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 *** to ***, the P90/10 ratio from *** to ***, and the Palma ratio between *** and ***.

In 2023, the United Kingdom's Gini coefficient score was 33.1, a slight decrease when compared with the previous year. The Gini coefficient is a measurement of inequality within economies, a lower score indicates more equality while a higher score implies more inequality.

South Africa had the highest inequality in income distribution in 2024, with a Gini score of **. Its South African neighbor, Namibia, followed in second. The Gini coefficient measures the deviation of income (or consumption) distribution among individuals or households within a country from a perfectly equal distribution. A value of 0 represents absolute equality, and a value of 100 represents absolute inequality. All the 20 most unequal countries in the world were either located in Africa or Latin America & The Caribbean.

75% of households from the Bangladeshi ethnic group were in the 2 lowest income quintiles (after housing costs were deducted) between April 2021 and March 2024.

Percentage of total wealth owned by households in each decile for London and Great Britain. Data extracted from the ONS Wealth and Assets Survey (WAS) microdata.

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

United Kingdom UK: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.700 % in 2021. This records an increase from the previous number of 11.500 % for 2020. United Kingdom UK: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 11.600 % from Dec 1968 (Median) to 2021, with 54 observations. The data reached an all-time high of 13.700 % in 1993 and a record low of 4.500 % in 1968. United Kingdom UK: Proportion of People Living Below 50 Percent Of Median Income: % 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: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Comparing the *** selected regions regarding the gini index , South Africa is leading the ranking (**** points) and is followed by Namibia with **** points. At the other end of the spectrum is Slovakia with **** points, indicating a difference of *** points to South Africa. The Gini coefficient here measures the degree of income inequality on a scale from * (=total equality of incomes) to *** (=total inequality).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than *** countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

United Kingdom UK: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 18.600 % in 2017. This records an increase from the previous number of 17.000 % for 2016. United Kingdom UK: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 17.800 % from Dec 2016 (Median) to 2017, with 2 observations. The data reached an all-time high of 18.600 % in 2017 and a record low of 17.000 % in 2016. United Kingdom UK: Poverty Headcount Ratio at National Poverty Lines: % of Population 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: Social: Poverty and Inequality. National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.;World Bank, Poverty and Inequality Platform. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.;;This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

What does the data show?

The data shows the S80/S20 income quintile ratio from the UK Climate Resilience Programme UK-SSPs project. The data is available for each ONS NUTS3 shape simplified to a 10m resolution.

The S80/S20 ratio is a measure of the inequality of income distribution. The ratio is the total income received by the 20% of the population with the highest income (the top quintile) against the total income received by the 20% of the population with the lowest income (the bottom quintile).

The data is available for the end of each decade. This dataset contains SSP1, SSP2, SSP3, SSP4 and SSP5. For more information see the table below.

Indicator

Inequality

Metric

S80/S20 income quintile ratio

Unit

Ratio [unitless]

Spatial Resolution

NUTS 3

Temporal Resolution

Decadal

Sectoral Categories

N/A

Baseline Data Source

OECD 2011

Projection Trend Source

Stakeholder process

What are the naming conventions and how do I explore the data?

This data contains a field for the year at the end of each decade. A separate field for 'Scenario' allows the data to be filtered, e.g. by scenario 'SSP3'.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to 2020 values.

What are Shared Socioeconomic Pathways (SSPs)?

The global SSPs, used in Intergovernmental Panel on Climate Change (IPCC) assessments, are five different storylines of future socioeconomic circumstances, explaining how the global economy and society might evolve over the next 80 years. Crucially, the global SSPs are independent of climate change and climate change policy, i.e. they do not consider the potential impact climate change has on societal and economic choices.

Instead, they are designed to be coupled with a set of future climate scenarios, the Representative Concentration Pathways or ‘RCPs’. When combined together within climate research (in any number of ways), the SSPs and RCPs can tell us how feasible it would be to achieve different levels of climate change mitigation, and what challenges to climate change mitigation and adaptation might exist.

Until recently, UK-specific versions of the global SSPs were not available to combine with the RCP-based climate projections. The aim of the UK-SSPs project was to fill this gap by developing a set of socioeconomic scenarios for the UK that is consistent with the global SSPs used by the IPCC community, and which will provide the basis for further UK research on climate risk and resilience.

Useful links: Further information on the UK SSPs can be found on the UK SSP project site and in this storymap.Further information on RCP scenarios, SSPs and understanding climate data within the Met Office Climate Data Portal.

Sampson's article, `Technology Gaps, Trade, and Income,' examines the impact of innovation efficiency gaps on income, wages, and trade dynamics. Our replication, which involves utilizing additional patent metrics, broadening the country selection, extending the time frame, widening the range of the trade elasticity, and excluding outliers, reinforces the significant role of technology gaps in shaping economic inequality. However, our findings indicate that the strength of this effect varies depending on country heterogeneity and the measures of innovation used.

Unpaid work in the sciences is advocated as an entry route into scientific careers. We compared the success of UK science graduates who took paid or unpaid work six-months after graduation in obtaining a high salary or working in a STEM (Science, Technology Engineering and Mathematics) field 3.5 years later. Initially taking unpaid work was associated with lower earnings and lower persistence in STEM compared with paid work, but those using personal connections to obtain unpaid positions were as likely to persist in STEM as paid workers. Obtaining a position in STEM six months after graduation was associated with higher rates of persistence in STEM compared with a position outside STEM for both paid and unpaid workers, but the difference is considerably smaller for unpaid workers. Socio-economic inequality in the likelihood of obtaining entry in STEM by taking an unpaid position is a well-founded concern for scientific workforce diversity.

Many of Europe's largest economies have seen falling shares of their national wealth taken by the bottom ** percent of the wealth distribution since the 1990s. Italy in particular stands out as a particularly stark case, as the bottom half owned around ** percent of the wealth in the country in 1995, while in 2021 they owned only *** percent. Russia is the other country which has seen a consistent decline in the wealth of its poorest ** percent, with the economic crises of the 1990s causing the poor to rapidly lose their share of wealth, but without any recovery during the years of economic success in the run-up to the 2008 financial crisis. Germany, France, Spain, and the United Kingdom have seen more moderate decreases in the bottom ** percent share, with Spain and the UK in fact showing increases in their shares during the early 2000s, as their respective housing booms inflated the wealth of the poorest, before retracting during the financial crisis and great recession. Turkey stands out as an outlier among the large European economies, as the share taken by its bottom half has more than tripled since the 1990s, now having a higher share than in Russia and Italy. This period in Turkey has been marked by rapid economic growth, modernization, and urbanization, some of which has benefitted the poorest by providing new economic opportunities.

Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 3.800 % in 2015. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 3.800 % from Dec 2015 (Median) to 2015, with 1 observations. The data reached an all-time high of 3.800 % in 2015 and a record low of 3.800 % in 2015. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Brazil – Table BR.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;

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.

Supplementary files for article Long-term relatedness and income distribution: understanding the deep roots of inequalityThis article explores the role of long-term relatedness between countries, captured by an index of genetic distance, in driving worldwide differences in income inequality. The main hypothesis is that genetic distance gives rise to barriers to the international diffusion of redistributive policies and measures, and institutions, leading to greater income disparities. Using cross-country data, I consistently find that countries that are genetically distant to Denmark—the world frontier of egalitarian income distribution—tend to suffer from higher inequality, ceteris paribus. I also demonstrate that genetic distance is associated with greater bilateral differences in income inequality between countries. Employing data from the European Social Survey, I document that second-generation Europeans descending from countries with greater genetic distance to Denmark are less likely to exhibit positive attitudes towards equality. Further evidence suggests that effective fiscal redistribution is a key mechanism through which genetic distance to Denmark transmits to greater income inequality.

This data and code accompanies the paper Robson, O'Donnell and Van Ourti (2024), "Aversion to Health Inequality – Pure, Income-Related and Income-Caused", Journal of Health Economics. In the paper, we design and run an online experiment, with a sample of the UK population, to identify aversion to pure health inequality separately from aversion to income-related and income-caused health inequality. Here, we provide data and code to enable replication of the experiment and analysis, alongside a policy evaluation tool. The Overview.pdf provides an overview of all code and data. Please contact us if you have any questions.

Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 3.600 % in 2017. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 3.600 % from Dec 2017 (Median) to 2017, with 1 observations. The data reached an all-time high of 3.600 % in 2017 and a record low of 3.600 % in 2017. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Indonesia – Table ID.World Bank.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Kanagaratnam, U., and Suppa, N. (2023). ‘The global Multidimensional Poverty Index (MPI) 2023 country results and methodological note’, OPHI MPI Methodological Note 55, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford. (https://ophi.org.uk/mpi-methodological-note-55-2/);;