 (Median) to 2017, with 9 observations. The data reached an all-time high of 2,574.000 Unit th in 2015 and a record low of 1,430.000 Unit th in 2012. South Africa Number of Households: Black African: by Income: Remittances data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.H007: Number of Households: by Income.
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Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in South Hanover township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for South Hanover township median household income by race. You can refer the same here
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South Africa Tourism Income: Total: Guest Houses and Farms data was reported at 124.200 ZAR mn in Aug 2018. This records an increase from the previous number of 112.000 ZAR mn for Jul 2018. South Africa Tourism Income: Total: Guest Houses and Farms data is updated monthly, averaging 101.100 ZAR mn from Sep 2004 (Median) to Aug 2018, with 168 observations. The data reached an all-time high of 238.800 ZAR mn in Dec 2017 and a record low of 16.300 ZAR mn in Jun 2005. South Africa Tourism Income: Total: Guest Houses and Farms data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.Q009: Tourism Income.
In 2023, the gross median household income for Asian households in the United States stood at 112,800 U.S. dollars. Median household income in the United States, of all racial and ethnic groups, came out to 80,610 U.S. dollars in 2023. Asian and Caucasian (white not Hispanic) households had relatively high median incomes, while the median income of Hispanic, Black, American Indian, and Alaskan Native households all came in lower than the national median. A number of related statistics illustrate further the current state of racial inequality in the United States. Unemployment is highest among Black or African American individuals in the U.S. with 8.6 percent unemployed, according to the Bureau of Labor Statistics in 2021. Hispanic individuals (of any race) were most likely to go without health insurance as of 2021, with 22.8 percent uninsured.
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South Africa Number of Households: Others: Male: by Income: Salaries, Wages or Commission data was reported at 1,568.000 Unit th in 2017. This records a decrease from the previous number of 1,572.000 Unit th for 2016. South Africa Number of Households: Others: Male: by Income: Salaries, Wages or Commission data is updated yearly, averaging 1,604.000 Unit th from Jul 2009 (Median) to 2017, with 9 observations. The data reached an all-time high of 1,802.000 Unit th in 2011 and a record low of 1,568.000 Unit th in 2017. South Africa Number of Households: Others: Male: by Income: Salaries, Wages or Commission data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.H007: Number of Households: by Income.
Goal 10Reduce inequality within and among countriesTarget 10.1: By 2030, progressively achieve and sustain income growth of the bottom 40 per cent of the population at a rate higher than the national averageIndicator 10.1.1: Growth rates of household expenditure or income per capita among the bottom 40 per cent of the population and the total populationSI_HEI_TOTL: Growth rates of household expenditure or income per capita (%)Target 10.2: By 2030, empower and promote the social, economic and political inclusion of all, irrespective of age, sex, disability, race, ethnicity, origin, religion or economic or other statusIndicator 10.2.1: Proportion of people living below 50 per cent of median income, by sex, age and persons with disabilitiesSI_POV_50MI: Proportion of people living below 50 percent of median income (%)Target 10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory laws, policies and practices and promoting appropriate legislation, policies and action in this regardIndicator 10.3.1: Proportion of population reporting having personally felt discriminated against or harassed in the previous 12 months on the basis of a ground of discrimination prohibited under international human rights lawVC_VOV_GDSD: Proportion of population reporting having felt discriminated against, by grounds of discrimination, sex and disability (%)Target 10.4: Adopt policies, especially fiscal, wage and social protection policies, and progressively achieve greater equalityIndicator 10.4.1: Labour share of GDPSL_EMP_GTOTL: Labour share of GDP (%)Indicator 10.4.2: Redistributive impact of fiscal policySI_DST_FISP: Redistributive impact of fiscal policy, Gini index (%)Target 10.5: Improve the regulation and monitoring of global financial markets and institutions and strengthen the implementation of such regulationsIndicator 10.5.1: Financial Soundness IndicatorsFI_FSI_FSANL: Non-performing loans to total gross loans (%)FI_FSI_FSERA: Return on assets (%)FI_FSI_FSKA: Regulatory capital to assets (%)FI_FSI_FSKNL: Non-performing loans net of provisions to capital (%)FI_FSI_FSKRTC: Regulatory Tier 1 capital to risk-weighted assets (%)FI_FSI_FSLS: Liquid assets to short term liabilities (%)FI_FSI_FSSNO: Net open position in foreign exchange to capital (%)Target 10.6: Ensure enhanced representation and voice for developing countries in decision-making in global international economic and financial institutions in order to deliver more effective, credible, accountable and legitimate institutionsIndicator 10.6.1: Proportion of members and voting rights of developing countries in international organizationsSG_INT_MBRDEV: Proportion of members of developing countries in international organizations, by organization (%)SG_INT_VRTDEV: Proportion of voting rights of developing countries in international organizations, by organization (%)Target 10.7: Facilitate orderly, safe, regular and responsible migration and mobility of people, including through the implementation of planned and well-managed migration policiesIndicator 10.7.1: Recruitment cost borne by employee as a proportion of monthly income earned in country of destinationIndicator 10.7.2: Number of countries with migration policies that facilitate orderly, safe, regular and responsible migration and mobility of peopleSG_CPA_MIGRP: Proportion of countries with migration policies to facilitate orderly, safe, regular and responsible migration and mobility of people, by policy domain (%)SG_CPA_MIGRS: Countries with migration policies to facilitate orderly, safe, regular and responsible migration and mobility of people, by policy domain (1 = Requires further progress; 2 = Partially meets; 3 = Meets; 4 = Fully meets)Indicator 10.7.3: Number of people who died or disappeared in the process of migration towards an international destinationiSM_DTH_MIGR: Total deaths and disappearances recorded during migration (number)Indicator 10.7.4: Proportion of the population who are refugees, by country of originSM_POP_REFG_OR: Number of refugees per 100,000 population, by country of origin (per 100,000 population)Target 10.a: Implement the principle of special and differential treatment for developing countries, in particular least developed countries, in accordance with World Trade Organization agreementsIndicator 10.a.1: Proportion of tariff lines applied to imports from least developed countries and developing countries with zero-tariffTM_TRF_ZERO: Proportion of tariff lines applied to imports with zero-tariff (%)Target 10.b: Encourage official development assistance and financial flows, including foreign direct investment, to States where the need is greatest, in particular least developed countries, African countries, small island developing States and landlocked developing countries, in accordance with their national plans and programmesIndicator 10.b.1: Total resource flows for development, by recipient and donor countries and type of flow (e.g. official development assistance, foreign direct investment and other flows)DC_TRF_TOTDL: Total assistance for development, by donor countries (millions of current United States dollars)DC_TRF_TOTL: Total assistance for development, by recipient countries (millions of current United States dollars)DC_TRF_TFDV: Total resource flows for development, by recipient and donor countries (millions of current United States dollars)Target 10.c: By 2030, reduce to less than 3 per cent the transaction costs of migrant remittances and eliminate remittance corridors with costs higher than 5 per centIndicator 10.c.1: Remittance costs as a proportion of the amount remittedSI_RMT_COST: Remittance costs as a proportion of the amount remitted (%)SI_RMT_COST_BC: Corridor remittance costs as a proportion of the amount remitted (%)SI_RMT_COST_SC: SmaRT corridor remittance costs as a proportion of the amount remitted (%)
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Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in South Franklin township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for South Franklin township median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in South Coventry township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for South Coventry township median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
South Africa Number of Households: by Income: Salaries, Wages or Commission data was reported at 10,590.000 Unit th in 2017. This records a decrease from the previous number of 10,896.000 Unit th for 2016. South Africa Number of Households: by Income: Salaries, Wages or Commission data is updated yearly, averaging 9,778.000 Unit th from Jul 2009 (Median) to 2017, with 9 observations. The data reached an all-time high of 10,896.000 Unit th in 2016 and a record low of 8,770.000 Unit th in 2009. South Africa Number of Households: by Income: Salaries, Wages or Commission data remains active status in CEIC and is reported by Statistics South Africa. The data is categorized under Global Database’s South Africa – Table ZA.H007: Number of Households: by Income.
The average monthly salary for South Africans who were employed in the formal non-agricultural sector was just over 26,800 South African rands (comparable to roughly 1,500 U.S. dollars) in November 2023, which represented a yearly increase of tw0 percent. During the period under review, the overall growth trend was positive, with the earnings increasing by 24.4 percent from 21,500 South African rands (approximately 1,180 U.S. dollars) in November 2018. Minimum wage and highest-paid professions Starting in March 2023, the minimum hourly wage in the country increased to 25.42 South African rands (comparable to 1.40 U.S. dollars), which represented an increase of 9.6 percent from 23.19 South African rands (1.27 U.S. dollars) per hour in the preceding year. On the other hand, professionals in executive and change management positions were paid the highest salaries in South Africa, with an average of 74,000 U.S. dollars yearly. Individuals with jobs in retail, trade, and craft followed, receiving an average of 66,000 U.S. dollars per annum. Highest unemployment among Black South Africans In 2022, the unemployment rate in South Africa was nearly 30 percent following an increasing trend since 2008. The rate was highest among Black South Africans reaching as high as 36.8 percent in the second quarter of 2023. Moreover, Colored South Africans followed with around 22 percent, while white South Africans had a much lower unemployment rate of over 7 percent.