The table only covers individuals who have some liability to Income Tax. The percentile points have been independently calculated on total income before tax and total income after tax.
These statistics are classified as accredited official statistics.
You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.
Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.
Note: comparisons over time may be affected by changes in methodology. Notably, there was a revision to the grossing factors in the 2018 to 2019 publication, which is discussed in the commentary and supporting documentation for that tax year. Further details, including a summary of significant methodological changes over time, data suitability and coverage, are included in the Background Quality Report.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
An average of 79% of Bangladeshi households were in the 2 lowest income quintiles (after housing costs were deducted) between April 2019 and March 2022
These tables only cover individuals with some liability to tax.
These statistics are classified as accredited official statistics.
You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.
Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.
Note: comparisons over time may be affected by changes in methodology. Notably, there was a revision to the grossing factors in the 2018 to 2019 publication, which is discussed in the commentary and supporting documentation for that tax year. Further details, including a summary of significant methodological changes over time, data suitability and coverage, are included in the Background Quality Report.
Households in the bottom decile in the United Kingdom earned, on average, ****** British pounds per year in 2022/23, compared with the top decile which earned ******* pounds per year.
Households in the lower income quantiles in England in 2024 were more likely to own a household outright than to be currently buying with a mortgage. As the weekly gross income of a household goes up, so does the likelihood that it occupies a home purchased with a mortgage. Of households in the first quantile (lowest income), 4.1 percent were buying with a mortgage, compared to 39.3 percent in the fifth quantile (highest income).
In 2022/23, the top quintile of earners in the United Kingdom had an average household disposable income of approximately ****** British pounds, compared with ****** for the bottom quintile.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in New Britain, CT, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for New Britain median household income. You can refer the same here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Estimates of annual household income for the four income types for Middle layer Super Output Areas, or local areas, in England and Wales.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Distribution of gross hourly earnings of full-time and part-time employees by sex, UK, quarterly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the England household income by gender. The dataset can be utilized to understand the gender-based income distribution of England income.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of England income distribution by gender. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
In this paper, we propose a model of income dynamics which takes account of mobility both within and between jobs. The model is a hybrid of the mover-stayer model of income dynamics and a geometric random walk. In any period, individuals face a discrete probability of moving, in which case their income is a random drawn from a stationary recurrent distribution. Otherwise, they stay and incomes follow a geometric random walk. The model is estimated on income transition data for the United Kingdom from the British Household Panel Survey (BHPS) and provides a good explanation of observed non-linearities in income dynamics. The steady-state distribution of the model provides a good fit for the observed, cross-sectional distribution of earnings. We also evaluate the impact of tertiary education on income transitions and on the long-run distribution of incomes.
This is the 23rd edition of the households below average income (HBAI) series.
This section includes an overview of the background, changes over time and shows:
This section includes the glossary and definitions of the terms used in the report, and more detail on HBAI methodology.
Find out how low income is measured.
In March 2025, the top one percent of earners in the United Kingdom received an average pay of over 16,000 British pounds per month, compared with the bottom ten percent of earners who earned around 800 pounds a month.
Income Dynamics provides estimates of the rates of persistent low income. An individual is classed as being in persistent low income if they are in low income in at least 3 out of 4 years.
Income Dynamics also provides estimates of mobility across the income distribution, including low income entry and exit rates. This year’s release includes new analysis on the events associated with low income entry and exit.
Income Dynamics estimates are based on Understanding Society, a longitudinal survey which follows respondents over time. This is unlike the Households Below Average Income (HBAI) series, which uses the Family Resources Survey (FRS) to look at the distribution of incomes within a different sample each year.
Official statistics are produced impartially and free from political influence.
In the 2022/23 financial year, various measures of inequality in the United Kingdom decreased when compared with 2021/22. The S80/20 ratio fell from 6.3 to 5.5, the P90/10 ratio from 4.5 to 4.2, and the Palma ratio between 1.5 and 1.3.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Data series for income, consumption and savings produced as part of the OECD exercise on household distribution. Also contains socio-demographic information.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the England median household income by race. The dataset can be utilized to understand the racial distribution of England income.
The dataset will have the following datasets when applicable
Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).
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.
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/.
Explore our comprehensive data analysis and visual representations for a deeper understanding of England median household income by race. You can refer the same here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Quarterly data on democratically weighted and CPI-consistent indices, annual inflation rates, expenditure shares and contributions for UK household groups.
The table only covers individuals who have some liability to Income Tax. The percentile points have been independently calculated on total income before tax and total income after tax.
These statistics are classified as accredited official statistics.
You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.
Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.
Note: comparisons over time may be affected by changes in methodology. Notably, there was a revision to the grossing factors in the 2018 to 2019 publication, which is discussed in the commentary and supporting documentation for that tax year. Further details, including a summary of significant methodological changes over time, data suitability and coverage, are included in the Background Quality Report.