In January 2025, the top one percent of earners in the United Kingdom received an average pay of 15,882 British pounds per month, compared with the bottom 10 percent of earners who earned 813 pounds a month.

In the 3 years to March 2021, black households were most likely out of all ethnic groups to have a weekly income of under £600.

The median annual earnings in the United Kingdom was 37,430 British pounds per year in 2024. Annual earnings varied significantly by region, ranging from 47,455 pounds in London to 32,960 pounds in the North East. Along with London, two other areas of the UK had median annual earnings above the UK average; South East England, and Scotland, at 39,038 pounds and 38,315 pounds respectively. Regional Inequality in the UK Various other indicators highlight the degree of regional inequality in the UK, especially between London and the rest of the country. Productivity in London, as measured by output per hour, was 33.2 percent higher than the UK average. By comparison, every other UK region, except the South East, fell below the UK average for productivity. In gross domestic product per head, London was also an outlier. The average GDP per head in the UK was 31,947 pounds in 2021, but for London it was 56,431 pounds. Again, the South East's GDP per head was slightly above the UK average, with every other region below it. Within London itself, there is also a great degree of inequality. In 2021, for example, the average earnings in the historic City of London borough were 1,138 pounds per week, compared with 588 pounds in Redbridge, a borough in the North East of London. Wages finally catch up with inflation in 2023 After the initial economic disruption caused by the COVID-19 pandemic subsided, wages began to steadily grow in the UK. This reached a peak in June 2021, when weekly wages for regular pay were growing at 7.3 percent, or 5.2 percent when adjusted for inflation. By that November, however, prices began to rise faster than wage growth, with inflation surging throughout 2022. In October 2022, for example, while regular pay was growing by 6.1 percent, the inflation rate had surged to 11.1 percent, Although inflation peaked in that month, it wasn't until June 2023 that wages started to outpace inflation. By this point, the damage caused by high energy and food inflation has precipitated the worst Cost of Living Crisis in the UK for a generation.

Households in the bottom decile in the United Kingdom earned, on average, 18,706 British pounds per year in 2022/23, compared with the top decile which earned 185,358 pounds per year.

Estimates of annual household income for the four income types for Middle layer Super Output Areas, or local areas, in England and Wales.

Mean and median average gross annual household income for Output Areas, Lower SOAs, Middle SOAs, Wards and Boroughs, London, 2011/12

This income data is unequivalised - that is it takes no account of average household size or composition within each area.

A full description of how the estimates were put together can be read in this GLA Intelligence Unit Update.

Download:

• Excel (all geographies included in single spreadsheet)

Or **Open: **

- Atlas (or click on image below)

These are experimental income estimates, which means that they are in the testing phase. Feedback is welcome with the intention that the model will be improved in future years if possible. Please send any comments to the Datastore email address.

This GLA Intellingence Update paper presents analysis of the headline findings of these data.

https://s3-eu-west-1.amazonaws.com/londondatastore-upload/Update6-income%20analysis%20screen.PNG" alt="">

The project adopted a broad approach, employing quantitative as well as qualitative methods. It covered both public and private forms of risk protection, and it analysed attitudes as well as actual behavior. First, we reviewed Britain's current 'mixed economy of welfare' in the aforementioned five key areas. We mapped the social programmes, occupational schemes and private options that have been available since the early 1990s. The second phase was based on quantitative data analysis, making use of the Family Resources Survey (FRS) and the ABI Risk and Protection Survey. We analysed the take-up of insurances and how it was influenced by attitudes and socio-demographic characteristics. Third, we conducted 61 qualitative interviews, where we explored personal risk management strategies of middle-income households from Scotland and England. The main result was a typology of risk management rationales that guide household economies. This stage also explored the ramifications of the recent financial uncertainties and economic downturn.

Comparing England and Scotland, the purpose was to review Britain's current 'mixed economy of welfare' in key areas: unemployment, sickness, costs of higher education for children, retirement and infirmity in old age. The aim was to map the types of statutory protection against such risks and contingencies and examine changes in the scope of public provision. In parallel, we will examine the scope of non-statutory (occupational and personal) provision, investigating how 'private welfare markets' have developed since the early 1990s. The second phase is based on quantitative data analysis of household savings and investment behaviour in insurances and private market-based contracts for risk protection. Finally, via qualitative interviews, we explore personal risk management of socially and economically similar families from Scotland and England. This stage will also explore the potential ramifications of the most recent financial uncertainties and economic downturn.

The project investigated risk management strategies of above average income households in England and Scotland. In the UK especially those with above average incomes are often assumed to have access to or seek private forms of risk protection, partly based on company provision or private voluntary protection complementing or substituting public social protection. The project investigated how households protect themselves against income loss due to unemployment, sickness or retirement and plan for expenses like long term care and higher education costs. We focused our analysis on how households balance these risks between public, occupational and private forms of protection. Moreover, we explored how the recent financial crisis has influenced the attitudes and behavior of households regarding their personal protection. The project sought to answer how and why some middle class households plan for contingencies and engage in private risk management strategies while others do not.

This article studies the median income of UK households from 1977 to 2011/12.

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: Median Household Income

By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 million in 2030.

Worldwide wealth

While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent of non-investable assets.

The middle-class

The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth to the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle-class.

In February 2025, employees in the United Kingdom were earning a median pay of 2,465 British pounds per month, compared with 2,474 in the previous month.

In 2023, the highest average amount of disposable income for any age group occurred in the 35 to 44-year-old group, while the age group with the lowest average disposable income were those aged 85 and over.

Model-based estimates of the proportion of households with mean weekly income lower than 60% of the national median weekly income, by middle layer super output area, England and Wales.

United Kingdom UK: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data was reported at 15.267 % in 2016. This records a decrease from the previous number of 16.649 % for 2015. United Kingdom UK: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data is updated yearly, averaging 14.874 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 28.682 % in 1960 and a record low of 9.212 % in 1999. United Kingdom UK: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Exports. Merchandise exports to low- and middle-income economies outside region are the sum of merchandise exports from the reporting economy to other low- and middle-income economies in other World Bank regions according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

In June 2024, the household cost inflation rate (HCI) for low-income households in the United Kingdom was 1.7 percent, compared with 2.3 percent for middle-income households, and 3.3 percent for high-income households. Unlike other measures of inflation such as the consumer price index (CPI) the HCI isn't based on a fixed basket of goods, but is weighted to show how price changes affect different households by their economic status.

This data file includes the Inequality and Poverty Key Figures (as of March 2022), constructed for all Luxembourg Income Study (LIS) Study datasets in all waves. It includes multiple national-level measures: • on inequality measures: Gini, Atkinson coefficients, and percentile ratios • on relative poverty rates for various demographic groups • median and mean of disposable household income

This project sought to renew the ESRC's invaluable financial support to LIS (formerly the Luxembourg Income Study) for a period of five more years. LIS is an independent, non-profit cross-national data archive and research institute located in Luxembourg. LIS relies on financial contributions from national science foundations, other research institutions and consortia, data-providing agencies, and supranational organisations to support data harmonisation and enable free and unlimited data access to researchers in the participating countries and to students world-wide. LIS' primary activity is to make harmonised household microdata available to researchers, thus enabling cross-national, interdisciplinary primary research into socio-economic outcomes and their determinants. Users of the Luxembourg Income Study Database and Luxembourg Wealth Study Database come from countries around the globe, including the UK. LIS has four goals: 1) to harmonise microdatasets from high- and middle-income countries that include data on income, wealth, employment, and demography; 2) to provide a secure method for researchers to query data that would otherwise be unavailable due to country-specific privacy restrictions; 3) to create and maintain a remote-execution system that sends research query results quickly back to users at off-site locations; and 4) to enable, facilitate, promote and conduct crossnational comparative research on the social and economic wellbeing of populations across countries. LIS contains the Luxembourg Income Study (LIS) Database, which includes income data, and the Luxembourg Wealth Study (LWS) Database, which focuses on wealth data. LIS currently includes microdata from 46 countries in Europe, the Americas, Africa, Asia and Australasia. LIS contains over 250 datasets, organised into eight time "waves," spanning the years 1968 to 2011. Since 2007, seventeen more countries have been added to LIS, including the BRICS countries (Brazil, Russia, India, China, South Africa), Japan, South Korea and a number of other Latin American countries. LWS contains 20 wealth datasets from 12 countries, including the UK, and covers the period 1994 to 2007. All told, LIS and LWS datasets together cover 86% of world GDP and 64% of world population. Users submit statistical queries to the microdatabases using a Java-based job submission interface or standard email. The databases are especially valuable for primary research in that they offer access to cross-national data at the micro-level - at the level of households and persons. Users are economists, sociologists, political scientists, and policy analysts, among others, and they employ a range of statistical approaches and methods. LIS also provides extensive documentation - metadata - for both LIS and LWS, concerning technical aspects of the survey data, the harmonisation process, and the social institutions of income and wealth provision in participating countries. In the next five years, for which support is sought, LIS will: - expand LIS, adding Waves IX (2013) and X (2016), and add new middle-income countries; - develop LWS, adding another wave of datasets to existing countries; acquire new wealth datasets for 14 more countries in cooperation with the European Central Bank (based on the Household Finance and Consumption Survey); - create a state-of-the-art metadata search and storage system; - maintain international standards in data security and data infrastructure systems; - provide high-quality harmonised household microdata to researchers around the world; - enable interdisciplinary cross-national social science research covering 45+ countries, including the UK; - aim to broaden its reach and impact in academic and non-academic circles through focused communications strategies and collaborations.

This data file includes the Gini coefficient calculated for different wealth welfare aggregates constructed for all Luxembourg Wealth Study (LWS) datasets in all waves (as of March 2022). It includes Gini coefficients calculated on: • Disposable Net Worth • Value of Principal residence • Financial Assets

This project sought to renew the ESRC's invaluable financial support to LIS (formerly the Luxembourg Income Study) for a period of five more years. LIS is an independent, non-profit cross-national data archive and research institute located in Luxembourg. LIS relies on financial contributions from national science foundations, other research institutions and consortia, data-providing agencies, and supranational organisations to support data harmonisation and enable free and unlimited data access to researchers in the participating countries and to students world-wide. LIS' primary activity is to make harmonised household microdata available to researchers, thus enabling cross-national, interdisciplinary primary research into socio-economic outcomes and their determinants. Users of the Luxembourg Income Study Database and Luxembourg Wealth Study Database come from countries around the globe, including the UK. LIS has four goals: 1) to harmonise microdatasets from high- and middle-income countries that include data on income, wealth, employment, and demography; 2) to provide a secure method for researchers to query data that would otherwise be unavailable due to country-specific privacy restrictions; 3) to create and maintain a remote-execution system that sends research query results quickly back to users at off-site locations; and 4) to enable, facilitate, promote and conduct crossnational comparative research on the social and economic wellbeing of populations across countries. LIS contains the Luxembourg Income Study (LIS) Database, which includes income data, and the Luxembourg Wealth Study (LWS) Database, which focuses on wealth data. LIS currently includes microdata from 46 countries in Europe, the Americas, Africa, Asia and Australasia. LIS contains over 250 datasets, organised into eight time "waves," spanning the years 1968 to 2011. Since 2007, seventeen more countries have been added to LIS, including the BRICS countries (Brazil, Russia, India, China, South Africa), Japan, South Korea and a number of other Latin American countries. LWS contains 20 wealth datasets from 12 countries, including the UK, and covers the period 1994 to 2007. All told, LIS and LWS datasets together cover 86% of world GDP and 64% of world population. Users submit statistical queries to the microdatabases using a Java-based job submission interface or standard email. The databases are especially valuable for primary research in that they offer access to cross-national data at the micro-level - at the level of households and persons. Users are economists, sociologists, political scientists, and policy analysts, among others, and they employ a range of statistical approaches and methods. LIS also provides extensive documentation - metadata - for both LIS and LWS, concerning technical aspects of the survey data, the harmonisation process, and the social institutions of income and wealth provision in participating countries. In the next five years, for which support is sought, LIS will: - expand LIS, adding Waves IX (2013) and X (2016), and add new middle-income countries; - develop LWS, adding another wave of datasets to existing countries; acquire new wealth datasets for 14 more countries in cooperation with the European Central Bank (based on the Household Finance and Consumption Survey); - create a state-of-the-art metadata search and storage system; - maintain international standards in data security and data infrastructure systems; - provide high-quality harmonised household microdata to researchers around the world; - enable interdisciplinary cross-national social science research covering 45+ countries, including the UK; - aim to broaden its reach and impact in academic and non-academic circles through focused communications strategies and collaborations.

United Kingdom UK: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: South Asia data was reported at 1.423 % in 2016. This records a decrease from the previous number of 1.586 % for 2015. United Kingdom UK: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: South Asia data is updated yearly, averaging 1.690 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 6.032 % in 1960 and a record low of 1.074 % in 1998. United Kingdom UK: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: South Asia data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Exports. Merchandise exports to low- and middle-income economies in South Asia are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the South Asia region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Estimates of mean weekly household income for the 4 income types.