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.

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.

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.

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.

Wages in Manufacturing in South Africa increased to 24088 ZAR/Month in the fourth quarter of 2024 from 23735 ZAR/Month in the third quarter of 2024. This dataset provides - South Africa Total Quarterly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Abstract

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.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the survey are households

Universe

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.

Kind of data

Sample survey data [ssd]

Sampling procedure

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.

Mode of data collection

Face-to-face [f2f]

Research instrument

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.

Response rate

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.

South Africa Number of Households: Female: by Income: Salaries, Wages or Commission data was reported at 3,774.000 Unit th in 2017. This records a decrease from the previous number of 3,804.000 Unit th for 2016. South Africa Number of Households: Female: by Income: Salaries, Wages or Commission data is updated yearly, averaging 3,387.000 Unit th from Jul 2009 (Median) to 2017, with 9 observations. The data reached an all-time high of 3,804.000 Unit th in 2016 and a record low of 2,632.000 Unit th in 2009. South Africa Number of Households: Female: 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.

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.

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.

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).

This map shows the purchasing power per capita in South Africa in 2019, in a multiscale map (Country, Province, District, Municipality, Main Place, Sub Place, and Small Area). Nationally, the purchasing power per capita is 54,780 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 2019.Additional Esri Resources:Esri DemographicsPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

About this dataset

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

• White: In South Franklin township, the median household income for the households where the householder is White decreased by $20,399(21.75%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $93,809 in 2013 and $73,410 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in South Franklin township, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in South Franklin township.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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.

Inspiration

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/.

Recommended for further 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

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.

As of January 2025, the average income per unit sold of hotel accommodations in South Africa reached roughly 1,661 South African rand (around 91 U.S. dollars). As of January 2023, the income per sold unit night has been steady and above 1,000 South African rand.

Key information about South Africa Household Debt: % of GDP

• South Africa household debt accounted for 40.7 % of the country's Nominal GDP in Sep 2024, compared with the ratio of 40.6 % in the previous quarter.
• South Africa household debt to GDP ratio is updated quarterly, available from Mar 1969 to Sep 2024.
• The data reached an all-time high of 49.6 % in Sep 2007 and a record low of 25.0 % in Sep 1980.

CEIC calculates quarterly Household Debt as % of Nominal GDP from quarterly Household Debt and quarterly Nominal GDP. Household Debt is calculated from Household Disposable Income and ratio of Household Debt to Household Disposable Income. South African Reserve Bank provides Household Debt in local currency. Statistics South Africa provides Nominal GDP in local currency.


Related information about South Africa Household Debt: % of GDP

• In the latest reports, South Africa Household Debt reached 171.2 USD bn in Sep 2024.
• Money Supply M2 in South Africa increased 7.1 % YoY in Oct 2024.
• South Africa Foreign Exchange Reserves was measured at 45.0 USD bn in Oct 2024.
• The Foreign Exchange Reserves equaled 4.8 Months of Import in Oct 2024.
• South Africa Domestic Credit reached 319.5 USD bn in Oct 2024, representing an increased of 6.8 % YoY.
• The country's Non Performing Loans Ratio stood at 5.3 % in Oct 2024, compared with the ratio of 5.2 % in the previous month.

As of 2019, approximately 10.68 million out of South Africa's 17.16 million households drew their income from regular salaries, wages or commissions. 7.9 million households received social grants paid by the government for citizens in need of state support.

About this dataset

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

• White: In South Hanover township, the median household income for the households where the householder is White increased by $6,993(6.84%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $102,310 in 2013 and $109,303 in 2023.
• Black or African American: In South Hanover township, the median household income for Black or African American households was $38,765 in 2013(2023 inflation-adjusted dollars). However there is no reported data for 2023, indicating a lack of information for this specific year.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

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:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in South Hanover township.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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.

Inspiration

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/.

Recommended for further 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

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

Wave 1 of the survey, conducted in 2008, collected the detailed information for the national sample. In 2010/2011 Wave 2 of NIDS re-interviewed these people, gathering information on developments in their lives since they were interviewed first in 2008. As such, the comparison of Wave 1 and Wave 2 information provides a detailed picture of how South Africans have fared over two years of very difficult socio-economic circumstances.

Completed and non-response interviews in the NIDS Data: The NIDS datasets contain both completed and non-response interviews (e.g. Refusals). It is recommended that researchers limit their research to completed interviews to avoid item non-response from non-response interviews. The completed interviews can be identified by making use of the wx'_y'_outcome variables, where x' represents the wave andy' represents the relevant data file/outcome type indicator. These outcome variables can be found in each of the following data files, Adult, Child, Proxy, HHQuestionnaire and Link File. The only exception to this is Wave 1 where no outcome variable exists. This is because at a household level, all of the interviews are completed. However this does not apply at an individual level where non-response interviews can be identified by making use of the "Reason for refusal" variables, namely w1_a_refexpl or w1_c_refexpl in the Adult and Child data files respectively.

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]

Mode of data collection

Face-to-face [f2f]

Research instrument

As in Wave 1 four types of questionnaires were administered in Wave 2:

Household questionnaire: One household questionnaire was completed per household by the oldest woman in the household or another person knowledgeable about household affairs and particularly household spending. Household questionnaires took approximately 45 minutes in non-agricultural households and 70 minutes in agricultural households to complete. Individual Adult questionnaire: The Adult questionnaire was applied to all present Continuing Sample Members and other household member's resident in their households that are aged 15 years or over. This questionnaire took an average of 45 minutes per adult to complete. Individual Proxy Questionnaire: Should an individual qualifying for an Adult questionnaire not be present then a Proxy Questionnaire (a much reduced Adult Questionnaire using third party referencing in the questioning) was taken on their behalf with a present resident adult. On average a Proxy questionnaire took 20 minutes. Proxy Questionnaires were also asked for CSMs who had moved out of scope (out of South Africa or to a non-accessible institution such as prison), except if the whole household moved out of scope, and could therefore not be tracked or interviewed directly. Child questionnaire: This questionnaire collected information about all Continuing Sample Members and residents in their household younger than 15. Information about the child was gathered from the care-giver of the child. The questionnaire focused on the child's educational history, education, anthropometrics and access to grants. This questionnaire took an average of 20 minutes per child to complete.

Phase Two of Wave 2: In June 2011 NIDS commissioned a Phase Two of Wave 2 as a Non-Response Follow-Up from Phase 1 of Wave 2. Household included in this subsample where those that refused and those that could not be located or tracked in Phase 1. Out of a total of 1064 households attempted, an additional 389 households were successfully interviewed in Phase Two.

Questionnaire Differences between W2 Phase 1 & W2 Phase2 There are two important methodological differences between Phase 1 and Phase 2: 1. Not all sections of the original Wave 2 questionnaires were asked. This reduced respondent burden and the time required for fieldworker training. Questions NOT asked in Phase 2 are indicated with the non-response code “-2”. Core modules such as household composition and income were still asked. Consult the Wave 2 Phase 2 questionnaires for more details of these differences. 2. Movers out of Phase 2 dwelling units were not tracked further. Address information was collected for this sub-sample and they will be tracked as part of the Wave 3 fieldwork exercise. These individuals are classified as “Not tracked” in the Wave 2 dataset.

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.