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.

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

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

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.

Data appraisal

All continous household income and expenditure data collected during the Income and Expenditure Survey 2010-2011 are contained in the Total IES data file. The household data file contains only categorical variables. For example, expenditure data on electricity collected with the questions in sub-section 5.7 of the questionnaire will be found in the "Total_IES" data file under the COICOP codes 04511010, 04511110, 04404500. This is explained under "Data Organisation" on page 6 of the metadata record for the IES 2010 2011, which documents how the data files are organised and the variables in each data file.

Key information about South Africa Monthly Earnings

• South Africa Monthly Earnings stood at 1,589 USD in May 2025, compared with the previous figure of 1,533 USD in Feb 2025
• South Africa Monthly Earnings data is updated quarterly, available from Nov 2004 to May 2025, with an average number of 1,430 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

*This indicator will be no longer available from March 2026, 4th onwards. CEIC has a plan to remove the non-standard frequency indicator after the standard frequency indicator has been added and be available on this table. 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 63 million people in Jun 2025
• Unemployment Rate of South Africa dropped to 32 % in Sep 2025
• The country's Labour Force Participation Rate dropped to 60 % in Sep 2025

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

View quarterly updates and historical trends for South Africa Household Personal Disposable Income. Source: Federal Reserve Bank of Dallas. Track economic…

Abstract

The Income and Expenditure Survey 2005-2006 conducted by Statistics South Africa (Stats SA) between September 2005 and August 2006. The survey was designed to collect data on items and services acquired by South African households, sources of household income (monetary or in-kind) and household expenditure within a given reference period. Studies of this nature play an important role in evaluating changes in consumption patterns and income distribution. The data collected provides input to the goods and services for inclusion in the Consumer Price Index (CPI) basket of goods and services.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the survey are households and individuals

Universe

The survey covered all de jure household members

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

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]

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.

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.

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 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.

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.

South Africa ZA: Price to Income Ratio: sa data was reported at 90.320 2015=100 in 2024. This records a decrease from the previous number of 92.422 2015=100 for 2023. South Africa ZA: Price to Income Ratio: sa data is updated yearly, averaging 98.221 2015=100 from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 132.663 2015=100 in 2007 and a record low of 71.323 2015=100 in 1997. South Africa ZA: Price to Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s South Africa – Table ZA.OECD.AHPI: House Price Index: Seasonally Adjusted: Non OECD Member: Annual. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database.

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.

Disposable Personal Income in South Africa increased to 4891661 ZAR Million in the second quarter of 2025 from 4821583 ZAR Million in the first quarter of 2025. This dataset provides - South Africa Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

South Africa Number of Households: Black African: by Income: Business data was reported at 1,756.000 Unit th in 2017. This records an increase from the previous number of 1,695.000 Unit th for 2016. South Africa Number of Households: Black African: by Income: Business data is updated yearly, averaging 1,292.000 Unit th from Jul 2009 (Median) to 2017, with 9 observations. The data reached an all-time high of 1,756.000 Unit th in 2017 and a record low of 177.000 Unit th in 2012. South Africa Number of Households: Black African: by Income: Business 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.

Abstract

South Africa's first Living Conditions Survey (LCS) was conducted by Statistics South Africa over a period of one year between 13 October 2014 and 25 October 2015. The main aim of this survey is to provide data that will contribute to a better understanding of living conditions and poverty in South Africa for monitoring levels of poverty over time. Data was collected from 27 527 households across the country. The survey used a combination of the diary and recall methods. Households were asked to record their daily acquisitions in diaries provided by Statistics SA for a period of a month. The survey also employed a household questionnaire to collect data on household expenditure, subjective poverty, and income.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The sample for the survey included all domestic households, holiday homes and all households in workers' residences, such as mining hostels and dormitories for workers, but excludes institutions such as hospitals, prisons, old-age homes, student hostels, and dormitories for scholars, boarding houses, hotels, lodges and guesthouses.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Living Conditions Survey 2014-2015 sample was based on the LCS 2008-2009 master sample of 3 080 PSUs. However, there were 40 PSUs with no DU sample, thus the sample of 30 818 DUs was selected from only 3 040 PSUs. Amongst the PSUs with no DU sample, 25 PSUs were non-respondent because 19 PSUs were not captured on the dwelling frame, and 6 PSUs had an insufficient DU count. The remaining 15 PSUs were vacant and therefore out-of-scope. Among the PSUs with a DU sample, 2 974 PSUs were respondent, 50 PSUs were non-respondent and 16 PSUs were out-of-scope. The scope of the Master Sample (MS) is national coverage of all households in South Africa. It was designed to cover all households living in private dwelling units and workers living in workers' quarters in the country.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Living Conditions Survey 2014-2015 used three data collection instruments, namely a household questionnaire, a weekly diary, and the summary questionnaire. The household questionnaire was a booklet of questions administered to respondents during the course of the survey month. The weekly diary was a booklet that was left with the responding household to track all acquisitions made by the household during the survey month. The household (after being trained by the Interviewer) was responsible for recording all their daily acquisitions, as well as information about where they purchased the item and the purpose of the item. A household completed a different diary for each of the four weeks of the survey month. Interviewers then assigned codes for the classification of individual consumption according to purpose (COICOP) to items recorded in the weekly diary, using a code list provided to them.

Data appraisal

Anthropometric data collected during the survey are not included in the dataset.

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 Carolina. 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 2012 and 2022, 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 Carolina, the median household income for the households where the householder is White increased by $9,334(14.54%), between 2012 and 2022. The median household income, in 2022 inflation-adjusted dollars, was $64,182 in 2012 and $73,516 in 2022.
• Black or African American: In South Carolina, the median household income for the households where the householder is Black or African American increased by $6,989(18.79%), between 2012 and 2022. The median household income, in 2022 inflation-adjusted dollars, was $37,198 in 2012 and $44,187 in 2022.
• 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-carolina-median-household-income-by-race-trends.jpeg" alt="South Carolina median household income trends across races (2012-2022, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-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 Carolina.
• 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 Carolina median household income by race. You can refer the same here

Abstract

The 2005-2006 IES was designed to collect information on items and services acquired by South African households, various sources of income acquired by participating households (monetary or in-kind) and details as to how they spent this income (on expenditure, remittances, etc.). This was accomplished by collecting details of all expenditure by a participating household and all acquisitions of goods and services for the household’s own consumption within a given reference period. Studies of this nature play an important role in evaluating changes in consumption patterns, levels of income and income distribution. The results of the survey serve as an input into identifying the goods and services that should be included in the Consumer Price Index (CPI) basket of goods and services.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Consumption expenditure items/services

Universe

The IES 2005/2006 included all domestic households, holiday homes and all households in workers’ residences such as mining hostels and dormitories for workers. It did not include institutions such as hospitals, prisons, old-age homes, student hostels and dormitories for scholars. Also excluded were boarding houses, hotels, lodges and guest houses.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design • A newly designed Master Sample, consisting of 3 000 Primary Sampling Units (PSUs), based on the 2001 Population Census Enumeration Areas, was used as the sampling frame. The Master Sample is used for all household surveys conducted by Statistics South Africa (Stats SA). • The 3 000 primary sampling units (PSUs) from the Master Sample were representatively divided into four quarterly allocations of 750 each. • Within each quarterly allocation, a random sample of 250 PSUs was selected every month. • Eight dwelling units were systematically selected from each of the sampled PSUs for fieldwork. In total, 24 000 dwelling units were covered during the twelve months of data collection for the IES 2005/2006. This process ensured that the sample was evenly spread over the twelve months, while it remained nationally representative in each quarter.

Mode of data collection

Face-to-face [f2f]

Response rate

From the 24 000 dwelling units sampled across South Africa, 25 192 households were identified. Out of these, there was a sample realisation of 22 617 households, with the remaining 2 575 households were classified as out of scope due to a number of reasons, such as listing error, vacant dwelling, unoccupied dwelling, etc.

South Africa Number of Households: Black African: Female: by Income: Salaries, Wages or Commission data was reported at 3,041.000 Unit th in 2017. This records a decrease from the previous number of 3,075.000 Unit th for 2016. South Africa Number of Households: Black African: Female: by Income: Salaries, Wages or Commission data is updated yearly, averaging 2,731.000 Unit th from Jul 2009 (Median) to 2017, with 9 observations. The data reached an all-time high of 3,075.000 Unit th in 2016 and a record low of 2,098.000 Unit th in 2009. South Africa Number of Households: Black African: 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.