House prices vary widely in the United Kingdom (UK), but housing in certain cities and counties is substantially pricier than in others. Surrey, for example, concentrated four of the most expensive towns to buy a home, including Virginia Water, Cobham, and Esher. With an average house price of over *********** British pounds as of June 2024, housing in these towns cost roughly **** times the national average. How did house prices change since the COVID-19 pandemic? Since the start of the coronavirus (COVID-19) pandemic, demand for housing has been especially high, causing house prices to soar. Among major UK cities, the house price increase was most prominent in Belfast, where it rose by *** percent in 2024. According to the UK House Price Index, the average annual house price increase on a national level was even higher. How long does it take to sell a house? With the demand for housing going strong and inventory running low, aspiring homeowners need to act faster than ever when making an offer on a home. The average number of days on market has continued shortening since the start of 2021 and was a little over a month as of October 2021. Surprisingly, selling a property took the longest in the UK’s most competitive market - London.

The gross domestic product per capita of London was ****** British pounds in 2023, far larger than that of other major cities in England, such as Manchester which had a GDP per capita of ****** pounds.

This GLA Intelligence Update takes a brief look at evidence around the wealth gap in London and examines how this has changed in recent years. Key Findings There is a significant gap between the rich and poor in London, both in terms of their wealth and their income. A higher proportion of the wealthiest households are in the South East of England than in London. Pension wealth accounts for more than half the wealth of the richest ten per cent of the population. In London, the tenth of the population with the highest income have weekly income after housing costs of over £1,000 while people in the lowest tenth have under £94 per week. The gap between rich and poor is growing, with the difference between the average income for the second highest tenth and second lowest tenth growing around 14 per cent more than inflation since 2003.

This statistic presents the outcome of prosperity index research conducted by Barclay for the regions of the United Kingdom (UK) as of August 2015. According to the research incorporating various factors into the prosperity score, the most prosperous region of the UK was the city of London, with a score of **** points. South East and Eastern England followed with **** and **** score, respectively. Least prosperous was North East, with **** index points on the scale.

At the turn of the twentieth century, the wealthiest one percent of people in the United Kingdom controlled 71 percent of net personal wealth, while the top ten percent controlled 93 percent. The share of wealth controlled by the rich in the United Kingdom fell throughout the twentieth century, and by 1990 the richest one percent controlled 16 percent of wealth, and the richest ten percent just over half of it.

A selected sample of this study, listed under SN 6512: Affluent Worker in the Class Structure, 1961-1962, is available via the UK Data Service Qualibank, an online tool for browsing, searching and citing the content of selected qualitative data collections held at the UK Data Service.

The 'Affluent Worker' project was undertaken to test empirically the thesis of working class embourgeoisement. Conducted in the early 1960s, the empirical study consisted of interviews with manual workers and their wives. The original project was exploring the social and cultural influences on manual workers’ class identities. Although the researchers rejected the original embourgeoisement thesis that working class people were becoming assimilated to the middle classes, they did argue that traditional working class norms had been adapted in the post war period of prosperity. They found that in place of assimilation ‘major on-going modification in manual-non manual differences were occurring at the level of values and aspirations’ (Goldthorpe et al. 1969:26).

The research studied the attitudes and behaviour of high wage earners in three mass or continuous flow companies. During 1961-1962, married, male workers from three Luton factories (Vauxhall, Skefco and Laporte) were firstly interviewed at work and then, again, at home with their wives. Additionally, a sample of middle-class, white-collar workers from the same companies were interviewed only at home. A pilot of the study was conducted in Cambridge prior to the main Luton study.

This Special License issue contains an additional 213 surveys from the Luton area and 12 more data files from the Cambridge area. A subset of the Luton study interviews was digitised and formed part of a wider ESRC project Living Standards, social identities and the working class in England, c.1945-c.1970. For this subset, 30 married male Vauxhall workers' completed questionnaires were selected from boxes 01 and 02 from the full collection, as the handwriting on the original papers was legible, and follow-up home interviews were available as well as the initial workplace interview. The resulting data have been collated into tabular form, within an MS Access database. The tables replicate the structure and variables of the questionnaires used in the original study. Street, place and personal names were standardised by the original investigators, and care has been taken to retain original spellings. The subset database therefore contains a total of 60 interviews, each with 464 variables.

The Summarised Botanical Value Map for England is a map identifying areas likely to be rich in high quality habitat based on BSBI vascular plant records. Under the Natural Capital and Ecosystem Assessment (NCEA) Pilot, Natural England and the Botanical Society of Britain and Ireland (BSBI) have been working in partnership to use BSBI's vast database of plant records to inform the evidence base for tree-planting activities. Poorly targeted tree planting risks damaging wildlife and carbon-rich habitats, therefore using these data we aim to ensure that areas of high conservation value are preserved in the landscape. The summarised botanical value map provides an easily interpretable output which categorises monads (1 x 1 km grid squares) as being of Low, Moderate or High botanical value according to the presence of Rare, Scarce and Threatened (RST) plant species and/or the proportion of Priority Habitat Positive Indicator (PHPI) species that were recorded within the 1 x 1 km grid square between 1970 and 2021. The PHPI species are a combination of BSBI axiophytes, positive indicators for common standards monitoring and ancient woodland indicators. The dataset includes an overall botanical value, as well as values based on only the presence of RST plant species, and a value for each broad habitat type based on the PHPI species records. By viewing the different attributes, you can gain insights into how valuable a monad is for different habitat types and for plant species of conservation concern, as well as an indication of how well a particular monad has been surveyed. The categories of 'No indicators, poor survey coverage' and 'No indicators, good survey coverage' indicate where no indicator species have been recorded and survey coverage either is above or below a threshold of 3 'recorder days'. A 'recorder day' is defined as being when 40 or more species have been recorded on a single visit and 3 recorder days is assumed sufficient to achieve good survey coverage within a 1 x 1 km grid square. This map is not intended to be used to carry out detailed assessments of individual site suitability for tree planting, for which the RST plant species heatmap at 100 x 100 m resolution and the PHPI heatmaps at 1 x 1 km resolution have been developed by BSBI and Natural England. However, the summarised botanical value map can provide useful insights at a strategic landscape scale, to highlight monads of high value for vascular plants and inform spatial planning and prioritisation, and other land management decision-making. These should be used alongside other environmental datasets and local knowledge to ensure decisions are supported by the appropriate evidence. Please get in contact if you have any queries about the data or appropriate uses at botanicalheatmaps@naturalengland.org.uk Further information can be found in the technical report here: http://nepubprod.appspot.com/publication/5063363230171136. Attribution statement: Contains data supplied by © Natural England © Botanical Society of Britain and Ireland. Reproduced by permission of Ordnance Survey on behalf of HMSO. © Crown copyright and database right 2020. Ordnance Survey Licence number 100022021. Source: Office for National Statistics licensed under the Open Government Licence v.3.0. Contains OS data © Crown copyright and database right [2020] © JNCC, licenced under Open Government Licence v.3.0. Walker, K.J. 2018. Vascular plant 'axiophyte' scores for Great Britain, derived from the assessments of the vice-county recorders of the Botanical Society of Britain and Ireland (May 2016). NERC Environmental Information Data Centre. (Dataset). Available under Open Government Licence v.3.0. Glaves, P., Rotherham, I.D., Wright, B., Handley, C. & Birkbeck, J. 2009. A survey of the coverage, use and application of ancient woodland indicator lists in the UK. Hallam Environmental Consultants Ltd., Biodiversity and Landscape History Research Institute and the Geography, Tourism and Environment Change Research Unit, Sheffield Hallam University. © NERC Copyright 2004. Hill, M. O., Preston C. D. & Roy D. B. 2004. PLANTATT. Attributes of British and Irish Plants: Status, Size, Life history, Geography and Habitats. NERC Centre for Ecology and Hydrology: Huntingdon.

This project investigated UK secondary school students’ views of inequality and their sense of agency concerning their occupational prospects, using questionnaire and interview data. The data came from 78 students from three secondary schools in England between Year 7 and Year 13 who were aged between 12 and 19. The three schools were in areas with different socioeconomic characteristics – an affluent town in the London commuter belt (School A), a city in the east of England (School B) and a town to the east of London (School C). School A had a lower than national average free school meals (FSM) rate, whereas both School B and School C had a higher than national average FSM rate. 18 participants were from School A, 38 from School B and 22 from School C. While all 18 students in School A and all 22 students in School C participated in both the questionnaire and follow-up interview stages, in School B 37 participants filled in the questionnaire and, of these, 22 took part in the interviews. One student from School B who did not fill in a questionnaire took part in the interview, making the total interviews from School B 23. One student from School C did not want to have their interview audio-recorded; therefore, their interview transcript does not exist. As a result, the dataset in total contains 77 questionnaires and 62 interview transcripts. The PDF files are questionnaire files and the word document files are interview transcripts. A file name (for both the pdf files and word document files) begins with ‘Y’ that is followed by a number which indicates a school year and this is followed by two letters that indicate a code for an individual participant, while the letter A, B or C immediately after a hyphen indicates School A, B or C respectively.

United Kingdom UK: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data was reported at 97.620 % in 2017. This records a decrease from the previous number of 99.490 % for 2014. United Kingdom UK: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ data is updated yearly, averaging 97.620 % from Dec 2011 (Median) to 2017, with 3 observations. The data reached an all-time high of 99.490 % in 2014 and a record low of 97.599 % in 2011. United Kingdom UK: Bank Account Ownership at a Financial Institution or with a Mobile-Money-Service Provider, Richest 60%: % of Population Aged 15+ 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: Bank Account Ownership. Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (richest 60%, share of population ages 15+).; ; Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank.; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Average weekly household expenditure on goods and services in the UK. Data are shown by region, age, income (including equivalised) group (deciles and quintiles), economic status, socio-economic class, housing tenure, output area classification, urban and rural areas (Great Britain only), place of purchase and household composition.

This dataset provides detailed home profile attributes for over 15,000 UK households, offering a rich view of residential characteristics. Key fields include:

1. Region – Geographical location (e.g., London, Wales, North East)
2. Property type – Detached, semi-detached, terrace, bungalow
3. Cooking type – Gas, electric, dual-fuel
4. Heating type – Primary heating system
5. Hot water – Source (gas, electric, dual-fuel)
6. Occupancy – Number of occupants (1–5+)
7. EVs, Solar, Heat Pump – Presence of these technologies
8. Bedrooms – Number of bedrooms

It is a specialised subset of our household data, providing rich context for electricity and gas consumption datasets, disaggregation data, and research on energy behaviour. The dataset continues to expand as more households are added.

As of 2025, the GDP per capita or gross domestic product per person was almost ****** U.S. dollars per person. The GDP per capita is derived from the country's total GDP divided by the population. The average or mean wealth per person in the United Kingdom (UK) was higher than the median or middle value of wealth per person living in the UK.

In 2024, the number of individuals living in the United Kingdom (UK) with a net worth of over *** million U.S. dollars, excluding the value of their primary residence, was roughly around **** million. This was a decline compared to the previous year, as the UK had over ***** million HNWI.

Between 2019 and 2023, people living in households in the Asian and ‘Other’ ethnic groups were most likely to be in persistent low income before and after housing costs

FOCUSONLONDON2011:POVERTY:THEHIDDENCITY One of the defining features of London is that it is a city of contrasts. Although it is considered one of the richest cities in the world, over a million Londoners are living in relative poverty, even before the additional costs of living in the capital are considered. This edition of Focus on London, authored by Rachel Leeser, presents a detailed analysis of poverty in London that reveals the scale and distribution of poverty in the capital. CHARTS: The motion chart shows the relationship between child poverty and worklessness at borough level, and shows how these two measures have changed since 2006. It reveals a significant reduction in workless households in Hackney (down 12 per cent), and to a lesser extent in Brent (down 7 per cent). The bar chart shows child poverty rates and the change in child poverty since 2006. It reveals that while Tower Hamlets has the highest rate of child poverty, it also has one of the fastest falling rates (down 12 per cent), though Haringey had the biggest fall (15 per cent). DATA: All the data contained within the Poverty: The Hidden City report as well as the data used to create the charts and maps can be accessed in the spreadsheet. FACTS: Some interesting facts from the data… ● Highest proportion of children in workless households, by borough, 2010 Westminster – 35.6% Barking and Dagenham – 33.6% Lewisham – 33.1% Newham – 31.4% Islington – 30.6% -31. Barnet – 9.1% -32. Richmond upon Thames – 7.0% ● Changes in proportions of workless households, 2006-09, by borough Hackney – down 12.3% Brent – down 7.3% Tower Hamlets – down 4.8% Lambeth – down 4.2% Hillingdon – down 4.1% -31. Enfield – up 5.8% -32. Bexley – up 7.3% ● Highest reduction in rates of child poverty 2006-09, by borough: Haringey – down 15.0% Newham – down 12.9% Hackney – down 12.8% Tower Hamlets – down 12.1% Southwark – down 11.5% -31. Bexley – up 6.0% -32. Havering – up 10.3%

Classification of small area 1981 census enumeration district data into clusters for purposes of data description and analysis.

United Kingdom Luxury Goods Market size was valued at USD 19.25 Billion in 2024 and is projected to reach USD 28.56 billion by 2032, growing at a CAGR of 5% from 2026 to 2032. United Kingdom Luxury Goods Market DriversThe UK luxury goods market is driven by a unique blend of traditional values and modern consumer behaviors. From a growing class of wealthy individuals to the pervasive influence of social media, several key factors are propelling this sector forward. Brands are adapting by embracing digital innovation, prioritizing ethical practices, and creating immersive experiences to capture the attention of a new generation of consumers.Affluent Consumer Base & Rising Disposable Income: The UK's luxury market is significantly fueled by a growing segment of High Net Worth Individuals (HNWIs). This demographic, with its substantial purchasing power, is a primary driver of demand for premium, exclusive products that signify status and quality. Furthermore, a general increase in disposable income, particularly among urban and more affluent households, allows for greater spending on high-end, discretionary items beyond just necessities. This broader economic trend expands the consumer base for luxury goods and experiences.Digital Transformation & E-Commerce Growth: Luxury brands are no longer just focused on physical stores. They are investing heavily in a digital transformation, building sophisticated e-commerce platforms and apps that mimic the exclusive feel of a physical boutique. Technologies like Augmented Reality (AR) and Virtual Reality (VR) allow customers to virtually try on products, while AI-driven personalization provides tailored recommendations.