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 26.2 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 just over 37,000 pounds in 2023, but for London it was almost 64,000 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 2023, for example, the average earnings in Kensington and Chelsea were 964 pounds per week, compared with 675 pounds in Barking and Dagenham. Wages continue to grow in 2025 In March 2025, weekly wages in the UK were growing by around 5.6 percent, or 1.8 percent when adjusted for inflation. For almost two years, wages have grown faster than inflation after a long period where prices were rising faster than wages between 2021 and 2023. This was due to a sustained period of high inflation in the UK, which peaked in October 2022 at 11.1 percent. Although inflation started to slow the following 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 had led to the the worst Cost of Living Crisis in the UK for a generation.

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by home-based region to local and unitary authority level.

In 2024, the average annual full-time salary for men in the United Kingdom was 40,035 British pounds, compared with 34,000 pounds for women, a difference of just over 6,000 pounds. In the previous year, men earned an average annual salary of 37,382, compared with women who earned 31,672.

Analysis of ‘Housing in London’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/justinas/housing-in-london on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

--- Original source retains full ownership of the source dataset ---

FOCUSON**LONDON**2010:**INCOME**AND**SPENDING**AT**HOME** Household income in London far exceeds that of any other region in the UK. At £900 per week, London’s gross weekly household income is 15 per cent higher than the next highest region. Despite this, the costs to each household are also higher in the capital. Londoners pay a greater amount of their income in tax and national insurance than the UK average as well as footing a higher bill for housing and everyday necessities. All of which leaves London households less well off than the headline figures suggest. This chapter, authored by Richard Walker in the GLA Intelligence Unit, begins with an analysis of income at both individual and household level, before discussing the distribution and sources of income. This is followed by a look at wealth and borrowing and finally, focuses on expenditure including an insight to the cost of housing in London, compared with other regions in the UK. See other reports from this Focus on London series. REPORT: To view the report online click on the image below. Income and Spending Report PDF https://londondatastore-upload.s3.amazonaws.com/fol/fol10-income-cover-thumb1.png" alt="Alt text"> PRESENTATION: This interactive presentation finds the answer to the question, who really is better off, an average London or UK household? This analysis takes into account available data from all types of income and expenditure. Click on the link to access. PREZI The Prezi in plain text version RANKINGS: https://londondatastore-upload.s3.amazonaws.com/fol/fol10-income-tableau-chart-thumb.jpg" alt="Alt text"> This interactive chart shows some key borough level income and expenditure data. This chart helps show the relationships between five datasets. Users can rank each of the indicators in turn. Borough rankings Tableau Chart MAP: These interactive borough maps help to geographically present a range of income and expenditure data within London. Interactive Maps - Instant Atlas DATA: All the data contained within the Income and Spending at Home report as well as the data used to create the charts and maps can be accessed in this spreadsheet. Report data FACTS: Some interesting facts from the data… ● Five boroughs with the highest median gross weekly pay per person in 2009: -1. Kensington & Chelsea - £809 -2. City of London - £767 -3. Westminster - £675 -4. Wandsworth - £636 -5. Richmond - £623 -32. Brent - £439 -33. Newham - £422 ● Five boroughs with the highest median weekly rent for a 2 bedroom property in October 2010: -1. Kensington & Chelsea - £550 -2. Westminster - £500 -3. City of London - £450 -4. Camden - £375 -5. Islington - £360 -32. Havering - £183 -33. Bexley - £173 ● Five boroughs with the highest percentage of households that own their home outright in 2009: -1. Bexley – 38 per cent -2. Havering – 36 per cent -3. Richmond – 32 per cent -4. Bromley – 31 per cent -5. Barnet – 28 per cent -31. Tower Hamlets – 9 per cent -32. Southwark – 9 per cent

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

Gross weekly and hourly earnings by level of occupation, UK, quarterly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.

This dataset contains disability pay gap estimates for all employees in London and the UK.

The disability pay gap is the difference in the average hourly wage of non-disabled employees and disabled employees across a workforce. If disabled employees do more of the less well paid jobs within an organisation than the non-disabled persons, the disablity pay gap is usually bigger.

This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

This dataset contains gender pay gap figures for the GLA, large employers in London and estimates for all employees in London.

The gender pay gap is the difference in the average hourly wage of all men and women across a workforce. If women do more of the less well paid jobs within an organisation than men, the gender pay gap is usually bigger.

The UK government publish gender pay gap figures for all employers with 250 or more employees. A cut of this dataset that only shows employers that are registered in London can be found below.

Read a report by the Local Government Association (LGA) that summarises the mean and median pay gaps in local authorities, as well as the distribution of staff across pay quartiles.

This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

This dataset is one of the Greater London Authority's measures of Economic Development strategy. Click here to find out more.

Affordability ratios calculated by dividing house prices by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Count of the number of employees earning over £50k.

These reports from the GLA Intelligence Unit look at the London figures from the DWP's households below average income series, on which the government's official poverty targets are based.

This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

This dataset is one of the Greater London Authority's measures of Economic Development strategy. Click here to find out more.

Gross weekly earnings of full-time employees by region, UK, quarterly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.

This dataset provides information about earnings of employees who are working in an area, who are on adult rates and whose pay for the survey pay-period was not affected by absence.

Tables provided here include total gross weekly earnings, and full time weekly earnings with breakdowns by gender, and annual median, mean and lower quartile earnings by borough and UK region. These are provided both in nominal and real terms.

Real earnings figures are on sheets labelled "real", are in 2016 prices, and calculated by applying ONS’s annual CPI index series for April to ASHE data.

Annual Survey of Hours and Earnings (ASHE) is based on a sample of employee jobs taken from HM Revenue & Customs PAYE records. Information on earnings and hours is obtained in confidence from employers. ASHE does not cover the self-employed nor does it cover employees not paid during the reference period.

The earnings information presented relates to gross pay before tax, National Insurance or other deductions, and excludes payments in kind.

The confidence figure is the coefficient of variation (CV) of that estimate. The CV is the ratio of the standard error of an estimate to the estimate itself and is expressed as a percentage. The smaller the coefficient of variation the greater the accuracy of the estimate. The true value is likely to lie within +/- twice the CV.

Results for 2003 and earlier exclude supplementary surveys. In 2006 there were a number of methodological changes made. For further details goto : http://www.nomisweb.co.uk/articles/341.aspx.
The headline statistics for ASHE are based on the median rather than the mean. The median is the value below which 50 per cent of employees fall. It is ONS's preferred measure of average earnings as it is less affected by a relatively small number of very high earners and the skewed distribution of earnings. It therefore gives a better indication of typical pay than the mean.

Survey data from a sample frame, use caution if using for performance measurement and trend analysis
'#' These figures are suppressed as statistically unreliable.
! Estimate and confidence interval not available since the group sample size is zero or disclosive (0-2).

Furthermore, data from Abstract of Regional Statistics, New Earnings Survey and ASHE have been combined to create long run historical series of full-time weekly earnings data for London and Great Britain, stretching back to 1965, and is broken down by sex.

This dataset contains ethnicity pay gap figures for the GLA and estimates for all employees in London.

The ethnicity pay gap is the difference in the average hourly wage of white employees and employees of other ethnicities across a workforce. If non-white employees do more of the less well paid jobs within an organisation than white persons, the ethnicity pay gap is usually bigger.

This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more.

This dataset provides information about earnings of employees who are working in an area, who are on adult rates and whose pay for the survey pay-period was not affected by absence. Tables provided here include total gross weekly earnings, and full time weekly earnings with breakdowns by gender, and annual median, mean and lower quartile earnings by borough and UK region. These are provided both in nominal and real terms. Real earnings figures are on sheets labelled "real", are in 2016 prices, and calculated by applying ONS’s annual CPI index series for April to ASHE data. Annual Survey of Hours and Earnings (ASHE) is based on a sample of employee jobs taken from HM Revenue & Customs PAYE records. Information on earnings and hours is obtained in confidence from employers. ASHE does not cover the self-employed nor does it cover employees not paid during the reference period. The earnings information presented relates to gross pay before tax, National Insurance or other deductions, and excludes payments in kind. The confidence figure is the coefficient of variation (CV) of that estimate. The CV is the ratio of the standard error of an estimate to the estimate itself and is expressed as a percentage. The smaller the coefficient of variation the greater the accuracy of the estimate. The true value is likely to lie within +/- twice the CV. Results for 2003 and earlier exclude supplementary surveys. In 2006 there were a number of methodological changes made. For further details goto : http://www.nomisweb.co.uk/articles/341.aspx. The headline statistics for ASHE are based on the median rather than the mean. The median is the value below which 50 per cent of employees fall. It is ONS's preferred measure of average earnings as it is less affected by a relatively small number of very high earners and the skewed distribution of earnings. It therefore gives a better indication of typical pay than the mean. Survey data from a sample frame, use caution if using for performance measurement and trend analysis '#' These figures are suppressed as statistically unreliable. ! Estimate and confidence interval not available since the group sample size is zero or disclosive (0-2). Furthermore, data from Abstract of Regional Statistics, New Earnings Survey and ASHE have been combined to create long run historical series of full-time weekly earnings data for London and Great Britain, stretching back to 1965, and is broken down by sex.

Abstract copyright UK Data Service and data collection copyright owner.

This secondary analysis dataset contains variables produced for use in conjunction with the United Kingdom Time Use Survey, 2000 (TUS) (held at the UK Data Archive (UKDA) under SN 4504). Users should refer to the TUS documentation for details on the original data collection, structure and content of that survey, including weighting and validation of results.

The variables in this dataset are designed to enhance the usefulness of the TUS for research on earnings, income inequality, and poverty. In particular, the TUS itself contains information on gross, but not net, household incomes. Therefore, this dataset used information provided in TUS combined with that from the Family Resources Survey, 2000-2001 (held at the UKDA under SN 4498) and the Households Below Average Income (HBAI) dataset (not currently held at the UKDA) for the same year, to impute individual net earnings and household net incomes for households containing at least one person of working age (16-59 years for women, 16-64 for men).

Furthermore, the TUS provides detailed information on use of childcare but not on childcare expenditure. Therefore, this dataset used information from the Department for Education and Skills' (DfES) Parents' Demand for Childcare surveys (held under GN 33341) to derive estimates of childcare expenditure. Household net incomes could then be calculated either with childcare expenditure included or not.

This dataset was prepared as part of a project titled Time and Income Poverty: a Double Bind?, which was funded by the Joseph Rowntree Foundation.
Main Topics:

The variables in the dataset are at individual level, although some relate to household characteristics. They comprise three linking variables, to enable users to match the income and childcare expenditure variables provided in this dataset to the main TUS; nine variables in relation to net income; and five variables in relation to childcare.