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

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.

Key information about South Africa Monthly Earnings

• South Africa Monthly Earnings stood at 1,547 USD in Aug 2024, compared with the previous figure of 1,470 USD in May 2024
• South Africa Monthly Earnings data is updated quarterly, available from Nov 2004 to Aug 2024, with an average number of 1,473 USD
• The data reached the an all-time high of 1,877 USD in Aug 2011 and a record low of 968 USD in Feb 2009

CEIC converts Monthly Earnings into USD. Statistics South Africa provides Nominal Average Monthly Earnings in local currency based on 2016 Business Sampling Frame. Federal Reserve Board average market exchange rate is used for currency conversions. Monthly Earnings exclude Agriculture sector. Monthly Earnings prior to Q2 2015 are based on 2013 Business Sampling Frame and prior to Q2 2013 are based on 2009 Business Sampling Frame. Monthly Earnings are in quarterly frequency, ending in February, May, August, November of each year.


Further information about South Africa Monthly Earnings

• In the latest reports, South Africa Population reached 61 million people in Jun 2022
• Unemployment Rate of South Africa dropped to 32 % in Sep 2024
• The country's Labour Force Participation Rate dropped to 60 % in Sep 2024

Disposable Personal Income in South Africa increased to 4830390 ZAR Million in the first quarter of 2025 from 4792181 ZAR Million in the fourth quarter of 2024. This dataset provides - South Africa Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Wages in South Africa decreased to 28289 ZAR/Month in the first quarter of 2025 from 28316 ZAR/Month in the fourth quarter of 2024. This dataset provides - South Africa Total Quarterly Wages - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Households Debt in South Africa increased to 62.50 percent of gross income in 2024 from 62.40 percent in 2023. This dataset provides - South Africa Households Debt To Income- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Gross National Income for South Africa (MKTGNIZAA646NWDB) from 1960 to 2024 about GNI, South Africa, and income.

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.

South Africa ZA: Households: Gross Disposable Income data was reported at 3,182,389.302 ZAR mn in Mar 2021. This records an increase from the previous number of 3,145,735.482 ZAR mn for Dec 2020. South Africa ZA: Households: Gross Disposable Income data is updated quarterly, averaging 2,264,354.000 ZAR mn from Mar 2008 (Median) to Mar 2021, with 53 observations. The data reached an all-time high of 3,182,389.302 ZAR mn in Mar 2021 and a record low of 1,333,769.000 ZAR mn in Mar 2008. South Africa ZA: Households: Gross Disposable Income data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s South Africa – Table ZA.IMF.FSI: 2006 Methodology: Sectoral Financial Statement: Income and Expense: Quarterly.

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.

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. The IES is based on the sample for the rotating panel of the twice yearly Labour force Survey (LFS). The IES 2000 was conducted in October 2000.

Geographic coverage

The survey had national coverage

Analysis unit

The units of analysis in the survey are households and individuals

Universe

The survey covered all household members

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

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.

South Africa Households Disposable Income per Capita data was reported at 49,712.000 ZAR in 2017. This records an increase from the previous number of 46,901.000 ZAR for 2016. South Africa Households Disposable Income per Capita data is updated yearly, averaging 1,546.000 ZAR from Dec 1946 (Median) to 2017, with 72 observations. The data reached an all-time high of 49,712.000 ZAR in 2017 and a record low of 101.000 ZAR in 1946. South Africa Households Disposable Income per Capita data remains active status in CEIC and is reported by South African Reserve Bank. The data is categorized under Global Database’s South Africa – Table ZA.A040: SNA 2008: Households Disposable Income per Capita.

Net primary income (Net income from abroad) (current US$) in South Africa was reported at --5166056341 USD in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. South Africa - Net income from abroad - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

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.

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]

This statistic shows the distribution of annual household income in South Africa in 2010. In 2010, 15.5 percent of households in South Africa had no income.

Gross National Product in South Africa increased to 4720054 ZAR Million in the first quarter of 2025 from 4690165 ZAR Million in the fourth quarter of 2024. This dataset provides the latest reported value for - South Africa Gross National Income - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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. Wave 2 of NIDS re-interviewed respondents interviewed in Wave 1, gathering information on developments in their lives since they were interviewed in 2008. Wave 3 of the survey took place between April and December 2012 and re-interviewed respondents from Waves 1 and 2.

Geographic coverage

The survey had national coverage

Analysis unit

The units of analysis in the survey are individuals and households. The NIDS questionnaires attempted to gather information on all members of the household; including those that were resident and those that were non-resident at the time of the interview. Those that were resident provided the base sample of individuals who will remain in the NIDS sample over time. Information about non-resident members is essential in understanding the household and family support systems that individuals have around them at the time of the interview.

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]

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 Gorin. 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 2011 and 2021, 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 Gorin, the median household income for the households where the householder is White decreased by $3,706(9.07%), between 2011 and 2021. The median household income, in 2022 inflation-adjusted dollars, was $40,862 in 2011 and $37,156 in 2021.
• Black or African American: As per the U.S. Census Bureau population data, in South Gorin, 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

https://i.neilsberg.com/ch/south-gorin-mo-median-household-income-by-race-trends.jpeg" alt="South Gorin, MO median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Gorin.
• 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
• Please note: 2020 1-Year ACS estimates data was not reported by Census Bureau due to impact on survey collection and analysis during COVID-19, thus for large cities (population 65,000 and above) median household income data is not available.
• Please note: All incomes have been adjusted for inflation and are presented in 2022-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 Gorin median household income by race. You can refer the same here